Relationships of Factors for Successful ICT Projects Management

Relationships of Factors for Successful ICT Projects Management

Michiko Miyamoto

Department of Management Science and Engineering Akita Prefectural University

Yurihonjo, Akita Japan

AbstractThis study presents a framework and empirical analyses to measure relationships of factors for successful ICT projects management, by using the survey data from 1,678 managers and professionals working in a collaborative environment for Japanese software houses. The results of the research model using SEM show that there is a significant, strong and positive relationship between managers roles and communication/atmosphere, accomplishment/challenge, and obstacles. Furthermore, communication/atmosphere is closely related to obstacles.

KeywordsManagers roles; communication/atmosphere; accomplishment/challnege; obstacles, SEM.

1. INTRODUCTION

   As for project management in Information and Communication Technology (ICT) industry, the companies have strived to apply the most secure practice for ensuring the success of their projects. ICT projects reflect a dynamic team-based work structure; however, firms realize that designing and managing teams that work well together is a complex challenge [1, 2, 3]. The theoretical literature on ITC project management tends to assume that certain organizational rules, executive procedures, and environmental conditions are essential to the success of all types of projects. Meanwhile, management practitioners frequently ignore such general rules, because they are convinced that their particular projects pose entirely unique kinds of problems [4].

   Projects vary greatly in terms of targets, duration, budget, staffing and difficulty. However, in all projects involve elements, such as communication, atmosphere, accomplishment, challenge and obstacles, need to be managed throughout the project life cycle. The project life cycle includes those phases; the initiation phase, the planning phase, the implementation (execution) phase, and the closing phase [5].

   This paper empirically investigates relationships between managers roles, communication, atmosphere, accomplishment, challenge and obstacles, within the collaborative environment, the ICT project team.

   For estimating a fit between factors, advanced quantitative techniques of structural equation modeling (SEM) [6] have been employed. SEM has been established as an analytical tool, leading to hundreds of published applications per year. Overviews of the state of the method can be found in Cudeck et al.[7], Jöreskog [8], Millerand Form [9], and Shirai [10]. In this study, a suggested SEM

   model connects factors such as managers roles, communication, accomplishment, obstacles by using a survey data of 1,678 Japanese software development managers and professionals.

   This paper is organized as follows. Following the introduction on Section 1, Section 2 presents literature review on factors needed for successful ICT development teams. Section 3 outlines research model and hypotheses. Section 4 describes the data and variables. Section 5 presents the result of analysis. Finally, a summary of results are discussed in Section 6.

2. LITERATURE REVIEW

   Successful project methodologies provide the framework for management cultures are based on trust, communication, cooperation, and teamwork [11].

   1. Communication/Atomosphere

      Communication is known as the most important component within any project. The project management literature frequently outlines the importance of good communication for success in projects [12, 13, 14, 15, 16]. The success of most projects, whether handled by a dedicated project team or a cross-departmental team, depends upon a set of crucial communication skills and techniques. Communication affects performance. Therefore, effective communication entrenchments are needed in order to get high-performance teams working on a project. Without well- established communication channels, it is likely that the project will fail. Successful project managers typically have good communications skills that include being able to effectively present the issues, listen and act on feedback, and foster harmony among team members. [1].

      Charvat [1] suggests that there are three communication channels that managers need to establish once the project has started (See Fig. 1), and managing and improving these channels can dramatically increase chances of project success. Communication has long been documented as important for building and maintaining a productive interface between functional units.

      Motivating people is a key activity of a project manager. The project management should be effective, initiating a collaborative and responsible working atmosphere within the project team and the partners. The project manager can create an atmosphere where informal communication is expected and reinforced.

      Special attention has been paid to explain the concept of the project in order to create a single project vision and federate the team and the partners. According to Nash [17],

      leaders distinguish themselves by strong will to win, focus on achieving the results, establishing the culture of readiness for changes, and creating an atmosphere of trust.

