Digital Transformation

A Study on the Role of IT Capability and Executive Sponsorship in Achieving Digital Maturity

Master Thesis

Author: Denitsa Danailova

Student number: 6087388

Date of submission: 23/06/2017

Qualification: MSc in Business Administration- Strategy Track

Institution: Amsterdam Business School, University of Amsterdam

Supervisor: Dr. Andreas Alexiou

Statement of Originality

This document is written by Denitsa Danailova who declares to take full responsibility for the

contents of this document.

I declare that the text and the work presented in this document are original and that no sources

other than those mentioned in this text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision and

completion of the work, not for the contents.

Abstract

Digital transformation is the hottest topic in the business world, yet academic literature has

understudied the phenomenon. As with every innovation, a lot of uncertainty accompanies the

concept. The concept itself remains ambiguous since digital transformation and digitization

are interchanged without necessarily being equivalent in meaning. Digital maturity is a more

accurate term to describe the never-ending natural but deliberate process of adapting to the

digital pressures from the external environment. This thesis adopts recognized antecedents of

organizational change in rapid environments such as dynamic capabilities and executive

sponsorship to test their validity in the new context of digital transformation, one that claims

to have the largest impact since the Second Industrial Revolution. By employing a cross-

industry survey among digital transformation managers from companies in the Netherlands

and the UK, we empirically tested with SEM-PLS method the extension of these change

determinants. The results show that there is a strong direct positive effect between IT-enabled

dynamic capabilities and the level of digital maturity. Senior management characteristics,

such as MBA or technical expertise seem to have no association with the ability of a firm to

digitally transform. Although expected, we found no evidence that the effect of IT-enabled

dynamic capabilities is moderated by leadership in terms of managerial support. Leadership

seems to have a direct effect on digital maturity itself. This thesis contributes to the literature

of dynamic capabilities, is among the first to empirically test in an academic setting the

antecedents of digital transformation, and provides guidance for managers on how to achieve

it.

Key words: IT-enabled dynamic capabilities, executive sponsorship, digitization, digital

maturity

Table of Contents

1. Introduction 5

2. Literature review 9

2.1. Digital Maturity 9

2.2. IT-enabled Dynamic Capabilities 15

2.3. Executive Sponsorship 23

3. Data and methods 29

3.1. Data collection 29

3.2. Measures 30

3.3. Method 32

4. Results 33

4.1. Data cleaning, descriptive statistics, EFA 33

4.2. SEM-PLS Measurement model 37

4.3. SEM-PLS Structural model 37

5. Discussion 40

5.1. Managerial implications 40

5.2. Limitations and ideas for further research 41

6. Conclusion 42

7. References 44

Appendix 1 Measures 47

Appendix 2 Descriptive statistics and EFA 55

1. Introduction

“Disrupt or be disrupted” is former Cisco CEO John Chambers‟ advice to firms that best

captures the urgency to adapt in the face of the phenomenon digital transformation (Kirkland,

2016). Digital technologies, such as big data, Internet of things, Industry 4.0, social media,

etc. call for a major organizational change. Digital transformation has become a buzzword in

the business world in the recent years. It is believed to be the next Industrial Revolution in

terms of size and impact and opportunities exist for those companies that manage to transform

while those who fail face the threat to discontinue their operations. Seventy-eight percent of

1559 executives surveyed in a study by the Massachusetts Institute of Technology and

Capgemini Consulting (Fitzgerald et. al 2013) indicated their belief that achieving digital

transformation will become crucial for their organizations in the next two years.

According to Gartner‟s 2017 CIO Agenda Survey spending on digital transformation

activities is on the rise, as companies that have already embraced digital transformation in

their strategic planning spend currently 34 percent and are expected to spend 44 percent by

2018 of their IT budget on embarking on explorative digital endeavors. Yet, a recent IDT

survey (2015) showed that while eighty percent of executive respondents admitted that they

see digital transformation as a top priority only thirty-eight percent have a clear

transformational strategy. The novelty and the extent of the concept that goes beyond

previous studies on innovation as well as the scarce academic literature on the topic do little

to guide practitioners on their path to digitally transform.

Although linked to technological change and disruption, the phenomenon of digital

transformation is way broader and multilevel. Digital transformation is a process with no

definite end and different companies may all be engaged in digital transformation but to

different extends depending on their level of digital maturity. Berghaus and Back (2016)

argue that digital transformation will be the most pronounced in industries which are

traditionally more customer centric, the B2C focused industries.

What distinguishes digital transformation from any rapid innovation is that it

encompasses all businesses and permeates all boundaries. It changes the way that companies

are doing business by creating a new digital ecosystem. Technology is only enabling but the

real focus is on the strategic implications and organizational change that has to occur.

According to Kane, Palmer, Phillips, Kiron, Buckley (2015) successful digital transformation

is less of a question of technology rather than strategy, culture, and talent development.

It is important to understand the true implications of the concept, relating it to another

concept it is often substituted with – digitalization. In this thesis, digital transformation is

defined as “the profound and accelerating transformation of business activities, processes,

competencies and models to fully leverage the changes and opportunities of digital

technologies and their impact across society in a strategic and prioritized way, with present

and future shifts in mind.” and digitalization as “the use of digital technologies to change a

business model and provide new revenue and value-producing opportunities; it is the process

of moving to a digital business.” (Louden, 2017). Companies embark on digital

transformation for three major reasons: to gain efficiency, to access new markets, or to

entirely transform their business model. Kane (2017) explains the problems associated with

the definitions of digital transformation, the difference between digital maturity and digital

transformation, and the reason why it is better to think in terms of digital maturity

conceptually in the first place. Digitization is not a linear or finite process. It is ongoing and

can take many paths. It is not a matter of choice whether the company wants to transform. It is

rather a necessity to cope with other players in its value chain- competitors, customers,

suppliers, partners, employees, even potential substitutes and new entrants- and the way that

they handle digital transformation. Digital transformation is not a process that can happen

overnight but it takes time to be learnt. It is then more accurate to represent with a maturity

model instead.

While the scarce previous literature has linked digital transformation with organizational

structure, agility, absorptive capacity, and dynamic capabilities, the human side of the

transformation has been surprisingly neglected. In this turbulent environment when entire

business models need to be redefined, people need the vision and the safety net of a strong

leadership figure that leads them more than ever. In reality, digital transformation success

would involve a combination and inputs from both a strong organizational capability base and

an inspiring leadership to navigate the team in the right direction to change.

Numerous studies have proven empirically that dynamic capabilities help companies to

sustain or improve their firm performance when embracing new technology. A recent study

by Wamba (2017) provides evidence for the interrelatedness of IT infrastructure and expertise

with higher-level process-oriented dynamic capabilities. According to their results, the

embedment of a stable IT base with corresponding dynamic capabilities facilitated a profit-

leading big data adoption. King and Tucci (2002) posit that dynamic capabilities are indeed

the enablers for incumbent companies to enter new technology created niches and to

ultimately survive.

Studies also show that management capabilities compliment the positive effect of

dynamic capabilities during technologically triggered strategy change. New roles such as

Chief Information Officer (CIO) and more recently the Chief Digital Officer (CDO) have

emerged to lead the organization towards digital transformation. King and Tucci (2002)

advocate the moderating role of management on dynamic capabilities in times of disruption.

Kaplan (2008) finds that CEO cognition and attention can even compensate for the lack of

some organizational capabilities in the context of fiber optics adoption. Furthermore,

leadership can provide the impetus for organizational transformation by updating underlying

dynamic capabilities. Without leadership, the power of dynamic capabilities would have been

insufficient to trigger the needed degree of change, Rosenbloom show for the case of NCR. It

can be inferred that top management characteristics are as important as the organizational

such for determining firm transformational success.

As a novel topic in academic research, little research has been done on digital

transformation and the studies are primarily qualitative and exploratory. Prior research has

focused either on management cognition or dynamic capabilities. Therefore, this thesis aims

to connect the human and technological sides of organizations when evaluating digital

transformation endeavors. The research question of this paper is

What is the role of executive sponsorship and IT capability in successful adoption of

digital transformation? What distinguishes digitally mature companies from those in the

initial stages of digital maturity?

