Requirements for the Degree Doctor of Business Administration

EXAMINING THE RELATIONSHIP BETWEEN LEADERSHIP STYLE AND PROJECT SUCCESS IN VIRTUAL PROJECTS by George E. Arnold A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Business Administration UNIVERSITY OF PHOENIX November 2008 3345049 3345049 2009 Copyright 2008 by Arnold, George E. All rights reserved 2008 by George E. Arnold ALL RIGHTS RESERVED ABSTRACT The purpose of this quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual projects. The number of virtual project teams is increasing (Anu, 2006). Furst et al. (2004) reported as many as 13 million employees in the United States are members of one or more virtual project teams. The target population for the study included 500 Project Management Professional-certified project managers who reside in the Kansas City, Missouri, metropolitan area. The entire target population of 500 project management professionals received a three-part questionnaire by way of direct mail. The mailing included a postage-paid return envelope for participants to return the completed anonymous questionnaires for data collection and analysis. The sample included all 229 respondents from the target population of 500 project management professionals. The response rate was consistent with the 218 responses needed to ensure a confidence level of .95 with a margin of error of .05 (Raosoft, 2008). The findings indicated a statistically significant relationship exists between leadership style, specifically transformational leadership, and project success in virtual projects. The quantitative data could assist leaders through increased understanding of the impact of leadership style on the success of virtual projects. iv ACKNOWLEDGMENTS Many individuals played a significant role in this doctoral journey. Such a journey would be impossible without a strong supporting cast. I was fortunate to have the help and support of family, friends, coworkers, faculty, and an outstanding dissertation committee, with the best mentor a student could ask for. Dr. Charlene Dunfee provided inspiration, motivation, expert guidance, encouragement when the process got difficult, and a gentle nudge when I needed it to stay on track. Dr. Dunfee set an example all dissertation mentors should seek to emulate. Dr. Alex Hapka and Dr. Mark Kass provided meaningful feedback and guidance as committee members. The leadership team and my coworkers at the University of Phoenix Kansas City Campus were always there with words of encouragement. Brian Messer, Campus Director, and Dr. Merlyne Starr, Regional Director of Academic Affairs, were consistently supportive of my efforts. Particularly noteworthy was the nonwavering support provided by my immediate supervisor Ron Heim, Director of Academic Affairs. And finally to my family, my wife Denise, daughter Kyla, son Rob, grandchildren Tristan, Bella, and Alexis, sister Karen, and mother Kathleen, I want to express my deepest gratitude. This journey would have been impossible to endure without their support and willingness to allow me to take time I could have, and should have, spent with them over the past 3 years. v TABLE OF CONTENTS LIST OF TABLES……………………………………………………………………………………. ix LIST OF FIGURES …………………………………………………………………………………….x CHAPTER 1: INTRODUCTION………………………………………………………………….1 Background of the Problem ………………………………………………………………………….2 Statement of the Problem……………………………………………………………………………..4 Purpose of the Study ……………………………………………………………………………………4 Significance of the Study……………………………………………………………………………..5 Significance of the Study to Leadership …………………………………………………………6 Nature of the Study ……………………………………………………………………………………..6 Research Questions……………………………………………………………………………………..7 Hypotheses…………………………………………………………………………………………………8 Theoretical Framework………………………………………………………………………………..9 Definition of Terms……………………………………………………………………………………10 Assumptions……………………………………………………………………………………………..11 Limitations……………………………………………………………………………………………….11 Delimitations…………………………………………………………………………………………….12 Summary………………………………………………………………………………………………….12 CHAPTER 2: REVIEW OF THE LITERATURE…………………………………………14 Keyword Search and Documentation …………………………………………………………..14 Historical Overview…………………………………………………………………………………..15 Project Success …………………………………………………………………………………..15 Leadership Styles………………………………………………………………………………..16 vi Project Success………………………………………………………………………………………….17 Leadership Styles………………………………………………………………………………………19 Laissez-faire……………………………………………………………………………………….20 Transactional………………………………………………………………………………………23 Transformational…………………………………………………………………………………25 Team Leadership……………………………………………………………………………………….33 Leadership in Virtual Project Teams ……………………………………………………………34 Conclusion ……………………………………………………………………………………………….41 Summary………………………………………………………………………………………………….42 CHAPTER 3: METHOD……………………………………………………………………………43 Research Method and Design Appropriateness……………………………………………..43 Quantitative Research………………………………………………………………………….43 Correlational Research…………………………………………………………………………45 Multiple Regression Analysis……………………………………………………………….46 Research Questions……………………………………………………………………………………46 Hypotheses……………………………………………………………………………………………….47 Population ………………………………………………………………………………………………..48 Informed Consent………………………………………………………………………………………48 Sampling Frame………………………………………………………………………………………..49 Confidentiality ………………………………………………………………………………………….50 Instrumentation …………………………………………………………………………………………50 Data Collection …………………………………………………………………………………………52 Data Analysis……………………………………………………………………………………………52 vii Validity and Reliability………………………………………………………………………………54 Multifactor Leadership Questionnaire……………………………………………………55 Project Implementation Profile……………………………………………………………..56 Summary………………………………………………………………………………………………….57 CHAPTER 4: RESULTS……………………………………………………………………………58 Research Questions……………………………………………………………………………………58 Hypotheses……………………………………………………………………………………………….58 Data Collection and Coding………………………………………………………………………..59 Findings……………………………………………………………………………………………………60 Description of Sample …………………………………………………………………………60 Data Analysis……………………………………………………………………………………..71 Data Analysis of the Regression……………………………………………………………73 Multiple Regression Model ………………………………………………………………….75 Assumptions of Multicollinearity Data ………………………………………………….77 Model Summary …………………………………………………………………………………83 Summary………………………………………………………………………………………………….87 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS…………………….88 Conclusions………………………………………………………………………………………………88 Implications………………………………………………………………………………………………89 Recommendations for Further Study……………………………………………………………90 Summary………………………………………………………………………………………………….91 REFERENCES …………………………………………………………………………………………93 viii APPENDIX A: COPY OF INFORMED CONSENT FORM FOR PARTICIPANTS 18 YEARS OF AGE AND OLDER…………………………………109 APPENDIX B: PERMISSION TO USE EXISTING SURVEY: PROJECT IMPLEMENTATION PROFILE……………………………………………………………….111 APPENDIX C: PERMISSION TO USE EXISTING SURVEY: MULTIFACTOR LEADERSHIP QUESTIONNAIRE…………………………………………………………..114 APPENDIX D: COPY OF SURVEY INSTRUMENT: DEMOGRAPHICS……117 APPENDIX E: COPY OF SURVEY INSTRUMENT: PROJECT IMPLEMENTATION PROFILE……………………………………………………………….120 APPENDIX F: COPY OF SURVEY INSTRUMENT: SAMPLE OF MULITFACTOR LEADERSHIP QUESTIONNAIRE ………………………………..122 APPENDIX G: QUESTIONNAIRE CODEBOOK ……………………………………..124 ix LIST OF TABLES Table 1 PMP Certification Eligibility Requirements…………………………………… 49 Table 2 Description of Variables……………………………………………………………….74 Table 3 Descriptive Statistics (N = 121) …………………………………………………….75 Table 4 Correlations………………………………………………………………………………..78 Table 5 Regression Analysis: All Possible Regressions (p values for the Coefficients)………………………………………………………………79 Table 6 Nonparametric Correlations (N = 121) ………………………………………….80 Table 7 Residuals Statistics (N = 121) ……………………………………………………….83 Table 8 Model Summaryb ………………………………………………………………………….84 Table 9 ANOVAb ……………………………………………………………………………………..84 Table 10 Coefficientsa ………………………………………………………………………………85 x LIST OF FIGURES Figure 1. Gender of respondents.. ……………………………………………………………. 61 Figure 2. Age range of respondents………………………………………………………….. 62 Figure 3. Year PMP certification earned…………………………………………………… 62 Figure 4. Number of years project management experience………………………… 63 Figure 5. Number of years virtual project experience…………………………………. 64 Figure 6. Highest education level achieved……………………………………………….. 64 Figure 7. Industry of employment……………………………………………………………. 65 Figure 8. Project geographical scope………………………………………………………… 65 Figure 9. Size of project team………………………………………………………………….. 66 Figure 10. Length of project……………………………………………………………………. 66 Figure 11. Size of project budget. ……………………………………………………………. 67 Figure 12. Time difference between team members. ………………………………….. 67 Figure 13. Number of firms or organizations represented. ………………………….. 68 Figure 14. Frequency of video conferencing……………………………………………… 69 Figure 15. Frequency of e-mail communication. ……………………………………….. 69 Figure 16. Frequency of voice mail communication…………………………………… 69 Figure 17. Frequency of telephone communication…………………………………… 69 Figure 18. Frequency of using Web-based Internet tools…………………………….. 70 Figure 19. Frequency of using conference calling. …………………………………….. 70 Figure 20. Frequency of using electronic meeting systems. ………………………… 70 Figure 21. Frequency of using instant messaging. ……………………………………… 71 Figure 22. Normal P-Plot of regression standardized residual……………………….82 xi Figure 23. Scatter plot ……………………………………………………………………………..83 1 CHAPTER 1: INTRODUCTION As organizations become more complex, dynamic, and global, the use of collaborative technology is growing rapidly (Carte, Chidambaram, & Becker, 2006). The need for innovative business solutions drives organizations to implement virtual, geographically dispersed project teams to pool the diverse talents of employees (Furst, Reeves, Rosen, & Blackburn, 2004). These virtual project teams function beyond the barriers of geographic space and differing time zones, allowing organizations to pool the talents of individuals who are not able to participate in traditional face-to-face project teams (Bengt, 2005). The number of virtual project teams is increasing in the current global business environment (Anu, 2006). Furst et al. (2004) reported as many as 13 million employees in the United States are members of one or more virtual project team. Virtual project teams create unique leadership challenges (Kerber & Buono, 2004). The distance between team members in virtual project teams restricts face-to-face communication and may impede primary leadership activities (Piccoli, Powell, & Ives, 2004). With more organizations relying on virtual project teams to accomplish organizational objectives, selecting an effective leadership style becomes increasingly important for virtual project success (Carte et al., 2006). Chapter 1 contains an introduction to the importance and significance of the research. The problem statement, purpose statement, and significance of the problem create an effective roadmap. The nature of the study, research questions, and hypotheses provide grounding and direction. Finally, the theoretical framework, definitions of terms, assumptions, limitations, and delimitations provide additional foundation for comprehending the research. 2 Background of the Problem A new paradigm is emerging: the virtual team. Geographically dispersed teams are challenging traditional leadership roles (Tovey, Southard, & Bates, 2005). The workplace is undergoing vast changes. An increasing trend toward dispersed project teams necessitates a fresh look at leadership in virtual project teams (Pearce, 2004). Past research focused on the impact of leadership in traditional face-to-face project team settings (Pauleen, 2003). Virtual project teams are different (Bock, 2003). Virtual projects bring together geographically dispersed workers through information and communication technologies (Cromb, 2005). Virtual project teams work together closely, though separated by miles or even continents. Virtual project teams meet through conference calls, video conferences, e-mail, or other communication tools such as application sharing (Beranek & Martz, 2005). Virtual project teams are becoming a key component of successful global companies (Kahai, Sosik, & Avolio, 2003). Major shifts in a new global economy are converging and increasing the need for virtual project teams. Virtual project teams will play a significant role in shaping future organizations (Reilly, Lojeski, & Reilly, 2005). Organizations are able to respond faster to competition in a rapidly changing business environment by quickly gaining access to expertise within the company regardless of the location of employees (McKinney, Barker, Smith, & Davis, 2004). Although virtual project teams offer a myriad of benefits, the virtual project environment also presents leadership challenges and potential pitfalls. The leadership challenge is to identify a leadership style allowing virtual project teams to be effective and successful (SobelLojeski & Reilly, 2006). 3 Globalization will drive the need for virtual project teams in the workplace (Harvey, Novicevic, & Garrison, 2005). As a result, business leaders must understand the significance of leadership behavior in a virtual project environment (Callan, 2003). Some of the traits most often observed in transformational leaders, such as charisma and vision, may not translate well to a virtual project team setting (Cromb, 2005). Status cues are harder to read in virtual project teams (Harvey et al.). Organizations wishing to implement virtual project teams understand specific leadership styles and investigate the impact of different leadership styles in a virtual project environment (Beranek & Martz, 2005). The literature on leadership styles, specifically transactional and transformational leadership, is extensive; however, only a small number of studies on leadership address how leadership style affects project success (Barbuto, 2005). Even less research exists concerning leadership style and project success in a virtual project environment (Dube & Pare, 2004). By appreciating the effectiveness of particular leadership styles, organizations may improve the selection and training of virtual project team leaders. The improvement, in turn, may assist organizations seeking to expand globally (Beranek & Martz, 2005). The issue of leadership in virtual project teams is an increasingly important issue for many organizations, particularly those seeking to expand globally (Chinowsky & Rojas, 2003). Although it appears clear that leadership is vital for success in the virtual project environment, the form the leadership takes is not as clear. Leadership is an interesting phenomenon for the virtual project environment, as most of the literature focuses only on a face-to-face leadership environment (Kahai et al., 2003). Countless leadership models exist that identify key leadership styles required for 4 business success; however, no models specifically address the leadership styles needed to ensure project success in the virtual project environment. The current study involved a search to determine how leadership style affects virtual project team success. Statement of the Problem Failed projects cost businesses millions of dollars each year (Jarman, 2005), and failed leadership is one of the leading causes of project failures (Piccoli et al., 2004). The problem is the failure to identify the most effective leadership style in a virtual project environment may result in projects being unsuccessful and may negatively affect the implementation of corporate strategic business goals and objectives (Goodbody, 2005). The current quantitative study examined the relationship between leadership styles as measured by the Avolio and Bass Multifactor Leadership Questionnaire (MLQ; Bass, Avolio, Jung, & Berson, 2003) and project success in virtual project teams as measured by the Pinto and Slevin Project Implementation Profile (PIP; Pinto & Slevin, 1988). Approximately 500 certified project management professionals received a three-part survey consisting of the MLQ, the PIP, and a series of questions pertaining to respondent demographics. Purpose of the Study The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. The study employed a correlational approach and multiple regression analysis to determine the strength of the relationships between the two variables. A quantitative research method, specifically correlation analysis, provided the group of statistical measures necessary to portray relationships 5 among the variables and to accomplish the stated purpose of the study (Creswell, 2005). Approximately 500 certified project management professionals received a three-part survey consisting of the MLQ, the PIP, and a series of questions pertaining to respondent demographics. All survey participants reside in the Kansas City, Missouri, metropolitan area. Significance of the Study Business organizations are becoming increasingly more global and competition from both foreign and domestic sources is growing dramatically (Harvey et al., 2005). As a result, organizations emphasize distributed virtual project teams (Beranek & Martz, 2005). Many organizations rely on the skills of professionals located throughout the world. Virtual project teams allow businesses to gather the most qualified employees for particular projects, regardless of the employees location (Zakaria, Amelinckx, & Wilemon, 2004). As the business environment grows more complex, becomes more uncertain, and moves faster, traditional organizational structures may be too cumbersome to respond effectively (Saunders, Van Slyke, & Vogel, 2004). Advances in technology and collaboration software enable the increased use of virtual project teams (Saunders et al.). Virtual project teams will play an important role in shaping organizational structure and flexibility (Seilheimer, Ishman, & Seilheimer, 2006). The future of any industry will include virtual project teams (Avolio & Yammarino, 2003). Businesses implementing virtual project teams can expect to see reduced real estate expenses, reduced transportation expenses, increased productivity, higher profits, environmental benefits, and increased access to global markets (Piccoli et al., 2004). The data collected in the 6 study may be of high relevance to business organizations seeking to implement virtual project teams. Significance of the Study to Leadership Creating and maintaining high-performance project teams requires strong leadership skills (Chia-Chen, 2004). Virtual project teams present new leadership challenges not present in