      Upward Channel

      Communication to senior executives Highlight issues, risks

      and exceptoins

      Lateral Channel

      Communication to clients, provide direciton to vendors, and functional project team managers

      Highlight tasks Involves negotiations for pending, scheduled resources, budgets, and tasks, dates, and time allocations

      general team briefings

      Downward Channel

      Upward Channel

      Communication to senior executives Highlight issues, risks

      and exceptoins

      Lateral Channel

      Communication to clients, provide direciton to vendors, and functional project team managers

      Highlight tasks Involves negotiations for pending, scheduled resources, budgets, and tasks, dates, and time allocations

      general team briefings

      Downward Channel

      Fig. 1. Three communication channels (Based on Charvat, 2002)

   2. Roles of Project Managers

      Projects are managed in a work environment that is complex because each project is unique and dynamic [18]. In the context of project management, good leaders are required to assign appropriate importance to relationships, communicate their values, and at the same time pay suitable importance to processes [19].

      Project management is the application of knowledge, skills, tools and techniques to project activities to meet project requirements. The project manager is the person responsible for accomplishing the project objectives [20].

      In addition to working across functional and organizational environments, the project manager has other challenges such as providing leadership without documented, formal authority, and working in matrix organizations where unity of command is an issue [21]. Consequently, project managers are perceived to be leading a diverse set of people with little direct control over the team members [22].

   3. Accomplishment/Challenges

      Uniqueness, complexity, and unfamiliarity, are often considered as the characteristics of projects. Projects usually experience frequent personnel changes. People involved with projects are often dispersed when projects end, which creates challenges for generating, transferring, and sharing knowledge [23]. Projects are often associated with change, habitually facing resistance. Consequently, leadership is a determinant of success, as it provides vision and ability to cope with change [24]. Te challenge for the project manager is to make best and most effective use of the team that is selected [25].

      One of the challenges of project leadership is its limited role as a transformational leader. Helping subordinates develop to their fullest potential is an integral part of transformational leadership; however, projects may offer a limited role for transformational leadership from this perspective in traditionally functional hierarchy organizations [26]. A limited role is attributed to project formation and organizational structure that are different from those of traditional organizations, including the time-bound

      participation of people in multiple projects reporting to different project leaders. The project manager is the person who can challenge and who is responsible for accomplishing the project objectives.

   4. Obstacles

   In the IT sector, the results of the Chaos survey from The Standish Group in 2014 shows that 31.1% of all projects are cancelled before they ever get completed, while the average is only 16.2% for software projects that are completed on- time and on-budget. The failure has been posited to result from managers not implementing projects that align with the business strategy in global businesses [27]. Lyytinen and Hirschheim [28] identified 4 major categories of ITC failure; correspondence failure, process failure, interaction failure and expectation failure. According to Sauer [29], failure occurs when the level of dissatisfaction of supporters with a system rises to the extent when there is no longer enough support to sustain it. Problems in any of these three relationships will be the source of consequential difficulties for the other two, and unless the problems can be solved, this will lead ultimately to total withdrawal of support and system failure. Projects fail to meet time and cost targets due to people-related issues, such as poor morale, poor human relations, poor productivity, and lack of commitment [30].

3. RESEARCH MODEL AND HYPOTHESES Based on literature, the author measures relationships of

   those factors for successful ICT projects management, including (1) managers roles, (2) communication/atmosphere,

   (3) accomplishment/challenge, and (4) obstacles. In this study, a research framework was developed as shown in Fig. 2.

   Fig. 2. A research framework

   More specifically the author will investigate the following six hypotheses regarding an effective ICT management:

   H1: Managers roles will affect communication/ atmosphere. H2: Managers roles will affect accomplishment/challenge. H3: Managers roles will affect obstacles.

   H4: Communication/ atmosphere will affect accomplishment/challenge.

   H5: Obstacles will afect accomplishment/challenge. H6: Communication/ atmosphere will affect obstacles.

   In structural equation modeling, the author considers the causalities among all variables, especially between the result

   and the latent variables. Latent variable enables us to find many compiled observed variables at the same time based on the notion of structure. This works for generating and verifying hypothesis to find factors and causalities.