Executive sponsorship in this thesis entails characteristics, such as top management

technical experience, MBA business education, and their interpersonal communication skills

from the employees‟ point of view. IT capabilities are the abilities of companies to

continuously leverage their IT base to improve business processes and to adapt them

strategically when change requires it. With the concept of digital maturity, we want to capture

the ongoing transformation process of companies. We seek to understand which underlying

TMT characteristics and firm capabilities a company needs to move along on this process.

Following the findings of previous studies discussed above, it is expected that possessing IT

capabilities will enhance the transition that companies make towards becoming digitally

transformed. The background of the responsible management (CIO or CDO) and their support

for employees during the period of rapid change, play a moderating role for the positive effect

of these IT capabilities on digital maturity.

Answering these questions hides substantial managerial and academic implications. On

the one hand, this research provides the first steps to empirically test digital maturity and its

antecedents. It provides insights on the commonalities between digital transformation and any

other rapid innovation disruption in the past by testing on new grounds the established

enablers of change- dynamic capabilities and executive sponsorship. On the other hand, it

guides management when taking decisions on digital initiatives. The research contributes

generalizable across industries results and shows which capabilities firms should strengthen

and what are the characteristics of senior management that smooth the process of

transformation before embarking on their digital journey.

The rest of the thesis will be structured as following. First, major relevant studies will be

presented in the literature review section. The concepts of interest and the corresponding

hypothesis will be developed. Then, the data and methods section will provide an overview of

the data collection process and the methodology employed to test the previously established

hypotheses. A results section will follow explaining the findings from the model tested. In the

discussion section, academic and managerial contributions as well as the limitations of the

study and possible directions for further research will be suggested. Finally, a conclusion

presenting an overview and takeaways will complete this thesis.

2. Literature review

2.1. Digital Maturity

Digital technologies, such as big data, Internet of things, Industry 4.0, social media, etc.

permeate the business world and propel transformation of business practices at tempos never

observed before. Companies must assess their current business models and adapt them to

survive but also to reap the emerging opportunities, Remane, Hanelt, and Wiesboeck (2017)

claim. There is disagreement about the real meaning of the term digital transformation. In

general, it is used to describe the demand from the rapidly changing environment towards

organizations to alter the ways in which they think, operate, and are managed. It is misleading

to think of digital transformation only as the adoption of state-of-the art digital technology,

posits Kane (2017). Recognizing that this technology should be utilized to help the company

do business in new and improved ways is closer to the truth but is still insufficient. The most

accurate definition of digital transformation is implementing new processes, practices, and

business models to be able to compete in the digital economy and stay relevant.

Berghaus and Bark (2016) also stress that digital transformation is a complex

multidimensional phenomenon that exceeds the degree of organizational change studied in the

past. It involves a technology-enabled change across the whole organization. On the one hand,

companies gain efficiency by leveraging digital technologies for existing processes. On the

other hand, they can even embark on the path of business model innovation enabled by digital

transformation (Berghaus and Back, 2016). To digitally transform, companies should rethink

their current organizational model and involve multiple divisional stakeholders- from strategy,

through marketing, to HR.

As with every management fashion, digital transformation is accompanied with a high

degree of uncertainty and the IDT survey (2015) confirmed that even though managers admit

the importance of digitally transforming, only a fraction of them have developed a strategy

how to accomplish that. Consultancy reports and practice-oriented research have addressed

this uncertainty by developing the concept of digital maturity. The concept allows for a more

thorough grasp of the undergoing sociotechnical dynamics and the equifinality of digital

transformation for different companies. Remane et al. (2017) argue that the most accurate

definition of digital maturity is “the status of a company‟s digital transformation”. This

definition is useful as it allows managers the ease to evaluate their current position and take

actions adjusted for their company‟s situation to reach a different level of digital

transformation. It makes the transformation process more tangible.

Kane (2017) also addresses the problems associated with the definitions of digital

transformation, the difference between digital maturity and digital transformation, and the

reason why it is better to think in terms of digital maturity conceptually. According to him

digitization is not a linear or finite process. It is ongoing and can take many paths. It is not a

matter of choice whether the company wants to transform. It is rather a necessity to cope with

other players in its value chain- competitors, customers, suppliers, partners, employees, even

potential substitutes and new entrants- and the way that they handle digital transformation.

Technology is only one aspect of digitization; among the others are strategy, organizational

culture and structure, and leadership. That is why it makes sense to employ the concept of

maturity as in learning the ability to react to external change outside of the control of the

organization.

Borrowing the term maturity from biology, we can make several useful analogies. First,

an organization will not and cannot become transformed overnight. This is a process and the

organization just as an individual must go through different stages of development. No matter

at which stage a company is, and as already mentioned different companies will likely be at

different stages, it can always grow further. As such, digital transformation is never ending

but one can adapt the lessons learnt and improve. Second, working with the term maturity

gives practitioners the ease to embark on the digital journey even in uncertainty, when they

cannot foresee the outcome of their digital endeavors. Third, it reminds managers that digital

maturity is a natural process that each company must undergo. However, it is not an automatic

process. Managers leading the transformation should take deliberate actions to learn digital

trends so that they can help the organization adapt. The permeability across functions and

departments, however, if combined with incomplete understanding of the organization in the

first place, makes managers struggle in setting the needed steps and prioritize them in time.

Some companies, for example the ones which are traditionally more customer-centric such as

the B2C ones, figure out their roadmap of transformation earlier. Others need guidance in

specific generalizable actions in this non-linear transformation process.

Berghaus and Back (2016) provide a Digital Maturity Model (DMM) that derives

maturity stages across 9 dimensions during the digital transformation process. Being broken

down into stages across certain criteria, digital transformation becomes easier to understand.

The aspects that define digital maturity according to the authors can be grouped around (1)

customer experience, (2) product innovation, (3) strategy, (4) organization, (5) process

digitization, (6) collaboration, (7) information technology, (8) culture and expertise, and (9)

transformation management. They invited managers with a good overview of the company

and digital initiatives in general to evaluate whether they agree (on a 5-point Likert scale)

with statements connected to the aspects in the context of their company. This resulted in the

case of 5 distinct clusters and stages of maturity, the items of each were grouped together

based on the difficulty to accomplish them. In their study, they find that the easiest to achieve

dimensions are customer experience and process digitization, whereas strategy and

collaboration were the least obtainable. The study resulted in some interesting conclusions.

First, digital change is a result of staff affinity and commitment to digital transformation. The

first stages of the digital process include the familiarity of employees with digital tools, their

use and promotion. Second, technology and having leadership qualities from the side of top

management promote digital transformation.

In this thesis, a similar approach is adopted. Managers involved in digital transformation

evaluated facets of digital transformation on a 7-point Likert scale. However, we decided that

it is best to use an independent assessment index developed by the Australian government for

the purposes of this study. The reason is the following. Despite the descriptive usability of

Berghaus and Back model in explaining the phenomenon digital transformation on an

organizational level, they stop at developing the model as clusters of aspects which require a

similar level of effort to attain. They provide no link between digital maturity and its potential

antecedents. The scholars claim the descriptive merits of their work at the expense of

prescriptive functionality. This thesis connects the concept of nonlinear transformation with

dynamic capabilities, which have been long established in the strategy literature as drivers and

enablers of organizational change. By doing so, the aim is to contribute possible courses of

action and capabilities that need to be established first before companies embark on their

successful digital journey. As such, the current model already requires high degrees of

freedom and therefore we restrain from cluster analysis in the dependent variable and instead

define one high level of digital maturity in a single factor following the dimensions proposed

by the Australian Maturity Tool.