traditional face-to-face team settings (Kerber & Buono, 2004). The distance between team members in virtual project teams restricts face-to-face communication, impedes primary leadership functions, and hampers the virtual team leaders ability to perform typical mentoring, coaching, and organizational development functions (Kaisa & Kirsimarja, 2005). Although existing leadership models address team development and effectiveness, the basis of the models is the traditional face-to-face perspective (Daft, 2005). The conclusions reached in the study may lead to practical leadership strategies and the development of a new leadership model for virtual project teams. Nature of the Study The purpose of the quantitative study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. A need to describe and measure the degree of relationship between the independent variable, leadership styles, and the dependent variable, project success in virtual project teams, resulted in the selection of a quantitative correlational design (Creswell, 2005). A quantitative research method, specifically correlation analysis, provided the group of statistical measures necessary to portray relationships among the variables and 7 accomplish the stated purpose of the study. A quantitative correlational design was appropriate because the study did not involve a search to prove relationships, but simply to explain the relationships between two or more variables (Creswell, 2005). The need to describe the relationship between two or more variables, without attributing the effect of one variable on another, made correlational research appropriate for the study. Correlational research uses multiple regression analysis to develop a mathematical equation to estimate the value of relationships among variables (Creswell). The quantitative study examined the relationship between leadership styles as measured by the MLQ (Bass et al., 2003) and project success in virtual project teams as measured by the PIP (Pinto & Slevin, 1988). A three-part survey consisting of the MLQ, the PIP, and a series of questions pertaining to respondent demographics provided the necessary research data for each of the variables. The MLQ instrument sought to determine whether the project manager of a virtual project employed a transformational, transactional, or laissez-faire leadership style. The PIP instrument provided a measurement of project success in a particular virtual project identified by the survey respondent. The demographic instrument collected the necessary data to provide descriptive statistics pertaining to the respondents project management experience, the scope and complexity of the project, and the project collaboration tools used to complete the project. Research Questions The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. Although a number of theories and 8 studies explain leadership effectives in traditional project settings, little empirical work exists examining leadership in a virtual project environment (Kaisa & Kirsimarja, 2005). Consequently, the focus of the study was to address the gap by investigating how leadership style affects virtual team effectiveness. Two research questions guided the study: 1. How does the project managers leadership style correlate with project success in a virtual project environment? 2. Which leadership style correlates with a higher level of project success in a virtual project environment? Hypotheses H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. 9 H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. Theoretical Framework A new paradigm for leadership is emerging, and the virtual environment is changing leadership roles (Tovey et al., 2005). Corporate mergers, globalization, the need to respond rapidly to changing markets and customer demands, and travel costs require organizational leaders to consider new methods of conducting business (Piccoli et al., 2004). Although a particular leadership style may be effective in a face-to-face environment, the same style may not work in a virtual project setting (Goodbody, 2005). Although many leadership theories exist, the characteristics identifying an individual as a leader are consistent throughout the literature (Yukl, 2006). The study of leadership includes thousands of scholarly works (Locke, 2003), each attempting to use previous theories to answer new questions about the nature of leadership. A contingent of leadership theorists contends leadership is no different in virtual settings than in face-toface settings (Piccoli et al., 2004). Other leadership theorists purport existing theory does not address the complexities in the global business environment and, in particular, in virtual project environments (Pauleen, 2003). Although existing literature demonstrates an understanding of the dynamics of virtual project teams (Furst et al., 2004), what constitutes best practices in the leadership of virtual project teams is not as clear (Cromb, 2005). In a world where time and distance are no longer a barrier (Kaisa & Kirsimarja, 2005), having strong leaders is critical for the success of any virtual project operation. 10 Project leadership is a complex task, requiring the project manager attend to a wide variety of factors in attempting to implement a project successfully. The notion of project success is often ambiguous and thus not easy to define. Because of the ambiguity, project managers have a tendency to rely on simplistic formulas in rating project success or failure. Projects meeting the performance objectives of being within budget and on time often meet the criteria for project success (Project Management Institute [PMI], 2004). However, measures of project success can be much more complex than simply meeting cost, schedule, and performance specifications. The current study employed a model of project success developed by Pinto and Slevin (1998) to evaluate the studys dependent variable. Definition of Terms Project: A project is a temporary endeavor undertaken to accomplish a unique product or service (PMI, 2004, p. 4). Projects have clearly defined beginning and end dates, dedicated resources, and desired performance outcomes. Project team: A project team consists of individuals with complementary skills who seek to combine efforts to achieve a common goal (Piccoli et al., 2004). Virtuality: The most common view of what it means to be virtual is defined in terms of dispersion (Dube & Pare, 2004). Virtual environments are dispersed on a variety of dimensions, most often geographically and in time; however, other dimensions include organizational structure, culture, and experience. The greater the dispersion, the more virtual the environment is said to be (Zigurs, 2003). Virtual project team: A virtual project team brings together a group of geographically dispersed workers through information and communication technologies 11 (Cromb, 2005). Virtual project teams work closely together even though many miles may separate them. Virtual project teams meet through conference calls, video conferences, e-mail, or other communication tools such as application sharing (Anu, 2006). Assumptions For the purpose of the study, a major assumption was participants would respond openly and honestly to the survey instrument. Another assumption was the MLQ (Bass et al., 2003) and the PIP (Pinto & Slevin, 1988) would provide an accurate measure of the variables selected for study. Although the total possible sample of participants might appear relatively small, an assumption was the participants experiences and responses were representative of project managers with significant experience with virtual project teams. Limitations The limitations of the study were participants who agreed to participate voluntarily, the number of participants surveyed, and the amount of time available to conduct the study. The informed consent form (see Appendix A) indicates participation in the study was voluntary and anonymous. Individuals receiving the survey could choose not to participate or to withdraw from the study at any time. Validity of the study was limited to the reliability of the instruments used and the honesty and truthfulness of the respondents. The MLQ and PIP are validated instruments. Both instruments contain questions requiring subjective responses. Project managers responding to the survey instrument likely provided a subjective analysis of project success and leadership style. Bias may be evident because project managers, in their own retrospections, may not have always accurately recalled the actual situations. The passing of time may have 12 added to the error of recall. Participants were invited to respond to the survey based on experience with a recent virtual project to lessen the passage of time, thus reducing the risk of memory failure. Delimitations In a research study, delimitations narrow the scope of the study and list what is not included or intended in the study (Creswell, 2005). The current study narrowed the focus to the entire target population of 500 certified project management professionals who reside in the Kansas City, Missouri, metropolitan area. However, study conclusions and recommendations may generalize to the 260,000 members of the PMI in 171 countries (PMI, 2008). Virtual project teams will play a significant role in shaping future organizations (Reilly et al., 2005). The results of the study could provide project management professionals around the world a new leadership model for virtual teams. The purpose of quantitative correlational design is to discover relationships between variables, not causality (Creswell, 2005). Other external project success variables such as reliability of suppliers, economic changes, and technology issues may have contributed to the results, adding potential threats to external validity (Leedy & Ormrod, 2005). The study was not intended to examine variables beyond those identified in the purpose of the study. Summary Chapter 1 introduced the importance of the study. The purpose statement and significance of the problem created an effective roadmap for the study. The nature of the study, research questions, and hypotheses provide grounding for the direction of the 13 study. Finally, the theoretical framework, definitions of terms, assumptions, limitations, and delimitations provided additional foundation for comprehending the research. The problem presented in the study was failure to identify and address leadership effectiveness in a virtual project environment will continue to result in project failures and negatively affect the implementation of corporate strategic business goals and objectives (Goodbody, 2005). The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. The quantitative correlational study examined the relationship between leadership styles as measured by the MLQ (Bass et al., 2003) and project success in virtual project teams as measured by the PIP (Pinto & Slevin, 1988). Chapter 1 contained an introduction of the basic concepts of the study. Chapter 2 presents a review of literature related to the research questions and hypotheses of the study. The literature review includes an overview of major leadership styles, virtual project team concepts, and methods for evaluating project success. 14 CHAPTER 2: REVIEW OF THE LITERATURE The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. Chapter 2 contains a review of literature related to the research questions and hypotheses of the study. The literature review includes an overview of major leadership styles, methods for evaluating project success, and an assessment of the effectiveness of virtual project team leadership. In an information-rich, technology-driven society, the traditional concepts of leadership style require reexamination to account for the nature of globally dispersed project teams (Goodbody, 2005). Where leadership style was once about creating stability and uniformity within an organization, the focus changed to adapting to change and diversity in a global business environment (Beranek & Martz, 2005). Keyword Search and Documentation ProQuest and EBSCOhost were the primary databases used for the search of peerreviewed journal articles, books, and Web sites. A Boolean search technique with a combination of search terms such as project, success, virtual, teams, and leadership resulted in the return of approximately 500 references. The next step was elimination of references deemed not relevant to the study. Literature that appeared related to the research variables received consideration for potential inclusion in chapter 2. Approximately 250 references met the criteria for entry into a dissertation library using EndNotes software. Of the 250 selected for the dissertation library, the reference section of the dissertation includes the 116 references considered most applicable to the study. 15 Historical Overview Creating and managing successful projects requires strong leadership skills (ChiaChen, 2004). An understanding of project success began to develop in the early 1970s (Belout & Gauvreau, 2004). In contrast, leadership theories and discussion of leadership styles date back to the ancient Greeks (Cawthon, 1996). Project Success In a complex era, individuals typically have less impact on overall organizational success or failure and are more dependent on collaborating with teams to achieve project success (Wren, 1995). Defining project success can be difficult because a diverse group of stakeholders may describe the concept differently (Pitno & Slevin, 1988). Since the early 1970s, attempts to identify variables critical to project and business success primarily focused on the product or the business unit level (Andrews, 1971). Zaltman, Duncan, and Holbeck (1973) suggested organizational issues such as organizational structure, the skills of the project manager, and project coordination play key roles in project success. Rubinstein et al. (1976) found people, rather than organizational factors, make projects successful. Certain individuals known as project champions can influence the outcome of projects (Rubinstein et al.). Pinto and Slevin (1988) identified 12 project success factors based on the project sponsors ability to meet client needs and expectations. Time may also affect the evaluation of project success. Objectives of time, cost, and quality are only short-term measures made at the end of a project. Judgment of whether the project meets client needs and expectations may require additional time (Collins & Baccarini, 2004). 16 Leadership Styles Ancient Greeks assumed leaders had traits such as knowledge, wisdom, competence, talent, and ability and such traits are by nature a circumstance of birth (Cawthon, 1996, p. 2). The leadership used in ancient Greece centered on authoritarian styles with little regard for subordinates (Cawthon). As time evolved, leaders began to understand the value subordinates had in enhancing situations and improving production when managed properly (Bass, 1990). The Modernist Period is characterized by an understanding of the changing dynamics of the industrial revolution, and the impact of interactions between organizations, employees, and societies (Wren, 1995). Lewin, Lippit, and White (1939) identified three different leadership styles relating to decision making. The first style identified was the autocratic style, in which the leader makes decisions without consulting others. The second style identified was the democratic style, in which the leader involves subordinates in the decision-making process. The third style identified was the laissez-faire style, which minimized the leaders involvement in decision making, allowing subordinates to make independent decisions (Lewin et al., 1939). While many dimensions of leadership are evident in the literature, Webers (1947) concept of charisma formed the basis for many of the contemporary approaches to leadership. Weber (1947) suggested the concept of charisma includes vision or mission, extraordinary or exceptional qualities, and recognition. In terms of leader behavior, Webers (1947) three dimensions of charisma equate to vision-related behaviors, personal behaviors, and empowering behaviors (Kim, Dansereau, & Kim, 2002). 17 During Post-Modernism, attitudes toward the use and sharing of knowledge influenced organizations to improve communication. Burns (1978) published a germinal work on transformational and transactional leadership, describing transformational leaders as uplifting the morale, motivation, and morals of followers. Transactional leaders, in contrast, embark upon an exchange relationship with followers in to meet self-interests. Burns (1978) introduced transformational leadership into research as a model of leadership that pays particular attention to initiating changes among followers and transforming followers personal values. Bass (1990) furthered the construct by noting transformational leaders build a different relationship with followers than transactional leadership based on personal, emotional, and inspirational exchanges. Project Success The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. This section of the literature review examines factors shown to impact project success, the dependent variable. In reviewing the literature on project success factors, Turner and Muller (2005) found the literature largely ignores the project manager and his or her leadership style (p. 49). An understanding of project success has continued to develop since the early 1970s. Initially, the definition of project success focused on measuring time, cost, and quality of project deliverables (Belout & Gauvreau, 2004). As project management methodology developed, the quality of planning and the perspectives of all stakeholders became important to measuring project success. More recently, other factors such as the 18 effective use of the project product, staff development, customer benefits, and the environment help to measure project success (Kendra & Taplin, 2004). The perception of success or failure of a project may not be the same for different people in different roles. Uncommon sets of values, experiences, and expectations among project stakeholders may result in conflicting assessments of project success (Rad, 2003). The concept of project success is a topic often discussed and yet seldom agreed upon by all stakeholders. A review of the literature revealed two distinct views on project success: the traditional view of the triple constraints of time, cost, and quality and an enhanced view considering the different perspectives of all project stakeholders (Collins & Baccarini, 2004; Hughes, Tippett, & Thomas, 2004; Rad, 2003). Additional success criteria may include stakeholder satisfaction, the benefit to organizational strategic goals, and team satisfaction. The client is primarily concerned with meeting the objectives of the project (Rad, 2003). Schedule and cost attributes are of secondary importance in determining project success (Shatz, 2006). When an organization initiates a project, the successful implementation of deliverables is typically the basis for measuring project success (Shatz). The project teams view of success is fundamentally different than the clients view of success. Whereas the client focuses on the deliverables, the project team focuses on means by which the deliverables are completed (Rad). For the project team to consider a project successful, the activities involved in managing the project and motivation of the people performing project tasks are key factors. People issues can have a considerable impact on project success (Kupakuwana & van der Berg, 2005). 