4. DATA

   The survey was sent to several software development companies in Tokyo, Japan, from January 2002 to March 2002 [31], and amassed 1,678 valid responses. The questionnaire was sent by mail to project managers of each firm, and they delivered the questionnaire to each project member.

   Since the survey was conducted through project managers of the companies where Enokida and Matsuodani

   [31] closely associated with, a response rate was close to100%. Most of the questionnaires are asked by a 4 point scale.

   Table I shows the demographics of the data. 84% of the participants are male, and most of them are between 26 and

   40 years old, having rich experiences in software development. One third of them are managing the project. There are short projects lasted less than one month, while more than 800 projects are going over one year long. A list of variables is shown in Table II.

   Table III contains the Pearson correlation coefficient between all pairs of twenty variables with the two-tailed significance of these coefficients. All variables correlate fairly well and are statistically significant, and none of the correlation coefficients are particularly large; therefore, multicollinearity is not a problem for these data.

   TABLE I. THE DEMOCRAPHICS OF DATA

   Variables	N			N
   Sex	male	1,276	female	265
   Age	25 or below 31-40	35 656	26-30 over 41	499 53
   Affiliation	user software house individual entrepreneurs	676 56 13	employee consultant Others	500 33 40
   Role within the project	manager	521	Professional	1,081
   Professional experiences	less than 2years 6-10 years	275 416	3-5 years over 11years	428 563
   Your work place	disperse others	772 16	concentrate –	807 –
   Number of people at the work place	less than 5 people 21-50 more than 101	239 388 278	6-20 51-100 –	595 196 –
   Management style of the project	top down	928	independent	596
   Length of your participation in the project	less than 1 month less than 6 mo over 1yr	94 200 804	less than 3 mo less than 1 yr –	212 325 –

   TABLE II. THE LIST OF VARIABLES FROM THE SURVEY

   	q7	Appropriate supports
   	q8	Ambitious management
   	q26	The good feeling, respect for the manager
   	q21	Having good communication
   	q6	Satisfied with the management and project policy
   	q19	Resolved unclear role responsibilities
   Roles of Project Managers	q3	The project role is determined by the right man in the right place, it operated smoothly
   	q33	Exactly fair evaluation
   	q5	Project policy and management policy have been told
   	q9	Sharing of necessary information
   	q39	This project will be successful
   	q11	Your role has been clearly explained
   	q4	Responsibility on the project is appropriate
   	q24	Communication with members of other teams is good
   	q25	Informal communication with project members is good.
   	q22	Communication between teams of each of the project is a good.
   Communication/	q23	Communication with team members is good
   Atmosphere	q36	Satisfied with workplace relationships
   	q27	Atmosphere conducive to aggressive behavior
   	q40	Hope to work with the same leader and same members in the next project.
   	q28	Cooperative atmosphere of "trying to achieve the goals of the job."
   	q31	It is possible to increase one's ability
   Accomplishment/	q32	Increase your market value
   Challenge	q1	Given a challenging worth work
   	q38	A sense of accomplishment for the day-to-day work.
   	q37	Have ever received the unreasonable treatment.
   	q17	By a sudden emergency, a trouble came to your work
   	q18	There were difficult problems associated with the adjustment of the user and the vendor
   Obstacles	q30	Troubles happened by uncooperative members.
   	q29	Because of the power relationships between organizations and members of the project, it is difficult to work.
   	q14	Working under time pressure.
   	q10	Disturbance sectionalism

   TABLE III. CORRELATIONS OF VARIABLES

   q1 q10 q11 q14 q17 q18 q19 q21 q22 q23 q24 q25 q26 q27 q28 q29 q3 q30 q1 1 .210** 323** -.025 .052* .044 .239** .295** .287** 255** .246** .244** .278** .328** .367** .203** .366** .215**

   q10 1 318** .119** .243** 229** .318** .319** .310** 261** .239** .243** .320** .340** .369** .409** .363** .372** q11 1 .042 .111** 099** .394** .368** .343** 312** .291** .288** .325** .391** .421** .280** .404** .211** q14 1 .293** 259** .151** .065** .080** 087** .041 .051* .046 .085** .079** .138** .164** .167**

