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Impact of Service Innovation Capabilities on Business Model
Innovation: A Dual Moderated Mediation Analysis
By
MALKAH NOOR KIANI
(1431178)
A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENT FOR THE DEGREE OF
DOCTORATE OF PHILOSOPHY
IN MANAGEMENT SCIENCES
TO
DEPARTMENT OF MANAGEMENT SCIENCES
Shaheed Zulfikar Ali Bhutto Institute of Science and Technology
(SZABIST), Islamabad
February, 2020
iii
CERTIFICATE OF APPROVAL
iv
DISSERTATION AND DEFENSE APPROVAL FORM
The undersigned certify that they have read the following dissertation, examined the defense, are
satisfied with the overall exam performance and recommend the dissertation to the Department of
Management Sciences SZABIST for acceptance:
Dissertation Title: Impact of Service Innovation Capabilities on Business Model
Innovation: A Dual Moderated Mediation Analysis
Submitted by: Malkah Noor Kiani Registration # 1431178
Doctorate of Philosophy
Department of Management Sciences
Dr. Mehboob Ahmad _
Name of the research supervisor Signature of the Research Supervisor
Dr. Mehboob Ahmad _
Name of the Program Manager Signature of the Program Manager
Dr. Muhammad Asif Khan _
Name of the Head of Department Signature of the HOD
Khusro Pervaiz Khan _
Name of the Head of Campus Signature of the HOC
v
AUTHOR’S DECLARATION
I, Malkah Noor Kiani D/o Sultan Farid Kiani, Registration # 1431178, hereby state that my PhD thesis
titled, “Impact of Service Innovation Capabilities on Business Model Innovation: A Dual Moderated
Mediation Analysis” is my own work and has not been submitted previously by me for taking any degree
from this University (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST) or
anywhere else in the country world.
At any time if my statement is found to be incorrect even after my Graduate the university has the right
to withdraw my PhD degree.
Signature:
____________________
Name: Malkah Noor Kiani
Dated: 27th February 2020 _____
vi
PLAGIARISM UNDERTAKING
I solemnly declare that research work presented in the thesis titled, “Impact of Service Innovation
Capabilities on Business Model Innovation: A Dual Moderated Mediation Analysis” is solely my
research work with no significant contribution from any other person. Small contribution/help wherever
taken has been duly acknowledged and that complete thesis has been written by me.
I understand the zero tolerance policy of the HEC and University (Shaheed Zulfikar Ali Bhutto Institute
of Science and Technology (SZABIST) towards plagiarism. Therefore, I as an Author of the above titled
thesis declare that no portion of my thesis has been plagiarized and any material used as reference is
properly referred/cited.
I undertake that if I am found guilty of any formal plagiarism in the above titled thesis even after award of
PhD degree, the University reserves the rights to withdraw/revoke my PhD degree and that HEC and the
University has the right to publish my name on the HEC/University Website on which names of students
are placed who submitted plagiarized thesis.
Student/ Author Signature: _________________
Name: Malkah Noor Kiani
Registration #:_1431178
vii
Copyright © 2020 MALKAH NOOR KIANI
All rights reserved. No part of the publication may be reproduced in any form by print, photo
print, microfilm or any means without written permission from the author
viii
DEDICATION
This research work is dedicated to my parents (late), husband and my kids who comforted me,
groomed me, supported me and lead me in my life.
I dedicate this work to my mother (late) who had always been the source of inspiration, emotional
enthusiasm till her last breath. She had always motivated me for the completion of my Ph.D. degree
program. Her prayers were the real essence for all my academic and professional achievements
and made me proud of what I am today.
I dedicate this work to my husband who always supported me in every walk of life including the
hard journey of this degree program. His love, trust, support, and faith have enabled me to
accomplish my studies.
Lastly, my research work is dedicated to my little sun-shines, Ali and Zainab. They are the reasons
behind my struggles and efforts for the persuasion of my academic goals. They are my real
emotional strength, no matter how hard and complicated this doctoral journey was for me. They
comforted me and relieved me from the exhaustion and tiredness experienced during this
challenging journey.
May ALLAH bless them all! (Ameen).
ix
ACKNOWLEDGMENTS
Innumerable thanks to Almighty Allah, for giving me the courage, empowering me with the
knowledge and confidence to accomplish this research work. First of all, I would like to express
my deep gratitude to my supervisor Dr. Mehboob Ahmad for his precious comments and guidance
has laid the groundwork for this Ph.D. dissertation. His guidance and encouragement from the
basics to the final level has enabled me to develop an understanding of the topic of this research
work. His knowledge and leadership provides a priceless model for my own career. I am very
thankful to my teachers and faculty of management sciences who have groomed me and enable
me to work on a research dissertation. I am very grateful to head of department, Dr. Muhammad
Asif Khan, for providing students such a desirable learning environment to pursue their MS /
Doctorate degrees. Acknowledging, it is the endeavors of our respected head of department that
enables the students foster learning with more enthusiasm, devotion and passion. Thanking him
for allowing all the students, the space to not only have dialogue, but be creative with our learning
as well. Words are powerless to express my gratitude to all of them for their steadfast diligence to
the noble profession of teaching.
I am grateful to my parents (late) who had always encouraged me and prayed for my success. I am
tremendously grateful to my family for being a constant source of inspiration, motivation and
emotional stimulation that added both to my enthusiasm and research work.
x
ABSTRACT
Cellular firms are compelled to innovate in terms of business model innovation. The introduction
of IT-enabled services to the general public of Pakistan has provided the cellular firms with new
business opportunities by opening new avenues of market competition. With an objective to ensure
the sustainability in growing trends of market competition, cellular firms are now engaged in other
subtle business models such as mobile banking service, G2P payment mechanisms, P2P payment
mechanism, utility bill payments, e-commerce, etc. in parallel with the parental business model
(of provision of mobile phone connection). Therefore, it is essential to study what are constituents
of business model innovation and what are the factors that shape the business model innovation.
The review of extensive literature further indicated the six important research gaps that form the
foundations and groundwork of this study. In order to address these research gaps, six research
objectives and research questions have been established. The data has been collected via a
questionnaire survey from the 427 upper and middle managers of four cellular firms (namely
Mobilink – Warid, Telenor, Ufone, and Zong) through simple random sampling strategy.
Regression-based conditional process analysis by Hayes (2018) is used for hypothesis testing.
Structural equal modeling is also implied for overall testing the model fitness of the hypothesized
theoretical framework.
The results show that service innovation capabilities directly affects the overall business
model innovation. It is also found that service innovation capabilities also indirectly affect the
business model innovation through the positive mediation of service innovation success. This
positive mediation effect is further positively moderated by the management entrepreneurial
orientation and negatively moderated by employee resistance to change. Furthermore, it is also
found that the management entrepreneurial orientation also positively moderates the direct effect
of service innovation capabilities on business model innovation. In addition, the negative
moderation effect of employee resistance to change on the direct effect of service innovation
capabilities and business model innovation is also found. Thus, this study attempts to contribute
the novelty by empirically testing the strategic entrepreneurship perspective through the lens of
the force field of changes. As previous researches indicated that there is a need to further
investigate the strategic entrepreneurship perspective in combination with the diverse theoretical
perspectives (Mazzei, Ketchen & Shook, 2016; Covin & Lumpkin, 2011). In addition, this study
contributes the novelty by addressing the identified six literature-based research gaps through deep
xi
empirical testing. Key findings for the practitioners of cellular firms of Pakistan are also
proclaimed to achieve a higher degree of business model innovation. Moreover, it is also
recommended for future researches to enrich this study by further investigating the other
contextual and organizational factor that may influence the business model innovation.
Comparative studies of cellular firms on the extent of business model innovation and its
implications on their competitive positioning also recommended for future researches.
xii
TABLE OF CONTENTS
DEDICATION………………………………………………………………………………..viii
ACKNOWLEDGMENTS ..…………………... …………………………………………...…ix
ABSTRACT……………………………………………………………………………………..x
TABLE OF CONTENTS ……………………………………..……………………………....xii
LIST OF APPENDICES ……………………………………….…………………………….xvi
LIST OF TABLES ………………………………………… ….………………………….....xvii
LIST OF FIGURES ……...………………………………… ….…………………………….xix
CHAPTER 1 - INTRODUCTION ............................................................................................... 1
1.1. BACKGROUND OF STUDY .................................................................................................. 1
1.2. GAP ANALYSIS...................................................................................................................... 3
1.3. PROBLEM STATEMENT ....................................................................................................... 6
1.4. OBJECTIVES OF RESEARCH STUDY ................................................................................ 7
1.5. RESEARCH QUESTIONS ...................................................................................................... 7
1.6. CONTRIBUTION OF STUDY ................................................................................................ 8
1.7. DISSERTATION STRUCTURE ........................................................................................... 10
1.8. CHAPTER SUMMARY ........................................................................................................ 11
CHAPTER 2 - LITERATURE REVIEW ................................................................................. 14
2.1. THEORETICAL FOUNDATIONS OF STUDY ................................................................... 14
2.1.1. Strategic Entrepreneurship Theory ............................................................................... 14
2.1.2. Force Field Theory of Change ..................................................................................... 15
2.2. CONCEPTS, DEFINITIONS AND ESTABLISHED RESEARCHES ................................. 15
2.2.1. Business Model Innovation (Dependent Variable). ..................................................... 16
2.2.1.1. Dimensions of Business Model Innovation. ........................................................ 17
2.2.1.2. Research Gap - 1: Operationalization of BMI Needs Empirical Validation ...... 21
2.2.2. Service Innovation Capabilities (Independent Variable). ............................................ 24
2.2.2.1. Review of Recent Theoratical Framework...…………………………………...27
2.2.2.2. Dimensions of Service Innovation Capabilities. ................................................. 30
2.2.2.3. Innovation Capabilities Concept Needs To Be Validated.. ................................. 37
2.2.3. Service Innovation Success (Mediating Variable). ...................................................... 38
2.2.4. Employee Resistance To Change (Moderating Variable - 1) ....................................... 43
xiii
2.2.5. Management Entrepreneurial Orientation (Moderating Variable - 2). ......................... 46
2.3. PROPOSED ASSOCIATION OF STUDY VARIABLES .................................................... 52
2.3.1. Relationship of Innovation Capabilities and Business Model Innovation (Research
Gap-2). .................................................................................................................................... 52
2.3.2 Relationship Of Innovation Capabilities and Service Innovation Success. .................. 54
2.3.3. Relationship of Service Innovation Success and Business Model Innovation. ............ 55
2.3.4. Service Innovation Success As Mediator (Research Gap – 3). .................................... 57
2.3.5. Moderation Effect of Employee Resistance To Change (Research Gap-4). ................ 59
2.3.6. Moderation Effect of Management Entrepreneurial Orientation (Research Gap – 5). 61
2.4. ANTECEDENT OF BMI NEEDS TO BE EXPLORED (RESEARCH GAP-6) .................. 63
2.5. CHAPTER SUMMARY ........................................................................................................ 67
CHAPTER 3 - RESEARCH METHODOLOGY ..................................................................... 68
3.1. RESEARCH PARADIGM AND PHILOSOPHY….……………………………………….68
3.1.1. Ontological Stance of Study. ........................................................................................ 68
3.1.2. Epistomological Stance of Study. ................................................................................ 69
3.1.3. Axiological Stance of Study. ........................................................................................ 70
3.1.4. Hypothesized Theoratical FrameworK ........................................................................ 71
3.2. RESEARCH DESIGN ............................................................................................................ 74
3.3. OPERATIONALIZATION OF RESEARCH INSTRUMENT AND MEASUREMENT .... 74
3.3.1. Service Innovation Capabilities. ................................................................................... 74
3.3.2. Service Innovation Success. ......................................................................................... 76
3.3.3. Business Model Innovation. ......................................................................................... 77
3.3.4. Management Entrepreneurial Orientation. ................................................................... 78
3.3.5. Employee Resistance To Change. ................................................................................ 79
3.3.6. Finalization of Research Instrument. ............................................................................ 79
3.4. POPULATION AND SAMPLE OF STUDY ........................................................................ 80
3.4.1. Unit of Analysis. ........................................................................................................... 81
3.4.2. Determination of Sample Size. ..................................................................................... 83
3.4.3. Selection of Sample and Sampling Technique. ............................................................ 84
3.4.4. Data Collection ............................................................................................................. 85
3.5. RELIABILITY AND VALIDITY OF RESEARCH INSTRUMENT ................................... 85
3.5.1. Face Validity. ............................................................................................................... 86
3.5.2. Content Validity. .......................................................................................................... 86
xiv
3.5.3. Construct Validity (Exploratory Factor Analysis). ...................................................... 86
3.5.4. Construct Reliability (Cronbach Alpha). ...................................................................... 98
3.5.5. Convergent Validity And Item Reliability (Confirmatory Factor Analysis). ............ 100
3.5.6. Discriminate Validity (Fornell-Lacker Criterion). ..................................................... 102
3.6. STATISTICAL TECHNIQUES ........................................................................................... 111
3.7. CHAPTER SUMMARY ...................................................................................................... 112
CHAPTER 4 - DATA ANALYSIS & RESULTS ................................................................... 114
4.1. DEMOGRAPHIC CHARACTERISTICS............................................................................ 114
4.2. DESCRIPTIVE ANALYSIS ................................................................................................ 114
4.3. CORRELATION ANALYSIS AMONG STUDY VARIABLES ....................................... 115
4.4. HYPOTHESES TESTING - REGRESSION BASED CONDITIONAL PROCESS
ANALYSIS.................................................................................................................................. 116
4.4.1. Assumptions of Regression Analysis. ........................................................................ 118
4.4.1.1. Data Normality. ................................................................................................ 118
4.4.1.2. Linearity of Residuals. ...................................................................................... 119
4.4.1.3. Multicollinearity. .............................................................................................. 120
4.4.2. Addressing Gap-II - Testing the Effect of ‘X’ on ‘Y’(H-1) ....................................... 121
4.4.3. Addressing Gap-III - Testing the Mediation Effect of ‘M’ on Relationship of ‘X’ on
‘Y’ ........................................................................................................................................ 121
4.4.4. Addressing Gap-IV -Testing the Moderation Effect of Employee Resistance ‘W’. .. 123
4.4.4.1. Testing the Moderation Effect of ‘W’ on Relationship of ‘X’ on ‘Y’. ................ 123
4.4.4.2. Testing the Moderation Effect of ‘W’ on Relationship of ‘X’ and ‘M’. ............. 126
4.4.5. Addressing Gap-V -Testing the Moderation Effect of ‘Z’. ........................................ 128
4.4.5.1. Testing the Moderation Effect of ‘Z’ on Relationship of ‘X’ on ‘Y’. ................ 128
4.4.5.2. Testing the Moderation Effect of ‘Z’ on Relationship of ‘X’ and ‘M’. ............. 130
4.4.6. Addresing Gap-VI - Testing the Antecedents of Business Model Innovation….…..132
4.4.6.1. Testing the Dual Moderation Effect of “W” and “Z” on Relationship of “X”
on “Y”with Putative Mediator Held Constant. ............................................................ 135
4.4.6.2. Testing the Dual Moderated Mediation Effect of “W” “Z” and “M” on
Relationship of “X” on “Y”. ........................................................................................ 135
4.5. CHECKING FITNESS INDICES OF DUAL MODERATED MEDIATION
FRAMEWORK ........................................................................................................................... 138
4.6. CHAPTER SUMMARY ...................................................................................................... 140
xv
CHAPTER 5 - DISCUSSION, RECOMMENDATION AND CONCLUSION................... 143
5.1. DISCUSSION ....................................................................................................................... 143
5.1.1. Research Objective 1……...………………………………………………………..143
5.1.2. Research Objective 2……...………………………………………………………..144
5.1.3. Research Objective 3……...………………………………………………………..144
5.1.4. Research Objective 4……...………………………………………………………..145
5.1.5. Research Objective 5……...………………………………………………………..146
5.1.6. Research Objective 6……...………………………………………………………..147
5.2. RECOMMENDATIONS ...................................................................................................... 149
5.2.1. Managerial Implications ............................................................................................. 149
5.2.2. Limitations and Future Research Directions .............................................................. 154
5.3. CONCLUSION….………………………………………………………………………....155
REFERENCES .......................................................................................................................... 158
APPENDICES ............................................................................................................................ 184
xvi
LIST OF APPENDICES
Appendix - I (Research Survey Questionnaire) ........................................................................... 184
Appendix - II (Confirmatory Factor Analysis of all Constructs) ................................................ 189
xvii
LIST OF TABLES
Table no Table Descriptions Page no
Table 1.1. Summarizing Research Gaps and Derivation of Research Hypotheses of Study ......... 12
Table 2.1. Survey evidence pertaining to the conceptualization of business model ..................... 23
Table 2.2. Survey evidence pertaining to the antecedents of business model innovation ............. 64
Table 3.1. Exploratory Factor Analysis for the Scale of Innovation Capabilities ......................... 87
Table 3.2. Exploratory Factor Analysis for the Scale of Service Innovation Success .................. 88
Table 3.3. Exploratory Factor Analysis for Management Entrepreneurial Orientation Scale ....... 90
Table 3.4. Exploratory Factor Analysis for Employee Resistance Scale ...................................... 92
Table 3.5. Exploratory Factor Analysis for Business Model Innovation Scale ............................. 95
Table 3.6. Summarizing the Overall Results of Exploratory Factor Analysis .............................. 97
Table 3.7. Reliability Analysis of Constructs and Sub-constructs after Extraction ...................... 99
Table 3.9. Discriminate Analysis of innovation capabilities scale .............................................. 103
Table 3.10. Discriminate Analysis of innovation success scale .................................................. 104
Table 3.11. Discriminate Analysis of entrepreneurial orientation scale ...................................... 105
Table 3.12. Discriminate Analysis of employee resistance scale ................................................ 106
Table 3.13. Discriminate Analysis of business model innovation scale ...................................... 108
Table 3.14. Summarizing the Reliability and Validity Iteration Outcome .................................. 110
Table 4.1. Demographic Analysis of Research Survey Participants ........................................... 114
Table 4.2. Descriptive Analysis among Study Variables ............................................................ 115
Table 4.3. Correlation Analysis among Study Variables ............................................................ 116
Table 4.4. Results of Data Normality .......................................................................................... 119
Table 4.5. Multicollinearity Statistics of Study Variables ........................................................... 121
Table 4.6. Regressing IV against DV in Simple Linear Regression ........................................... 121
Table 4.7 Mediation Model Coefficients of Study Variables ...................................................... 122
Table 4.8. Total Effect, Direct and Indirect Model of Mediation Analysis ................................. 123
Table 4.9. Model Coefficients for Moderation Effect of Employee Resistance on X and Y ...... 124
Table 4.10. Conditional Effect of X on Y at values of Employee Resistance (W) ..................... 125
Table 4.11. Model Coefficients for Moderation Effect of Employee Resistance on X and M ... 127
Table 4.12. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and Y
..................................................................................................................................................... 128
Table 4.13. Conditional effect of X on Y at values of Entrepreneurial Orientation (Z) ............. 129
xviii
Table 4.14. Model Coefficient for Moderation Effect of Entrepreneurial Orientation on X and M
..................................................................................................................................................... 131
Table 4.15. Moderation Effects of W and Z with Putative Mediator Held Constant .................. 133
Table 4.16. Conditional Effect of X on Y at values of Both Moderators W and Z ..................... 134
Table 4.17. Coefficients for Hypothesized Research Model of Study ........................................ 136
Table 4.18. Conditional Direct, Indirect Effect of X on Y at values of Moderators ................... 137
Table 4.19. Model Fitness Summary of Hypothesized Theoretical Framework ......................... 138
Table 4.20. Summarizing Results of Research Hypotheses ........................................................ 141
xix
LIST OF FIGURES
Figure no Figure Descriptions Page no
Figure 3.1. Hypothesized Conceptual Framework of Research Study .......................................... 73
Figure 3.2. Scree Plot for Innovation Capabilities Scale ............................................................... 88
Figure 3.3. Scree Plot for Innovation Success Scale ..................................................................... 90
Figure 3.4. Scree Plot for Management Entrepreneurial Orientation Scale .................................. 92
Figure 3.5. Scree Plot for Employee Resistance Scale .................................................................. 94
Figure 3.6. Scree Plot for Business Model Innovation Scale ........................................................ 97
Figure 4.1. Scatterplot depicting Linearity of Residuals ............................................................. 120
Figure 4.2. Statistical Diagram of Table 4.7 ................................................................................ 122
Figure 4.3. Statistical Diagram of Table 4.9 ................................................................................ 124
Figure 4.4. Moderating effect of W on relationship of X and Y ................................................. 125
Figure 4.5. Statistical Diagram of Table 4.11 .............................................................................. 127
Figure 4.6. Statistical Diagram of Table 4.12 .............................................................................. 129
Figure 4.7. Moderating effect of Z on relationship of X and Y ................................................... 130
Figure 4.8. Statistical Diagram of Table 4.14 .............................................................................. 131
Figure 4.9. Statistical Diagram of Table 4.15 .............................................................................. 133
Figure 4.10. Statistical Diagram of Table 4.17 ............................................................................ 136
Figure 4.11. Single Measurement Model of Hypothesized Research Model .............................. 139
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
1
CHAPTER 1
INTRODUCTION
Today is the era of growing technological advancements. Organizations are constantly
striving for running their business in new ways. It is a need for organizations to further innovate
in the domain of business model itself (Chung, Choi & Du, 2017). Globalization has also opened
new ways of doing business for the organizations. Therefore, the sustainability of continuous
innovation in business models is something very critical among the market players. This opens the
question that how an organization can sustain innovation in existing business models and the
success of new services among such ever-changing market dynamics?
This research work aims to study the factors and enablers of business model innovation
and their nature of complex interaction among each other specifically in the cultural context of
Pakistan. This section briefly discusses the background of the research study, identification of gap
analysis, the specific problem statement of this research study, objectives of the research study,
research questions, the contribution of this research study and lastly, the dissertation structure.
1.1. Background of the Study
Growing market competition, increasing technological advances, and globalization itself
have led the organizations to pursue innovation for sustainability. The essence of bringing change
in business models is thought to be essential for overall business success (Spieth & Meissner Nee
Schuchert, 2018). It reflects that the business model(s) may not be viewed as persistent with static
nature in the current world. Business model innovation posits the new ways of doing business with
an objective to create, capture and deliver value to customers as well as other stakeholders (Bashir
& Verma, 2019). The organizations have recognized that innovation in the business model(s)
necessitates a viable extent of profitability. Now, the organizations are needed to capitalize in
emerging market opportunities in order to meet the evolving wants of customers and potential
markets in a valued manner. Subsequently, it essential to illustrate that business model innovation
is a means for an organization to grow profitably (Teece, 2018).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
2
In addition, the present intense competitive market dynamics of organizations further calls
the need for them to behave quite vibrant in innovation capabilities for capturing the on-going
technological developments. In pursuit of sustaining the existing market share piece, the
organizations need to get more malleable towards their capabilities for the creation of value in the
existing business model (Teece, 2018). Innovating the existing business model and adopting the
new business model in parallel with an existing parental business model are the emerging
approaches of the organization to endure the market competition. Therefore, it can be said that the
business model innovation may be largely determined and influenced by the innovation
capabilities of the organization (Teece, 2018). The planning, developing, crafting, implementation
and altering the business models are also sequential to the innovation capabilities of the
organization (Teece, 2018). However, there exists very little empirical evidences on the
consequential influence of innovation capabilities.
Innovation capabilities may bring innovation outcomes in delivered services to the
customer with more satisfaction. Steadily streams of researches are attempting to identify the
factors that contribute to innovation success. However, it is necessary to state that “service
innovation success” may not be confused with “innovativeness” as it is something different from
it. Service innovation success reflects the outcome of innovation process in terms of success
achieved in new launched or offered service (Riel, Lemmink & Ouwersloot, 2004; Baker &
Sinkula, 2009) while on the other hand, innovativeness refers to the extent of openness of an
organization towards the new ideas (Hult & Ketchen, 2001; Hamel, 2000; Verhees & Meulenberg,
2004). The researches from the discipline of strategic management and corporate entrepreneurship
are manifest with the fact that the service innovation success is a principal means through which
an organization manages to expand its consumer base as well as service markets. However, the
literature evidence that service innovation success may not contribute to the overall profitability
of the organization (Pelham, 1997; Baker & Sinkula, 2009). The success of the new service itself
represents an excellent performance of new service but contextually, at the expense of existing
services i.e. such as cannibalization (Chandy & Tellis, 1998). It may further pave the way for the
business model innovation for the organization.
Besides that, there might be multiple elements from corporate entrepreneurship discipline
that are also linked with business model innovation and even some are highlighted in literature-
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
3
based bibliographic researches documented for future avenues of research (Scheinder & Speith,
2014; Bashir & Verma, 2019). Among those, management entrepreneurial orientation and
employee resistance to change are the prominent notions that are pinpointed by recent researches
on business model innovation that needs to be studied further (Foss & Saebi, 2018).
It would not be incorrect to proclaim that innovation lies at the heart of entrepreneurship,
however, all forms of innovation are not the result of strong entrepreneurial orientation. Each and
every organization or firm regulate the innovation routinely i.e. may be newness brought in
response to competitors action. However, the entrepreneurial orientation triggered innovations is
somewhat more than the adaptation or responses to ongoing market trends. The innovation
triggered by entrepreneurial orientation is basically rejuvenation, redefining the concepts and
renewal in nature (Covin & Miles, 1999) that may influence the overall business model of the
organization. The organizations with strong entrepreneurial orientation are more indulged in
activities to establish new service concepts aiming to address the present on-going customer needs
(Baker & Sinkula, 2009). However, it may not be as simple as it could be assumed. Organizations
operating in real-world hinge on the human capital (employee) for the successful transaction of
activities. These employees are the ones who carry the cognitive and behavioral processes for the
pursuit of personal as well as organizational goals. There exists a vast amount of literature since
the late 1950s that advocates that the resistance from employees is something natural obstacle in
ways of change or implementation of something new or better version. This fact is also pointed by
a researcher to be further explored. Vaznyte and Andries (2019) pointed out that more empirical
researches are needed to investigate the effect of employee resistance in effecting the extent of
business model innovation.
1.2. Gap Analysis
The review of the literature reveals that the notion of business model innovation is the
recently evolved (Bashir & Verma, 2019; Spieth & Schneider, 2016). The researches on this
recently evolved construct have failed to achieve the consensus and general belief that what are
the factors that constitute the business model innovation (Mintzberg, 2017; Saebi, Lien, & Foss,
2017; Trapp, Voigt, & Brem, 2018; Bashir & Verma, 2019). The existing researches on business
model innovation are not harmonized with each other (Bashir & Verma, 2019; Scheinder & Speith,
2014). There exists incoherency in the dimensions of business model innovation among
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
4
researchers in various different directions (Bashir & Verma, 2019; Foss & Saebi, 2017; Scheinder
& Speith, 2014). This issue of incoherence among the studies may be obvious because the concept
of business model innovation is the recently evolved construct and presentation of different
aspects, viewpoints and debates serve as the foundation for the knowledge building mechanism
(Spieth, Schneckenberg, & Ricart, 2014). Resultantly, this may not be fruitful for the general
agreement on the operationalization of concept over the newly emerging concept. This has created
a gap in the existing knowledge body as well as the managers to understand the mechanism of
business model innovation in the real world. The understanding of what constitutes and contributes
to the business model innovation is something essential for the managers or practitioners to be
familiar with. Some of the researches have presented their viewpoints on the elements or
constituents of business model innovation, but no or negligible empirical evidence of these
viewpoints further doubts the generalizability of their statement (Bashir & Verma, 2019; Foss &
Saebi, 2018). A very little is also known on the matter that what are the factors that instigate or
influences this business model innovation in the organization (Bashir & Verma, 2019; Teece,
2018; Foss & Saebi, 2018; Hossain, 2018; Geissdoerfer et al., 2018). This highlights that the
problems exist in the existing literature of business model innovation.
Furthermore, the review of extensive literature on business model innovation reveals that
most of them have adopted the qualitative research method and limited or few researches are
available with empirical testing of the operationalization. This also indicates a gap in the literature
body. Geissdoerfer, Vladimirova, Van Fossen and Evans (2018) also debated that future researches
necessarily needs to validate the dimensions of business model innovation through empirical
analysis in different cultural contexts. Scheinder and Speith (2014) also argued that more cross-
cultural empirical researches are needed to validate the adaption of business model innovation in
different cultural contexts. There is a need for future researches to bring coherence and legalize
the components that constitute the business model innovation through empirical analysis (Bashir
& Verma, 2019; Foss & Saebi, 2017, 2018). This establishes the need to empirically validate the
dimensions of business model innovation in pursuance of goal to generate foci of
operationalization in a specific direction for the overall uniformity (Bashir & Verma, 2019;
Hossain, 2018; Geissdoerfer et al., 2018). This also serves as a research gap in the existing body
of knowledge. It is also crucial to state that the economies of western counterparts are different
than the developing economies in their institution, infrastructural and economic structures. The
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
5
researches on business model innovation conducted in the West need to be reconsidered, validated
and tested for further modification, alteration, and extension of theories/conception among the
developing countries. This fact is also argued earlier by Hofstede (2001) who conducted the
research in a global context. Hosfstede (2001) found that Pakistan, being the state in South-Asian
region, possess the score of 70 for preference to avoid the uncertainty that was too high in
comparison to other countries like the United States (46), Canada (48), Denmark (23) and United
Kingdom (35). This reflects that the cultural context of Pakistan is less keen towards innovation
due to the higher preference of avoiding uncertainty in comparison to the West (Hofstede, 2001)
leading to the need to empirically validate the operationalization of business model innovation in
Pakistani cultural setting.
The extensive of recent researches discloses that the researches on the enablers of business
model innovation are scarce in the present literature body and thus, it paves the further avenues
for forthcoming researches (Bashir & Verma, 2019; Foss & Saebi, 2018, 2017; Scheider & Speith,
2014; Teece, 2018). This stresses a need for forthcoming researches to examine the enablers of
business model innovation (Geissdoerfer et al., 2018; Hossain, 2018; Bashir & Verma, 2019).
Scheider and Speith (2014) also pinpointed certain challenging research questions for forthcoming
researches that also states the need to investigate the factors of business model innovation in
different cultural settings? Teece (2018) has argued that the innovation capabilities may play an
influential role in determining the business model innovation and thus, needs to be further
empirically explored. Similarly, some of the researches have also argued that the complex
interaction of innovation capabilities and business model innovation needs to be further
empirically studied concerning some performance indicator i.e. innovation success (Bashir &
Verma, 2019; Teece, 2018). Thus, they serve as research gaps that may pave the way towards the
development of the research objectives of study.
Foss and Saebi (2018) posed three crucial research challenges for investigating the
antecedent of business model innovation in future researches. These posed research challenges
state that (i) there is a need to study the influence of capabilities as the internal drivers of business
model innovation (Teece, 2018; Bashir & Verma, 2019; Foss & Saebi, 2018), (ii) there is a need
to explore the effect of entrepreneurial orientation or vision in predicting the business model
innovation (Vaznyte & Andries, 2019; Foss & Saebi, 2018), and (iii) there is a need to empirically
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
6
study the effect of employee resistance in effecting the extent of business model innovation
(Muller, 2019; Foss & Saebi, 2018). Thus, there is a need to study the tentative effect of these
factors on the business model innovation of an organization that serves as a research gap in the
existing body of knowledge.
It is pertinent to mention that the concept of business model innovation falls in the domain
of strategic entrepreneurship. The proponents of the strategic entrepreneurship perspective (Hitt et
al., 2001; Ireland et al., 2003, 2009, 2011) advocate a multi-theoretic approach towards the
strategic entrepreneurship perspective for future avenues of researches. It is because the theory-
based approach allows the new stream of researches to investigate and elaborate on the conceptual
insight phenomenon and enables the researches to illustrate the scientific and systematic reasoning
of some occurrence or non-occurrences. Corley and Gioia (2011) also indicate that the theories are
the instrument by which the investigators enhance the understandings of concepts, paradigms and
their complex nature of association. Thus it surfaces the avenues for exploration and illustration
of new knowledge by apprehending the different viewpoints of concepts, paradigms or
phenomenon through different theoretical approaches or lense (Corley & Gioia, 2011). Prior
researches have called for new researches to empirically study the theory of strategic
entrepreneurship through the lens of different existing foundational theories (Covin & Lumpkin,
2011; Ireland et al., 2003, 2009, 2011; Miller, 2011). Therefore, this research work focuses to
contribute the novelty by investigating the strategic entrepreneurship initiative of business model
innovation through theoretical perspective of force field of change.
1.3. Problem Statement
The problem statement of this work lies in the scope of the strategic entrepreneurship
theoretical perspective (i.e. advancement of knowledge relating business model innovation). The
review of the extensive body of knowledge reveals that there exist some research gaps that need
to be researched for the progression of knowledge in a specific direction. These research gaps are
briefly elaborated in the gap analysis section. In order to fill these identified gaps of the reviewed
literature, this dissertation aims to study the enablers and different factors influencing the business
model innovation specifically in Pakistani cultural context. The problem statement guiding this
research work is as follows;
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“There is a need to empirically investigate the effect of innovation capabilities on business
model innovation. In addition, there is also a need to further empirically investigate the
mediation effect of service innovation success on the direct effect of innovation capabilities
and business model innovation. Furthermore, there is also a need to further empirically
investigate the moderating effect of employee resistance and management entrepreneurial
orientation on the direct relationship of innovation capabilities and business model
innovation in the cultural context of Pakistan. These are the guiding statement of the
problem of this research study”.
1.4. Objectives of the Research Study
The objectives of this dissertation are as follows;
i. To empirically test the dimensions of business model innovation in the cultural context of
Pakistan.
ii. To examine the role of service innovation capabilities being the predictor of business model
innovation.
iii. To examine the indirect mediation impact of service innovation success on the association
of service innovation capabilities and business model innovation.
iv. To examine the moderation impact of employee resistance on the direct and indirect
association of service innovation capabilities and business model innovation.
v. To examine the moderation impact of management entrepreneurial orientation on the
direct and indirect association of service innovation capabilities and business model
innovation
vi. To examine the overall indirect effect of service innovation capabilities on business model
innovation (through mediation effect of service innovation success) that are further
moderated by employee resistance and management entrepreneurial orientation.
1.5. Research Questions
This research study addresses the answers of following six research questions;
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
8
RQ 1: What are the main factors that explain the operationalization of business model
innovation among cellular companies in Pakistan?
RQ 2: Do service innovation capabilities associate with business model innovation?
RQ 3: Does service innovation success mediate the relationship between service innovation
capabilities and business model innovation?
RQ 4: Does employee resistance to change moderate the direct and indirect effect of service
innovation capabilities on business model innovation?
RQ 5: Does management entrepreneurial orientation moderate the direct and indirect effect
of service innovation capabilities on business model innovation?
RQ 6: Do the innovation capabilities indirectly affect (through significant mediation effect of
innovation success) the business model innovation, which is further moderated by
employee resistance to change and management entrepreneurial orientation?
1.6. Contribution of the Study
This research work carries six major contributions. Primarily, this research study
contributes to the existing literature body by empirically testing the operationalization of business
model innovation. It is crucial to inform that the majority of previous researches on business model
innovation are found to be qualitative in nature and very few or limited researches have been
carried earlier on the empirical testing of the dimensions of business model innovation up-til-now.
Furthermore, the researchers on the business model innovation do not carry any coherence and
harmony with each other in relevance to the elements of business model innovation. Some of the
researches have also argued that future researches may need to bring coherence and legalize the
components that constitute the business model innovation through empirical analysis (Bashir &
Verma, 2019; Foss & Saebi, 2018, 2017; Geissdoerfer et al., 2018; Clauss, 2017; Scheinder &
Speith, 2014). Thus, the novelty of this work is manifest with the fact that this work will be solitary
that empirically testifies dimensions of BMI in the cultural context of Pakistan.
Secondly, this research work aims to contribute to the body of knowledge by further
exploring the antecedents of business model innovation as the conception of business model
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
9
innovation is newly emerged and underutilized in the present literature (Bashir & Verma, 2019;
Teece, 2018; Foss & Saebi, 2018, 2017; Geissdoerfer et al., 2018; Speith & Meissner, 2018).
Future researches also indicate the need to further investigate the factors that influences the
interaction and influencing effects of factors on the business model innovation also constitutes as
a research gap in the body of literature (Bashir & Verma, 2019; Teece, 2018; Foss & Saebi, 2018,
2017; Geissdoerfer et al., 2018; Speith & Meissner, 2018). The significance of this work is evident
from the fact that this study attempts to address this gap by investigating some of the antecedent
factors of construct business model innovation.
Thirdly, this research study also contributes to the existing body of literature by attempting
to address some of the identified literary gaps posed by some recent researches (Speith & Messner,
2019; Foss & Saebi, 2018; Teece, 2018; Muller, 2019; Scheinder & Speith, 2014; Bashir & Verma,
2019). These identified research gaps state that there is need to investigate (i) the role of innovation
capabilities as internal driver of business model innovation (Speith & Messner, 2019; Teece,
2018), (ii) the role of entrepreneurial orientation or vision in determining business model
innovation (Vaznyte & Andries, 2019; Foss & Saebi, 2018), and (iii) the role of employee
resistance in influencing the business model innovation of the organization (Foss & Saebi, 2018;
Muller, 2019). This research work has contributed to the body of literature by closing these posed
future research avenues by certain recent research studies.
Fourthly, this research work attempts to contribute to the existing theoretical body of
knowledge as there is no such agreement or consensus by researchers in existing literature on what
are those factors that determine the innovation capabilities for the attainment and assurance of
service success and business model innovation (Chamsuk et al., 2017; Teece, 2018; Narcizo et al.,
2017). Furthermore, the existing literature does not also pertain to the general consensus on the
particular definition of the concept of service innovation capabilities and there is further need to
validate the concept of service innovative capabilities among different contexts (Chamsuk et al.,
2017; Narcizo et al., 2017). Thus, this research work contributes to the body of knowledge by
validating the concept of innovation capabilities in the cultural context of Pakistan. Furthermore,
this research work is one of the prior researches that have studied the dimensions of innovation
capabilities in the cultural context of Pakistan as no or negligible related research has previously
been conducted.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
10
Fifthly, this study attempts to contribute to the body of knowledge by validating, testing
and reconsidering the measures of some crucial constructs (i.e. employee resistance, management
entrepreneurial orientation, and service innovation success) in Pakistani cultural settings. It is
essential to state that these research measures are developed and tested in the West. They require
further modification, alteration, and extension for the application in the Pakistani’s cultural
settings. Moreover, the cultural dynamics of a Western counterpart (in which the conception and
theory of these measures have been developed) are different from Eastern countries like Pakistan
(Hofstede, 1991). Therefore, there is a need to reconsider and validate these measures in Pakistani
culture. This research work is considered to be a pioneer in exploring and studying the relationship
of innovation capabilities, service success, employee resistance, entrepreneurial orientation, and
business model innovation in Pakistani cultural settings.
Lastly, this study signifies itself with the fact that it carries some essential understandings
for the practitioners relating what enables their organization to perform business model innovation.
This information might be beneficial for the managers to understand what are the essential
elements to achieve service innovation success and business model innovation more healthily.
1.7. Dissertation Structure
This dissertation is planned to consist of five chapters.
Chapter 1 namely ‘Introduction’ discusses in detail the background of the study, problem
identification or problem statement, aim/objectives of conducting this research, research questions
and significance/contribution of this research work.
Chapter 2 namely ‘Literature Review’ covers all major past research literature reviews and
theories relating to the research construct. Past and recent researches, theories and concepts
relevant to topic and research constructs collected through primary and secondary sources are
studied, analyzed and reviewed. These instances of reviewed literature are then quoted and
critically presented in this chapter. Then, the research gap is discussed in light of quoted literature.
Based on the identified gap from literature, the hypothesized conceptual framework is discussed
and the hypotheses are drawn reflecting the nature of the relationship between dependent,
independent and mediating/moderating variables of the research work.
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11
Chapter 3 namely ‘Research Methodology’ briefly discusses the theoretical underpinnings
of the proposed research model of this study. The theoretical framework, study variables, and
nature of the relationship among the variables are discussed in this chapter. Then, the key study
variables of this research work along with the operational definitions are explained. Then it depicts
in-depth the methodology adopted in this work illustrating the research design, population and
sample frames, sampling strategy used, sample size drawn, research instrument development, and
information about the analytical techniques.
Chapter 4 namely ‘Data Analysis and Results’ covers the analytical/statistical results
drawn by conducting the statistical techniques to check the hypothesized relationships of research
constructs. Descriptive statistics are computed and demographic analysis of respondents is also
tabulated to elaborate on the characteristics of participants. The results of statistical tests conducted
to check the research hypothesis are discussed in the end.
Chapter 5 namely ‘Discussion, Recommendation, and Conclusion’ includes the important
literature review quoted in association with the posed research question and purpose of the study.
The hypothesized relationships of research variables are discussed in link with the analytical
results drawn and the existing theories/researches of vast literature bodies. Then, the major
conclusion of this research work illustrated on the basis of the arguments made in the previous
chapter. Lastly, the practical and managerial implications along with the future research
dimensions are discussed.
1.8. Chapter Summary
Table 1.1 illustrates the research gaps of this study and further explains a mechanism
carried to address these research gaps as,
Table 1.1.
Illustrating Research Gaps and Formulation of Proposed Hypotheses
Research gaps refer
by researcher A mechanism to address the research gap
Contribution
to previous
theories
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
12
Gap – 1 :
The operationalization of business model
innovation needs empirical analysis as the
majority of the previous researches have opted
for qualitative approach with no or less
empirical analysis (Foss & Saebi, 2018, 2017;
Bashir & Verma, 2019; Geissdoerfer et al.,
2018; Hossain, 2018; Scheider & Spieth, 2014).
• Research objective 1 and research question 1
have been established to address this gap.
• Similarly, the concept of business model
innovation is empirically validated by
conducting the detailed reliability and validity
analysis and composite reliability of the
research instrument of the construct.
S.E Theory
Gap – 2 :
It is vital to investigate influence of innovation
capabilities as a driver of BMI with empirical
analysis (Scheinder & Speith, 2014; Foss &
Saebi, 2018, 2017; Teece, 2018).
• Research objective 2 and research question 2
have been formed.
• Hypothesis 1, will be formed to address this
research gap. This identified gap may be
addressed by empirically testing this hypothesis
1.
S.E Theory
Gap – 3 :
More empirical researches are needed to testify
the relationships of business model innovation
with the performance indicator i.e. maybe
innovation success (Teece, 2018; Speith &
Messner, 2019).
• Research objective 3 and research question 3
have been established to address this gap.
• Hypotheses 3 and 4 will be established to
address this research gap. Hypotheses 2 will also
be developed in provision of hypothesis 4. This
identified gap may be addressed by empirically
testing these three hypotheses.
S.E Theory
Gap – 4 :
It is essential to testify the role of employee
resistance on business model innovation
(Muller, 2019; Foss & Saebi, 2018). There is
also a need to explore the moderation effect (i.e.
employee resistance) among innovation
capabilities and service success (Hao & Yu,
2011; Muller, 2019)
• Research objective 4 and research question 4
have been established.
• Hypotheses 5 and 6 will be formed to address
this research gap. This identified gap may be
addressed by empirically testing these
hypotheses.
S.E Theory
and
F.F Theory
of Change
Gap – 5 :
It is essential to testify the influence of
management entrepreneurial orientation in
shaping business model innovation (Foss &
Saebi, 2018; Vaznyte & Andries, 2019).
• Research objective 5 and research question 5
have been established.
• Hypotheses 7 and 8 will be formed to address
this research gap. This identified gap may be
addressed by empirically testing these
hypotheses.
S.E Theory
and
F.F Theory
of Change
Gap – 6 :
There is a need to bring deep insight into the
antecedents of the business model innovation.
The number of researches indicated that no
researches have been carried up-till-now relating
the antecedents of the business model
• Research objective 6, research question 6 is
formed to address this gap. Further, hypotheses 9
and 10 will be formulated to testify the overall
research model of this research work.
S.E Theory
and
F.F Theory
of Change
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
13
innovation. Thus it also serves as a research gap.
Business model innovation needs to be explored
as a dependent variable in future researches
(Foss & Saebi, 2018; Bashir & Verma, 2019;
Geissdoerfer et al., 2018; Speith & Meissner,
2018; Hossain, 2018; Saebi, Lien & Foss, 2017).
*whereas S.E Theory =Strategic entrepreneurship theory (Hitt, Ireland & Camp 2001; Ireland, Hitt & Sirmon, 2003; 2011); F.F Theory of
Change = Force Field Theory of Change (Lewin, 1951).
The mentioned six research gaps are further deeply explained and illustrated in light of
extensive literature review in consequent chapter two.
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CHAPTER 2
LITERATURE REVIEW
This section briefly discusses the existing theories, literature, and researches on study
variables that are business model innovation, service innovation success, innovation capabilities,
management entrepreneurial orientation and employee resistance to change. The critical review of
the theoretical aspect and nature of the relationship among the study variables are also discussed.
The discussion on the association of study variables and hypotheses development further pave the
way towards the formation of a theoretical model of this work.
2.1. Theoretical Foundations of Study
This research work efforts to view strategic entrepreneurship perspective (Hitt et al., 2001;
Ireland et al., 2003, 2009, 2011) through the lens of force field of changes (Lewin, 1951).
2.1.1. Strategic Entrepreneurship Perspective
A strategic entrepreneurship perspective has evolved as the intersection of strategic
management and entrepreneurship by Ireland and colleagues (2001). Strategic entrepreneurship
theory is illustrated as the interplay of strategic and entrepreneurial initiatives that intend to attain
strategic performance in the competitive external environment by focusing on the emerging market
opportunities (Ireland et al., 2001). Pursuing an entrepreneurial mindset along with the regulation
of entrepreneurial culture within the organization with an intention to sense the emerging market
opportunities and then exercising the existing capabilities with effective utilization of resources
for the enhancement of business innovation are some essential parameters of strategic
entrepreneurship initiatives (Ireland et al., 2001, 2003). Mazzei, Ketchen, and Shook (2016)
explained the strategic entrepreneurship theory as a combination of behavior seeking for the new
opportunities as well as the emerging advantages from these opportunities. The scope of strategic
entrepreneurship theory falls in the domain of management body of knowledge. But, there still
exists the necessity to examine this theory in blend with other varied theoretical perspectives
(Mazzei et al., 2016).
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2.1.2. Force Field Theory of Change
Force field theory of change by Kurt Lewin (1951) is one of the most established, referred
and leading theories of change management. The work of Lewin (1951) states that there are forces
who shape and influence the behaviors of organizational members and these forces are generally
termed as ‘driving forces’. The mere emphasis of Lewin’s work lies at the dynamic or status quo
nature of context that determines the behaviors of organizational members including managers.
