Upload
anaam-shafique
View
44
Download
0
Embed Size (px)
Citation preview
ACKNOWLEDGEMENT
We would like to express our special thanks of gratitude to our teacher (Mr. Abdullah
Sahi) who gave us the golden opportunity to do this wonderful project on the topic (Standardized
Project management Factors Critical to Project Success), which also helped us in doing a lot of
Research and we came to know about so many new things we are really thankful to them.
Secondly we would also like to thank our parents and friends who helped us a lot in finalizing this
project within the limited time frame.
1
Abstracts
The success of project management initiatives depends on knowledge sharing and Leadership Skills
of the project managers and project team. This research reviews qualitative and quantitative studies of
individual-level knowledge sharing and group knowledge sharing activities. Based on the literature review
we developed a framework for project success by knowledge sharing research and leadership activities
especially interpersonal skills. The paper concludes with a discussion of emerging issues, new research
directions, and practical implications of knowledge sharing tecniques.
2
Chapter No. 1
Introduction
Background:
This study is based on the previous research named as ‘Standardized project management may
increase development projects successes by Dragan Milosevic and Peerasit Patanakul in 2005. The main
focus of this study is to analyze the major success factors and their role in projects completion. Because the
success of any project is mainly related to the project delivery and its output. For this purpose Pakistan’s
Textile industry was under discussion in this research work because Textile is the major exports of Pakistan
and it’s the back bone of Pakistan’s emerging economy. There are many project underway in this sector
like power generation, Process & Resource optimization, Sustainable Resources, and many others.
Project management is about managing people. The project manager must manage the project team
to ensure that they do their job correctly, effectively and efficiently, but it is project team members who
achieve almost all of the project goals and objectives. Projects tend to start with nothing more than a project
manager doing some planning and requirement gathering. The project then grows through the planning
phase and reaches a crescendo during execution when the full project team are on board and then fades
away with a project manager doing the closing administration. As such, it is fairly obvious that the middle
part of the project is likely to have more staff and more expenditure than the project start or finish.
With globalization come ever bigger challenges and the need for increased speed-to-market with
products and services. Projects become larger, more complex and increasingly difficult to manage. Teams
are more diverse and spread across the world. The economic crisis pushes work offshore to low cost
countries, which itself presents several issues. The world is changing and project management will need to
change with it. Project Management Institute (PMI) came into existence in 1969, PMI held its first
symposium in Atlanta, Georgia and had an attendance of 83 people. Since then, the PMI has become best
known as the publisher of, 'A Guide to the Project Management Body of Knowledge (PMBOK)' considered
one of the most essential tools in the project management profession today.
Selection of Topic:
This topic was selected because world has become a global village in 21st century and more and
more research has been taken place in every field especially in business and information technology. Project
based organizations are important now a days and they are working on different projects and success of
these projects is very important for these organizations to move forward and expand. Project Management
is getting more and more importance by every passing day and project managers become the highly paid
personnel’s among the employees. So due to this vital importance the topic selection came into existence.
Research Questions:
In this study there is a relationship regarding the success factors and project delivery. Project
success is normally measured by the output of the project and completion of objectives associated with that
3
project. Project success is the tool to measure the performance of project teams and revenue. This study
proposed the standardized factors which are critical to any project success. And to support the topic two
hypothesis were developed for this purpose; one is A high degree of Knowledge Sharing tends to increase
the success of projects and second is Project Managers having standardized sets of leadership skills tend to
have increased the project success.
User of Study:
This study is very useful for the future researchers for more work and also at the same time useful
for industrialists to adopt this model for making success path smoother. Industrialists may use this research
to solve different problems during planning and execution phase of projects. Planning is the heart of any
project and more working groups involved in this phase as compared to any other phase. Feasibility reports
are being made during planning and objective are being set during the planning phase.
4
Chapter No. 2
Literature Review:
Shen Wang and Raymond A. Noe (2010) they used qualitative and quantitative approach for
individual level of knowledge sharing in organizations. They developed a frame work of understanding
knowledge sharing research, framework identifies five areas of knowledge sharing; organization context,
interpersonal and team characteristics, cultural characteristics, individual characteristics, and motivational
factors. They found these five areas have a major role in making any project successful within the defined
time limits. The more better the information flow and knowledge about the company will increase chances
of project success.
