THE RELATIONSHIP BETWEEN LEADERSHIP TRAITS AND EFFECTIVENESS AMONG THE PRIVATE, PUBLIC, AND NONPROFIT SECTORS
Ruth Ann Petroff
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF EDUCATION
August, 2015
Committee:
William K. Ingle, Committee Co-Chair
Patrick Pauken, Committee Co-Chair
Maureen Wilson, Graduate Faculty Representative
Lynn Bachelor
Michael Gillespie
Chris Willis
© 2015
Ruth Ann Petroff
All Rights Reserved iii ABSTRACT
William K. Ingle,Committee Co-Chair
Patrick Pauken, Committee Co-Chair
Leadership and its aspects have been studied for more than two centuries. There are a variety of definitions of leadership and leadership effectiveness. However, studies investigating how leadership and leader effectiveness differ by sector have been limited. This study explored three research questions: (1) are the traits of involvement, adaptability, consistency, and mission
related to ratings of leadership effectiveness; (2) are there significant differences in the traits
among the private, public, and nonprofit sectors; (3) are there significant differences in the
correlation between X and Y among the three sectors. The traits and ratings of leader
effectiveness were measured using the Denison Leadership Survey, a 360 multi-rater instrument
developed by Denison and Neal (1996). This study defined leader effectiveness as high ratings
of role modeling, relationship, communication, change agent and high performance.
Bivariate correlation was used to determine the relationship between each trait and leadership effectiveness ratings. Analysis of Variance (ANOVA) with post hoc tests examined the differences among the sectors for each trait. The correlation coefficients were transformed using Fisher’s Z for sector to sector comparison utilizing independent samples. The sample consisted of 7,570 respondents to the instrument.
Analysis supported a strong positive relationship between the traits and ratings of
leadership effectiveness. ANOVA with post hoc analysis indicated involvement and adaptability
traits significantly differed for the public vs. private sectors and the private vs. nonprofit sectors.
The consistency and mission traits significantly differed among the three sectors. Results were
mixed in the correlation coefficients between traits and effectiveness. Adaptability-effectiveness iv and mission-effectiveness were significantly different among all three sectors. However, consistency-effectiveness was different between the private and public sectors only.
The results of this study confirm that leadership traits and sector context play roles in leadership effectiveness. The implication is leadership theory and practice should not be treated in a generic manner, but should consider the sector as well as leadership traits. For leaders dealing with multiple stakeholders, adapting behaviors based on sector helps to form relationships, such as with board members. The results of this study also may also inform the designing of leadership development programs and leadership selection/promotion.
Enter text of Abstract. v
This manuscript is dedicated to:
My parents Peter B. Petroff, may God bless his soul, and Ruth A. Petroff. Without their love,
support and emphasis on education, this would not be possible.
This is also dedicated to:
My paternal grandparents Belcho and Kristina Petroff for their amazing courage to seek a new
life in a new country and a better life for their family.
And to my maternal grandparents Frank and Clara Morlock for raising two loving and caring
daughters with a strong sense of values that I possess today.
vi ACKNOWLEDGMENTS
This dissertation would not be possible without the encouragement, knowledge, support
and motivation from a number of people who worked to make this manuscript come to fruition
successfully.
First and foremost I cannot thank enough Dr. William K. (Kyle) Ingle. Dr. Ingle became
not only an advisor, but a valued mentor. Dr. Ingle provided guidance, not just for the purpose to
complete a dissertation, but for the completion of quality research with my career goals in mind.
Without Dr. Ingle’s positive support, motivation encouragement, and high level of rigor, I would
not have been able to complete this dissertation to the level I desired. Under Dr. Ingle’s
mentorship I became a published author of peer reviewed academic research, presented at
conferences and gained confidence in my abilities to enter a career in higher education.
My greatest appreciation and thanks to Dr. Michael Gillespie, my methodologist.
Without Dr. Gillespie’s help and recommendations, I would not have this research project at all.
It was Dr. Gillespie who was able to take my very broad and loose idea and turn it into a viable
research project. I am very grateful to Dr. Gillespie for his constructive and collaborative
approach. His experience with the data set and instrument and his strong research skills helped
me immeasurably through the statistical analysis which improved the robustness of my research.
I am also grateful for the collaboration between Dr. Ingle and Dr. Gillespie. Their ability
to work together on this project guaranteed my successful completion.