Remane et al. (2017) aim to clear the perception of digital maturity as a two-dimensional

concept, the one dimension of which accounts for the impact of digital transformation on the

firm and the other caters for the readiness of the firm to transform. In most maturity studies,

scholars use only the readiness as an indicator of maturity. Remane et al. take a firm-specific

approach, stressing that there is no ultimate optimal level of maturity that each firm should

strive for, but that digital maturity should be aligned with the impact that transformation has

on it. The scholars link these two dimensions to the two factors believed to be of decisive

importance for the survival of a company in the face of disruption. Digital impact refers to the

managerial ability to perceive the significance of the coming change. Whether the manager is

able to summon the existing resource and capability basis to prepare the company is best

measured with the degree of digital readiness.

As mentioned, most of the studies on digital maturity are non-academic and as such may

lack scientific rigor. This thesis contributes to investigating the construct of digital maturity

by developing an empirical model for its antecedents. We adopt the definition of digital

maturity as digital readiness defined by Berghaus and Back (2016) but by using the survey

items developed by the Australian government. Remane et al. (2017) include digital impact to

distinguish between the need to transform in firm specific contexts. Our research includes a

general measure of digital maturity as readiness to transform. Distinguishing between impact

and readiness may include bias as managers may easily under or overestimate the impact of

digital disruption in their firm. It is very difficult to foresee the full effects of disruption.

Rosenbloom (2000) claimed that the internet alone triggered such a tremendous wave of

change in the beginning of the millennium that even then it was inevitable that every company

would sooner or later encounter a technology that is disruptive to its operations. Therefore, we

assume the viewpoint that it is crucial to be ready to transform regardless of the potential

impact of change on a firm specific level.

Finally, the Australian government assessment tool entails 17 elements, which correspond

to a highly digitally transformed company. These are (1) strategy across departments. (2)

engagement with employees, (3) digital ownership, (4) integration of digital strategy, (5)

consumer understanding, (6) change appetite, (7) strategy initiative development, (8)

engagement of staff with digital media, (9) digital policies, (10) staff digital training, (11)

resource allocation for digital initiatives, (12) staff digital capabilities, (13) process

innovation, (14) digital service, (15) integration of digital channels with processes, (16)

strategy alignment, and (17) IT strategy, and their exact definitions are included in the

Appendix.

2.2. IT-enabled dynamic capabilities

Berghaus and Bark (2016) define digital transformation as a technology-enabled major

change. King and Tucci (2002) argue that any technological innovation creates opportunities

for entering new markets, just as in the case of digital transformation. The ability to enter

these new markets is contingent on the organizational abilities of firms, captured in dynamic

capabilities (Eisenhardt and Martin, 2000). Karimi and Walter (2015) extend on the

disruptive innovation literature by exploring the role of dynamic capabilities for reacting to

digital disruption. Even though technology is just the enabler and digital transformation

involves the integration of business, IT, and digital strategy, in the context of culture,

leadership and talent development (Kane, 2015), it is a starting point to analyze the ability of

the firm to leverage its IT resources. IT-enabled dynamic capabilities encompass as a second-

order construct the integration of IT and business operations to create value. Lu and

Ramamurthy (2011) prove the positive effect of IT capabilities on agility. IT capabilities

accelerate the decision making process to respond swiftly to changing market requirements.

Hassna, Wei, and Lowry (2014) use case studies to prove IT capabilities as antecedents of

transformation as a respond to digital disruption.

Ultimately, companies which are successful in utilizing their IT base, have gained the

experience and adaptability needed to get ahead and undergo a smoother transformation

process in the face of digital disruption. They are better equipped to reconfigure their

resources, which will result in a more digitally mature and evolved form of transformation.

This is the main hypothesis the thesis will test.

Hypothesis 1: Companies which possess IT Capabilities are more Digitally Mature.

The development of the concept of IT-enabled dynamic capability is explained as

follows. Bharadwaj (2000) first introduces the notion of IT capabilities in the beginning of the

2000s at the peak of the Dot-com bubble. At this time, scholars experienced growing

skepticism towards the actual benefits of IT. Despite the belief that IT was crucial for the

firm‟s survival and growth, it was not apparent how investments in IT led directly to financial

gains (Nolan, 1994). Several studies found mixed or inconclusive results about the direct link

from IT investment to business value, in terms of return on assets, return on equity, etc.

Bharadwaj (2000) offers an explanation to this “productivity paradox” by arguing that IT

solely is not sufficient to contribute to sustained competitive advantage and translate into

monetary gains. Instead, it is the underlying mechanisms of using and reconfiguring IT that

differentiate successful from not successful companies.

In this way, Bharadwaj (2000) expands on the Resource-based view and argues that IT is

nothing less than an organizational capability and that actual IT investments are solely

resources. In this sense, following Barney‟s (1991) criteria for resources to be sources for

sustainable competitive advantage (being firm-specific, rare, and difficult to imitate or

substitute) IT investments cannot provide sustained advantages because they are easy to

reproduce from the competitors. Among firms who spend equally high amounts on

technology, the one that can leverage better its investment is the one who possesses better

human IT resources and intangibles, such as customer orientation and organizational

knowledge. Grant (1991) makes the clear distinction between resources and capabilities.

Whereas resources can be tangible (technology, physical assets), intangible (brand or product

quality) and staff related (technical know-how and organizational culture), their assembling to

work together and deploying creates organizational capabilities. Grant later, in 1995, makes a

hierarchical classification of capabilities where specialized capabilities are further integrated

into functional capabilities, among which Grant puts IT capabilities, and finally integrated

into cross-functional capabilities, such as customer orientation capability.

Scholars proposed different IT related resources that potentially could lead to competitive

advantage, among which a close cooperation with an IT firm or managerial IT skills.

Bharadwaj (2000) uses Grant‟s (1991) classification for IT resources: tangible, intangible, and

personnel-based. He defines IT capabilities as the ability of the firm to summon, integrate,

and deploy IT-based resources complemented with other firm resources and capabilities. The

tangible resources constitute of the IT infrastructure. As already mentioned, physical IT

systems can readily be bought or copied by competitors and cannot be a source of sustained

advantage. However, this is true only for the individual components of the systems and

ignores any benefits that may arise from the synergy of fully integrated IT infrastructure.

Seamlessly integrated components are tailored for the strategic needs of a firm and are not

easy to copy or imitate. Further, firms who already have deployed IT systems may enjoy time

compression diseconomies (Dierickx and Cool, 1989). That means that these firms have

gained enough experience to outperform any late comers. This experience and IT

infrastructure resources allow firms subsequently to continuously innovate and improve their

products and processes. This is where the difference of costs and value of innovations in

different companies comes from. Bharadwaj concludes that firms which have a strong IT

infrastructure can readily identify and develop new applications at the right time as well as

exploit synergy opportunities.

Human and managerial skills fall under human IT resources. This can be either technical

IT skills, such as programming, or managerial IT skills, all gained through experience,

training, and relationships of the employees. Well-performing firms distinguish themselves by

having the managerial ability to integrate and coordinate user contact with project

management and leadership qualities, ensuring the successful implementation of IT systems.

Further, the ability of the organization to rapidly change and develop and deploy critical IT

systems can be traced to a skilled workforce.

Finally, knowledge assets and customer orientation belong to the intangible IT

capabilities. Scholars who have been skeptical about the direct positive effects of IT to firm

performance have emphasized that IT can create value through leveraging other pre-existing

resources. This comes to say that IT actually has an enabling or complementary role to

organization intangibles, the three perhaps most important of which according to Bharadwaj

are customer orientation, knowledge assets, and synergy. As such, the true value of IT is

derived from the complex social relationships between IT systems and other parts of the

organization.

Simply investing in or purchasing IT systems will not deliver the desired long-term effect

unless the personnel are able to achieve any of the following. First, they are able to extract the

information provided by the systems and use it to improve customer relationship seamlessly.

Second, the staff can translate accumulated knowledge into firm specific assets embedded into

these systems and make it therefore difficult to copy by competitors. Finally, employees

together with management can use IT systems to achieve synergy through making firm

resources more available and shareable. By removing any limitations to communication,

whether physical, spatial, or temporal, firms become more flexible to react to market changes

and trends.