The force field theory of change explains that there are two forms of forces (driving forces and
resistive forces) that surround the members working in any organization. These two forces efforts
in the opposite direction to each other, consequently determining the behavior of organizational
members. The theory further explains that when these two opposite forces (driving forces and
resistive forces) are equal in magnitude within the organization, then it creates a state of inertia
(also termed as quasi-stationary equilibrium). The organization can foster no change during this
state of inertia. Lewin (1951) further explains that when the field of these two forces fluctuates
with the change in their magnitudes (i.e. resistive forces higher or lower than the driving forces)
then the behaviors of the organizational members also change. For the organization who pursues
the change implementation, it is desirable that the driving forces should be higher in magnitude in
comparison to resistive forces (Lewin, 1951). The theory further explains that the organization
needs to break the inertia state before introducing the novel changes. At first instance, the
organization requires to identify its current state by knowing the magnitude of the resistance level
and driving forces and pursue to create awareness for the necessity of novel changes. On successful
declaration and acceptance of the necessity of novel changes, an organization needs to implement
its planned action by further involving the members act in a participative manner. Once the desired
novel changes have successfully introduced within the organization, this further paves the way to
ensure the sustainability of these changes by their permanent incorporation (Lewin, 1951). Dent
and Goldberg (1999), Cameron and Green (2015) indicate that the concept of employee resistance
to change originates from the work of Lewin (1951).
2.2. Concepts, Definitions, and Established Researches
This section explains the critical review of different theoretical and conceptual frameworks
of all the study variables of this research work that are innovation capabilities, management
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
16
entrepreneurial orientation, business model innovation, employee resistance to change and
innovation success. In this section, different standpoints on this variable are discussed in different
ways with an objective to provide deep insight into constructs.
2.2.1. Business Model Innovation (Dependent variable).
The concept of the business model in several decades old (Bellman, 1957) that was thought
to be static in nature. This concept has been originated from the field of corporate practice (George
& Bock, 2011). Notwithstanding the scholars and researchers have invested their considerations
in this field, however no regularly acknowledged definition and comprehension of business model
innovation have yet been established (Saeibi et al., 2017; Bashir & Verma, 2019; Scheinder &
Speith, 2014). The reason behind this diversity in the researcher’s advancement was the missing
association among their concurrent thought – process (Bashir & Verma, 2019; Zott, Amit & Massa,
2011). The existing researches are scattered and were not found to be linked with each other for
the advancement of concept clarity (Saeibi et al., 2017; Bashir & Verma, 2019; Scheinder &
Speith, 2014).
The concept of business model innovation is basically the extension of the existing concept
of a business model. The static business model conception gradually emerged into dynamic
business model innovation when the researchers of entrepreneurship and strategy (in the early
years of the twenty-first century) explained the static concept as a holistic illustration of key
business processes (Zott et al., 2011). Researches on business model innovation have gained great
momentum in present periods. It is vital to inform that the call for research by special issue editions
of the “Long Range Planning” journal in the year of 2013 has primarily played the role of catalyst
for researches on the emergence of business model innovation. Later on, further call for research
from two special issues of “R & D Management” journal and “Global Strategy” journal in the year
of 2015 transparently paved the emergence of business model innovation conception from the
older static business model concept. Thus, it would not be incorrect to proclaim that business
model innovation is the recently evolved concept and that needs to be explored (in terms of concept
clarity, factors driving it and its consequent effects) as also indicated by some researchers
Scheinder and Speith (2014) Foss and Saeibi (2018, 2017) Clauss (2017).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
17
The concept of the business model is no more static in the present era. It is something that
needs to managed, sustained and developed with the passage of time (Hedman & Kalling, 2003).
This development is necessary as the external market dynamics of the organization became more
competitive with market shifts and technological advancements. This requires the organization to
improve and develop their existing business models in order to sustain in present competitive
market dynamics. Thus, the business models are the one that seems to be dynamic in nature now
(Teece, 2018; Morris, Schindehutte & Allen, 2005). The continuous changes (in terms of
development) may be denoted as business model innovation.
The review of the existing literature has revealed that different authors have elaborated on
the phenomenon of business model innovation in different aspects. Witell and Lofgren (2013)
explained the business model innovation as the extent of changes in the current business model
either incremental or radical in nature. The researcher explained that the business model innovation
enables the organization to accelerate product and service innovation. This concept is related and
important for the practitioners and academicians due to some reasons. First of all, the business
model innovation reflects an underused cause of value creation. Secondly, the rivals also regard it
difficult to replicate and lastly, the business model innovation can also serve as an essential
competitive tool for the organization (Witell & Lofgren, 2013).
Apart from this illustration of business model innovation in literature, Teece (2018, 2010)
claimed that the business models deceptively look simpler but they cannot be patented. This further
supports the argument that the business models are difficult to replicate by the rivals but due to
some other possible causes. The concept of business model innovation scopes beyond the domain
of product or service innovation only, rather it serves as a tool for attaining a competitive advantage
by strengthening the competitive positioning of the organization among rivals (Teece, 2018, 2010).
2.2.1.1. Dimensions of business model innovation.
Johnson, Scholes, and Whittington (2008) explained the business model innovation as a
constituent of three basic elements that are (i) customer value proposition, (ii) key organizational
resources and process and lastly, (iii) profit formula of the organization. Koen, Bertels, and Elsums
(2011) explained the concept of business model innovation as of three types that are (i) technology,
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
18
(ii) financial hurdle, and (iii) value network. However, other researches are of the opinion that the
concept of business model innovation delivers uncertain outcomes as the innovation to the
organizational products, services and process requires more investment and time (Amit & Zott,
2012). Santos and Eisenhardt (2009) explained the business model innovation as the realignment
of activities in the present business model of the organization that is something novel to the market
of product or service in which the organization struggles. Gambardella and McGahan (2010)
defined the concept of business model innovation as the novel approach of the organization to
commercialize its existing assets. On the other hand, Casadesus and his colleagues (2012) defined
the concept of business model innovation as the search of an organization to acquire new logistics,
new ways of creating value and new ways of capturing value for all the stakeholders of the
organization. In line with the Casadesus and Richart (2012) explanation, another investigator has
also differentiated the business model innovation in terms of value creation, value proposition and
value capture for all the stakeholders of the organization (Richter, 2013). Comes and Berniker
(2008) claimed that the business model innovation carries the answers of the two important
questions that are (i) what value does the organization deliver to its customers? And how does this
delivered value benefit (i.e. financial, value chain, organizational structure, etc.) the organization
back? Yunus, Moingeon, and Lehmann-Ortega (2010) explained that the business model
innovation comprises of three elements of value proposition, profit equation, and value
constellation. The value proposition refers to the description of the customer and the value
delivered to those customers. The profit equation answers the questions that how the value is
captured from the revenue generation mechanism through a value proposition. The third element
value constellation refers to the mechanism that how the organization may deliver the promised
value to its customers. On the other hand, another researcher claimed that the business model
innovation comprises of three capabilities of strategic sensitivity, resource fluidity, and leadership
unit.
The literature review also reveals that the concept of business model innovation is most
limitedly debated than any other concept in the field of strategy. The middle layer managers play
an essential role in regulating business model innovation (Hossain, 2017). Managerial and
entrepreneurial skills affect the extent of innovation in business models (Hossain, 2017). Basically,
the business model innovation process is accelerated and flourished by the strategic activities of
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
19
experimenting, abstracting and reframing the existing business models (Doz & Kosonen, 2010).
However, some organizations put behind low-cost methods for the overall improvement in
profitability. This fact is also argued by Hinterhuber and Liozu (2014) who argued that the majority
of the organizations stress the innovation in new products or services. However, the innovation in
pricing strategies of product or service may also be a powerful tool in the hands of an organization
for the attainment of competitive advantage. In a competitive environment, the suppressed and
week (in terms of the competition) organization uses the pricing innovation as a defensive strategy
to bring innovation in the business model for its stability (Velu, 2016). It is essential for the
organization to bring innovation in its business model through a generative cognition mechanism
as a proactive approach (Geissdoerfer et al., 2018).
However, the existing management theories need more detailed precision relating to the
manner the business models of the organization get innovated (Fuller & Haefliger, 2013). The
managers are essential to understanding the in-depth complexities of the ongoing innovation and
factors of business model innovation (Fuller & Haefliger, 2013). Basically, the business model
innovation effectuates the firm on a broader level. It is because the phenomenon of business model
innovation itself requires the organizational restructuring that is not similar in the cases of the other
forms of innovations. In this regard, the participation of top management is fundamental for the
attainment of business model innovation. The relational dynamics by managers are key for the
business model innovation at informal levels within the organization (Zott et al., 2012). This fact
is also supported by Doz and Kosonen who argued that the role of leadership in bringing innovation
at the business model is necessarily critical for fostering leadership unity. The facilitative activities
(such as dialogue, alignment, and collaboration among all levels of the organization) need to be
encouraged by the organization to attain leadership unity. In parallel to this, the cross-functional
teams and individual behaviors of acceptance or resistance may also possess an influential role on
the extent of business model innovation. The organizations need to be flexible in this regard as the
mechanism of business model innovation involves the transfer of existing business models from
one market to another (Amit and Zott, 2009). The organization needs to be flexible with respect to
their internal customers (that are employees) and patience for business failure due to innovation in
the business model. This business failure may be caused by some cost structures, unit margins or
some false assumptions of innovation or the velocity of the external environment dynamics
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20
(Schirmer, Hartmann, Bertel, & Echtler, 2015). Business model innovation is no more a static
process and overall the organization’s intention to improve its business models always possess a
positive impact on its ability to perform. However, it was argued in the existing literature that new
organizations with the low level of business model innovation may be studied to be successful in
the longer run in comparison to those new organizations who possess the moderate level of
business model innovation (Velu, 2016). It means that the new organizations experience a decrease
in the survival challenge as the extent of business model innovation increases.
Despite a wide disagreement among the different researches on the conceptualization and
clarity of concept between the researchers, they generally agree on a point that business model
innovation articulates the value creation. It involves the different values promised to deliver to the
customer and their interrelation among each other (McGrath, 2010) while on the other hand, value
proposition refers to how value is delivered to the customer (Teece, 2010). Although it is believed
that the integration of product and service delivery business models may be essential for the
creation of value for the customers. As the delivery of service may be viewed as the strategic
complement to the product with an intention to please the customer. But it is essential to mention
that providing the service along with the product may not be sufficient enough to create and capture
the value for the customer. Innovation in business model may another footstep for the value
creation and capture. Johnson et al., (2008) pointed out that business model innovation may
possess the luminous value proposition, as the offered complementary services may not address
the same need of value.
Innovation in business model may be of two folds for the organizations (i) with the
integration of new technological advancement or (ii) adoption, experimenting of new ideas.
Innovation in business model may acquire through the integration of updated technological
advancement for the creation of value. But, technological innovation may not prove popular
enough in comparison to innovative ideas (Chesbrough, 2010). It may happen that the simple novel
idea with a great business model may create more value to the customer than the business model
with superior technology offerings. Capturing the value basically requires the demonstration of
value creation, generation of business model options or choices, further identification of the risks
for each option proposed during generation of business model, prioritize the risk elements,
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
21
reducing the extent of risk through experimentation and doing homework for incubation (Euchner
& Ganguly, 2014). This process approach towards the capture of value may yield an effective
innovation in business model (Euchner & Ganguly, 2014). Option choices are critical for
innovation in the business model. Poor option choices may yield week business model innovation
while the strong option choices (i.e complementary product offerings etc.) may consequent to
strong business model innovation (Fuller & Haefliger, 2013). Although, the business model
innovation involves the phenomenon that how an organization may capture value for the customers
from their product or service offerings. Still this phenomenon carries the complex decision
processes with heavy investments, costs for the acquisition of new required resources,
orchestrating of existing business processes and the efforts to overcome the internal resistance
from employees (Desyllas & Sako, 2013).
Furthermore, the role of the manager in identifying the external opportunity, searching for
new business models, experimenting the new ideas and implementing at the appropriate time are
some fundamental aspects of business model innovation. An organization may observe some
differences among the implementation of the new business model either completely replacing the
existing business model or implemented parallel with the in-practice business model. In secondary
case, the organization attempts to overcome the failure risks by pilot testing the new business
model in single business-unit or small targeted market for a restricted time period (Bucherer, Eisert
& Gassmann, 2012). The organization may have the option to revert back to the previous old
business model (parallel in practice) in case the new business model met with failures. However,
running a new business model parallel with the existing old business model would require some
additional separate business units either partially centralized with other functioning of an
organization or completely independent (Bucherer, Eisert & Gassmann, 2012).
2.2.1.2. Research Gap - 1: Operationalization of BMI needs further empirical validation.
(Foss & Saebi, 2018, 2017; Bashir & Verma, 2019; Geissdoerfer et al., 2018; Hossain, 2018;
Scheider & Spieth, 2014)
Extensive previous researches are available on the literature of business model (Lambert
& Davidson, 2013; Wirtz, Pistoia, Ullrich & Gottel, 2016) however, the extensive review of an
existing body of knowledge reveal that the only limited articles (by Schneider & Spieth, 2014;
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
22
Saebi et al., 2017; Teece, 2018, Geissdoerfer et al., 2018; Bashir & Verma, 2019) specifically
reviews the literature streams of business model innovation. These researches discussed in detailed
the present literature stream of business model innovation identified the research gaps and set forth
the potential research questions for the promotion of new researches on the clarity of conception
and development of theoretical frameworks. Foss and Saebi (2018, 2017) argued that there exists
a little agreement by researchers on the dimensionality of business model innovation. The
researcher also claimed that up till now no systematic and empirical analysis of dimensionalization
of business model innovation has been carried out that pinpoints the research gap in present
knowledge body. Scheinder and Speith (2014) also indicated that there is a need to further examine
the factors of business model innovation in different cultural settings in order to establish a better
understanding of business model innovation. Scheider and Speith (2014) posed some research
questions for future researches that includes “what constitutes the factors of business model
innovation among different cultural settings?” and “which general forms of business model
innovation can be notorious among different cultural settings?”. Similarly, Geissdoerfer and
colleagues (2018) debated that future researches necessarily needs to validate the dimensions of
business model innovation through empirical analysis in different cultural contexts. Saebi, Lien,
and Foss (2016) also argued that more cross-cultural empirical researches are needed to validate
the adaption of business model innovation in different cultural contexts. Saeibi et al., (2017) and
Hossain (2018) stated that there is a lack of clarity in existing literature pertaining to the
dimensions and operationalization of business model innovation as this field is emerging one. The
existing new researches are not coordinated and branching off the conception of business model
innovation in various different directions that consequently may not be fruitful for the compact
and general agreement over the new emerging concept. Thus, there is a need for future researches
to bring coherence and legalize the components that constitute the business model innovation
through empirical analysis (Hossain, 2018; Foss & Saebi, 2018, 2017). In this regard, it is essential
to state that Clauss (2017) has developed a research instrument for the measurement of business
model innovation conception after a rigorous scientific research mechanism. However, the
researcher argued that the developed research instrument was validated only in manufacturing
firms and the generalizability of the instrument cannot be promised. The researcher further claimed
that the differences exist in business model innovation among the different industries such as
service business models (Clauss, 2017; Claub et al., 2014). Therefore, future researches are
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
23
recommended by Clauss (2017) to testify the provided instrument of business model innovation
for the different national cultures and organizations. Thus, this indicates a research gap in present
literature of business model innovation. Below mentioned table 2.1 explains all the major
researches conducted on the conceptualization of business model innovation that further supports
this identified gap discussed in detail.
Table 2.1.
Survey evidence pertaining to the conceptualization of business model innovation
Researches on
BMI
Proposed dimensions
of BMI
Methodology
adopted
Limitation and Future
Research Direction
Spieth &
Meissner
(2018)
• Dynamic BMI
• Relational BMI
• Architectural BMI
A qualitative
approach with
case study
approach
Future studies may broaden the results of
a study by testifying the parameters in
different organizations. Longitudinal
studies are also recommended.
Trapp, Voigt
& Brem (2018)
• New value proposition
• Innovative value
constellation
• New BM to firm
• Integrated into daily
operations
• BM created internally
A qualitative
approach with
interview
method
Future research can evaluate the business
model innovation parameters from the
survey method. Future research is also
called to investigate international
business models in detail.
Teece (2018)
Discussed the conception of
business model innovation in
connection with dynamic
capabilities.
Conceptual
paper
Forthcoming researches are suggested to
testify the influence of innovation
capabilities in bringing innovation among
business
Foss & Saeibi
(2018)
Discussed in detailed the future
avenues of research in three
streams of BMI (dimensions, the
effect of BMI and antecedent of
BMI). Supports the dimensions of
BMI as a constituent of three
constructs in line with Teece
(2010) illustration of BMI
construct.
Literature
Review
Future researches are recommended to
explore the role of BMI as independent,
moderating or mediating and dependent
variable. Few challenging research
questions are posed by the researcher for
future researches.
Geissdoerfer,
Vladimirova,
Van Fossen &
Evans (2018)
Discussed the conception of
business model innovation in
connection with service
innovation.
Conceptual
Paper
Future researches are recommended to
explore the dimensions of BMI.
Furthermore, it is also suggested that
future researches may take into account
the differentiation among business model
innovation, service innovation, and
product innovation.
Hossain (2018)
Discussed the past, present
research streams on business
model innovation and paved the
way for future researches
Thematic
Analysis This research has suggested that its
elements must be empirically
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
24
investigated and it is something different
from product and process innovation.
Adrodegari,
Pashou &
Saccani (2017)
Explained the components of
product-service BMI.
• Idea generation,
• Selection of idea
• Requirement analysis
• Implementation and
• Evaluation
Conceptual
Paper
This research has suggested that its
parameters among different sectors and
contexts must be empirically researched
for the advancement of knowledge.
Foss & Saebi
(2017)
Discussed the fifteen years of a
literature review on BMI
Literature
Review
Future researches need to explore and
establish general agreement on constructs
of BMI.
Clauss (2017)
In line with Teece (2010)
illustration of BMI construct
• Value capture
• Value creation and
• Value proposition
Quantitative
approach with
survey method
Future researches are needed to testify the
provided instrument of business model
innovation for the different national
cultures and organizations as the existing
instrument is only tested among
manufacturing firms.
Schneider &
Spieth (2014)
Discussed in detailed the existing
researches and new research
directions on the field of business
model innovation.
Literature
Review
Future researches are needed to explore
the constructs and elements of this newly
evolved concept.
Another essential point to discuss here is that the existing researches on the
conceptual clarity of business model innovation are conceptual in nature or adopted the
qualitative research approach. Furthermore, Foss and Saeibi (2018, 2017); Hossain (2018),
Bashir & Verma (2019), Geissdoerfer et al., (2018); Saeibi, Lien and Foss (2016); and
Scheider and Spieth (2014) also envisions the need to empirically testify the components
and dimensions of business model innovation. This research gap is addressed by empirically
validating the scale comprising of the dimensionality of business model innovation. Detailed
reliability and validity analysis (i.e. through construct validity, composite reliability,
convergent validity and discriminate validity) of the sub-constructs of business model
innovation will be carried in consequent chapters in order to close this research gap.
2.2.2. Service Innovation Capabilities (Independent Variable).
Various researchers have explained the innovation capabilities in various perspectives.
Teece and Pisano (1994) have defined the firm’s innovative capability as those capabilities,
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
25
abilities and resources of the organization that enables the firms to generate the innovation as an
outcome. They further explained that there are four dimensions that enable the firm innovative
capacity that is culture, resources, competence and networks. Culture is embedded within the firms
and is reflected by what and how things are done by the firm. It basically comprises of the
knowledge, skills embedded within the processes and activities of the firm’s systems. Resources
comprise of the sets of assets, skills and internal abilities of the firms that shapes the competitive
position in external environment. Competence represents the ability of firm to convert the
resources into the outcome of productivity and innovation. It involves the effective grabbing of
marketing opportunities through external environment assessment. On the other hand, networks
form the basis to acquire competitiveness. Organizations through informal and formal networking
acquire the relevant knowledge. This acquired knowledge is then translated into the new business
opportunities by the resources and competence of the firm. Thus, the outcome is the innovative
services.
Swink and Hegarty (1998) defined the innovative capabilities as the ability of the firm to
identify the existing crucial technologies and processes of firms for their further development and
improvement in addition to the integration of new technologies from the outside external
environment. In their research study, Swink and Hegarty (1998) have operationalized the
conception of innovative capabilities as the second-order construct. Its first order constructs are (i)
search for new technologies, (2) processes and equipment developments and (iii) cross-functional
product development. Lawson and Samson (2001) explained the concept of innovation capabilities
as the combination of different capabilities of an organization’s practices, resources and
procedures aimed to bring and adopt the innovation within the organization. It refers to the ability
of the organization to effectively execute and capabilities of the organization to ensure innovation.
In addition, the organization’s human resources, funding and investment channels, operational
champions as the element of time and money all are crucial for the success of any innovative
project in the realm of project management (Lawson & Samson, 2001).
Neely, Filippini, Forza, Vinelli and Hii (2001) has defined the concept of innovation
capabilities as the ability of the organization to produce innovative outputs and continuously
transform the acquired new knowledge or ideas into new products or service offerings to the
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
26
customer. Neely et al., (2001) presented a theoretical framework illustrating the association
linkage between innovation capability and business performance. The authors explained that the
innovation capabilities cause the organization to perform innovative in terms of product
innovation, process innovation, management system, and organizational innovation. This
innovative performance of the organization impacts the overall business performance in terms of
return on investments, market share, competitive position and value to the customer. Smith, Busi,
Ball, and Meer (2008) argued that the innovation capabilities are comprised of nine factors that
help the organization to build innovation. The author argued that these nine factors of innovation
capabilities are also linked with each other. They are technology, innovation process, corporate
strategy, organizational structure, organizational culture, employees, resources, knowledge
management, and management style & leadership. Nilsson, Regnell, Larsson, and Ritzen (2010)
have defined the innovation capabilities as the multifaceted phenomenon that revolves around
workforce skills, team works, cross-sectional collaboration and many other organizational
characteristics that are related with the innovation. The author has taken the team as the basic unit
of analysis for the study of the conception of innovative capabilities. Innovative teams are treated
as those organizational units that are aimed to produce new products or services to meet the
competitive market needs. Nilsson et al. (2010) presented a three-level conceptual framework
referred to as measuring innovations in teams, illustrating in-depth the concept of innovation
capabilities. It depicts the innovation capability at the team level and the unit of analysis are the
managers and team members. It comprises of three levels that are measurement areas,
measurement factors and finally the measurement inspiration in depth discussed in consequent
paras. The four major measurement areas are the innovation elicitation, project selection, ways of
working and impact. Innovation elicitation represents the measurement area of innovation
capabilities that are more related to innovative ideas identification activities of the project (Nilsson
et al., 2010). Project selection is made on the basis of the most feasible proposal innovation team
got on the terms of finances, resources and time (Nilsson et al., 2010). Project selection is made
on different eligibility criteria including timing, size of project, risk element, internal stakeholders
of the project, external stakeholders and return on investment. Innovation team operates in lieu of
project selection. It may also comprises of the organizational as well as the team capabilities to
run the project, the innovation process and the extent of flexible climate of innovation and
creativity among the team members aimed at ensuring the continuous improvement in processes.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
27
The innovation team overall falls accountable for the output of the project and responsible to
communicate the benefits of the project or any other further development if required by the project.
The overall generic objective of any project is to provide beneficial impact on the organization.
The measurement factor that revolves in this measurement area of impact are product features,
interaction, trust, intellectual property rights and standards and practices.
Preez, Louw and Essmann (2006) conducted a synthesis on evolutionary literature on
innovation processes and integrates the latest developments / researches and proposed a conceptual
framework illustrating the conception of innovation capabilities and innovation process. Preez et
al. (2006) argued that there are three factors that are complementary and essential for innovation
capabilities to prove sufficient enough to be innovative for the organization. These three factors of
innovation capabilities include innovation process, knowledge exploitation and organizational
efficacy. Christensen (1995) has proposed a framework that has studied all assets of the firm
inclusive of all innovation capabilities and illustrated the inter-linkages and nature of association
among them. The framework by Christensen proposes that the capabilities of organization can be
classified into three broad categories of tradeable resources, capabilities, technical or functional
capabilities and managerial competencies. These group of capabilities helps the organization to
develop new product and services in addition to the major improvements in existing products or
services. Organization needs a specific combination of these innovation capabilities in order to
achieve higher productivity and sustain its survival in competitive dynamics. Martinez – Roman,
Gamero, Tamayo (2011) argued that the innovation capability is deeply affected by three factors
that are (i) knowledge, (ii) organization and, (iii) human factors. The creation, maintenance,
sharing and preservation of knowledge from the external and internal sources of the firm depicts
the extent of knowledge. Incorporation of new organizational member includes the phenomenon
of acquiring new knowledge from the external environment with an objective to enhance the
innovation capability of the firm. The phenomenon of creation of knowledge within the
organization through providing developmental opportunities to employees. Training and
developmental opportunities may eventually lead to increased learning by the employees and thus,
increase the knowledge acquisition phenomenon inside the organization with the increased
employee’s capacity.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
28
2.2.2.1. Review of recent theoretical frameworks of service innovation capabilities.
Aziati, Tasmin, Jia and Abdullah (2014) have explored the concept of innovative
capabilities among the thirty (30) Malaysian food SMEs and have classified the innovation
capabilities into two broad spectra of technological innovation capabilities and business innovation
capabilities. Technological innovation capabilities as explained by Aziati et al. (2014) refers to the
ability of the firm to continuously convert the acquired new knowledge, information and ideas into
the new product offerings, services, structures, processes and systems with the help of the
technology in – a place with an objective to benefit the organization and other internal
stakeholders.
Story, Raddats, Burton, Zolkiewski and Baines (2017) in-depth studied the innovative
capabilities needed to provide the advanced services from the perspectives of three main
organizational actors that are a manufacturer, intermediaries and, customers. The authors discussed
that there are seven key innovative capabilities that are essential for effective service delivery by
these three organizational actors. For manufacturers, there are three innovative capabilities that
could help those foster better services and these three innovative capabilities are (i) need to create
balance among product and service innovation, (ii) Using life service methodologies develop a
customer focused, and (iii) develop synergistic product and service cultures. For intermediaries,
there are two innovative capabilities that could help them provide better-advanced service and
these two innovative capabilities are (i) coordination with a third party and (ii) integration of third-
party product and services. Customers play a crucial role in defining the faith of service
effectiveness as the interaction with customers opens the new ways of thinking for the
manufactures. For the customer, the author defines there are two major innovative capabilities that
are (i) co-creating innovation, and (ii) service outsourcing. Thus, the authors are of the opinion
that this complex interconnectivity of all the network actors together facilitates the effective
service deliveries with the help of these seven innovative capabilities.
Iddris (2016) conducted a research study to study in – depth the conception of innovative
capabilities specifically in the context of supply chain and explored the dimensions of innovative
capabilities. Iddris (2016) explained that the innovation capabilities are comprised of four crucial
dimensions that are idea management, idea implementation, collaboration and finally the learning.
The author argued that together all these four constructs of innovative capabilities helps the
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
29
organization to foster innovative performance. Idea management as explained by Iddris (2016)
refers to the ability of the firm to convert new acquired knowledge and ideas into the new product
or services offering or improvement in existing product or services. The author further explains
that the idea management enables the firm to strengthen the interactions with other market players
and stakeholders (for example suppliers, manufacturers, customers, business partners, employees,
etc.) for the gathering of new knowledge and ideas. Idea implementation as explained by Iddris
(2016) refers to the transformation of newly acquired knowledge or idea at idea management phase
into the establishment of new processes, practices, technologies and routines within the boundaries
of the organization with the objective to achieve innovative performance.
Collaboration is a crucial construct of innovative capabilities that refers to the positive
interaction and smooth flow of information, acquired knowledge, ideas across all the
organizational members with the intention of facilitating the knowledge sharing with the openness.
Iddris (2016) further explained that the learning forms another essential construct of innovative
capabilities that involves the process of sharing of knowledge along with the preservation of
knowledge for future reference within the organization.
Chamsuk, Fongsuwan and Takala (2017) explained the concept of innovative capabilities
as those abilities required by the group of companies, enterprises and organizations belonging to
same existing / to be an industry for the execution and effective implementation of the new idea.
The authors further explained that the innovative capabilities involve the phases of creation,
development and promotions of all the new established products, services, processes, technologies,
techniques and systems in place. The concept of innovative capabilities is further operationalized
into five dimensions that are (i) product innovative capabilities, (ii) process innovative capabilities,
(iii) service innovative capabilities, (iv) organization innovative capabilities, and (v) marketing
innovative capabilities. Product innovative capabilities as explained by Chamsuk et al. (2017)
refers to the ability of the firm to bring in the new or existing markets both the new developed new
products or services and improved existing products or services with value creation of the firm
before the competitors introduce. Process innovative capabilities as explained by Chamsuk et al.
(2017) refers to the ability of the firm execution of the newly created or improved version of the
production (product or service) and the delivery channels methods. Service innovative capabilities
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
30
as explained by the author Chamsuk et al. (2017) refers to the ability of the firm to align the
innovative activities of the firm with the organizational goals, core objectives and address the
customer’s / market’s needs with the practical institutionalization of organizational goals in
operational practices at the individual level. Organization innovative capabilities as explained by
Chamsuk et al. (2017) refers to the ability of the firm to regulate such management style within
the organization that can facilitate the innovation-based investment and creates the innovation-
based procedures and practices. Finally, the marketing innovative capabilities as explained by the
Chamsuk et al. (2017) refer to the ability of the firm to introduce effectively and successfully the
new products or services to the new and existing markets.
Chamsuk et al. (2017) further explained that the organization’s needs to focus on its
technological and research development skills that can help the organization in strengthening
innovative capabilities. They further argued that the recent researches have viewed the conception
of innovative capabilities only in the perspective of new product development however, they are
many other critical perspectives and aspects of innovative capabilities that are neglected and need
to be further studied (Chamsuk et al., 2017).
2.2.2.2. Dimensions of service innovation capabilities.
Generally, it is believed that the organization needs to identify its core internal capabilities
and then strive to strengthen them by critically reviewing these internal capabilities. Four
characteristics are necessary for the internal capabilities for the assurance of survival of the
organization in tough competitive dynamics that value, rare, inimitability and non- substitutability
(Barney, 1991). Value refers to the maximized benefits offered to customers in terms of valued
product or services (Barney, 1991). The internal capabilities are termed as valued if they result in
the output of valued product or services to customers. Internal capabilities must only be owned by
the organization itself or few other organizations and thus, non-reachable to the other market
players. If the characteristics of the rarity of internal capabilities are lost by the organization and
more organization tends to access that particular internal capability then this eventually paves the
way towards the competitive parity (Barney, 1991). Similarly, the internal capabilities possessing
the earlier both characteristics of value and rarity if and only if owned by the single / one
organization may eventually open the ways towards the competitive advantage for the parent
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
31
organization (Barney, 1991). But here lies the condition that the temporary service success could
only be sustainable by the parent company if and only if the competitors are unable to replicate
and duplicate that internal capability. The particular internal capabilities are not replaceable by any
other competitor. If the internal capabilities are value creating, rare and even perfectly inimitable
but lack the in- substitutability element then its results into the zero financial benefit. As the other
market players and competitors are able to counter the parent firm’s value-creating a strategy with
the new substitute that may be offered at lower prices thus results in zero financial earning to
parent firm. Hence it can be said that the internal resources with the value-creating strategies,
rarity, perfectly imitable and non- substitutability would help the firm in building and sustaining
the competitive advantage over the other competitors (Barney, 1991). But the organization needs
to protect these internal capabilities that possess the characteristics of these four crucial elements
of value, rarity, inimitability and non-substitutability (Barney, 1991). Because this is the only
successful way for the firm to achieve innovation success and sustain the overall business success.
However, the work of Barney (1991) carries some critical drawbacks and also received
some critiques (Priem & Butler, 2001). The theory applies to the static external environment of
the organization, however, the environment in which the organizations are operating are carrying
rapid changes with time to time with high velocity thus the theory is least applicable to a dynamic
equilibrium. Furthermore, the term resource and internal capabilities are also used interchangeably
with the lease in-depth illustration of the conception of firm capabilities (Priem & Butler, 2001).
It is also very crucial to state that the capabilities cannot be categorized as resources and possess
some differences from the resources (Amit & Schoemaker, 1993). Resources of the firms are not
something firm-specific but tradable entities while on the other hand, the capabilities are the firm-
specific that helps the firms to engage and maintain its internal resources (Amit & Schoemaker,
1993). Capabilities may also involve those implicit firm’s process that regulates and transfers the
knowledge within the organization. This fact is also widely acknowledged by other researchers as
well (Conner & Prahalad, 1996; Makadok, 2001; Barney, Wright & Ketchen, 2001; Hoopes,
Madsen & Walker, 2003).
The extent of new knowledge and capability to sense an organization possess to run its
operational activities is an essential element of innovation capabilities (Christensen, 1995). The
capabilities to sense aim to improve the understandings of the organizational events or procedures
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
32
in order to bring clarity into innovative assets and capabilities while on the other hand applying
the new knowledge aims to develop the technologies, processes and techniques to achieve value
and cutting the production costs. All the innovative capabilities associated with the organizational
and managerial innovation inclusive of the capabilities related to technological innovation
represents the process of innovative asset. It may include quality control measures, management
structure development, cultural development, etc. Aesthetic design assets is another form of
innovation capabilities that refers to the innovative capabilities of predicting, explaining and
adopting the on-going market trends (Christensen, 1995). It includes the marketing activities as
well as the interaction of marketing entities for integration of industrial designs for the expression
of artistic and on-going fashion trends in product or service. The high degree of these inter
innovative capabilities linkages results into the higher degree of innovation among the
organizations.
2.2.2.2.1. Sensing customer needs
Sensing the customer needs is a form of innovative capabilities that represents the capacity
of the organizational members to search for the new opportunities in terms of growing unfilled
customer needs and based on these needs, generate the new business idea. It would also enable the
organizational members to sustain the individual knowledge that can help them in bringing the
creativity and new mechanisms of performing assigned tasks in a productive manner (Momeni,
Nielsen and Kafash, 2015). Searching for the new opportunities especially for the organization
who are operating in dynamic market conditions serves as the biggest challenge for the human
resource of the firm (Lichenthaler, 2009). As the first step towards the innovation process, is the
exploration and search for the new external opportunities and the organization that are more good
in searching the opportunities and generating the new ideas are more stronger in their innovative
capabilities. Generation of new ideas is the execution phase of the earlier one whose output is the
new product or service offerings to the customers. A new idea can be transformed into a new
product, new service, any new technology or any new techniques of the management.
The firm acquires the new knowledge about the cost-cutting processes, new technologies and
better performance mechanisms are then acquired from the external environment. It further helps
the firm to decide to what extent the resources needs to allocate at this new idea and what are the
resources that are critical for the development of this new idea brought from the external
environment. Literature has also discussed this phenomenon as sensing new technological trends
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
33
(Den Hertog, Van der Aa, & De Jong, 2010) that basically refers to the phenomenon of exploring
the new technologies from surrounding and improving the existing technologies in light of the
acquired new information.
2.2.2.2.2. Sensing technological options
Sensing new technology and technological development is a crucial element that produces
the technology-based advantage to the firm by developing the internal technology of the
organization (Swink & Hegarty, 1998). The development of internal process and equipment can
also help the organization in customizing the existing technologies and processes as per the needs
with more efficiency and flexibility. Cross-functional product development is mostly accepted for
the creation of a new product or service. The participation of different functions of the organization
in the development of product, process and design helps the organization in bringing the
customer’s voice into the new product design and promotes the product customization thus
significantly contributes to the innovation capabilities of the firm. However, the cooperation and
collaborative attitude are the must factor for the cross-functional product development.
Capabilities to sense new technological trends contributes to the organizational goals of
achieving innovation and business success. Technological capabilities contribute to the outcome
of new product, service and technology offerings to the customer and are regarded as the most
necessary ingredient of the innovation capabilities of the firm. It paves the way to effectively utilize
the technology into the processes, procedures, techniques, mechanisms and the constituents of the
major organizational programs or events. The extent of the strengthening of the technological
capability of any firm is dependent upon the extent of financial investment and time has been
incurred by the organization for its maintenance and development. Another important aspect that
strengthens the technological capacity of the organization is the learning processes and ample use
of new knowledge for the generation of innovative activities or products.
Smith et al., (2008) also termed the sensing technology as the most crucial and essential
element of innovation capabilities as the progress of innovation process and innovation activities
are highly dependent upon the effective utilization of technology within and across the
organization. Smith et al., (2008) has further categorized the technology element into three sub-
constructs of (i) use of technology, (ii) technical skills and education, and (iii) technology strategy.
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The construct use of technology represents that to what extent the organization adapts the
technology in daily routine processes to complex issues. The construct technical skills and
education represents the abilities of human resource skills of the organization in the field of
technology. The third construct technology strategy represents the organizational stance toward
technology in strategic planning.
2.2.2.2.3. Conceptualization
Conceptualization is another form of innovation capability that contributes to the ratio of
success of any organization (Lawson & Samson, 2001). It is the ability of the organization to learn,
understand, translate and predict the value-added information and knowledge from the surrounding
competitors and markets into a new idea. Organizations effectively identify the opportunities and
threats by effectively using this innovative capability and proactively adopts the practices in light
of the changes or events occurring in the external environment. The transformation of the new
ideas into the establishment and creation of something is an essential aspect. It is argued that the
creativity serves as the foundation for the innovation that enables the organization to proficiently
gather the new knowledge and ideas, evaluate the applicability and truthfulness and further the
enhance the new ideas into profitable terms.
The new ideas may possess three forms of sources that either the new idea is created actively
or the new idea may be gathered from the existing resources or either it may be sourced from the
internal or external stakeholders of the organization (Nilsson, Regnell, Larsson & Ritzen, 2010).
This newly elicited idea forms the basis of the new project proposal being processed by the
innovative team of the organization at this phase of conceptualization. Innovation
conceptualization as explained by Smith et al., (2008) involves the process of creation, execution
and application of innovation within and across the organization. The author has further classified
this process into three sub-constructs of (i) idea generation, (ii) implementation mechanism, (iii)
selection and evaluation techniques. The author also argued that innovation is also affected by
other factors of leadership styles, employee’s behavior and usage of technology. Thus, it is
pertinent to mention that knowledge in this manner forms the basis for the decision making as the
process of gathering information and assimilating the relevant knowledge is crucial for the decision
making of an appropriate idea for conceptualization. The acquisition of right and relevant
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35
knowledge and application of this specific knowledge serves the organization with the innovative
capabilities initiatives in the right direction with the right intensity (Preez et al., 2006). The
organization possesses the appropriate technologies, strategies, culture, structures, policies,
procedures, leadership, management practices and sufficient resources to facilitate the innovative
capabilities initiatives by the organization. Thus, conceptualization plays the foundational role as
innovation requires effective and timely decision making in order to cope with the growing market
changes. Management literature further explained that the conceptualization involves the two key
phases that are thinking of ideas as a possible option and selection of the relevant idea (Sborn,
1992; Soltani, 2008). It is pertinent to mention that the searching the new opportunities and
generating the new ideas both are dependent upon the abilities and skill sets of the organizational
members. For the effective identification of external opportunities, organizations need to
strengthen the knowledge at an organizational level and upgradation of the knowledge with the
new one at the individual level is a crucial aspect for the innovation capabilities.
2.2.2.2.4. Coproducing and Orchestring
Coproducing and orchestring is another form of innovative capabilities that enable the
organization to transform the research and development findings into the new product or service
development with effective quality control and improvement in production processes with an
overall objective to fulfill the market and customer needs. Coproducing and orchestring
capabilities can be enhanced by ensuring the good vendor quality input to the production process,
strong quality control processes, effective pre-testing of new products or services, ensure an
acceptable degree of flexibility in new product, services, customer personalization (Aziati et al.,
2014). It may also enable the organization to assemble, expand and effectively utilize the essential
resources of human skills, technological and financial for the progress of innovation within the
organization. Besides technological innovation activities, any other form of organizational activity
cannot be performed without the financial aspects. Human capital is also another critical aspect of
this capability that carries, fosters and reserves the organizational activities as well as the
knowledge. It is pertinent to mention here that most of the enterprises face the major barrier of
financial strength (for example availability of funds). Thus, an organization possessing the sound
technological innovation capabilities can foster healthy coproducing and orchestring capability
within the organization.
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Coproducing and orchestring help the organization to ensure the effective utilization of
resources and anticipates the shortages (if any). It helps in maintaining the smooth flow of
knowledge and outputs to achieve the targeted higher productivity. In simple words, co-producing
and orchestring help the sensing customer needs and growing technological trends capabilities to
integrate into conceptualization and consequently combines the physical resources of a firm with
the productive human capabilities (Zawislak et al., 2012).
2.2.2.2.5. Scaling and Stretching
Scaling and stretching capabilities refers to the ability of the firm to interpret the existing
state of the technology of firm and absorb the new technology or product or service and gradually
transform the new technologies into existing operational capacities of firm with an objective to
achieve high degree of technical economic efficiency in business processes (Zawislak et al., 2012).
This forms of innovative capability enable the firm to diffuse new forms of methods, process, and
technologies into the existing organizational process, routines or technology with the objective to
stabilize new product and service to the market. These capabilities are driven by tracing the path-
dependent routines of operational activities with the integration of new technology, product or
service. It may also involve the ability of the firm to cut – down its existing marketing, logistics,
delivery, outsourcing and bargaining costs. Limited researches have also termed this capability as
transaction capability (Zawislak et al., 2012).
Summarizing, each firm acquires some specific set of knowledge that is further translated
into new technology or improved existing technology having some value for the market and thus
could be termed as the ‘firm sells the technology’. This potential technology solution is further
integrated into existing daily operational routines to ensure the production of desired new products
or services at a commercial scale and thus can be termed as ‘creates the operations’. However, the
organization ensures the effective utilization of resources and technologies for production. Still,
the problem lies, that these capabilities do not guarantee the innovation success until unless the
organization possesses the ability to cut-down the different forms of costs to ensure the competitive
position among the market players. This coordination and diffusion function by the scaling and
stretching capabilities serves as a control effort for the other innovative capabilities and could be
termed as ‘guarantees the sale’. The two innovative capabilities conceptualization and co-
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37
producing and orchestring play the most critical role in firm innovative performance. The earlier
capability is merely accountable for the creation of new products or services while the latter
capability enables the firm to produce these new products at a commercial scale. However, all the
firm needs another form of the important innovative capability to manage these two capabilities
workable in an organized manner. Thus, scaling capability is required to integrate these two
innovative capabilities and ensure effective coordination among them. But these innovative
capabilities together are not sufficient for the attainment of innovation success and business model
innovation. Organizations need to cut-down their different forms of costs in order to ensure its
leading position among the competitors and this further requires the set of knowledge and abilities.
2.2.2.3. Innovation capabilities sub-construct needs to be validated. (Chamsuk et al.,
2017; Narcizo et al., 2017)
Different researchers have conducted detailed researches on the concept of firm innovative
capabilities in different perspectives of human resource management, distinctive competencies,
human skills, absorptive capacity, organizational capabilities, dynamic capabilities, technological
capabilities, marketing capabilities, etc. There are also some researches who have addressed the
conceptualization of innovative capabilities (Zawislak et al., 2012; Yam et al., 2011; Nisula &
Kianto, 2013; Momeini et al., 2015; Story et al., 2017; Iddris, 2016; Chamsuk et al., 2017).
However, the previous researches have emphasized one or a few specific dimensions of innovative
capabilities such as research and development, new product development, etc (Nisula & Kianto,
2013; Chamsuk et al., 2017). This serves as a gap that there is a need to examine the different
forms of capabilities. In addition, the recent researches have viewed the conception of innovative
capabilities only in the perspective of new product development however, they are many other
critical perspectives and aspects of innovative capabilities that are neglected such as process
development, marketing capabilities, behavioral aspects etc. that needs to be further studied
(Chamsuk et al., 2017)
Narcizo et al., (2017) conducted a bibliometric literature study on the conception of
innovation capabilities and found that the existing literature pertains the nineteen (19) different
conceptual definitions and explanation of innovation capability concept. This concludes that the
researches on the conceptualization of innovation capability carry the variability in explaining the
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38
phenomenon itself (Narcizo et al., 2017). Thus, there is a need to bring some coherence in
conceptualization through validation research studies.
Concluding, it is not incorrect to state that still there is a need to further explore the
conception of innovation capabilities as there is no such agreement in existing literature on what
are those factors that determine the innovative capabilities for the attainment and assurance of
service innovation (Zawislak et al., 2012; Nisula & Kianto, 2013; Narcizo et al., 2017). This arises
the need to validate the concept of innovation capabilities. Furthermore, the existing literature does
not also pertain the general consensus on the particular definition of the concept of firm’s
innovative capabilities and there is further need to clarify the concept of firm innovative
capabilities by developing some comprehensive framework (Zawislak et al., 2012; Breznik &
Hisrich, 2014). This points towards the research gap in present literature body.
Thus, this research work has attempted to address this research gap (indicated by Zawislak
et al., 2012; Breznik & Hisrich, 2014; Nisula & Kianto, 2013; Narcizo et al., 2017; Chamsuk et
al., 2017) by reviewing and validating the research construct of innovative capabilities. This
research work has adopted the research instrument of Den Hertog, Van der Aa, and De Jong
(2010). It is pertinent to mention that some of the researchers have already validated this research
instrument in different countries of the globe. However, negligible or no research study has been
conducted to validate this research instrument for the operationalization of innovation capabilities
in the Pakistani’s cultural settings. Consequently, this study contributes to body of knowledge by
extending existing research chain on validation to bring coherence in the definition of innovation
capabilities. Thus, attempting to contribute to closing this identified research gap. The detailed
operationalization and definitions of measures of innovation capabilities are discussed in the
consequent chapter.
2.2.3. Service Innovation Success (Mediating Variable).
The concept of service innovation success became evident and opaque with the passage of
time that it involves the phenomenon in which the renewal is achieved in provided services
(Toivonen & Tuominen, 2006). However, different stakeholders of the organization are involved
in the process of service concept design, service delivery channels and service launch, thus the
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39
concept of service innovation is a combination of different elements and stages of new service
offering with a final objective of achieving the customer satisfaction and fulfilling the customer
need in more valuable and profitable manner (Preissel, 2000).