   q17 1 569** .273** .110** .103** 107** .022 .072** .137** .143** .208** .226** .181** .268**

   q18 1 .300** .110** .104** 107** .033 .052* .140** .101** .159** .208** .165** .256**

   q19 1 .424** .338** 276** .272** .290** .456** .363** .417** .350** .448** .322**

   q21 1 .491** 405** .434** .479** .675** .506** .436** .319** .370** .251**

   q22 1 483** .636** .551** .413** .494** .467** .409** .352** .319**

   q23 1 .433** .489** .326** .374** .368** .297** .263** .315**

   q24 1 .614** .360** .401** .362** .287** .238** .207**

   q25 1 .393** .459** .390** .317** .270** .236**

   q26 1 .489** .458** .335** .409** .310**

   q27 1 .572** .483** .389** .319**

   q28 1 .466** .460** .359**

   q29 1 .358** .515**

   q3 1 .313**

   q30 1

5. RESULTS

   Testing the efficacy of the structural equation model was conducted by AMOS 22, and the major results of analysis are shown in Fig. 3. The path diagram highlights the structural relationships. In this diagram, the measured variables are enclosed in boxes, latent variables are circled, and arrows connecting two variables represent relations, and open arrows represent errors.

   q1	q31 q32 q33 q36 q37 q38 q39 q4 q40 q5 q6 q7 q8 q9 .605** .550** .366** .292** .202** .426** .332** .428** .402** .313** .373** .336** .295** .260**	TABLE IV. RELIABILITY TEST FIT indices Recommended level Research Model
   q10	.281** .284** .296** .329** .344** .256** .297** .247** .332** .298** .353** .330** .271** .350**	CMIN/DF CM CMIN/DF 6.954
   q11	.317** .276** .345** .325** .270** .365** .406** .435** .370** .462** .429** .416** .344** .396**	CFI >0.90 (Bentler, 1990) 0.900
   q14	.029 .046 .096** .148** .320** .090** .182** .081** .094** .054* .200** .106** -.014 .124**	IFI >0.90 ( Bollen, 1989) 0.901
   q17 .150** .140** .144** .182** .367** .142** .215** .076** .146** .115** .225** .159** .132** .181**	RMSEA	<0.08(Browne and Cudeck,1993)	0.060
   q18 .103** .116** .113** .161** .347** .128** .238** .103** .140** .104** .233** .165** .132** .154** AIC		Smaller values suggest a good fitting (Akaike, 1974)	3220.622
   q19	.283** .302** .433** .364** .340** .362** .442** .363** .397** .343** .449** .502** .460** .416**	p-value >0.05 0.000
   q21	.281** .271** .485** .432** .303** .358** .379** .349** .443** .391** .414** .602** .499** .357**
   q22 q23	.312** .318** .340** .495** .278** .371** .379** .282** .474** .343** .379** .327** .290** .364** .281** .250** .284** .530** .265** .292** .266** .295** .471** .233** .254** .303** .209** .300**	When SEM is used to verify a theoretical model, a
   q24	.217** .217** .311** .404** .183** .320** .244** .250** .359** .265** .277** .289** .228** .304**	better goodness of fit is required for SEM analysis [6]; the
   q25	.244** .251** .336** .486** .254** .349** .294** .278** .422** .290** .287** .317** .251** .276**	better the fit, the closer the model matrix and the sample
   q26	.329** .304** .490** .422** .317** .346** .413** .324** .480** .383** .435** .659** .608** .377** matrix. By means of various goodness-of-fit indexes,
   q27	.357** .357** .404** .489** .344** .356** .380** .345** .493** .401** .406** .416** .365** .379** including the comparative fit index (CFI) [32], the
   q28	.395** .398** .415** .485** .323** .418** .476** .341** .496** .391** .456** .446** .420** .420** incremental fit index (IFI) [32], and the root mean squared
   q29	.275** .280** .323** .505** .463** .300** .340** .294** .459** .261** .357** .343** .307** .329** error of approximation (RMSEA) [33], the estimated matrix
   q3