19 Pinto and Slevin (1988), in one of the most widely quoted project success models, identified 12 project success factors. The instrument developed by Pinto and Slevin to collect data on the 12 factors is the PIP (see Appendix E). The PIP uses a 7-point Likert type scale to rate 12 project success factors from strongly disagree to strongly agree. Measuring project success is a complex endeavor but extremely important to effective project implementation. Determination of project success or failure rests with the project sponsor and the ability to fulfill the clients needs and expectations (Kendra & Taplin, 2004). Understanding how the project managers leadership style affects projects, specifically in a virtual project environment, will aid in the development of future project managers (Belout & Gauvreau, 2004). Leadership Styles Organizations of the future will need leaders who can manage uncertainty and competition within an increasingly diverse workforce to achieve organizational viability and profitability (Antonakis, Cianciolo, & Sternberg, 2004). Past descriptions of leadership include motivating and inspiring (Avolio, 2004), influencing the behavior of other people toward group goals (Barbuto, 2005), and giving direction to others to accomplish specific results (Chia-Chen, 2004). Leadership, when shared, is dynamic, interactive, and influential (Kark, Shamir, & Chen, 2003). Because the purpose of the current study was to determine how leadership style, the independent variable, affects virtual project team success, the dependent variable, a review of prominent leadership styles is necessary. The survey instrument used to collect data on leadership styles was the MLQ. The MLQ uses the full-range leadership model developed by Bass, Avolio, Jung, and Berson (2003). The MLQ is a comprehensive assessment including 45 items 20 measuring leadership styles ranging from laissez-faire to transactional to transformational (Avolio & Bass, 2004). The following literature review and analysis of leadership styles begins with laissez-faire, followed by transactional, and transformational. Laissez-faire Lewin, Lippit, and White (1939) first described the laissez-faire leadership style by identifying three different styles of decision making: autocratic, democratic, and laissez-faire. The autocratic leader makes decisions without consulting others. Much like a dictatorship, the leaders word is law. Manipulation, threats, and even force ensure the accomplishment of the leaders goals. Communication is usually one-way. Employees are told what, how, and when to accomplish a task. Feedback is limited to communicating with employees only when a mistake occurs or a task is not complete (Daft, 2005). Employees often resent such treatment, which results in higher levels of absenteeism and turnover (Hernez-Broome & Hughes, 2004). Although subordinates may object to the stressful nature of the autocratic style, the style may be appropriate in some situations. Rapidly changing conditions in the workplace may call for urgent action, leaving little time for seeking employee input. Some employees may even favor an autocratic leader in stressful times, preferring to be told exactly what to do and when (Ciampa & Watkins, 2005). The democratic leader involves subordinates in the decision-making process; however, after gathering input from employees, the leader still has the final say. Employees often respond to a democratic style with high morale and team spirit. When used with experienced and highly skilled employees who exhibit buy-in through empowerment, the participative style can be effective. Team members feel more engaged 21 in the decision-making process when encouraged to participate in the process (Baldoni, 2005). Allowing subordinates to participate is not a sign of weakness. Employees will likely gain respect for a leader who values input from others before making decisions. Together, the leader and the team members can generate alternatives for consideration (Antonakis et al., 2004). The democratic leadership style offers less control than the autocratic style and more guidance than the laissez-faire style (Blanchard, Edeburn, OConnor, & Zigarmi, 2005). The laissez-faire leader allows subordinates to make independent choices. Laissez-faire is a French phrase meaning leave it be, implying no leadership because the leader provides little or no direction to the followers. The laissez-faire style is neither transactional nor transformational because leaders avoid responsibilities, fail to make decisions, and are usually absent when needed (Skogstad, Einarsen, Torsheim, SchankeAasland, & Hetland, 2007). The leader provides no direction to employees on how to determine goals, make decisions, or resolve problems (Northouse, 2004). The follower receives little support or feedback. The absence of direction and feedback could be problematic in a virtual environment. Virtual teams need a clear purpose and focus (Cromb, 2005). Even using communications technology [will not] help your team get the job done if it is missing these critical ingredients (Bock, 2003, p. 43). Without an opportunity to observe visual cues, small misunderstandings quickly escalate into serious problems (Gareis, 2006). Face-to-face communication uses verbal and nonverbal cues to transmit subtle shades of meaning (Rico & Cohen, 2005). Without the ability to discern ambiguous directions, the virtual team is less likely to be successful (Sobel-Lojeski & Reilly, 2006). 22 Laissez-faire leadership is not the same as democratic leadership or empowerment. Democratic and empowering leaders have a sense of purpose and direction. Tasks are delegated to subordinates, and follow-up helps make certain the tasks are successfully completed (Skogstad et al., 2007). The disassociation from active leadership is often disempowering and can have a negative effect on production. A lack of adequate leadership creates stress and frustration with the followers (Daft, 2005). When leaders fail to provide a meaningful work environment, team members get frustrated and restless, leading to a loss of control. Control is necessary in a team environment to keep task completion on track (Northouse, 2004). For members of virtual project teams, guidance and control provide belonging and goal alignment with the organization (Reilly et al., 2005). Skogstad et al. (2007) posited, Laissez-faire leadership may be more of a counterproductive leadership style than a zero type of leadership style, associated with a stressful environment characterized by high levels of role stress and interpersonal conflicts (p. 89). Organizations should be aware of the potential negative effects of a laissez-faire style. Role conflict and role ambiguity result in employee interpersonal stress (Kelloway, Mullen, & Francis, 2006). Indirect behavior such as intentionally missing a meeting hosted by a subordinate or failing to support a subordinate when a client or customer questions the subordinates actions can create an undesirable effect on followers (Skogstad et al.). A transactional or transformational leadership style may provide the structure and discipline needed to move a virtual project team in the desired direction (Keegan & Den Hartog, 2004). Laissez-faire leaders assume team members are intrinsically motivated 23 and need little direction or guidance (Eagly, Johannesen-Schmidt, & van Engen, 2003). Although leaders may emerge from the virtual team to provide organization and structure, communication of organizational goals and objectives from top leadership remains a necessity (Carte et al., 2006). A feeling of separation from corporate knowledge is common for virtual project team members (Zhang, Fjermestad, & Tremaine, 2005). Laissez-faire leadership could increase team member frustration from the lack of adequate communication. Transactional Transactional leadership is an exchange process whereby followers receive rewards for accomplishing specified goals or achieving specific levels of performance (Bass et al., 2003). Leaders recognize followers needs and clarify how those needs will be met (Bono & Judge, 2004). In the realm of leadersubordinate relations, the leader provides incentives for the followers efforts. Leaders exchange wages for work performed by the employee; in the political environment, politicians may swap favors or government jobs for votes. Maximizing efficiency and profits is the short-term goal of transactional leadership (Robinson, 2005). Leaders offer wages for work seeking to influence employees, but do not tap into workers creativity. Transactional leadership may encourage leaders to change leadership style to meet the perceived needs of the followers. Focusing on the needs of followers or on followers personal development is not a priority for transactional leader (Bass, 1990). Acknowledging individual and group behavior with meaningful incentives fosters team spirit. If a team member foresees positive feedback or rewards, he or she will possibly contribute more to achieve team goals (Kuo, 2004). 24 Positive transactional reinforcement using rewards is not the only method for appealing to followers self-interest. For example, when teams complete projects on time and within budget, the transactional leader may provide monetary rewards or other incentives. However, if projects exceed budgets or deadlines, negative reinforcement such as reprimands or other disciplinary action may be used (Barbuto, 2005). Historically, most management and leadership theories focus on actions or traits (Northouse, 2004). If transactional leadership is an exchange process as described above, the relationship requires closer examination. Graen and Uhl-Bien (1995) posited leadership includes three separate components: the leader, the subordinate, and the relationship between the two. Leader-member exchange posits leaders will have highquality relationships with some employees, whereas relationships with other employees will be low quality. Leader-member exchange views leadership as the interactions between leaders and followers (Charles, Epitropaki, Martin, McNamara, & Thomas, 2005). Leader-member exchange starts with the premise that leaders and followers form unique relationships within an organizational unit. Graen (1976) assumed leaders behave differently toward each follower and categorized followers as belonging to an in-group or an out-group. Followers become part of either an in-group or an out-group based on how well the follower works with the leader and how well the leader works with the follower. Relationships within the in-group reflect trust, respect, and reciprocal influence. Relationships within the out-group encourage formal communication based on job description (Graen & Uhl-Bien, 1995). Leader-member exchange suggests supervisors will use varying communication methods depending on the relationship with employees. Employees with better 25 relationships with supervisors expect to have higher quality communications. Further, employees in higher quality relationships reported communication with a supervisor was participatory; however, individuals in low-quality relationships reported one-way communication (Charles et al., 2005). The quality of the exchange is contingent upon the mutual trust, loyalty, and influence of the leader and the member. A favorable relationship is possible when the leader perceives the employee to be reliable and competent (Yukl, 2006). When the quality of the relationship is high, employees tend to be more responsible and contribute more to the organization (Bass, 1990). Although transactional leaders enforce rules to avoid mistakes, the arrangement of mutually satisfactory agreements and the exchange of rewards for performance lead to successful outcomes (Judge & Piccolo, 2004). However, Avolio and Bass (2004) posited, transactional leadership often fails to work because the leader lacks the necessary reputation or resources to deliver the needed rewards (p. 23). When negative contingent reinforcement is used, followers tend to see the transactional leader in a different way (Avolio & Bass, 2004). Employees typically view negative reinforcement as punishment. People experiencing negative reinforcement will only work as hard as necessary to avoid unpleasant consequences. A negative approach does not encourage maximum effort (Yukl, 2006). Virtual project teams require self-motivated members who are willing to provide maximum effort to accomplish project tasks with little supervision (SobelLojeski & Reilly, 2006). Transformational Bass (1990) contrasted transactional leaders, who work within the boundaries of self-interest (p. 23), with transformational leaders, who move to change the 26 framework (p. 23). This contrast suggests leadership is more than the simple exchange process defined in transactional leadership. Transcending self-interest for the organization is good for the leader, the follower, and the organization (Tucker & Russell, 2004). Exploring the differentiation further, transactional leaders focus on the innovation necessary to advance a personal agenda. Transformational leaders focus on the innovation necessary to advance an agenda for the organization. Beng-Chong and Ployhart (2004) maintained the transformational leader will possess a complete understanding of both the organization and its place in society. The transactional leadership model limits innovation, personal growth, and building a sense of team spirit (Bass, 1990). The transactional leader works within the existing organizational culture: the transformational leader changes it (Avolio & Bass, 2004, p. 31). While transactional leaders use rewards to motivate, transformational leaders motivate followers through charisma, inspiration, intellectual stimulation, and individual consideration (Bono & Anderson, 2005). Innovation, communication, and chaos through change are critical components for successful transformation leaders. Although the same measurement in terms of individual performance exists with a transformational leader, the organizational impact of performance is also considered. Transformational leadership requires transformation, beginning first with the individual and then with the organization. Although seminars, books, training, and formal education will better prepare an individual for transformational leadership, the method for doing so is highly dependent upon the individuals predisposition toward change and the organizations readiness for change. Burns (1978) described transformational leaders as uplifting the morale, motivation, and morals of followers. Transactional leadership is a 27 telling style, while transformational leadership is more of a selling style. Using words of inclusion, recognizing the individual needs of followers, and assuring followers no obstacle is too large to overcome will sell the organizations vision to all stakeholders (Rubin, Munz, & Bommer, 2005). Transformational leadership requires a transformation in the followers by raising awareness regarding the importance of the organization and not just the individual (Gillespie & Mann, 2004). Northouse (2004) described transformational leadership as a leadership style depicting the description of a wide range of leadership (p. 131). Burns (1978) introduced transformational leadership into research as a model giving particular attention to initiating changes that transform followers personal values. Bass (2005) furthered the construct by noting transformational leadership builds a different relationship with followers than transactional leadership based on personal, emotional, and inspirational exchanges. Transformational leaders motivate followers to work for transcendental goals and for aroused higher level needs for self-actualization in place of immediate self-interest (Burns). Avolio and Bass (2004) identified four unique but interrelated behavioral components of transformational leadership: idealized influence, or charismatic role modeling; inspirational motivation, or articulating an appealing vision; intellectual stimulation, or promoting creativity and innovation; and individualized consideration, or coaching or mentoring. A closer look at the four key aspects of transformational leadership identified by Avolio and Bass (2004) clarifies how transformational leaders can achieve results in several ways. The first aspect, idealized influence, indicates transformational leaders have associates who view them in an idealized way, and as such, these leaders wield 28 much power and influence over followers (Avolio & Bass, 2004, p. 28). Followers develop strong feelings about such leaders and want to identify with the leaders and the mission. The second aspect, inspirational motivation, involves articulating shared goals and understanding in simple ways. When organizational goals and objectives are clear, follower identification with the leader is not essential. The third aspect, intellectual stimulation, encourages followers to question beliefs, assumptions, and values to develop the capacity to solve problems by being creative and innovative. The final aspect, individualized consideration, involves treating each follower uniquely and recognizing individual contributions to organizational goals and objectives (Avolio & Bass). Consideration for the subordinate is a concern for transformational leaders, as in other models of leadership (Beng-Chong & Ployhart, 2004). Transformational leaders have a vision of how things could be in a work group in contrast to the status quo; the vision is imparted to subordinates through excitement and enthusiasm, which inspires followers to support the vision (Dionne, Yammarino, Atwater, & Spangler, 2004). Transformational leadership has a constructive impact on effectiveness in traditional face-to-face teams (Garman, Davis-Lenane, & Corrigan, 2003). Transformational leaders contribute to team spirit, as they tend to promote a vision and a mission, build commitment and confidence, emphasize group recognition, instill team spirit by welcoming all input, create opportunities for others, and introduce humor with appropriate frequency (Chia-Chen, 2004). Transformational leadership recognizes and exploits an existing need or demand of a potential follower . . . , looks for potential motives in followers, seeks to satisfy higher needs, and engages the full person of the follower (Burns, 1978, p. 4). 