Samer Alhawari, Louay Karadsheh, Amine Nehari Talet and Ebrahim Mansour (2012) their
objective of this research is to inquire the field of Risk Management (RM) in relation with Knowledge
Management (KM). They attempted to create a conceptual framework, Knowledge-Based Risk
Management (KBRM) that utilize KM Process to improve its effectiveness and increase the probability of
success in Information Technology (IT) Projects. They reviewed and interpreted the related and relevant
literature and threw a light on Integration with RM in IT projects. They succeeded in proposing a framework
which fertilized current research by offering specification and justification of a set of interrelationships
between important factors.
Mian Ajmal, petri Helo and Tuano Kakale (2010) they purposed a new model of critical success
factors for KM initiatives in the context of project-based business. They purposed a conceptual model of
six factors of potential importance to the success of KM initiatives. Familiarity with KM, coordination
among employees and departments, incentive for knowledge efforts, authority to perform knowledge
system for handling knowledge; and cultural support are the six factors involved in developing a conceptual
model. The findings of the empirical study have revealed that the absence of incentives and the lack of an
appropriate system are the most significant barriers for successful KM initiatives in projects.
Sofia Pemsel and Anna Wiewiora (2012) the aim of their research was to examine PMO functions
from a knowledge sharing perspective and to determine whether or not these functions reflect the
knowledge sharing behaviors of PMs. They investigated through a cross case analysis of seven
organizations. They found that PMO needs to possess multiple knowledge sharing behaviors. Moreover,
the PMOs need capabilities in educating PMs to strategically use similar boundary objects and endeavors
in their operations.
J. Scott Holste and Dail Fields (2010) their study aims to explore the impact of affect-based and
knowledge-based trust of co-workers on the willingness of professionals to share and use tacit knowledge.
The method used in finding the relationship was based on data provided by a sample of 202 professionals
and managers in world headquarters of an international organization. They found affect-based trust has a
significantly greater effect on the willingness to share tacit knowledge, while cognition-based trust plays a
greater role in willingness to use tacit knowledge.
Seul-Ki Lee and Jung-Ho Yu (2012) the main objective of their study is to develop and validate
the PMIS success model based on the DeLone and McLean (2003) IS success model. They used some
questionnaire instruments and in that regard 253 questionnaires were regained. They used Structural
5
Equation Modeling for hypothesis testing. They found that impact of efficient construction management
and the impact of effective construction management are considered to be a closer measure for PMIS
success than the other. They also found that user satisfaction has the strongest total effect on efficient and
effective construction management. They also concluded that intention of PMIS use has the strongest total
effect on effective construction management.
Todd Dewett and Gareth R. Jones (2001) the objective of this paper is to study and provide a broad
overview of how Information Technology (IT) affect organizational characteristics and productivity. They
reviewed the information efficiencies and information synergies and identified the five main organizational
outcomes by using the IT application. They discussed the role of IT played in structure, size, learning,
culture, and interorganizational relationships and innovation. They concluded that role of IT is very
important in defining organizational innovation by increasing coordination and collaboration and creating
opportunities for information synergies.
Louis Raymond and Francois Bergeron (2007) the purpose of this study is to empirically assess the
lineament of the Project Management Information System (PMIS) presently used in organizations and to
evaluate their impact on project managers and project performance. They developed a PMIS Success model
having five concepts; quality of PMIS, quality of PMIS information output, use of PMIS, individual impact
of PMIS and impact of PMIS on project success. They found that PMIS plays a key role in effective and
efficient project planning, scheduling, monitoring and controlling.
Mike Hobday (2000) the main objective of his research was to examine the effectiveness of
producing complex high value products, systems, networks, capital goods, and constructs in a project-based
organization (PBO). They developed a simple model to show how the PBO relates to identified forms of
matrix and functional organization. They analyzed that the PBO is able to cope with emerging properties
in production and respond flexibly to changing client needs. They found that the wide variety of
organizational choices involved in producing CoPS (Complex Product System) and argues that the nature,
composition, and scale of the product in question have an important bearing on appropriate organizational
form.