The idea of service innovation has merely evolved by Miles (1993) who has coined the
term service innovation first time in literature. In his research article published in journal namely
“Futures” the author has very deeply illustrated the numerous characteristics of services and in a
step forward, deeply explained the linkage of these characteristics or features of services with the
different forms of innovations. The objective was to illustrate the barriers and arising problems
associated with the service characteristics and make the phenomenon understandable and opaque
for the resolution of the contemporary service innovation-related issues. Miles (1993) has
classified these features of services in four broader terms that are (a) features of services in terms
of service production, (b) features of services in terms of service product, (c) features of services
in terms of services consumption and (d) features of services in terms of services markets. Features
of services associated with the service production basically refer to the five interconnected and
interdependent characteristics of services that pave the way for the enhanced service innovation
success within the organization or enterprise. The second service feature of labor involves the
professionalized skills highly equipped with the interpersonal skills and specialist knowledge are
required but the services have reduced the greater dependence on the expensive labor skills due to
the usage of expert systems and telecommunication. Features of services that are associated with
the service product basically refer to the nature of the product and features of the product. The
nature of the product involves the services processes or services product that are hard to distinguish
and difficult to store or transportation. It involves the material components such as the
membership’s cards, however, telecommunication or electronic channels are used for the purpose
of the order placement, reservations or delivery information. On the other hand, the features of the
product involve those characteristics of services that are customized and personalized as per the
laid down requirements of the end-user. Internets or other electronic protocols are used for the
input of the customer requirement and the other expert systems or software are used by the
organization or enterprise for the storage of customer’s records (i.e. likings, requirements, etc.).
Features of services that are associated with the consumption of the service basically refer to the
delivery of the product, the role of consumer and organization of consumption. Delivery of product
involves the particulars of distribution and consumption with the aspects of time and space. The
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40
role of the consumer is crucial for the success of services as the consumer needs or demands
information serves as the input for the design and production of services. The organization of
consumption is somewhat difficult to separate from the production in services. Self-service is
another formal official economies that are found common at some places however technology and
user-friendly software are also services consumption modes fashionable. Features of services that
are associated with the services markets basically refer to the organizations of markets, regulations,
and marketing. Organizations of markets involve the provision of services delivered to end-users
either in governmental bureaucratic sectors or retails sectors. However, now the quasi-markets are
also delivering the services through the privatization or outsourcing of services. Electronic point
of sales and new reservation systems are all growing technological trends of markets organizations.
Regulations are quite common in services either regulated by national bodies or foreign
conventions. Performance indicators and monitoring of laid down basic requirements are made by
the regulating bodies and institutions. Marketing in services involves the guarantees and the
demonstration packages involved for the promotion and placement of services in the market among
the rivals.
A critical review of existing literature reveals that the conception of innovation success is
viewed in three different perspectives in the present literature. The first perspective of this concept
endures the ‘innovation success in services products’ that is new, improved and novel services
may be offered to the customers (Hertog, 2000; Johne and Storey, 1998; Nijssen et al., 2006; Smith
et al., 2007; Menor & Roth, 2007; Storey & Hull, 2010). This perspective of service innovation
success upholds the majority of service development strands of innovation in existing literature
(Johne and Storey, 1998; Nijssen et al., 2006). This perspective of service innovation success is
also contrasted with the concept of technological innovation in literature as the latter one defines
the success of innovation in products. Thus, the literature explains that the innovation in the
product is quite different and distinguishable from innovation in services and therefore the service
innovation needs to be studied as a separate concept (Miles, 1993). Present literature on innovation
pertains to the second perspective of conception on ‘innovation in service processes’ that states
the service innovation as the new, improved and novel way of designing, making, producing and
delivering the service processes. This perspective of service innovation upholds the numerous
researches on the strands of new service delivery mechanisms in the literature (Araujo & Spring,
2006; Chen, Tsou & Huang, 2009; Lenfle & Midler, 2009). The third perspective views the service
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41
innovation concept as ‘innovation in service firms, organizations, industries’ in existing theories.
But, the review of the literature has revealed that most of the previous researches on innovation
generally addresses the concept of technological innovation in manufacturing firms and the
concept of service innovation is relatively newer one that is less explored (Toivonen & Tuominen;
2009). However, it is very crucial to state that the concept of service innovation success is serving
as a central driver to economic growth in many developing nations (Toivonen & Tuominen, 2009;
Gallouj & Windrum, 2009). Recent digitization and incorporation of ever-changing technological
advancement in business processes of service industries have revealed that the service innovation
requires more research in the present area (Ostrom, Bitner, Brown, Burkhard, Goul, Smith-
Daniels, Rabinovich, 2010).
Furseth and Cuthberton (2013) explained the service innovation success as the service
innovation triangle that consists of a value, business model, customer experiences, service system,
technology, key internal resources, and strategic capacity. Den Hertog, Van der Aa, and De Jong
(2010) explained that service innovation success consists of, (i) service concept innovation, (ii)
new customer interaction, (iii) set of business partners and new value system, (iv) new revenue
model, (v) new delivery system, (vi) new service delivery system (that is technological). Flikkema,
Jansen, and Sluis (2007) have also defined the concept of service innovation as the
multidisciplinary process of designing, testing, launching and marketing the new services with the
ultimate effort to establish the valuable customer experience.
Edvardsson (1997) has defined the service innovation success as the combination of two
mandatory aspects that are an in-depth understanding of what customers have needed and what
could be the different ways in which the design of the new services may wholly fulfill the needs
of the customer with higher satisfaction. However, there are other factors that may not be
neglected. It may include the customer’s needs of preference (i.e. some demanding needs of the
customer are primary and others are secondary and there is a need to prioritize these need levels
accordingly etc.), and any other associated support services. Consequently, this in-depth
understanding of the service concept may eventually describe the actual value of the services
offered in terms of the success of service innovation.
However, service innovation does not occur as a single activity rather it’s a combination
of a series of activities taking place either in a mutual or sequential manner (Edvardsson, 1997).
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42
The services either new or unique are not solely created or developed by the organization but they
are partly co-created by the suppliers that do not fall under the direct control of the organization
itself. However, an organization can set basic parameters and requirements for the suppliers to be
eligible for the success of innovative services co-creation. That is how an organization can
effectively control service innovation success. Three basic aspects of the organization’s service
innovation success are (i) define quality requirements, (ii) understand internal customer’s
expectations, and (iii) understand end customer’s expectations.
Toivonen, Tuaminen and Brax’s (2007) envision the service innovation success as the
value proposition of service innovation. The authors explained that most of the service firms in
today’s world have used the rapid application model of the service innovation process. It can be
used because of the rapid application model of service innovation outcomes the urgent delivery of
service offerings. As the present competitive dynamics of markets call for the urgent need of
service launch so it also provides the opportunity to further develop the service offering in support
of customers or clients along with the existing ongoing operations of the organization to ensure
service innovation success. Furthermore, the development of the new service offering goes parallel
with the service testing or launch by answering the raised queries or issues of the real markets. In
addition, rapid application innovation processes require small investments for the testing and
execution and thus, the risk for economic loss may be minimal with greater chances of service
success.
Furseth and Cuthbertson (2013) explained the service innovation success as the summation
of all the interactions between the service organization and the customer for the offer and delivery
of the services took place. Although the service firms pursuit to deliver all its customers with the
same and equal level of satisfaction and pleasure from an organizational point of view, however,
it varies at customers' end in light of their desires and differentiating personalities. Thus, it is not
incorrect to state that the major part of the concept of service innovation success revolves around
the notion of commercializing the service offerings in a manner that may establish the value not
only for the customers only but the owner of the service firms and the suppliers. Furseth and
Cuthbertson (2013) have defined the value as the custodian of the societal, environmental,
economic and emotional aspects of the services however this description cannot be termed as
universal as the definition of value differs among the different service organizations. Some service
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43
organizations may describe it in terms of financial profit or market share while the other may
regard it as the outcome of firm-specific targets. Thus, numerous researches have illustrated the
concept of innovation success specifically in the realm of small and medium enterprises. The
existing literature on service innovation success is dominated by the research studies that are
illustrating the dimensions for service innovation success. This research work has adopted the Riel,
Lemmink, and Ouwersloot (2004) operationalization of service innovation success and measured
the construct with three dimensions. Details on operational definitions and measures of the
constructed service innovation success are discussed in the next chapter.
2.2.4. Employee Resistance to Change (Moderating Variable - 1)
Resistance by employees is considered as one of the basic underlying reason for the
deterioration in the implementation of new initiatives within the organization. Organizational
changes met with failure at first instance due to the resistance of organizational members (Egan &
Fjermestad, 2005). Resistance is a sort of organizational disease that keeps on spreading
(increases) with the passage of time and serves as a barrier for the innovation which an innovative
organization needs to find ways to imitate. Zander (1950) defined the resistance as the behaviors
of organizational members that are directed to protect and preserve themselves from the planned
change. Folger and Skarlicki (1999) explained the resistance as the behavior of seeking challenges,
disruption, invert prevailing planned change assumptions and power relations by the
organizational member. Ashforth and Mael (1998) explained the resistance as the intentional acts
of disobedience and non-cooperation by the organizational members. Brower and Abalofia (1995)
explained the resistance as the intention and act of opposition against the change or responding
passively to change activities.
In fact, the existing literature on the concept, operationalization, and dimensions of
employee resistance to change are well established. The literature also clarifies that there exists a
distinction in causes and the symptoms of employee resistance and managers need to address the
reasons for resistance, not the symptoms (Lewin, 1951; Zander, 1950). A number of researches
have explained and listed the factors that cause the employee resistance to change. Zander (1950)
explained that there are six main reasons due to which resistance to change emerges by the
organizational members, (i) ambiguity in the minds of organizational members who perceives that
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
44
the change initiatives will coarsely affect them, (ii) carrying and interpreting the change initiative
in diverse and negative manner, (iii) the presence of other strong forces that convinces the
organizational member to oppose the change initiatives, (iv) lack of employee involvement or
participation and the autocratic imposition of change activities by the top management, (v)
resistance due to personal interests of the organizational members, and (vi) lastly, inbuilt ignorance
of organizational members relating the pre-established institution or structures.
Some researchers have also indicated that the ignorance of the skills, abilities of the
organizational members also serves as the cause for them to resist (Hoffman, Festinger &
Lawrence, 1954). The resistance to change emerges and further heightens because the managers
who execute the novel activities misunderstood their employees and the situation of the
organization (Flower, 1962). In the opinion of these managers, implementing the novel changes
and innovation is simple as moving from one position to another. They fail to identify how the
other organizational members will conceive when the novel changes would be implemented.
Lackness in communicating the clarity of the necessity of change is a baseline cause for the
resistance that is self-trouble by the managers who strive for the implementation of novel changes
(Flower, 1962). Resultantly, the members of the organization perceive these implementations as a
threat that can harm their social status at the workplace. The rewards systems and other systems to
acknowledge or recognize the employees are also critical as they determine the behavior of the
employees thus consequents to the innovative or non-innovative aptitude among the human skills
of the organization.
There could be other factors like the personal interests of the individual that fosters them to
deviate the implementation of novel changes. Generally, the managers strive to bring change in
the existing status quo of organization with the foundational goal of profit maximization and
safeguarding organizational survival. The organizational change may be either for the cost
minimization, service quality standards, innovation adoption, increased productivity or process
product developments. It all requires the organization to merely become self-centered. However,
the members of the organization also pursue some personal interests. The organizational pursuit
for the change approach may be in clash with the personal interests or goals of the organizational
members. This prospective conflict between the interests of the organizational members and the
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
45
interests of the organization is widely considered as the heart of management sciences (Barnard,
1938). Different established theories also advocate these diverging interests between the
organizational owners and the employees (Mitnick, 1982). The literature theorizes that the
organization pursues the interests of maximizing the profits by cutting the organizational expenses
either through paying less while on the other hand employees are more interested in less work with
more pay or wages. This heightens the conflict among the owner and employee. The employee’s
stance of opposition to the organizational viewpoint is termed as resistance (Keen, 1981). Strebel
(1996) also advocated that the owners and members of the organization both pursue the give-and-
take obligations and commitment with each other and this give-and-take obligation between the
two, further shapes their behaviors and relationship. Implementation of any novel idea that detritus
the personal compacts of the organizational members would necessarily be resisted by the
members (Strebel, 1996).
Literature also identifies the psychological aspects of the individuals as a reason for the
resistance to implied novel changes (Dent & Goldberg, 1999; Kegan & Lahey, 2001; Oreg, 2003;
Coch & French, 1948). Some researches explained that resistance is a product of context in which
the novel changes are going to take place and the behavior of individuals or groups (Dent &
Goldberg, 1999; Lewin, 1951). Thus, imposing novel changes may not be fruitful until and unless
the factors of organizational context may be molded as per the desired requirements (Dent &
Goldberg, 1999; Lewin, 1951). Expectations of employees versus the expectations of the
employers basically refer to these factors of organizational context (Rousseau, 1995). The
employees expect facilitative and valued pays, rewards, developmental opportunities, career
growth paths, etc. from their organizations. While on the other hand, the employers expect that the
employees may behave more proprietor towards the organizational goals, work efforts,
commitment and responsibility, etc. The stability prevails within the organization until the time
the expectation from both sides stays compatible. But, when such novel changes are introduced
that may imbalance the factor of the employee’s expectation to lower scale (in contrast to
employer’s expectation), it paves way for the resistance (Rousseau, 1995).
Besides the factors of organizational context and participative role of employees as
tempering towards the resistance level, the psychological disposition of the organizational
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46
members is influentially accepted as the contributing element of resistance to change (Oreg, 2003,
2006, 2008, 2011; Burnes, 2014). In recent researches in this field, the individual is termed as the
main source of resistance in comparison to the organizational factors (Oreg, 2003, 2006, 2008;
Oreg & Sverdlik, 2011; Burnes, 2014). An organization possesses the individuals with varying
degrees of psychological disposition of acceptance or rejection towards the novel changes (Oreg,
2003). The members who possess a higher level of psychological disposition mainly holds the
negative or opposing approach towards the novel changes. While on the other hand, the members
who possess the lower level of psychological disposition are of those who accept the change or
engages themselves in novel changes with the passage of time (Oreg, 2003). This level of
psychological disposition is measured by the four personality attributes of routine seeking
behavior, cognitive rigidity, the emotional reaction towards the implanted changes and the short
term focus of the individual (Oreg, 2003). The researchers also agreed that the individuals who are
close-minded, rigid in nature prove to be less willing to introduced new ideas, situations, things or
events (Fox, 1999; Lau & Woodman, 1995; Oreg, 2003). This close-mindedness and rigid behavior
shape the cognitive rigidity of individuals (Oreg, 2003).
A past extensive literature has been reviewed on the concept and established
operationalization of employee resistance to change. This research work has adopted the Oreg
(2003) operationalization of employee resistance because of its consistency in development and
widely validation by different researchers in different contexts have made it as one of influential
research measure of existing literature. The construct employee resistance to change has been
operationalized into five sub-constructs of routine seeking, emotional reaction, short term thinking
and cognitive rigidity (Oreg, 2003). Details on operational definitions and measures of the
construct employee resistance to change are discussed in the next chapter.
2.2.5. Management Entrepreneurial Orientation (Moderating Variable - 2).
The concept of ‘Entrepreneurial orientation’ belongs to the field of strategic
entrepreneurship and being considered as a form of strategic orientation in the existing body of
knowledge that involves the entrepreneurial aspects of an organization’s strategic planning
(Wiklund & Shepherd, 2005). Entrepreneurship is a distinctive characteristic that distinguishes the
traditional manager and employees from the entrepreneurs. Entrepreneurs are those members of
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47
the organization that are always in continuous search for innovative and proactive activities (Choo
& Lee, 2018). However, the traditional managers, employees and other members of the
organization slightly or larger possess the tendency to avoid risk-taking entrepreneurial actions
(Choo & Lee, 2018). Thus, the literature evidence that the continuous search for new business
opportunities and creating those opportunities into new values for growth as well as for the
customer are the real facet of entrepreneurial members of the organization (Brockhaus, 1980;
McClelland, 1961).
The review of existing literature on entrepreneurial orientation reveals that recently this
concept has become one of the promising area of research in entrepreneurship and strategic
management literature (Wales, 2016; Campos, 2018). The recent researches illuminate the concept
of an entrepreneurial orientation as a necessary condition for the organizations that desire to sustain
in competitive market environments (Choo & Lee, 2018; Campos, 2018). The concept was
recognized in early researches by Mintzberg (1973) as an entrepreneurial aspect of strategy
creating an approach of the organization. However, the concept gained more attention from the
work of Miller and Friesen (1982) who termed the phenomenon as an “entrepreneurial model”.
Originally, the concept of entrepreneurial orientation implies the organizations that continuously
strive to innovate aggressively by taking risks in their product and marketing strategies (Miller &
Friesen, 1982). Later on, the concept was properly operationalized into three essential dimensions
of innovation, risk-taking, and proactiveness (Miller, 1983). Miller’s conceptualization of
entrepreneurial orientation by any organization requires the emphasis on these three sets of
dimensions. However, Miller’s (1983) dimensional based conceptualization of entrepreneurial
orientation pertains to some lacking. The three dimensions of entrepreneurial orientation may need
to covary in order to be the foundational parameter of entrepreneurial orientation. The absence of
covariance among the three sub-constructs may not claim the constituent of an entrepreneurial
orientation as conceptualized by Miller’s work (Covin & Wales, 2012).
Lumpkin and Dess (1996) further addition the two dimensions of autonomy and
competitive aggressiveness in the previous three-dimensional conceptualization of entrepreneurial
orientation. However, the Lumpkin and Dess (1996) illustration of entrepreneurial orientation was
based on the clarification of Miller’s work lacking. It states that the entrepreneurial orientation
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48
does not require the complete set of these five dimensions as a whole. Rather it was suggested that
the dimensions do not strongly require to covary strongly or positively with each other in order to
claim the presence of entrepreneurial orientation. This illustration of entrepreneurial orientation
by Lumpkin and Dess (1996) was somewhat of a typical latent construct type that explains the
concept of being entrepreneurial. However, the specific context of these five-dimensional views
as explaining the construct itself was not covered by this research.
However, it has been long believed in the existing literature that taking the risks in gripping
the new business opportunities and proving to be innovative are the essential parameters of the
organization to sustain its survival in competitive market dynamics. It has also been believed that
the individuals who carry the challenging goals and seeks for the challenging tasks (within an
organization) may pursue the characteristics of an entrepreneur (McCllelland, 1961). This is
evident from these earlier conceptualizations of entrepreneurial orientation by different
researchers. Zahra and Neubaum (1998) defined the concept of entrepreneurial orientation as the
collective output of an organization’s radical innovation, risk-taking activities and proactive
approach in strategic activities of the organization that is carried in the sustenance of existing
riskier projects. Covin and Slevin (1989) explained that those organizations can be regarded to
possess the entrepreneurial orientation whose middle and top managers carry the entrepreneurial
traits and entrepreneurial style in decision-making processes. Voss, Voss, and Moorman (2005)
defined the entrepreneurial orientation as an organizational level proposition to engage its
employees in risk-taking, proactive, innovative, competitive aggressiveness and autonomy related
behaviors that trigger the change within the organization as per the external environment. Avlonitis
and Salavou (2007) defined entrepreneurial orientation as an integral phenomenon through which
an organization embarks the proactive and innovative activities to achieve a better competitive
position among its rivals. Cools and Boreck (2008) explained the entrepreneurial orientation as the
strategy of the top management of the organization relating to the innovativeness, proactiveness
and risk-taking initiatives. Pearce, Fritz, and Davis (2010) defined entrepreneurial orientation as
the set of distinctive interrelated behaviors that constitutes the initiatives of proactiveness, risk-
taking, autonomy, competitive aggressiveness and innovativeness. Rauch (2009) defined
entrepreneurial orientation as the strategy creation process that enables the organization in
achieving competitive advantage and sustaining its vision in the longer run through an
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49
entrepreneurial manner. In essence, the entrepreneurial orientation elucidates the practices of
entrepreneurship in the strategic stance of the organization in carrying its existing businesses. The
conceptualization of entrepreneurial orientation laid down by Covin and Miles (1999) was found
to be the predominant one. However, Covin and Wales (2012) argued that future researchers can
opt unidimensional or multidimensional construct of entrepreneurial orientation in light of the best
reflection of measures as per their study dynamics. Covin and Wales (2012) conducted a detailed
systematic study on the conceptualization of entrepreneurial orientation in a challenging
perspective. They concluded that the measurement of entrepreneurial orientation should be
grounded from the theoretical perspective of the research. Similarly, Anderson et al., (2015)
studied the construct of an entrepreneurial orientation as the combination of two entrepreneurial
behaviors of management (that are proactiveness and innovativeness) with the manager’s stance
of favoring the risk-taking behavior in strategic decision-making phenomenon. This
conceptualization of entrepreneurial orientation was also in line with the conceptualization by
Covin and Miles (1999) illustration.
Ready to innovate is entitled to be the prime component of entrepreneurial orientation by
the existing literature. It is believed that the absence of ready to innovate consequents to the
negligible extent of entrepreneurial orientation in organizations even rest of all determinants
functions to their peaks (Morris et al., 2011). Lumpkin and Dess (1996) explained the concept of
ready to innovate as the willingness of the organization to carry new ideas and exploit these new
ideas through experimentation in a more creative manner. Ready to innovate is the most researched
and studied determined of entrepreneurial orientation (Parkman et al., 2012). It flourishes at all
levels of the organization including individual, team or group, organizational and inter-
organizational levels (Ireland et al., 2006).
It is argued that ready to innovate is a force between the two foundational functions of
corporate entrepreneurship that are business venturing and the most important strategic renewal
(Yildiz, 2014). Proctor (2014) has defined the ready to innovate as the practical implementation
of the new ideas, concepts, and discoveries into profitable product or services. The phenomenon
of ready to innovate originates with the stage of proposal drafting or formation, further moving to
the development of the basic generated idea and ends with commercially exploiting the developed
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50
idea in form of some marketable product or service (Tonnessen, 2005). Freeman and Soete (1997)
defined the ready to innovate as the accomplishment of an organization in successfully conducting
the first transaction of their newly produced product, service offer or any process from the newly
generated idea. Thus, the number of explanations on the conception of ready to innovate are
researched in the literature of entrepreneurial orientation. It was revealed that all these conceptions
carry the same explanation that the ready to innovate is a phenomenon that possesses some
processes from the origination of an idea to outcome in the shape of product or service or systems.
It also revealed that the output of this sub construct ready to innovate involves the launch of end-
product in the market to add value to the organization as well as the customer.
Competitive aggressiveness refers to the organization’s tendency to challenge its rivals
intensively being the new entrant to market or with the improvement in its competitive position
(Lumpkin & Dess, 1996). However, the rigorous act of challenging the rivals necessarily requires
the organization to pursue some unconventional strategies instead of traditional conventional
tactics. This may also require the organization to behave proactive and reactive towards the moves
of their competitors (Stambaugh et al., 2011). Chen et al., (2006) explained that the competitive
aggressive is an ability of an organization to perform more effective and healthier, with more
strong offensive position holder and being the aggressive market entrant dominant by others in
contrast to its rivals. Chen et al., (2006) further explained that the extent of competitive
aggressiveness of an organization may be reflected by the degree of its responsiveness in a manner
that how the organization immediately defends itself if the rivals lower its product or service prices.
However, some of the researches have also argued that the merger and joint business ventures also
prove to be effective in increasing the competitive aggressiveness of organization (Harrison et al.,
1991; King et al., 2004). It may happen due to the synergy effect of the business venture with
higher profit returns.
Besides the competitive aggressiveness, the ability to work independently by taking actions
and decisions with more empowerment and delegation are also essential for the organization to
regulate entrepreneurial orientation. Autonomy refers to the extent of freedom and openness
provided to employees to experiment with the new ideas and creative techniques to promote
entrepreneurship orientation within the organization (Lumpkin & Dess, 1999). It is also generally
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51
believed that when the top and middle management authorizes the functional and line managers
with some autonomy, the resultantly the extent of innovation increases within the organization
(Janssen et al., 2015; Ireland et al., 2006). The organizations providing their employees with
sufficient autonomy consequently flourishes the innovative culture within an organization where
the individuals are free to share and experience new ideas and opportunities. The individual and
team efforts to pursue the new market opportunities may lead the organization to be the new
entrant. The new ideas and opportunities based concepts generated or developed by the individuals
or team members are communicated to middle managers for the decision making (Hart, 1992).
Thus, autonomy promotes creativity and innovation within the organization that is also dependent
upon the personal attributes of the individuals (Eder, 2007).
Risk-taking results from the autonomy and self-employment decisions is also an essential
element of entrepreneurial orientation. Organizational risks are the outcome of experimenting the
creative ideas and innovation. Risk-taking refers to the organization performing an act that is
considered suspicious and uncertain to the profitable outcomes with the tentative probability of
failure and loss (Wiklund & Shepherd, 2008). These uncertain actions by the organization may
include the decision to venture into uncertain or new markets, huge lending from markets or
investing in those business ventures whose outcomes are doubtful (Baker & Sinkula, 2009). It can
be argued that risk-taking involves those strategic acts by organizations that require heavy
investment either in terms of human or financial capital but carries a higher propensity of failure
(Eggers & Kaplan 2013). The outcome of risk-taking may be either success (positive) or failure
(negative in nature). Although risk-taking flourishes and enhances the innovation within the
organization, however, it is not necessarily that the outcome of risk-taking always is positive in
nature. It is something that is influenced by the past experiences of the organization in parallel
with the ability to frame the propensity of risk propositions (Lumpkin & Dess, 1996). Calculating
the risk is essential for the organization rather than playing gamble with uncertain outcomes.
Because the organizations that avoid uncertainties with less inclination towards the new
opportunities always stay far behind from the innovation and consequently the strong competitive
positing in markets (Nishimura, 2015).
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Past extensive literature has been reviewed on the conception and established theories of
management entrepreneurial orientation. This research work has adopted the Wang (2008)
conceptualization of entrepreneurial orientation by operationalizing the construct into essential
sub-constructs of ready to innovate, competitive aggressiveness, risk-taking and proactiveness.
Details on operational definitions and measures of the construct management entrepreneurial
orientation are discussed in consequents section.
2.3. Proposed Association of Study Variables
2.3.1. Association of Innovation Capabilities and Business Model Innovation (Gap-2).
Majority of organizations who are striving in a complex market dynamics are thought to
continuously oblige to address growing industry demands (Teece, 2012). However, the
organization ability to identify, learn, integrate and reconfigure its internal competencies,
capabilities and resource base is essential to cope with this changing nature of external market
dynamics. The resources of an organization that are difficult to reproduce and imitate by the
competitors firm, if used in value generation for the customers ultimately bring the innovation in
the organization (Weking, Lupberger, Hermes, Hein, Böhm, & Krcmar, 2020). This dynamic
capabilities perspective stresses on renewing the existing capabilities of the organization along
with the generation of new organizational capabilities in order to achieve competitive advantage
(Weking et al., 2020).
This determines that the capabilities of an organization are the prerequisite for the efficient
and speedy realignment of existing resources of the organization to meet the needs of the customer
and the market. These innovative capabilities such as sensing and seizing are required to design
and implement the new business models with an objective to meet the growing needs of new
markets (Hock-Doepgen, Clauss, Kraus, & Cheng, 2020). Continuously sensing and seizing the
external opportunities and periodically integrating them into the internal facets of the organization,
may ultimately enable the organization to proactively guard against the new threats as they arise
(Hock et al., 2020). Furthermore, seizing the external opportunities from the growing market also
requires the capabilities of the organization for the generation of sustainable advantage over the
rivals (Teece, 2012). However, the organization can only achieve this objective, if it proves to be
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53
keen toward the capabilities that allows them in the realignment of resources towards the service
innovation success (Siebold, 2020). The speed and extent of effectively utilizing the resources in
pursuance of customer needs and wants would yield the extent of success of these capabilities. It
is crucial to discuss here that the innovation capabilities of the organization are multi-facet. It is
essential to discuss that all the organization may not essentially strengthen enough in every factor
of innovation capabilities. Those who are stronger in sensing and coproducing, may not be strong
enough in scaling and stretching capabilities. This may vary among different organizations in
different contexts. There may also be a chance that the organization who are stronger in forming
the new business model, may proves to be flimsy in implementation skills. Consequently, it could
be said that firms carry the stronger innovative capabilities in contrast to its competitors, if it is
more stronger in all elements. These are the organizations that may bring novelty in their existing
business model (Hock et al., 2020). Teece (2018) discussed that business models and dynamic
capabilities are two interdependent concepts of management. Theoretically, the role of capabilities
as the driver of business model innovation can be understood and explained. However, there is a
need to further testify this association through empirical analysis in order to getter better
understandings of the phenomenon. Scheinder and Speith (2014) also argued that there is a need
to explore how an organization identifies its relevant external opportunities in terms of
capabilities? And does these capabilities emphases the business model innovation within the
organization? Some of the recent researches also posed a challenging research question for future
researches that states, what is the role of innovation capabilities of the organization as an internal
driver of business model innovation? That needs to be empirically investigated (Saebi et al., 2017;
Teece, 2008; Speith & Messner, 2019). Thus, the influence of innovation capabilities in
determining business model innovation needs to be explored in light of these researches (Teece,
2018; Scheinder & Speith, 2014; Foss & Saebi, 2018, Speith & Messner, 2019; Saebi et al., 2017).
Based on the discussions above paras and the gap identified from the review of the literature, the
following research hypotheses are developed as,
H1: Innovation capabilities may possess positive influence on business model innovation.
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54
Scheinder and Speith (2014), Foss and Saeibi (2018, 2017) and Teece (2018) comprehend
the need to testify the proposed relationship of innovation capabilities and business model
innovation. The empirical testing of this hypothesis contributes to the existing literature body by
closing this research gap.
2.3.2. Relationship of Innovation Capabilities and Service Innovation Success.
The strength of innovation capabilities of the organization basically determines the speed
and extent of synchronizing the organization resources to deliver value to the customers by
fulfilling their unmet needs and wants (Helfat & Martin, 2015). Achieving the success of
innovation is a challenging task for the organizations especially for the service organizations. It is
also self-evident in existing literature body of entrepreneurship and strategic management
disciplines that the outcome of the innovation (innovation success) is a foundational means for the
organization to enhance and sustain its customer base (Kiel et al., 2017). The existing literature
generally believes that the organization who are capable enough to assess and actively responds
the growing market or customer needs, such organizations are more likely to be the first entrant
with the generation of new service or new changes in existing product or services (Arnold et al.,
2016). This indicates that the organization requires some of the capabilities to identify the customer
needs, assessing technological trends, available technological options and conceptualizing the new
product or services in combination with these capabilities and customer or market growing needs.
It represents the magnificent skill of science and analysis by the organization to script the success
story of new innovative service (Teece, 2014; Helfat & Martin, 2015). It basically requires the
innovative capabilities of the organization to fully explore the external opportunities of potential
innovative service and its consequential outcome to the external environment of the organization.
Literature has also evidences that the role of innovation capabilities in predicting the extent
of innovation success is also dependent upon the extent of the new opportunities explored either
through the use of experimentation or research etc. Service success is dependent upon the
information about the recent trends and growing market needs. It may be obvious as previous
mainstream literature agrees with the fact that the organization necessarily requires the
development and re-work on the innovation capabilities to generate more economic as well as
societal value (Zack, McKeen & Singh, 2009; Kogut & Zander, 1992).
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55
The organization pursuing the success of new innovative services needs to develop and
sustain its capabilities to cater for its short term survival and long term growth of services (Lee et
al., 2018; He & Wong, 2004). The organizations that manage the information relating external
environment and market needs may be competent enough to develop the new innovative ideas into
the new innovative services through effectively utilizing its resource base and capabilities.
Similarly, the organization fails to manage and promote these aspects of the external environment
may render in week new service outcome. The literature also supports the fact that the success of
the organization operating in dynamic or stable environment involves the identification of
technological available options and growing trends while on the other hand survival in such
environments requires the continuous development of new competencies through effective
utilization of innovation capabilities (Gonzalez et al., 2018). However, the alignment and
coherence of these innovation capabilities are mutually desirable in order to understand the extent
of innovation success consequentially achieve. The existing literature also states that the
innovation capabilities may possess some influence on the performance indicator of innovation
may need to be studied (Teece, 2018; Gonzalez et al., 2018). As it is essential to understand that
to what extent the innovative success enhances by improving the same differentiation of novel and
efficiency centered innovation capabilities. Based on the above discussion, the research hypothesis
2 has been established as;
H2: Innovation capabilities may possess a positive influence on service innovation success.
2.3.3. Relationship of Service Innovation Success and Business Model Innovation.
Existing concept of blue ocean strategy advocates that the high competition shifts the
organization's foci and energies towards the competitor’s moves rather than customer demands.
The competition in the overcrowded market does not guarantee organizations with higher
productivity (Kim Mauborgne, 2004). Exploring the quests with new ways of doing things opens
up the saturated market with the new ocean to quest (Kim Mauborgne, 2004). Thus, innovation
creates a new market space and creating value in business for the customers.
The existing body of literature has defined innovation success as dimensional variable that
refers both the process and consequential aspects (Menor, Tatikonda & Sampson, 2002). The
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56
majority portion of service innovation literature has emphasized on the performance of innovation
from competitive lens. However, there also exists limited research studies who have focused the
financial performance as central theme in relation to this newly evolved construct (Gima, 2003;
Froehle, Roth, Chase & Voss, 2000). It highlights that more researches are required to testify the
innovation success from performance parameters. In order to achieve this goal, this work has taken
this construct as determinant of success i.e short term, long term and indirect nature. It is pertinent
to state that the success of new service settles on its path when the new service offerings are aligned
with the customer needs in such a way that company earns an ongoing stream of revenues from it.
However, pioneering a new service is not always a path for continuous financial benefit. Being the
first in service offering resultantly educates the customer about the new value propositions. This
paves the way for the rivals to enter with more substitute features or characteristics of service, with
the potential threat to pioneer organization. In this way, the competitive position, commercial
success, service reputation and level of customer satisfaction towards the pioneer service are
critical for the long term success of the pioneer service offerings.
It has also been found in existing literature that successful service innovation requires the
effective and timely decision making in order to cope the growing market changes of the
competitive world (Mennens, Gils, Schroder & Letterie, 2018). The success of new services loses
its essentiality if the valued knowledge gained through the success of this new service offerings is
not completely retained by the organization for future references (Preez et al., 2006). The
transformation right and relevant information and experience of service innovation success may
serve the organization with the developmental changes in the existing business model of the
organization. This may predict that experience of service innovation success is an essential factor
that may affect the extent of developmental changes in existing business process and business
model.
However, the organization are necessarily require to develop new competences in
pursuance of growing market need in order to ensure its continuous survival. They are needed to
continuously update themselves with new technological advancements in their existing the service
portfolios. This would consequentially reap the organizations with the benefits of more improved
internal processes that would be required for more innovative value creation and proposition.
Similarly, the lasting good reputation of pioneer service and healthy customer satisfaction may
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57
further enable the organization to seek new customer segments or markets with more improved
delivery channels. Strengthening customer based on the retention of the existing customers and
building the new ones would resultantly strengthening the innovative revenue models with
additional sales. Based on the above discussion, the research hypothesis three is formed as,
H3: Service innovation success may possess positive influence on business model
innovation.
2.3.4. Service Innovation Success as Mediator (Research gap – 3).
Each and every organization in the real world possess some parameters of innovation
capabilities but it does not imply the fact that all the organizations are continuously innovating. It
implies that innovation capability is a necessary condition for the organization to innovate but not
sufficient enough for innovation. It is essential to state that the development and launch of novel
services require the significant funds along with the danger of overall disappointment. It is
apparent that the failure reflects that all efforts, capabilities and capitals are compensated as
wastage. Therefore, the forthcoming researches are taking the construct innovation success as
central emphases. Brentani and Ragot (1996) have distinguished the service innovation success
factor in terms of internal and external aspects based on the conception of strength, weakness,
opportunities and threats analysis. How well a service has taken into consideration the external
opportunities and threats, overall shapes the customer perception of new service benefits. It
determines why the customer should opt for that specific new service offerings. While the service
value proposition such as the new ways of channel deliveries would be considered as the internal
success factor of the new service. The organization necessarily requires strengthening themselves
in recognizing the unmet market and customer desires. They further necessarily require to adopt
some efficient technologies and then orchest, scale and stretch these new acquired capabilities with
the prevailing organizational processes. Such organizations may evidence to be efficacious in
delivering the customer value. It is vital to proclaim that the extent of the innovation capabilities
align with the existing process of organization may further surface the extent of the success of
innovation of organization in terms of financial parameters, parameters of competitive positioning
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58
and the parameter which may sustain the overall success of innovation (Hossain, 2018). An
organization deliberately achieving the success in competitive positioning and sustainability
parameters, may further enhances the ability of an organization to posited new ways of doing
business to deliver and capture value (Helfat & Martin, 2015). Bashir and Verma (2019) explained
that the organization is capable of delivering the customer with the value proposition with the
increased profits to the organization. Such new service offering may be met with the success
overall to the organization, customer and other business partners.
Thus, it would not be wrong to state the service innovation capabilities of sensing,
conceptualizing, orchestrating and stretching may influence the success of the new service offering
with more competitive positioning and sustainability. It may further yields the value creation, value
proposition and value capture to customers as well as the organization with the success of the new
service offering. These arguments are also supported by some of researchers that indicated the
more empirical researches are needed to investigate this phenomenon (Bashir & Verma, 2019;
Hossain, 2018; Teece, 2018). Teece (2018) has suggested that the forthcoming researches should
empirically testify the influence of innovation capabilities on their innovative business models.
The focus is to understand that whether the strong capabilities produces the operative, novel and
efficient business model. Teece (2018) also proposed that the forthcoming researches may also
requires to illustrate the potential influence of some critical significant connections among the
association of innovation capabilities and business model(s) innovation. He also explained that it
is very crucial to examine their intricate connection for the further advancement of knowledge in
the field of this newly evolved construct business model innovation. The researcher has also
suggested that forthcoming researchers may examine the influence of these innovative capabilities
in relation to any performance indicators that could be the innovation success. In light of these
arguments, this work efforts to fill this research gap by developing the research hypotheses four
as,
H4: Service innovation success mediates the relationship between innovation
capabilities and business model innovation.
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59
Teece (2018), Scheinder and Speith (2014), and Foss and Saeibi (2018) comprehend
the need to explore the possible association with performance indicators (such as innovation
success in this work). The empirical testing of this hypothesis 4 contributes to the existing
literature body by closing this research gap.
2.3.5. Moderation Effect of Employee Resistance to Change (Research gap-4).
There is a number of organizations that spend heavily on their innovative capabilities but
still unable to achieve innovation success while on the same perspectives there exist some
organizations in the real world that do not invest much but still successful in achieving the
innovation success (Zawislak et al., 2012). This raises the concern to ponder and the answers lie
into the innovation capabilities. The innovation capabilities are the handheld parameters that
enables the organizations to absorb, implement, adapt and transform the new technologies and
practices into laid down operational, transaction and management routines of the organization with
an objective to be profitable in terms of innovation. It might also be possible that the two
organizations who possess the same level of educated, skilled and competent workforce /
organizational members may behave different towards their innovation and organizational goals
(Nisula & Kianto, 2013). The reason for different output is the differences these two organizations
possess in regulating the environment of collaboration and contextual elements that shape the
stance of the employees towards novel things (Miller, 2019). Hence, this discussion concludes to
the point that it is not only the innovation capabilities of the firm that drives the innovation success
but behind there lies the behavior of employees for managing the novel changes (Miller, 2019;
Nisula & Kianto, 2013).
Employee resistance was treated as an essential barrier to the innovation mechanism in
existing literature therefore, it is critical for the organization (to take in consideration) who intends
to carry innovation either in product or service offerings, business process and existing business
models (Rodriguez, Molina-Castillo, & Svensson, 2019). The resistance by employees against any
newness or developmental change in form of innovation may disclose the conflict of interests of
employees and employers (Hauschildt, 1999; Rodriguez et al., 2019). Although, the literature
argues that the employee resistance to change may have a substantial effect on the business success
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60
of the organization in the longer run. It may be higher among the organizations in which the pay-
back compensation on the ongoing innovation was not guaranteed by the organization. This
employee resistance to change may have divesting effect not only on the innovation capabilities
of the organization but also on the ongoing innovation mechanism that consequently may lead to
the abolishment of innovation within the organization (Guldmann, & Huulgaard, 2020). The
genesis of innovative service success and the ultimate innovation in existing or new business
models by innovation capabilities of the organization may be interdependent on the extent of
employee resistance to change within the organization (Guldmann, & Huulgaard, 2020). Hao and
Yu (2011) conducted detailed research on the nature of association among the different forms of
innovation capabilities of organization and outcome of innovation that is innovation success. The
researchers found that all the forms of innovation capabilities possess the positive effect on the
innovation success among the Chinese organizations and further call for future research to explore
the role of some moderating elements that effect the association of innovation capabilities and
service success.
Generally, it can be argued that the phenomenon of business model innovation carries both
forms of employees i.e. winners and losers. The organizational members who losses during the
ongoing mechanism of bringing newness or change in business model may be expected to
disproportionately behave more negatively towards the ongoing business model innovation. In
comparison to those, who gain during this ongoing phenomenon may expect to behave more
positive towards business model innovation. Summarizing, the researcher was of the opinion that
business model innovation may regulate some extent of employee resistance to change (Muller,
2019). This debate is further supported by Foss and Saebi (2018) and that needs to be explored by
future researches. This posed research question by Foss and Saebi (2018) states that there is a need
to explore the role of entrepreneurial orientation (or vision) on the business model innovation. In
light of these theoretical discussion and an efforts to address these research gaps articulated by
researchers Hao and Yu (2011) Muller (2019) Foss and Saebi (2018, 2017), the hypothesis 5 and
6 are developed as,
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61
H5: Employee resistance to change moderates the direct relationship of innovation
capabilities and business model innovation, in such a way that the relationship is
stronger with lower employee resistance.
H6: Employee resistance to change negatively moderates the relationship between
innovation capabilities and service innovation success in such a way that the
relationship is stronger with lower employee resistance.
Thus, the empirical testing of these hypotheses 5 and 6 contributes to the existing
literature body by closing these research gaps comprehend by Muller (2019) Hao and Yu
(2011) Foss and Saebi (2018, 2017).
2.3.6. Moderation Effect of Management Entrepreneurial Orientation (Gap – 5).
Generally, it is argued that the heart of entrepreneurship can be termed as innovation but it
is not necessary that all the innovation is the not the outcome of higher entrepreneurial orientation
only (Groskovs & Ulhoi, 2019). Organizations continuously experience some routine forms of
innovation in response to its rivals or customer growing needs that guarantee its survival in
competitive market dynamics. However, the innovation within the organization that is inspired by
the entrepreneurial orientation may be more distinguishable than this routine innovation of
adaptation and responses to market new trends (Baker & Sinkula, 2009). Actually, this mechanism
of identifying external opportunities is the precursor one that brings innovation success with the
ultimate objective of bringing new service offerings to market or customer. This phenomenon
requires the entrepreneurial orientation by the management of the organization at the heart of
which this new innovation would rest (Al‐Jinini, Dahiyat, & Bontis, 2019).
Thus, the organization that possesses a strong entrepreneurial orientation by the
management may likely to develop successful innovative service offerings as per the customer or
market needs. Similarly, such organization learns from the service’s success and may efficiently
brings newness in the existing business model either by replacing the older business model with
the newer one or may bring some new developmental changes in existing business model
(Groskovs & Ulhoi, 2019). The genesis of these forms of innovation depends on the
entrepreneurial insight and orientation by the management, not through traditional customer
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
62
research. Vaznyte and Andries (2019) argued that the entrepreneurial orientation serves as a
instrument for the organization to decide whether the new business model can be pursue or not.
Some of the other researchers also supported the argument that the entrepreneurial orientation may
affect the organization that whether the new business model or corporate start-up fits with the
dynamic external environment irrespective of the enhanced capabilities to innovate (Lafuente,
Vaillant, and Leiva, 2018; Vaznyte & Andries, 2019) . Thus, there is a need to empirically
investigate the understanding of the phenomenon that how the entrepreneurial orientation predicts
the success of innovation success as well as the degree to which an organization capture, deliver
or propose value (Vaznyte & Andries, 2019). Foss and Saebi (2018, 2017) conducted a detailed
systematic literature survey on the business model innovation and argued that there is a need to
explore the moderation effect of certain factors (such as the management entrepreneurial
orientation) on the association of antecedents and business model innovation itself. Foss and Saebi
(2018) further elaborated this research direction and posed a challenging research question that
states that the role of entrepreneurial orientation (or vision) needs to be explored on the business
model innovation. Hao and Yu (2011) also argued that the different forms of innovation
capabilities possess a direct effect on the service innovation success. However, the future
researches are recommended to explore this association of innovation capabilities and service
innovation success with some potential moderating factors with an objective to bring more clear
insight of this association (Hao and Yu, 2011). In light of these theoretical discussion and an effort
to address these research gaps articulated by researchers Vaznyte and Andries (2019) Hao and Yu
(2011) Foss and Saebi (2018, 2017), the hypothesis 7 and 8 are developed as,
H7: Management entrepreneurial orientation moderates the direct relationship of
innovation capabilities and business model innovation, in such a way that the
relationship is stronger with increased entrepreneurial orientation.
H8: Management entrepreneurial orientation positively moderates the relationship
between innovation capabilities and service innovation success in such a way that
the relationship is stronger with increased entrepreneurial orientation.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
63
Thus, the empirical testing of this hypotheses 7 and 8 contributes to the existing literature
body by closing this research gap articulated by researchers Vaznyte and Andries (2019) Hao and
Yu (2011) Foss and Saebi (2018, 2017).
2.4. Antecedent of BMI Needs to be Explored (Research Gap-6)
The evolution of this new construct ‘business model innovation’ is only decade earlier. It
is not wrong to state that the increased globalization, growing technological advancements and
tough competitive market dynamics have led today’s businesses to fall in prey of continuous
innovation. This consequently has led to the emergence of the concept of ‘business model
innovation’. However, it is also pertinent to mention that the business models of the organizations
tend to be stable and static in natural characteristic especially when an organization is enjoying a
success with efficient and effective practiced activities and strategies that further serves as a path
to imitate for rivals (Teece, 2018, 2010; Doz & Kosonen, 2010).
The review of existing literature body reveals that the detailed researches have been
conducted on the barrier of business model innovation by some of the researches (Amit & Zott,
2001; Chesbrough & Rosenbloom, 2002; Christensen & Raynor, 2003). However, the consequent
researches have summarized and organized these barriers of business model innovation in two
broad classifications of obstruction and confusion (Chesbrough, 2010). Furthermore, the literature
also recommended the strategies of experimentation, leadership style and change leadership to
overcome the effects of these barriers on the business model innovation (Chesbrough, 2010). The
literature also indicated that managerial cognition also plays an essential role in the transformation
of business model innovation (Aspara et al., 2012). However, it was a single case study and
directed for future researches to testify the effect of management cognitive orientation in
determining the business model innovation at a larger scale. Some of the other researches were
also found to explore the role of individuals (employees) in the creation of new ideas and the
development of business model innovation (Bjork, 2012; Eppler et al., 2011). However, the
majority of these previous research studies provided more concrete concepts but followed the
qualitative research methodology. Below mentioned table 2.2 explains this progress of researches
on the antecedents of business model innovation. It also explains the way forward for future
researches in quest of search for antecedents of business model innovation phenomenon.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
64
Table 2.2.