29 Transformational leaders are those individuals who tap the motives of followers to reach the goals of leaders and followers (Burns, 1978). Burns proposed the leader follower interaction could be either transactional or transforming, where the motivation of the leaders and followers is raised (as cited in Reinhardt, 2004). Transformational leadership has a greater affect on followers than transactional leadership (Burns). Transformational leaders create an awareness of moral and ethical implications transcending self-interest for the greater good (Walumbwa, Lawler, Avolio, Wang, & Shi, 2005). Morals and ethics were central to Burns theory (Burns). Bass (1990) extended Burns (1978) work by giving more attention to followers needs. With Burns theory as a foundation, Bass (1990) posited leadership need not be an either/or proposition between transactional and transformational behaviors. Rather, Bass (1990) perceived the two concepts to be complementary, with transformational leadership augmenting transactional leadership, particularly in response to the needs of the situation. Transformational leadership motivates followers to go beyond what is required (Avolio, 2004) and accounts for a larger share of the variance in performance outcomes (Bass, 2005). Transformational leaders act as change agents, transforming followers attitudes and beliefs (Bass et al., 2003). By providing vision and developing emotional relationships with followers, transformational leaders motivate followers to a higher level, going beyond self-interest (Antonakis, Avolio, & Sivasubramaniam, 2003). Avolio and Bass (2004) proposed transformational leader behaviors include four components: inspirational motivation, idealized influence, individualized consideration, and intellectual stimulation. The challenge becomes how to apply the transformational process to virtual project teams (Keegan & Den Hartog, 2004). 30 One leadership trait addressed in the transformational leadership model is charisma. The term comes from the ancient Greek word charismata, meaning gift, in particular a gift from the gods (Conger, 1989). The Christian church later used the term to describe traits bestowed by God such as wisdom, prophecy, and healing (Conger & Kanungo, 1988). Charisma has been studied as a set of behaviors and as a trait (Conger, 1989; Wren, 1995). Weber (1947) retained much of the Christian meaning of charisma and purported the authority of some leaders stemmed from a divine gift setting them apart from ordinary men and causing them to be treated as endowed with supernatural, superhuman, or at least exceptional powers and qualities (pp. 358-359). Weber saw charismatic leaders as highly esteemed persons who exude confidence. Conger and Kanungo (1988) described charismatic leader behavior as being radical, unconventional, risk taking, visionary, entrepreneurial, and exemplary. Followers are often mesmerized by the charismatic leaders words and sense of urgency (Choi, 2006). Personality and charm help to gain influence over followers (Bass, 1990) and display an indescribable energy that inspires and motivates (de Hoogh et al., 2004). The concept of charisma is prevalent in a wide variety of leadership models and appears to be an important component of transformational leadership (Kerber & Buono, 2004). Focusing on the personal characteristics of charismatic leaders, House (1977) purported charismatic leaders display moral conviction and self-confidence (as cited in Barbuto, 2005). Nadler and Tushman (1995) outlined three observable behavioral characteristics of charismatic leaders: envisioning, energizing, and enabling. Envisioning involves articulating a vision of the future or of the desired future state. Energizing involves generating energy by demonstrating personal excitement and confidence. 31 Enabling involves empathizing and expressing confidence in people. Charismatic leaders set high expectations and show confidence these expectations can be achieved (Choi, 2006). While many dimensions of charismatic leadership are evident in the literature, Webers (1947) concept forms the basis for many of the contemporary approaches to charismatic leadership. Weber suggested the concept includes vision or mission, extraordinary or exceptional qualities, and recognition. In terms of leader behavior, Webers three dimensions equate to vision-related behaviors, personal behaviors, and empowering behaviors (Choi, 2006). Existing leadership models identify common characteristics of the charismatic transformational leader. The common characteristics typically include vision and the ability to articulate the vision (Conger & Kanungo, 1988). Conger and Kanungo provided the basis for a heuristic model of charismatic leadership based on a number of different perspectives. Most contemporary approaches view vision or mission as the most essential factor in the concept of charisma (Callan, 2003). A sense of strategic vision characterized charismatic leaders (Conger, 1989). Conger and Kanungo (1998) defined vision as a set of idealized future goals established by the leader that represent a perspective shared by followers (p. 156). Therefore, vision-related behaviors formulate and articulate a future goal (Callan, 2003). A leaders personal behavior reflects the leaders motivation, self-confidence, personal risk, selfsacrifice, and dedication to the vision (de Hoogh et al., 2004). Conger and Kanugo purported that to achieve a vision, leaders must display self-confidence and dedication to achieving the vision. 32 A charismatic leader also displays empowering behaviors by communicating expectations and exhibiting confidence in the followers ability to meet expectations (Choi, 2006). Conger and Kanugo (1988) described empowerment as a process whereby an individuals belief in his or her self-efficacy is enhanced (p. 474). In contrast, Kouzes and Posner (2002) rejected the myth of the charismatic leader, which may lead to hero worship and cultism. Although leader charisma might play a key role in strategic leadership, some researchers hold an opposing view of this style, warning that such leaders might be self-serving, self-aggrandizing, and exploitative (de Hoogh et al., 2004). Conger and Kanugo (1988) reshaped the conceptualization of charismatic leaders as radical, unconventional, risk-taking, visionary, entrepreneurial, and exemplary. The charismatic transformational leader inspires others to excel, considers others first, and stimulates followers to think innovatively (Javidan & Waldman, 2003). Consideration of the leader/follower relationship primarily takes into account the abilities, interests, and personal traits of leaders and the strong desire of followers to identify with the leader (Raelin, 2003). Watching a charismatic leader interact with team members in a face-to-face team meeting can be fascinating. The leader pays close attention to each individual, making each person feel important and valued. The leader is able to adapt quickly to the people and the situation in the room. Body language and other visual cues help to create the desired effect (Takala, 2005). The significance of charismatic behavior in a virtual project environment is not clear (Callan, 2003). Some of the traits most often observed in transformational leaders, such as charisma and vision, may not translate well to a virtual project team setting 33 (Cromb, 2005). Status cues are harder to read in virtual project teams (Harvey et al., 2005). The lack of visual cues means less opportunity for nonverbal cues to be expressed (Bock, 2003). Hand and face movements and gestures are the most pervasive types of nonverbal messages and the most difficult to control. Body movements illuminate true feelings that are difficult to mask (Burtha & Connaughton, 2004). More than words are necessary to create productive teams. In the virtual environment, the inability to process nonverbal cues may create unintended misunderstandings (Fiol & OConnor, 2005). Team Leadership The use of work teams constitutes a major trend in organizational structure (Thamhain, 2004). As a result, the topic of leadership in organizational teams is becoming increasingly valuable (Avolio, Jung, Murry, Sivasubramaniam, & Garger, 2003). Groups work together to accomplish organizational goals. The use of teams as a central element of decision making and performance is increasing (Atwater, Spangler, & Yammarino, 2004). Organizations of all kinds use teams to accomplish goals. Teams have increasingly become the focus of leadership training (Anu, 2006). The workplace is changing. With an increase in the use of teams, understanding the role of leadership within teams is necessary to ensure team success and avoid team failure (Chia-Chen, 2004). Leadership needs to be practical and focus on needs and performance outcomes (Dousman, Labia, & Morin, 2003). The role of a leader changes in a team environment. The focus is on behaviors engaged in by the team, rather than on the behavior of a single individual (Carte et al., 2006). Although team leaders still fulfill many of the functions of traditional leaders, team leaders serve more as facilitators and coaches. Team leaders help 34 achieve goals by providing guidance, conflict management, encouragement, and resources when needed (Pearce & Conger, 2003). The primary functions of leadership include helping tasks and keeping the team supported, maintained, and functioning (Yukl, 2006). Leadership plays a significant role in creating and maintaining high-performance work teams in a traditional team environment (Thamhain, 2004). Drawing a distinction between traditional teams and virtual teams may no longer be practical due to the expansion of technology throughout most organizations. The global economy is forcing many organizations to adopt innovative approaches to survive (Goodbody, 2005). As a result, many organizations are abandoning traditional face-to-face work teams in favor of virtual teams (Sobel-Lojeski & Reilly, 2006). Moving to a virtual team environment does not guarantee project success. Although developing a metric for project success would appear straightforward, inconsistencies exist regarding which factors should be included (Pinto & Slevin, 1988). Leadership in Virtual Project Teams A virtual project team is a group of geographically dispersed workers brought together across time and space through information and communication technologies (Cromb, 2005). Virtual project teams work closely together, even though many miles, time zones, and cultures may separate them. Virtual project teams meet through conference calls, video conferences, e-mail, or other communication tools such as application sharing (Zhang et al., 2005). A new paradigm for leadership is emerging, and the virtual environment is changing leadership roles (Tovey et al., 2005). For many reasons, including corporate mergers, globalization, the need to respond rapidly to 35 changing markets and customer demands, increasing sophistication of technology, travel costs, and the trend toward flexibility in the workforce, organizations change from the old ways of conducting business to new ones (Piccoli et al., 2004). The number of virtual teams is increasing in the global business environment (Anu, 2006). Furst et al. (2004) estimated as many as 13 million employees in the United States were members of one or more virtual team. Advances in technology and collaboration software enable greater use of virtual teams (Saunders et al., 2004). Virtual teams will play an important role in shaping organizational structure and enable organizations to become more flexible (Seilheimer et al., 2006). Whatever the industry, the future appears to include the virtual team. Businesses implementing virtual teams can expect to see reduced real estate expenses, increased productivity, higher profits, environmental benefits, and greater access to global markets (Piccoli et al., 2004). In the year 2034, virtual teams and e-leadership will be the rule rather than the exception (Bass, 2005, p. 383). The issue of leadership in virtual project teams is complicated for many modern organizations. As organizations become more complex, dynamic, and global, the use of collaborative technology is growing (Carte et al., 2006). Globalization is driving organizations to implement virtual, geographically dispersed teams to pool the assorted talents of employees (Furst et al., 2004). Virtual project teams eliminate the barriers of time and space. Organizations can bring together important contributors from throughout the organization (Bengt, 2005). Many organizations rely on the skills of professionals located throughout the country and even the world. Virtual project teams allow businesses to gather the most qualified employees for particular jobs, regardless of the 36 employees location (Zakaria et al., 2004). Organizations using virtual project teams can maximize resources and hire the best people for the job, regardless of where the people live (Beranek & Martz, 2005). However, the distance between team members in virtual project teams often restricts face-to-face communication and impedes primary leadership functions (Sobel-Lojeski & Reilly, 2006). The inability to observe and measure performance makes coaching and mentoring difficult. Virtual project teams are different from traditional face-to-face teams (Bock, 2003). Status cues are harder to read in virtual project teams (Reilly et al., 2005). Some of the traits attributed to transformational leaders, such as charisma and vision, may not translate well to a virtual project team setting. With more people working in physically displaced virtual settings, less opportunity exists for nonverbal cues expressed through body language, dress, and demeanor helping to promote clear understanding (Bock). Clarifying communication dynamics, specifically the role of human, present-moment awareness through the communicative process, may be valuable for leaders and work groups who cannot communicate in both face-to-face and computer-mediated modalities. Leadership in the virtual environment is extremely important as leaders attempt to influence individuals not seen on a regular basis (Piccoli et al., 2004). The task of being an effective leader in a virtual environment can be daunting (Bengt, 2005). Virtual project teams can indeed be difficult to design, costly and complex to implement, difficult to manage, and potentially less productive than traditional face-to-face, collocated teams (Gibson & Cohen, 2003). A contingent of theorists contended leadership is no different in virtual project settings (Piccoli et al., 2004). Other leadership theorists purported existing theory does 37 not address the complexities existing in the global business environment and, in particular, in virtual project environments (Pauleen, 2003). Although a significant amount of research indicates leadership is vital for success in virtual project teams, the form leadership takes in an emerging virtual realm remains unclear (Bengt, 2005; Carte et al., 2006; Furst et al., 2004). The virtual project team leader does not always have all the facts and information team members do, and vice versa. Leaders ensure the team members have enough information to understand the leaders expectations as well as those of the team (Sirkka, Thomas, & Staples, 2004). Leaders define the tasks, the expectations, and the environment so virtual project team members will have a clear understanding of how to do the work and in what . Clear lines of communication are essential for the success of a virtual project team. Without clear lines of communication, mistakes, mistrust, unexpressed viewpoints, and unresolved conflicts are likely to occur (Lee-Kelley, Crossman, & Cannings, 2004). Zigurs (2003) proposed virtual project teams might eventually learn to communicate as effectively as face-to-face teams when developing intragroup relationships. This process will take longer for virtual project teams than for traditional teams because casual conversations are the basis for developing these relational ties (Zigurs). According to research by Zigurs (2003), groups establish frames of reference through unintended casual conversations occurring in face-to-face communications that help build trust within groups. Because virtual project teams usually do not share a common physical workspace, a leader must find a way to develop and maintain a sense of team identity (Aubert & Kelsey, 2003). Leaders create strong symbols uniting people 38 across distance and promise as much access for virtual project team members as available to colleagues located in the same building (Beranek & Martz, 2005). Virtual project teams, in contrast to traditional face-to-face teams, have two distinct hurdles when establishing the teams purpose. First, a cost is associated with getting the team to a position of being mature in team purpose. A certain amount of time is necessary for team members to become comfortable with the virtual teaming situation and to develop relationships with others on the team. Second, the purpose of the team has to serve as the glue keeping team members focused because team members are geographically dispersed, without a boss looking over workers shoulders (Bengt, 2005). One essential element for the success of a virtual project team is trust (Panteli & Duncan, 2004). Positive relationships established in traditional face-to-face teams are even more important in virtual project teams (Bock, 2003). In virtual teams, studies indicate early social exchanges promote trusting environments (Piccoli & Ives, 2003). Because trust relates to so many positive organizational characteristics, building a trusting environment for virtual employees is critical. Trust in any type of environment takes time to develop, and face-to-face communication may be a critical factor to building trust in a virtual environment (Piccoli & Ives). Furst et al. (2004) found trust in virtual environments was particularly difficult to establish (p. 14). Frequent communications appear to be essential in building trust in virtual teams. Building trust requires conscious and planned effort on the part of the virtual team leader because virtual team members do not have the traditional ways to meet each other and develop relationships. The lack of daily face-to-face time can heighten misunderstandings (Gareis, 2006). Virtual teams lack the social cues characterized by face-to-face communication. 