   q1	q31 q32 q33 q36 q37 q38 q39 q4 q40 q5 q6 q7 q8 q9 .605** .550** .366** .292** .202** .426** .332** .428** .402** .313** .373** .336** .295** .260**	TABLE IV. RELIABILITY TEST FIT indices Recommended level Research Model
   q10	.281** .284** .296** .329** .344** .256** .297** .247** .332** .298** .353** .330** .271** .350**	CMIN/DF CM CMIN/DF 6.954
   q11	.317** .276** .345** .325** .270** .365** .406** .435** .370** .462** .429** .416** .344** .396**	CFI >0.90 (Bentler, 1990) 0.900
   q14	.029 .046 .096** .148** .320** .090** .182** .081** .094** .054* .200** .106** -.014 .124**	IFI >0.90 ( Bollen, 1989) 0.901
   q17 .150** .140** .144** .182** .367** .142** .215** .076** .146** .115** .225** .159** .132** .181**	RMSEA	<0.08(Browne and Cudeck,1993)	0.060
   q18 .103** .116** .113** .161** .347** .128** .238** .103** .140** .104** .233** .165** .132** .154** AIC		Smaller values suggest a good fitting (Akaike, 1974)	3220.622
   q19	.283** .302** .433** .364** .340** .362** .442** .363** .397** .343** .449** .502** .460** .416**	p-value >0.05 0.000
   q21	.281** .271** .485** .432** .303** .358** .379** .349** .443** .391** .414** .602** .499** .357**
   q22 q23	.312** .318** .340** .495** .278** .371** .379** .282** .474** .343** .379** .327** .290** .364** .281** .250** .284** .530** .265** .292** .266** .295** .471** .233** .254** .303** .209** .300**	When SEM is used to verify a theoretical model, a
   q24	.217** .217** .311** .404** .183** .320** .244** .250** .359** .265** .277** .289** .228** .304**	better goodness of fit is required for SEM analysis [6]; the
   q25	.244** .251** .336** .486** .254** .349** .294** .278** .422** .290** .287** .317** .251** .276**	better the fit, the closer the model matrix and the sample
   q26	.329** .304** .490** .422** .317** .346** .413** .324** .480** .383** .435** .659** .608** .377** matrix. By means of various goodness-of-fit indexes,
   q27	.357** .357** .404** .489** .344** .356** .380** .345** .493** .401** .406** .416** .365** .379** including the comparative fit index (CFI) [32], the
   q28	.395** .398** .415** .485** .323** .418** .476** .341** .496** .391** .456** .446** .420** .420** incremental fit index (IFI) [32], and the root mean squared
   q29	.275** .280** .323** .505** .463** .300** .340** .294** .459** .261** .357** .343** .307** .329** error of approximation (RMSEA) [33], the estimated matrix
   q3

   .318** .321** .414** .368** .356** .383** .467** .468** .420** .399** .595** .486** .425** .444**

   q30 .336** .238** .278** .412** .452** .229** .294** .250** .384** .218** .307** .300** .273** .267** q31 1 .757** .448** .338** .256** .392** .330** .373** .436** .336** .359** .324** .297** .280** q32 1 .458** .323** .240** .413** .332** .350** .406** .318** .383** .328** .323** .263** q33 1 .413** .339** .358** .374** .423** .420** .381** .451** .486** .423** .342**

   q36 1 .414** .341** .361** .331** .612** .305** .382** .387** .323** .331**

   q38	1 .441** .362** .451** .333** .452** .392** .329** .305**
   q39	1 .362** .496** .398** .505** .431** .377** .377**
   q4	1 .398** .353** .423** .406** .313** .309**
   q40	1 .356** .457** .456** .372** .349**
   q5	1 .559** .444** .415** .392**
   q6	1 .544** .468** .481**
   q7	1 .712** .450**
   q8	1 .391**
   q9	1