Survey evidence pertaining to the antecedents of business model innovation
Authors Focus and Contribution Methodology
Adopted
Findings and Future
Research Directions
Trapp, Voigt
& Brem
(2018)
Develop and test the business
model innovation identification
instrument for the new
researches and practitioners
A qualitative
approach with
interview
method
The characteristics of BMI were
investigated an an attempt to address the
research gap. The future research can
evaluate these business model innovation
parameters from survey method. Future
research is also called to investigate the
international business models and their
configurational changes in details.
Loon & Chik
(2018)
Investigates the role of
technology and innovation in
bring novelty in business
models of SMEs.
A qualitative
study with
case study
approach
Technology, innovation and customer
relations plays an influential role on
business model innovation. Future research
may adopt a quantitative approach for
investigating business model innovation
phenomenon.
Speith &
Meissner
(2018)
Investigates the business model
innovation of a company in
terms of developmental
alliances and innovation success
A qualitative
approach
with case
study
approach
Future study may broaden the results of a
study by testifying the parameters in
different organizations. Longitudinal
studies are also recommended.
Valter,
Lindgren &
Prasad (2018)
Explains the role of seven forces
on the business model
innovation process in
engineering lab set-up
Case study
approach
Empirical studies are recommended that
may investigate the individual, group and
emotion forces on the business model
innovation.
Foss & Saebi
(2018)
Discussed in detailed the future
avenues of research in three
streams of BMI i.e. dimensions,
the effect of BMI and
antecedent of BMI.
Literature
Review
Future researches are recommended to
explore the role of BMI as independent,
moderating or mediating and dependent
variable. Few challenging research
questions are posed by the researcher for
future researches.
Adrodegari,
Pashou &
Saccani
(2017)
Discusses the methodology for
the selection and design of a
new business model for revenue
generation
Case Study of
ULMA
company
--
Teece (2018)
Discussed the conception of
business model innovation in
connection with dynamic
capabilities.
Conceptual
paper
Future research is recommended to testify
the association of capabilities and business
model innovation.
Geissdoerfer,
Vladimirova,
Van Fossen &
Evans (2018)
Discussed the conception of
business model innovation in
connection with service
innovation.
Conceptual
Paper
Future researches are recommended to take
into account the differentiation among
business model innovation, service
innovation and product innovation. The
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
65
validation of constructs of BMI are also
recommended
Hacklin,
Bjorkdahl &
Wallin (2018)
Explains the role of value
migration on business model
innovation
A qualitative
study based
on interviews
Empirical testing and collection of field
data are recommended.
Foss and
Saeibi (2017)
Discussed the fifteen years of a
literature review on BMI
Literature
Review
Future researches need to explore the
antecedent, element and effects of BMI.
Some challenging research questions are
also recommended for future researches.
Cortimiglia,
Ghezzi &
Frank (2015)
Discussed that the organization
engages in strategic making
process while achieving
business model innovation. It
also aimed to check the
relationship of SMP on
business model innovation
Mix method
approach
Future researches need to investigate the
different value propositions shaping the
business model innovation in an empirical
setting.
Maglio and
Spohrer
(2014)
Investigated the service science
perspective on one type of
business model innovation
Conceptual
Paper
Four principles of service sciences are
proposed that stress on the basic
relationship of service on the business value
propositions.
Scheinder
and Speith
(2014)
Discussed in detailed the
existing researches and new
research directions on the field
of business model innovation.
Literature
Review
Future researches are needed to explore the
elements and antecedents of business model
innovation.
It is crucial to state that these researches are conducted in-depth in investigating the
business model innovation as an outcome. However, these researches have not taken in parallel
the phenomenon of business model innovation (operationalization) itself (Foss & Saeibi, 2018).
Rather, the mere focus of the majority of these previous researches was on explaining a particular
type of change of business model (Foss & Saeibi, 2018). In addition, the majority of these
researches have used the qualitative research methodology and the empirical testing of the
dimensions and phenomenon was also found to be limited. The explanation of the factors that led
to the change in business model was also found to be limited in previous researches (Foss & Saebi,
2018). This research work also attempted to address these challenges of literature as well.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
66
The new researches on business model innovation pose certain significant queries for
forthcoming studies. Teece (2018) indicated that the aspects of capabilities (i.e. identifying market
opportunities and adoption in current practice) may revitalize the aspects of business model
innovation. Therefore, these associations and their influential role for performance (i.e. may be a
success) need to further explored in future researches (Teece, 2018). Thus, the recent researches
on business model innovation indicate some key questions (theoretical as well as empirically
analyzed) that need to be explored in order to contribute in the existing body of knowledge (Foss
& Saeibi, 2018, 2017; Scheinder & Speith, 2014).
• What is the role of capabilities as a driver of business model innovation? (Teece, 2018; Foss
& Saebi, 2018, 2017; Scheinder & Speith, 2014) (Gap-2 of this work)
• What are the elements and dimensions of business model innovation? (Hossain, 2018;
Bashir & Verma, 2019; Geissdoerfer et al., 2018; Scheinder & Speith, 2014; Foss & Seibi,
2018, 2017). (Gap-1 of this work)
• And what are the drivers, and factors that shape the business model innovation? (Scheinder
& Speith, 2014; Saebi et al., 2017; Foss & Saeibi, 2018, 2017; Hossain, 2018; Bashir &
Verma, 2019; Geissdoerfer et al., 2018; Speith & Meissner, 2018). Foss and Saeibi (2018)
further clarified the path by posing the challenging research questions that there is need to
explore the role of employee resistance and management orientation or cognition on
business model innovation (Gap – 3, Gap – 4, Gap – 5 and Gap – 6 of this work).
These are certain crucial queries that are not yet answered in present literature body (Foss
& Saebi, 2018, 2017). Foss & Saebi (2018, 2017) also highlighted that up till now no researches
have been found that deals with the antecedents of the business model innovation and thus it also
serves as a gap in literature body. These are some of the identified research gaps that are attempted
to address in this research work. Based on the above discussion on possible antecedent of business
model innovation and the research gaps identified by the researchers Schneider and Spieth (2014),
Foss and Saeibi (2018, 2017); Saebi et al., (2017), Hossain (2018), Bashir and Verma (2019),
Geissdoerfer et al., (2018), Speith and Meissner (2018), and Teece (2018), following research
hypotheses H9 and H10 are developed to address these research gaps,
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
67
H9: Employee resistance and management entrepreneurial orientation moderates
the direct relationship of innovation capabilities and business model innovation
when the putative mediator service innovation success held constant.
H10: Service innovation capabilities possess the positive indirect effect on the
business model innovation (through positive mediation effect of service innovation
success), that is further negatively moderated by employee resistance to change and
positively moderated by the management entrepreneurial orientation.
2.5. Chapter Summary
This chapter has discussed in detail the existing theories, conceptual models and different
standpoints of existing literature relating the research constructs of this research work. On the
basis of this extensive review of the literature, six crucial research gaps were identified. In order
to address these research gaps, ten testable research hypotheses have been developed. Chapter
three discusses in detail the theoretical stance of these posited relationship and proposed
theoretical framework.
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68
CHAPTER 3
RESEARCH METHODOLOGY
This chapter explains in detail the philosophical underpinnings including ontological,
epistemological and axiological stance of this research study. Based on these theoretical
underpinnings, the study variables, the theoretical model of this research and the nature of the
relationship among the variables are discussed in detail. Then, it discusses the methodology
followed in the completion of this research work. It includes the brief illustration of the research
design, population and sample frames, sampling strategy adopted, the process of drawing the
sample size, development of research instrument and brief information about the analytical
techniques
3.1. Research Paradigm and Philosophy
The research paradigm comprises of six essential layers of research onion that are
philosophy, approach, strategy, choices, time horizons and data collection techniques (Saunder et
al., 2009). The research philosophy basically identifies the deep-rooted beliefs and assumptions of
the research study (Saunder et al., 2009). The research philosophy including the ontological
assumption and epistemological assumptions of this study are elaborated as,
3.1.1. Ontological Stance of Study
Ontology basically refers to the “reality of being”. It refers to the study of reality and how
things exists (Saunder et al., 2009). The ontological assumption of this study is based on strategic
entrepreneurship perspective that pays attention towards the entrepreneurial stance of the
organization in exploring new innovative opportunities and simultaneously considers the
challenges in forms of employee resistance towards the innovative ideas, practices, and activities
(Holcomb et al., 2009; Ireland & Webb, 2007). Therefore, it is very essential and important to
researches on the concept of business model innovation in which the organization pursues of the
developmental changes of existing business model or adoption of new distinguished business
models for the delivery of value to customer and markets (Amit & Zott, 2010; Foss & Saebi, 2018).
Porter (2001) illustration of business model conception as “invitation for faulty thinking and self-
delusion” evolved this concept in different theoretical frameworks in relations with different fields
of management. However, there still lacks a well-articulated theoretical contribution in the realm
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
69
of business model innovation (Teece, 2018; Foss & Saebi, 2018, 2017; Bashir & Verma, 2019;
Hossain, 2018; Scheinder & Speith, 2014).
3.1.2. Epistemological Stance of Study
Epistemology basically concerns with the scope of knowledge (Saunder et al., 2009). It basically
refers to nature of reality that how to know what is known. The epistemological stance of this study
basically attempts to overview the realm of business model innovation falling in strategic
entrepreneurship perspective through the lens of force field of change theory (Lewin, 1951). The
concept of business model innovation itself originates from the amalgam of resource-based
perspective and strategic entrepreneurship perspective (Ireland et al., 2003). The resource-based
theory emphases on the rare, imitable, unique and non-substitutable attributes of an organization’s
resources (Barney, 1991; Teece, 1984). The potential of business models of the organization to
assemble, organize and coordinate the organizational resources (Morris, Schindehutte & Allen,
2005) further indicates the need to consider the capabilities in combination with resources to
deliver rare, imitable and non-substitutable value to customers and markets (Teece, 2010; 2018).
The dynamic capabilities perspective prolongs the resource-based theory by indicating the need
for the organizations to be innovatively capable of adopting and implementing the new value
creating, capturing and proposition strategies (Grant, 1996; Pisanno, 1994; Schreyogg & Eberl,
2007). Enhanced and developed capabilities of the organization are considered to sense the
customer or market needs, available technological options and provide the potential opportunities
to the organization (Teece, 2010; 2018) that are further conceptualized into new innovative ideas
to orchest and stretch in existing business processes of the organization. This determines the
service innovation capabilities of an organization (Janssen et al., 2015; Teece, 2018). Enhancing
these capabilities are necessary to achieve overall innovation success and innovation in the overall
business model of the organization (Hao & Yu, 2011; Teece, 2018). Force Field Theory of Change
by Lewin (1951) explains that there are two forms of forces that affect the process of bringing some
change in the organization (either the organization is striving for some form of innovation or
attempts to revolutionize the organizational culture). These influencing forces (or factors) need to
be managed in order to ensure the successful outcome (Lewin, 1951). The forces that are driving
the change needs to be stronger in relation to the forces that attempt to restrain the change process.
This would establish positive results towards the desired outcome. However, if there exists the
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
70
equilibrium between the driving forces and restraining forces then no change will happen in
desired outcomes (Lewin, 1951). This force field theory of change by Lewin (1951) provides the
best prototype for the moderation effects of two study variables management entrepreneurial
orientation and employee resistance to change on the complete accomplishment of business model
innovation. The managers of the organization strive to bring the positive change or innovation in
the overall business model of the organization through promoting and practicing the behaviour or
activities alike risk-taking, readiness to innovate, aggressively competitiveness and market
proactiveness. This is also supported by upper echelons theory (Hambrick & Mason, 1984) which
states that the senior executives and their teams are responsible for bringing and sustaining the
innovation, strategic formations and enactment. These individuals and group of individuals do so
by their experiences, personal attributes and values (Hambrick & Mason, 1984). In parallel to this
driving force of management entrepreneurial orientation, the mechanism of enhancing business
model innovation within the organization also experiences the restraining effects of employee
resistance to change. This employee resistance to change may constitute the single or
combinational behavior of routine seeking, short term thinking, cognitive rigidity and emotional
reaction from the employees. Thus, the moderation effect of management entrepreneurial
orientation (as the driving force of bringing innovation mechanism) and the employee resistance
to change (as the restraining force of bringing innovation mechanism) may exist on the service
innovation capabilities, service innovation success and business model innovation. This represents
the epistemological stance of this study that also lays the foundations of the theoretical framework
of this research work that is established on the prototypes of these philosophical underpinnings of
strategic entrepreneurship theory and force field theory of change.
3.1.3. Axiological Stance of Study
Axiology basically refers that how the investigator would investigates the beliefs. It basically
involves the standards, procedures and practices put to be in action in search of the raised beliefs
(Saunder et al., 2009). The above stated epistemological stance further paves the way for the
formulation of theoretical framework of this study. As stated above, the two foundational theories
namely strategic entrepreneurship theory and force field theory of change provide a more useful
and suitable prototype for the formation of theoretical framework of this study. It is also essential
to state that, the extensive critical review of the literature has revealed the six major research gaps
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
71
that are explained and articulated in this research work. Based on the ontological and
epistemological stance of study and an attempt to address these identified six research gaps
(detailed in chapter two), this research work limits the scope of tentative theoretical framework of
this research work to two broad theoretical perspectives that are theory of strategic
entrepreneurship (Hitt, et al., 2001; Ireland, et al., 2003; Hitt, et al., 2011) and force field theory
of change (Lewin, 1951).
3.1.4. Hypothesized Theoretical Framework
Based on these ontological, epistemological and axiological assumptions, this research
work carries the positivist research philosophy under which generalizable body of knowledge may
be generated with emphasis on quantifiable results. In this connection, the research survey strategy
has been used with a deductive approach. The deductive approach starts with the formation of
research question or hypothesis and tries to find the answer to posed research question through
collection and analysis of data (Saunder et al., 2009).
An effort to fill these keen research gaps and formation of proposed hypotheses further
surfaced the avenues towards the establishment of proposed theoretical model of this study. The
hypothesized theoretical framework clearly illustrates how the research constructs are affecting
and interacting with each other. The research construct “service innovation capabilities” plays its
role as an independent variable that possesses the two types of effects on the dependent variable
“business model innovation”. The first type of causal effect of service innovation capabilities on
business model innovation is hypothesized to be a direct effect that is also reflected in hypothesis
1. The other type of causal effect (indirect) of service innovation capabilities on business model
innovation is hypothesized to be an indirect effect that is covered with the series of hypotheses
from 2 to 9. This indirect effect of independent on the dependent variable is influenced by one
form of the mediator (service innovation success) and two proposed moderators (i.e employee
resistance, and management entrepreneurial orientation).
It is essential to clarify here that this indirect effect may exist due to some an
epiphenomenon association between the mediator or moderator in simple mediation or moderation
between the independent and dependent variables (Hayes, 2017). These mediator or moderators
may have the transmitting effect on the relationship of the independent and dependent variables
thus, converting their direct effect into indirect effect (Hayes, 2017).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
72
The hypothesized conceptual framework of the study illustrates that the indirect effect of
innovation capabilities (independent variable) on business model innovation (dependent variable
is comprised of three forms of paths and influencing factors. Stage one: at first level, this indirect
effect is mediated by service innovation success and it is hypothesized that this mediation effect
may be of positive nature (i.e. increase in the extent of service innovation success would result
into more strengthen the effect of innovation capabilities on business model innovation (i.e.
hypothesis 4). In addition to this hypothesis 4, the three foundational support hypotheses namely
1, 2 and 3 are also developed. Stage two: in addition to this mediating influence, the influence of
the moderation effect of employee resistance (moderator 1) may exist that is further classified into
two paths. The first path of moderation effect of employee resistance (moderator 1) may exist on
the indirect relationship of innovation capabilities and service innovation success that will be
checked through hypothesis 5. The other second path of moderation effect of employee resistance
(moderator 1) may exist on the direct effect of innovation capabilities and business model
innovation that will be testified through hypothesis 6. It is also hypothesized that this moderation
effect may be negative in nature that means the higher employee resistance may yield the
weakening effect on these two paths i.e. direct and indirect relationships. Stage three: in sum of
these two previous effect of mediation (service innovation success) and moderation (employee
resistance), it is hypothesized that another moderating variable “management entrepreneurial
orientation” (moderator - 2) may also exist parallel that also influences the direct effect of service
innovation capabilities and business model innovation and the effect of service innovation
capabilities and service innovation success. It is also hypothesized that this moderation effect may
be positive in nature that means the higher management entrepreneurial orientation may yield the
strengthening effect on these two paths i.e. direct and indirect relationships. This will be further
testified by the development of hypothesis 7 and 8 as also depicted in the figure 3.1.
Concluding, this discussion reveals that the influencing magnitude and direction of one
mediator and two modertors would termed this hypothesized model as conditional in nature.
Hypothesis 9 will check the conditionality of the two moderators on the direct effect of service
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
73
innovation capabilities on the business model innovation with the putative mediation effect of
service innovation success considered to be held constant. Hypothesis ten is also formed in order
to empirically testify the validity of this proposed research framework.
Figure 3.1. Hypothesized Conceptual Framework of Research Study
Thus, the recent researches of Foss and Saebi (2018, 2017), Bashir and Verma (2019),
Hossain (2018), Geissdoerfer and colleagues (2018), Speith and Meissner (2018), Teece (2018),
and Schneider and Spieth (2014) envisions the need to investigate the concept of business model
innovation as the dependent variable and further explore the factors precursor to business model
Employee Resistance to Change
• Routine seeking
• Emotional reaction
• Short term thinking
• Cognitive rigidity
Service Innovation Success
• Short term success
• Long term success
• Indirect success
Innovation Capabilities
• Sensing user needs
• Sensing technological options
• Conceptualization
• Coproducing and orchestrating
• Scaling and stretching
H5
H3
Business model innovation
• Value creation innovation
• Value proposition innovation
• Value capture innovation
H6
H2
H1
H7 H8
Management entrepreneurial orientation
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
74
innovation. The empirical testing of all the research hypotheses of this work contributes to the
existing literature body by closing the mentioned research gaps. The summarization of research
gaps and mechanism adopted to address these research gaps are already illustrated in table 1.1 in
chapter one of this research work. The formation of mentioned ten hypotheses with an objective
to address these identified six research gaps consequently led to the development of this proposed
research model. The tentative hypothesized research model of this work will be tested through
empirical analysis of hypothesis 10.
3.2. Research Design
The research design refers to the research plan of how the posed research questions may
be answered (Saunder et al., 2009). The research strategy of this research work is research survey
as it is considered to be one of an efficient tool for data collection by researchers with more
accurate results with minimal biases (Saunder et al., 2009). As the population framework is
geographically spread nationwide, the self – administer research survey are provided to HR
departments for the complete response by the picked participant. The research work has opted for
mono-method choice (single data collection technique i.e. survey) with quantitative methods as
this work falls in positivist research philosophy. The collection of data may be attempted on a
single point of time. The population constitutes the four cellular companies of Pakistan. The unit
of analysis are chiefs, departmental heads and middle managers discussed in detail in section 3.4.
3.3. Operationalization of Research Instrument and Measurement
This research work has used the existing research instrument of previous past researches
in order to measure the research constructs. Most of the items/scales from previous researches are
adopted with no changes and amendments.
3.3.1. Service innovation capabilities.
The first research construct service innovation capabilities are operationalized with the five
second-order sub-constructs that are sensing user needs, sensing technological options,
conceptualizing, co-producing and orchestrating, and finally the scaling and stretching (Den
Hertog, Van der Aa, & De Jong, 2010. These five dimensions of service innovation capabilities
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
75
were measured with the adopted 15-items scale developed by Den Hertog et al., (2010). The
original items of this previous study were measured on a 7-point Likert scale with (1) strongly
disagree to (7) strongly agree. This research work has adopted these original items for the
measurement of service innovation capabilities as it is, with no change or amendment. The
operational definitions of these five indicators are stated as follows,
i. Sensing user needs: Sensing user need refers to the capability of the
organization to sense or understand the existing and potential needs of the
customers in advance through interactions with different segments of customers
and markets (Den Hertog et al., 2010).
ii. Sensing technological options: Sensing technological options refers to the
capability of the organization to sense or adapt the new technologies and
potential new services through interactions with competitors, technology
providers and clients, etc. (Den Hertog et al., 2010). This indicator is more linked
with the business development aspect of the organization (Den Hertog et al.,
2010).
iii. Conceptualizing: Conceptualization refers to the capability of the organization
to smartly rework on the new idea or new sensed technological options by
combining the new and existing service elements into something new service
offering to market (Den Hertog et al., 2010).
iv. Coproducing and Orchestrating: Coproducing and orchestrating refer to the
capability of the organization to co-design and co-produce the new service
offerings with the suppliers, customers and other accompanying alliances (Den
Hertog et al., 2010).
v. Scaling and stretching: Scaling basically refers to the capability of the
organization to diffuse the elements or concept of new service offering across
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
76
the different functioning of the organization (Den Hertog et al., 2010). On the
other hand, stretching refers to the capability of the organization to promote this
new service offering with effective branding strategies in a way that seems
valuable for potential customers (Den Hertog et al., 2010).
3.3.2. Service innovation success.
The second research construct service innovation success is operationalized with the three
second-order sub-constructs that are short term success, long term success, and indirect success
(Riel et al., 2004). Eighteen item scale has been adopted from the work of Riel, Lemmink, and
Ouwersloot (2004) for the measurement of these three sub-construct research variable. The
original items were measured on 7-point Likert scale with (1) strongly disagree to (7) strongly
agree. Similarly, this work has adopted these eighteen items as they were developed, with no
change or amendment. The operational definitions of these three indicators are stated as follows,
i. Short term success: The short term success refers to those elements of new
service that represent the salient aspects of innovation success such as
contribution to financial success, add substantial value to other services or
product and overall success. (Riel et al., 2004).
ii. Long term success: The long term success refers to those elements of new
service that are linked with the sustained competitive advantage of the
organization such as commercial success, competitive position, brand equity and
reputation, expansion in new markets and customer satisfaction. (Riel et al.,
2004).
iii. Indirect success: The indirect success refers to those elements of new service
that serves as a precondition for the future success of the organization such as
in-house technological knowledge of the organization, employee satisfaction, the
creation of new innovation opportunities (Riel et al., 2004).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
77
3.3.3. Business model innovation.
The construct business model innovation is constituent of three second-order sub-
constructs namely value creation innovation, value proposition innovation, and value capture
innovation. The value creation innovation was operationalized further into four third-order
subcontracts namely new capabilities, new technology or equipment, new partnerships and new
processes (Clauss, 2017). The second dimension of business model innovation “value proposition”
was further operationalized into four sub-constructs of namely new offerings, new customers and
markets, new channels and new customer relationships (Clauss, 2017). These four sub-constructs
are measured with twelve items. The third dimension of business model innovation “value capture”
was further operationalized into two sub-constructs of new revenue models and new cost
structures. These two sub-constructs are measured with eight adopted items. In sum, the concept
of business model innovation has been measured with the total thirty-three items scale adopted
from the previous work of Clauss (2017) with no change or amendment. The original scale is
measured on a five-point Likert scale mainly (1) strongly disagree to (5) strongly agree. The
operational definitions of these sub-constructs are stated as,
i Value creation innovation: Value creation innovation refers to the acquisition
of new capabilities, new technology or equipment, new business partnerships
and improvement of existing routines through the acquisition of new processes
with an objective to bring positive substantial changes in business model (Clauss,
2017).
ii Value proposition innovation: Value proposition innovation refers to the new
offerings introduce by the organization to meet growing needs of existing and
new customers or new market segments with the new delivery channels
purposely to build strong customer relations so that the substantial positive
change can be brought in business model (Clauss, 2017).
iii Value capture innovation: Value capture innovation refers to the development
of new revenue models and new cost structures to utilize the potential
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opportunities with an objective to bring positive substantial changes in business
model (Clauss, 2017).
3.3.4. Management entrepreneurial orientation.
The research constructs “management entrepreneurial orientation” is operationalize into
four sub-constructs of ready to innovate, aggressively competitiveness, market proactiveness and
risk-taking (Wang, 2008). These four sub-constructs are measured with the adopted eleven items
scale adopted from the previous research work of Wang (2008). The original items are adopted as
they were developed with no change or modifications. The original items were measured on a
seven-point Likert scale mainly (1) strongly disagree to (7) strongly agree. The operational
definitions of these sub-constructs are stated as,
i. Ready to innovate: Ready to innovate refers to the extent to which the management of the
organization encourages new ways of performing things, seek unusual and novel
opportunities or solutions and facilitates its employees to behave and think in a novel
manner (Wang, 2008).
ii. Aggressively Competitiveness: Aggressively competitiveness refers to the extent to which
the organization initiates leading foremost action in comparison to rivals with an objective
to adopt competitive positioning to overtake rivals (Wang, 2008).
iii. Market Proactiveness: Market proactiveness refers to the extent to which the organization
facilitates the research and development, technological leadership and continuously
markets new lines of product with more improvements (Wang, 2008).
iv. Risk-taking: Risk-taking refers to the extent to which the organization embraces the
uncertain projects with higher profit returns with the belief that some uncertain acts are
necessary to attain the organizational objectives (Wang, 2008).
3.3.5. Employee resistance to change.
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The fifth research construct employee resistance to change is operationalized with the four
dimensions that are routine seeking, emotional reaction, short term thinking, and cognitive rigidity.
Fifteen item scale has been adopted from the work of Oreg (2003) for the measurement of these
four sub-construct research variable. The original items were measured on 6-point Likert scale
with (1) strongly disagree to (6) strongly agree. Similarly, this work has adopted these fifteen items
as they were developed, with no change or amendment. Employee resistance to change is
operationally defined as dispositional resistance that means all the individuals are disposed to resist
the change but the extent of resistance varies among all (Oreg, 2003). Some individuals are much
more disposed to resist the newness or change in comparison to others (Oreg, 2003). The
operational definitions of the four sub-constructs that are routine seeking, emotional reaction, short
term thinking and cognitive rigidity are stated as,
i. Routine seeking: Routine seeking refer to the desire of individuals to stabilize
the existing daily routines of work or life with the obvious reluctance towards
the adoption of novel acts (Oreg, 2003).
ii. Emotional Reaction: Emotional reaction refers to the feelings of psychological
resilience and hesitancy to lose control experienced by the individual when any
novelty or change is brought (Oreg, 2003).
iii. Short term thinking: Short term thinking refers to the intolerance for the
adjustments and weak stimulation for experiencing something different or new
when any novel act or changes are brought within the organization (Oreg, 2003).
iv. Cognitive Rigidity: Cognitive rigidity refers to the attribute of close-mindedness
of individuals that are less willing to adjust themselves in new contexts and
situations (Oreg, 2003).
3.3.6. Finalization of research instrument.
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The consolidated version of the instrument of this research work consists of six parts (with
a total of 92 items). The first section (A) of the questionnaire consists of the fifteen items measuring
the conception of service innovation capabilities ranging from items 01 – 15. The second section
(B) consists of the thirteen items measuring the conception of service innovation success ranging
from the items 16 – 28. The third section of the survey questionnaire (C) constitutes the eleven
items of construct of management entrepreneurial orientation ranging from 29 – 39. The fourth
section of the questionnaires (D) contains the fifteen items measuring the concept of employee
resistance to change ranging from 40 – 54. The fifth section of the survey (E) comprises of thirty-
three items measuring the concept of business model innovation ranging from 55 – 87. The last
part of the survey questionnaire (F) contains the three items measuring the demographic attributes
of the respondents namely gender, age and education.
It is pertinent to mention that the research instrument of this research study comprises of
different measurement scales of 5-point, 6-point, and 7-point Likert scale. Hair, Black, Babin, and
Anderson (2009) explained that measurement error can be caused by imposing the one type of
Likert scale (i.e. 7-point) by the researcher for measurement of the construct. However, the
respondent can accurately respond to the other type of Likert scale (i.e. 3-scale) for that particular
construct (Hair et al., 2009). It is also advisable by some researchers that the previously existing
scales may be adopted (with no change) or adapted with minor changes i.e. grammar (Saunder,
2009; Sekaran, 2010; Hair et al., 2009). So that the credibility of scale validity may not be
compromised (Saunder, 2009).
Dawes (2008) conducted detailed experimental research to check the impact of different
Likert scales (i.e. 5-point, 6-point, 7-point, and 10-point etc.) on the data characteristics. He
concluded that all of these different Likert scales are desirable for obtaining the data for regression
analysis. He also explained that the values of kurtosis and skewness for these different Likert scales
are approximately similar and these different Likert scales were found to all comparable in
different statistical techniques of regression analysis, confirmatory factor analysis and structural
equation modeling (Dawes, 2008).
3.4. Population and Sample of study
The population of this research work consists of cellular companies in Pakistan. It is
pertinent to mention that cellular companies of Pakistan presently carry different forms of
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81
additional business model (i.e. payment mechanism in collaboration with financial institutes such
as branchless banking etc.) in parallel with the parental business model of providing sim based
cellular services to citizens. Currently, these four cellular companies are engaged in branchless
banking business models that includes (i) Easypaisa (operated by Telenor and Tameer
microfinance bank), (ii) Mobicash (operated by Mobilink and Waseela microfinance bank), (iii)
Timepey (operated by Zong and Askari bank) and (v) Upayment (operated by Ufone, Habib bank
limited, Summit bank limited, Soneri bank and Bank Al Habib limited).
The justification for choosing the cellular companies of Pakistan is evident with the fact
that it is the fastest growing and economic contributing sector that boosts the 0.28 percent of
Pakistan GDP with only 1 percent increase in its mobile phone subscription (PTA, 2018). Presently
the cellular companies of Pakistan are not only providing cellular services (through GSM sims) to
general public, but also playing its crucial role in some Government-to-Public G2P payment
projects such as Benazir Income Support Program Project, Guzara Allowance in Sindh, e-
Agriculture project (i.e. providing weather forecast, farm advisory and market prices alert etc.)
(PTA, 2018). In addition to these, cellular companies are also regulating the branchless banking
operations in collaboration with certain financial institutes of Pakistan (PTA, 2018). These are
some additional business models carried by cellular companies for the generation of revenues in
parallel with the parental business model of mobile services subscription (PTA, 2018). Thus, the
concept of business model innovation and innovation capabilities that are briefly investigated in
this research work are best reflected in the existing operations of cellular companies of Pakistan.
In this connection, this research work has selected the four cellular companies of Pakistan as the
population of this research work.
3.4.1. Unit of Analysis
The unit of analysis of this research work are the upper management and middle managers
(i.e. including chief executives, deputy chiefs, head of departments, senior managers, divisional
managers, team leaders, project managers, zonal managers etc.) of cellular companies of Pakistan.
Upper and middle managements are selected because of the following reasons,
• Den Hertog et al. (2010) argued that the concept of innovation capabilities can be measured
from those members who carries the information and valid knowledge relating major
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82
business process of the organization (Miller et al., 1998; Janssen, Castaldi & Alexiev,
2015). It may include chief executives, senior executives and senior managers (Den Hertog
et al., 2010; Janssen et al., 2015).
• The concept of service innovation success involves the salient features of innovation
success that are also associated with competitive positioning among the other industry
players. Riel et al. (2016) argued that the service innovation success can be better reflected
among the responsible position holders of the organization such as chief executives,
departmental heads, product managers, technical managers, service managers, marketing
manager, other senior managers etc.
• Mitchell and Coles (2003) were the first ones who coined the idea that the chief executives
of the organization can objectively bring innovation in their organization’s business model.
The concept of business model innovation involves the changes in the creation of values
(in terms of new capabilities, processes, equipment etc.) offering value to customer or
market and capturing the value in terms of new cost or revenue structures. Clauss (2017)
stated that these forms of changes could better be measured from the responsible position
holder of the organization that are upper management (such as chief executive and business
leaders) and a middle layer of management (including divisional managers, group leaders,
project manager, product manager etc.) Trapp et al. (2018) also argued that the tool to
measure the existing definitions and illustration of business model innovation in the
organization needs the senior corporate managers and executives to articulate.
Therefore, keeping in view these existing researches supported aspect and the philosophy
of the research framework, this research work have chosen the upper management and middle
managers of the four cellular companies as the unit of analysis for this research work.
3.4.2. Determination of Sample Size
The population frame of this research work consists of approximate 1274 participants
(including chief executive, deputy chiefs, head of departments, senior managers, divisional
managers, regional or zonal managers, and project managers) from the four cellular firms
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83
nationwide, as per the statistics gathered by their respective HR departments. Saunder (2009)
indicated that the minimum 370 sample size (roughly) may be required from the population frame
of 5001 to 10,000 at a 95 percent confidence interval for a five percent margin of error. Some of
the other researchers pointed out that the minimum sample size of 200 is sufficient for the
attainment of generalizable results (Kelloway, 1988; Roscoe, 1975). On the other hand, Krejice
and Morgan (1970) came up with a mathematical formula for the calculation of minimum sample
size for the finite population as,
S = X2 NP (1-P)
d2 (N-1) + X2 P (1-P)
However, the term ‘N’ in this mathematical expression, represents the total population size
(1274); the term “P” refers to the population proportion (0.5) that is usually assumed to 50 percent
(maximum possible sample size); the term “d” indicates the degree of accuracy (0.05) usually
assumed to be 5 percent margin of errors and lastly the term “X” refers to the constant value of
1.96 at 95 percent confidence level. By putting these values, it can be calculated as,
S = (1.96)2 (1274) (0.5)(1 - 0.5) .
(0.05)2 (1274-1) + (1.96)2 (0.5) (1 - 0.5)
S = 295
It reveals that the minimum sample size of ‘295’ would be required by this research work
in order to obtain acceptable and generalizable results at of 95 percent level of confidence, by
using the finite population formula of Krejcie and Morgan (1980).
3.4.3. Selection of Sample and Sampling Technique
In order to select the minimum size of 295 participants, this research work has adopted a
simple random sampling strategy. A random sampling strategy is a form of probability sampling
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
84
technique in which the each and every member of the whole population frame carries the equal
chance to get picked for a sample of the study (Sekaran, 2001). Random sampling provides a better
representation of the population in the selected sample with enhanced generalizability of results
(Sekaran, 2001). Saunder et al., (2009) explained that the researches who does not require face to
face contacts and no relevant strata exist in the sampling frame with no periodic patterns, such
researches should choose simple random sampling strategy. It is pertinent to mention that the
responses from the senior chiefs, departmental heads and middle managers of cellular companies
do not require face-to-face contact for the filling of the research questionnaire. In addition, the
population frame does not constitute any prominent cluster or strata. Therefore, this research work
has opted for the simple random sampling strategy for the selection of sample size from the
population frame in light of illustration of selecting the probability sampling strategy by Saunder
et al. (2009). Thus, five hundred and fifty (550) participants were selected under the simple random
sampling technique. The methodology followed in the selection of sample under simple random
sampling strategy is as follows,
• At the initial step, the list of participants of four cellular companies (comprising of total
1274 approximate population) is obtained from the respective HR departments of each
organization. It is crucial to inform here that the HR departments have only shared the
employee code keeping in view the secrecy and privacy of credentials.
• Each employee code in the provided list is allocated with a unique serial number, starting
from zero (0).
• The respondents are randomly picked through the MS Excel program. The ‘RAND’
function is used in MS Excel program that automatically picked the five hundred and
fifty participants with the coded unique serial number. The questionnaire (mentioned
with the selected employee code) were floated to the respective HR department for the
acquisition of responses from the picked sample of 550 participants.
3.4.4. Data Collection
The research questionnaires (with the marked employee codes) were handed to the
respective HR departments of four cellular companies namely Telenor, Mobilink – Warid, Ufone,
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85
and Zong. The concerned authorities of HR Department were requested to hand over the provided
printed questionnaires (each with the marked employee codes) to the respective personnel only.
These selected personnel’s of cellular firms were numerous time reminded via the concerned HR
authorities for the return of filled questionnaires. Numerous telephonic, email reminders and
personal visits to HR departments were the efforts of this survey process. Total of five hundred
and fifty (550) research questionnaires were floated. In response four hundred and twenty-seven
(427) completely filled questionnaires were received with the overall response rate of 77.63
percent.
3.5. Reliability and Validity of Research Instrument
Pre-testing constitutes the face validity and content validity analysis of finalized research
instrument. The establishment of satisfactory level of face validity and content validy, further
paves the way for the rigorous validity and reliability testing of research instrument. The validity
and reliability of the research instrument were tested by using Kouftero’s (1999) approach.
Kouftero (1999) explained that the validity of the research instrument can be tested in four steps.
First of all, the traditional method (i.e. measuring construct validity only) may be employed for
testing the measurement model through the exploratory factor analysis and reliability estimation
after item extraction of EFA. However, this earlier traditional approach carries some shortcomings
in terms of assessment of uni-dimensionality and other measurement model properties i.e. item
reliability and model fit indices (Kouftero, 1999; Gerbing & Anderson, 1988) that are covered by
Kouftero’s approach (1999). In the next steps, these shortcomings are covered through testing the
convergent validity (t-values and item reliability), model fit indices through confirmatory factor
analysis. After the iterative process of confirmatory factor analysis, the construct reliability of
residual eligible items of measurement models is calculated. In the last step, the discriminate
validity of the constructs is checked through the Pearson correlation. Average variance extracted
are also calculated at this step. The successful validation of the items measuring the construct and
sub-constructs further entails the testing of structural relationship of constructs.
3.5.1. Face Validity.
The face validity involves the process of reviewing the research questionnaire by the expert
of the questionnaire’s subject area (Saunder et al., 2009). The face validity of the research
instrument is said to be establish when this expert concludes that the questionnaire carries all the
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86
traits or characteristics to which it intends to measure (Saunder et al., 2009). In this regard, the
final version of the research instrument is shared with the three reputable Ph.D. faculty members
of national universities (of subject area) with an intention to obtain the valuable constructive expert
opinion from an academic research perspective. In addition to the three local opinions, an expert
opinion is also obtained by an international researcher (Ph.D. faculty member) of technologically
/ academically advance country (as categorized by HEC, Pakistan). The finalized research
instrument, operationalization of constructs, measures of constructs, sources of measures, the
elaboration of theoretical framework and research objectives of study were shared with these
subject experts to get conformity. Just being checked on the face of finalized research with this
provided information of study, all experts verbally agree that the finalized research instrument is
a valid measure for the constructs which are being measured. Thus, the face validity of the research
instrument is established.
3.5.2. Content Validity.
The content validity involves that the research measures represents all the facets or
contents of the research constructs that needs to be measured (Saunder et al., 2009). In order to
assess the content validity of the research instrument, the three reputable practitioners of middle
management were asked to review all of the items for readability, clarity and comprehensiveness.
The practitioners were asked to provide their feedback about items in two judgments (favorable or
not favorable) keeping in view the readability, clarity and comprehensive of items. All the
practitioners passed the favorable judgment for all the items of finalized research instrument with
the recommendation of negligible changes.
3.5.3. Construct validity (Exploratory factor analysis).
The construct validity checks how well the results justifies and rationalizes the theory for
which that particular research instrument was developed (Sekaran, 2003). The exploratory factor
analysis is considered as the most common statistical tool for checking the construct validity of
the research instruments (Hair et al., 2010; Sekaran, 2003; Koufteros, 1999). Therefore, this
research study has also tested the construct validity via the exploratory factor analysis. Table 3.1
reveals the results of the exploratory factor analysis for the construct of innovation capabilities.
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Table 3.1. Exploratory Factor Analysis for the Scale of Innovation Capabilities
Items
Factors
1
*IC4
2
*IC2
3
*IC5
4
*IC1
5
*IC3
1. We systematically observe and evaluate the need of our customers .178 .297 .177 .742 .100
2. We analyze the actual use of our services. .340 .234 .227 .689 .097
3. Our organization is strong in distinguishing different groups of users and
market segments .313 .201 .233 .675 .011
4. Staying up to date with promising new services and technologies is
important for our organization .336 .768 .003 .061 .049
5. In order to identify the possibilities for new services, we use different
information sources .153 .781 .135 .224 .084
6. We follow which technologies our competitors use .197 .861 .163 .091 .005
7. We are innovative in coming up with ideas for new service concepts .048 .033 .049 .016 .894
8. Our organization experiments with new service concepts .156 .106 .147 .184 .061
9. We align new service offerings with our current business and processes .069 .057 .091 .025 .878
10. Collaborations with other organizations helps us in improving or
introducing new services .755 .207 .072 .094 .041
11. Our organization is strong in coordinating service innovation activities
involving several parties .827 .179 .121 .124 .015
12. Our organization is efficient in initiatives and maintaining the partnerships .749 .242 .191 .106 .063
13. In the development of new services, we take into account our branding
strategy .182 .125 .742 .101 .059
14. Our organization is actively engaged in promoting its new services -.002 -.023 .841 -.013 -.026
15. We introduce new services by following our marketing plan .255 .275 .627 .221 .027
Total Rotation Sum of Squares
% of Variance (Rotated)
Cumulative % of Variance
2.365
15.766
15.766
2.364
15.762
31.529
1.920
12.803
44.332
1.873
12.487
56.819
1.613
10.755
67.574
KMO & Barlett’s Test: KMO = .842; Chi-Square =2193.450, df = 105, p-value = .000
Note. *IC1 = Sensing user needs; IC2 = Sensing technological options; IC3 = Conceptualization; IC4 = Coproducing
and orchestrating; IC5 = Scaling and Stretching.
It was found that the 67.54 percent of the cumulative variance of innovation capabilities
are explained by its five sub-constructs. The result also revealed that the sub-construct “co-
producing and orchestrating” accounts for the highest variance (15.766 percent) among the other
sub-constructs with the highest rotated sum of squares value of 2.365. On the other hand, the sub-
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88
construct “conceptualization” was found to possess the lowest variance (10.75 percent) with the
lowest rotated sum of squares of 1.613. The results also revealed that all the items of the research
instrument (except item number 8) were appropriately loaded with the factor loading values
ranging from .627 to .894 (that is greater than 0.4). However, the item number 8 (measuring the
sub-construct conceptualization) showed poor factor loading that needs to be excluded from the
final research instrument. The results of KMO and Barlett’s Test for the sample adequacy for the
construct of innovation capabilities was also found to be significant with the value of .842 (that is
greater than .6) with the p-value of .000 (that is less than .05).
Figure 3.2. Scree Plot for Innovation Capabilities Scale
Figure 3.2 portrays the scree plot for the extracted factors of the construct innovation
capabilities. The results of the exploratory factor analysis sketch the scree plot with the number of
factors (drawn at x-axis) and the loaded initial eigenvalues (drawn at y-axis). Figure 3.2 also
reveals that component 1 - 5 possess the initial eigenvalue greater than one. From component six
(lying near the cut-off value one), the scree plot starts flattens onwards with the lower eigenvalues
of the residual components. Thus, the scree plot supports the above results that the five components
(lying above the cut-off value one) factors stand eligible for the retention.
Table 3.2. Exploratory Factor Analysis for the Scale of Service Innovation Success
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89
Items
Factors
1
*IS1
2
*IS3
3
*IS2
16. The new service is an overall success .784 .223 .153
17. Success exceeds expectations. .802 .164 .224
18. The new service contributed to financial success .795 .153 .178
19. The new service was a good idea to invest in .778 .232 .207
20. The new service adds substantial value to other products and services .631 .476 .124
21. The new service contributed to commercial success. .273 .332 .583
22. The new service improved our competitive position. .161 .102 .702
23. The new service improved brand equity and reputation. -.002 -.069 .829
24. The new service enabled expansion into new markets .313 .250 .562
25. The new service increased customer satisfaction and loyalty .280 .319 .640
26. The new service increased in-house technological knowledge .217 .814 .060
27. The new service increased employee satisfaction. .246 .740 .210
28. The new service created innovation opportunities .213 .831 .212
Total Rotation Sum of Squares
% of Variance (Rotated)
Cumulative % of Variance
3.325
25.576
25.576
2.571
19.775
45.351
2.503
19.253
64.604
KMO & Barlett’s Test: KMO = .906; Chi-Square =2465.339, df = 78, p-value = .000
Note. *IS1 = Short term success; IS2 = Long term success; IS3 = Indirect Success.
Table 3.2 reflects the results of the exploratory factor analysis for the construct of
innovation success. The results show that 64.604 percent of cumulative variance on innovation
success is explained by its three sub-constructs. The result also reflect that the sub-construct “short
term success” accounts for the highest variance (25.576 percent) among the other sub-constructs
with the highest rotated sum of squares value of 3.325. On the other hand, the sub-construct “long
term success” is found to possess the lowest variance (19.25 percent) with the lowest rotated sum
of squares of 2.503. The results also reveal that all the items of the research instrument (except
item number 20) are appropriately loaded with the factor loading values ranging from .562 to .831.
However, the item number 20 (measuring the sub-construct short term success) was found to be
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90
cross-loaded with the values of .631 and .476 among the component 1(short term success) and
component 2 (indirect success). This cross-loading qualifies the item number 20 to be excluded
from the final research instrument. The results of KMO and Barlett’s Test for the construct of
innovation success was also found to be significant with the value of .906 (that is greater than .6)
with the p-value of .000 (that is less than .05). Figure 3.3 portrays the scree plot for the extracted
factors of the construct innovation success. The scree plot also reflects that the three components
(lying above the cut-off value one) stand eligible for the retention.
Figure 3.3. Scree Plot for Innovation Success Scale
Table 3.3 shows the results of exploratory factor analysis for the construct of management
entrepreneurial orientation. The results show that 74.288 percent of cumulative variance on
entrepreneurial orientation is explained by its four sub-constructs that are ready to innovate,
aggressively competitiveness, market proactiveness, and risk-taking. The result also reflects that
the sub-construct “ready to innovate” accounts for the highest variance (20.55 percent) among the
other sub-constructs with the highest rotated sum of squares value of 2.26. On the other hand, the
sub-construct “aggressive competitiveness” is found to possess the lowest variance (14.56 percent)
with the lowest rotated sum of squares value of 1.602.
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Table 3.3. Exploratory Factor Analysis for Management Entrepreneurial Orientation Scale
Items
Factors
1
*EO1
2
*EO3
3
*EO4
4
*EO2
29. In general, the top managers of our organization favor a strong
emphasis on research and development, technological leadership and
innovations.
.807 .198 .246 .091
30. In the past five years, our organization has marketed a large variety
of new lines of products or services. .800 .163 .241 -.003
31. In the past five years, changes in our product or service lines have
been mostly of a minor nature (reverse coded) .836 .252 .126 -.019
32. In dealing with competitors, our organization often leads the
competition, initiating actions to which our competitors have to
respond.