39 Collaboration in any environment requires mutually agreed-upon dates and parallel work. In the virtual environment, schedules need to be coordinated. Team members need to determine when to get together, in what fashion, and what work to carry out in the interim between meetings (Lee-Kelley et al., 2004). The key is building trust in virtual project teams. Members of virtual project teams are not always from the same department or do not always work for the same company. Thus, traditional means of exerting influence may not be as effective. Virtual project teams need a clear statement of the teams purpose to keep functioning. Purpose sustains and initiates process and is the source of life for the virtual project team (Lee-Kelley et al., 2004). The leadership in virtual project teams tends to be informal and persuasive, as the leaders influence workers not seen on a daily or weekly basis, or even at all (Beranek & Martz, 2005). In some cases, the appointed team leader may have no direct reporting relationship with anyone on the team and team members could be from different organizations altogether. For this reason, at different points throughout the virtual project team life cycle, leadership may be shared among team members (Pearce & Conger, 2003). Virtual project teams earn a distinction as a new form of working due to the teams links. People connect via telephone, e-mail, videoconferencing, or specific software packages designed for virtual work. Roles take on more importance because face-to-face interaction is not available to clarify expectations. People in virtual project teams may play many different roles at different stages of the teams work life (Furst et al., 2004). More than one leader may be necessary to navigate a successful virtual project 40 team. Leaders in the virtual project team environment influence rather than force, and different people take the lead as circumstances require (Furst et al.). Managing the performance of virtual employees may not be easy. At best, the current state of the literature is conflicting. Some studies found virtual employees increased performance over traditional face-to-face employees (Gaeris, 2006; Gibson & Cohen, 2003), while others indicated a decrease in performance (Jarman, 2005; Kerber & Buono, 2004). Prior research indicates many managers are unsure about virtual environments and are hesitant to implement virtual teams (Sobel-Lojeski & Reilly, 2006). Virtual teams face many challenges not present in face-to-face teams due to the geographic dispersion. These challenges include building trust, navigating communication obstacles, and building team cohesiveness. Moreover, the nature of virtual teams diminishes social interaction (Burtha & Connaughton, 2004). Face-to-face interaction is the richest communication medium and allows for the availability of instant feedback and the use of multiple nonverbal cues, such as voice tone and inflection and body language. Bass (1990) reported managers and leaders find employees seem to be communicating differently when geographically separated. Bass (1990) noted isolated managers routinely do not interpret headquarters memos accurately. The lack of nonverbal cues available to virtual employees may result in the reduced quality of performance feedback, leading to lower quality relationships along with decreased job satisfaction and performance. Bass (1990) similarly remarked, Physical proximity and the availability of channels of communication increase interaction potential (p. 658). In a virtual team where the majority of communication is via e-mail, message meaning can become unclear. Bass (1990) proposed physical distance might neutralize 41 the effects of leader behaviors because of reduced social interaction. According to Lipnack and Stamps (1997), Virtual teams and networks demand more leadership, not less (p. 173). To be a successful virtual team leader requires a special set of skills (Bock, 2003). Successful virtual team leaders understand the fundamental principles of team output and accountability and do not let time and space alter those precepts. Virtual team leaders possess all the qualities of traditional face-to-face team leaders, plus an additional set of skills and competencies (Dube & Pare, 2004). Effective virtual team leaders know how to facilitate team-based processes: coordinating and collaborating across geographical and cultural boundaries via technology (Hogel & Proserpio, 2005). The use of teams of workers dispersed geographically will continue to change the way people work in groups and refine the nature of teamwork in the future (Zakaria et al., 2004). Conclusion The literature review revealed virtual employees and project teams are becoming more prevalent in organizations (Furst et al., 2004). However, the decision to have virtual project teams work at remote locations, away from project managers and organizational support structures, may impede primary leadership functions (Piccoli et al., 2004). There exists a gap in the literature pertaining to leadership aspects of virtual project teams. Expanding the research on virtual employees will help organizations meet the leadership challenges ahead (Burtha & Connaughton, 2004). The purpose of the current quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. The literature review identified three major leadership styles and revealed significant differences between the styles. However, the literature did not make conclusions 42 regarding which style might be more effective in a virtual environment. The current study may help close the gap. Summary Chapter 2 contained a review of the literature related to the research questions of the study. The intent of the presented information was to ground the study upon current research on the topics and to lend support for an investigation into what correlations exist among the variables of the study. To understand the concepts inherent in leading virtual project teams, the literature review included a review of three major leadership styles identified in the full-range leadership model developed by Bass and Avolio (2003). Other topics reviewed included methods for measuring project success, team leadership, and virtual project team leadership. Chapter 3 contains a detailed description of the methodology employed to gather and analyze data in sufficient detail to suggest recommendations to answer the research questions. 43 CHAPTER 3: METHOD The current quantitative correlational study involved an examination of the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual project teams. Additionally, the study sought to determine if a transformational, transactional, or laissez-faire leadership style is better suited for virtual project teams. The study employed a correlational approach and multiple regression analysis to determine the strength of the relationships between the two variables. Research Method and Design Appropriateness The research design is an elaboration of the Nature of the Study section from chapter 1 and logically derives from the Statement of the Problem and Purpose of the Study sections from chapter 1 (Simon & Francis, 2006). A need to describe and measure the degree of relationship between two or more variables resulted in the selection of a quantitative correlational design (Creswell, 2005). A quantitative research method, specifically correlation analysis, provided the group of statistical measures considered necessary to portray the relationships between the independent variable, leadership style, and the dependent variable, project success in virtual project teams (Leedy & Ormrod, 2005). Quantitative Research The aim of quantitative research is to collect numerical data and construct statistical models in an attempt to explain observations (Creswell, 2005). Researchers sometimes use questionnaires to collect data, which is efficient in testing hypotheses (Leedy & Ormrod, 2005). Quantitative research is objective and the research field 44 describes it as countable. Quantitative research involves asking specific, narrow questions to obtain measurable variables (Creswell). The use of a survey instrument to collect data from preset questions lends itself well to a quantitative method of measuring the variables (Neuman, 2006). Quantitative research differs from qualitative as quantitative seeks to systematically, factually, and accurately describe the facts and characteristics of a given population or area of interest (Neuman, 2006). Quantitative research uses detailed questions to obtain measurable and observable numerical data on variables (Creswell, 2005). Qualitative data collection is subjective because the data collected are in words, pictures, or objects (Neuman). The selection of a quantitative design is appropriate when variables of the study are clear (Creswell, 2005). When variables are unknown, a qualitative design may help identify what is import and what needs to be studied (Leedy & Ormrod, 2005). Qualitative research studies typically help describe, interpret, and validate certain assumptions or generalizations (Neuman, 2006). Because the variables for the study were clear, a quantitative design examined the relationship between the variables in to address the research questions. Quantitative research uses a language of variables and relationships among variables to investigate research questions. A variable, as opposed to a constant, can fluctuate or be expressed as more than one value (Simon & Francis, 2006). Quantitative designs have at least two types of variables: independent and dependent (Creswell, 2005). 45 Understanding variables is essential in analyzing the data collected. Distinguishing between dependent variables and independent variables is imperative (Creswell, 2005). An independent variable stands alone and is not changed by the other variables measured. Dependent variables are contingent on other factors. For example, a test score is a dependent variable because the score could differ depending on how much a person studied or slept the night before (Neuman, 2006). Quantitative descriptive research methodologies include correlations, observations, and surveys. Additional quantitative approaches include experimental and causal-comparative methodologies (Neuman, 2006). Each of these approaches yield information summarized with statistical analysis. For the purpose of the current study, a correlational research design simplified the data analysis process by looking only at the relationship between one dependent variable and one independent variable (Creswell, 2005). With the variables identified and distinguished, correlational research determines the degree of relationships (Leedy & Ormrod, 2005). Correlational Research Correlational research attempts to measure the correlations between variables to determine whether and to what degree a relationship exists (Neuman, 2006). If a significant relationship exists between two variables, it does not mean one variable causes the other. Correlation does not mean causation (Simon & Francis, 2006). When correlating two variables, predicting the value on one variable for a participant is possible if the participants value on the other variable is available. The investigator frequently reports the correlation coefficient and the p value to determine the strength of the relationship (Leedy & Ormrod, 2005). 46 Multiple Regression Analysis Multiple regression analysis uses correlation; however, regression allows a more sophisticated exploration of the interrelationships among a set of variables. The main use of multiple regression is to provide an estimate of the relative importance of the different independent variables in producing changes in the dependent variable (Leedy & Ormrod, 2005). The study involved the application of standard multiple regression. The four distinct types of quantitative research are descriptive, correlational, causal comparative, and experimental. A quantitative correlational design using multiple regression analysis was appropriate for the current study. The need to describe the relationship between two or more variables, without attributing the effect of one variable on another, made correlational research suitable for the study (Leedy & Ormrod, 2005). Correlational research uses multiple regression analysis to develop a mathematical equation to estimate the value of relationships among a number of independent variables (Creswell, 2005). Research Questions The research questions originated with the Statement of the Problem and Purpose of the Study sections from chapter 1 (Simon & Francis, 2006). Research questions translate the problem statement into specific areas for examination, leading to alternative hypotheses (Neuman, 2006). Two research questions guided the study: 1. How does the project managers leadership style correlate with project success in a virtual project environment? 2. Which leadership style correlates with a higher level of project success in a virtual project environment? 47 Hypotheses Hypotheses assert probable answers to research questions (Neuman, 2006). Hypotheses allow for a tentative prediction or expectation about the relationship between the variables and are either supported or not supported by the data (Leedy & Ormrod, 2005). Eight hypotheses guided the study: H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. 48 Population The specific population included certified project management professionals who reside in the Kansas City, Missouri metropolitan area, which includes 15 counties anchored by Kansas City, Missouri. The 15 counties are Johnson, Leavenworth, Franklin, Wyandotte, Miami, and Linn counties in Kansas and Jackson, Cass, Bates, Caldwell, Clay, Johnson, Lafayette, Plate, and Ray counties in Missouri. Although the entire target population reside in the Kansas City metropolitan area, many work for global organizations such as Sprint, Hallmark, Burns & McDonald, Garmin, Black & Veach, Cerner, and Honeywell where virtual project teams are used extensively. The Project Management Professional (PMP) certification is one of project managements most widely recognized professional credentials (PMI, 2008). To be eligible for the PMP credential, applicants must first meet specific educational and experience requirements (PMI, 2008). Table 1 provides the certification eligibility requirements for the PMP certification. Informed Consent An informed consent form for each study participant was included with each questionnaire distributed (see Appendix A). The informed consent form advised perspective participants that participation in the study was voluntary and return of the questionnaire would be considered consent to participate. All responses were confidential. In all cases, respondent identity was anonymous in all reporting of results. There were no anticipated risks to participants in the study. 49 Table 1 PMP Certification Eligibility Requirements Diploma or degree Experience Education or exam High school diploma or Associates degree Five years of professional project management experience with at least 7,500 hours of leading and directing project tasks 35 hours of formal project management education and a passing score on the PMP certification exam Bachelors degree Three years of professional project management experience during which at least 4,500 hours are spent leading and directing project tasks 35 hours of formal project management education and a passing score on the PMP certification exam Note. Project Management Institute (2008). Sampling Frame The form of sampling applicable to the study was convenience sampling because the participants were available to participate but not randomly selected (Neuman, 2006). Leedy and Ormrod (2005) suggested compensating for potential bias; therefore, researchers should select the largest sample possible. If the target population is less than 2,000, the survey should go to the entire population. The target population for the study included 500 PMP-certified project managers who reside in the Kansas City, Missouri, metropolitan area. Traditionally social science research projects use a level of 50 significance of .05 with a confidence level of .95 for quantitative correlational studies (Creswell, 2005). Ensuring a confidence level of .95 with a margin of error of .05, the recommended minimum sample size from a target population of 500 is 218 (Raosoft, 2008). Confidentiality Questionnaires were mailed directly to the entire population of certified project management professionals who reside in the Kansas City, Missouri metropolitan area. The questionnaires contained no respondent identification data. Respondents returned the anonymous questionnaires in an enclosed postage-paid envelope for coding and analysis. Instrumentation Quantitative data collection and data analysis require careful consideration of the survey instrument design. The primary goal is to ensure the survey, and the data collected with the survey, provide the intended measurement (Creswell, 2005). Meaningful conclusions should be attainable through the survey and data collection process if the study is to be worthwhile. The current quantitative study examined the relationship between leadership styles as measured by the MLQ (Bass et al., 2003) and project success in virtual project teams as measured by the PIP (Pinto & Slevin, 1988). An anonymous three-part survey, consisting of a series of questions pertaining to respondent demographics included in Appendix D, the PIP included in Appendix E, and the MLQ included in Appendix F, provided the necessary research data for each of the variables. The demographic instrument collected the data necessary to provide a number of descriptive statistics pertaining to the respondents project management experience, the scope and complexity of the project, and the project collaboration tools used to complete 51 the project. Researchers use descriptive statistics to describe raw data. Descriptive statistics include measures of central tendency such as the mean, median, and mode (Leedy & Ormrod, 2005). The PIP instrument provided a measurement of project success in a particular virtual project identified by the survey respondent. Few topics in project management are so rarely agreed upon as the notion of project success (Pinto & Slevin, 1988). Measuring project success often involves the consideration of only three factors: time, budget, and project performance. If a project comes in on time, is near budget, and performs as expected, the project is successful. Pinto and Slevin added an additional factor to the measurement of success: accounting for the satisfaction and welfare of the client. The client is any party the project is for, either internal or external to the organization. The Pinto and Slevin model of project success includes budget, schedule, performance, and client satisfaction. The MLQ is a valuable tool in field and laboratory research to study transformational, transactional, and laissez-faire leadership styles. For the purpose of the study, the MLQ instrument sought to determine whether the project manager of a virtual project employed a transformational, transactional, or laissez-faire leadership style. The MLQ contains 45 items identifying and measuring key leadership and effectiveness behaviors shown in prior research to be strongly linked with both individual and organizational success. The MLQ scores can help to account for the varying impact different types of leaders have on their associates, teams, and organizations (Avolio & Bass, 2004). 