   q38	1 .441** .362** .451** .333** .452** .392** .329** .305**
   q39	1 .362** .496** .398** .505** .431** .377** .377**
   q4	1 .398** .353** .423** .406** .313** .309**
   q40	1 .356** .457** .456** .372** .349**
   q5	1 .559** .444** .415** .392**
   q6	1 .544** .468** .481**
   q7	1 .712** .450**
   q8	1 .391**
   q9	1

   q37 1 .302** .340** .317** .413** .232** .372** .336** .256** .311**

   can be evaluated against the observed sample covariance matrix to determine whether the hypothesized model is an acceptable representation of the data. In general, incremental fit indexes (i.e., CFI, IFI) above 0.90 signify good model fit. RMSEA values lower than .08 signify acceptable model fit, with values lower than .05 indicative of good model fit [33]. The research model is shown in figure 3; CFI=0.900, IFI=0.901, RMSEA= 0.060 (see table IV). The

   Path Coefficient for both structural models suggested that the regression coefficient for all constructs show significance. Since all of the indexes satisfy the cut-off values, these results are regarded as acceptable.

   Fig. 3. A research model

   TABLE V. THE PATH COEFFICIENTS OF RESEARCH MODEL

6. CONCLUSIONS

construct Std.

Unstd. S.E. C.R. P

This paper presents a framework and empirical analyses

weight weight (t-value) value

failure, as communication is a component of a project at

the scope [36]. A survey conducted by Mnkandla [37] also

A result of the research model for relationships among factors relating to an effective ICT management; (1) managers roles, (2) communication/ atmosphere, (3) accomplishment/challenge, and (4) obstacles, shows the following six findings;

H1: There is a significant, strong and positive relationship between managers roles and communication/ atmosphere.

H2: There is a siginificant and positive relationship between managers roles and accomplishment/challenge.

H3: There is a siginificant and positive relationship between managers roles and obstacles.

H4: There is a siginificant and positive relationship between communication/ atmosphere and accomplishment/ challenge.

H5: There is a siginificant, but weak and negative relationship between obstacles and accomplishment/ challenge.

H6: There is a siginificant and positive relationship between communication/ atmosphere and obstacles.

are important for collaborative environments, and managers have to design their project teams carefully in order to maintain smooth project operation, and achieve a successful project completion.

A project team is generally quite a diverse group of people. Diversity within a project team can be cultural, geographical, organizational, functional, age related, level of education and so on. Project management communication within such diverse groups is a challenge at the best of times.

ACKNOWLEDGMENT

THIS WORK WAS SUPPORTED IN PART BY GRANT- IN-AID FOR SCIENTIFIC RESEARCH (C) 15K03607.

REFERENCES

1. J Charvat Project communications: A plan for getting your message across. TechRepublic, November 13, 2002. http://www.techrepublic. com/article/project-communications-a-plan-for-getting-your-message- across/

2. JR Hackman The design of work teams. In: Lorsch JW, editor. Handbook of organizational behavior. Englewood Cliffs, NJ: Prentice- Hall; 1987. pp. 315342.

3. JR Hackman, editor. Groups that work and those that dont. San Francisco: Jossey-Bass; 1990.

4. R Loo, Assessing team climate in project teams. International Journal of Project Management, 21(7), 2003, pp. 511517.

5. Project Management Institute, Inc., A Guide to the Project Management Body of Knowledge (PMBOK Guide), 4th ed., Newtown Square, PA: Project Management Institute, Inc., 2008, pp.1116.

6. B.M.Byrne, Structural equation modeling using AMOS. Basic concepts, applications, and programming 2nd Ed, New York: Routledge; 2010.

7. R Cudeck, S. du Toit, D. Sörbom, (Eds.), Structural Equation Modelling: Present and Future, Scientific Software International, Chicago, 1992.

8. KG. Jöreskog, New developments in LISRELAnalysis of Ordinal Variables Using Polychoric Correlations and Weighted Least Squares. Quality and Quantity, 24, 1990, pp. 387-404.

9. D Miller, , W Form, Industrial Sociology. New York Harper; 1951.

10. T Shirai, Contemporary Industrial Relations in Japan. Madison: University of Wisconsin Press; 1983.

11. HR Kerzner, Using the Project Management Maturity Model: Strategic Planning for Project Management, 2nd Edition, Wiley, New York. 2005.