.011 .030 .041 .892
33. In dealing with competitors, our organization typically adopts a
very competitive posture aiming at overtaking the competitors. .034 -.049 -.053 .885
34. In general, the top managers of my organization have a strong
propensity for high risk projects (with chances of high return) .141 .761 .324 .048
35. The top managers believe owing to the nature of environment,
bold, wide-ranging acts are necessary to achieve our organization
objectives
.257 .783 .167 -.073
36. When there is uncertainty, our organization typically adopts a
“wait and see” posture in order to minimize the probability of making
costly decisions (reverse coded)
.224 .853 .182 .002
37. Management actively responds to the adoption of “new ways of
doing things” by main competitors .120 .223 .773 .049
38. We are willing to try new ways of doing things and seek usual,
novel solutions. .247 .167 .812 -.015
39. We encourage people to think and behave in original and novel
ways. .238 .230 .751 -.060
Total Rotation Sum of Squares
% of Variance (Rotated)
Cumulative % of Variance
2.262
20.559
20.559
2.182
19.840
40.399
2.126
19.327
59.726
1.602
14.562
74.288
KMO & Barlett’s Test: KMO = .833; Chi-Square =1850.653, df = 55, p-value = .000
Note. *EO1 = Ready to innovate; EO2 = Aggressively competitiveness; EO3 = Market Proactiveness; EO4 = Risk
Taking.
The results also reveal that all the items of the research instrument are appropriately
loaded with the factor loading values ranging from .751 to .892. The results of KMO and Barlett’s
Test for the construct of entrepreneurial orientation is also found to be significant with the value
of .833 (that is greater than .6) with the p-value of .000 (that is less than .05). Figure 3.4 portrays
the scree plot for the extracted factors of the construct management entrepreneurial orientation.
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The scree plot also reflects that the four components (lying above the cut-off value one) stand
eligible for the retention.
Figure 3.4. Scree
Plot for Management
Entrepreneurial
Orientation Scale
Table 3.4
shows the results of exploratory factor analysis for the construct of employee resistance. The
results show that 60.203 percent of cumulative variance on employee resistance is explained by its
four sub-constructs (that are routine seeking, emotional reaction, short term focus, and cognitive
rigidity). The result also reflects that the sub-construct “routine seeking” accounts for the highest
variance (17.26 percent) among the other sub-constructs with the highest rotated sum of squares
value of 2.58. On the other hand, the sub-construct “cognitive rigidity” is found to possess the
lowest variance (13.74 percent) with the lowest rotated sum of squares value of 2.06.
Table 3.4. Exploratory Factor Analysis for Employee Resistance Scale
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Items
Factors
1
*ER1
2
*ER2
3
*ER3
4
*ER4
40. I would rather be bored than surprise. .783 .122 .195 .082
41. Generally change is not good .735 .263 .032 .263
42. Whenever my life forms a stable routine, I look for ways to change it. .658 .130 .217 .211
43. I prefer having a stable routine of experiencing a change in my life .756 .146 .215 .063
44. If I were to be informed that there’s going to be a significant change regarding the
way things are done at work, I would probably feel stressed. .271 .563 .269 .120
45. If I were to be informed that there’s going to be a change in one of my assignment at
work, prior to knowing what the change actually is, it would probably stress me out. .127 .690 .089 .179
46. When I am informed of a change of plans, I tense up a bit. -.027 .821 .000 .055
47. If my boss changed the criteria of evaluating employees, it would probably make me
feel uncomfortable even if I thought I’d do just as well without having to do any extra
work.
.240 .372 .272 .223
48. If in the middle of the work year, I were to be informed that there’s going to be a
change in the schedule of deadlines, prior to knowing what the change actually is, I
would probably presume that the change is worse
.291 .524 .101 .065
49. Changing plans seems like a real hassle to me .159 .063 .748 .291
50. When someone pressures me to change something, I tend to resist it even if I think
the change may ultimately benefit me. .246 .209 .709 .080
51. Once I have made plans, I am not likely to change them. .175 .147 .834 .201
52. I don’t change my mind easily .070 .096 .245 .716
53. I don’t often change my mind .193 .168 .106 .802
54. My views are very consistent over time. .202 .173 .170 .740
Total Rotation Sum of Squares
% of Variance (Rotated)
Cumulative % of Variance
2.589
17.262
17.262
2.223
14.819
32.082
2.156
14.376
46.458
2.062
13.746
60.203
KMO & Barlett’s Test: KMO = .891; Chi-Square =2027.072, df = 105, p-value = .000
Note. *ER1 = Routine seeking; ER2 = Emotional Reaction; ER3 = Short term focus; ER4 = Cognitive Rigidity.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
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The results also reveal that all the items of the research instrument (except item number
47) are appropriately loaded with the factor loading values ranging from .524 to .834. However,
the item number 47 (measuring the sub-construct emotional reaction) is found to possess the poor
factor loading (that is below than 0.4). Thus, the item number 47 founds eligible to be eliminated
from the final version of the research instrument. The results of KMO and Barlett’s test is also
found to be significant with the value of .891 (that is greater than .6) with the p-value of .000 (that
is less than .05). Figure 3.5 portrays the scree plot for the extracted factors of the construct
employee resistance. The scree plot also reflects that the four components (lying above the cut-off
value one) stand eligible for the retention.
Figure 3.5. Scree Plot for Employee Resistance Scale
Table 3.5 shows the results of exploratory factor analysis for the construct of business
model innovation. The results show that the 60.203 percent of cumulative variance on employee
resistance is explained by its ten third-order sub-constructs (that are new capabilities, new
technology or equipment, new partnerships, new processes, new offerings, new customers and
markets, new channels, new customer relationship, new revenue models and lastly, new cost
structures). The result also reflects that the sub-construct “new cost structures” accounts for the
highest variance (10.67 percent) among the remaining nine sub-constructs with the highest rotated
sum of squares value of 3.52. On the other hand, the sub-construct “new customer relationship” is
found to possess the lowest variance (3.72 percent) with the lowest rotated sum of squares value
of 1.22.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
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Table 3.5. Exploratory Factor Analysis for Business Model Innovation Scale
Items
Factors
1
*B10
2
*B5
3
*B3
4
*B2
5
*B1
6
*B9
7
*B6
8
*B4
9
*B7
10
*B8
55. Our employees constantly receive
training in order to develop new
competences
.114 -.042 .025 .127 .813 .074 .037 .074 .013 .028
56. Relative to our direct competitors,
our employees have very up-to-date
knowledge and capabilities.
.098 .030 -.046 .072 .893 .089 .117 .108 .000 .005
57. We constantly reflect on which new
competencies need to be established in
order to adapt to changing market
requirements.
.061 -.031 .034 .077 .889 .148 .049 .132 -.038 -.059
58. We keep the technical resources of
our company up-to-date. .070 .091 .028 .807 .168 .134 .077 .134 -.018 .043
59. Relative to our competitors our
technical equipment is very innovative. .116 .044 .013 .910 .065 .109 .131 .190 .034 -.008
60. We regularly utilize new technical
opportunities in order to extend our
product and service portfolio.
.113 .054 .028 .932 .065 .069 .088 .172 .032 -.13
61. We are constantly searching for new
collaboration partners. .102 .103 .057 -.222 .253 -.401 .157 .181 .264 .310
62. We regularly utilize opportunities
that arise from integration of new
partners into our processes.
.042 -.060 .943 -.001 -.007 .002 .048 .000 .039 .015
63. We regularly evaluate the potential
benefits of outsourcing. .047 -.041 .951 .013 -.001 .001 -.002 .037 .018 .001
64. New collaboration partners regularly
help us to further develop our business
model.
.049 -.036 .955 -.003 -.033 .020 .018 .014 .007 .006
65. We were recently able to
significantly improve our internal
processes.
.201 .237 .073 .051 .184 .364 .178 .693 .040 .040
66. We utilize innovative procedures and
processes during the manufacturing of
our products as well as in all business
processes.
.236 .117 .008 .266 .093 .128 .101 .842 .026 -.012
67. Existing processes are regularly
assessed and significantly changed if
needed.
.121 .138 -.004 .314 .174 .123 .111 .836 .022 .004
68. We regularly address new, unmet
customer needs. .116 .940 -.049 .075 -.046 .142 .042 .125 .084 .079
69. Our products or services are very
innovative in relation to our competitors. .109 .901 .039 .063 .016 .158 .048 .146 .083 .050
70. Our products regularly solve
customer needs, which were not solved
by competitors.
.107 .934 .075 .077 -.046 .146 .060 .135 .086 .081
71. We regularly take opportunities that
arise in new or growing markets. .011 .052 .048 .192 -.039 .115 .760 .091 -.009 -.025
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
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72. We regularly address new, unserved
market segments. .006 .045 -.002 .052 .173 .053 .851 .130 -.006 -.002
73. We are constantly seeking new
customer segments and markets for our
products and services.
-.025 .060 -.008 .070 .145 .244 .831 .027 .019 -.025
74. We regularly utilize new distribution
channels for our products and services. .004 .157 .015 -.007 -.017 .128 .008 .043 .907 .002
75. Constant changes of our channels
have led to improved efficiency of our
channel functions.
.003 .353 .008 -.245 .235 .263 .054 -.120 .103 -.376
76. We consistently change our portfolio
of distribution channels. -.034 .079 .029 .048 -.008 .093 .009 .015 .920 .056
77. We try to increase customer retention
by new service offerings. -.008 .000 .014 .016 -.005 .134 -.064 -.001 -.039 .734
78. We emphasize innovative/modern
actions to increase customer retention
(e.g. CRM).
.111 .367 -.044 .021 -.004 .068 .045 -.032 .177 .614
79. We recently took many actions in
order to strengthen customer
relationships.
.057 -.026 -.379 -.112 -.138 -.106 .356 .003 .067 .012
80. We recently developed new revenue
opportunities (e.g. additional sales, cross-
selling).
.232 .315 .030 .220 .070 .529 -.063 .339 .151 .019
81. We increasingly offer integrated
services (e.g. maintenance contracts) in
order to realize long-term financial
returns.
.212 .136 .036 .118 .194 .748 .262 .145 .157 .139
82. We recently complemented or
replaced one-time transaction revenues
with long-term recurring revenue models
(e.g. Leasing).
.209 .240 .062 .065 .118 .755 .212 .200 .108 .082
83. We do not rely on the durability of
our existing revenue sources. .178 .272 .009 .147 .251 .668 .222 .231 .100 .136
84. We regularly reflect on our price-
quantity strategy. .924 .118 .038 .070 .061 .102 .031 .120 -.016 .006
85. We actively seek opportunities to
save manufacturing costs. .866 .060 .036 .045 .086 .067 -.057 .096 .004 .040
86. Our production costs are constantly
examined and if necessary amended
according to market prices. .803 .056 -.003 .102 .091 .181 .041 .103 .001 .045
87. We regularly utilize opportunities
which arise through price differentiation. .926 .115 .047 .080 .061 .089 .021 .116 -.014 .006
Total Rotation Sum of Squares
% of Variance (Rotated)
Cumulative % of Variance
3.521
10.670
10.670
3.273
9.917
20.58
2.891
8.760
29.34
2.844
8.619
37.965
2.697
8.173
46.139
2.578
7.812
53.95
2.439
7.392
61.34
2.417
7.325
68.66
1.887
5.719
74.38
1.229
3.724
78.11
KMO & Barlett’s Test: KMO = .808; Chi-Square =13359.552, df = 528, p-value = .000
Note. *B1 = New capabilities; B2 = New technology / equipment, B3 = New partnerships; B4 = New processes; B5
= New offerings; B6 = New customers and markets; B7 = New channels; B8 = New customer relationship; B9 = New
revenue models; B10 = New cost structures.
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The results also revealed that all the items of the research instrument (except item number
61, 75, 79) are appropriately loaded with the factor loading values ranging from .529 to .955.
However, the three items 61, 75 and 79 (measuring the sub-constructs new partnerships, new
channels, and new customer relationships respectively) are found to possess the poor factor loading
(that is below than 0.4). Thus, these items (i.e. 61, 74 and 79) are found eligible to be eliminated
from the final version of the research instrument. The results of KMO and Barlett’s Test is also
found to be significant with the value of .808 (that is greater than .6) with the p-value of .000 (that
is less than .05). Figure 3.6 portrays the scree plot for business model innovation.
Figure 3.6. Scree Plot for Business Model Innovation Scale
The scree plot also reflects that the ten components (lying above the cut-off value one)
stand eligible for the retention. Table 3.6 summarizes the overall results of exploratory factor
analysis for all the constructs of this research study. It is pertinent to mention here, that one of the
objectives of conducting the exploratory factor analysis is to reduce the data with more defined
clusters (in form of factors). Similarly, it is found that the total six items (that are 8, 20, 47, 61, 75
and 79) qualify to be eliminated due to cross loading or poor factor loadings. Thus, it reduces the
earlier ninety (90) items research instrument to the eighty-four (84) items research instrument for
the measurement of the five constructs of this research study. Thus, all the basic conditions of
exploratory factor analysis are successfully met for the five constructs of this research work that
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
98
are innovation capabilities, innovation success, management entrepreneurial orientation, employee
resistance, and business model innovation).
Table 3.6. Summarizing the Overall Results of Exploratory Factor Analysis
Constructs Sub-Constructs Total
Items
Items
removed
Items
retained in
scale
Innovation
Capabilities
Sensing user needs 3 0 3
Sensing technological options 3 0 3 Conceptualization 3 1 2 Coproducing and Orchestrating 3 0 3 Scaling and Stretching 3 0 3
15 1 14
Innovation
Success
Short term success 5 1 4
Long term success 5 0 5
Indirect success 3 0 3
13 1 12
Management
Entrepreneurial
Orientation
Ready to innovate 3 0 3
Aggressively competitiveness 2 0 2
Market Proactiveness 3 0 3
Risk taking 3 0 3
11 0 11
Employee
Resistance
Routine seeking 4 0 4
Emotional Reaction 5 1 4
Short term focus 3 0 3
Cognitive Rigidity 3 0 3
15 1 14
Business
Model
Innovation
New capabilities 3 0 3
New technology 3 0 3
New partnerships 4 1 3
New processes 3 0 3
New offerings 3 0 3
New customer and markets 3 0 3
New channels 3 1 2
New customer relationships 3 1 2
New revenue models 4 0 4
New cost structures 4 0 4
33 3 30
Demographics 3 -- 3
Total Items 90 6 84
3.5.4. Construct reliability (Cronbach alpha).
The construct reliability reflects that all the items measuring a single construct are
consistent with each other (Sekaran, 2003). The Cronbach alpha value is generally checked in
order to test the construct reliability (Sekaran, 2003). It is believed that the values above and equals
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
99
to the 0.6 are minimally required for the items of the construct to be claimed as reliable (Sekaran,
2003). Table 3.7 shows the results of Cronbach alpha reliability estimates for all the research
constructs and sub-constructs of this research work.
Table 3.7. Reliability Analysis of Constructs and Sub-constructs after Extraction
Constructs Sub-Constructs
Total
Items after
extraction
Cronbach
alpha value
Innovation
Capabilities
Sensing user needs 3 .822
Sensing technological options 3 .815
Conceptualization 2 .739
Coproducing and Orchestrating 3 .779
Scaling and Stretching 3 .675
14 .841
Innovation
Success
Short term success 4 .864
Long term success 5 .770
Indirect success 3 .810
12 .876
Management
Entrepreneurial
Orientation
Ready to innovate 3 .833
Aggressively competitiveness 2 .739
Market Proactiveness 3 .815
Risk-taking 3 .779
11 .830
Employee
Resistance
Routine seeking 4 .799
Emotional Reaction 4 .759
Short term focus 3 .774
Cognitive Rigidity 3 .731
14 .860
Business
Model
Innovation
New capabilities 3 .886
New technology 3 .925
New partnerships 3 .958
New processes 3 .899
New offerings 3 .974
New customer and markets 3 .828
New channels 2 .862
New customer relationships 2 .950
New revenue models 4 .878
New cost structures 4 .926
30 .885
Total items 81 .891
The results show that all the five research constructs of this research study (that are
innovation capabilities, innovation success, entrepreneurial orientation, employee resistance and
business model innovation) possess the acceptable Cronbach alpha value of .841, .876, .830, .860
and .885 respectively. Furthermore, it is also found that all the sub-constructs of these five study
variables also possess the acceptable Cronbach alpha values ranging from .675 to .958.
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Thus, the basic condition on construct reliability for the five study variables (innovation
capabilities, innovation success, management entrepreneurial orientation, employee resistance and
business model innovation) is also found to be consistent.
3.5.5. Convergent validity and item reliability (confirmatory factor analysis).
Convergent validity refers to the extent to which the measures of the construct or sub-
construct (that are theoretically correlated) are factually correlated with each other or not (Sekaran,
2003). Koufteros (1999) explain that the convergent validity can be checked by overlooking the
two essential aspects of item’s squared correlation values (that is also known as item reliability)
and the t-value (the ratio of factor loading and error terms). These two parameters can be calculated
through confirmatory factor analysis (Koufteros, 1999). It is also pertinent to mention that the
dimensionality assessment and model fit indices are also essential performance parameters for the
validity of research instrument. And these dimensionality assessment and model fit indices can
only be checked through confirmatory factor analysis. The results of confirmatory factor analysis
for all the constructs of this research study are detailed in table 3.8 in appendix-II.
The results revealed that all the remaining eighty one (81) items (six items qualified to
eliminate during construct validity) measuring the five research constructs of this study possess
the significant factor loading (that is above than 0.4) ranging from .503 to .999. Items t-values are
calculated by comparing (i.e. ratio of) the factor loadings with their standard errors (Bollen, 1989).
Higher factor loadings in comparison to their standard error refers that stronger these item
measures their constructs. The t-values above or equal to 2 are considered to be significant (Bollen,
1989). The results reveal that the t-value of all the items are significant with the values (greater
than 2) ranging from 5.405 to 997. It means that all these items are significantly related to their
respective constructs.
The second parameter of convergent validity is item reliability (R square value) that should
be above than 0.5 (Bollen, 1989; Koufteros, 1999). It is found that all the items (except item
number 14, 23, 42 and 48) possess the R square value greater than 0.59. It reflects that these items
possess the significant item reliability. The items (ie. 14, 23, 42 and 48) possessing the R square
value less than 0.5 can be regarded as less performers and qualifies to be dropped from the
respective scale (Koufteros, 1999). Thus, four items (14, 23, 42 and 48) qualifies to be eliminated
during this iterative process of confirmatory factor analysis.
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The model fitness of the five constructs are also checked in confirmatory factor analysis.
Some researchers explain that the ratio of CMIN to degree of freedom below or equals to three (3)
represents the goodness fit of the measurement model (Marsh and Hocevar, 1985; Joreskog and
Sorbom, 1993). The results show that all the five constructs namely innovation capabilities,
innovation success, management entrepreneurial orientation, employee resistance and business
model innovation possess the good parsimonious fit with CMIN / df values of 2.01, 2.62, 1.69,
2.29 and 2.37 with the p-values of .000, .000, .000, .000 and .000 respectively.
The other model fitness measures such as absolute fitness measures and incremental fitness
measures of these five constructs are also checked. It is believed that the score of one (1) for
incremental fitness measures such as comparative fit index (CFI), adjusted goodness of fit (AGFI),
tucker lewis index (TLI) and normed fit index (NFI) reflects the perfect model (Bentler, 1972).
Tanaka and Huba (1985) report that the value of adjusted goodness of fit (AGFI) and goodness of
fit (GFI) should not be less than 0.9 for model to be claimed as good. Similarly, some researchers
also report that the value of tucker lewis index (TLI) and normed fit index (NFI) should not be less
than 0.9 (Bentler and Bonett, 1980; Bollen, 1989). Table 3.8 shows that the values of incremental
fit measures of NFI, GFI, AGFI and TLI for five constructs of study are found to be above than
0.9 that reflects the good fitness of measurement models. The absolute fit measures such as root
mean square error of approximation (RMSEA), standardized root mean square residual (SRMR)
and p of close fit (PCLOSE) are also checked. These measures represents the bad fitness of model.
Browne and Cudeck (1993) report that the values of bad fitness measures SRMR and RMSEA
should be less than or equal to .08. The values higher to .08 reflects the bad fitness of model and
the value closer to zero (but less than .08) reflects the good fitness of model. Table 3.8 shows that
value of RMSEA for five constructs namely innovation capabilities, innovation success,
management entrepreneurial orientation, employee resistance and business model innovation are
.049, .062, .041, .055 and .047 respectively. Kenny (2014) report the value of PCLOSE should be
greater than 0.05 for the good fit model in comparison to close fitting. The results of fit indices at
table 3.8 also show that the five constructs possess the PCLOSE values of .758, .603, .828, .906
and .628 that are greater than 0.05. Similarly, the value of SRMR for the five constructs are also
found to be less than .08 such as .014, .069, .012, .018 and .029. This also supports the good fitness
of measurement models.
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Summarizing, the confirmatory factor analysis carries the iteration of four more items (14,
23, 42 and 48). It yields the 80 items final version of research instrument that measures the five
constructs of this study namely innovation capabilities, innovation success, management
entrepreneurial orientation, employee resistance and business model innovation. It is also found
that this final version of research instrument possesses the adequate convergent validity (item t-
values and item reliability) and holds the adequate performance (i.e model fit indices) for
measurement of five constructs.
3.5.6. Discriminate validity (Fornell-Lacker criterion).
Discriminate validity checks the extent of correlation of all the measures who are supposed
to be uncorrelated with each other (Sekaran, 2003). Basically, it attempts to testify that all the
research measures who theoretically should be uncorrelated, also empirically carries no or either
low correlation. Pearson correlation is generally believed as the statistical tool for testing the
discriminate validity. Tian and Wilding (2008) report that the correlation values of .1 to .3 shows
the small or weak correlation, .3 to .5 shows the moderate correlation and .5 to .9 shows the large
or strong correlation and 1 shows the perfect correlation. Furr and Bacharach (2014) explain that
there should be no correlation among the research measures in order to fulfill the elementary pre-
requisites of this validity. However, the small or weak significant correlation would be acceptable
and may be interpreted as the meaningless or negligible if the sample size is larger (Furr &
Bacharach, 2014). Fornell and Larcker (1981) explain that the discriminate validity can be checked
by comparing the value of square correlation of measures with the value of average variance
extracted. The value of average variance extracted (AVE) should be larger than the square
correlation value (Fornell & Larcker, 1981).
The results of discriminate validity for the construct of innovation capabilities are shown
in table 3.9. It is found that the sub construct sensing user needs (IC1) possess the no correlation
with the sub-constructs sensing technological options (IC2), conceptualization (IC3) and
coproducing (IC4) with the non-significant p-value of .197, .175 and .235 respectively (that are
greater than .05). The results also reveal the sensing technological options (IC2) also possess no
correlation with the sub-constructs conceptualization (IC3), coproducing (IC4) and scaling
stretching (IC5) with the non-significant p-values of .280, .328 and .279 (greater than .05)
respectively.
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Table 3.9. Discriminate analysis of innovation capabilities scale
Dimensions IC1 IC2 IC3 IC4 IC5 AVE
Values
IC1
Correlation
Sig(2tailed)
R Square
1 .610
IC2
Correlation
Sig(2tailed)
R Square
.063
.197
.003
1 .573
IC3
Correlation
Sig(2tailed)
R Square
.066
.175
.004
.052
.280
.002
1 .631
IC4
Correlation
Sig(2tailed)
R Square
.058
.235
.003
.047
.328
.002
.021
.660
.001
1 .559
IC5
Correlation
Sig(2tailed)
R Square
.144
.003
.021
.053
.279
.003
.014
.771
.001
.133
.006
.017
1 .433
Note. *IC1 = Sensing user needs; IC2 = Sensing technological options; IC3 = Conceptualization; IC4 = Coproducing
and orchestrating; IC5 = Scaling and Stretching.
Similarly, it is also found that the sub construct conceptualization (IC3) possesses no
correlation with the sub-constructs coproducing (IC4) and scaling stretching (IC5) with the non-
significant p-values of .660 and .771 that are greater than .05. However, the sub-construct scaling
and stretching (IC5) is found to possess a significant weak correlation with the sub-construct
sensing user needs (IC1) and coproducing (IC4) with the correlation value of .144 and .133 with
the p-values of .003 and .006 that is also negligible.
It is also found that the average variance extracted value (.573) of sub construct sensing
technological options (IC2) is greater than the correlation squared value of .003. Similarly, the
average variance extracted value .631 of sub construct conceptualization (IC3) is also found to be
greater than the correlation squared values of .004 and .002. Table 3.9 also show that the average
variance extracted values .559 and .433 of sub-constructs coproducing (IC4) and scaling stretching
(IC5) are found to be greater than the correlation squared values of .003, .002, .001, .021, .003,
.001 and .017 respectively. Thus, these results of discriminate validity for the construct of
innovation capabilities are found to be satisfactory. Table 3.10 represents the results of
discriminate validity for the sub-constructs of innovation success.
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Table 3.10. Discriminate analysis of innovation success scale
Dimensions IS1 IS2 IS3 AVE
Values
IS1
Correlation
Sig(2tailed)
R Square
1
.615
IS2
Correlation
Sig(2tailed)
R Square
.143
.003
.021
1
.440
IS3
Correlation
Sig(2tailed)
R Square
.017
.723
.001
.038
.432
.001
1
.601
Note. *IS1 = Short term success; IS2 = Long term success; IS3 = Indirect Success.
It is found that the sub-construct long term success (IS2) possesses a weak correlation with
the sub-construct short term success (IS1) with the correlation value of .143 and p-value of .003 <
.05 that is negligible. The result also reveals that the average variance extracted value .440 of long
term success (IS2) is greater than the correlation squared value of .021. Table 3.10 also reflects
that the sub-construct indirect success (IS3) possesses no correlation with the sub-constructs short
term success (IS1) and long term success (IS2) with the non-significant p-values of .723 and .432
respectively. Furthermore, the results also show that the average variance extracted value .601 of
sub construct indirect success (IS3) is greater than the correlation squared values of .001 and .001.
Thus, these results fulfills the foremost assumption of this form of validity for the construct of
innovation success.
Table 3.11 represents the results of discriminate validity for the sub-constructs of
management entrepreneurial orientation. The results show that;
• The sub-construct aggressive competitiveness (EO2) possesses no correlation with the sub-
construct ready to innovate (EO1) with the p-value of .550 which is greater than .05. The result
also reveals that the average variance extracted value .632 of aggressive competitiveness (EO2)
is greater than the correlation squared value of .001.
• The sub construct market proactiveness (EO3) possesses no correlation with the sub construct
aggressive competitiveness (EO2) with the non-significant p-value of .395 that is greater than
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
105
.05. However, it possesses a weak correlation with the sub constructs ready to innovate (EO1)
with the correlation value of .183 and significant p-values of .000 < .05 that is also negligible.
Furthermore, the results also show that the average variance extracted values .568 of sub
construct market proactiveness (EO3) is larger than the correlation squared values of .033 and
.001.
• The sub construct risk-taking (EO4) possesses no correlation with the sub constructs market
proactiveness (EO3) with the non-significant p value of .189 that is greater than .05. However,
it is also found that risk taking (EO4) possesses the weak correlation with the sub constructs
ready to innovate (EO1) and aggressive competitiveness (EO2) with the correlation value of
.166 and .117 with the significant p-values of .001 and .016 respectively that are negligible.
Furthermore, the results also show that the average variance extracted value .558 of sub
construct risk taking (EO4) is greater than correlation square values of .027, .013 and .004.
Thus, these results fulfill the elementary assumption of discriminate validity for the
construct of management entrepreneurial orientation.
Table 3.11. Discriminate analysis of entrepreneurial orientation scale
Dimensions EO1 EO2 EO3 EO4 AVE
Values
EO1
Correlation
Sig(2tailed)
R Square
1
.621
EO2
Correlation
Sig(2tailed)
R Square
.029
.550
.001
1
.632
EO3
Correlation
Sig(2tailed)
R Square
.183
.000
.033
.041
.395
.001
1
.568
EO4
Correlation
Sig(2tailed)
R Square
.166
.001
.027
.117
.016
.013
.064
.189
.004
1
.558
Note. *EO1 = Ready to innovate; EO2 = Aggressively competitiveness; EO3 = Market Proactiveness; EO4 =
Risk Taking.
Table 3.12 represents the results of discriminate validity for the sub constructs of employee
resistance. The results showed that;
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106
• The sub construct emotional reaction (ER2) possesses no correlation with the sub construct
routine seeking (ER1) with the non-significant p-value of .738 that is greater than .05. The
result also reveals that the average variance extracted value .425 of emotional reaction (ER2)
is larger than the correlation squared value of .001.
• The sub construct short term focus (ER3) possesses no correlation with the sub construct
emotional reaction (ER2) and routine seeking (ER1) with the non-significant p-value of .280
and .372 that is greater than .05. Furthermore, the results also show that the average variance
extracted values .581 of sub construct short term focus (ER3) is larger than the correlation
squared values of .002 and .001.
• The sub construct cognitive rigidity (ER4) possess no correlation with the sub constructs short
term focus (ER3), emotional reaction (ER2) and routine seeking (ER1) with the non-significant
p values of .441, .246 and .385 that are greater than .05. It is also found that the average
variance extracted value .567 of sub construct cognitive rigidity (ER4) is larger than correlation
square values of .001, .003 and .001.
Thus, these results fulfill the elementary assumption of discriminate validity for the
construct of employee resistance.
Table 3.12. Discriminate analysis of employee resistance scale
Dimensions ER1 ER2 ER3 ER4 AVE
Values
ER1
Correlation
Sig(2tailed)
R Square
1
.629
ER2
Correlation
Sig(2tailed)
R Square
.016
.738
.001
1
.425
ER3
Correlation
Sig(2tailed)
R Square
.043
.372
.001
.052
.280
.002
1
.581
ER4
Correlation
Sig(2tailed)
R Square
.042
.385
.001
.056
.246
.003
.037
.441
.001
1
.567
Note. *ER1 = Routine seeking; ER2 = Emotional Reaction; ER3 = Short term focus; ER4 = Cognitive Rigidity.
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Table 3.13 represents the results of discriminate validity for the sub constructs of business
model innovation. The results showed that;
• The sub construct new technology (B2) possess weak correlation with the sub construct new
capabilities (B1) with the correlation value of .213 and significant p-value of .000 < .05 that is
negligible. The result also reveal that the average variance extracted value .924 of new
technology (B2) is greater than the correlation squared value of .045.
• The sub construct new partnerships (B3) possess no correlation with the sub construct new
technology (B2) and new capabilities (B1) with the non-significant p-value of .804 and .095
that are greater than .05. Furthermore, the results also shows that the average variance extracted
values .949 of sub construct new partnerships (B3) is greater than the correlation squared
values of .006 and .001.
• The sub constructs new processes (B4) possess the no correlation with the sub-constructs new
partnerships (B3) with the non-significant p values of .098 that is greater than .05. However,
the new processes (B4) possess weak correlation with the sub-constructs new technology (B2)
and new capabilities (B1) with the correlation values of .140 and .197 with the significant p-
values of .000 and .004 that are also negligible. It is also found that the average variance
extracted value .869 of sub construct new processes (B4) is greater than correlation square
values of .019, .038 and .006.
• The sub constructs new offerings (B5) possess no correlation with the sub-constructs new
capabilities (B1), new partnerships (B3) and new processes (B4) with the non-significant p
values of .555, .091 and .231 that are greater than .05. However, the new offerings (B5) possess
the weak correlation with the new technology (B2) with a correlation value of .169 and
significant p-values of .000 that is also negligible. It is also found that the average variance
extracted value .978 of sub construct new offerings (B5) is greater than correlation square
values of .001, .028, .006 and .003.
• The sub constructs new customers and markets (B6) possess no correlation with the sub-
constructs new partnerships (B3) and new processes (B4) with the non-significant p values of
.725 and .197 that are greater than .05. However, the new customers and markets (B6) possess
the weak correlation with the new capabilities (B1), new technology (B2) and new processes
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
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(B5) with correlation values of .218, .204, .149 and significant p-values of .000, .000, .002 that
are also negligible. It is also found that the average variance extracted value .943 of sub
construct new customers and markets (B6) is greater than correlation square values of .047,
.041, .001, .003 and .022.
Table 3.13. Discriminate analysis of business model innovation scale
Dimensions B1 B2 B3 B4 B5 B6 B7 B8 B9
B10
AVE
Values
B1
Correlation
Sig(2tailed)
R Square
1
.905
B2
Correlation
Sig(2tailed)
R Square
.213
.000
.045
1
.924
B3
Correlation
Sig(2tailed)
R Square
.012
.804
.001
.081
.095
.006
1
.949
B4
Correlation
Sig(2tailed)
R Square
.140
.004
.019
.197
.000
.038
.080
.098
.006
1
.869
B5
Correlation
Sig(2tailed)
R Square
.029
.555
.001
.169
.000
.028
.082
.091
.006
.058
.231
.003
1
.978
B6
Correlation
Sig(2tailed)
R Square
.218
.000
.047
.204
.000
.041
.017
.725
.001
.063
.197
.003
.149
.002
.022
1
.943
B7
Correlation
Sig(2tailed)
R Square
.008
.873
.001
.047
.330
.002
.028
.563
.001
.029
.555
.001
.234
.000
.054
.060
.216
.003
1
.880
B8
Correlation
Sig(2tailed)
R Square
.011
.827
.001
.020
.682
.001
.008
.867
.001
.062
.200
.003
.151
.002
.022
.001
.100
.000
.096
.048
.009
1
.555
B9
Correlation
Sig(2tailed)
R Square
.040
.404
.002
.009
.851
.001
.042
.381
.002
.012
.798
.001
.145
.003
.021
.061
.205
.003
.080
.098
.006
.042
.383
.002
1
.862
B10
Correlation
Sig(2tailed)
R Square
.003
.956
.000
.002
.965
.000
.049
.315
.002
.082
.091
.006
.012
.804
.001
.094
.053
.008
.039
.424
.001
.044
.364
.002
.137
.004
.018
1
.855
Note. *B1 = New capabilities; B2 = New technology / equipment, B3 = New partnerships; B4 = New processes;
B5 = New offerings; B6 = New customers and markets; B7 = New channels; B8 = New customer relationship; B9 =
New revenue models; B10 = New customer relationships.
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• The sub construct new channels (B7) possess no correlation with the sub-constructs new
capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4) and new
customers and markets (B6) with the non-significant p values of .873, .330, .563, .555 and
.216 that are greater than .05. However, the new channels (B7) possess the weak correlation
with the new processes (B5) with correlation values of .234 with a significant p-value of .000
that is also negligible. It is also found that the average variance extracted value .880 of sub
construct new channels (B7) is greater than correlation square values of .001, .002, .001, .001,
.054 and .003.
• The sub construct new customer relationships (B8) possess no correlation with the sub-
constructs new capabilities (B1), new technology (B2), new partnerships (B3), new processes
(B4) and new customers and markets (B6) with the non-significant p values of .827, .682, .867,
.200 and .100 that are greater than .05. However, the new customer relationships (B8) possess
the weak correlation with the new processes (B5) and new channels (B7) with correlation
values of .151, .096 with a significant p-value of .002, .048 that is also negligible. It is also
found that the average variance extracted value .555 of sub construct new customer
relationships (B8) is greater than correlation square values of .001, .001, .001, .003, .022, .000
and .009.
• The sub construct new revenue models (B9) possess no correlation with the sub-constructs
new capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4), new
customers and markets (B6), new channels (B7) and new customer relationships (B8) with the
non-significant p values of .404, .851, .381, .798, .205, .098 and .383 that are greater than .05.
However, the new revenue models (B9) possess the weak correlation with the new processes
(B5) with correlation values of .145 with a significant p-value of .003 that is also negligible. It
is also found that the average variance extracted value .862 of sub construct new revenue
models (B9) is greater than correlation square values of .002, .001, .002, .001, .021, .003, .006
and .002.
• The sub construct new cost structures (B10) possess no correlation with the sub constructs new
capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4), new
processes (B5), new customers and markets (B6), new channels (B7) and new customer
relationships (B8) with the non-significant p values of .956, .965, .312, .091, .804, .053, .424
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
110
and .364 that are greater than .05. However, the new cost structures (B10) possess the weak
correlation with new revenue models (B9) with correlation values of .137 with significant p-
value of .004 that is also negligible. It is also found that the average variance extracted value
.855 of sub construct new cost structures (B10) is greater than correlation square values of
.000, .000, .002, .006, .001, .008, .001, .002 and .018.
Table 3.14. Summarizing the Reliability and Validity Iteration Outcome
Constructs Sub-Constructs Initial
Items
Items
removed
in EFA
Items
removed
in CFA
Total
items
removed
Items
retained in
Final scale
Innovation
Capabilities
Sensing user needs 3 0 0 0 3
Sensing technological options 3 0 0 0 3 Conceptualization 3 1 0 1 2 Coproducing and Orchestrating 3 0 0 0 3 Scaling and Stretching 3 0 1 1 2
15 1 1 2 13
Innovation
Success
Short term success 5 1 0 1 4
Long term success 5 0 1 1 4
Indirect success 3 0 0 0 3
13 1 1 2 11
Management
Entrepreneurial
Orientation
Ready to innovate 3 0 0 0 3
Aggressively competitiveness 2 0 0 0 2
Market Proactiveness 3 0 0 0 3
Risk taking 3 0 0 0 3
11 0 0 0 11
Employee
Resistance
Routine seeking 4 0 1 1 3
Emotional Reaction 5 1 1 2 3
Short term focus 3 0 0 0 3
Cognitive Rigidity 3 0 0 0 3
15 1 2 3 12
Business
Model
Innovation
New capabilities 3 0 0 0 3
New technology 3 0 0 0 3
New partnerships 4 1 0 1 3
New processes 3 0 0 0 3
New offerings 3 0 0 0 3
New customer and markets 3 0 0 0 3
New channels 3 1 0 1 2
New customer relationships 3 1 0 1 2
New revenue models 4 0 0 0 4
New cost structures 4 0 0 0 4
33 3 0 3 30
Demographics 3 -- -- 0 3
Total Items 90 6 4 10 80
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Thus, these results satisfy the basic assumption of discriminate validity for the construct of
business model innovation. Table 3.14 summarizes the overall results of these reliability and
validity iteration process for all the five constructs.
It is found that the total ten items (that are 8, 14, 20, 23, 42, 47, 48, 61, 75 and 79) qualify
to be eliminated due to cross loading in EFA, poor factor loadings in EFA and poor item reliability
in CFA. Thus, it reduces the earlier ninety (90) items research instrument to the eighty (80) items
research instrument for the measurement of the five constructs of this research study namely
innovation capabilities, innovation success, management entrepreneurial orientation, employee
resistance and business model innovation. It can also be claimed that this 80-item final version of
iterative purified scale carries the adequate construct validity, convergent validity, sufficient
construct reliability, adequate discriminate validity and holds the adequate performance (i.e model
fit indices) for measurement of five constructs. It is pertinent to mention here that some researchers
Chamsuk, Fongsuwan and Takala (2017), Narcizo, Canen and Tammela (2017) comprehend the
need to empirically validate the operationalization of innovation capabilities with a core objective
to bring uniformity in the operationalization of construct globally. Similarly, some other
researchers Foss and Saebi (2018); Foss and Saebi (2017); Clauss (2017); Scheider and Spieth
(2014) indicated that the majority of the previous researches on the concept of business model
innovation have opted for qualitative approach with no or less empirical analysis (Gap-1 of this
research work). This previously indicate the need to empirically test and validate the dimensions
of business model innovation (Foss & Saebi, 2018, 2017; Hossain, 2018; Bashir & Verma, 2019;
Clauss, 2017; Scheider & Spieth, 2014).
Thus, the detailed reliability and validity iterative process for testing the psychometric
properties of the above five constructs (namely innovation capabilities, innovation success,
entrepreneurial orientation, employee resistance and business model innovation) attempts to
successfully address the research objective one of this research work by further contributing to this
research gap.
3.6. Statistical Techniques
The collected data is analyzed by using the SPSS (version 20.0) and AMOS (version 22.0)
software. The demographic analysis of the respondents is checked to get deep insight into the
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
112
psychometric attributes of the sample. The descriptive statistics including means and standard
deviation are calculated for each construct of the study. In order to check the psychometric
characteristics of the research instrument, the validity analysis including construct validity,
discriminate validity and reliability analysis is checked through the statistical techniques of
exploratory factor analysis, Cronbach alpha value, confirmatory factor analysis, and Pearson
correlation. Before hypotheses testing, the basic assumptions of regressions are checked including
linearity, multicollinearity and data normality. Hayes (2017) regression-based process approach,
statistical technique are used for the testing of hypotheses and proposed theoretical model of this
research work. Finally, the overall model fitness measures are calculated through structural
equation modeling.
3.7. Chapter Summary
This chapter has discussed in detail the formation of the theoretical framework and theoretical
underpinnings along with the development of ten testable research hypotheses. The hypothesized
theoretical framework of this research study contains five constructs. The direct effect of
innovation capabilities (independent variable) on business model innovation (dependent variable)
has been hypothesized. The mediation role of service innovation success in between the direct
effect of the independent and dependent variable is also hypothesized. In addition to this, the
moderating effect of employee resistance (moderator 1) on the relationship of innovation
capabilities - service innovation success and the innovation capabilities – business model
innovation is also proposed. Furthermore, the moderating effect of management entrepreneurial
orientation (moderator 2) is also hypothesized on the direct and indirect effects of innovation
capabilities (independent variable) and business model innovation (dependent variable). Ten
testable research hypotheses are developed. The operational definitions of the research constructs
are also stated. Finally, the development of a research instrument for the collection of data from
target respondents and methodology of research survey are discussed. This chapter has discussed
in depth the methodology adopted to address the six posed research questions of this research
work. Quantitative research design with an empirical research approach has been used. The
research survey has been as a research strategy and the research questionnaire has been used as the
tool for the collection of data. The research instrument has been developed by adopted the items
from the previous existing researches. The research questionnaires of this research work constitute
the total ninety (90) items. The population constitutes the cellular companies of Pakistan. The
population frame consists of 1274 approximate senior chiefs, departmental heads and middle
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
113
managers from four cellular companies (namely Mobilink, Warid, Zong, and Telenor). Using
Krejice and Morgan (1980) illustration for a finite population, 295 number of respondents were
required to ensure the generalizability of the results. Five hundred and fifty (550) participants are
picked from the population frame under the simple random sampling strategy. However, four
hundred and twenty-seven (427) completely filled questionnaires are received back with the
overall response rate of 77.63 percent. The validity and reliability of research measures are also
checked in light of Kouftero’s approach (1999). The construct validity is analyzed using the
statistical technique of exploratory factor analysis. The results of exploratory factor analysis show
that all the basic conditions of exploratory factor analysis are successfully met for the five
constructs. However, the total six items (that are 8, 20, 47, 61, 75 and 79) qualify to be eliminated
due to cross loading or poor factor loadings. Resultantly, it reduces the earlier ninety (90) items to
the eighty-four (84) items in research instrument. The construct reliability is checked through
Cronbach alpha value and it is found that all the five constructs and sub-constructs possess the
acceptable values ranging from .675 to .958. The convergent validity and item reliability of the
constructs are also checked through confirmatory factor analysis. The results reveal that the t-
value of all the items are significant with the values (greater than 2) ranging from 5.405 to 997. It
means that all these items are significantly related to their respective constructs. However, the item
reliability of the four items (ie. 14, 23, 42 and 48) are not found to be significant and therefore,
qualifies to be eliminated during this iterative process of confirmatory factor analysis. It
consequents the final version of a research instrument to comprise of 80 items at this stage. The
discriminate validity of all the constructs is also checked through correlation values of sub-
constructs and the comparison of squared correlation value with the calculated average variance
extracted (AVE) values. The results show that the sub-constructs of all the five constructs possess
weak or no correlation. The comparison of the squared correlation of sub-constructs with the
calculated average variance extracted (AVE) values are also found to be in acceptable ranges.
These results satisfy the basic criteria of discriminate validity. Thus, this 80-item final version of
iterative purified scale carries the adequate construct validity, convergent validity, sufficient
construct reliability, adequate discriminate validity and holds the adequate performance (i.e. model
fit indices) for measurement of five constructs. This further shows the eligibility of the data for
hypothesis testing. The collected data may be analyzed by different statistical techniques using the
SPSS (version 20.0) and AMOS (version 22.0) software.
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CHAPTER 4
DATA ANALYSIS AND RESULTS
This chapter explains in detail the results of the statistical techniques applied to the collected data.
This section attempts to empirically answer the research questions of this research work and further
provides the empirical evidence for the actuality of the hypothesized relationships of constructs.
In this regard, the demographic analysis, descriptive analysis, correlation of research measures and
Hayes (2017) based moderation mediation analysis have been conducted in detail.
4.1. Demographic Characteristics
The results of the demographic analysis of the participants of the research survey are
discussed in table 4.1. The results revealed that 71.19 percent of the respondent with the frequency
of 304 were males and the remaining 28.81 percent were female. The results also showed that 3.98
percent of respondents were aged less than thirty years, 83.61 percent of the (357) respondents
were aged between 31 years - 40 years and the residual 53 respondents (12.41 percent) were aged
above than forty years. Furthermore, it was also found that 16.9 percent of respondents (71) were
graduate, 71.90 percent of respondents (302) were post-graduate qualified and the remaining 11.20
percent with the frequency of 47 were MS or MPhil or Doctorate or equivalent qualified.
Table 4.1. Demographic Analysis of Research Survey Participants
S # Demographics Classifications Frequency Percentage
Males 304 71.19
1 Gender Females 123 28.81
Total 427 100
2 Age
Less than 30 years 17 3.98
31 yrs. – 40 yrs. 357 83.61
Above than 40 yrs. 53 12.41
Total 427 100
3 Education
Graduation 71 16.90
Post-Graduation 302 71.90
MS or MPhil or Ph.D. and Equivalent 47 11.20
Total 427 100
4.2. Descriptive Analysis
The results of the descriptive analysis are shown in table 4.2. The construct innovation
capabilities, service innovation success, entrepreneurial orientation are measured by 7-point Likert
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
115
scale. Whereas the employee resistance is measured by 6-point Likert scale and business model
innovation is measured by 5-point Likert scale. The results show that the average mean score of
innovation capabilities, service innovation success, and entrepreneurial orientation falls under the
category of “Agree” of seven-point Likert scale with the values of 5.0334, 5.0423 and 5.1370
respectively. It was also found that the mean score of employee resistance falls under the category
of “disagree” of six-point Likert scale with the value of 2.1734. Similarly, the mean score of
business model innovation falls in the category of “agree” of five-point Likert scale with the value
of 4.1647.