52 Data Collection The target population included 500 certified project management professionals who reside in the Kansas City, Missouri metropolitan area. The entire target population received an informed consent form (see Appendix A), a demographics questionnaire (see Appendix D), the PIP (see Appendix E), and the MLQ (see Appendix F) by way of direct mail. The mailing included a postage-paid return envelope for participants to return the completed anonymous questionnaires for data collection and analysis. To ensure confidentiality, the return envelopes and the questionnaires contained no respondent identification information. Participants names and addresses came from a combination of two public domain Web sites (KC Mid-America PMI Chapter, 2008; Whitepages, 2008). Data Analysis Analysis of the collected data relating to the research questions and hypotheses occurred through the application of the software programs Microsoft Excel and Statistical Package for Social Sciences (SPSS). Data tabulated from the MLQ determined the type of leadership style used by project managers in the sample. The MLQ assesses perceptions of leadership behaviors representing avoidance of responsibility and action known as laissez-faire leadership. The MLQ assesses perceptions of leadership performance effects known as transformational leadership. The MLQ is a validated form of 45 items used for organizational survey and research purposes (Avolio & Bass, 2004). The philosophy of the PIP indicates project management is a complex task requiring the project manager and team members to attend to a wide variety of factors in attempting to implement projects successfully (Pinto & Slevin, 1988). The PIP 53 questionnaires results show overall scores calculated on successful project indicators. In addition to the factors related to the technical, operational aspects of the project, managers must also consider the human side of managing the project and project team (Pinto & Slevin). Descriptive statistics provided an analysis tool for data collected from the demographics questionnaire to present a detailed description of the target population. Data collected from the MLQ and PIP was imported to the statistical software application SPSS to perform correlational and multiple regression analysis. SPSS can calculate two types of correlation: a simple bivariate correlation between two variables and a partial correlation to explore the relationship between two variables while controlling for another variable. SPSS also calculates the Pearson correlation coefficients (r) with values ranging from -1 to +1 and the Spearman rank correlation that presents a nonparametric alternative (Pallant, 2003). To answer Research Question 1 and test Hypothesis 1, a correlation of data from the most significant outcome of Hypothesis 2, 3, or 4 provided the necessary data. 1. How does the project managers leadership style correlate with project success in a virtual project environment? H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. 54 Hypotheses 2, 3, and 4 were tested using data from the MLQ and the PIP questionnaire results. Additionally, testing Hypotheses 2, 3, and 4 answered Research Question 2. 2. Which leadership style correlates with a higher level of project success in a virtual project environment? H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. Validity and Reliability Leedy and Ormrod (2005) identified a number of internal and external validity concerns for researchers conducting quantitative data collection and analysis. Issues of internal validity include selection bias, history effect, maturation, testing, and instrument validity. Internal validity is the extent to which accurate conclusions about relationships within the data are attainable. Issues of external validity include experimental realism, 55 mundane realism, the Hawthorne effect, and demand characteristics (Neuman, 2006). External validity is the extent to which results apply to situations beyond the study itself (Creswell, 2005). The study included participants from the same local chapter of a professional organization for project management professionals, which allowed the study to apply to a broader population of the organizations global membership of 260,000 members in 171 countries. Care was taken in the design of the survey instrument to be used in the study to avoid validity issues such as those outlined above. Multifactor Leadership Questionnaire The MLQ, based on the full-range leadership model developed by Bass and Avolio, is a short and comprehensive survey used extensively worldwide. The MLQ has excellent validity and reliability (Heintiz, Liepmann, & Felfe, 2005). The survey measures 45 items on a full range of leadership styles. In support of external validity, Avolio and Bass (2004) reported that during the period from 1995 to 2004, nearly 300 research programs, doctoral dissertations, and masters theses around the world used the MLQ to determine leadership style. Avolio and Bass (2004) contended the fundamental phenomenon of transformational leadership transcends organizations, cultures, and countries. By employing a hierarchical measurement of leadership behaviors or a full range of leadership, the MLQ shows reliability for different levels within an organization and for varying types of organizations, from civilian to military (Heintiz et al.). Reliability refers to the dependability of measure, meaning the measure can produce the same results repeatedly (Neuman, 2006). The consistency with which an instrument yields a certain result when the entity has not changed determines the reliability (Leedy & Ormrod, 2005). Avolio and Bass (2004) reported the following 56 reliability scores for the transformational behaviors measured by the MLQ: (a) idealized influence (attributed) = 0.70, (b) idealized influence (behaviors) = 0.64, (c) inspirational motivation = 0.76, (d) intellectual stimulation = 0.64, and (e) individual consideration = 0.62. Scores for transactional behaviors measured by the MLQ range from 0.60 to 0.79. According to Heintiz et al. (2005), several studies assess the validity and reliability of the 1999 version of the MLQ, upon which the current version of the MLQ is based and found the survey is psychometrically solid. Project Implementation Profile The Pinto and Slevin (1988) PIP is considered the best current measurement of project success in the field (Judgev & Muller, 2005). The PIP generalizes project success and includes two subscales: project and client. A project score, client score, and overall score relate to a database of 418 projects. Scores found to be below the 50th percentile indicate less than successful areas in the project (Pinto & Slevin, 1988). 57 Summary Chapter 3 contained a detailed description of the methodology employed to gather and analyze data in sufficient detail to suggest recommendations to answer the research questions (Neuman, 2006). Chapter 3 also contained a rationale for the appropriateness of a quantitative approach using a correlational design and multiple regression analysis (Creswell, 2005; Leedy & Ormand, 2005). A description of the target population, geographic location, and sampling frame provided some initial insight into the demographics of study participants. A review of the data collection and analysis process included details of survey instruments, obtaining informed consent, maintaining confidentiality, and ensuring validity and reliability. Chapter 4 contains the results of the study. 58 CHAPTER 4: RESULTS Chapter 4 presents a detailed analysis of surveys completed in September 2008 by 229 PMP-certified project managers who reside in the Kansas City, Missouri, metropolitan area. The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual projects. This chapter reports the results of the statistical analysis of the examined relationship. The first 21 figures present a preliminary analysis of demographic data. The primary data analysis presents the results from both a correlation and regression analysis. Two research questions and eight hypotheses statements guided the study. Research Questions 1. How does the project managers leadership style correlate with project success in a virtual project environment? 2. Which leadership style correlates with a higher level of project success in a virtual project environment? Hypotheses H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. 59 HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. Data Collection and Coding The target population for the study included 500 PMP-certified project managers who reside in the Kansas City, Missouri, metropolitan area. The entire target population of 500 project management professionals received an informed consent form (see Appendix A), a demographics questionnaire (see Appendix D), the PIP (see Appendix E), and the MLQ (see Appendix F) by way of direct mail. The mailing included a postagepaid return envelope for participants to return the completed anonymous questionnaires for data collection and analysis. The sample included all 229 respondents from the target population of 500 project management professionals. The response rate was consistent with the 218 responses needed to ensure a confidence level of .95 with a margin of error of .05 (Raosoft, 2008). The aim of quantitative research is to collect numerical data and construct statistical models in an attempt to explain observations (Creswell, 2005). Because the 60 variables for the study were clear, a quantitative design examined the relationship between the variables in to address the research questions. Data collected from a three-part questionnaire provided input into the spreadsheet software application Microsoft Excel that was imported into the statistical software application SPSS to perform correlational and multiple regression analyses. The questionnaire codebook (see Appendix G) outlines the coding method for data entry. Coding is the process of assigning numbers to responses collected in the completed questionnaires (Newton & Rudestam, 1999). Findings Organizing findings by a common structure related to the research questions or hypotheses provided an understanding of the data collected (Leedy & Ormrod, 2005). A two-step analysis process provided the results necessary to determine findings and make conclusions. First, respondent data from the demographic questionnaire (see Appendix D) provided a detailed description of the sample. Second, analysis of data from the PIP (see Appendix D) and the MLQ (see Appendix F) provided the primary research data needed to test the hypotheses. Description of Sample The sample included all 229 respondents from the target population of 500 project management professionals. Part one of a three-part questionnaire (see Appendix D) collected demographic information to describe personal and project characteristics of the sample. Personal information included the respondents gender, age, PMP certification date, project management experience, virtual project experience, and education level. To keep the study anonymous, the questionnaire did not include respondents personal 61 identification data. Project information included the scope and complexity of the project and the project collaboration tools used to complete the project. All 229 respondents were certified project management professionals and currently involved in virtual projects. Over 94% of the respondents had 6 or more years of project management experience, including virtual project experience, and 96% of respondents had bachelors degrees or higher. Figures 1 through 21 contain respondent results to the demographic questionnaire. Figure 1 reveals near equal distribution between male and female respondents. Approximately 52% of the respondents were male, and 48% female. The results are consistent with the overall gender distribution of certified project management professionals globally (Project Management Institute, 2008). 109 120 0 50 100 150 200 Female Male Gender Number of Responses Figure 1. Gender of respondents. The median age range of respondents was 31 to 50 years as shown in Figure 2. Based upon project management professional education and experience certification requirements outlined in Table 1, the results are not surprising. To attain the required education and experience levels for certification, project managers are likely to be 30 years or older at time of certification (Project Management Institute, 2008). 62 52 85 84 8 0 0 50 100 150 200 >50 41 – 50 31 – 40 26 – 30 20 -25 Age Range Number of Responses Figure 2. Age range of respondents. Figure 3 reflects a wide range of respondent PMP certification dates occurring over the past eight years. A combination of project management experience and education is necessary for PMP certification as outlined in Table 1. The wide range of certification dates is indicative of the varying points at which project managers meet PMP certification requirements. 14 14 32 50 26 24 21 26 13 9 0 50 100 150 200 2008 2007 2006 2005 2004 2003 2002 2001 2000 <2000 Year PMP Earned Number of Responses Figure 3. Year PMP certification earned. 63 The median range of years of project management experience of respondents is 6 to 15 years as shown in Figure 4. Based upon project management professional experience certification requirements outlined in Table 1, the results are not surprising. To attain the required experience levels for certification, project managers are likely to have five or more years of project management experience (Project Management Institute, 2008). 19 38 74 85 12 1 0 50 100 150 200 >20 16 – 20 11 – 15 6 – 10 1 – 5 <1 Years of PM Experience Number of Responses Figure 4. Number years of project management experience. The number of virtual project teams is increasing (Anu, 2006). Furst et al. (2004) reported as many as 13 million employees in the United States are members of one or more virtual project teams. All respondents reported at least one or more years of virtual project team experience with the median range being 6 to 10 years as reflected in Figure 5. 64 8 7 44 102 64 4 0 50 100 150 200 >20 16 – 20 11 – 15 6 – 10 1 – 5 <1 Years of Virtual Project Experience Number of Responses Figure 5. Number years of virtual project experience. The majority of respondents reported holding a Bachelors degree or higher as shown in Figure 6. Based upon project management professional education certification requirements outlined in Table 1, the results are not surprising. To attain the required education level for certification, project managers are likely to have a Bachelors degree or higher (Project Management Institute, 2008). 1 66 153 7 2 0 50 100 150 200 Doctorate Masters Bachelors Associates High School Education Level Number of Responses Figure 6. Highest education level achieved. Figure 7 shows a high percentage of respondents work in the Telecom and Information Technology (IT) industries. The Kansas City metropolitan area is home to the corporate headquarters of major Telecom and IT companies such as Sprint and DST 65 Systems. The results shown in Figure 7 are not surprising based upon the large number of respondents employed at local Telecom and IT companies. 39 22 95 73 0 50 100 150 200 Other IT Industry Number of Responses Figure 7. Industry of employment. Approximately 80% of respondents worked on virtual projects on a national of global level. The results shown in Figure 8 are not surprising based upon the large number of respondents employed by global Telecom and IT companies. The industries of employment reported in Figure 7 are also an indication of the national and global nature of project geographical scope. 83 101 45 0 50 100 150 200 Global National Regional Project Scope Number of Responses Figure 8. Project geographical scope. Figure 9 shows a median project team size of 6 to 15. The Project Management Institute (2004) describes the preferred project team size to be in the 6 to 15 range. While 66 a significant number of respondents reported team sizes of 15 or larger, the median team size of respondents is not surprising. 83 101 45 0 50 100 150 200 >15 6 – 15 <6 Size of Team Number of Responses Figure 9. Size of project team. The length of a project is largely dependent upon the scope of the project (Project Management Institute (2004). Approximately 80% of respondents worked on virtual projects on a national of global level. The results shown in Figure 10 are not surprising based upon the national and global scope reflected in Figure 8. 152 63 14 0 50 100 150 200 >12 Months 6 – 12 Months <6 Months Project Schedule Number of Responses Figure 10. Length of project. The project budget is largely dependent upon the scope of the project (Project Management Institute (2004). Approximately 80% of respondents worked on virtual 67 projects on a national of global level. The results shown in Figure 11 are not surprising based upon the national and global scope reflected in Figure 8. 132 63 25 9 0 50 100 150 200 >$500,000 $251, 000 – $500,000 $100,000 – $250,000 <$100,000 Project Budget Number of Responses Figure 11. Size of project budget. The number of virtual project teams is increasing (Anu, 2006). Furst et al. (2004) reported as many as 13 million employees in the United States are members of one or more virtual project teams. The time differences reflected in Figure 12 are indicative of virtual projects. 