IRJA HYVÄRI (2006) he used the method of surveying different organization and by doing meta-
analysis he concluded his research. The main objective of his work to examine the relationship between
critical success factors and organizational background variables. The project implementation profile is also
analyzed on average and by phases. The found he importance of project communication that is related to
company size. They also concluded that communication was ranked highest in most project phases.
Mian M. Ajmal and Kaj U. Koskinen (2008) they investigated the process of knowledge sharing
from the view of organizational culture. They found that for positive knowledge sharing first of all
organization must prepare itself for this and to adopt the new ways in knowledge sharing. They further
concluded that organizations must prepare to create, share and utilize knowledge so that PM’s can work in
a vibrant culture to achieve maximum from their projects for the enterprise.
Vittal S. Anantatmula (2010) he found that the manager’s leadership role is of great importance in
motivating people and creating competitive working environment to meet the goals set by the management
in today’s global economy. He used the methods of conducting surveys and structured interviews to make
a PM’s leadership and management model. He further analyzed that technology tools assist knowledge
sharing, team development, efficiency, and effectiveness, motivating factors which finally lead towards
knowledge sharing, team development, and innovation and are dependent on the project leadership role in
establishing trust and open communications.
6
Linda Geoghegan and Victor Dulewicz (2008) they established a hypothesis for their finding that
there is a relationship between PM’s leadership skills and probability of project success. Two types of
questionnaires Leadership Dimensions Questionnaire (LDQ) and Project Success Questionnaire (PSQ)
were used by them to support their hypothesis. They found that Management Leadership Dimensions
contribute a lot in making any project successful. They further concluded that the company’s project
managers have demonstrated a level of emotional competencies that should enable them to perform better
in leadership.
J. RODNEY TURNER and RALF MÜLLER (2005) they found that personality and leadership
style, of the project manager is a success factor for projects. The inner confidence and self-belief from
personal knowledge and experience are likely to play an important role in a manager’s ability to deliver a
project successfully.
Li-Ren Yang, Chung-Fah Huang and Kun-Shan Wu (2011) they investigated the relationships
among the project manager's leadership style, teamwork, and project success. Questionnaire-based survey
technique adopted by them to support their hypothesis. The major factors in determining the project success
were schedule performance, cost performance, quality performance, and stakeholder satisfaction. They
found that project type has a moderating effect on the relationship between teamwork dimensions and
overall project success.
Mohan Thite (2000) after empirical study he found that a combination of transformational and
technical leadership behaviors augment the effectiveness of transactional leadership leading to high project
success. Transformational leadership is characterized by charisma and vision. He found that active
monitoring of exceptions monitor the performance of subordinates for errors, irregularities and deviations
from standards in order to enforce rules.
Aaron J. Shenhar (2004) he developed a new approach Strategic Project Leadership (SPL) in
project management focusing on creating competitive edge over competitors. Through this leadership style
he presented a presents a mindset, a framework, and a practical, step-by-step approach on how to connect
project management to business results and how to turn projects into powerful competitive weapons. He
found that to adopt this leadership style organizations require commitment from the top, and it involves
modified processes, better procedures, new training, and organizational monitoring.
Martina Huemann, Anne Keegan and J. Rodney Turner (2007) they found that due to specific
environment of the project-oriented organizations like temporary nature of work process and dynamic
nature of work environment their exist specific challenges for both employees and organization for HRM.
Stuart Maguire and Tom Redman (2006) they examined the internal integral weaknesses the most
organizations have in implementing and to develop information system structures in completing any
project. They gathered the data from various case studies on public sector organizations and found that IS
failure is often linked with lack of attention from management on culture change, organizational
development and user involvement. HR has a key but neglected role in successful implementation of IS.
Adnane Belout and Clothilde Gauvreau (2004) they found that no doubt that there is a link between
project success and the Personnel factor but this factor did not have a significant impact on project success.
The three organizational structures (functional, project based and matrix), the Management Support and
Trouble-shooting variables are significantly correlated with success. HRM in the context of project
management have specific characteristics that make its role, social responsibility and operation different
from the so-called traditional HRM.