Table 4.2. Descriptive Analysis among Study Variables
Variables Mean S.D Minimum Maximum
Innovation capabilities 5.0334 .757 2.86 7.00
Service innovation success 5.0423 .615 3.29 6.79
Entrepreneurial orientation 5.1370 .796 2.85 7.0
Employee resistance 2.1734 .659 1.0 4.06
Business model innovation 4.1647 .510 2.0 4.50
4.3. Correlation Analysis among Study Variables
Formal correlation is checked among the study variables with an objective to check the
nature and magnitude of the relationship among variables once before testing the research
hypotheses. Table 4.3 explains the results of correlation analysis, mean and standard deviations of
study variables. The results show that the innovation capabilities are positive correlated with
service innovation success (r=.584, p =.000) and business model innovation (r = .598, p = .000).
Similarly, it is also found that the service innovation success is strongly positive correlated with
entrepreneurial orientation (r = .577; p = .000) and business model innovation (r = .568; p = .000).
However, the service innovation success is negatively strongly correlated with the employee
resistance (r = -.511; p = .000). Table 4.3 also shows that the innovation capabilities possess the
weak correlation with the entrepreneurial orientation (r = .119; p = .000) and negative weak
correlation with employee resistance (r = -.109; p = .000).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
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Table 4.3. Correlation Analysis among Study Variables
Variables IC IS EO ER BMI
IC Correlation
Sig(2tailed)
1
IS Correlation
Sig(2tailed)
.584
.000
1
EO Correlation
Sig(2tailed)
.119
.000
.577
.000
1
ER Correlation
Sig(2tailed)
-.109
.000
-.511
.000
-.157
.001
1
BMI Correlation
Sig(2tailed)
.598
.000
.568
.000
.694
.000
-.652
.002
1
4.4. Hypotheses Testing - Regression based Conditional Process Analysis
The hypothesized research model of this study consists of five research variables. It
portrays that the innovation capabilities (independent variable) not only possess the direct effect
on the business model innovation (dependent variable) but it also holds the indirect effect on
business model innovation through the mediation effect of innovation success. Furthermore, the
hypothesized research model of this study also illustrates that this indirect effect is further
moderated by the two variables of employee resistance and management entrepreneurial
orientation. This indicates that the effect of innovation capabilities (independent variable) on
business model innovation (dependent variable) is conditional in nature that is dependent upon the
magnitude and nature of the influence of these mediating and moderating variables.
It is pertinent to mention here that the structural equation modeling is considered as the
most widely used statistical technique for the testing of latent and observed structural relationships.
It is also believed by some researchers that the structural equation modeling is one of those
statistical techniques that constitutes the integrated characteristics of other statistical methods such
as MANOVA, regression, correlation and factor analysis etc. (Nachtigall, Kroehne, Funke &
Steyer, 2003; Eid, 2000). However, the recent researches claim that the structural equation
modeling does not examine the mediation effects that further leads to the erroneous conclusions
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
117
(Hair et al., 2012, 2013; Hair, Sarstedt, Hopkin & Kuppelwieser, 2014). Hair et al., (2014) argue that
there is a need for future statistical researches to come up with statistical solutions of moderated
mediation and mediated moderation analyses and this statistical research gap was later on filled by
Hayes (2017, 2018) regression based conditional process analysis. It is pertinent to mention here that
the hypothesized theoretical framework of this research work is dually moderated mediation research
model. Therefore, this research work has used the Hayes (2017) regression based conditional
process analysis for the testing of hypothesized relationships. The testing of all the proposed
hypotheses of this research work are embarked in following manner;
• Addressing Gap 2 - Testing the effect of X on Y. In this stage, the simple regression is
conducted to check the effect of service innovation capabilities (X) on business model
innovation (Y). This stage empirically tests the proposed hypotheses 1 of this study.
• Addressing Gap 3 - Testing the mediating effect of M on the relationship of X on Y. In
this stage, the simple mediation analysis (Hayes model 4 process template) is conducted to
check the mediation effect of service innovation success (M) on innovation capabilities (X)
and business model innovation (Y) relationship. This stage empirically tests the proposed
hypotheses 2, 3 and 4 of this study.
• Addressing Gap 4 – Testing the moderation effect of W. This stage is further categorized
into two sub-stages for further elaboration. At first instance, the moderation effect of
entrepreneurial orientation (W) is checked on the effect of innovation capabilities (X) and
service innovation success (M). This sub-stage empirically tests the proposed hypothesis 5 of
this study. At the second instance, the moderation effect of entrepreneurial orientation (W) is
checked on the direct effect of innovation capabilities (X) and business model innovation (Y)
that empirically tests the proposed hypothesis 6 of this research work.
• Addressing Gap 5 – Testing the moderation effect of Z. Similarly, this stage is also further
categorized into two sub-stages for further elaboration. At first instance, the moderation effect
of employee resistance (Z) is checked on the effect of innovation capabilities (X) and service
innovation success (M). This sub-stage empirically tests the proposed hypothesis 7 of this
study. At the second instance, the moderation effect of employee resistance (Z) is checked on
the direct effect of innovation capabilities (X) and business model innovation (Y) that
empirically tests the proposed hypothesis 8 of this research work.
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• Addressing Gap 6 – Testing the moderation effect of W and Z on the relationship of X
on Y with putative mediator held constant. In this stage, the moderation effect of both
entrepreneurial orientation (W) and employee resistance (Z) simultaneously checked on the
direct relationship of innovation capabilities (X) and business model innovation (Y) with
considering the service innovation success (M) being held constant. This stage empirically
tests the proposed hypothesis 9 of this research work.
• Addressing Gap 6 – Testing the moderation effect of W and Z on relationship of X on Y
through mediation effect of M. In this final stage, all the above mediation and moderation
indirect effects (of stage one to stage four) are combined and simultaneously checked on the
relationship of innovation capabilities (X) and business model innovation (Y). This stage
empirically tests the hypothesized theoretical model of this research study in the form of
proposed hypothesis 10 of this research work.
Before proceeding for these step-wise hypotheses testing phenomenon, the assumptions of
regression analysis are also needed to be checked as under;
4.4.1. Assumptions of Regression analysis.
Regression Analysis is one of powerful parametric statistical test that requires some basic
assumptions to be met first. There are three basic assumptions of regression analysis that are a
normal distribution of data, linearity and multicollinearity.
4.4.1.1. Data normality.
Normal distribution of data is considered as the foremost basic assumption of regression
analysis. It can be checked through the statistical test of the Kolmogorov-Smirnov test and the
values of skewness, kurtosis (Hair et al., 2009). If the K-S test seems to significant (that is p-value
less than .05) then it refers to the data as “non-normal”. Similarly, if K-S tests are found to be non-
significant (that is p-value greater than .05) then the data is characterized as “normal” (Hair et al.,
2009). Skewness refers to the symmetry of data distribution and the normal data carries the
perfectly symmetric distribution (Hair et al., 2009). Data is termed as positively skewed if the
majority of scores are clustered at the left side with their tails extending towards the right side
(Hair et al., 2009). On the other hand, data is termed as negatively skewed if the majority of scores
are found to be clustered at right sight with their extended tails at left side. Kurtosis refers to the
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weakness of the data distribution and the data is termed “normal” if its distribution is found to bell-
shaped (no too flat nor too peaked). The data is termed as normal if its value of skewness and
kurtosis falls in acceptable range of +1 and -1 (Hair et al., 2009).
Table 4.4. Results of Data Normality
Variables K-S Normality Test
Skewness Kurtosis Statistic Df Sig.
Innovation capabilities .036 427 .199 .054 .062
Service Innovation success .042 427 .075 .062 .118
Entrepreneurial orientation .036 427 .200 .029 .226
Employee resistance .034 427 .150 .023 .190
Business model innovation .033 427 .062 . 018 .169
Table 4.4 depicts the results of data normality of study variables. It is found that the sample
data of five study variables of this research work is a factual representation of the expected data
distribution with the non-significant p-values of .199, .075, .200, .150 and .062 > .05. The value
of skewness and kurtosis of the study variables are also found to lie within the range of .018 - .226
(that falls in an acceptable range of +1 and -1). Thus, these results imitate that the basic assumption
of data normality hence triumphs.
4.4.1.2. Linearity of residuals.
The linearity of residuals is another crucial assumption of regression analysis. It basically
denotes that the standardized residuals and the values of dependent variable are directly
proportional to each other with a defined linear pattern (Hair et al., 2009). A scatterplot is graphed
in which the values of dependent variable are marked at vertical y-axis and the values of
standardized residuals are plotted at horizontal x-axis. If the produced scatterplot follows a linear
pattern (not curvilinear), then it is believed that the assumption of linearity of residuals is truly met
(Hair et al., 2009). Figure 4.1 shows the scatterplot graph among the values of dependent variable
(business model innovation) at vertical y-axis and standardized residuals at horizontal x-axis. It
clearly shows the linear relationship and no curve can be seen among the values of dependent
variable and standardized residuals. Thus, the assumption of linearity of residuals is met.
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Figure 4.1. Scatterplot depicting Linearity of Residuals
4.4.1.3. Multicollinearity.
Multicollinearity is another critical assumption of regression analysis. Multicollinearity is
considered to occur when any one of the explanatory variable (independent or moderator) possess
a strong linear relationship with others with strong accuracy of prediction (Hair et al., 2009).
Perfect multicollinearity or high multicollinearity is the violation of assumptions of regression
analysis. Multicollinearity is checked by witnessing the values of ‘Tolerance’ or ‘Variance
inflation factor’ (VIF) of each study variable (Hair et al., 2009). Tolerance represents the
variability of one explanatory variable that is not explained by the other explanatory variables.
Whereas, the variance inflation factor (VIF) is the inverse of tolerance. It is believed that the
tolerance value less than 0.10 and variance inflation factor value of 10 or above indicates the issue
of multicollinearity (Hair et al., 2009). Table 4.5 depicts the results of multicollinearity for all the
study variables of this research work. The results show that the tolerance value of all study
variables is greater than 0.10 with the values .649, .561, .767 and .841 that is in acceptable range.
Similarly, it is also found that variance inflation factor values of all study variables are below 10
with the values of 1.540, 1.782, 1.303 and 1.063. Thus, these results reveal that there exists no
issue of multicollinearity in data.
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Table 4.5. Multicollinearity Statistics of Study Variables
Variables Tolerance VIF
Innovation capabilities .649 1.540
Service Innovation success .561 1.782
Entrepreneurial orientation .767 1.303
Employee resistance .841 1.063
Note. Dependent variable = business model innovation
4.4.2. Addressing Gap two - Testing the effect of ‘X’ on ‘Y’ (H-1)
Table 4.6 illustrates the effect of innovation capabilities (IV) on business model innovation
(DV). It showed that only 35.76% of variance on business model innovation is explained by
innovation capabilities with positive coefficient effect of .2813 and p-value of .001 that is less than
.05. Thus, these results reflects that there exists a positive significant effect of innovation
capabilities (independent variable) on business model innovation (dependent variable). Hence, it
testifies the hypothesis one (H1: Innovation capabilities may possess positive influence on
business model innovation) as correct.
Table 4.6. Regressing IV against DV in Simple Linear Regression
Variable Coeff Se T P
Constant 2.3658 .1511
Innovation capabilities .2813 .0438 6.4267 .000
R2 = 0.3576, F (1, 425) = 41.302, p = 0.000
4.4.3. Addressing Gap Three - Testing the mediation effect of ‘M’ on relationship of
‘X’ on ‘Y’ (H2-H4)
The mediation effect of service innovation success on the relationship of innovation
capabilities (X) and business model innovation (Y) is checked through the regression-based
process macro of Hayes (2017) using model 4.
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Table 4.7 portrays the mediation model coefficient results of study variables. The results
show that 34.12 % of variance in service innovation success can be explained by innovation
capabilities with p-value of .000 that is less than .000. It was also found that innovation capabilities
positively affects the service innovation success with the standardized coefficient of α = .4936,
with significant t-value of 14.83 greater than 2 and p-value of .000 < .05. Hence, it reflects that
hypothesis two (H2: Innovation capabilities may possess positive influence on service innovation
success) stands to be valid.
It is also found that 42.01 % of variance in business model innovation can be explained by
both innovation capabilities and service innovation success. The results also show that service
innovation success (M) possess the significant positive effect of coefficient β = 0.4998 on business
model innovation (Y) with t-value of 8.455 > 2 and p-value of .000 < .05. Thus, it proves that
hypothesis three (H3: Service innovation success may possess positive influence on business
model innovation) stands to be correct.
Table 4.7 Mediation Model Coefficients of Study Variables
Precursors
M
(Innovation success)
Y
(Business model innovation)
Coeff S.E T P Coeff S.E T P
Constant i1 1.6936 .1148 14.74 .000 i2 1.519 .1721 8.829 .000
Innovation capabilities (X) a .4936 .0333 14.83 .000 c' .0346 .0499 .6932 .488
Innovation success(M) -- -- -- -- -- β .4998 .0591 8.455 .000
R2 = 0.3412,
F (1, 425) = 220.12
p = 0.000
R2 = 0.4201,
F (2, 424) = 59.82
p = 0.000
Figure 4.2. Statistical Diagram of Table 4.7
Innovation success
(M)
β = .4998
α = .4936
R2 = 0.4201,
p = 0.000
Innovation capabilities
(X)
c' = .0346
Business Model innovation
(Y)
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In addition, table 4.8 depicts the results of total effect, direct effect and indirect effect of
mediation analysis. From table 4.7, multiplying the coefficient values of α and β yields (0.4936)
(0.4998) = 0.2467 also mentioned in table 4.8 as indirect effect. This indirect effect of 0.2467
means that two individuals who differ by one unit in their innovation capabilities are estimated to
differ by 0.2467 units in bringing business model innovation as a outcome of the propensity for
those individuals with relatively more innovation capabilities to attain more innovation success
(because the sign of α is positive), which in results brings the more business model innovation
(because the direction of β is positive).
Summing the direct effect and indirect effect c = c' + ab = (0.0346 + 0.2467) = .2813 yields
the total effect of innovation capabilities on business model innovation as shown in table 5.22 as
well as in table 4.7. Table 4.7 and 4.8 both depicts the direct effect of innovation capabilities as c'
= .0346. This direct effect reflects the estimated difference in business model innovation between
the two individuals who experience the same level of innovation success but they differ by one
unit in their experience of innovation capabilities. This direct effect of .0346 is positive in nature.
It refers that the more innovation capabilities would yield the equal service innovation success that
would achieve the .0346 unit more business model innovation. It is pertinent to mention here, that
this direct effect is not statistically significant with the p-value of .488 > .05 and t-value of .693 <
2. Hence, it proves that there exists a positive mediation effect of service innovation success with
the magnitude of .0346 among the relationship of innovation capabilities (X) and business model
innovation (Y). Hence, hypothesis four (H4: Service innovation success mediates the relationship
between innovation capabilities and business model innovation) also stands to be correct.
Table 4.8. Total Effect, Direct and Indirect Model of Mediation Analysis
Total Effect of X on Y Direct Effect of X on Y Indirect Effect of X on Y
Effect Se T P
Effect Se t P
Effect Boot SE
.2813 .043 6.42 .000 .0346 .049 .693 .488 .2467 .0323
4.4.4. Addressing Gap Four -Testing moderation effect of employee resistance ‘W’.
4.4.4.1. Testing the moderation effect of ‘W’ on relationship of ‘X’ on ‘Y’ (H-5).
Table 4.9 depicts the results of the moderation effect of employee resistance on the direct
relationship of innovation capabilities (X) and business model innovation (Y). The results show
that 31.34 % of variance on business model innovation (Y) can be explained by innovation
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
124
capabilities (X) and the moderator employee resistance (W) with p-value of .000 that is less than
.05. The results also reflect that the effect of employee resistance (W) is negatively significant on
the business model innovation with the t-value of -4.42 that is greater than 2; coefficient of β = -
.445 and significant p-value of .000. Furthermore, it is also found that interaction term “Int_1”
(multiple of innovation capabilities and employee resistance) possess the significant effect of .3723
with t-value of 4.218 > 2 and the p-value of .01 less than 0.05. This means that the moderation
effect of employee resistance is significantly negatively affecting the relationship between
innovation capabilities and business model innovation. In addition, it is also found that this
interaction effect of innovation capabilities and employee resistance have caused the decrease of
3.65 percent of variance on business model innovation explained by innovation capabilities with
the significant p-value of .000 < .05.
Table 4.9. Model Coefficients for Moderation Effect of Employee Resistance on X and Y
Precursor
Y
(Business Model Innovation)
Coeff S.E t P LLCI ULCI
Constant 7.117 1.07 6.61 .000 5.003 9.231
Employee Resistance (W) -.445 .3269 -4.42 .000 -2.0877 -.802
Innovation Capabilities (X) .9438 .2894 -3.26 .001 -1.512 -.375
Interaction_1 -.3723 .0882 4.218 .000 -.1988 -.545
R2 = 0.3134, F (3, 423) = 21.71; p = 0.000
R-Square decrease due to interaction = -.0365; F (1, 423) = 17.79; p = .000
Figure 4.3. Statistical Diagram of Table 4.9
R2 = 0.3134,
p = 0.000
.9438
-.445
Employee Resistance
(W)
Innovation Capabilities
(X)
Business Model Innovation
(Y)
Int_1 (XW)
-.3723
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Table 4.10. Conditional Effect of X on Y at values of Employee Resistance (W)
Employee
Resistance (W)
Effect Se t P LLCI ULCI
Weak / Low .0416 .0683 .6095 .542 -.0926 .1759
Moderate .2332 .0443 5.26 .000 .1461 .3203
Strong / High .4247 .0582 7.29 .000 .3103 .5391
Table 4.10 depicts at which condition of employee resistance (W) does the interaction
effect (of innovation capabilities and employee resistance) significant on the relationship of
innovation capabilities (X) and business model innovation (Y). The results show that at lower
employee resistance the moderation effect is not significant on the effect of innovation capabilities
(X) on business model innovation (Y) with the t-value .6095 < 2 and p-value .542 > .05. However,
it is also found that at moderate and high level of employee resistance, the moderation effect of
.2332, .4247 are significant on the effect of innovation capabilities (X) on business model
innovation (Y) with the t-values 5.26, 7.29 and p-values of .000, .000 respectively. This conditional
moderation effect of employee resistance on X and Y relationship can also be view in figure 4.4.
Figure 4.4. Moderating effect of W on relationship of X and Y
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126
It depicts that the individuals with high resistance to change tend to contribute less towards
the business model innovation. The graph also reflects that the individuals who feels lower level
of resistance to change and carries the higher innovation capabilities would tend to perform higher
towards business model innovation. However, the individuals who feels moderate level of
resistance to change and carries the higher innovation capabilities would tend to perform little less
than the previous individual who feels the lower resistance to change. This effect continues to
occur until the innovation capabilities are at lower stage.
Hence, these results reflect that hypothesis five (H5: Employee resistance to change
negatively moderates the relationship between innovation capabilities and business model
innovation in such a way that innovation capabilities – business model innovation relationship are
weaker with higher employee resistance and vice versa) is found to be correct.
4.4.4.2. Testing the moderation effect of ‘W’ on relationship of ‘X’ and ‘M’(H-6).
This step includes the testing of moderation effect of employee resistance ‘W’ on the
conditional effect of innovation capabilities (X) on mediator service innovation success (M). The
moderation effect is checked on the conditional effect of innovation capabilities (X) on business
model innovation (Y) through service innovation success (M) as depicted in figure 4.5. Hayes
(2017) has termed it as mediated moderation. Edwards and Lambert (2007) define such
measurement models as “first stage moderation”.
Table 4.11 shows the results of model coefficients for the moderation effect of employee
resistance on conditional effect of innovation capabilities (X) on business model innovation (Y)
through service innovation success (M). Table 4.11 depicts that the effect of employee resistance
(W) is (-1.036) negatively significant on the mediator service innovation success (M) with the t-
value of -4.16 > 2 and significant p-value of .000 < .05. It is also found that interaction term
“Interaction_1” (multiple of innovation capabilities and employee resistance) also possess the
significant effect of .2636 with t-value of 3.92 > 2 and the p-value of .01 less than 0.05. This means
that the moderation effect of employee resistance is significantly negatively affecting the
relationship between innovation capabilities and service innovation.
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Table 4.11. Model Coefficients for Moderation Effect of Employee Resistance on X and M
Precursors
M
(Innovation success)
Y
(Business model innovation)
Coeff Se T p Coeff Se T P
Constant 5.112 .8184 6.24 .000 1.519 .1721 8.829 .000
Innovation capabilities (X) -1.377 .2202 6.22 .000 .0346 .0499 .6932 .488
Employee Resistance (W) -1.036 .2487 -4.16 .000 -- -- -- --
Innovation success(M) -- -- -- -- .4998 .0591 8.455 .000
Interaction_1 .2636 .067 3.92 .001 -- -- -- --
R2 = 0.3722,
F (3, 423) = 83.609
p = 0.000
Direct effect of X on Y: Effect = .0346, t = .6932, p = .4886
Index of moderated mediation = .1318
Furthermore, table 4.11 also reflects that the mediation effect of service innovation success
(M) significantly exists between the innovation capabilities (X) and business model innovation
(Y) under the influence the employee resistance (W). It can be evident from the non-significant
direct effect of .0346 with the non-significant p-value of .488 (that is greater than .05) and t-value
of .6932 (that is less than acceptable 2). Thus, this evidences that the moderation effect of
employee resistance negatively moderates the mediation effect of service innovation success on
the conditional effect of innovation capabilities (X) on business model innovation (Y). And the
index of this moderated mediation is found to be .1318.
Figure 4.5. Statistical Diagram of Table 4.11
-.3772
-
1.03
6
.0346
Innovation success (M)
Employee Resistance (W)
Innovation capabilities
(X)
Business Model Innovation
(Y)
R2 = 0.3722,
p = 0.000
.4998
.2636
Interaction 1 (XW)
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128
Thus, these results evidence that the hypothesis six of this research study (H6: Employee
resistance to change negatively moderates the relationship between innovation capabilities and
service innovation success) also stands to be valid.
4.4.5. Addressing Gap Five -Testing the moderation effect of ‘Z’.
4.4.5.1. Testing the moderation effect of ‘Z’ on relationship of ‘X’ on ‘Y’ (H-7).
Table 4.12 depicts the results of the moderation effect of management entrepreneurial
orientation on the direct relationship of innovation capabilities (X) and business model innovation
(Y). The results show that 68.89 % of variance on business model innovation (Y) can be explained
by innovation capabilities (X) and the moderator management entrepreneurial orientation (Z) with
p-value of .000 that is less than .05. The results also reflect that the effect of management
entrepreneurial orientation (Z) is positively significant on the business model innovation with the
t-value of 19.15 that is greater than 2; coefficient of β = .7965 and significant p-value of .000.
Table 4.12. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and Y
Precursor
Y
(Business Model Innovation)
Coeff Se t P LLCI ULCI
Constant .7506 .1384 5.42 .000 .4785 1.022
Entrepreneurial orientation
(Z) .7965 .041 19.15 .000 .7148 .8782
Innovation Capabilities (X) .1986 .041 4.95 .000 .2774 .1198
Interaction_1 .053 .011 4.46 .000 .0298 .0767
R2 = 0.6889, F (3, 423) = 1256.2; p = 0.000
R-Square increase due to interaction = .1005; F (1, 423) = 19.96; p = .000
Furthermore, it is also found that interaction term “Int_1” (multiple of innovation
capabilities and entrepreneurial orientation) possess the significant effect of .053 with t-value of
4.46 > 2 and the p-value of .000 less than 0.05. This means that the moderation effect of
entrepreneurial orientation is significantly positively effecting the relationship between innovation
capabilities and business model innovation. In addition, it is also found that this interaction effect
of innovation capabilities and entrepreneurial orientation have caused the increase of 10.05 percent
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
129
of variance on business model innovation explained by innovation capabilities with a significant
p-value of .000 < .05.
Figure 4.6. Statistical Diagram of Table 4.12
Table 4.13 depicts at which condition of entrepreneurial orientation (Z) does the interaction
effect (of innovation capabilities and entrepreneurial orientation) significant on the relationship of
innovation capabilities (X) and business model innovation (Y). The results show that at lower
entrepreneurial orientation the moderation effect is not significant on the effect of innovation
capabilities (X) on business model innovation (Y) with the t-value .1487 < 2 and p-value .881 >
.05. However, it is also found that at moderate and high level of entrepreneurial orientation, the
moderation effect of .0215, .0440 are significant on the effect of innovation capabilities (X) on
business model innovation (Y) with the t-values 4.19, 6.05 and p-values of .000, .000 respectively.
This conditional moderation effect of entrepreneurial orientation on X and Y relationship
can also be view in figure 4.7. It depicts that the individuals with higher entrepreneurial orientation
who carries the higher innovation capabilities would contribute higher in business model
innovation. The individuals who feel a a moderate level of entrepreneurial orientation and
simultaneously possessing the higher innovative capabilities would contribute less towards
business model innovation than that of previous individuals with higher entrepreneurial
orientation. The graph also depicts that the individuals with lower entrepreneurial orientation
carrying the higher innovative capabilities would contribute little less towards the business model
innovation than that of previous individuals with moderate and higher entrepreneurial orientation.
This effect continue to occur until the innovation capabilities are at a lower level.
R2 = 0.6889,
p = 0.000
.1986
.1986
Entrepreneurial orientation
(Z)
Innovation Capabilities
(X)
Business Model Innovation
(Y)
Int_1 (XZ)
.053
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130
Table 4.13. Conditional effect of X on Y at values of Entrepreneurial Orientation (Z)
Entrepreneurial
orientation (Z)
Effect Se T p LLCI ULCI
Weak / Low .0011 .007 .1487 .881 .0129 .0150
Moderate .0215 .005 4.19 .000 .0315 .0114
Strong / High .0440 .007 6.05 .000 .0582 .0297
Figure 4.7. Moderating effect of Z on relationship of X and Y
Hence, these results reflect that hypothesis seven (H7: Management entrepreneurial
orientation positively moderates the relationship between innovation capabilities and service
innovation success in such a way that the relationship is stronger with increased entrepreneurial
orientation) is found to be correct.
4.4.5.2. Testing the moderation effect of ‘Z’ on the relationship of ‘X’ and ‘M’(H-8).
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131
This step includes the testing of moderation effect of entrepreneurial orientation ‘Z’ on the
conditional effect of innovation capabilities (X) on mediator service innovation success (M). The
moderation effect is checked on the conditional effect of innovation capabilities (X) on business
model innovation (Y) through service innovation success (M) as depicted in figure 4.8.
Table 4.14. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and M
Precursors
M
(Innovation success)
Y
(Business model innovation)
Coeff Se t P Coeff Se T P
Constant 2.765 .8788 3.14 .001 1.519 .1721 8.829 .000
Innovation capabilities (X) .6091 .2546 2.03 .000 .0346 .0499 .6932 .488
Entrepreneurial orientation
(Z) .2336 .0264 8.84 .000 -- -- -- --
Innovation success(M) -- -- -- -- .4998 .0591 8.455 .000
Interaction_1 .1499 .075 2.00 .048 -- -- -- --
R2 = 0.6635,
F (3, 423) = 110.8
p = 0.000
Direct effect of X on Y: Effect = .0346, t = .6932, p = .4886
Index of moderated mediation = .0746
Figure 4.8. Statistical Diagram of Table 4.14
Table 4.14 shows the results of model coefficients for the moderation effect of
entrepreneurial orientation on the conditional effect of innovation capabilities (X) on business
model innovation (Y) through service innovation success (M). Table 4.14 depicts that the effect of
entrepreneurial orientation (Z) is (.2336) positively significant on the mediator service innovation
success (M) with the t-value of 8.84 > 2 and a significant p-value of .000 < .05. It is also found
.6091
.233
6
.0346
Innovation success (M)
Entrepreneurial orientation (Z)
Innovation capabilities
(X)
Business Model Innovation
(Y)
R2 = 0.6635, p = 0.000
.4998
.1499
Interaction_1 (XZ)
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132
that interaction term “Interaction_1” (multiple of innovation capabilities and entrepreneurial
orientation) also possess the significant effect of .1499 with t-value of 2 and the p-value of .048
less than 0.05. This means that the moderation effect of entrepreneurial orientation is significantly
positively affecting the relationship between innovation capabilities and service innovation.
Furthermore, table 4.14 also reflects that the mediation effect of service innovation success
(M) significantly exists between the innovation capabilities (X) and business model innovation
(Y) under the influence the entrepreneurial orientation (Z). It can be evident from the non-
significant direct effect of .3446 with the non-significant p-value of .4886 (that is greater than .05)
and t-value of .6932 (that is less than acceptable 2). Thus, this evidences that the moderation effect
of entrepreneurial orientation positively moderates the mediation effect of service innovation
success on the conditional effect of innovation capabilities (X) on business model innovation (Y).
And the index of this moderated mediation is found to be .0746. Thus, these results evidence that
the hypothesis eight of this research study (H8: Management entrepreneurial orientation moderates
the direct relationship of innovation capabilities and business model innovation) also stands to be
valid
4.4.6. Addressing Gap Six – Antecedents of Business Model Innovation
4.4.6.1. Testing the dual moderation effect of ‘W’ and ‘Z’ on relationship of ‘X’ on ‘Y’
with putative mediator held constant (H-9).
To testify the hypothesis nine, moderation effect of both moderators employee resistance
(W) and entrepreneurial orientation (Z) are checked with putative mediator service innovation
success considered to be held constant. Table 4.15 shows the results of double moderation analysis
on conditional effect of innovation capabilities (X) on business model innovation (Y).
The results show that 79.94 % of variance on business model innovation can be explained
by one independent innovation capabilities (X) and the two moderators employee resistance (W)
and the entrepreneurial orientation (Z) with the p-value .001 that is less than acceptable .05. The
results also reflect that the employee resistance (W) possess the significant negative effect of -
.5066 at the conditional effect of innovation capabilities (X) on business model innovation (Y)
with the service innovation success (M) held constant with the p-value .001; t-value of 12.35 > 2.
It is also found that the entrepreneurial orientation (Z) also carries the significant positive effect of
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
133
.8201 at the conditional effect of innovation capabilities (X) on business model innovation (Y)
with the p-value .001; t-value of 17.51 > 2. Furthermore, it is also found that the interaction term
“Int_1” (that is the product of innovation capabilities (X) and employee resistance (W) has also
found to possess the significant effect of .1059 with the p-value of .000 and t-value of 9.45 > 2.
Similarly, it is also found that the interaction term “Int_2” (that is the product of innovation
capabilities (X) and entrepreneurial orientation (Z) has also found to possess the significant effect
of .0469 with the p-value of .000 and t-value of 3.53 > 2.
Table 4.15. Moderation Effects of W and Z with Putative Mediator Held Constant
Figure 4.9. Statistical Diagram of Table 4.15
Antecedent
Y
(Business Model Innovation)
Coeff. SE T P LLCI ULCI
Constant .4916 .2473 1.987 .067 .0054 .9777
Employee Resistance (W) -.5066 .0418 12.35 .000 -.0257 -.0138
Entrepreneurial orientation (Z) .8201 .0468 17.51 .000 .7281 .9121
Innovation capabilities (X) .2169 .0176 12.32 .000 .0061 .2598
Int_1 (WX) -.1059 .0112 9.45 .000 .0061 .0379
Int_2 (ZX) .0469 .0133 3.53 .004 .0209 .0730
R2 = 0.79.90, F (5, 421) = 7544.403, p = 0.000
R-Square increase due to interaction term:
Int_1 R2 change = -.0174; F(1, 421) = 20.153; p = .0000
Int_2 R2 change = .0212 ; F(1, 421) = 20.527; p = .0004
Both = .0137 ; F(1, 421) = 19.134; p = .0000
constant
-
.50666
.2169
(M) Held Constant
Employee Resistance
(W)
Innovation capabilities
(X)
Business Model Innovation
(Y)
R2 = 0.79.90,
p = 0.000
constant .8201
Entrepreneurial orientation
(Z)
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134
Table 4.15 also reflects that the interaction effect of innovation capabilities and employee
resistance causes an overall decrease of 1.74 percent of the variance in business model innovation
with the significant p-value of .000 < .05. Whereas, it also refers that the interaction effect of
innovation capabilities and entrepreneurial orientation causes the overall increase of 2.12 percent
of the variance in business model innovation with the significant p-value of .000 < .05. The total
effect of this double moderation has caused the 1.37 percent of variance on business model
innovation.
Table 4.16 depicts at which condition of both employee resistance (W) and entrepreneurial
orientation (Z) do their interaction effects significant on the relationship of innovation capabilities
(X) and business model innovation (Y). The results show that at conditions of either medium
employee resistance or low-low interaction or high-high interactions of moderators, the double
moderation effect of combined moderators (W) and (Z) are not significant on the conditional
effect of (X) on (Y) with the t-values 1.307, -1.56, -.9205, -.1715, .8444, and p-value .074, .118,
.357, .863, .398. However, it is also found that at remaining conditions of low-medium, low-high,
high-low, high-medium interactions, the double moderation effect of combined moderators (W)
and (Z) are found to be significant with the t-values 5.80, 6.12, -4.02, -4.01 and p-value .000, .000,
.000, .000.
Table 4.16. Conditional Effect of X on Y at values of Both Moderators W and Z
Employee
Resistance (W)
Entrepreneurial
orientation (Z)
effect Se T P
Low Low -.0027 .1015 1.307 .074
Low Medium .0409 .0080 5.80 .000
Low High .0491 .0080 6.12 .000
Medium Low .0129 .0082 -1.56 .118
Medium Medium -.0012 .0073 -.1715 .863
Medium High -.0094 .0102 -.9205 .357
High Low -.0292 .0073 -4.01 .000
High Medium -.0211 .0052 -4.02 .000
High High .0069 .0082 .8444 .398
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135
Hence, these results reflect that hypothesis nine (H9: Employee resistance and management
entrepreneurial orientation moderates the direct relationship of innovation capabilities and
business model innovation when the putative mediator service innovation success held constant)
is found to be correct.
4.4.6.2. Testing the dual moderated mediation effect of “W” “Z” and “M” on
relationship of “X” on “Y” (H-10).
This stage is the final consolidation of the previous four stages and results in a formation
of coherent single hypothesized research model of this research study. The hypothesized research
model of this research work is moderated moderated mediation model and also known as dual
moderated mediation (Hayes, 2017, 2018). Lambert and Edwards (2007) termed such
measurement model as first stage moderation direct effect model. This measurement model
consists of five key research variables, independent variable (X) possess the conditional effect on
dependent variable (Y) through a single mediator (M) that is moderated by double moderators (W)
and (Z). Double moderators have two kinds of moderation effect in this measurement model. A
moderation effect on the indirect effect of mediator (M) and the moderation effect on the direct
effect of independent (X) on dependent (Y). Table 4.17 reveals the results of this dual moderated
mediation model.
It reflects that the 68.09 percent of variance on the mediator service innovation success (M)
was explained by the independent variable (X) and the two moderators (W) and (Z) with the
significant p-value of .000 < .05. The results also revealed that there exist significant moderation
effect (.2610) of interaction term one “Int_1”(innovation capabilities (X) and employee resistance
(W)) with the t-value of 3.74 > 2 and significant p-value of .002 < .05. It was also found that there
exists a significant moderation effect (.3034) of interaction term two “Int_2” (innovation
capabilities (X) and entrepreneurial orientation (Z)) with the t-value of 3.67 > 2 and p-value of
.002 < .05. Thus, it proves the significant moderation effect of double moderators on the indirect
effect through mediator of independent (X) on dependent variable (Y).
Table 4.17 also shows that 79.94 percent of variance on the dependent business model
innovation (Y) was explained by the independent variable (X), the two moderators (W) and (Z),
and a mediator (M) with the significant p-value of .000 < .05. The results also shows that there
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136
exist significant moderation effect (.0175) of interaction term three “Int_3”(innovation capabilities
(X) and employee resistance (W)) with the t-value of 12.5 > 2 and significant p-value of .000 <
.05. It is also found that there exists a significant moderation effect (.0451) of interaction term four
“Int_4” (innovation capabilities (X) and entrepreneurial orientation (Z)) on business model
innovation (Y) with the t-value of 3.34 > 2 and p-value of .000 < .05.
Table 4.17. Coefficients for Hypothesized Research Model of Study
Precursors
Model -1
(Innovation success)
Model – 2
(Business model innovation)
Coeff Se T P Coeff Se T P
Constant 8.009 1.541 5.19 .000 .4433 .2553 1.73 .083
Innovation capabilities (X) .7456 .4216 3.45 .000 .1181 .0686 1.72 .086
Employee Resistance (W) -.7027 .2608 -3.93 .000 -.0628 .0226 -2.77 .000
Interaction_1 (XW) .2610 .0697 3.74 .002 -- -- -- --
Entrepreneurial orientation (Z) .8050 .2917 2.75 .006 .8249 .0473 17.45 .000
Interaction_2 (XZ) .3034 .0826 3.67 .003 -- -- -- --
Innovation success(M) -- -- -- -- .1060 .0078 13.58 .000
Interaction_3 (XW) -- -- -- -- -.0175 .0014 -12.5 .000
Interaction_4(XZ) -- -- -- -- .0451 .0135 3.34 .000
R2 = 0.6809; F (5, 421) = 72.78
p = 0.000
R2 = 0.7994; F (6, 420) = 6281.03
p = 0.000
Figure 4.10. Statistical Diagram of Table 4.17
Thus, it proves the significant moderation effect of double moderators on the conditional
direct effect of independent (X) on dependent variable (Y). The non-significant effect of
.7456
R2 = 0.7994 p = 0.000
.824
9
-.0628
.805
0
Entrepreneurial orientation (Z)
Innovation success (M)
.1181
Innovation capabilities
(X)
.1060
Business Model Innovation
(Y)
-.7027
Employee Resistance
(W)
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137
independent variable (X) on dependent variable (Y) in model-2 with the t-value of 1.72 < 2 and p-
value of .086 > .05 evidences that the mediation effect of service innovation success exists between
the relationship of innovation capabilities (X) and business model innovation (Y). Table 4.18
reveals the conditional direct and indirect effect of innovation capabilities (X) on business model
innovation (Y) at values of both moderators.
Table 4.18. Conditional Direct, Indirect Effect of X on Y at values of Moderators
Employee
Resistance
(W)
Entrepreneurial
orientation (Z)
Direct Effect Indirect effect through mediator
Effect S.E T P Effect BootLLCI BootULCI
Low Low -.0143 .011 -1.14 .083 .2007 .0005 .0046
Low Medium .0234 .006 3.88 .000 .2115 .0018 .0059
Low High .0424 .008 5.12 .000 .2122 .0029 .0086
Medium Low -.0144 .008 -1.69 .091 .2115 .0018 .0057
Medium Medium -.0047 .008 -.5380 .590 .2123 .0030 .0083
Medium High -.0043 .008 -.5190 .604 .2131 .0041 .0115
High Low -.0514 .008 -6.01 .000 .2123 .0028 .0094
High Medium -.0323 .008 -3.88 .000 .2131 .0038 .0122
High High -.0133 .011 -1.16 .244 .2139 .0048 .0151
The direct effect (left column) shows at which condition of both employee resistance (W)
and entrepreneurial orientation (Z) do their interaction effects significant on the relationship of
innovation capabilities (X) and business model innovation (Y). The results show that at conditions
of either medium employee resistance or low-low interaction or high-high interactions of
moderators, the double moderation effect of combined moderators (W) and (Z) are not significant
on the conditional effect of (X) on (Y) with the t-values -1.14, -1.69, -.5380, -.5190, -1.16 and p-
values of .083, .091, .590, .604, .244. However, it is also found that at remaining conditions of
low-medium, low-high, high-low, high-medium interactions, the double moderation effect of
combined moderators (W) and (Z) are found to be significant with the t-values 3.88, 5.12, -6.01, -
3.88 and p-value .000, .000, .000, .000. The indirect effect (right column) shows at which condition
of both moderators (W) and (Z) do their interaction effect significant on the indirect effect of
innovation capabilities on business model innovation (Y) through mediator service innovation
success (M). The results reveal that the mediation effect at different conditions of moderators (i.e.
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138
low, medium and high) are found to be significant with the values of BootLLCI and BootULCI
ranging different from zero. Thus, it can be said that the mediation effect of service innovation
success was positively significant at all conditions and interaction types of double moderators (W)
and (Z) in predicting the conditional effect of innovation capabilities (X) on business model
innovation (Y).
Thus, these results evidences that the hypothesis ten of this research study (H10: Service
innovation capabilities possess the positive indirect effect on the business model innovation
(through positive mediation effect of service innovation success), that is further negatively
moderated by employee resistance to change and positively moderated by the management
entrepreneurial orientation) also stands to be valid.
4.5. Checking the Fitness Indices of Dual Moderated Mediation Framework
The fitness of hypothesized theoretical framework (dual moderated mediation framework)
of this research work is also checked through structural equation modeling. The results of model
fitness summary of the hypothesized theoretical framework of this research work are shown in
table 4.19.
Table 4.19. Model Fitness Summary of Hypothesized Theoretical Framework
Fitness Indices Result Found Desired range Fit / Unfit
1) CMIN/df
p value
2.65
.087
< 3
>.05 Fit
2) Incremental Fitness Measures
• CFI
.974
> .90
Fit
• GFI .962 > .90 Fit
• AGFI .951 > .90 Fit
• TLI .907 > .90 Fit
• NFI .969 > .90 Fit
3) Absolute Fitness Measures
• RMSEA
.058
< .08
Fit
• PCLOSE .801 > .05 Fit
• SRMR .047 < .08 Fit
Generally, three forms of fitness indices may be noted in order to check the overall model
fitness. These include (i) CMIN ratio to degree of freedom, (ii) incremental fit indices and (iii)
absolute fit indices. It is believed that the value of “CMIN / df” below or equals to three (3) and
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
139
the non-significant p-value (greater than .05) reflects the goodness fit of the measurement model
(Marsh and Hocevar, 1985; Joreskog and Sorbom, 1993). It is also believed that the values of
incremental fitness measures such as such as comparative fit index (CFI), adjusted goodness of fit
(AGFI), tucker lewis index (TLI) and normed fit index (NFI) should be greater than 0.9 in order
to claim a model as good fit (Bentler & Bonett, 1980; Bollen, 1989; Tanaka & Huba, 1985).
Figure 4.11. Single Measurement Model of Hypothesized Research Model
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
140
Similarly, the measures of absolute fit indices such as root mean square error of
approximation (RMSEA), standardized root mean square residual (SRMR) and p of close fit
(PCLOSE) represents the bad fitness of model. The values of bad fitness measures SRMR and
RMSEA should be less than or equal to .08 (Browne and Cudeck, 1993). The values higher to .08
reflects the bad fitness of model and the value closer to zero (but less than .08) reflects the good
fitness of model. The value of PCLOSE should be greater than 0.05 for the good fit model in
comparison to close fitting (Kenny, 2014). The results reveal that the values of all the fitness
indices measures fall in the desired range. Thus, it is found that the hypothesized dual moderated
mediation framework of this research work possess the good fitness of measurement. The pattern
matrix builder of the measurement model is also shown in figure 4.11.
4.6. Chapter Summary
This chapter has shed light on the statistical tools and techniques used to empirically
validate and analyze the research constructs as well as the hypothesized relationships. First of all,
the demographic statistics are checked by overlooking the psychometric properties of the survey
participants. The results show that 71.19 percent of the respondent are males, 28.81 percent are
female, 3.98 percent are aged less than thirty years, 83.61 percent are aged between 31 years - 40
years and 12.41 percent are aged above than forty years. It is also found that 16.9 percent of
respondents are graduate, 71.90 percent are post-graduate qualified and 11.20 percent are MS or
MPhil or Doctorate or equivalent qualified. The descriptive statistics of the collected data is also
checked and it is found that the average mean score of innovation capabilities, service innovation
success, and entrepreneurial orientation falls under the category of “agree” of seven-point Likert
scale with the values of 5.0334, 5.0423 and 5.1370 respectively. On the other hand, the mean score
of employee resistance falls under the category of “disagree” of six-point Likert scale with the
value of 2.1734.
For testing the hypotheses, Regression based conditional process approach of Andrew
Hayes (2017, 2018) was adopted. The present theoretical framework of this research work is
termed as dual moderated mediation model by Hayes (2018). Before using the regression analysis
as statistical tool, the assumptions of data normality, multicollinearity and linearity were checked
and found to be satisfactory. The testing of all the ten proposed hypotheses of this research work
are embarked in five stages. In first stage, the simple mediation analysis is conducted to check the
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141
mediation effect of service innovation success (M) on innovation capabilities (X) and business
model innovation (Y) relationship. This stage empirically tests the proposed hypotheses 1, 2, 3 and
4 of this study. In second stage, the moderation effect of entrepreneurial orientation (W) is checked
on the effect of innovation capabilities (X) and service innovation success (M). This empirically
tests the proposed hypothesis 5 of this study. Simultaneously, the moderation effect of
entrepreneurial orientation (W) is checked on the direct effect of innovation capabilities (X) and
business model innovation (Y) that empirically tests the proposed hypothesis 6 of this research
work. In third stage, the moderation effect of employee resistance (Z) is checked on the effect of
innovation capabilities (X) and service innovation success (M) that empirically tests the proposed
hypothesis 7. Simultaneously, the moderation effect of employee resistance (Z) is also checked on
the direct effect of innovation capabilities (X) and business model innovation (Y) that empirically
tests the proposed hypothesis 8 of this research work. In fourth stage, the moderation effect of both
entrepreneurial orientation (W) and employee resistance (Z) simultaneously check on the direct
relationship of innovation capabilities (X) and business model innovation (Y) with considering the
service innovation success (M) being held constant. This stage empirically tests the proposed
hypothesis 9 of this research work. In final fifth stage, overall the hypothesized theoretical
framework of this research work is tested that empirically tests the proposed hypothesis 10 of this
research work. The model fitness of the hypothesized theoretical framework of this research work
is also tested through Structural equation modeling. And it is found that the hypothesized dual
moderated mediation framework of this research work possess the good fitness of measurement.
Table 4.20 summarizes the results of hypotheses testing as follows;
Table 4.20. Summarizing Results of Research Hypotheses
Hypotheses Accepted or
Rejected
H1 Innovation capabilities may possess positive influence on business model
innovation. Accepted
H2 Innovation capabilities may possess positive influence on service innovation
success. Accepted
H3 Service innovation success may possess positive influence on business model
innovation Accepted
H4 Service innovation success mediates the relationship between innovation
capabilities and business model innovation Accepted
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142
H5
Employee resistance to change moderates the direct relationship of innovation
capabilities and business model innovation, in such a way that the relationship
is stronger with lower employee resistance
Accepted
H6
Employee resistance to change negatively moderates the relationship between
innovation capabilities and service innovation success in such a way that the
relationship is stronger with lower employee resistance
Accepted
H7
Management entrepreneurial orientation moderates the direct relationship of
innovation capabilities and business model innovation, in such a way that the
relationship is stronger with increased entrepreneurial orientation
Accepted
H8
Management entrepreneurial orientation positively moderates the relationship
between innovation capabilities and service innovation success in such a way
that the relationship is stronger with increased entrepreneurial orientation.