39 18 133 39 0 50 100 150 200 >9 Hours 4 – 9 Hours <4 Hours No Difference Time Difference Number of Responses Figure 12. Time difference between team members. Projects may be internal and involve only one organization, however some projects include external team members from partner organizations, suppliers, or other project stakeholders (Project Management Institute, 2004). Figure 13 reflects the number 68 of organizations involved in virtual projects managed by respondents. More than half include team members from two or more organizations. 121 108 0 50 100 150 200 Two or More Organizations One Organization Number of Organizations Represented Number of Responses Figure 13. Number of firms or organizations represented. Figures 14 through 21 address the virtual nature of projects managed by respondents. The frequency of use of a variety of electronic communication tools by team members gives an indication of methods used to overcome the lack of face-to-face communication in virtual projects. A virtual project team brings together a group of geographically dispersed workers through information and communication technologies (Cromb, 2005). Virtual project teams meet through conference calls, video conferences, e-mail, or other communication tools such as application sharing (Anu, 2006). 1 8 13 114 93 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use Video Conferencing Number of Responses 69 Figure 14. Frequency of video conferencing. 183 41 4 1 0 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use email Number of Responses Figure 15. Frequency of e-mail communication. 30 149 36 12 2 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use Voicemail Number of Responses Figure 16. Frequency of voice mail communication. 55 155 13 6 0 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use Telephone Number of Responses Figure 17. Frequency of telephone communication. 70 17 106 78 26 2 0 50 100 150 200 Use web-based Internet Almost Always Seldom Tools Number of Responses Figure 18. Frequency of using Web-based Internet tools. 42 142 40 4 1 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use Conference Calling Number of Responses Figure 19. Frequency of using conference calling. 42 142 40 4 1 0 50 100 150 200 Almost Always Seldom Use Electronic Meeting Systems Number of Responses Figure 20. Frequency of using electronic meeting systems. 71 26 98 74 15 16 0 50 100 150 200 Almost Always Frequently Moderately Seldom Never Use Instant Messaging Number of Responses Figure 21. Frequency of using instant messaging. Data Analysis The aim of the data analysis was to test for a correlation between the independent variable, leadership style, and the dependent variable, project success in virtual projects. Five-step hypothesis testing provided the means for testing the hypotheses of the study. Hypothesis testing determined the statistical significance of the correlation and answered the research questions posed in this study. Step 1. Step 1 was to restate the alternate and null hypotheses. The aim of the study was to test hypotheses of correlation and relationship. The null being the present condition was used for statistical testing (Pallant, 2003). H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. 72 HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. Step 2. Step 2 was to determine the level of significance. The significance level for the study was .05. The amount of risk the researcher is likely to accept, and the effect this choice has on risk, largely determines the significance level. The larger the , the lower the (Pallant, 2003). Step 3. Step 3 was to determine the appropriate test based on the sample, population, and type of measurement scale. A standard multiple regression was applied to the three categories of the independent variable and one dependent variable completing one model to test the following: H0: Each of the betas of the model is zero. H2: At least one of the betas of the model is not zero (Pallant, 2003). Step 4. Step 4 involved formulating the decision rule, or the condition in which the null hypothesis would be rejected if a numerical value was applied to the significance level (Pallant, 2003). A correlation without a zero value is significant; however, the 73 strength of the correlation supports the strength of the correlation of the variables. In addition, by inspecting the Mahalanobis distances produced by the multiple regression programs, an identification of outliers is possible. The Mahalanobis distance takes into account the covariance among the variables in calculating distances (Pallant, 2003). Step 5. Step 5 involved conducting the statistical test selected in Step 3. The results of the test note the outcome of the study. At this point, the null hypotheses were rejected or not rejected. Data Analysis of the Regression The regression of the three categories of the independent variable provided a comparison to observe which one or more of the results would indicate how well the data set is able to evaluate the hypotheses. Table 2 presents the description and the data set of the output. 74 Table 2 Description of Variables Name Type Width Decimals Label Align Measure 1 project Numeric 11 0 Project performance Right Ordinal 2 transfor Numeric 11 2 Transformational Right Scale 3 transact Numeric 11 3 Transactional Right Scale 4 laissez Numeric 11 3 Laissez-faire Right Scale Descriptive Statistics Descriptive statistics provided in Table 3 describe the sample in a measure of central tendency using the mean and a measure of variability using the standard deviation (Creswell, 2005). While the total sample size was 229, the smaller subset of 121 used in Tables 4 through 11, and in Figures 22 and 23, identifies respondents who scored in the 67 to 84 range on the PIP (see Appendix E). Pinto and Slevin (1988) established a range of 67 to 84 on the PIP to define project performance as good. The highest possible score on the PIP is 84. Scores of 42 to 66 reflected fair performance and scores of 41 or below reflected poor or critical performance. For the purpose of this study, respondents who scored in the 67 to 84 range on the PIP were considered to have managed successful projects. The MLQ (see Appendix F) used a range of 0 to 4 to rate the three leadership styles. Table 3 provides the mean and the standard deviation for respondent PIP and MLQ scores. 75 Table 3 Descriptive Statistics (N = 121) Mean Standard deviation Project performance 74.12 4.988 Transformational 3.39 .431 Transactional 2.48864 .678348 Laissez-faire .63843 .404017 Multiple Regression Model A regression is the prediction of a dependent variable from an independent variable (Newton & Rudestam, 1999). A linear model or straight line, where the line describing the data is the method of least squares, determines the outcome (Pallant, 2003). Multiple regression describes how much of the variance in the dependent variable is contingent upon the independent variable (Pallant). A multiple regression develops a self-weighting estimating equation to predict values (Creswell, 2005). A descriptive application of this type of regression shows controlling confounding variables and evaluates the effect of other variables. In addition, path analysis, a form of multiple regression, is used to describe an entire structure of linkages that can advance from a casual theory. Not only can multiple regression be used as a descriptive tool, but is also used as an inference tool testing hypotheses and estimating population values (Creswell). The main purpose of multiple regression is to provide an estimate of the relative significance of the independent variable in producing changes in the dependent variable (Leedy & Ormrod, 2005). Multiple regression employs three major analytic strategies: 76 standard multiple regression, sequential regression, and statistical regression (Pallant). The current study applied multiple regression to the three categories of the independent variable and one dependent variable. Lines of best fit, used in any formal research method, use a linear regression (Leedy & Ormrod, 2005). This involves finding the line of the squared deviation of individual points from a line of the vertical Y axis. Therefore, using the data normally distributed with no problematic outliers is the preferable method of obtaining a line of best fit. The equation for this is Y = bX + a, where Y and X are the two variables. However, if there is more than one independent variable, multiple regression can be used where Y is the dependent variable, X1 and X2 are the two independent variables, a is the intercept, and b1 and b2 are the regression coefficients for the two independent variables. The equation is Y = a + b1X1 + b2X2 (Pallant, 2003). Not only can a line of best fit be used, but multiple regression provides prediction through substitutions of different values of X1 and X2 (Leedy & Ormrod, 2005). The slope and the intercept of the line define the lines with the residual term being the difference between the score of the line and the actual score. The method of least squares is plotting the lines to show the least difference between the observed data and the data line. Converting the regression coefficients allows for the different scales on which the data are measured. Standardized regression coefficients or beta weights tell the number of standard deviations the dependent variable will change for a unit change in the independent variable (Pallant, 2003). The differences, either positive or negative, are the residuals. The variances are the differences, both positive and negative, that might cancel each other out. The 77 goodness of fit compared to the sum of the squares is the regression line. The process continues by fitting the actual data to the assessment, thus the deviation from the outcome of the regression. In prediction, using the mean is typical, although the sum of the squares shows the difference between the mean and the outcome variable. The sum could be larger or smaller than the mean. R-squared is the expression for this value and thus the amount of variance from the mean. The Pearson correlation coefficient is the fit of the regression mode. The F-test of the sums of squares shows the ratios of improvement based on the model (Pallant, 2003). Assumptions of Multicollinearity Data According to Leedy and Ormrod (2005), confirming the independent variables demonstrate at least some relation with the dependent variable, above a .3 is preferred, and checked that the correlation is not too high, not above .7. If the correlation is not within this range, omitting one of the variables or forming composite variables from the scores of the two highly correlated variables might be in . The Pearson correlation in Table 4 shows project performance falls within these limits. 78 Table 4 Correlations (N = 121) Project performance Transformational Transactional Laissezfaire Pearson correlation Project performance 1.000 .282 -.049 -.144 Transformational .282 1.000 .069 -.571 Transactional -.049 .069 1.000 -.036 Laissez-faire -.144 -.571 -.036 1.000 Sig. (1-tailed) Project performance . .001 .297 .058 Transformational .001 . .225 .000 Transactional .297 .225 . .346 Laissez-faire .058 .000 .346 . The equation of the regression model shown in Table 5 provides an assumed difference of Y from the conditional mean represented by a random error. The coefficients are represented by Y=o + 1X1+ 2X2+ 2X3+ (Pallant, 2003). Within Table 5, the transformational leadership style ranks one, two, and three with an adjusted R2 of .072 and a R2 of .080 showing a p value of .0017. The difference of the adjusted R2 ranking is less than .011 (.072 to .061), with a difference of coefficient of determination less than -.005 (.072 to.085). The standard errors of the estimates are less than -.973 (4.832 to 4.805). The conclusion can thus be made the transformational leadership style has a significant effect on project success in virtual projects. 79 Table 5 Regression Analysis: All Possible Regressions (p Values for the Coefficients) Nvar Transformational Transactional Laissezfaire s Adj. R2 R2 Cp p value 1 .0017 4.805 .072 .080 0.662 .0017 2 .0015 .4377 4.813 .069 .084 2.061 .0055 2 .0066 .8078 4.824 .065 .080 2.603 .0072 3 .0059 .4390 .8059 4.832 .061 .085 4.000 .0152 1 .1163 4.957 .012 .021 8.227 .1163 2 .5531 .1127 4.970 .007 .024 9.853 .2455 1 .5947 5.003 .000 .002 10.556 .5947 Table 6 provides a series of nonparametric correlations as an alternative to the correlations provided in Table 4. Many behavioral indicators are not normally distributed and nonparametric tests do not require variables to be normally distributed. Thus, nonparametric tests are also termed distribution-free tests (Newton & Rudestam, 1999). 80 Table 6 Nonparametric Correlations (N = 121) Project performance Transformational Transactional Laissez-faire Kendalls tau_b Project performance Correlation coefficient 1.000 .209** .031 -.152* Sig. (1-tailed) . .001 .322 .011 Transformational Correlation coefficient .209** 1.000 .075 -.464** Sig. (1-tailed) .001 . .126 .000 Transactional Correlation coefficient .031 .075 1.000 .034 Sig. (1-tailed) .322 .126 . .309 Laissez-faire Correlation coefficient -.152* -.464** .034 1.000 Sig. (1-tailed) .000 .000 .376 .000 81 Table 6 (continued) Project performance Transformational Transactional Laissez-faire Spearmans rho Project performance Correlation coefficient 1.000 .291** .049 -.207* Sig. (1-tailed) . .001 .298 .011 Transformational Correlation coefficient .291** 1.000 .115 -.608** Sig. (1-tailed) .001 . .105 .000 Transactional Correlation coefficient .049 .115 1.000 .046 Sig. (1-tailed) .298 .105 . .309 Laissez-faire Correlation coefficient -.207* -.608** .046 1.000 Sig. (1-tailed) .011 .000 .309 . *Correlation is significant at the .05 level (1-tailed). **Correlation is significant at the .01 level (1-tailed). The outliersnormality, linearity, homoscedasticity, and independence of residuals assumptioncan be checked by inspecting the residual scatter plot and the normal probability plot. In the normal probability plot, the point will lie in a reasonably straight diagonal line from left to right, bottom to top (Pallant, 2003). As seen in Figure 22, the points are to some extent in a straight line. 82 Normal P-P Plot of Regression Standardized Dependent Variable: Project Performance Observed Cum Prob 0.00 .25 .50 .75 1.00 Expected Cum Prob 1.00 .75 .50 .25 0.00 Figure 22. Normal P-P plot of regression standardized residual. Figure 23 identifies outliers, cases with value well above or well below the majority of other cases. The scatter plot depicts cases that have standardized residual of more than 3.3 or less than 3.33. As noted in Table 7, these standardized residuals have a minimum of -1.516 and a maximum of 2.332 that fall within the limits suggested by the residual scatter plot (Leedy & Ormrod, 2005). 83 Scatterplot Dependent Variable: Project Performance Regression Standardized Predicted Value -3 -2 -1 0 1 2 Project Performance 90 80 70 60 Figure 23. Scatter plot. Table 7 Residuals Statistics (N = 121) Minimum Maximum Mean Std. deviation Predicted value 70.79 76.33 74.12 1.486 Residual -7.34 11.29 .00 4.761 Std. predicted value -2.244 1.482 .000 1.000 Std. residual -1.516 2.332 .000 .983 a Dependent variable: Project performance. Model Summary Table 8 shows an R-square factor .089 related to the project performance variable. This means the regression model explains the variance in project performance. In the model shown in Table 9, the significance level is .028, which is less than .05; thus the second null hypothesis is rejected. Thus, the conclusion reached is each of the betas of the model is not zero, showing a forecasting model with statistically significant variables 84 is possible. The analysis of variance (ANOVA) in Table 9 also tests the statistical significance and null hypothesis. The ANOVA test also reflected a significance level of .028. Table 10 provides the coefficients that describe the role of individual predictor variables in the regression analysis, including the standardized and unstandardized regression coefficients (Newton & Rudestam, 1999). Table 8 Model Summaryb Change statistics Model R R square Adjusted R square Std. error of the estimate R square change F change df1 df2 Sig. F change 1 .298a .089 .057 4.843 .089 2.825 4 116 .028 a Dependent variable: project performance. b Predictors: (constant), transformational, transactional, laissez-faire. Table 9 ANOVAb Model 1 Sum of squares df Mean square F Sig. Regression 264.957 4 66.239 2.825 .028a Residual 2720.183 116 23.450 Total 2985.140 120 a Dependent variable: project performance. b Predictors: (constant), transformational, transactional, laissez-faire. 85 Table 10 Coefficientsa Unstandardized coefficients Standardized coefficients 95% confidence interval for B Model 1 B Std. error Beta t Sig. Lower bound Upper bound (Constant) 68.822 5.034 12.479 .000 52.851 72.793 Transformational 2.378 2.034 .206 1.169 .245 -1.651 6.407 Transactional -.446 .659 -.061 -.676 .500 -1.751 .860 Laissez-faire .335 1.333 .027 .252 .802 -2.304 2.975 a Dependent variable: project performance. Research Questions and Acceptance or Rejection of Null Hypotheses The statistical analyses performed in Tables 3 through 10 and Figures 22 and 23 provided the findings necessary to answer the research questions based on the acceptance or rejection of the null hypotheses. 1. How does the project managers leadership style correlate with project success in a virtual project environment? 2. Which leadership style correlates with a higher level of project success in a virtual project environment? H01: The project managers leadership style does not correlate with project success in a virtual project environment. HA1: The project managers leadership style correlates with project success in a virtual project environment. 86 The Null Hypothesis H01 was rejected based on the identification of a general relationship trend between a project managers leadership style and project success (see Table 4). H02: A transformational leadership style does not correlate with a higher level of project success in a virtual project environment. HA2: A transformational leadership style correlates with a higher level of project success in a virtual project environment. Null Hypothesis H02 was rejected based on the correlation of .282, thus showing a strong correlation between a transformational leadership style and project success (see Table 4). H03: A transactional leadership style does not correlate with a higher level of project success in a virtual project environment. HA3: A transactional leadership style correlates with a higher level of project success in a virtual project environment. Null Hypothesis H03 was not rejected, based on the correlation of -.049, thus showing a negative correlation between a transactional leadership style and project success (see Table 4). H04: A laissez-faire leadership style does not correlate with a higher level of project success in a virtual project environment. HA4: A laissez-faire leadership style correlates with a higher level of project success in a virtual project environment. 