7
Julien Pollack (2006) he found that explicit understanding of the theoretical basis of PM and HRM
is necessary, as it provides the opportunity to understand the assumptions.
Dov Dvira, Tzvi Raz and Aaron J. Shenhar (2003) they gathered the data from more than 100
defense research and development projects and found that project success is insensitive to the level of
implementation of management processes and procedures, which are readily supported by modern
computerized tools and project management training. And project success is positively correlated with
development of technical specifications and project management processes and procedures.
8
Chapter No. 3
Methodology
This research is based on the analysis of factors and correlation between those factors in
determining the Project Success. Two independent factors were chosen like; Knowledge Sharing and
Leadership Skills and one dependent factor; Project Success for our study. Project success was measured
Project Delivery.
Research Philosophy: A research philosophy is a belief about the way in which data about a phenomenon should be
gathered, analyzed and used. The term epistemology (what is known to be true) as opposed to doxology
(what is believed to be true) encompasses the various philosophies of research approach. Two types of
research philosophies were defined by the researchers; one is positivist and second is interpretivist. Social
constructivism and Realism are the other two philosophies under positivist category.
Philosophy of social constructivism:
Philosophy of social constructivism was adopted which is an approach to qualitative study. Social
constructivists hold assumptions that individuals seek understanding of the world in which we live and
work. We as a team were the main observer of the whole research and for this purpose we conducted five
type of surveys related to independent factors which were mentioned earlier and tried to standardize those
factors by relating with project success. We collected the data from reliable and related industrialists and
managers from which we derived our results.
Research Approaches:
Research approaches are plans and the procedures for research. That span the steps from broad
assumptions to detailed methods of data collection, analysis, and interpretation. Researchers will have one
or more hypotheses. These are the questions that they want to address which include predictions about
possible relationships between the things they want to investigate (variables). In order to find answers to
these questions, the researchers will also have various instruments and materials (e.g. paper or computer
tests, observation check lists etc.) and a clearly defined plan of action.
Induction Research:
Induction research approach has been adopted to obtain results from our collected data. It
is also called as bottom up approach. Surveys were conducted in order to observe and develop patterns to
support the hypothesis of the research. Two hypothesis has been developed to support the results;
1. A high degree of Knowledge Sharing tends to increase the success of projects
2. Project Managers having standardized sets of leadership skills tend to have increased the
project success
9
Research Classification:
Descriptive research approach used to find the relationship between Knowledge Sharing,
Leadership Skills and Project Success. The term descriptive research refers to the type of research question,
design, and data analysis that will be applied to a given topic. Descriptive statistics tell what is, while
inferential statistics try to determine cause and effect. Descriptive research involves gathering data that
describe events and then organizes, tabulates, depicts, and describes the data collection (Glass & Hopkins,
1984).
Descriptive statistics utilize data collection and analysis techniques that yield reports concerning
the measures of central tendency, variation, and correlation. The combination of its characteristic summary
and correlational statistics, along with its focus on specific types of research questions, methods, and
outcomes is what distinguishes descriptive research from other research types.
Collection of Data:
Data has been collected through observations and questionnaire tools. For this purpose we prepared
two type of questionnaire for each hypothesis. For Leadership Skills we selected 18 different questions
related to Administrative Skills, Interpersonal Skills and Conceptual Skills and against each question we
put five different options on a grading scale.
For Knowledge Sharing we also selected 18 questions related to Knowledge Management and
Sharing System during planning, monitoring and controlling phases of projects. And against each question
we put five different options on grading scale.
We choose the textile industry for our field of research. Textile industry is the backbone on
Pakistan’s economy. Pakistan’s textile industry ranks amongst the top in the world. Cotton based textiles
contribute over 60% to the total exports, accounts for 46% of the total manufacturing and provide
employment to 38% manufacturing labor force. The availability of cheap labor and basic raw cotton as raw
material for textile industry has played the principal role in the growth of the Cotton Textile Industry
in Pakistan. The cotton-processing and textile industries make up almost half of the country’s
manufacturing base, while cotton is Pakistan’s principal industrial crop, supplying critical income to rural
households. Altogether, the cotton-textile sectors account for 11 percent of GDP and 60 percent of export
receipts.