The realization of all of these intangible benefits requires changes in the organization

structure and management and coordination of both social and technical aspects. The

interaction of all three aspects of IT, tangible, intangible and human-embedded defines the

firm‟s IT organizational capability. The involvement of the social context and other

intangibles in the organization make this interaction more complex and leads to the

heterogeneity when it comes to firms profiting from their IT investments.

Bharadwaj (2000) proceeds with proving the link between IT and firm performance, in

the sense that firms who exhibit a higher level of IT capability by combining effectively

different IT resources are able to achieve superior financial performance. In his analysis,

Bharadwaj (2000) links firms assessed as IT leaders by experts to comparable control group

of firms from the same industry and size. He finds that indeed the IT leader firms achieved

both higher profit ratios and lower cost ratios in comparison to the control firms. The

relationship between superior IT capability and firm performance is positive and significant.

The conclusion that the author makes is that IT dollar investments are not an accurate proxy

for IT intensiveness. IT resources take time to acquire and the complexity associated with

creating a firm-wide IT capability from them derives from social embedment and resource

complementarity. IT should be understood as a capability to leverage technology as a

differentiation strategy rather than a combination of technological functionalities (Henderson

and Venkatraman, 1993). Path dependencies, causal ambiguity, and time compression

diseconomies impede competitors from imitating the success that one company was able to

achieve with its IT capability.

Mikalef and Pateli (2017) have developed the work of Bharadwaj (2000). They set the

goal to fill in one of the major limitations gap in the RBV operationalization of IT

capabilities, mainly through which mechanisms do IT capabilities contribute to superior

competitive performance. The scholars base their analysis on the notion that IT capabilities

should be examined in terms of the organization processes they facilitate. The effect on firm

performance would thus be indirect. Mikalef and Pateli (2017) argue that the effect that IT has

on firm performance is mediated by enabling organizational agility.

They start with discussing the difference between operational and dynamic capabilities,

being that dynamic capabilities help firms adapt, reconfigure, and change to rapid shifts in

their external environment (Winter, 2003). They focus on the second, bringing dynamism into

examining the value that IT brings. Digitalization certainly provides a source of change that

requires the understanding of dynamic capabilities. Following the definition of Teece (2007),

dynamic capabilities represent the deliberate action of reconfiguring and deploying new

operational capabilities to address changing business environments. As such, they constitute

a set of identifiable and specific routines. To understand dynamic capabilities better, one can

concentrate on these set of routines that comprise them.

Mikalef and Pateli (2017) focus on the sub-dimensions of dynamic capabilities as

proposed by Teece, Pisano and Shuen (1997) (reconfiguring, learning, integrating, and

coordinating). Teece (2007) adds sensing the environment as the final sub-dimension. All five

of these processes enable organizational capability revival. Dynamic capabilities serve as

strategic options, since firms can use them to reconfigure their organizational capabilities

should the changing environment require it. Learning is the ability to “acquire, assimilate, and

exploit new knowledge that enables informed decision making”. The learning process is one

of repetition and experimentation and is intrinsically social in its nature, Teece (1997) argues.

Individual but also organizational skills are involved in the learning process as it is a

collection of individual contributions. Common language and codes within the organization

facilitate knowledge creation and ensure the smooth process to be carried out as a group

routine. Collaborations and joint ventures allow also inter-organizational learning where

companies can figure out the blind spots in their own routines compared to other companies

and act upon them (Teece et al. 1997). Sensing is the ability to “spot, interpret and pursue

opportunities in the environment”. It is about identifying market developments, new

technologies, and market opportunities and expecting how competitors, potential entrants,

suppliers, and consumers will react. Based on this information, the firm can make a decision

on what technologies to pursue and which market segment to situate itself in. Coordinating is

defined as the capacity to “orchestrate and deploy tasks and resources and synchronize

activities with involved stakeholders”. Firms which succeed in coordinating ability can

benefit from synergy and complementarities, increase efficiencies, and knowledge transfer

through collaboration. Integrating on its turn is the ability of a firm to evaluate its own and its

partners resources and capabilities and to incorporate and exploit them in new or updated

organizational capabilities. The ability to integrate is the key driver of dynamic capabilities

according to Teece (2007). Last but not least, reconfiguring is the ability of firms to enact

strategic decisions and change of direction. Reconfiguration allows firms to make the difficult

rapid change in their organizational capabilities and avoid their capabilities turning into

rigidities.

So defined, the five complementary facets of IT-enabled dynamic capabilities create a

virtuous circle and help firms survive and grow in periods of unexpected changes in the

business environment when firms have to react very quickly and enact new strategic

directions. This firm-wide ability is known as organizational agility and it mediates the

relationship between IT capabilities and firm performance. Mikalef and Pateli develop and

verify the validity of constructs in a survey about the processes in which IT is embedded.

They targeted high-level executives, primarily CIOs, CEOs and IT managers, as they believe

that TMT would have the right knowledge to answer questions related to the firm-level

business and technical aspects of the constructs. The importance of their paper is that it

conceptualizes, operationalizes, and measures IT capabilities and allows for equifinality,

meaning that there are different paths through which IT capabilities can be achieved, each

having different combinations of underlying IT resources. The details of the scale they

develop will be explained further in the methodology section as this thesis recreates it.

Finally, Karimi and Walter (2015) test dynamic capabilities effect on digitization in the

newspaper industry. They argue that first-order dynamic capabilities, created by molding and

extending existing firm resources, values, and processes, enable the development of digital

platform capabilities, which on their side help companies manage digital disruption. These

findings could be generalized to other industries according to the scholars. Digital platform

capabilities development is analogous to any response to digital transformation.

In Karimi and Walter‟s (2015) viewpoint, incumbent firms should assess their organizational

capabilities (both strengths and weaknesses) with the explanation that disruptive innovation

literature provides for the success of ones and failure of other firms.

The scholars argue that disruptive innovation theory has put little attention to technology

as a key resource to fight the pressures of disruptive innovations. Dynamic capabilities are

also understudied in this respect. Therefore the authors call for a more holistic approach, one

where IT, dynamic capabilities, and the environmental turmoil, coexist and interact to shape

“digital ecodynamics”. Literature has investigated how resources and capabilities determine

the success or failure of an incumbent to react to discontinuous change. In their nature

organizational capabilities are automated routines that cater for efficiency and exploitation in

the daily operations of a business. However, rapid change opens capability gaps because it

introduces new ways of functioning that incumbent firms often miss. Dynamic capabilities are

higher order capabilities that essentially manage the ability of a firm to reorganize and adjust

its capabilities in turbulent times. As such, dynamic capabilities are also a source of variation,

which creates more flexibility for the firm to have the right resources and capabilities to

respond to an external change. The scholars hypothesize and prove that first-order dynamic

capabilities facilitate the development of digital platform capabilities, which increase the

performance in responding to digital disruption. Digital platform capabilities act as a

mediator.

2.3. Executive Sponsorship

Kim and Kwon (2012) introduce the notion of sociomaterialism in investigating the

construct of IT capabilities. The Korean scholars argue that both actors and materials define

IT capabilities and that agency should be accounted for. Humans and technologies are related

and enact each other. On the one hand, technology is configured to have certain functional

capabilities. That is the material agency. On the other hand, IT is the basis to set goals for the

IT users and IT producers as it both enables and constrains human actors in choosing a

suitable goal to pursue. There, human agency plays a role. IT capability is therefore created in

an iterative process in which IT human actors perceive the opportunities and drawbacks of the

technology they make use of and that triggers a series of changes and adjustments of the

underlying technology but also in the organizational routines.

As a result, Kim and Kwon (2012) propose a more balanced way to evaluate IT

capabilities, including both material and human aspects and allowing for the interaction in a

three dimension modeling. IT capability is examined in terms of infrastructure (IT), personnel

(IT people), and management capabilities (IT routines). Infrastructure is analogical to

Bharadwaj‟s tangible IT resources. The staff related resources from Bharadwaj (2000) are

similar to personnel capabilities. Instead of using intangibles to mean the enablement of other

resources in the organization, Kim and Kwon expand the dimension to include not only the

IT-business relationship but also the management of IT, the deployment of its resources and

the culture of IT use under an organizational aspect that they call management capabilities.