I would be remiss if I did not acknowledge and thank Dr. Patrick Pauken. Dr. Pauken
joined my dissertation committee as a co-chair just prior to defense. Without his willingness to take on the task of co-chair, this dissertation would not be defended. I am grateful for his passion to the leadership program and support of my dissertation. vii I am also very grateful to Dr. Lynn Bachelor (University of Toledo) for her willingness to serve on my dissertation committee. Her insight and experience in the public and nonprofit sectors was invaluable. I have known Dr. Bachelor for a number of years outside of academia and have found her to be not only intellectual, but a caring and supportive person, engaged in our community. Her feedback was greatly appreciated and provided additional rigor to my research.
Thank you to Dr. Lynda Dixon and Dr. Maureen Wilson, Graduate School
Representatives. During the proposal defense, Dr. Dixon provided constructive feedback along with affirmation of a worthy research topic. And, to Dr. Wilson for graciously stepping in during the final phases dissertation process and the dissertation defense. In addition, a special thank you to Dr. Chris Willis for stepping in as a committee member at almost the last moment. His input during my dissertation defense was valuable and welcome.
I also want to extend a thank you to the faculty during my studies in the Masters of
Organizational Leadership program at Lourdes University. It was during my Masters that I became interested in pursuing a doctorate degree. In particular I want to express my gratitude to
Dr. Stephen Ball and Dr. Patricia O’Connell for their support of my intellectual pursuits and personal growth and for being inspirations to me.
On a personal level I am ever so grateful to my parents, Peter and Ruth Petroff for their unconditional love and support. I am very blessed to have inherited my father’s love of knowledge, reading and education.
A special thank you to my dear friend Dr. Mariam Iskandarani for her encouragement during this process. We spent many an hour over good food discussing our dissertation frustrations, work, families, and solving the world’s problems.
I am very blessed with supportive friends who have encouraged me along the journey and believed in my success. And to my cohort mates who made me laugh, educated me in areas I was viii unfamiliar, shared frustrations and concerns and became like a family. I am especially grateful to
Dr. Michele Toth and Dr. Paul Soska for the compassion and caring when I needed it the most and their willingness to sit in an emergency room with me providing comfort and companionship. And I am thankful to Dr. Soska for the many hours of chats, rantings and venting. And for his encouragement to keep moving forward. ix
TABLE OF CONTENTS
Page
CHAPTER 1: INTRODUTION……………………………………..……………………… 1
Background of the Problem…………………………………………………………. 1
Rationale…………………………………………………………………………….. 4
Research Questions ...... …………………………………………. 5
Significance of the Study …………………………………………………………… 5
Definition of Terms...... …………………………………………. 7
Data Sources………………………………………………………………………… 8
Organization of the Study ...... …………………………………………. 9
CHAPTER 2: LITERATURE REVIEW…...... …….. 10
Organizational Leadership and Theory – Why Care? ………………………………. 10
Situational Leadership……………………………………………………… 15
Organizational Context ...... ………………………………. 15
Organizational Effectiveness ...... 18
Private Sector ...... 20
Public Sector ...... 21
Nonprofit Sector...... 24
Sector Comparison ...... 26
level 5 ...... 18
Assessing Leadership Effectiveness ...... ………………………………. 28
Perceptions of Effectiveness………………………………………………… 30
Multi-Source Feedback ...... 31 x
Outcomes ...... 31
Leadership Frameworks ...... ………………………………. 35
Denison Leadership Effectiveness Framework……………………………… 37
Leadership Traits ...... 38
Involvement ...... 39
Consistency ...... 40
Adaptability...... 41
Mission ...... 42
Effectiveness Constructs ...... ………………………………. 43
Overall Effectiveness ...... ……………………………… 43
Role Models ...... ……………………………… 45
Leadership Potential...... ……………………………… 45
Capability ...... ……………………………… 46
Developing Relationships ...... ……………………………… 46
Change Agent...... ……………………………… 47
Summary……………………………… ...... 47
CHAPTER 3: METHODOLOGY ...... ………………………. 52
Data Sources………………………………………………………………...... 52
Instrumentation………………………………………………………………………. 53
Validity and Reliability……………………………………………………. . 55
Research Design…………………………………………………...... 57
Data Analysis……………………………………………………...... 57
Summary…………………………………………………...... 59 xi
CHAPTER 4: RESULTS ...... ……………………………. 60
Overview………………………………………………………………...... 60
Data Screening………………………………………………………………………. 61
Descriptive Analysis…………………………………………………………………. 62
Demographics by Sector……………………………………………………. 63
Reliability Analysis ...... ………………………………………………….. 67