Survey Technique:
We conducted a survey on 25 different textile units based in Lahore Region. Interviewed personals
are directly or indirectly involved in different ongoing projects in their respective units related to product
development, process optimization, new machinery erection, research and development sector and cost
optimization. Following is the list of surveyed textile units.
10
Sr No Textile Units
1 Nishat Mills Unit 35
2 Nishat Mills Unit 36
3 Nishat Mills Unit 22, 23, 24
4 Kohinoor Textile Millls
5 Master Textiles
6 Sarena Industries
7 Nishat Chunia Dyeing and Finishing
8 Sapphire Finishing Mills
9 Sapphire Fibers
10 Sapphire Textile Mills
11 Sapphir Diamond Fabrics
12 Bhanearo Textiles
13 Blessed Textiles
14 Faisal Spinning and Weaving Mills
15 Hunbul Textile
16 Shafi Texcel
17 Asian Textile Network
18 Kohinoor Dyeing Mills
19 Hira Terry Textile
20 Azgar 9
21 Indus Homes
22 US Denim Mills
23 US Apparels
24 Kohinoor Weaving Mills
25 Style Textile Table 1 Name of Surveyed Textile Units
Administrative Skills are the ability to perform organizational and basic, technical services.
Administrative skills include (but are not limited to) the abilities to file papers appropriately, take dictation,
set up meetings and help prepare presentations. Administrative skills are necessary for administrative
assistants and personal assistants.
Interpersonal skills are the life skills we use every day to communicate and interact with other
people, both individually and in groups. People who have worked on developing strong interpersonal skills
are usually more successful in both their professional and personal lives.
Conceptual skills are skills that allow a person to think creatively while also understanding abstract
ideas and complicated processes. A person who has conceptual skills will be able to solve problems,
formulate processes and understand the relationship between ideas, concepts, patterns and symbols.
Knowledge management is fundamentally about making the right knowledge or the right
knowledge sources (including people) available to the right people at the right time. Knowledge sharing is
therefore perhaps the single most important aspect in this process, since the vast majority of KM initiatives
depend upon it. Knowledge sharing can be described as either push or pull. The latter is when the knowledge
worker actively seeks out knowledge sources (e.g. library search, seeking out an expert, collaborating with
a coworker etc.), while knowledge push is when knowledge is "pushed onto" the user (e.g. newsletters,
unsolicited publications, etc)
11
Regression Analysis:
Regression Analysis is the possible methodology and statistical tool used for the investigation of
relationship between variables for the purpose of getting results. Regression analysis is used when you want
to predict a continuous dependent variable from a number of independent variables. If the dependent
variable is dichotomous, then logistic regression should be used. (If the split between the two levels of the
dependent variable is close to 50-50, then both logistic and linear regression will end up giving you similar
results.) The independent variables used in regression can be either continuous or dichotomous.
Independent variables with more than two levels can also be used in regression analyses, but they first must
be converted into variables that have only two levels. Usually, regression analysis is used with naturally-
occurring variables, as opposed to experimentally manipulated variables, although you can use regression
with experimentally manipulated variables. One point to keep in mind with regression analysis is that causal
relationships among the variables cannot be determined. While the terminology is such that we say that X
"predicts" Y, we cannot say that X "causes" Y.
To find the relationship between project success and knowledge sharing, simple regression equation
is in this research methodology because of only one variable present in Hypothesis 1. Knowledge sharing
score is the independent variable against dependent variable (Project Success). For hypothesis 1 the possible
equation will be;
𝒀 = 𝜶 + 𝜷𝑿
Where;
α and β are the regression coefficients
X = Knowledge Sharing Score
Y = Project Success measured by Project Delivery
To find the relationship between project success and leadership skills, Multiple Regression equation
is used in this research because of more than one variable present in Hypothesis 2. Administrative skills,
interpersonal skills and conceptual skills are the three independent variables against project success
(Dependent Variable) measured by project delivery. For Hypothesis 2 the possible equation will be;
Y = 𝜶 + 𝜷𝟏𝑿𝟏 + 𝜷𝟐𝑿𝟐 + 𝜷𝟑𝑿𝟑
Where;
α, β1, β2, β3 are the parameters known as regression coefficients
X1 = Administrative Skills Score
X2 = Interpersonal Skills Score
X3 = Conceptual Skills Score; and
Y = Project Success measured by Project Delivery
Regression coefficient enable us to measure the power of relationship between a dependent variable
and one or more independent variables. The coefficient of determination can get any value between 0 and
+1. It measures the proportion of the variation in a dependent variable that can be explained statistically by
independent variable or variables.