Routines as known in management literature are both a source of stability and change. The

different human and technological agencies underpinning them create continuous variations,

and following selection and retention of new routines which facilitate organizational change.

IT, humans, and routines, Kim and Kwon (2012) argue, are interwoven, not separable,

and the individual contributions to IT capability cannot be measured. Being distinct but

interdependent, they create a complementary and synergistic effect that distinguishes

companies from each other and explains the heterogeneity in firm performance. The joint

effect of all there aspects is larger than the summation of the three of them individually. We

could then make an analogy and argue that the human side of leadership will moderate the

positive relationship of the IT-enabled dynamic capabilities also in the firm digital

performance. The presence of both IT capabilities and Executive Sponsorship will accelerate

the process of digitally maturing. They have a positive interaction effect. Executive

Sponsorship is therefore a moderator of IT capability.

Hypothesis 2: Executive sponsorship positively moderates the positive relationship

between IT-enabled dynamic capabilities and digital maturity.

A breakdown of Kim and Kwon‟s (2012) three dimensions of IT capabilities follows. IT

infrastructure capability includes all kinds of applications, hardware, data, and networks that

allow the IT personnel to quickly develop and set up necessary systems. A key characteristic

for IT infrastructure is to be flexible, which enables the IT staff to be agile in its practices.

Kim and Kwon state that flexibility of the IT infrastructure is especially crucial nowadays,

when business models and industry paradigms shift as quickly as never before. Firms that

have a high level of connectivity, compatibility, and modularity of their IT infrastructure are

more adept to deploy new systems. IT personnel capabilities refer to technical know-how

(networking, programming languages, and operating systems), technological management

knowledge (IT resource management and use), business knowledge (sound understanding of

the business units to link IT with the units‟ needs) and relational knowledge (interpersonal

communication skills). Finally, IT management capabilities represent the routines through

which the organization can manage and match IT resources with business needs and concerns.

These include planning, decision making, coordinating, and controlling.

Matt, Hess, and Benlian (2015) add on the managerial importance in digital

transformation considering the uncomfortable degree of change that needs to be

accommodated. The authors discuss the aspects of digital transformation strategies. They

argue that to account for the firm-wide changes accompanying products, processes, and

organizational structure, digital strategy should be closely aligned with IT strategy but also

operational and functional strategies. They should all be continuously realigned to fit with

each other. This constant process of change involves hard commitment and involvement from

stakeholders across the organization. Otherwise, companies are running the risk to fall into

operational problems and not reap the whole benefits of the digital investments they have

made. Even though there is disagreement whether it should be the responsibility of the CIO,

CEO, or perhaps the more recent role of CDO, top management should lead the organization

through the digital transformation process. Management should have experience in such

transformational projects, but importantly he should have leadership skills. Major

transformations turning around the whole organization are likely to face resistance from

employees. It is, thus, essential that the employees feel the support of the responsible

executive.

Berghaus and Baker (2016) yet again stress the importance of leadership in getting the

staff on board through the transformation process. Often, a merit for the enthusiasm of the

employees has the management figure and his leadership style. One of the key resources in

digital transformation as also pointed out by Karimi and Walter is the senior management

support. It is the role of management to emphasize the strategic importance of innovative

projects and be closely involved in them. Hassna, Wei, and Lowry (2014) argue that

transformational leadership, which is a style of leadership that leads the organizations to

achieve major transformations rather than to manage everyday processes, is a catalyst of

digital transformation. Transformational leadership is entrenched with culture and structural

aspects of the firm and it creates a culture of empowerment and innovation, which enhance

the effects of IT capabilities.

Hypothesis 2a: The leadership qualities of TMT positively moderate the positive

relationship between IT-enabled dynamic capabilities and digital maturity.

Companies, whose employees feel more supported during the process of digital

transformation by senior management, are more Digitally Mature. In the period of major

change and associated instability, employees feel the need to be encouraged through the

reward system and to be given reassurance, vision, and emotional support from their

superiors.

Kaplan (2008) observes that demographic characteristics of top management, which were

previously found linked with the ability of a firm to accommodate rapid change, modify the

effect of organizational capabilities to shape the strategic response towards disruption.

Characteristics such as tenure and experience can capture the management‟s risk appetite or

affinity for technology and thus can be used as proxies for managerial cognition. They can

precipitate change when combined with adaptation capabilities. Even more, they can

substitute for these organization capabilities if the last are missing. Therefore, Kaplan uses as

controls the functional background of a CEO (technical or other), and his years of experience

to account for tolerance for change to show that the attention of senior management towards

new technology infuses change. Managerial capabilities make the difference and lead the

company to a successful transformation that cannot be accomplished only with organizational

capabilities gained through firm experience. These insights lead to the next two hypotheses.

Hypothesis 3: Executive sponsorship has a positive effect on digital maturity.

The support of TMT and their leadership qualities are a strong propeller of change. As

such, they are enough to lead the organization on its digital path even if organizational

capabilities are missing.

Hypothesis 2b: The technical experience of TMT members positively moderates the

positive relationship between IT-enabled dynamic capabilities and digital maturity.

These TMT members can better understand the trends and benefits of digital initiatives.

They have affinity for technology and ability to manage digital initiatives based on their

gained experience.

Sobol and Klein (2009) investigate whether CIO characteristics influence the return on IT

investments. The role of the CIO has first emerged in the 1970s and since then it has evolved

to include not only the technical but also the strategic aspects of technology initiatives in their

company. In recent years, another role has been added to cater for the raising firm digital

needs – that of CDO. The two roles are interconnected and there is no consensus for the exact

responsibilities of the one and the other. Sobol et al. include CIO characteristics, likely to

influence the CIO strategic decisions and overall performance- his education and technical

knowledge. They prove a positive relation between a CIO technical expertise and the financial

performance of the firm. Technical CIOs are also found to invest more in IT infrastructure,

which on its turn lead to higher returns. At the same time, CIOs who have a more general

management experience adopted a strategic technical orientation, delivering higher results

compared to the efficiency utilitarian orientation of technical CIOs. Ideally, Sobol et al.

suggest a CIO would have both the technical expertise and the business education to deliver

the most optimal results. They would be able to bridge and align the IT and organization

strategy.

Hypothesis 2c: The business of TMT members positively moderates the positive

relationship between IT-enabled dynamic capabilities and digital maturity.

As a proxy for business awareness is used MBA business education qualification. These

TMT members who have a MBA are more commercially aware with interdisciplinary

interests and leadership qualities. They are able to take strategic long-term decisions and use

technology as an enhancer to these strategic goals rather than as a means to an end.

The above focus on human agency provides the background to argue that TMT

characteristics are important determinants of digital transformation success. TMT

characteristics such as MBA degree and Technical background, as well as the support that

employees feel from their management, will be included as moderators to capture

predisposing to engage in digital initiatives, understanding the value of new technology and

its business value, and interpersonal qualities. We hypothesize that the positive effect of IT-

enabled dynamic capabilities on digital maturity will be moderated by them. Below the

conceptual model to be tested can be found.

Figure 1. Conceptual model

3. Data and methods

3.1. Data collection

The most substantial load of work proved to be the data collection. The target population

is professionals in middle to top management roles, ideally ones with actual title Digital

Transformation Manager. In some cases, employees with functions, such as Digital

Marketing, IT or Strategy managers were questioned. The end sample includes the opinions of

a couple of Chief Digital Officers as well. The population of interest is chosen on the basis

that its members are tech savvy, familiar with the topic of digital transformation and are very

likely currently leading digital transformation projects within their organizations.