Inferential Statistics ...... ………………………………………………….. 69
Summary………………………………………………...... 80
CHAPTER 5: DISCUSSION, RECOMMENDATIONS, and CONCLUSIONS ...... 83
Introduction ...... ………………………………………………….. 83
Summary of the Study’s Purpose and Importance………………………………….. 83
Discussion of Findings ...... ………………………………………………….. 85
Traits and Ratings of Effectiveness…………………………………………. 85
Trait Differences Among Sectors……………………………………………. 87
Invlovement ...... 89
Consistency ...... 89
Adaptability...... 90
Mission ...... 91
Relationship between Traits and Effectiveness Sector Comparison ...... 92
Involvement-effectiveness ...... 94
Consistency-effectiveness ...... 95
Adaptability-effectiveness ...... 99
Mission-effectiveness ...... 100 xii
Implications for Leadership Practice………………………………………………. 102
Current Leadership Practice ...... …………. 103
Leadership Development ...... …………. 105
Leadership Selection ...... …………. 107
Limitations and Future Research………………………………………………...... 108
Limitations of the Study...... …………. 108
Future Research ...... …………. 110
Conclusions ...... 112
REFERENCES ...... 113
APPENDIX A: HSRB APPROVAL LETTER ...... 129
APPENDIX B: DENSION CONSULTING TERMS OF USE AND DATABASE
AGREEMENT ...... 133
APPENDIX C: DENISON LEADERSHIP DEVELOPMENT SURVEY
INSTRUMENT ...... 135
APPENDIX D: VISUAL INSPECTION OF MEANS FOR SKEWNESS AND KURTOSIS
……………………………………..………………………...... 138
APPENDIX E: DESCRIPTIVE STATISTICS OF TRAITS AND EFFECTIVENESS NOT
SEGREGATED BY SECTOR ...... ……………………… 140
APPENDIX F: SUMMARY OF CASE CHARACTERISTICS…………………………… 141
APPENDIX G: SUMMARY OF HOMOGENEITY TESTS ...... 143
APPENDIX H: RESULTS OF KRUSKAL-WALLIS TEST ...... 144 xiii
LIST OF TABLES
Table Page
1 Mainstream Leadership Theories ...... 11
2 Reliability Coefficients of Leadership Traits ...... 57
3 Variables and Analysis by Research Question ...... 58
4 Participant Characteristics by Sector ...... 64
5 Demographics Characteristics by Sector (Percentages) ...... 66
6 Descriptive Statistics of Traits and Effectiveness ...... 67
7 Descriptive Statistics of Traits and Effectiveness Segregated by Sector ...... 67
8 Reliability Coefficients of Leadership Traits and Effectiveness ...... 68
9 Variables and Analysis by Research Question ...... 69
10 Correlation Results Between Traits and Ratings of Effectiveness ...... 70
11 ANOVA Results for Traits ...... 74
12 Trait Means by Sector ...... 74
13 Fisher’s Z Test Values ...... 77
14 Correlations for Private Sector...... 79
15 Correlations for Public Sector ...... 80
16 Correlations for Nonprofit Sector ...... 80
17 Summary of Sector Significance with Post Hoc ...... 88
18 Summary of Trait-Effectiveness Significance by Sector ...... 94 xiv
LIST OF FIGURES
Figure Page
1 The Denison Model of Leadership Traits ...... 38
2 DLDS 360 Model ...... 55
3 Normal Distribution Curve with Critical Values ...... 77
1
CHAPTER 1: INTRODUCTION
Background of the Problem
Effective leaders have been described as transformational, relational, agents for change, empowering, and motivational (Bass, 1999, Burns, 1978; Kotter, 2007; Kouzes and Posner,
2002). Additionally, leadership theorists espouse that effective leaders have the ability to create a shared vision, promote organizational values, develop personnel, build consensus, and strike a balance between relationships and production (Bennis & Nanus, 1985; Blake & Mouton, 1975;
Blake & McCanse, 1991; Kouzes & Posner, 2002). Burns (1978) originally described leadership as transformational or transactional. Transactional leadership is an exchange between the leader and the employee in which the relationship satisfies each party’s self-interest (Bass, 2008; Burns,
1978). Transformational leaders are defined as leaders who create organizational cultures and values through hiring and personnel development, innovation, communication, and modeled behavior (Bennis & Nanus, 1985; Burns, 1978; Kouzes & Posner, 2002). It has also been argued that while effective leaders display certain traits and behaviors, it is the organization’s context, culture, and values that influence innovation, personnel development, and change (Jaskyte,
2004). Further, it is the existing norms, values, traditions, and culture of the organization that influence leadership style and effectiveness (Bennis, 2003; Bennis & Nanus, 1985; Bolman &
Deal, 2008; O’Toole, 2008). Additionally, the type of organization influences the effectiveness and behaviors of leaders. Leaders deemed effective in one organization may not be as successful and effective in an organization with a totally different culture and/or context (Bass & Avolio,
1993; Denison & Mishra, 1995; Yukl, 1981). For example, hierarchical and bureaucratic organizations require different leadership styles and behaviors from organizations that embrace 2
empowerment, innovation, and change (Baldwin, 1987; Bolman & Deal, 1991, 2008; Yukl,
1981).