12
Chapter No. 4
Results and Analysis
We have done analysis on the basis of Questionnaires filled by 25 different General Managers and
Project Managers from 25 different textile organizations based in Lahore Region. We applied the regression
analysis by the use of SPSS (a statistical tool developed by IBM). In this regard vales were put in the data
entries table and test was performed against the given data obtained from questionnaire results.
Hypothesis 1: First research hypothesis was to prove that “A high degree of Knowledge Sharing tends to increase
the success of projects”.
From the following correlations results obtained through SPSS it’s prove that Knowledge Sharing
is (0.751) positively correlate with the project delivery. The Pearson product-moment correlation
coefficient tells us about the strength of the linear relationship between two variables. It is referred to as
Pearson's correlation or simply as the correlation coefficient. If the relationship between the variables is not
linear, then the correlation coefficient does not adequately represent the strength of the relationship between
the variables. Pearson correlation can range from -1 to +1. -1 indicates a perfect negative linear relationship
between variables, 0 indicates no linear relationship between the variables and +1 indicates a perfect
positive linear relationship between variables.
Correlations
Project Delivery Knowledge
Sharing
Pearson Correlation Project Delivery 1.000 .751
Knowledge Sharing .751 1.000
Sig. (1-tailed) Project Delivery . .000
Knowledge Sharing .000 .
N Project Delivery 25 25
Knowledge Sharing 25 25
Table 2 Pearson's Correlation
These positive, negative and no relationships can also be shown in graphical way. (Figure 1). A positive
correlation exists when as one variable decreases, the other variable also decreases and vice versa. In
statistics, a perfect positive correlation is represented by the value +1.00. From above Table 1 its
demonstrated that if knowledge sharing during the project increased to 0.751 then there are strong chances
of getting the projected results on time.
13
Figure 1 Pearson’s Possible Correlations
The table below showing the summarized results from regression analysis. R-squared is a statistical
measure of how close the data are to the fitted regression line. It is also known as the coefficient of
determination, or the coefficient of multiple determination for multiple regression.
The R-Squared is calculated by the formula;
R-Squared = Explained Variation/Total variation
The value of R squared is always between 0% and 100%. 0% indicates that model explains none
of the variability of the response data around its mean and 100% indicates that the model explains all the
variability of the response data around its mean. You can say that higher the value of R-Squared the better
the model fits your data and it means data is more real. From the below table calculated value of R-Squared
is 56% which means proposed model is around its mean with real data.
There are some limitations of R-Squared value
1. R-squared cannot determine whether the coefficient estimates and predictions are biased, which is
why you must assess the residual plots.
2. R-squared does not indicate whether a regression model is adequate. You can have a low R-squared
value for a good model, or a high R-squared value for a model that does not fit the data!
R-Squared provides an estimate of the strength of the relationship between model and the response
variable. While the F significance determines whether this relationship statistically significant or not. If Sig.
F < 0.05 it means the model is very much significant.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .751a .563 .544 .27554 .563 29.685 1 23 .000
a. Predictors: (Constant), Knowledge Sharing
b. Dependent Variable: Project Delivery Table 3 Model Summary (Regression Analysis0
The F-test of the overall significance is a specific form of the F-test. It compares a model with no
predictors to the model that specify. A regression model that contains no predictors is also known as an
intercept-only model. The F value is the ratio of the mean regression sum of squares divided by the mean
error sum of squares.
14
The value of Sig. F in above table 2 is .000, which means the proposed model is highly significant.
Which means knowledge sharing is the key to project success.