The data collection method is electronic distribution of the survey. We used LinkedIn

Search engine for members with the “Digital Transformation Manager” title to generate a list

Digital Maturity Digital Maturity

Digital Maturity

Leadership

IT-enabled dynamic

capabilities

Technical experience

MBA degree

H3 +

H2b +

H2c +

H2a+

H1 +

of potential survey participants. Within the population, a nonprobability quota sampling was

performed and followed by at least 500 email invitations to the survey. Professionals were

picked up randomly but to avoid overrepresentation, only one response from a professional

for each company was recorded in the final sample of observations. Using this technique for

response collection has the following benefits. First, the dependent variable, Digital Maturity,

is more specific and not every manager in the organization has the right knowledge and

experience to provide answers. Targeting specific employees ensured high responsiveness to

the survey and quality of responses. Second, a study on digital transformation makes sense to

be conducted via digital tools.

A response rate of 21.07% was achieved in Mikalef and Pateli 2017 study, a number

which according to them is consistent with past research. The final achieved response level to

our survey is 26.7%, a little higher perhaps due to the narrow targeting of invitations to

participate. The responses include firms from various industries: financials (13%), consumer

goods (13%), healthcare (12%), telecommunications and IT (11%), consulting services

(10%), public sector (7%), manufacturing (7%), oil, gas, and utilities (6%), media and

publishing (6%), transportation and logistics (4%) and others, providing a good cross-industry

overview.

3.2. Measures

The questionnaire asked the respondents about their opinion on the IT capabilities and

the characteristics of digital maturity that their company possesses, as well as to provide

information about their direct supervisor background (whether they have a MBA, or technical

education/experience) and ability to make their staff feel supported in pursuing digital

initiatives. Additional information, such as the year in which the company was founded and

the corresponding industry, was also summoned.

IT-enabled dynamic capabilities are measured by using Mikalef and Pateli 2017 validated

scale. It consists of total 20 items, spread across 5 dimensions (IT capability is a second-order

latent variable). An example item is “How effective is your company in using IT for the

following purposes…Scanning the environment and identifying new opportunities?” All items

within it are measured on a 7-point Likert scale which ranges from 1= “very ineffective” to 7=

“very effective”.

Digital maturity is measured by using a Digital Maturity Assessment Tool developed by

the Australian government and adapting it to a questionnaire. The fact that it is constructed by

a governmental institution implies a greater degree of independence than indexes developed

by consultancy firms. The participants have to choose whether they agree with statements

about different aspects of digital maturity in their company in line with the current situation.

An example item is “Does this statement currently fit in your company: Digital services and

channels drive the organizational culture and reporting?”. All items are again measured on a

7-point Likert scale which ranges from 1 = “Strongly disagree” to 7 = “Strongly agree”.

Constructs are reflective, meaning that the latent variable Sensing, e.g. is the predictor and the

observed variables (SENS_1, SENS_2, SENS_3, SENS_4) are the outcomes. Because a

company has Sensing capability, it can “Scan the environment and identify new business

opportunities.” The complete item definitions can be found under Table 1. and 2. in the

appendix.

3.3. Method

This study is of quantitative nature and is built around cross-sectional survey data. The

survey was pretested with two university researches as well as two consultant industry experts

for content validation and overall user experience. A survey is the most useful way to collect

data as experts‟ opinions are used to measure the variables in this research. The constructs

aggregate processes, underpinning or associated with the latent variables the constructs aim to

measure and as argued by Mikalef and Pateli are a reliable way to quantify otherwise blurry

concepts.

Research is conducted on a firm level where one respondent is representative for one

company. In their study, Kim and Kwon use a matching set of a professional from an IT

department and one from a business department to assess correspondently IT capability and

business performance. In this way they mitigate common method bias. However, for the ease

of the time and resources limitations of this thesis, only one professional is approached to

answer questions for both constructs (IT-enabled dynamic capabilities and Digital Maturity).

To control, ex ante for another potential source of common method bias, the respondents were

assured in the beginning of the survey that their responses will remain anonymous on the

individual level and will only be used to draw conclusions on an aggregate level (Mikalef and

Pateli, 2017). Because the surveys were sent on a continuous basis rather than at once, there is

little probability of response bias between early and late participants.

Finally, the relationships between the variables are first explored with exploratory factor

analysis and then confirmed using partial-squares structural equation modeling. With the

explored factors, the proposed hypotheses are tested using SEM-PLS and SmartPLS software.

Structural equation modeling (SEM) is a technique highly adopted in social sciences and

information systems because it allows modeling of latent variables, correction of

measurement errors, and parameter estimations of entire models to happen simultaneously

(Dijkstra, Henseler, 2015). Partial least squares (PLS) on its turn is the most fully developed

variance-based SEM technique. SEM-PLS has its advantages when working with small

sample sizes, complex models, ordinal and binary scaled questions as well as single item

constructs. Multiple theories can be integrated and tested at once. The consistent PLS

algorithm is used. It applies a reliability coefficient to correct for reflective items correlations

(attenuation) and thus adjusts the path coefficients making them consistent (Dijkstra,

Henseler, 2015). Bootstrapping technique with 1000 subsamples was used to check for

consistency of the estimates, should a larger sample with an approximate distribution be used

instead.

4. Results

4.1 Data cleaning, descriptive statistics, EFA

To begin with, the data was cleaned. No counter-indicative items were part of the survey

so there was no need for recoding. Missing values were filled in with the mean values of the

corresponding variable. Tests for normality were run based on skewness and kurtosis and for

most items the hypothesis that the items are normally distributed cannot be rejected. It is safe

to assume they do not deviate from normality significantly to cause problems in the further

analysis.

The factorability criterion for running EFA requires that there are strong correlations

between the scale items (above 0.50) without causing multicollinearity issues. The

correlations meet this criterion (Table 3. and 4.) and following expectations, items measuring

the same construct have the highest correlations between each other. For Sensing, this

relationship is the most pronounced. SNS_1 has the highest correlations with SNS_2 (0.64),

SNS_3 (0.69), and SNS_4 (0.62). Learning and Integrating items are not only highly

correlated within their own groups, but also with each other. The same counts for

Coordinating and Reconfiguring. Finally, with regards to the sample size, the final

observations after cleaning the data are 83. To keep the bare minimum of 3 to 1 cases to

items, exploratory factor analysis was first run on the 17 DigitalMaturity indicative items to

reduce them.

From the summary statistics (Table 5.and 6.) it could be seen that the means of the

indicative scale items of both the dependent and independent variables are above 4 (they are

slightly skewed to the right). The lowest scoring indicative item is Dmat_7 Strategy Initiative

Development, which has a mean of 3.53. Firms on average underperform with regards to “All

staff are digitally savvy and aware; having a defined „digital team‟ becomes obsolete.” The

majority of firms are not yet at the level of maturity where employees have enough

understanding to come up with their own digital initiatives, from bottom-up. Instead, they

need the guidance of specially designed teams to lead the digital endeavors. At the same time,

firms are the most successful when it comes to customer understanding. On average,

respondents agree that their firm “encourages feedback from customers and staff, makes it

public, and apply the lessons learned” (Dmat_5 Customer Understanding Mean: 4.92, S.D.

1.56). Both the most accessible and the most difficult to achieve facets are in line with the

findings of Berghaus and Back. Further, firms tend to find it the most difficult to foresee

drastic changes in their business environment and respond to them by developing new

processes, products, and strengths, as can be deducted from the means

of RCF_1 (3.95), RCF_4 (3.95), and SNS_4 (3.98), which is not surprising. Learning seems to

be not so challenging, especially when it comes to the more passive forms of learning, such as

assimilating and accumulating knowledge (LRN_3 and LRN_ 4 with means of 4.37).