Accepted
H9
Employee resistance and management entrepreneurial orientation moderates the
direct relationship of innovation capabilities and business model innovation
when the putative mediator service innovation success held constant
Accepted
H10
Service innovation capabilities possess the positive indirect effect on the
business model innovation (through positive mediation effect of service
innovation success), that is further negatively moderated by employee
resistance to change and positively moderated by the management
entrepreneurial orientation.
Accepted
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143
CHAPTER 5
DISCUSSION, RECOMMENDATION AND CONCLUSION
This chapter deliberates the arguments derived from the results of data analysis in the light
of the posed research questions of this research work. On the basis of discussion, the conclusion
and major recommendations are made for practitioners. The future avenues of research are also
discussed in light of the limitations of this research work.
5.1. Discussion
This research work examines the concepts from three important streams of theoretical
underpinnings i.e. dynamic capabilities theory, strategic entrepreneurship theory and force field
theory of change.
5.1.1. Research Objective – 1.
Recent researches indicate that limited articles review the literature streams of business
model innovation elaborating the identified gaps and potential research questions for promotion of
new research on clarity of conception and development of theoretical frameworks (Schneider &
Spieth, 2014; Foss & Saebi, 2018, 2017; Teece, 2018, Geissdoerfer et al., 2018). This indicates
that the existing literature body on business model innovation has just begun to evolve with a need
to address the dimensions, facilitators and consequents of business model innovation (Saebi, Lien
& Foss, 2016; Teece, 2018; Foss & Saebi, 2018). There also exists a little agreement of researchers
on the dimensions of business model innovation as up till now very limited empirical analysis have
been conducted to establish the better understanding of the concept (Geissdoerfer et al., 2018; Foss
& Saebi, 2018). This serves as a gap in the existing literature. In order to contribute in addressing
this research gap, the research objective one was established as, “to empirically test the dimensions
of business model innovation in cultural context of Pakistan”. The empirical results of detailed
reliability and validity analysis affirmed the (ten factor based) operationalization of business model
innovation by Clauss (2017) in Pakistani cultural context. Thus, this work has attempted to address
the need for more empirical knowledge about the dimensions of business model innovation in
pursuance of laid down research objective one of study. Thus, in light of the findings of this
research work, the newly evolved concept of business model innovation can be defined as,
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144
“Business model innovation refers to the acquisition of new capabilities, new technology or
equipment, new business partnerships and new business processes with an objective to offer new
products or services to address unmet needs of new markets or customers through more improved
distribution channels in order to attain the regulate the cordial customer relationship. This
phenomenon also involves the adoption of more improved and beneficial revenue model and cost
structures for the cellular organizations so that value can be captured for both i.e. customers as
well as the cellular organization”.
5.1.2. Research Objective – 2.
The research objective two of this research study was “to examine the role of service
innovation capabilities being the predictor of business model innovation”. This research objective
attempts to investigate, that does an organization adapt changes in its existing business model in
response to the internal driving forces of organizations such as innovation capabilities? The
empirical results of this research work shows that bringing substantial positive change in terms of
value in business model of organization depends upon the extent of organization’s capability to
smartly rework, co-design and co-produce on the new idea or new technological options along
with the diffusion of these new elements or concept of new services across the different functioning
of the organization. In particular, it has been found that the higher the innovative capable the
organization, the more likely that organization will bring the positive change in terms of value in
the existing business model. This finding is consistent with the dynamic capabilities theory, which
suggests that successful organization are the ones who are capable enough to timely respond to the
changing dynamics of the market through innovation (Teece et al., 1997). Even, Teece (2018) also
has conceptualized that strong innovation capabilities may yield strong business model innovation
and has recommended to be empirically tested in future researches. This empirical finding
contributes to the existing body of literature as some of the recent researches comprehend the need
to empirically explore the possible effect of innovation capabilities on business model innovation
(Scheinder & Speith, 2014; Foss & Saeibi, 2018, 2017; Teece, 2018).
5.1.3. Research Objective – 3.
The research objective three of this research study was “to examine the indirect mediation
impact of service innovation success on the association of service innovation capabilities and
business model innovation”. The empirical analysis in accomplishment of this laid down research
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
145
objectives, highlights that the executives of organization regulates the higher capabilities of
organization to smartly rework, co-design and co-produce on the new ideas or new technological
options. These executives regulates these capabilities in diffusion of these new elements or concept
of new services across the different functioning of the organization would achieve higher success.
This success could be illuminate in terms of adding substantial value to existing product or
services, sustained competitive position, financial success and precondition for future successes.
These successes by newly offered services further yield the substantial positive change in the
overall business model of the organization. Empirically, it can be stated from results that one unit
increase in innovation capabilities of organization would yield .4936 unit increase in innovation
success that would further yield .4998 unit increase in overall business model innovation. This
means that two executives of the cellular company who differ in regulating one unit of innovation
capabilities in the organization are estimated to differ in .2467 unit in bringing the substantial
positive change in terms of value in their existing business model. These findings are also found
to be consistent with the existing researches. These researches argue that the effect of innovation
capabilities on business model innovation is complex in nature (Teece, 2018). And further
conceptualize that there is a need to explore the association of these variables with some
performance indicators (as innovation success in this case) (Scheinder & Speith, 2014; Foss &
Saeibi, 2018; Teece, 2018). These empirical findings contribute to the existing body of knowledge
by addressing this need identified by existing researches (Scheinder & Speith, 2014; Foss & Saeibi,
2018; Teece, 2018). However, there further stands some inferences and barriers in an attempt to
achieve innovation success and business model innovation that further paves the way for research
objective four.
5.1.4. Research Objective – 4.
The research objective four of this research study was “to examine the moderation impact
of employee resistance on the direct and indirect association of service innovation capabilities and
business model innovation”. It is essential to discuss here that individuals of an organization are
the basic unit for the regulation of organizational processes inclusive of functional level, middle
level or top management level. It is obvious, that there may be some individuals that may carry
resistance to innovation due to their routine seeking behavior or close-mindedness or intolerance
of new adjustments or fear of losing control. The empirical analysis was conducted to accomplish
the laid down research objective four. And it also shows that organization’s capability to smartly
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146
rework, co-design, co-produce and integrating the new idea or new technological options to bring
substantial valued change in business model is negatively affected by the employee’s resistance to
change if only if the overall employee resistance exists at higher levels among the executives and
senior managers. At an overall low level of employee resistance, its negative effect on the business
model innovation is nullified. It means that if the majority or maximum executive or senior
manager of any cellular firm carries the routine seeking behavior, or attribute of close-mindedness,
or intolerance to new adjustments and or fear of losing authority and control, then such cellular
firm may fails or minimally achieve the valued change in existing business model(s) irrespective
of pursuing higher intense firm’s innovative capabilities.
Similarly, it is also found that this resistive behavior of the individuals also prior affects
the innovation success of the firm that is also an outcome of organization’s innovation capabilities
and further paves the way forward towards the achievement of valued change in existing business
model(s). These results are also consistent with existing researches that claim the resistance of
individuals serve as a primary concern that affects the overall success ratio of business (Kegan &
Lahey, 2001; De Wit & Meyer, 2004). The recent researches also conceptualized that the employee
resistance is an essential internal factor that is critical to the achievement of business model
innovation (Foss & Saebi, 2017, 2018) and overall achievement of innovation success (Hao & Yu,
2011). They further pose a challenging research question that there is a need to empirically explore
the role of employee resistance on overall business model innovation of the organization (Foss &
Saebi, 2017, 2018). This finding also contributes to the existing body of knowledge by addressing
this posed research question of existing recent researches (Foss & Saebi, 2017, 2018).
5.1.5. Research Objective – 5.
The research objective five of this research study was “to examine the moderation impact
of management entrepreneurial orientation on the direct and indirect association of service
innovation capabilities and business model innovation”. It is essential to discuss here that,
generally, it is not necessary that all the individuals of the organization may carry this resistive
behavior. There may be some individuals (executives or senior managers) that may possess and
engage themselves in seeking unusual or novel opportunities with risk-taking with an intention to
adopt aggressive competitiveness against rivals and behave proactively to recent market trends. It
can be said because organizations continuously carry some routine forms of innovation in response
to its rivals or customer growing needs that guarantee its survival in competitive market dynamics.
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147
Identifying the unusual or novel opportunities is something precursor to innovation success and
bringing substantial valued change in business models. Similarly, the empirical analysis was
conducted to accomplish the research objective five. And the findings also highlight that the
organization’s capability to smartly rework, co-design, co-produce and integrating the new ideas
or new technological options to bring substantial valued change in business model is substantially
affected by the management entrepreneurial stance, if and only if the overall management
entrepreneurial stance exists at moderate or higher levels among middle and top management. At
an overall low level of entrepreneurial orientation, its substantial enhancing effect on the business
model innovation is not empirically justified by the findings of this work. It means that if the
majority or equal number of executives or senior managers of any cellular firm carry the
entrepreneurial stance of readiness to innovate, follow aggressive competitiveness, act market
proactively and believe on risk-taking, then such cellular firm may successfully achieve the valued
change in their existing business model(s) with enhancing the overall effect of higher intense
firm’s innovative capabilities. Similarly, it was also found that this entrepreneurial stance of
middle and top management also substantially affects the innovation success of the firm that is an
outcome of organization’s innovation capabilities and further pave the way forward towards the
achievement of valued change in existing business model(s). These results are also consistent with
existing researches that claims the innovation as a heart of entrepreneurial activities (Baker &
Sinkula, 2009). Foss and Saebi (2018) also argue that the role of entrepreneurial orientation is
critical to business model innovation. They further pose a challenging research question that there
is a need to empirically explore the role of the entrepreneurial orientation of management on
overall business model innovation of the organization (Foss & Saebi, 2017, 2018). The above
finding also contributes to the existing body of knowledge by addressing this identified research
gap posed by the existing recent researches (Foss & Saebi, 2017, 2018).
5.1.6. Research Objective – 6.
Presently, the majority of the researches on the determinants of the business model
innovation are conceptual in nature and there are negligible or few research studies that offer
empirical evidence on what actually determines the business model innovation?. It is pertinent to
mention here that recent research studies have conceptually predicted that the business model
innovation may likely to occur in the influence of organization’s internal drivers of innovation
capabilities, entrepreneurial orientation and employee resistance that needs to be further
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148
empirically explored (Teece, 2018; Foss & Saebi, 2018). This also serves as a research gap. In
light of above, the research objective six was established as “to examine the overall indirect effect
of service innovation capabilities on business model innovation (through mediation effect of
service innovation success) that are further moderated by employee resistance and management
entrepreneurial orientation”. In accomplishment of this research objective, this work presents the
empirical evidence on the effects of management entrepreneurial orientation and employee
resistance to change under which the innovation capabilities drive the organization to adopt
innovation in existing business models.
It is essential to discuss that the organizations may encompass a blend of both attributes
of individuals i.e. resistive-nature and entrepreneurial-nature. Generally, this statement can be
justified with the fact that organizations carry both winners and losers at the same time for the
attainment of business success (Foss & Saebi, 2017). The loser’s attempts to behave negatively
towards the ongoing or initiated innovation activities while the winner’s struggles to act positively
to bring substantial novel change. Hypothesis 9 and 10 of this research work can be elaborated in
this regard that proposed the influential tempering effect of employee resistance and management
entrepreneurial orientation at the same time on the role of innovation capabilities in shaping
business model innovation. The overall findings of this work indicate that if the innovation success
is considered constant, then the employee resistance casts the decreasing effect of 1.74 percent
variance in the attainment of business model innovation. On the other hand, the management
entrepreneurial orientation casts the increasing effect of 2.12 percent variance in the achievement
of substantial value in the business model simultaneously. The employee resistance and
management entrepreneurial orientation both attempts to cast their (negative and positive
respectively) effects on the indirect effect of innovation capabilities on business model innovation
(through innovation success). It is essential to discuss that the overall cumulative effect of both
forces (i.e. employee resistance and entrepreneurial orientation) is positive on the achievement of
business model innovation when the employee resistance (negative force) is at lower levels in
comparison to entrepreneurial orientation (positive force). The overall cumulative effect of both
forces are negative on the achievement of business model innovation when the entrepreneurial
orientation (positive force) is at lower levels in comparison to employee resistance (negative
force).
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These findings are also consistent with the force field theory of change (Lewin, 1951;
Burnes, 2014). This theory states that there are two types of forces within the organization that
affects the change process. One is the driving force that accelerate the changes within the
organization while the other force is resistive in nature that opposes the on-going change
mechanism. The theory also claims that the driving forces should be higher than the resistive forces
in order to bring substantial novel change within the organization (Lewin, 1951). The findings of
this research work are found to be consistent with this previously established theory of force field
of change (Lewin, 1951; Burnes, 2014). The findings of this research work are significant as the
majority of previous researches have adopted the qualitative research methodology with the
limited or negligible empirical testing of the determinants as well as associations (Teece, 2018;
Foss & Saebi, 2018, 2017; Clauss, 2017; Saebi et al., 2017; Scheinder & Speith, 2014). The
explanation on the antecedents of business model innovation is also found to be limited with no or
negligible empirical evidence in previous researches (Teece, 2018; Foss & Saeibi, 2018, 2017;
Clauss, 2017; Saebi et al., 2017; Scheinder & Speith, 2014). This research work, to best of
knowledge, is the first empirical study on the validation of operationalization of business model
innovation and investigation of antecedents of business model innovation specifically in the
cultural context of Pakistan. This research work also implies the crucial findings for the
practitioners in the managerial implications section.
5.2. Recommendations
This research work concludes with two forms of recommendations. Recommendations for
the practitioners of cellular companies of Pakistan are discussed as ‘managerial implications’. On
the other hand, the recommendations for academicians that lay downs the vision for future
researches are discussed as ‘limitations and future research directions’.
5.2.1. Managerial Implications
The findings of this research work imply some critical recommendations for the managers
and executives of cellular companies that are explained as below;
5.2.1.1. Need to consider business model innovation
Generally, it is believed that innovating the new products or services and bringing
innovation in existing processes (i.e. cost reduction techniques etc) paves the way for business
success in comparison to rivals. However, these elements are proved to be insufficient, in practice,
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to ensure competitiveness and overall business success (Chesbrough, 2010). With the advent of
“internet of things”, the concept of “e-commerce”, “digital economy” and “national financial
inclusion strategy” by the Pakistan Telecommunication Authority (PTA), the practitioners of
cellular companies needs to manage the speed of change along with the breathtaking pace of
technological advancements. Innovating in terms of new products, services or better-tailored
processes can easily be copied and thus, cannot be relied on for sustainability in such complex
market dynamics of the telecom sector. Furthermore, the returns attained from innovating product,
service or processes are not guaranteed in the longer run and erodes with the time. Cellular
companies need a different type of innovation that can allow a cellular company to change the rule
of games and let an organization prove itself more competitive. This required new form of
innovation is business model innovation that is difficult to replicate or copy or follow by
competitors as replication or copy or follow may require substantial time and efforts by the rivals.
Consequently, it also results in more consistent returns. This study has provided a deeper insight
into the business model innovation that what are the constituents of business model innovation in
the cultural context of the cellular company. Usually, it is also believed that an organization can
innovate their business models by altering their value mechanisms by integrating more advanced
technology. However, it is pertinent to explain that business model innovation is innovating
inclusive of all, classified in groups of creating value, proposition a value and capturing value.
5.2.1.2. Need to consider value creation
Practitioners of cellular companies can create value through new capabilities, new
technologies and equipments, new processes and structures, and developing new partnerships.
Capabilities are something that is embedded in activities. New capabilities can succeed and
develop through continuous learning of organizational members. Integration of new knowledge
relating technologies, market recent trends, new business practices, exploration and exploitation
of new ideas, empowerment of organizational members to experiment self-learn and self-develop
(through training, seminars, informational platforms and developmental opportunities) are all
sources to acquire the new capabilities. Similarly, the adoption of new technological trends, new
technological equipments and aligning these technological developments to the existing are the
contributing element to business model innovation. In addition to these, new processes and
structures also serve as a basis for achieving business model innovation. This factor is an essential
ingredient and critical for the introduction of product or service’s personalized customization
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151
offers. Little altering or addition of new process at the last stage of production of product or service
offering can lead to personalized customization offers to the customer that would serve as an
innovation in the business model.
5.2.1.3. Need to consider value proposition
Practitioners of cellular companies can also achieve innovation in business models through
extending proposition value that requires new offerings, new customers and markets, new channels
and strong customer relationships. Practitioners can make new offerings by addressing the unmet
needs of customers, offer more innovative product or service in comparison to rivals and engage
themselves in a continuous struggle to solve customer needs that are left unmet by rivals. New
customers and markets are also a source for ensuring business model innovation through value
proposition. It includes taking an opportunity to penetrate in growing or new markets and seeks to
target the new customer segments on a regular basis. However, increasing the customer base
should not the only strategy to achieve business model innovation. Practitioners should also focus
to retain the existing customers by developing a cordial relationship with them.
5.2.1.4. Need to consider value capture
Furthermore, another important aspect is the capture of value. This capture of value can be
made by practitioners of cellular company through introduction of new revenue model and new
cost structures. Practitioners can introduce the new revenue models by developing new revenue
opportunities (such as additional sales or cross-selling etc.) and replace one-time transaction
revenues with the long-term recurring revenue models (such as leasing). Similarly, new cost
structures can be adopted regularly by reflecting the price-quantity strategy, seek ways to cut down
manufacturing costs, upgrade the cost structures with changing market prices and utilize the
opportunities of price differentiation as needed. These are some crucial indicators and constituents
of business model innovation. The practitioners of cellular companies need to strengthen these
discussed parameters as they reflect the extent of business model innovation carried by their
organization. However, the findings of this research work also suggest that there are also some
enablers and barrier to business model innovation. Practitioners of the cellular company also need
to consider these enablers and barrier in order to achieve maximum business model innovation.
5.2.1.5. Need to consider capabilities to innovate
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The results of this research work suggest that the factor of innovation capabilities should
also be aligned and synchronized with the business model innovation efforts of the organization.
Strategist of the cellular company should spend more time, energies and efforts on new
technological options, customer needs and market opportunities. Strategist needs to smartly re-
work on these newly sensed elements to create something new product or service offerings to
market. However, the findings of this research work suggest that this higher effort of innovation
capabilities may still hamper organizational inertia in overall efforts of attaining business model
innovation. There are some other critical factors that also need to be considered by the strategist
and practitioners of the cellular company along with the above explained elements.
5.2.1.6. Need to manage behavioral resistance
It is essential to state that managing the organizational members (in context of behavioral
resistance) is as crucial for the organization, as the other efforts put forth for accelerating the
innovation capabilities and entrepreneurial orientation for the success of innovation mechanism.
The findings of this work also indicate that the resistance to change is the major barrier that
devastatingly effects the above discussed constituents and enabler of business model innovation.
Practitioners and strategists need to seriously look into this barrier that plays a role of trauma to
the attainment of overall business model innovation. This resistance would not be uniform among
members instead it would vary as per the individual’s personality (Oreg, 2003). Those individuals
who carries low level of this dispositional resistance to change will be supposed to accept the novel
changes. While on the other hand, the members who carry a high level of this dispositional
resistance will attempt to reject the novel changes. Now, those individuals with high dispositional
resistance may carry resistance due to the attributes of routine seeking behavior, emotional reaction
fear of loss of control, closed mindedness and weak stimulation for experiencing something
different or new.
The resistance caused by the routine seeking behavior, close mindedness and weak
stimulation for experiencing something new, can be managed by the organization through effective
communication strategies and participative roles of employees (Oreg, 2003; Burnes, 2014).
Constructively engaging these individuals in novel change’s process and convincing them through
communication may help. There is a need to realize them a sense of urgency by discussing the
potential crises or major opportunities. Inquiry and dialogue may be used to communicate them
with the underlying problems that require those novel changes and then, engaging them in finding
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the solutions of the problem, may automatically disposition the higher resistance by these
individuals to minimal or negligible levels. It is obvious that the employees if provided with the
full authority to exercise their assigned jobs / targets with freedom further strengthens the
innovative culture with higher innovative productivities and sense of accountability. The literature
also supports the arguments that the employees provided with challenges, freedom, openness, risk-
taking, liveliness and humor encourages the creative climate among the organizational members
(Ekvall, 1996; Deal & Kennedy, 1982; Lawson & Samson, 2001).
Another essential aspect here is the influence of transformational leadership attributes of a
single individual on another. An individual with transformation leadership attributes motivates the
surrounding individuals to strive for more long-term goals rather than short-term profits (Burnes,
2014). Therefore, interactions (through formal meetings or informal gatherings) among the
executives and senior managers play a crucial role in spreading motivation across the top and a
middle layer of management by the transformational leadership attributes of the single individual.
The resistance of members due to emotional reactions of fear of control loss may also overcome
by stimulating the positive emotions about the novel change by reappraising the situation. Again,
the above explained parameters would be helpful to change the mindsets of individuals by
emphasizing on the positive outcomes of the novel changes and realizing the need for urgency.
5.2.1.7. Need to consider management entrepreneurial skills
The findings of this work also suggest that the entrepreneurial skills of management along
with the innovation capabilities casts a synergizing effect on the business model innovation. These
entrepreneurial orientation involves the risk-taking behavior of management, encouragement of
new ways of doing thinks, seeking novel solutions or opportunities, facilitating employees in
taking risks, struggles to initiate leading foremost actions in comparison to competitors, facilitates
research and development, technological leadership and continuously markets new lines of product
with more improvements. This synergizing effect of entrepreneurial orientation also attempts to
nullify the devastating effect of resistance to change. The findings have also highlighted that the
stronger entrepreneurial stance of the organization in comparison to resistance would yield a
substantial enhancing change in business model innovation. However, the findings also pointed
that the lower entrepreneurial stance of the organization in comparison to resistance level would
yield the devastating effect on the business model innovation (by terminating the effects of higher
innovation capabilities of organization). Thus, the strategist and practitioners of the cellular
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154
company of Pakistan need to consider these factors wholeheartedly for the pursuit of business
model innovation.
5.2.1.8. Research instrument as practicing tool for practitioners
Another important implication for the practitioners of the cellular company are the research
instruments (questionnaire) of this research work. Strategists and practitioners of the cellular
company can use the research instruments of this study in order to identify the relevant problem
areas of their organization and further stimulate the extent of business model innovation through
addressing those identified problem areas. These research questionnaires would help the
practitioners to self-assess their organization’s business innovation strategies, resistance level,
entrepreneurial orientation level and extent of business model innovation captured by the cellular
company. Proper allocation of resources can be made in the right way by assessing the extent of
different constituents of business model innovation. Furthermore, resistance to change
questionnaire can be used for the personnel selection of key management positions of the cellular
company. It can also be used to identify and select change-resilient personnel for the role positions
that entail frequent changes. Overall, it can be said that more informed decisions can be made on
the basis of the gathered knowledge by using these research questionnaire.
5.2.2. Limitations and Future Research Directions
This work has attempted to address some of the literary gaps by empirically investigating
the enablers and elements influencing the business model innovation, however still this research
study carries some limitations. Firstly, this work carries a methodological limitation as the
collection of data are based on multiple respondents from a single organization selected under the
umbrella of simple random sampling technique. This work is based on single-industry that is
cellular companies of Pakistan. Thus, the empirical testing of enablers of business model
innovation cannot be claimed to be generalized on other service segments / industries of the
cultural context of Pakistan. This limitation was because of limited time and financial budgetary
constraints. Another limitation of this study that this research work has not cited the role of
experimentation and learning processes in identifying the different innovative capabilities and its
influence on other enablers. The existing literature also pertains the evidences that the learning
processes, knowledge exploration and exploitative practices are required to enhance the innovative
capabilities of the organization, however their nature of influence as value creating attribute have
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155
not yet been studied. This further opens the new avenues for research. There are many other
organizational variables that are left out by this research work. Bringing innovation in business
model stands as a cognitive structures that requires a philosophy of earmarking the boundaries of
organization’s internal structures, mechanisms to generate value and enduring its corporate
governance. This perspective highlights the role of organizational and managerial cognition as key
foci for regulating the innovation in business model. Although, this research work has attempted
to study the entrepreneurial orientation of the management but the role of organizational cognition
has not taken in account. This serves as a limitation. A separate detailed research can be conducted
to investigate the role of different cognitive processes of management in decisions of business
model innovation. Other organizational factors such as strategic flexibility including resource and
coordination flexibility, organizational culture may also be explored as the influencers of business
model innovation. The role of product market strategies, promotional and pricing strategies,
customer brand knowledge and brand reputation are other influencing factors that may impact the
innovative success of new business models that needs to be studied in future studies. In this way,
business model innovation may be undertaken as strategy of process optimization or value creation
that may ultimately attains the better financial or sustainable results.
Summarizing, future researches are recommended to further testify the theoretical
framework of this research work by taking in account the large sample of Pakistani service sector.
It is recommended that future researches may empirically testify the theoretical framework of this
research work in different nature of industries and cultural contexts. Furthermore, based on the
theoretical framework of this research work, future researches may also carry a comparative study
among the four cellular companies relating the extent of business model innovation achieved and
their effect on the competitive positioning of the organization in the telecom industry. New
researches can also extend the present theoretical framework by investigating the role of other
organizational factors such as learning processes, knowledge exploration and exploitation
practices, organizational cognition processes, structural flexibility, organizational culture etc.
5.3. Conclusion
This study attempts to investigate the antecedents of business model innovation. The
review of extensive literature has revealed six crucial research gaps pointed by existing recent
researches. An attempt to address these identified six research gaps further paves the way for the
establishment of research objectives and research questions of this research work.
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156
The objective of this research work is to examine the role of innovation capabilities in
determining the business model innovation and to further empirically investigate the role of service
innovation success, employee resistance and entrepreneurial orientation on the direct association
of innovation capabilities and business model innovation. In addition to this, it is also aimed to
examine the overall indirect effect of innovation capabilities on business model innovation
(through the mediation effect of service innovation success), that is moderated by employee
resistance and entrepreneurial orientation. It is also aimed to empirically validate the
operationalization of business model innovation.
On the basis of these laid down research objectives, six research questions have been
framed. The quest to answer these guiding six research questions inevitably addresses the
identified six research gaps of this research work and further paves the way for the formation of
ten research hypotheses.
The review of extensive literature body and the empirical results of this research work has
shown that the employee resistance (a resistive negative factor) and entrepreneurial orientation
(driving accelerating factor) both need special attention by managers and executives in daily
organizational activities and processes. Gearing up the innovation capabilities of the organization
alone may not produce a substantial effect on the attainment of innovation success and business
model innovation. The diagnosis of the extent of the two forces (employee resistance and
management entrepreneurial orientation) are critical for the organizations in order to understand
how substantial value effect in business models may be achieved. Referring to diagnosis here
means the extent of sub-elements of these forces that cumulatively measure the overall effect of
these two forces. The findings of this research work serve as critical implications for the managers
and executives of cellular companies of Pakistan. To sum up, these findings and managerial
implications serve as an initial step for practitioners who are striving for the innovation in their
current business model. It may help the practitioners in determining the extent of various sub-
elements of employee resistance and management entrepreneurial, and to deeply understand their
nature of effect that further yield the positive desired outcome of business model innovation.
In light of all above remarks, it can be concluded that the innovation capabilities,
entrepreneurial orientation, synergizing interaction effect of entrepreneurial orientation
(interaction of innovation capabilities and entrepreneurial orientation), employee resistance and
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157
the devastating interaction effect of employee resistance (interaction of innovation capabilities and
employee resistance), all these five constructs cast an overwhelming effect on service innovation
success and business model innovation. Therefore, these factors can be considered and termed as
an antecedent factor of business model innovation.
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158
REFERENCES
Adler, P. S., & Shenbar, A. (1990). Adapting your technological base: The organizational
challenge. Sloan management review, 32(1), 25-37.
Adrodegari, F., Pashou, T., & Saccani, N. (2017). Business model innovation: process and tools
for service transformation of industrial firms. Procedia CIRP, 64, 103-108.
Amit, R., & Schoemaker, P. J. (1993). Strategic assets and organizational rent. Strategic
Management Journal, 14(1), 33-46.
Amit, R., & Zott, C. (2012). Creating value through business model innovation. MIT Sloan
Management Review, 53(3), 41-49.
Araujo, L., & Spring, M. (2006). Services, products, and the institutional structure of production.
Industrial Marketing Management, 35(7), 797-805.
Arvanitis, S., & Stucki, T. (2012). What determines the innovation capability of firm founders?
Industrial and Corporate Change, 21(4), 1049-1084.
Ashforth, B. E., & Mael, F. A. (1998). Sustaining Valued Identities. Power and influence in
organizations, 89.
Aspara, J., Rajala, R., & Tuunainen, V. K. (2012). The future of banking services.
Atuahene-Gima, K. (2003). The effects of centrifugal and centripetal forces on product
development speed and quality: How does problem solving matter? Academy of
Management Journal, 46(3), 359-373.
Avlonitis, G. J., & Salavou, H. E. (2007). Entrepreneurial orientation of SMEs, product
innovativeness, and performance. Journal of Business Research, 60(5), 566-575.
Aziati, A. N., Tasmin, R. H., Jia, L. B., & Abdullah, N. H. (2014). The relationship of
technological innovation capabilities and business innovation capabilities on organization
performance: Preliminary findings of Malaysian food processing SMEs. Paper presented
at the Engineering, Technology and Innovation (ICE), 2014 International ICE Conference
on.
Baden-Fuller, C., & Haefliger, S. (2013). Business models and technological innovation. Long
range planning, 46(6), 419-426.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
159
Baer, M. (2007). Innovation in organizations: The generation and implementation of radical ideas.
University of Illinois at Urbana-Champaign.
Baker, W. E., & Sinkula, J. M. (2009). The complementary effects of market orientation and
entrepreneurial orientation on profitability in small businesses. Journal of small business
management, 47(4), 443-464.
Barnard, C. (1938). 1.(1938). The functions of the executive.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management,
17(1), 99-120.
Barney, J. B. (1996). The resource-based theory of the firm. Organization science, 7(5), 469-469.
Barney, J., Wright, M., & Ketchen Jr, D. J. (2001). The resource-based view of the firm: Ten years
after 1991. Journal of management, 27(6), 625-641.
Barrett, M., Davidson, E., Prabhu, J., & Vargo, S. L. (2015). Service innovation in the digital age:
key contributions and future directions. MIS quarterly, 39(1), 135-154.
Bartolucci, F., Bacci, S., & Gnaldi, M. (2015). Statistical analysis of questionnaires: A unified
approach based on R and Stata: Chapman and Hall/CRC.
Bashir, M., & Verma, R. (2019). Internal factors & consequences of business model
innovation. Management Decision, 57(1), 262-290.
Bellman, R. (1957). E. 1957. Dynamic programming. Princeton University Press. Bellman
Dynamic programming1957, 151.
Bentler, P. M. (1992). On the fit of models to covariances and methodology to the Bulletin.
Psychological bulletin, 112(3), 400.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of
covariance structures. Psychological bulletin, 88(3), 588.
Björkdahl, J., & Börjesson, S. (2012). Assessing firm capabilities for innovation. International
Journal of Knowledge Management Studies, 5(1-2), 171-184.
Bollen, K. A. (1989). A new incremental fit index for general structural equation models.
Sociological Methods & Research, 17(3), 303-316.
Breznik, L., & D. Hisrich, R. (2014). Dynamic capabilities vs. innovation capability: are they
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
160
related? Journal of small business and enterprise development, 21(3), 368-384.
Brockhaus Sr, R. H. (1980). Risk taking propensity of entrepreneurs. Academy of Management
Journal, 23(3), 509-520.
Brower, R. S., & Abolafia, M. Y. (1995). The structural embeddedness of resistance among public
managers. Group & Organization Management, 20(2), 149-166.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage focus editions,
154, 136-136.
Bryson, J. R., & Daniels, P. W. (2010). Service Worlds service worlds Handbook of service science
(pp. 79-104): Springer.
Bucherer, E., Eisert, U., & Gassmann, O. (2012). Towards systematic business model innovation:
lessons from product innovation management. Creativity and innovation management,
21(2), 183-198.
Burnes, B. (2015). Understanding resistance to change–building on Coch and French. Journal of
change management, 15(2), 92-116.
Camelo-Ordaz, C., Garcia-Cruz, J., Sousa-Ginel, E., & Valle-Cabrera, R. (2011). The influence of
human resource management on knowledge sharing and innovation in Spain: the mediating
role of affective commitment. The International Journal of Human Resource Management,
22(07), 1442-1463.
Cameron, E., & Green, M. (2015). Making sense of change management: A complete guide to the
models, tools and techniques of organizational change. Kogan Page Publishers.
Campos, A. C., Mendes, J., Valle, P. O. d., & Scott, N. (2018). Co-creation of tourist experiences:
A literature review. Current Issues in Tourism, 21(4), 369-400.
Capaldo, A. (2001). The leveraging of a dual network as a distinctive relational capability.
Evidence from three longitudinal case studies. Paper presented at the 2001 Academy of
Management (AOM) Conference.
Casadesus-Masanell, R., & Ricart, J. E. (2012). 22 Competing through business
models1. Handbook of Research on Competitive Strategy, 460.
Castellacci, F., & Natera, J. M. (2013). The dynamics of national innovation systems: A panel
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
161
cointegration analysis of the coevolution between innovative capability and absorptive
capacity. Research policy, 42(3), 579-594.
Cavana, R., & Delahaye, B. Uma Sekaran (2001). Applied Business Research: Qualitative &
Quantitative Method.
Chae, B. K. (2012). An evolutionary framework for service innovation: Insights of complexity
theory for service science. International journal of production economics, 135(2), 813-
822.
Chamsuk, W., Fongsuwan, W., & Takala, J. (2017). The Effects of R&D and Innovation
Capabilities on the Thai Automotive Industry Part’s Competitive Advantage: A SEM
Approach. Management and Production Engineering Review, 8(1), 101-112.
Chan Kim, W., & Mauborgne, R. (2004). Value innovation: The strategic logic of high growth.
Harvard business review, 82(7-8), 172-180.
Chandler, A. D. (1992). Organizational capabilities and the economic history of the industrial
enterprise. The Journal of Economic Perspectives, 6(3), 79-100.
Chandy, R. K., & Tellis, G. J. (2000). The incumbent’s curse? Incumbency, size, and radical
product innovation. Journal of marketing, 64(3), 1-17.
Chang, S., Gong, Y., & Shum, C. (2011). Promoting innovation in hospitality companies through
human resource management practices. International Journal of Hospitality Management,
30(4), 812-818.
Chen, J.-S., Tsou, H. T., & Huang, A. Y.-H. (2009). Service delivery innovation: Antecedents and
impact on firm performance. Journal of Service Research, 12(1), 36-55.
Chen, J.-S., Weng, H.-H., & Huang, C.-L. (2018). A multilevel analysis of customer engagement,
its antecedents, and the effects on service innovation. Total Quality Management &
Business Excellence, 29(3-4), 410-428.
Chesbrough, H., & Rosenbloom, R. S. (2002). The role of the business model in capturing value
from innovation: evidence from Xerox Corporation's technology spin‐off companies.
Industrial and Corporate Change, 11(3), 529-555.
Chiesa, V., Coughlan, P., & Voss, C. A. (1996). Development of a technical innovation audit.
Journal of Product Innovation Management: AN INTERNATIONAL PUBLICATION OF
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
162
THE PRODUCT DEVELOPMENT & MANAGEMENT ASSOCIATION, 13(2), 105-136.
Christensen, C. M., & Raynor, M. E. (2003). The innovation’s solution. Harvard Business School
Press, Boston, Massachusetts.
Christensen, J. F. s. (1996). Innovative assets and inter-asset linkages—A resource-based approach
to innovation. Economics of Innovation and New Technology, 4(3), 193-210.
Chung, G. H., Choi, J. N., & Du, J. (2017). Tired of innovations? Learned helplessness and fatigue
in the context of continuous streams of innovation implementation. Journal of
Organizational Behavior, 38(7), 1130-1148.
Clauss, T. (2017). Measuring business model innovation: conceptualization, scale development,
and proof of performance. R&D Management, 47(3), 385-403.
Coch, L., & French Jr, J. R. (1948). Overcoming resistance to change. Human relations, 1(4), 512-
532.
Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning
and innovation. Administrative science quarterly, 128-152.
Comes, S., & Berniker, L. (2008). Business model innovation From strategy to execution (pp. 65-
86): Springer.
Comes, S., & Berniker, L. (2008). Business model innovation. In From strategy to execution (pp.
65-86). Springer, Berlin, Heidelberg.
Conner, K. R., & Prahalad, C. K. (1996). A resource-based theory of the firm: Knowledge versus
opportunism. Organization science, 7(5), 477-501.
Corley, K. G., & Gioia, D. A. (2011). Building theory about theory building: what constitutes a
theoretical contribution?. Academy of management review, 36(1), 12-32.
Covin, J. G., & Lumpkin, G. T. (2011). Entrepreneurial orientation theory and research:
Reflections on a needed construct. Entrepreneurship theory and practice, 35(5), 855-872.
Covin, J. G., & Miles, M. P. (1999). Corporate entrepreneurship and the pursuit of competitive
advantage. Entrepreneurship theory and practice, 23(3), 47-63.
Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign
environments. Strategic Management Journal, 10(1), 75-87.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
163
Covin, J. G., & Wales, W. J. (2012). The measurement of entrepreneurial orientation.
Entrepreneurship theory and practice, 36(4), 677-702.
Cui, A. S., & Wu, F. (2017). The Impact of Customer Involvement on New Product Development:
Contingent and Substitutive Effects. Journal of Product Innovation Management, 34(1),
60-80.
Cummings, A., & Oldham, G. R. (1997). Enhancing creativity: Managing work contexts for the
high potential employee. California Management Review, 40(1), 22-38.
Danneels, E. (2004). Disruptive technology reconsidered: A critique and research agenda. Journal
of Product Innovation Management, 21(4), 246-258.
Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An
experiment using 5-point, 7-point and 10-point scales. International journal of market
research, 50(1), 61-104.
Day, G. S. (1994). The capabilities of market-driven organizations. The Journal of Marketing, 37-
52.
De Brentani, U., & Ragot, E. (1996). Developing new business-to-business professional services:
what factors impact performance? Industrial Marketing Management, 25(6), 517-530.
Deal, T. E., & Kennedy, A. A. (1983). Culture: A new look through old lenses. The journal of
applied behavioral science, 19(4), 498-505.
Del Canto, J. G., & Gonzalez, I. S. (1999). A resource-based analysis of the factors determining a
firm's R&D activities. Research policy, 28(8), 891-905.
Den Hertog, P., Van der Aa, W., & De Jong, M. W. (2010). Capabilities for managing service
innovation: towards a conceptual framework. Journal of service Management, 21(4), 490-
514.
Dent, E. B., & Goldberg, S. G. (1999). Challenging “resistance to change”. The Journal of applied
behavioral science, 35(1), 25-41.
Desyllas, P., & Sako, M. (2013). Profiting from business model innovation: Evidence from Pay-
As-You-Drive auto insurance. Research policy, 42(1), 101-116.
Dosi, G., Nelson, R., & Winter, S. (2001). The nature and dynamics of organizational capabilities:
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
164
OUP Oxford.
Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for
accelerating business model renewal. Long range planning, 43(2-3), 370-382.
Du Preez, N. D., Louw, L., & Essmann, H. (2006). An innovation process model for improving
innovation capability. J. High Technol. Manag. Res, 1-24.
Duane Ireland, R., Kuratko, D. F., & Morris, M. H. (2006). A health audit for corporate
entrepreneurship: innovation at all levels: part I. Journal of business strategy, 27(1), 10-
17.
Edvardsson, B. (1997). Quality in new service development: Key concepts and a frame of
reference. International journal of production economics, 52(1-2), 31-46.
Edvardsson, B., & Olsson, J. (1996). Key concepts for new service development. Service
Industries Journal, 16(2), 140-164.
Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: a
general analytical framework using moderated path analysis. Psychological
methods, 12(1), 1.
Egan, R. W., & Fjermestad, J. (2005). Change and Resistance help for the practitioner of change.
Paper presented at the System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual
Hawaii International Conference on.
Eggers, J. P., & Kaplan, S. (2013). Cognition and capabilities: A multi-level perspective. Academy
of Management Annals, 7(1), 295-340.
Eid, M. (2000). A multitrait-multimethod model with minimal assumptions. Psychometrika, 65(2),
241-261.
Ekvall, G. (1996). Organizational climate for creativity and innovation. European journal of work
and organizational psychology, 5(1), 105-123.
Eppler, M. J., Hoffmann, F., & Bresciani, S. (2011). New business models through collaborative
idea generation. International Journal of Innovation Management, 15(06), 1323-1341.
Euchner, J., & Ganguly, A. (2014). Business model innovation in practice. Research-Technology
Management, 57(6), 33-39.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
165
Evans, S., Vladimirova, D., Holgado, M., Van Fossen, K., Yang, M., Silva, E. A., & Barlow, C.
Y. (2017). Business model innovation for sustainability: Towards a unified perspective for
creation of sustainable business models. Business Strategy and the Environment, 26(5),
597-608.
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares
structural equation modeling (PLS-SEM) An emerging tool in business research. European
Business Review, 26(2), 106-121.
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares
structural equation modeling (PLS-SEM) An emerging tool in business research. European
Business Review, 26(2), 106-121.
Fisk, R. P., Brown, S. W., & Bitner, M. J. (1993). Tracking the evolution of the services marketing
literature. Journal of retailing, 69(1), 61-103.
Fleury, A., Fleury, M. T. L., & Borini, F. M. (2013). The Brazilian multinationals' approaches to
innovation. Journal of International Management, 19(3), 260-275.
Flikkema, M., Jansen, P., & Van Der Sluis, L. (2007). Identifying neo-Schumpeterian innovation
in service firms: A conceptual essay with a novel classification. Economics of Innovation
and New Technology, 16(7), 541-558.
Flower, O. D. (1962). Overcoming resistance to change [Film]. Beverly Hills, CA: Roundtable
Productions.
Folger, R., & Skarlicki, D. P. (1999). Unfairness and resistance to change: Hardship as
mistreatment. Journal of organizational change management, 12(1), 35-50.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and
measurement error: Algebra and statistics. Journal of Marketing research, 382-388.
Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: how far
have we come, and where should we go?. Journal of Management, 43(1), 200-227.
Foss, N. J., & Saebi, T. (2018). Business models and business model innovation: Between wicked
and paradigmatic problems. Long range planning, 51(1), 9-21.
Fox, K. J. (1999). Changing violent minds: Discursive correction and resistance in the cognitive
treatment of violent offenders in prison. Social Problems, 46(1), 88-103.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
166
Freel, M. S. (2005). Patterns of innovation and skills in small firms. Technovation, 25(2), 123-134.
Freeman, C., & Soete, L. (2009). Developing science, technology and innovation indicators: What
we can learn from the past. Research policy, 38(4), 583-589.
Froehle, C. M., Roth, A. V., Chase, R. B., & Voss, C. A. (2000). Antecedents of new service
development effectiveness: an exploratory examination of strategic operations choices.
Journal of Service Research, 3(1), 3-17.
Fu, X. (2008). Foreign direct investment, absorptive capacity and regional innovation capabilities:
evidence from China. Oxford Development Studies, 36(1), 89-110.
Furr, R. M., & Bacharach, V. R. (2014). Test dimensionality and factor analysis. Psychometrics:
an introduction, 61-77.
Furseth, P. I., & Cuthbertson, R. (2013). The service innovation triangle: a tool for exploring value
creation through service innovation. International Journal of Technology Marketing 24,
8(2), 159-176.
Gallouj, F., & Weinstein, O. (1997). Innovation in services. Research policy, 26(4-5), 537-556.
Gallouj, F., & Windrum, P. (2009). Services and services innovation: Springer.
Gambardella, A., & McGahan, A. M. (2010). Business-model innovation: General purpose
technologies and their implications for industry structure. Long range planning, 43(2-3),
262-271.
Gatignon, H., Tushman, M. L., Smith, W., & Anderson, P. (2002). A structural approach to
assessing innovation: Construct development of innovation locus, type, and characteristics.
Management science, 48(9), 1103-1122.
Gebauer, H., Worch, H., & Truffer, B. (2012). Absorptive capacity, learning processes and
combinative capabilities as determinants of strategic innovation. European Management
Journal, 30(1), 57-73.
Geissdoerfer, M., Vladimirova, D., Van Fossen, K., & Evans, S. (2018). Product, service, and
business model innovation: A discussion. Procedia Manufacturing, 21, 165-172.
George, G., & Bock, A. J. (2011). The business model in practice and its implications for
entrepreneurship research. Entrepreneurship theory and practice, 35(1), 83-111.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
167
Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development
incorporating unidimensionality and its assessment. Journal of marketing research, 25(2),
186-192.
Ghezzi, A., Cortimiglia, M. N., & Frank, A. G. (2015). Strategy and business model design in
dynamic telecommunications industries: A study on Italian mobile network
operators. Technological Forecasting and Social Change, 90, 346-354.
Giraud Voss, Z., Voss, G. B., & Moorman, C. (2005). An empirical examination of the complex
relationships between entrepreneurial orientation and stakeholder support. European
journal of Marketing, 39(9/10), 1132-1150.
Grant, R. M. (1996). Toward a knowledge‐based theory of the firm. Strategic Management
Journal, 17(S2), 109-122.
Green, S. G., Welsh, M. A., & Dehler, G. E. (2003). Advocacy, performance, and threshold
influences on decisions to terminate new product development. Academy of Management
Journal, 46(4), 419-434.
Guan, J., & Ma, N. (2003). Innovative capability and export performance of Chinese firms.
Technovation, 23(9), 737-747.
Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The interplay between exploration and
exploitation. Academy of Management Journal, 49(4), 693-706.
Hacklin, F., Björkdahl, J., & Wallin, M. W. (2018). Strategies for business model innovation: How
firms reel in migrating value. Long range planning, 51(1), 82-110.
Hair, J. F. (2010). Black, WC, Babin, BJ, & Anderson, RE (2010). Multivariate data analysis, 7.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: the better approach to
structural equation modeling?. Long Range Planning, 45(5-6), 312-319.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling:
Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2),
1-12.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial
least squares structural equation modeling in marketing research. Journal of the academy
of marketing science, 40(3), 414-433.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
168
Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its
top managers. Academy of management review, 9(2), 193-206.
Hamel, G. (2001). Leading the revolution: An interview with Gary Hamel. Strategy &
Leadership, 29(1), 4-10.
Hao, S., & Yu, B. (2011). The impact of technology selection on innovation success and
organizational performance. Ibusiness, 3(04), 366.
Hao, S., & Yu, B. (2011). The impact of technology selection on innovation success and
organizational performance. Ibusiness, 3(04), 366.