Hypothesis 2:
For hypothesis 2, “Project Managers having standardized sets of leadership skills tend to
have increased the project success”. Same questionnaire survey having 18 questions was distributed
among 25 different project managers.
Correlations
Project Delivery Administrative
Skills
Interpersonal
Skills
Conceptual
Skills
Pearson Correlation
Project Delivery 1.000 .692 .861 .739
Administrative Skills .692 1.000 .763 .751
Interpersonal Skills .861 .763 1.000 .823
Conceptual Skills .739 .751 .823 1.000
Sig. (1-tailed)
Project Delivery . .000 .000 .000
Administrative Skills .000 . .000 .000
Interpersonal Skills .000 .000 . .000
Conceptual Skills .000 .000 .000 .
N
Project Delivery 24 24 24 24
Administrative Skills 24 24 24 24
Interpersonal Skills 24 24 24 24
Conceptual Skills 24 24 24 24
Table 4 Pearson's Correlations Analysis
From above table it is shown that Administrative Skills have positively (O.692) correlation with
Project Delivery, it means success of any project is somehow dependent on the administrative skills of the
project manager. Interpersonal Skills have highly positive (0.861) correlation with the project delivery. And
conceptual skills have positive (0.739) correlation with the project delivery. Form the above table its shown
that leadership skills have perfect positive linear relationship with project delivery (success), when one
variable increases the other variable will increase by the same amount.
A positive correlation exists when as one variable decreases, the other variable also decreases and
vice versa. In statistics, a perfect positive correlation is represented by the value +1.00. From above Table
3 it’s demonstrated that if leadership skills during the project increased then there are strong chances of
getting the projected results on time.
15
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F Change
1 .863a .745 .707 .240 .745 19.475 3 20 .000
a. Predictors: (Constant), Conceptual Skills, Administrative Skills, Interpersonal Skills
b. Dependent Variable: Project Delivery
Table 5 Model Summary (Regression Analysis)
The table 4 above showing the summarized results from regression analysis. R-squared is a
statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient
of determination, or the coefficient of multiple determination for multiple regression. The value of R square
will be between 0% and 100%. The more the value of R-Square the more it near to its mean value which
means the model is more fit. In leadership skills hypothesis the value of R-Square is around 74%
(.745*100). This means that proposed model is 74% fit and having real data.
There are some limitations to R-Squared value, R-squared does not indicate whether a regression
model is adequate or not. For this the term Sig. F will explain the significance of the model, if value of Sig.
F < 0.05 it means proposed model is significant. From above table 4 it concluded that value of Sig. F is
0.00 which means model is perfectly fit in terms of significance.
From above results it’s evident that the Leadership Skills and Knowledge Sharing have a positive
correlation with the project success and delivery.
16
Chapter No. 5
Conclusion and Recommendations:
Results and Discussion:
From analysis part it’s concluded that project success propose model is very successful and project
delivery is mainly dependent on the Knowledge Sharing and Leadership Skills. Knowledge sharing and
leadership skills are positively correlate with the project delivery. Project delivery is associated with project
completion or project failure. Interpersonal skills which are the project managers’ main attribute has highly
perfect positive correlation with the project delivery. Project managers should have to focus on knowledge
sharing among their team members especially during planning and execution phase of the project to avoid
any re-invention during planning process. Interpersonal skills of a project manager plays a vital role in
decision making and resource usage dusting project completion process, right resources at the right time to
avoid any cost addition and time factor because these factors may lead project managers towards project
failure.
Recommendations for Future Work:
Further research can be done in this area by considering and by making this model more complex
and reliable. For this new researchers should also work on behavior and role of Human Resource
Management, Information Technology and Organizational Structure in project success. They may develop
a new model or can make some additions in the existing ones to propose a new model which is critical to
project success. HRM is the major success factor in any project because it deals with resources needed for
workforce. Information Technology also plays a key role in making the processes more reliable and
versatile to shorten the time required. Organizational structure is also playing the important role in
determining the project success.
17
References
[1] R. A. Noe and S. Wang, "Knowledge Sharing: A review and directions for future research," Human
Resource Management Reviw, vol. 20, pp. 115-131, 2010.