The survey tested various scale items and delivered rich data. Since the dependent

variable DigitalMaturity is constructed from an index by the Australian government and

measures 17 different aspects, it is best to conduct initially EFA (explorative factor analysis)

in Stata to investigate the shared variance of the 17 items that is attributable to the latent

variable DigitalMaturity. Since the primary aim is data reduction, principal component

method is used instead of maximum likelihood. Maximum likelihood might also be biased in

small sample sizes (83obs.), so that makes the choice for principal component method even

more obvious. The loadings were rotated with the Promax Horst option to return standardized

measures. All loadings below the threshold of 0.30 were excluded. The Kaiser-Meyer-Olkin

(KMO) measure delivered a value of 0.84, verifying a high proportion of variance among the

items that may be due to common variance and therefore the sampling adequacy to run factor

analysis. The correlations between the items are sufficient enough to run factor analysis also

according to the Bartlett‟s test of sphericity (χ2(136)=777.7, p=0.000 ). To simplify the model

due to small sample size, through item deletion the items were brought down until the

majority of them loaded on only on factor. Items that were cross-loading and at the same time

had high uniqueness were removed one by one. The final pattern matrix for DigitalMaturity

can be seen under Table7.

The DigitalMaturity items were then factored together with the items for IT-enabled

dynamic capabilities. This resulted in 4 distinct factors, one for DigitalMaturity and IT items

were loaded on the rest 3 factors. Sensing items load high together, making up one of the

factors (factor 1). Factor 2 consists of items from Learning and Integrating, whereas factor 3

contains Reconfiguring and Coordinating. These factor groupings were anticipated

considering the high correlations discussed in the descriptive statistics. For further analysis,

equal factor weights within the constructs are assumed. The factor groupings even if different

from Mikalef and Pateli‟s (2017) findings, are in line with Teece‟s (2007) distinction of three

types of dynamic capabilities.

Factor 1 items match the Sensing capabilities described by Teece. These are the abilities

of the firm to scan its environment and identify through better customer knowledge new

business opportunities. However, the ability to identify opportunities is not enough to achieve

them. The items following under Factor 2 are those associated with responding to market

opportunities by learning from experience, integrating existing resources with new ideas, and

careful planning to formulate a strategy. Factor 3 corresponds to what Teece defines as

Reconfiguring capabilities, which are the capabilities to continuously match strategy with

organizational design to achieve the opportunities identified through Sensing and Seizing

capabilities. The pattern matrix can be seen under Table 8.

4.2. SEM-PLS Measurement model

The latent variables are tested for construct reliability, convergent and discriminant

validity. The high Cronbach‟s alphas and Composite reliability scores (above 0.86> 0.70)

confirm the consistency of the indicators with each other within a given construct. The path

weights of all items included measuring ITdyncap, as well as those for DigitalMaturity are

high above 0.660, indicating high correlations within the constructs, and that they are all

highly relevant in determining the constructs. Construct reliability is therefore met. Average

Variance Extracted (AVE) is above 0.5 for all variables (outer loadings are above 0.708).

Thus, convergent validity is also confirmed. Fornell-Larcker criterion that each construct‟s

AVE square root is greater than its highest correlation with any other construct is also met.

HTMT values are all less than 1, meaning that the factors indeed are different from each

other. Discriminant validity is also established. VIFs values were also checked for

multicollinearity issues and they were all below 5. The first-order t-statistics of Sensing,

Seizing, and Reconfiguring capabilities are all high (the lowest is 8.43), as well as the t-

statistics of the items composing DigitalMaturity (all above 5.46), indicating the soundness of

the measurement model.

4.3. SEM-PLS Structural model

As goodness-of-fit of the model, SRMR is checked. Saturated and estimated models have

very close SRMR (root mean square residual) score, meaning that they must be almost

identical. SRMR is border line with a value of 0.078 but still acceptable according to Hu and

Bentler (1999). The model fit is evaluated using RMSEA, Chi-squared/degrees of freedom,

and CFI measures. RMSEA = 0.096, Chi-squared/degrees of freedom= 1.76, whereas CFI =

0.964 confirm the soundness of the model fit.

First, we examine the relationship between ITdyncap and DigitalMaturity. The t-statistic

for the effect of ITdyncap on DigitalMaturity produced has value of 10.63, considerably

higher than the critical value of 1.96. It can be concluded that the independent variable does

have a strong significant positive effect (β=0.69, p-value=0.000. The is 0.477, meaning

that the variance in DigitalMaturity explained by the independent variable is 47.7%, which is

reasonable. Hypothesis 1 is confirmed.

To the initial model, Leadership is added to test whether the fact that TMT is able to

encourage the embracement of digital initiatives and make the employees feel supported has a

direct effect on the level of DigitalMaturity. With a t-statistic of 2.22 the null hypothesis is

rejected. There is evidence for significant moderate positive effect (β=0.23, p-value=0.027).

Hypothesis 3 is supported. The effect of ITdyncap on DigitalMaturity somewhat decreases

(β=0.59) but remains strong. The explained variance of the model increases ( =52.7%).

There is no direct effect of TMT having a business post-qualification on the level of

DigitalMaturity that the firm has achieved as the t-statistic is 0.83. There is even less reason

to believe that technical background has an effect on DigitalMaturity with a t-statistic of

merely 0.48 (p-value 0.74).

To test the hypothesis that the positive effect of ITdyncap on DigitalMaturity is

strengthened in the presence of executive sponsorship and introduce the human side of digital

transformation, a moderating effect is added in three different models between Leadership,

MBAMan, and TechMan subsequently and ITdyncap. However, the t-statistics of 0.56, 1.30,

and 0.48 and very high p-value (0.570; 0,190; 0.630) correspondingly disconfirm the presence

of such moderating effect. Although Leadership has significant effect on its own on

DigitalMaturity, it cannot be argued that it strengthens the effect of ITdyncap. MBAMan and

TechMan have neither direct nor moderating effects. Hypotheses 2a, 2b, and 2c are thus not

supported.

As an extra insight, the observations were divided into firm who are Established and

those who are Young (less than 30 years since their foundation). Multi-group analysis (MGA)

was run to check if the differences in DigitalMaturity between the two subgroups are

significant. Very high p-values came as a result. With this definition of Young to be a

company of less than 30 years and current sample, there is no significant difference and we

cannot claim that older companies are less digitally mature than younger ones. If the sample

consisted of more start-ups, the results would like be different.

Figure 2. Causal relationships (path coefficients) of structural model with moderating

effect

IT-enabled dynamic

capabilities Digital Maturity

Leadership

Technical experience

MBA degree

H3 0.229* H2a

0.105

H2b 0.086

H2c 0.227

H1 0.585**

N=83 All values reflect standardized beta coefficients

**p<0.01, *p<0.05, p<0.10

5. Discussion

5.1. Managerial implications

This thesis proves the crucial role that IT-enabled dynamic capabilities have for the

success of digital initiatives. Although no moderating effects of TMT characteristics on

dynamic capabilities were found significant, the role of TMT as a leader and supporter of

digital transformation is on its own contributing to a more evolved stage of digital

transformation for companies.

It would be useful for companies to compare themselves to those who have reached a

higher level of digital maturity and judge for themselves whether it will be beneficial for their

own business to transform further. Although all industries are impacted by digitization,

different industries would be impacted by different degrees. If managers decide that their

company is falling behind the desired level of digital maturity, they can use the benchmarking

to see in which areas (Sensing, Seizing, or Reconfiguring) they are lacking and which IT-

enabled organizational capabilities they need to upgrade first, following Baharadwaj‟s (2000)

argument. There is a clear positive effect of IT-enabled dynamic capabilities on the level of

digital maturity. Companies should first leverage their existing IT resources to build on their

cross-department capabilities. Digital transformation should be a logical step for a company

that is successful in analyzing its external environment and adapting its process, products, and

activities to stay relevant. Digital transformation would be a less successful endeavor for

companies that follow the trend but lack the built capabilities of reinventing themselves for

efficiency, knowledge share, and innovativeness. Further, companies should not

underestimate the human agency in transformational projects. Leadership is a quality that

every higher manager in a company that undergoes digital transformation should possess. The

role of the CIO/ CDO is not myth but directly influences positively digital maturity.

Experience and education seem to be less relevant in this process of transformation and

change. Vision and interpersonal communication deliver more value than qualifications.