Harrison, R., & Mason, C. (1992). The role of investors in entrepreneurial companies: a
comparison of informal investors and venture capitalists: University of Southampton,
Urban Policy Research Unit.
Hart, S. L. (1992). An integrative framework for strategy-making processes. Academy of
management review, 17(2), 327-351.
Hauschildt, J. (1999). Opposition to innovations—destructive or constructive? The dynamics of
innovation (pp. 213-236): Springer.
Hauschildt, J., & Schewe, G. (2000). Gatekeeper and process promotor: key persons in agile and
innovative organizations. International Journal of Agile Management Systems, 2(2), 96-
103.
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A
regression-based approach. Guilford Publications.
Hayes, A. F. (2018). Partial, conditional, and moderated moderated mediation: Quantification,
inference, and interpretation. Communication Monographs, 85(1), 4-40.
He, Z.-L., & Wong, P.-K. (2004). Exploration vs. exploitation: An empirical test of the
ambidexterity hypothesis. Organization science, 15(4), 481-494.
Hedman, J., & Kalling, T. (2003). The business model concept: theoretical underpinnings and
empirical illustrations. European journal of information systems, 12(1), 49-59.
Hernández-Espallardo, M., Sánchez-Pérez, M., & Segovia-López, C. (2011). Exploitation-and
exploration-based innovations: the role of knowledge in inter-firm relationships with
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
169
distributors. Technovation, 31(5-6), 203-215.
Hertog, P. d. (2000). Knowledge-intensive business services as co-producers of innovation.
International Journal of Innovation Management, 4(04), 491-528.
Hii, J., & Neely, A. (2000). Innovative capacity of firms: on why some firms are more innovative
than others.
Hinterhuber, A., & Liozu, S. M. (2014). Is innovation in pricing your next source of competitive
advantage? Business Horizons, 57(3), 413-423.
Hitt, M. A., Bierman, L., Shimizu, K., & Kochhar, R. (2001). Direct and moderating effects of
human capital on strategy and performance in professional service firms: A resource-based
perspective. Academy of Management Journal, 44(1), 13-28.
Hitt, M. A., Ireland, R. D., Camp, S. M., & Sexton, D. L. (2001). Strategic entrepreneurship:
Entrepreneurial strategies for wealth creation. Strategic Management Journal, 22(6‐7),
479-491.
Hitt, M. A., Ireland, R. D., Sirmon, D. G., & Trahms, C. A. (2011). Strategic entrepreneurship:
creating value for individuals, organizations, and society. Academy of management
perspectives, 25(2), 57-75.
Hoffman, P. J., Festinger, L., & Lawrence, D. H. (1954). Tendencies toward group comparability
in competitive bargaining. Human Relations, 7(2), 141-159.
Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions and
organizations across nations: Sage publications.
Hogan, S. J., Soutar, G. N., McColl-Kennedy, J. R., & Sweeney, J. C. (2011). Reconceptualizing
professional service firm innovation capability: Scale development. Industrial Marketing
Management, 40(8), 1264-1273.
Holcomb, T. R., Ireland, R. D., Holmes Jr, R. M., & Hitt, M. A. (2009). Architecture of
entrepreneurial learning: Exploring the link among heuristics, knowledge, and action.
Entrepreneurship theory and practice, 33(1), 167-192.
Hoopes, D. G., Madsen, T. L., & Walker, G. (2003). Guest editors' introduction to the special
issue: why is there a resource‐based view? Toward a theory of competitive heterogeneity.
Strategic Management Journal, 24(10), 889-902.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
170
Hossain, M. (2018). Business model innovation: past research, current debates, and future
directions. Journal of Strategy and Management, 10(3), 342-359.
Huarng, K.-H., & Ribeiro-Soriano, D. E. (2014). Developmental management: Theories, methods,
and applications in entrepreneurship, innovation, and sensemaking. Journal of Business
Research, 67(5), 657-662.
Huarng, K.-H., Cervera, A., & Mas-Verdu, F. (2018). Innovation and service-dominant logic:
Springer.
Hult, G. T. M., & Ketchen Jr, D. J. (2001). Does market orientation matter?: A test of the
relationship between positional advantage and performance. Strategic management
journal, 22(9), 899-906.
Hurley, R. F., & Hult, G. T. M. (1998). Innovation, market orientation, and organizational learning:
an integration and empirical examination. The Journal of Marketing, 42-54.
Hwang, E. H., Singh, P. V., & Argote, L. (2015). Knowledge sharing in online communities:
Learning to cross geographic and hierarchical boundaries. Organization science, 26(6),
1593-1611.
Iddris, F. (2016). Measurement of innovation capability in supply chain: an exploratory study.
International Journal of Innovation Science, 8(4), 331-349.
Ireland, R. D., & Webb, J. W. (2009). Crossing the great divide of strategic entrepreneurship:
Transitioning between exploration and exploitation. Business horizons, 52(5), 469-479.
Ireland, R. D., Hitt, M. A., & Sirmon, D. G. (2003). A model of strategic entrepreneurship: The
construct and its dimensions. Journal of management, 29(6), 963-989.
Ireland, R. D., Hitt, M. A., & Sirmon, D. G. (2003). A model of strategic entrepreneurship: The
construct and its dimensions. Journal of management, 29(6), 963-989.
Johne, A., & Storey, C. (1998). New service development: a review of the literature and annotated
bibliography. European journal of Marketing, 32(3/4), 184-251.
Johnson, G., Scholes, K., & Whittington, R. (2008). Exploring corporate strategy: text & cases:
Pearson education.
Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
171
command language: Scientific Software International.
Kallio, A., Kujansivu, P., & Parjanen, S. (2012). Locating the weak points of innovation capability
before launching a development project. Interdisciplinary Journal of Information,
Knowledge, and Management, 7(1), 21-38.
Kamoche, K. (1996). Strategic human resource management within a resource‐capability view of
the firm. Journal of Management studies, 33(2), 213-233.
Kang, S. C., & Snell, S. A. (2009). Intellectual capital architectures and ambidextrous learning: a
framework for human resource management. Journal of Management studies, 46(1), 65-
92.
Kanter, R. M. (1984). Change masters: Simon and Schuster.
Keen, P. G. (1981). Value analysis: justifying decision support systems. MIS quarterly, 1-15.
Kegan, R., & Lahey, L. L. (2001). The real reason people won’t change. HBR’s 10 Must Reads on
Change, 77.
Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide:
Sage.
Kenny, D. A. (2014). Measuring model fit.
Keskin, H. (2006). Market orientation, learning orientation, and innovation capabilities in SMEs:
An extended model. European Journal of innovation management, 9(4), 396-417.
Kiani, M. N., & Gillani, S. H. M. (2014). The impact of learning organization practices on
organizational effectiveness. PAKISTAN BUSINESS REVIEW, 248.
Kim, J., Lee, S., Geum, Y., & Park, Y. (2012). Patterns of innovation in digital content services:
The case of App Store applications. Innovation, 14(4), 540-556.
Kim, W. C., & Mauborgne, R. (2004). Blue ocean strategy. If you read nothing else on strategy,
read thesebest-selling articles., 71.
King, D. R., Dalton, D. R., Daily, C. M., & Covin, J. G. (2004). Meta‐analyses of post‐acquisition
performance: Indications of unidentified moderators. Strategic Management Journal,
25(2), 187-200.
Knight, G. A., & Cavusgil, S. T. (2004). Innovation, organizational capabilities, and the born-
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
172
global firm. Journal of international business studies, 35(2), 124-141.
Knowles, C., Hansen, E., & Dibrell, C. (2008). Measuring firm innovativeness: Development and
refinement of a new scale. Journal of Forest Products Business Research, 5(5), 1-24.
Koen, P. A., Bertels, H. M., & Elsum, I. R. (2011). The three faces of business model innovation:
Challenges for established firms. Research-Technology Management, 54(3), 52-59.
Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the
replication of technology. Organization science, 3(3), 383-397.
Kotabe, M., Srinivasan, S. S., & Aulakh, P. S. (2002). Multinationality and firm performance: The
moderating role of R&D and marketing capabilities. Journal of international business
studies, 33(1), 79-97.
Koufteros, X. A. (1999). Testing a model of pull production: a paradigm for manufacturing
research using structural equation modeling. Journal of Operations Management, 17(4),
467-488.
Kowalkowski, C., Kindström, D., & Brehmer, P.-O. (2011). Managing industrial service offerings
in global business markets. Journal of Business & Industrial Marketing, 26(3), 181-192.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities.
Educational and psychological measurement, 30(3), 607-610.
Kungu, G., Desta, I., & Ngui, T. (2014). An assessment of the effectiveness of competitive
strategies by commercial banks: A case of Equity bank. International Journal of Education
and Research, 2(12), 333-346.
Lambert, S. C., & Davidson, R. A. (2013). Applications of the business model in studies of
enterprise success, innovation and classification: An analysis of empirical research from
1996 to 2010. European Management Journal, 31(6), 668-681.
Lau, C. M., & Woodman, R. W. (1995). Understanding organizational change: A schematic
perspective. Academy of management journal, 38(2), 537-554.
Lawson, B., & Samson, D. (2001). Developing innovation capability in organisations: a dynamic
capabilities approach. International Journal of Innovation Management, 5(03), 377-400.
Lenfle, S., & Midler, C. (2009). The launch of innovative product-related services: lessons from
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
173
automotive telematics. Research policy, 38(1), 156-169.
Lewin, K. (1951). Field theory in social science (D. Cartwright, Ed.). New York, 165.
Liao, S.-H., Fei, W.-C., & Chen, C.-C. (2007). Knowledge sharing, absorptive capacity, and
innovation capability: an empirical study of Taiwan's knowledge-intensive industries.
Journal of information science, 33(3), 340-359.
Lichtenthaler, U. (2009). Absorptive capacity, environmental turbulence, and the complementarity
of organizational learning processes: Academy of Management Briarcliff Manor, NY.
Lichtenthaler, U., & Lichtenthaler, E. (2009). A capability‐based framework for open innovation:
Complementing absorptive capacity. Journal of Management studies, 46(8), 1315-1338.
Loon, M., & Chik, R. (2018). Efficiency-centered, innovation-enabling business models of high
tech SMEs: Evidence from Hong Kong. Asia Pacific Journal of Management, 1-25.
Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and
linking it to performance. Academy of management review, 21(1), 135-172.
Lund Vinding, A. (2006). Absorptive capacity and innovative performance: A human capital
approach. Economics of Innovation and New Technology, 15(4-5), 507-517.
Maglio, P. P., & Spohrer, J. (2014). A service science perspective on business model innovation.
Industrial Marketing Management, 42(5), 665-670.
Makadok, R. (2001). Toward a synthesis of the resource‐based and dynamic‐capability views of
rent creation. Strategic Management Journal, 22(5), 387-401.
Malhotra, Y. (2000). Knowledge management for e-business performance: advancing information
strategy to “internet time”. Information Strategy: The Executive's Journal, 16(4), 5-16.
Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of
self-concept: First-and higher order factor models and their invariance across groups.
Psychological bulletin, 97(3), 562.
Martinez-Roman, J. A., Gamero, J., & Tamayo, J. A. (2011). Analysis of innovation in SMEs
using an innovative capability-based non-linear model: A study in the province of Seville
(Spain). Technovation, 31(9), 459-475.
Mazzei, M. J., Ketchen, D. J., & Shook, C. L. (2017). Understanding strategic entrepreneurship: a
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
174
“theoretical toolbox” approach. International Entrepreneurship and Management
Journal, 13(2), 631-663.
McClelland, D. C. (1961). The achievement society. Princenton, NJ: Von Nostrand.
McGrath, R. G. (2010). Business models: A discovery driven approach. Long range planning,
43(2-3), 247-261.
Mennens, K., Van Gils, A., Odekerken-Schröder, G., & Letterie, W. (2018). Exploring antecedents
of service innovation performance in manufacturing SMEs. International Small Business
Journal, 0266242617749687.
Menor, L. J., & Roth, A. V. (2007). New service development competence in retail banking:
Construct development and measurement validation. Journal of Operations Management,
25(4), 825-846.
Menor, L. J., Tatikonda, M. V., & Sampson, S. E. (2002). New service development: areas for
exploitation and exploration. Journal of Operations Management, 20(2), 135-157.
Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement.
Journal of consumer research, 4(4), 229-242.
Miles, I. (1993). Services in the new industrial economy. Futures, 25(6), 653-672.
Miller, D., & Friesen, P. H. (1982). Innovation in conservative and entrepreneurial firms: Two
models of strategic momentum. Strategic Management Journal, 3(1), 1-25.
Miller, D., & Le Breton–Miller, I. (2011). Governance, social identity, and entrepreneurial
orientation in closely held public companies. Entrepreneurship Theory and
practice, 35(5), 1051-1076.
Mintzberg, H. (2017). Planning on the left side, managing on the right Leadership Perspectives
(pp. 413-426): Routledge.
Mitchell, D., & Coles, C. (2003). The ultimate competitive advantage of continuing business
model innovation. Journal of business strategy, 24(5), 15-21.
Mitnick, B. M. (1975). The theory of agency. Public Choice, 24(1), 27-42.
Mitnick, B. M. (1982). REGULATION AND THE THEORY OF AGENCY 1. Review of Policy
Research, 1(3), 442-453.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
175
Mom, T. J., Van Den Bosch, F. A., & Volberda, H. W. (2007). Investigating managers' exploration
and exploitation activities: The influence of top‐down, bottom‐up, and horizontal
knowledge inflows. Journal of Management studies, 44(6), 910-931.
Momeni, M., Nielsen, S. B., & Kafash, M. H. (2015). Determination of Innovation Capability of
Organizations: Qualitative Meta Synthesis and Delphi Method. Proceedings of
RESER2015-Innovative Services in the 21st Century.
Morris, M. H., Webb, J. W., & Franklin, R. J. (2011). Understanding the manifestation of
entrepreneurial orientation in the nonprofit context. Entrepreneurship theory and practice,
35(5), 947-971.
Morris, M., Schindehutte, M., & Allen, J. (2005). The entrepreneur's business model: toward a
unified perspective. Journal of Business Research, 58(6), 726-735.
Nachtigall, C., Kroehne, U., Funke, F., & Steyer, R. (2003). Pros and cons of structural equation
modeling. Methods Psychological Research Online, 8(2), 1-22.
Narcizo, R. B., Canen, A. G., & Tammela, I. (2017). A conceptual framework to represent the
theoretical domain of “innovation capability” in organizations.
Narver, J. C., Slater, S. F., & Tietje, B. (1998). Creating a market orientation. Journal of market-
focused management, 2(3), 241-255.
Neely, A., Filippini, R., Forza, C., Vinelli, A., & Hii, J. (2001). A framework for analysing
business performance, firm innovation and related contextual factors: perceptions of
managers and policy makers in two European regions. Integrated manufacturing systems,
12(2), 114-124.
Nijssen, E. J., Hillebrand, B., Vermeulen, P. A., & Kemp, R. G. (2006). Exploring product and
service innovation similarities and differences. International Journal of Research in
Marketing, 23(3), 241-251.
Nilsson, F., Regnell, B., Larsson, T., & Ritzén, S. (2010). Measuring for innovation-A guide for
innovative teams. Applied Innovation Management(3).
Nisula, A.-M., & Kianto, A. (2013). Evaluating and developing innovation capabilities with a
structured method. IJIKM, 8.
O'Connor, G. C. (2008). Major innovation as a dynamic capability: A systems approach. Journal
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
176
of Product Innovation Management, 25(4), 313-330.
Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of
applied psychology, 88(4), 680.
Oreg, S. (2006). Personality, context, and resistance to organizational change. European journal
of work and organizational psychology, 15(1), 73-101.
Oreg, S., & Sverdlik, N. (2011). Ambivalence toward imposed change: The conflict between
dispositional resistance to change and the orientation toward the change agent. Journal of
Applied Psychology, 96(2), 337.
Oreg, S., Bayazit, M., Vakola, M., Arciniega, L., Armenakis, A., Barkauskiene, R., ... &
Hřebíčková, M. (2008). Dispositional resistance to change: Measurement equivalence and
the link to personal values across 17 nations. Journal of Applied Psychology, 93(4), 935.
Ostrom, A. L., Bitner, M. J., Brown, S. W., Burkhard, K. A., Goul, M., Smith-Daniels, V.,
Rabinovich, E. (2010). Moving forward and making a difference: research priorities for the
science of service. Journal of Service Research, 13(1), 4-36.
Page, A. L., & Schirr, G. R. (2008). Growth and development of a body of knowledge: 16 years
of new product development research, 1989–2004. Journal of Product Innovation
Management, 25(3), 233-248.
Parkman, I. D., Holloway, S. S., & Sebastiao, H. (2012). Creative industries: aligning
entrepreneurial orientation and innovation capacity. Journal of Research in Marketing and
Entrepreneurship, 14(1), 95-114.
Pearce, J. A., Fritz, D. A., & Davis, P. S. (2010). Entrepreneurial orientation and the performance
of religious congregations as predicted by rational choice theory. Entrepreneurship theory
and practice, 34(1), 219-248.
Pelham, A. M. (1997). Mediating influences on the relationsmp between market orientation and
profitability in small industrial firms. Journal of Marketing Theory and Practice, 5(3), 55-
76.
Penrose, E., & Penrose, E. T. (2009). The Theory of the Growth of the Firm: Oxford university
press.
Pisano, G. P. (1994). Knowledge, integration, and the locus of learning: An empirical analysis of
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
177
process development. Strategic Management Journal, 15(S1), 85-100.
Porter, M. E., Michael, & Gibbs, i. (2001). Strategy and the Internet.
Preissl, B. (2000). Service innovation: what makes it different? Empirical evidence from Germany.
In Innovation systems in the service economy (pp. 125-148). Springer, Boston, MA.
Priem, R. L., & Butler, J. E. (2001). Is the resource-based “view” a useful perspective for strategic
management research? Academy of management review, 26(1), 22-40.
Proctor, T. (2014). Strategic marketing: an introduction: Routledge.
PTA. (2018). PTA Annual Report 2018. Islamabad.
Raisch, S., Birkinshaw, J., Probst, G., & Tushman, M. L. (2009). Organizational ambidexterity:
Balancing exploitation and exploration for sustained performance. Organization science,
20(4), 685-695.
Rangus, K., & Slavec, A. (2017). The interplay of decentralization, employee involvement and
absorptive capacity on firms' innovation and business performance. Technological
Forecasting and Social Change.
Rauch, A., Wiklund, J., Lumpkin, G. T., & Frese, M. (2009). Entrepreneurial orientation and
business performance: An assessment of past research and suggestions for the future.
Entrepreneurship theory and practice, 33(3), 761-787.
Reinhold, O., & Alt, R. (2012). Social Customer Relationship Management: State of the Art and
Learnings from Current Projects. Paper presented at the Bled eConference.
Richardson, G. B. (2003). The organization of industry re-visited. Paper presented at the DRUID
Summer Conference.
Richter, M. (2013). Business model innovation for sustainable energy: German utilities and
renewable energy. Energy Policy, 62, 1226-1237.
Robbins, P., & O'Gorman, C. (2015). Innovating the innovation process: an organisational
experiment in global pharma pursuing radical innovation. R&D Management, 45(1), 76-
93.
Romijn, H., & Albaladejo, M. (2002). Determinants of innovation capability in small electronics
and software firms in southeast England. Research policy, 31(7), 1053-1067.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
178
Roscoe, J. T. (1975). Fundamental research statistics for the behavioral sciences [by] John T.
Roscoe.
Rousseau, D. (1995). Psychological contracts in organizations: Understanding written and
unwritten agreements. Sage publications.
Saebi, T., & Foss, N. J. (2015). Business models for open innovation: Matching heterogeneous
open innovation strategies with business model dimensions. European Management
Journal, 33(3), 201-213.
Saebi, T., Lien, L., & Foss, N. J. (2017). What drives business model adaptation? The impact of
opportunities, threats and strategic orientation. Long range planning, 50(5), 567-581.
Santos, F. M. (2012). A positive theory of social entrepreneurship. Journal of business ethics,
111(3), 335-351.
Santos, F. M., & Eisenhardt, K. M. (2009). Constructing markets and shaping boundaries:
Entrepreneurial power in nascent fields. Academy of Management Journal, 52(4), 643-671.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students: Pearson
education.
Saunila, M. (2014). Innovation capability for SME success: perspectives of financial and
operational performance. Journal of Advances in Management Research, 11(2), 163-175.
Sborn, A. (1992). Foster innovation and creative talent for the public, translated by Hasan
GhasemZadeh. Tehran: Niloofar Pub.
Schirmer, M., Hartmann, J., Bertel, S., & Echtler, F. (2015). Shoe me the way: a shoe-based tactile
interface for eyes-free urban navigation. Paper presented at the Proceedings of the 17th
International Conference on Human-Computer Interaction with Mobile Devices and
Services.
Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future
research agenda. International Journal of Innovation Management, 17(01), 1340001.
Schreyögg, G., & Kliesch‐Eberl, M. (2007). How dynamic can organizational capabilities be?
Towards a dual‐process model of capability dynamization. Strategic Management Journal,
28(9), 913-933.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
179
Selznick, P. (2011). Leadership in administration: A sociological interpretation: Quid Pro Books.
Sirmon, D. G., Hitt, M. A., Ireland, R. D., & Gilbert, B. A. (2011). Resource orchestration to create
competitive advantage: Breadth, depth, and life cycle effects. Journal of management,
37(5), 1390-1412.
Smith, M., Busi, M., Ball, P., & Van der Meer, R. (2008). Factors influencing an organisation's
ability to manage innovation: a structured literature review and conceptual model.
International Journal of Innovation Management, 12(04), 655-676.
Snow, C. C., & Hrebiniak, L. G. (1980). Strategy, distinctive competence, and organizational
performance. Administrative science quarterly, 317-336.
Soltani Tirani, F. (1999). Institutional Innovation in Organizations. the Institute for Cultural
Services Resa Publishing-Printing, 10, 2310-0079.
Song, M., Nason, R. W., & Di Benedetto, C. A. (2008). Distinctive marketing and information
technology capabilities and strategic types: A cross-national investigation. Journal of
International Marketing, 16(1), 4-38.
Sousa-Zomer, T. T., & Cauchick-Miguel, P. A. (2019). Exploring business model innovation for
sustainability: an investigation of two product-service systems. Total Quality Management
& Business Excellence, 30(5-6), 594-612.
Spieth, P., & Meissner Née Schuchert, S. (2018). Business Model Innovation Alliances: How To
Open Business Models For Cooperation. International Journal of Innovation Management,
22(04), 1850042.
Spieth, P., & Schneider, S. (2016). Business model innovativeness: designing a formative measure
for business model innovation. Journal of business Economics, 86(6), 671-696.
Spieth, P., Schneckenberg, D., & Matzler, K. (2016). Exploring the linkage between business
model (&) innovation and the strategy of the firm. R&D Management, 46(3), 403-413.
Spieth, P., Schneckenberg, D., & Ricart, J. E. (2014). Business model innovation–state of the art
and future challenges for the field. R&D Management, 44(3), 237-247.
Srivastava, S. C., & Shainesh, G. (2015). Bridging the Service Divide Through Digitally Enabled
Service innovations; Evidence from Indian Health Care Service Providers. MIS Q, 39(1).
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
180
Stambaugh, J. E., Yu, A., & Dubinsky, A. J. (2011). Before the attack: a typology of strategies for
competitive aggressiveness. Journal of Management Policy and Practice, 12(1), 49.
Storey, C., & Hull, F. M. (2010). Service development success: a contingent approach by
knowledge strategy. Journal of service Management, 21(2), 140-161.
Story, V. M., Raddats, C., Burton, J., Zolkiewski, J., & Baines, T. (2017). Capabilities for
advanced services: A multi-actor perspective. Industrial Marketing Management, 60, 54-
68.
Strebel, P. (1996). Why do employees resist change?. Harvard business review, 74(3), 86.
Subramaniam, M., & Youndt, M. A. (2005). THE INFLUENCE OF INTELLECTUAL CAPITAL
ON THE TYPES OF INNOVATIVE CAPABILITIES. [Article]. Academy of Management
Journal, 48(3), 450-463. doi: 10.5465/amj.2005.17407911
Sundbo, J. (1996). The balancing of empowerment. A strategic resource based model of organizing
innovation activities in service and low-tech firms. Technovation, 16(8), 397445-409446.
Swink, M., & Harvey Hegarty, W. (1998). Core manufacturing capabilities and their links to
product differentiation. International Journal of Operations & Production Management,
18(4), 374-396.
Tanaka, J. S., & Huba, G. J. (1985). A fit index for covariance structure models under arbitrary
GLS estimation. British Journal of Mathematical and Statistical Psychology, 38(2), 197-
201.
Tavassoli, M., Faramarzi, G. R., & Saen, R. F. (2014). Efficiency and effectiveness in airline
performance using a SBM-NDEA model in the presence of shared input. Journal of Air
Transport Management, 34, 146-153.
Teece, D. J. (2010). Business models, business strategy and innovation. Long range planning,
43(2-3), 172-194.
Teece, D. J. (2012). Dynamic capabilities: Routines versus entrepreneurial action. Journal of
Management studies, 49(8), 1395-1401.
Teece, D. J. (2018). Business models and dynamic capabilities. Long range planning, 51(1), 40-
49.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
181
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management.
Strategic Management Journal, 18(7), 509-533.
Terziovski, M. (2007). Building innovation capability in organizations: An international cross-
case perspective (Vol. 13): Imperial College Press.
Tether, B. S. (2003). The sources and aims of innovation in services: variety between and within
sectors. Economics of Innovation and New Technology, 12(6), 481-505.
Tian, L., & Wilding, G. E. (2008). Confidence interval estimation of a common correlation
coefficient. Computational statistics & data analysis, 52(10), 4872-4877.
Tidd, J., Bessant, J., & Pavitt, K. (2005). Managing innovation integrating technological, market
and organizational change: John Wiley and Sons Ltd.
Toivonen, M., & Tuominen, T. (2009). Emergence of innovations in services. The Service
Industries Journal, 29(7), 887-902.
Tonnessen, T. (2005). Continuous innovation through company wide employee participation. The
TQM Magazine, 17(2), 195-207.
Trapp, M., Voigt, K.-I., & Brem, A. (2018). Business models for corporate innovation
management: Introduction of a business model innovation tool for established firms.
International Journal of Innovation Management, 22(01), 1850007.
Valter, P., Lindgren, P., & Prasad, R. (2018). Valter’s Seven Forces; a Model for Analyzing the
Forces Affecting the Business Model Innovation Process. Nordic and Baltic Journal of
Information and Communications Technologies, 2018(1), 47-64.
Van Leeuwen, G., & Klomp, L. (2006). On the contribution of innovation to multi-factor
productivity growth. Economics of Innovation and New Technology, 15(4-5), 367-390.
Van Riel, A. C., & Lievens, A. (2004). New service development in high tech sectors: A decision-
making perspective. International Journal of Service Industry Management, 15(1), 72-101.
Van Riel, A. C., Lemmink, J., & Ouwersloot, H. (2004). High‐technology service innovation
success: a decision‐making perspective. Journal of Product Innovation
Management, 21(5), 348-359.
Van Riel, A. C., Lemmink, J., & Ouwersloot, H. (2004). High‐technology service innovation
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
182
success: a decision‐making perspective. Journal of Product Innovation Management,
21(5), 348-359.
Velu, C. (2016). Evolutionary or revolutionary business model innovation through coopetition?
The role of dominance in network markets. Industrial Marketing Management, 53, 124-
135.
Verhees, F. J., & Meulenberg, M. T. (2004). Market orientation, innovativeness, product
innovation, and performance in small firms. Journal of small business management, 42(2),
134-154.
Wales, W. J. (2016). Entrepreneurial orientation: A review and synthesis of promising research
directions. International Small Business Journal, 34(1), 3-15.
Wang, C.-h., Lu, I.-y., & Chen, C.-b. (2008). Evaluating firm technological innovation capability
under uncertainty. Technovation, 28(6), 349-363.
Watanabe, K., Fukuda, K., & Nishimura, T. (2015). A technology-assisted design methodology
for employee-driven innovation in services. Technology Innovation Management Review,
5(2).
Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2),
171-180.
Wiklund, J., & Shepherd, D. (2005). Entrepreneurial orientation and small business performance:
a configurational approach. Journal of Business Venturing, 20(1), 71-91.
Wiklund, J., & Shepherd, D. A. (2008). Portfolio entrepreneurship: Habitual and novice founders,
new entry, and mode of organizing. Entrepreneurship theory and practice, 32(4), 701-725.
Wirtz, B. W., Pistoia, A., Ullrich, S., & Göttel, V. (2016). Business models: Origin, development
and future research perspectives. Long range planning, 49(1), 36-54.
Witell, L., & Löfgren, M. (2013). From service for free to service for fee: business model
innovation in manufacturing firms. Journal of service Management, 24(5), 520-533.
Witell, L., Anderson, L., Brodie, R. J., Colurcio, M., Edvardsson, B., Kristensson, P., . . . Wallin
Andreassen, T. (2015). Exploring dualities of service innovation: implications for service
research. Journal of Services Marketing, 29(6/7), 436-441.
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
183
Yam, R. C., Guan, J. C., Pun, K. F., & Tang, E. P. (2004). An audit of technological innovation
capabilities in Chinese firms: some empirical findings in Beijing, China. Research policy,
33(8), 1123-1140.
Yam, R. C., Lo, W., Tang, E. P., & Lau, A. K. (2011). Analysis of sources of innovation,
technological innovation capabilities, and performance: An empirical study of Hong Kong
manufacturing industries. Research policy, 40(3), 391-402.
Yıldız, S., Baştürk, F., & Boz, İ. T. (2014). The effect of leadership and innovativeness on business
performance. Procedia-Social and Behavioral Sciences, 150, 785-793.
Yoo, W.-J., Choo, H., & Lee, S. (2018). A Study on the sustainable growth of SMEs: The
mediating role of organizational metacognition. Sustainability, 10(8), 2829.
Yunus, M., Moingeon, B., & Lehmann-Ortega, L. (2010). Building social business models:
Lessons from the Grameen experience. Long range planning, 43(2-3), 308-325.
Zack, M., McKeen, J., & Singh, S. (2009). Knowledge management and organizational
performance: an exploratory analysis. Journal of knowledge management, 13(6), 392-409.
Zahra, S. A., & Neubaum, D. O. (1998). Environmental adversity and the entrepreneurial activities
of new ventures. Journal of developmental entrepreneurship, 3(2), 123.
Zander, A. (1950). Resistance to change—its analysis and prevention. Advanced Management
Journal.
Zawislak, P. A., Cherubini Alves, A., Tello-Gamarra, J., Barbieux, D., & Reichert, F. M. (2012).
Innovation capability: From technology development to transaction capability. Journal of
technology management & innovation, 7(2), 14-27.
Zheng, Y., Liu, J., & George, G. (2010). The dynamic impact of innovative capability and inter-
firm network on firm valuation: A longitudinal study of biotechnology start-ups. Journal
of Business Venturing, 25(6), 593-609.
Zott, C., Amit, R., & Massa, L. (2011). The business model: recent developments and future
research. Journal of management, 37(4), 1019-1042.
Zwick, T. (2002). Employee resistance against innovations. International journal of Manpower,
23(6), 542-552.
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APPENDIX - I
RESEARCH SURVEY QUESTIONNAIRE
Respected Sir / Madam,
I am a PhD (scholar) from SZABIST Islamabad, pursuing my degree in Management Sciences program. It is
requested to please fill in this questionnaire to be carried for my dissertation work. I would like to inform you
that the information provided on this questionnaire solely for research purpose and it will be held confidential.
Thank you for your precious time!
A) Service Innovation Capabilities
How much do you agree with each statement?
1 ___________2_________3____________________4___________5__________6____________7
Strongly Disagree Disagree Slightly Disagree Neutral Slightly Agree Agree Strongly Agree
Sensing user needs
1 We systematically observe and evaluate the need of our customers 1 2 3 4 5 6 7
2 We analyze the actual use of our services 1 2 3 4 5 6 7
3 Our organization is strong in distinguishing different groups of users
and market segments 1 2 3 4 5 6 7
Sensing technological options
4 Staying up to date with promising new services and technologies is
important for our organization 1 2 3 4 5 6 7
5 In order to identify the possibilities for new services, we use different
information sources 1 2 3 4 5 6 7
6 We follow which technologies our competitors use 1 2 3 4 5 6 7
Conceptualizing
7 We are innovative in coming up with ideas for new service concepts 1 2 3 4 5 6 7
8 Our organization experiments with new service concepts 1 2 3 4 5 6 7
9 We align new service offerings with our current business and
processes 1 2 3 4 5 6 7
Coproducing and orchestrating
10 Collaborations with other organizations helps us in improving or
introducing new services 1 2 3 4 5 6 7
11 Our organization is strong in coordinating service innovation
activities involving several parties 1 2 3 4 5 6 7
12 Our organization is efficient in initiatives and maintaining the
partnerships 1 2 3 4 5 6 7
Scaling and stretching
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13 In the development of new services, we take into account our
branding strategy 1 2 3 4 5 6 7
14 Our organization is actively engaged in promoting its new services 1 2 3 4 5 6 7
15 We introduce new services by following our marketing plan 1 2 3 4 5 6 7
B) Service Innovation Success
How much do you agree with each statement?
1 ___________2_________3____________________4___________5__________6____________7
Strongly Disagree Disagree Slightly Disagree Neutral Slightly Agree Agree Strongly Agree
Short term success
16 The new service is an overall success 1 2 3 4 5 6
17 Success exceeds expectations. 1 2 3 4 5 6
18 The new service contributed to financial success 1 2 3 4 5 6
19 The new service was a good idea to invest in 1 2 3 4 5 6
20 The new service adds substantial value to other products and
services 1 2 3 4 5 6
Long term success
21 The new service contributed to commercial success. 1 2 3 4 5 6
22 The new service improved our competitive position. 1 2 3 4 5 6
23 The new service improved brand equity and reputation. 1 2 3 4 5 6
24 The new service enabled expansion into new markets 1 2 3 4 5 6
25 The new service increased customer satisfaction and loyalty 1 2 3 4 5 6
Indirect success
26 The new service increased in-house technological knowledge 1 2 3 4 5 6
27 The new service increased employee satisfaction. 1 2 3 4 5 6
28 The new service created innovation opportunities 1 2 3 4 5 6
C) Management Entrepreneurial Orientation
How much do you agree with each statement?
1 ___________2_________3____________________4___________5__________6____________7
Strongly Disagree Disagree Slightly Disagree Neutral Slightly Agree Agree Strongly Agree
Ready to Innovate
29. In general, the top managers of our organization favor a strong emphasis on
research and development, technological leadership and innovations. 1 2 3 4 5 6 7
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30. In the past five years, our organization has marketed a large variety of new lines of
products or services. 1 2 3 4 5 6 7
31. In the past five years, changes in our product or service lines have been mostly of
a minor nature (reverse coded) 1 2 3 4 5 6 7
Aggressively Competitiveness
32. In dealing with competitors, our organization often leads the competition,
initiating actions to which our competitors have to respond. 1 2 3 4 5 6 7
33. In dealing with competitors, our organization typically adopts a very competitive
posture aiming at overtaking the competitors. 1 2 3 4 5 6 7
Market Proactiveness
34. In general, the top managers of my organization have a strong propensity for high
risk projects (with chances of high return) 1 2 3 4 5 6 7
35. The top managers believe owing to the nature of environment, bold, wide-ranging
acts are necessary to achieve our organization objectives 1 2 3 4 5 6 7
36. When there is uncertainty, our organization typically adopts a “wait and see”
posture in order to minimize the probability of making costly decisions (reverse coded) 1 2 3 4 5 6 7
Risk Taking
37. Management actively responds to the adoption of “new ways of doing things” by
main competitors 1 2 3 4 5 6 7
38. We are willing to try new ways of doing things and seek usual, novel solutions. 1 2 3 4 5 6 7
39. We encourage people to think and behave in original and novel ways. 1 2 3 4 5 6 7
D) Employee Resistance
How much do you agree with each statement?
1 _______________2____________3______________4______________5_____________6
Strongly Disagree Disagree Slightly Disagree Slightly Agree Agree Strongly Agree
Routine seeking
40 I would rather be bored than surprise. 1 2 3 4 5 6
41 Generally change is not good 1 2 3 4 5 6
42 Whenever my life forms a stable routine, I look for ways to change it. 1 2 3 4 5 6
43 I prefer having a stable routine to experiencing change in my life 1 2 3 4 5 6
Emotional Reaction
44 If I were to be informed that there’s going to be a significant change
regarding the way things are done at work, I would probably feel stressed. 1 2 3 4 5 6
45
If I were to be informed that there’s going to be a change in one of my
assignment at work, prior to knowing what the change actually is, it
would probably stress me out.
1 2 3 4 5 6
46 When I am informed of a change of plans, I tense up a bit. 1 2 3 4 5 6
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47
If my boss changed the criteria of evaluating employees, it would
probably make me feel uncomfortable even if I thought I’d do just as well
without having to do any extra work.
1 2 3 4 5 6
48
If in the middle of the work year, I were to be informed that there’s going
to be a change in schedule of deadlines, prior to knowing what the change
actually is, I would probably presume that the change is worse
1 2 3 4 5 6
Short term focus
49 Changing plans seems like a real hassle to me 1 2 3 4 5 6
50 When someone pressures me to change something, I tend to resist it even
if I think the change may ultimately benefit me. 1 2 3 4 5 6
51 Once I have made plans, I am not likely to change them. 1 2 3 4 5 6
Cognitive Rigidity
52 I don’t change my mind easily 1 2 3 4 5 6
53 I don’t often change my mind 1 2 3 4 5 6
54 My views are very consistent over time. 1 2 3 4 5 6
E) Business Model Innovation
How much do you agree with each statement?
1 _________________2_________________3____________________4_________________5
Strongly Disagree Disagree Neutral Agree Strongly
Agree
E.1 Value Creation Innovation
New capabilities
55 Our employees constantly receive training in order to develop new
competences 1 2 3 4 5
56
Relative to our direct competitors, our employees have very up-to-date
knowledge and capabilities. 1 2 3 4 5
57
We constantly reflect on which new competencies need to be established in
order to adapt to changing market requirements. 1 2 3 4 5
New technology / equipment
58 We keep the technical resources of our company up-to-date. 1 2 3 4 5
59 Relative to our competitors our technical equipment is very innovative. 1 2 3 4 5
60
We regularly utilize new technical opportunities in order to extend our product
and service portfolio. 1 2 3 4 5
New partnerships
61 We are constantly searching for new collaboration partners. 1 2 3 4 5
62
We regularly utilize opportunities that arise from integration of new partners
into our processes. 1 2 3 4 5
63 We regularly evaluate the potential benefits of outsourcing. 1 2 3 4 5
64 New collaboration partners regularly help us to further develop our business
model. 1 2 3 4 5
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New processes
65 We were recently able to significantly improve our internal processes. 1 2 3 4 5
66
We utilize innovative procedures and processes during the manufacturing of
our products as well as in all business processes. 1 2 3 4 5
67 Existing processes are regularly assessed and significantly changed if needed. 1 2 3 4 5
E.2 Value Proposition Innovation
New offerings
68 We regularly address new unmet customer needs. 1 2 3 4 5
69 Our products or services are very innovative in relation to our competitors. 1 2 3 4 5
70
Our products or services regularly solve customer needs, which were not
solved by competitors. 1 2 3 4 5
New customers and markets
71 We regularly take opportunities that arise in new or growing markets. 1 2 3 4 5
72 We regularly address new, unserved market segments. 1 2 3 4 5
73
We are constantly seeking new customer segments and markets for our
products and services. 1 2 3 4 5
New channels
74 We regularly utilize new distribution channels for our products and services. 1 2 3 4 5
75
Constant changes of our channels have led to improved efficiency of our
channel functions. 1 2 3 4 5
76 We consistently change our portfolio of distribution channels. 1 2 3 4 5
New customer relationships
77 We try to increase customer retention by new service offerings. 1 2 3 4 5
78 We emphasize innovative/modern actions to increase customer retention (e.g.
CRM). 1 2 3 4 5
79 We recently took many actions in order to strengthen customer relationships. 1 2 3 4 5
E.3 Value Capture Innovation
New revenue models
80 We recently developed new revenue opportunities (e.g. additional sales, cross-
selling). 1 2 3 4 5
81
We increasingly offer integrated services (e.g. maintenance contracts) in order
to realize long-term financial returns. 1 2 3 4 5
82
We recently complemented or replaced one-time transaction revenues with
long-term recurring revenue models (e.g. Leasing). 1 2 3 4 5
83 We do not rely on the durability of our existing revenue sources. 1 2 3 4 5
New cost structures
84 We regularly reflect on our price-quantity strategy. 1 2 3 4 5
85 We actively seek opportunities to save manufacturing costs. 1 2 3 4 5
86
Our production costs are constantly examined and if necessary amended
according to market prices. 1 2 3 4 5
87 We regularly utilize opportunities which arise through price differentiation. 1 2 3 4 5
F) Demographics
88. Gender: Male/Female Organization: ___________________________________
89. Age: (1) Less than 30 yrs (2) 31 yrs - 40 yrs (3) Above than 40 yrs
90. Education: (1) Graduate (2) Post Graduation (3) MS/MPhil/PhD or Equivalent
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
189
APPENDIX - II
RESULTS OF CONFIRMATORY FACTOR ANALYSIS FOR ALL
CONSTRUCTS
Table 3.8. Results of Confirmatory Factor Analysis for All Constructs
Construct Sub-
Constructs Items
Factor
loadings
Error
term t-value
R2
(Item
reliability)
Model Fit Indices
Innovation
Capabilities
Sensing user
needs
1
2
3
.77
.83
.74
.06
.06
.07
12.84
13.84
10.57
.606
.685
.647 CMIN / df =2.01
P = .000
Absolute Fit measures:
RMSEA = .049, PCLOSE
= .758,
SRMR = .014
Incremental Fit measures:
NFI = .935, TLI = .957,
CFI = .966, GFI = .955,
AGFI = .933
Sensing
technological
options
4
5
6
.67
.74
.85
.10
.09
.08
6.70
8.22
10.62
.648
.649
.721
Conceptualiz
ation
7
8
9
.63
*Excluded
.93
.08
--
.06
7.87
--
15.5
.865
--
.699
Coproducing
and
Orchestrating
10
11
12
.69
.79
.76
.09
.08
.09
7.67
9.87
8.44
.675
.620
.685
Scaling and
Stretching
13
14
15
.69
.51
.75
.10
.09
.10
6.90
5.67
7.50
.671
**.262
.661
Innovation
Success
Short term
success
16
17
18
19
.774
.812
.745
.803
.05
.04
.06
.04
15.48
20.3
12.41
20.07
.600
.660
.654
.645
CMIN / df =2.62
P = .000
Absolute Fit measures:
RMSEA = .062, PCLOSE
= .603,
SRMR = .069
Incremental Fit measures:
NFI = .938, TLI = .949,
CFI = .961, GFI = .952,
AGFI = .927
Long term
success
20
21
22
23
24
25
*Excluded
.664
.567
.503
.658
.752
--
.09
.10
.08
.05
.07
--
7.38
5.67
6.29
13.16
10.74
--
.641
.621
**.253
.634
.666
Indirect
success
26
27
28
.717
.738
.863
.10
.08
.07
7.170
9.225
12.33
.614
.645
.746
Entrepreneur
ial
Orientation
Ready to
innovate
29
30
31
.810
.757
.797
.05
.06
.05
16.20
12.62
15.94
.656
.673
.636
CMIN / df =1.69
P = .003
Absolute Fit measures:
RMSEA = .041, PCLOSE
= .828,
SRMR = .012
Incremental Fit measures:
NFI = .962, TLI = .979,
CFI = .984, GFI = .971,
AGFI = .955
Aggressively
competitive
32
33
.931
.630
.07
.06
13.30
10.50
.867
.697
Market
Proactiveness
34
35
36
.672
.737
.843
.09
.08
.07
6.967
10.53
12.04
.652
.643
.711
Risk taking
37
38
39
.689
.792
.756
.09
.08
.09
7.656
9.900
8.400
.675
.628
.672
IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS
190
Employee
Resistance
Routine
seeking
40
41
42
43
.832
.793
.698
.753
.04
.04
.05
.04
20.80
19.82
13.90
18.83
.692
.629
**.487
.667
CMIN / df =2.29
P = .000
Absolute Fit measures:
RMSEA = .055, PCLOSE
= .906,
SRMR = .018
Incremental Fit measures:
NFI = .909, TLI = .935,
CFI = .946, GFI = .947,
AGFI = .926
Emotional
Reaction
44
45
46
47
48
.755
.625
.561
*Excluded
.513
.07
.07
.05
--
.04
10.79
8.929
11.22
--
12.82
.671
.690
.614
--
**.263
Short term
focus
49
50
51
.740
.687
.851
.07
.06
.05
10.57
11.45
17.02
.648
.672
.724
Cognitive
Rigidity
52
53
54
.719
.786
.753
.08
.06
.07
8.988
13.10
10.76
.617
.618
.668
Business
Model
Innovation
New
capabilities
55
56
57
.902
.979
.971
.01
.01
.01
90.2
97.9
97.1
.813
.958
.943
CMIN / df =2.37
P = .000
Absolute Fit measures:
RMSEA = .047, PCLOSE
= .628,
SRMR = .029
Incremental Fit measures:
NFI = .961, TLI = .965,
CFI = .985, GFI = .962,
AGFI = .951
New
technology
58
59
60
.886
.994
.999
.01
.004
.004
88.6
248.5
249.75
.785
.988
.998
New
partnerships
61
62
63
64
*Excluded
.979
.967
.977
--
.005
.006
.005
--
195.8
161.16
195.4
--
.959
.935
.954
New
processes
65
66
67
.847
.971
.973
.029
.016
.018
29.21
60.68
54.06
.718
.942
.947
New
offerings
68
69
70
.996
.971
.997
.001
.004
.001
996.0
242.75
997.0
.997
.943
.993
New
customer and
markets
71
72
73
.967
.971
.976
.007
.004
.004
138.1
242.7
244.0
.935
.942
.952
New channels
74
75
76
.973
*Excluded
.902
.005
--
.007
194.6
--
128.8
.969
--
.941
New
customer
relationships
77
78
79
.627
.847
*Excluded
.116
.036
--
5.405
23.52
--
.934
.717
--
New revenue
models
80
81
82
83
.814
.965
.964
.962
.015
.013
.014
.007
54.26
74.23
68.85
137.4
.663
.931
.929
.925
New cost
structures
84
85
86
87
.997
.871
.816
.993
.001
.022
.019
.001
997.0
39.59
42.94
993.0
.998
.758
.666
.998
Note. *Excluded = items that were previously excluded in light of EFA results and are not considered in latter stage
of construct reliability and confirmatory factor analysis. **values = possess lower item reliability and qualifies to be
dropped from final version of instrument.