12. F.T. Hartman, Dont Park Your Brain Outside. Project Management Institute, Newtown Squre, PA, 2000.

13. R Mu¨ller, JR Turner, The impact of performance in project management knowledge areas on earned value results in information technology projects. Project Management: International Project Management Journal 7(1), 2001, pp.44-51.

14. Standish Group, CHAOS 98: A Summary Review. A Standish Group Research Note 1998, 1-4, The Standish Group, USA.

15. Standish Group, CHAOS 98: A Summary Review. A Standish Group Research Note 1998, The Standish Group, USA, pp. 1-4.

16. R Keller, Cross-functional project groups in research and new product development: diversity, communications, job stress, and outcomes, Academy of Management Journal 44(3), 2001, pp.547-555.

17. S Nash, Vision, Leadership in Project Management 2005 v1, Project Management Institute (PMI). Pennsylvania, USA, 2004.

18. S J Zaccaro, A L Rittman, M A Marks, Team leadership. Leadership Quarterly, 12,.2001, pp. 451-483.

19. R J Turner, Matching the Project Managers Leadership Style with the Project Type, PMI Research Conference, July 2006, pp. 16-19.

20. AA Al-Hatmi, Public IT Investment – The Success of IT Projects, Partridge Publishing, India, 2014.

21. D Cleland, Leadership and the Project Management Body of Knowledge, International Journal of Project Management,13(2), 1995, pp.83-88.

22. D Cleland, L R Ireland, Project Management:Strategic Design and Integration, McGraw-Hill, 2002.

23. J T Karlsen, P Gottschalk, Factors affecting knowledge transfer in IT projects. Engineering Management Journal, 16(1), 2004, pp. 310.

24. J P Kotter, John P. Kotter on what leaders really do. Boston: Harvard Business School Press, 1999.

25. VS Anantatmula, Project Manager Leadership Role in Improving Project Performance. Engineering Management Journal, Vol. 22 No. 1. March 2010, pp. 13-22.

26. A E Keegan, D N Den Hartog, Transformational leadership in a project-based environment: A comparative study of the leadership styles of project managers and line managers. International Journal of Project Management, 22(8), 2004, pp.609618.

27. M Stanleigh, "From Crisis to Control: A New Era in Strategic Project Management", Business Improvement Architects, Business Improvement Architects. (2006, May 3). Retrieved August 27, 2015, from https://www.bia.ca/articles/pj-FromCrisisToControl.htm.

28. K. Lyytinen, and R.Hirschheim, Information systems failures a survey and classification of the empirical literature, Oxford Surveys in Information Technology, 1987, pp.257-309.

29. C. Sauer, Why Information Systems Fail: A Case Study Approach. Alfred Waller Henley-On-Thames, 1993.

30. H Kerzner, Project management: A systems approach to planning, scheduling, and controlling (9th ed.). New York: Wiley, 2006.

31. Y Enokida, T.Matsuodani, A Development of Team-Building Skills, Journal of the Society of Project Management, 6(2), 2004, pp. 9-11.

32. PM Bentler, Comparative t indexes in structural models, Psychological Bulletin; 1990, pp.238-246.

33. MW. Browne, R Cudeck, Alternative ways of assessing model fit, Sociological Methods and Research.21, 1993, pp.230239.

34. D Remenyi, F Bannister, A Money, The Effective Measurement and Management of ICT Costs and Benefits (third edition),CIMA Publishing/Elsevier, 2008.

35. L Rosencrance, Survey: Poor communication causes most IT project failures, Computerworld, Mar 9, 2007.

36. L Lopes, AV Mañas, Delays in IT Projects due to Failures in the Stakeholders Management, Future Studies Reserach Journal, v.5, n.2, Jul./Dec. 2013, pp.158-185.

37. E Mnkandla, A review of Communication Tools and Techniques for Successful ICT Projects, The African Journal of Information Systems, 6(1), 2013, pp.1-8.