5.2. Limitations and suggestions for further research

There are a couple of limitations associated with this study. First, the sample is very

likely to exclude those companies that have made no efforts to digitally transform and focus

only on those that are somewhere in the process of digital transformation. Second, the data is

gathered by one single representative of a company. Thus, his/her response may not be

representative to the firm as a whole as the individual may be subject to bias. Both

DigitalMaturity as well as ITdyncap are assessed by the same employee, which creates bias as

to whether factual data do not correspond to the perceptions of the questioned individual.

Finally, as with every survey, it may suffer from common-method bias as it depends on self-

reported opinions.

The relationship between IT dynamic capabilities and Digital Maturity was established

which is a major contribution of this thesis. Further research can be done on the specific

mechanism through which IT-enabled dynamic capabilities enhance the process of digital

transformation. There is still a huge gap that should be filled by academic literature on the

topic and at this point academic research is behind the consultancy research and industry

practices.

To get a more detailed view of the IT-enabled dynamic capabilities that drive digital

maturity in its different stages, future research can incorporate cluster analysis of stages of

digital maturity, rather than creating one class of digital maturity to measure digital

transformation as a whole.

6. Conclusion

Digital transformation is an area where academic literature is underdeveloped, yet

practice demands a more thorough definition of the concept, a better understanding of the

requirements for a smoother transition process but also strategic guidance in long-term

perspective.

This study aimed to empirically test the validity of established enablers of organizational

change, such as dynamic capabilities and executive sponsorship in the context of the greatest

rapid period of change since the Industrial Revolution. The major contribution of this thesis is

making the first steps towards bridging the gap in literature regarding antecedents of a

successful digital transformation. This study contributes to the work of Hassna, Wei, and

Lowry (2014) by testing empirically with the means of an appropriately developed survey the

effects of IT capability and transformational leadership on responding to digital disruption.

The results are generalizable since the study was conducted across industries and among

companies with different sizes and history.

As such, this research expands on dynamic capabilities literature in the context of digital

transformation and brings new angles to the importance of developing skills, such as sensing,

learning, integrating, coordinating, and reconfiguring, as ways to cope with any external

challenge. By breaking down capabilities into concrete skills, we provide companies with

more tangible, empirically proven strategic actions to take in order to reach a more mature

level of digital transformation. To account for the ongoing process and non-linear path to

transformation, we make use of the more accurate notion of digital maturity. Direct positive

associations were found between the ability of a company to leverage its IT base to support

strategic processes and the degree to which it is able to become digitally transformed. This

thesis also brings the human agency into explaining successful digital transformation.

Although we did not find any evidence that TMT characteristics such as MBA education and

technical experience aid the technologically- enabled rapid change, the TMT support felt by

employees encourages change on an interpersonal level. Therefore, the role of the CIO/CDO

as a leader is not a myth advocated by consultancy reports.

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Appendix 1

Measures

Digital Maturity by Digital Maturity Assessment Tool, Government of South Australia (2016)

Do you agree that the following statement fits the current situation in your company?

Aspect/ variable

item

Name Cronbachs’s

alpha

Statement

Strategy across

departments

Dmat1 0.92 Digital services and channels drive the

organizational structure and reporting.

Engagement with

employees

Dmat2 0.92 New services and products are born

digital & non-digital services and

products are reengineered, joined up and

re-born as digital.

Digital ownership Dmat3 0.92 Executive understands and fully

embraces digital channels and leads by

example.

Integration of digital

strategy

Dmat4 0.92 Digital strategy is embedded in, and

indistinguishable from, the organizational

vision and strategy.

Consumer

understanding

Dmat5 0.92 Feedback from customers and staff is

encouraged, made public, and lessons

learned are applied.

Change Appetite Dmat6 0.92 Digital culture is embedded into overall

corporate culture and constantly

monitored, improved and refined.

Strategy initiative

development

Dmat7 0.92 All staff are digitally savvy and aware;

having a defined „digital team‟ becomes

obsolete.

Engagement of staff

with digital media

Dmat8 0.92 Staff proactively generate and explore

ways to improve digital service delivery

and internal productivity via digital

solutions.

Digital policies Dmat9 0.92 All digital policies, procedures and digital

activities are in place and are core to

everyday business activity & constantly

reviewed and optimized.

Staff digital training Dmat10 0.92 Staff training supports the current digital

strategy and anticipates future skills and

knowledge requirements.

Resource allocation

for digital initiatives

Dmat11 0.92 Resources and budgets are appropriate

for supporting the digital channels,

activities and service delivery.

Staff digital

capabilities

Dmat12 0.92 Staff have the resources to anticipate and

respond to new technologies and digital

innovation.

Process innovation Dmat13 0.92 Imagining future needs and technologies

and exploring and experimenting with

methods and solutions is common

practice.

Digital service Dmat14 0.92 The whole organization seeks ways to use

digital channels and technologies to

redefine customer service and to generate

new benefits.

Integration of digital

channels with

processes

Dmat15 0.92 Business processes and IT systems are

driven by the digital channels and

customers‟ needs.

Strategy alignment Dmat16 0.92 IT strategy and performance are entirely

aligned to the organizational vision and

strategy.

IT Strategy Dmat17 0.92 IT constantly optimizes the benefits of

digital service delivery & on-going

feedback is encouraged.

Table 1. DigitalMaturity survey items

IT-enabled dynamic capability by Mikalef and Pateli (2017)

How effective is your company at…?

Dimension Name Cronbach’s

alpha(Mikalef

and Pateli)

Cronbach’s

alpha current

sample

Statement

Sensing 0,883 0.897

SNS_1 Scanning the environment

and identifying new business

opportunities

SNS_2 Reviewing our product

development efforts to ensure

they are in line with what the

customers want

SNS_3 Implementing ideas for new

products and improving

existing products or services

SNS_4 Anticipating discontinuities

arising in our business

domain by developing greater

reactive and proactive

strength

Coordinating 0,872 0.881

CRD_1 Providing more effective

coordination among different

functional activities

CRD_2 Providing more effective

coordination with customers,

business partners and

distributors

CRD_3 Ensuring that the output of

work is synchronized with

the work of other functional

units or business partners

CRD_4 Reducing redundant tasks, or

overlapping activities

performed by different

operational units

Learning 0,939 0.890

LRN_1 Identify, evaluate, and import

new information and

knowledge

LRN_2 Transform existing

information into new

knowledge

LRN_3 Assimilate new information

and knowledge

LRN_4 Use accumulated information

and knowledge to assist

decision making

Integrating 0,891 0.906

INT_1 Easily accessing data and

other valuable resources in

real time from business

partners

INT_2 Aggregating relevant

information from business

partners, suppliers and

customers (operating

information, business

customer performance)

INT_3 Collaborating in demand

forecasting and planning

between our firm and our

business partners

INT_4 Streamlining business

processes with suppliers,

distributors, and customers

Reconfiguring 0,904 0.916

RCF_1 Adjusting for and responding

to unexpected changes easily

RCF_2 Easily adding an eligible new

partner that you want to do

business with or removing

ones that you have terminated

your partnership

RCF_3 Adjusting our business

processes in response to

shifts in our business

priorities

RCF_4 Reconfiguring our business

processes in order to come up

with new productive assets

Table 2. IT-enabled dynamic capabilities survey items

Appendix 2

Descriptive statsistics and EFA

Table 3. Correlation matrix IT-enabled dynamic capabilities indicator variables

Table 4. Correlation matrix Digital Maturity indicator variables

Table 5. Descriptive statistics IT-enabled dynamic capabilities indicator variables

Table 6. Descriptive statistics Digital Maturity indicator variables

Table 7. Pattern matrix Digital Maturity

Table 8. Pattern matrix Digital Maturity, Sensing, Coordinating, Learning, Integrating,

Reconfiguring

Cronbach's

Alpha

rho_A Composite

Reliability

AVE

Reconfiguring 0,918 0,921 0,919 0,654

Digital Maturity 0,863 0,870 0,862 0,514

IT-enabled dynamic capability 0,946 0,948 0,947 0,542

Seizing 0,901 0,901 0,901 0,645

Sensing 0,897 0,900 0,897 0,687

Table 9. Construct reliability and validity