87 Null Hypothesis H04 was not rejected, based on the correlation of -.144, thus showing a negative correlation between a laissez-faire leadership style and project success (see Table 4). Summary Chapter 4 included two sets of analyses and presented the findings of the study. The methodology outlined in chapter 3 was applied to the data, and the results were shown in tabular form. Two research questions and eight hypotheses statements guided the study. This chapter reported the results of the statistical analysis of the examined relationship. Figures 1 through 21 presented a preliminary data analysis of demographic data. The primary data analysis presented the results from both a correlation and a regression analysis. The primary data reflected a general correlation between leadership style and project success. More importantly, the primary data reflected a positive correlation between transformational leadership style and project success (see Table 4). Chapter 5 uses the findings from chapter 4 to reach conclusions, develop implications, and develop recommendations for further study. 88 CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS The purpose of the current quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual projects. A three-part survey consisting of a series of questions pertaining to respondent demographics (see Appendix D), the PIP (see Appendix E), and the MLQ (see Appendix F) formed the basis for the data reported. Chapter 5 uses the findings from chapter 4 to reach conclusions, develop implications, and develop recommendations for further study. Conclusions Evidence presented in chapter 4 shows a statistically significant relationship exists between leadership style, specifically transformational leadership, and project success in virtual projects. The statistical analyses provided in Tables 3 through 10 identify transformational leadership style as the dominant and effective style in virtual projects. The primary data reflect a positive correlation between transformational leadership style and project success (see Table 4). Based on the nature of virtual project teams, status cues are harder to read (Reilly et al., 2005). Some traits attributed to transformational leaders, such as charisma and vision, may not translate well to a virtual project team setting. With more individuals working in physically displaced virtual settings, less opportunity exists for nonverbal cues expressed through body language, dress, and demeanor to promote clear communication (Bock, 2003). Because the virtual project environment may restrict many transformational leadership traits, the conclusion that a transactional leadership style might be more 89 effective is understandable. One reason for the statistical analyses pointing to transformational leadership as being more effective is the possibility transformational leaders are more capable of employing a situational leadership approach when needed. Often in a virtual project environment, a transactional approach is appropriate to ensure task completion (Shatz, 2006). A transformational leader is more likely to be flexible based on the needs of the project (Bono & Anderson, 2005). The transactional leadership model limits innovation, personal growth, building a sense of team, and flexibility (Bass, 1990). Transformational leaders are those individuals who use the motives of followers to reach specific objectives (Burns, 1978). Burns proposed the leaderfollower interaction could be either transactional or transforming, where the motivation of the leaders and followers is raised (as cited in Reinhardt, 2004). Implications The findings from the current study are useful for organizations that have created, or plan to create, virtual project teams, particularly in the area of leadership style deployment. The future of any industry will include virtual project teams (Avolio & Yammarino, 2003). The conclusions reached may lead to practical leadership strategies and the development of a new leadership model for virtual project teams. Leaders can leverage the knowledge obtained from the study to improve virtual project team success using an appropriate leadership style. Recruiting and training virtual project team leaders can also improve based on the findings. The results indicate transformational leadership skills are associated with the success of virtual projects (see Table 4). The study was limited to individuals who agreed to participate voluntarily. Validity of the study was limited to the reliability of the instruments used and the 90 honesty and truthfulness of the respondents. The MLQ and PIP are validated instruments (Bass et al., 2003; Pinto & Slevin, 1988). Both instruments contain questions requiring subjective responses. Project managers responding to the survey instrument likely provided a subjective analysis of project success and leadership style (Leedy & Ormrod, 2005). Bias may be evident because project managers, in their own retrospections, may not have always accurately recalled the actual situations (Leedy & Ormrod, 2005). The passing of time may have added to the error of recall. Participants were invited to respond to the survey based on experience with a recent virtual project to lessen the effects of the passage of time and thus reduce the risk of memory failure. Recommendations for Further Study Recommendations for further research include replication of the study with a larger geographical target population and sample, examination of emergent leadership in virtual project teams, and the inclusion of additional project success variables, such as risk assessment competencies and communications effectiveness. The study was regional in scope because the target population was limited to PMP-certified project managers who reside in the Kansas City, Missouri, metropolitan area. Further study could replicate the methodology of the study in other parts of the country or world to see if similar results are attainable. The PMI is one of project managements most widely recognized professional organizations with more than 265,000 project professionals in over 170 countries (PMI, 2008). PMP-certified project managers in other countries may face cultural issues affecting leadership style not addressed in the current study. 91 The study did not address the distinction between assigned leaders and emergent leaders. Further study could examine the differences and similarities among the characteristics of transformational leaders and the characteristics of emergent leaders in virtual teams. The distinction between assigned leadership and emergent leadership is important. An assigned leader is an individual assigned to a position of leadership (Bass, 1990). Leadership based on occupying a position is assigned leadership (Northouse, 2004). An emergent leader has the same status as other team members initially, but gradually emerges as a leader through the acceptance of the team over time (Bass, 1990; Northouse). A model might develop identifying characteristics of emergent leaders in virtual project teams based on the characteristics of transformational leaders. The current study examined the relationship between leadership style and project success in virtual projects. Failed leadership is one of the leading causes of project failures (Piccoli et al., 2004). However, other variables, such as risk, technology, culture, and language may also contribute to project failures. Future studies should examine the impact of additional independent variables on project success. Summary The purpose of the quantitative correlational study was to examine the relationship between the independent variable, leadership style, and the dependent variable, project success in virtual projects. Interpretation of the research study findings revealed a statistically significant relationship exists between leadership style, specifically transformational leadership, and project success in virtual projects. The implications of the research study demonstrate the findings are critical for organizations that have created, or plan to create, virtual project teams. 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Zhang, S., Fjermestad, J., & Tremaine, M. (2005). Leadership styles in virtual team context: Limitations, solutions, and propositions. Proceedings of the 38th Hawaii International Conference on System Sciences. Retrieved December 12, 2007, from EBSCOhost database. Zigurs, I. (2003). Leadership in virtual teams: Oxymoron or opportunity? Organizational Dynamics, 31, 339-351. Retrieved March 1, 2007, from EBSCOhost database. 109 APPENDIX A: COPY OF INFORMED CONSENT FORM FOR PARTICIPANTS 18 YEARS OF AGE AND OLDER 110 Dear fellow PMP, I am a student at the University of Phoenix completing a Doctor of Business Administration degree and conducting a research study entitled Examining the Relationship between Leadership Style and Project Success in Virtual Projects. The purpose of the study is to determine how leadership style affects virtual project team success. Your voluntary participation involves completing the enclosed anonymous three-part questionnaire. The questionnaire asks you to answer questions about yourself, your experience with virtual projects, and your leadership style. A virtual project is any project consisting of team members distributed geographically. Virtual project team members could also be from different organizations, different cultures, or working in different time zones. However, the key is because of geographic dispersion, a virtual team has to rely on communications technologies like e-mail or chat rooms to achieve project goals. Participation in this study is voluntary and return of the anonymous questionnaire will be considered your consent to participate. All responses will be confidential and your identity anonymous in any reporting of results. There are no anticipated risks, compensation or other direct benefits to you as a participant in this study. However, there will be indirect benefits. In particular, you and other project management professionals may benefit from the studys conclusions. Thank you for your participation in this study, which may help to develop a new leadership model for virtual teams. Please return the completed three-part questionnaire in the enclosed postage paid envelope. If you have any questions concerning the study, please contact me at 913-909-9141. Sincerely, George Arnold, PMP 111 APPENDIX B: PERMISSION TO USE EXISTING SURVEY: PROJECT IMPLEMENTATION PROFILE 112 113 114 APPENDIX C: PERMISSION TO USE EXISTING SURVEY: MULTIFACTOR LEADERSHIP QUESTIONNAIRE 115 116 117 APPENDIX D: COPY OF SURVEY INSTRUMENT: DEMOGRAPHICS 118 119 120 APPENDIX E: COPY OF SURVEY INSTRUMENT: PROJECT IMPLEMENTATION PROFILE 121 122 APPENDIX F: COPY OF SURVEY INSTRUMENT: SAMPLE OF MULITFACTOR LEADERSHIP QUESTIONNAIRE 123 124 APPENDIX G: QUESTIONNAIRE CODEBOOK 125 Questionnaire / Question No. Description Coding MS Excel Cell No. Respondent ID No. Self-coding three digits A4 A232 A1 Gender 1=Male 2=Female 9=Missing value B4 B232 A2 Age 1=20-25 2=26-30 3=31-40 4=41-50 5=>50 C4 C232 A3 Year PMP certified Self-coding 9999=Missing value D4 D232 A4 PM experience 1=<1 2=1-5 3=6-10 4=11-15 5=16-20 6=>20 9=Missing value E4 E232 126 Questionnaire / Question No. Description Coding MS Excel Cell No. A5 Virtual project experience 1=<1 2=1-5 3=6-10 4=11-15 5=16-20 6=>20 9=Missing value F4 F232 A6 Education level 1=Associates 2=Bachelors 3=Masters 4=Doctorate 9=Missing value G4 G232 A7 Virtual project 1=Yes 2=No 9=Missing value H4 H232 A8 Industry 1=IT 2=Telecom 3=Manufacturing 4=Other 9=Missing value I4 I232 127 Questionnaire / Question No. Description Coding MS Excel Cell No. A9 Scope 1=Regional 2=National 3=Global 9=Missing value J4 J232 A10 Size of team 1=<6 2=6-15 3=>15 9=Missing value K4 K232 A11 Planned schedule 1=< 6 months 2=6-12 months 3=> 12 months 9=Missing value L4 L232 A12 Approximate budget 1=< $100, 000 2=$100,000-$250,000 3=$251,000-$500,000 4=> $500,000 9=Missing value M4 M232 128 Questionnaire / Question No. Description Coding MS Excel Cell No. A13 Time difference 1=No difference 2=< 4 hours 3=4-9 hours 4=> 9 hours 9=Missing value N4 N232 A14 No. of organizations 1=One 2=Two or more 9=Missing value O4 O232 A15 Use video conferencing 1=Never 2=Seldom 3=Moderately 4=Frequently 5=Almost always 9=Missing value P4 P232 A16 Use email Same as A15 Q4 Q232 A17 Use voice mail Same as A15 R4 R232 A18 Use telephone Same as A15 S4 S232 A19 Use web-based tools Same as A15 T4 T232 A20 Use conference calling Same as A15 U4 U232 129 Questionnaire / Question No. Description Coding MS Excel Cell No. A21 Use Electronic meeting systems Same as A15 V4 V232 A22 Use instant messaging Same as A15 W4 W232 B1 Project has / will come in on schedule 1=Strongly disagree 2=Disagree 3=Somewhat disagree 4=Neutral 5=Somewhat agree 6=Agree 7=Strongly agree 9=Missing value X4 X232 B2 Project has / will come in on budget Same as B1 Y4 Y232 B3 The project that has been developed works Same as B1 Z4 Z232 B4 Project seems to do the best job of solving problem Same as B1 AA4 AA232 130 Questionnaire / Question No. Description Coding MS Excel Cell No. B5 Results of project represent a definite improvement in performance Same as B1 AB4 AB232 B6 Project will be / is used by its intended client Same as B1 AC4 AC232 B7 Project will be used by important clients Same as B1 AD4 AD232 B8 Project will be readily accepted by its intended users Same as B1 AE4 AE232 B9 Satisfied with the process by which project was / is completed Same as B1 AF4 AF232 B10 Project has / will benefit intended users Same as B1 AG4 AG232 131 Questionnaire / Question No. Description Coding MS Excel Cell No. B11 Project has / will lead to improved decision making or performance for the clients Same as B1 AH4 AH232 B12 Project will have a positive impact on those who make use of it Same as B1 AI4 AI232 PIP Project Score Total B1-B5 Self-coding 99=Missing value AJ4 AJ232 PIP Client Score Total B6-B12 Self-coding 99=Missing value AK4 AK232 PIP Overall Score Total B1-B12 Self-coding 99=Missing value AL4 AL232 132 Questionnaire / Question No. Description Coding MS Excel Cell No. C1 Provide others with assistance 0=Not at all 1=Once in a while 2=Sometimes 3=Fairly often 4=Frequently, if not always 9=Missing value AM4 AM232 C2 Re-examine critical assumptions Same as C1 AN4 AN232 C3 Fail to interfere Same as C1 AO4 AO232 C4 Focus attention on mistakes Same as C1 AP4 AP232 C5 Avoid getting involved Same as C1 AQ4 AQ232 C6 Talk about my values Same as C1 AR4 AR232 C7 Absent when needed Same as C1 AS4 AS232 C8 Seek differing perspectives Same as C1 AT4 AT232 C9 Talk optimistically about the future Same as C1 AU4 AU232 C10 Instill pride in others Same as C1 AV4 AV232 133 Questionnaire / Question No. Description Coding MS Excel Cell No. C11 Discuss who is responsible Same as C1 AW4 AW232 C12 Wait for things to go wrong Same as C1 AX4 AX232 C13 Enthusiastic about what needs to be accomplished Same as C1 AY4 AY232 C14 Importance of strong sense of purpose Same as C1 AZ4 AZ232 C15 Spend time teaching and coaching Same as C1 BA4 BA232 C16 Expectations when goals achieved Same as C1 BB4 BB232 C17 Believer in If it aint broke, dont fix it Same as C1 BC4 BC232 C18 Go beyond self-interest for good of group Same as C1 BD4 BD232 C19 Treat other as individuals Same as C1 BE4 BE232 C20 Problems must be chronic before action taken Same as C1 BF4 BF232 C21 Build others respect Same as C1 BG4 BG232 134 Questionnaire / Question No. Description Coding MS Excel Cell No. C22 Concentrate full attention on mistakes Same as C1 BH4 BH232 C23 Consider moral and ethical consequences Same as C1 BI4 BI232 C24 Keep track of all mistakes Same as C1 BJ4 BJ232 C25 Display sense of power and confidence Same as C1 BK4 BK232 C26 Articulate compelling vision of the future Same as C1 BL4 BL232 C27 Direct attention toward failures Same as C1 BM4 BM232 C28 Avoid making decisions Same as C1 BN4 BN232 C29 Individuals have different needs from others Same as C1 BO4 BO232 C30 Look at problems from different angles Same as C1 BP4 BP232 C31 Help others develop strengths Same as C1 BQ4 BQ232 C32 Suggest new ways to complete assignments Same as C1 BR4 BR232 135 Questionnaire / Question No. Description Coding MS Excel Cell No. C33 Delay responding to urgent questions Same as C1 BS4 BS232 C34 Emphasize a collective sense of mission Same as C1 BT4 BT232 C35 Express satisfaction when expectations met Same as C1 BU4 BU232 C36 Express confidence goals will be achieved Same as C1 BV4 BV232 C37 Meet others job-related needs Same as C1 BW4 BW232 C38 Use leadership that is satisfactory Same as C1 BX4 BX232 C39 Get other to do more than expected Same as C1 BY4 BY232 C40 Effective in representing others to higher authority Same as C1 BZ4 BZ232 C41 Work with others in satisfactory way Same as C1 CA4 CA232 C42 Heighten others desire to succeed Same as C1 CB4 CB232 136 Questionnaire / Question No. Description Coding MS Excel Cell No. C43 Effective in meeting organizational requirements Same as C1 CC4 CC232 C44 Increase others willingness to try harder Same as C1 CD4 CD232 C45 Lead an effective group Same as C1 CE4 CE232 MLQ (IA) Idealized Influence (Attributed) (C10+C18+C21+C25) / 4 Self-coding 9=Missing value CF4 CF232 MLQ (IB) Idealized Influence (Behavior) (C6+C14+C23+C34) / 4 Self-coding 9=Missing value CG4 CG232 MLQ (IM) Inspirational Motivation (C9+C13+C26+C36) / 4 Self-coding 9=Missing value CH4 CH232 MLQ (IS) Intellectual Stimulation (C2+C8+C30+C32) / 4 Self-coding 9=Missing value CI4 CI232 137 Questionnaire / Question No. Description Coding MS Excel Cell No. MLQ (IC) Individualized Consideration (C15+C19+C29+C31) / 4 Self-coding 9=Missing value CJ4 CJ232 MLQ (CR) Contingent Reward (C1+C11+C16+C35) / 4 Self-coding 9=Missing value CK4 CK232 MLQ (MBEA) Management by Exception (Active) (C4+C22+C24+C27) / 4 Self-coding 9=Missing value CL4 CL232 MLQ (MBEP) Management by Exception (Passive) (C3+C12+C17+C20) / 4 Self-coding 9=Missing value CM4 CM232 MLQ (LF) Laissez-faire Leadership (C5+C7+C28+C33) / 4 Self-coding 9=Missing value CN4 CN232 MLQ Extra Effort (C39+C42+C44) / 3 Self-coding 9=Missing value CO4 CO232 MLQ Effectiveness (C37+C40+C43+C45) / 4 Self-coding 9=Missing value CP4 CP232 138 MLQ Satisfaction (C38+C41) / 2 Self-coding 9=Missing value CQ4 CQ232

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