[2] S. Alhawari, L. Karadsheh, A. Nehari Talet and E. Mansour, "Knowledge-Based Risk Management
framework for Information Technology Project," Interantional Journal of Information
Management, vol. 32, pp. 50-65, 2012.
[3] M. Ajmal, P. Helo and T. Kakale, "Critical factors for knowledge management in project business,"
Journal of Knowledge Management, vol. 14, pp. 156-168, 2010.
[4] S. Pemsel and A. Wiewiora, "Project management office a knowledge broker in project-based
organisations," International Journal of Project Management, vol. 31, pp. 31-42, 2013.
[5] J. S. Holste and D. Fields, "Trust and tacit knowledge sharing and use," Journal of Knowledge
Management, vol. 14, pp. 128-140, 2010.
[6] S.-K. Lee and J.-H. Yu, "Success model of project management information system in
construction," Automation in Construction, vol. 25, pp. 82-93, 2012.
[7] T. Dewett and G. R. Jones, "The role of information technology in the organization: a review,
model, and assessment," Jourmal of Management, vol. 27, pp. 313-346, 2011.
[8] L. Raymond and F. Bergeron, "Project management information systems; An emprical study of
their impact on project managers and project success," International Journal of Project
Management, pp. 1-9, 2001.
[9] M. Hobday, "The project-based organisation: an ideal form for managing complex products and
systems?," Research Policy, vol. 29, pp. 871-893, 2000.
[10] I. HYVÄRI, "SUCCESS OF PROJECTS IN DIFFERENT ORGANIZATIONAL CONDITIONS,"
Project Management Journal, vol. 37, no. 4, pp. 31-41, 2006.
[11] M. M. Ajmal and K. U. Koskinen, "Knowledge Transfer in Project-Based Organizations: An
Organizational Culture Perspective," Project Management Journal, vol. 39, no. 1, pp. 7-15, 2008.
[12] V. S. Anantatmula, "Project Manager Leadership Role in Improving Project Performance,"
Engineering Management Journal, vol. 22, no. 1, pp. 13-22, 2010.
[13] L. Geoghegan and V. Dulewicz, "Do Project Managers’ Leadership Competencies Contribute to
Project Success?," Project Management Journal, vol. 39, no. 4, pp. 58-67, 2008.
[14] J. R. TURNER and R. MÜLLER,, "THE PROJECT MANAGER’S LEADERSHIP STYLE AS A
SUCCESS FACTOR ON PROJECTS:," Project Management Journal, vol. 36, no. 1, pp. 49-61,
2005.
18
[15] L.-R. Yang, C.-F. Huang and K.-S. Wu, "The association among project manager's leadership style,
teamwork and project success," International Journal of Project Management, vol. 29, pp. 258-267,
2011.
[16] M. Thite, "Leadership styles in information technology projects," International Journal of Project
Management, vol. 18, pp. 235-241, 2000.
[17] A. J. Shenhar, "Strategic Project Leaderships Toward a strategic approach to project management,"
R&D Management, pp. 569-578, 2004.
[18] M. Huemann, A. Keegan and J. R. Turner, "Human resource management in the project-oriented
company: A Review," International Journal of Project Management, vol. 25, p. 315–323, 2007.
[19] S. Maguire and T. Redman, "The role of human resource management in information systems
development," Management Decision, vol. 45, no. 2, pp. 252-264, 2007.
[20] A. Belout and C. Gauvreau, "Factors influencing project success: the impact of human resource
management," International Journal of Project Management, vol. 22, pp. 1-11, 2004.
[21] J. Pollack, "The changing paradigms of project management," International Journal of Project
Management, pp. 1-9, 2006.
[22] D. Dvira, T. Raz and A. J. Shenhar, "An empirical analysis of the relationship between project
planning and project success," International Journal of Project Management, vol. 21, pp. 89-95,
2003.
19
Appendices:
The questionnaires on each hypothesis are attached in this section. Each questionnaire has 18
questions and filled from 25 different organizational heads and Project Managers. Total number of
appendices are 50 (25 against each hypothesis)
Subject No. of Questionnaires
Hypothesis 1 25
Hypothesis 2 25
Total 50