Some have characterized the private sector as having a climate of innovation, constant change, and flexibility. The public sector has been described as hierarchical, inflexible, and inefficient (Baldwin, 1987; Burns, 1978; O’Toole & Meier, 1999; Rainey & Steinbauer, 1999;
Trottier, Van Wan Wart & Wang, 2008; Weber, 1922; Wilson, 1887). The nonprofit sector occupies the space in between, often receiving funding from government sources (complying with government mandates), and yet expected to be responsive and creative in delivering service and attracting funding in order to meet clientele needs (Morris, Combs, Schindehutte, & Allen,
2007). The implication is that different types of leaders with different characteristics and attributes may be needed for private, public, and nonprofit organizations (Farrow, Valenzi, &
Bass, 1980). Leadership theory and research have been criticized as being generic, disregarding organizational differences (Denhardt, 1984; Goulet & Frank, 2002; Rainey, 1979). Comparative literature has focused on differences in characteristics such as leadership style, motivation, and decision making (Anderson, 2010; Boyne, 2002; Denhardt, 1984; Haque, 1996; Harmon &
Mayer, 1986). Further, researchers have argued differences in organizational context, or sector, influence the behaviors of leaders within the organization (Anderson, 2010; Feeney & Rainey,
2010; Rainey, 1979; Rainey, 1983; Rainey, Backoff, & Levine, 1976; Rainey & Bozeman,
2000).
Theorists in public administration have argued that individuals enter the realm of public service willfully and purposefully often less focused on prestige and social status and more motivated by job context (Willem, De Vos, & Buelens, 2010). People without motivation to serve in the public sector will not do well (Appleby, 1945; Denhardt & Denhardt, 2006; Wright, 3
2007). Denhardt and Denhardt (2006) suggested that individuals choose careers such as teachers, police officers, firefighters, or social workers due to a strong commitment to serve in the public sector. They stated that:
What is most significant, and most valuable, about public administration is that we serve
citizens to advance the common good. Public administrators are responsible for
improving the public health, for maintaining public safety, for enhancing the quality of
our environment, and myriad other tasks. Ultimately, for them, for us, what really matters
is not how efficiently we have done our jobs, but how we have contributed to a better life
for all. (2006, p. 4)
This assumption asserts that individuals in the public sector need different characteristics to be effective than those in the private/business world, or that different types of people are attracted to the public and nonprofit sectors.
As Appleby (1945) indicated, individuals with more years working outside of government and achieving a certain level of success develop behaviors that make the person unfit to work in the government. Appleby stated that “It should be equally patent that men with excellent records in private business will not necessarily make competent government officials”
(p. 119). This theory indicates that as individuals move from private to nonprofit to public organizations, their leadership skills do not necessarily translate well. Contemporary empirical research has suggested that despite wage differentials, individuals enter the public sector because of higher job security and higher retirement pay (Borjas, 2002; Luechinger, Stutzer, &
Winkelmann, 2006; Pfeifer, 2011). Pfeifer (2011), in fact, found individuals who were more risk averse and wanted employment stability tended to work in the public sector. Similar to the public sector, those entering the nonprofit sector value quality of work, challenging and varied 4
work, and a passion for a mission (Johnson, 2009). However, unlike the public sector,
individuals preferring the nonprofit sector tended to have a greater capacity for status and social
presence, a greater need for power, and less need for security (Rawls, Ulrich, & Nelson, 1975).
Rationale
Historically, there has been little empirical research on the differences in leadership qualities between private industry, public, and nonprofit organizations. Much of the public administration discussion has been theoretical in nature and from public administration scholars.
Additionally, the discussions have centered on the differences between private and public or between the nonprofit and private sector, but not all three together. There has emerged empirical research focusing on the differences in the organizational cultures and purposes (Andersen,
2010; Bolman & Deal, 1991; Morris et al., 2007; O’Toole & Meier, 1999; Rainey & Steinbauer,
1999). The leader’s ability to motivate follower performance has also been an area of concentration (Shamir, House, & Arthur, 1993; Wager, 1965; Wright, 2007).
There have been a limited number of research studies comparing the sectors for leadership effectiveness and multiple traits among the sectors. Baldwin (1987) focused on the differences in relation to personnel management and identified three main differences: goal clarity, leadership turnover, and job security. Hooijberg and Choi (2001) compared only the private and public sector for leadership effectiveness and specific roles as defined in the competing values framework. Research examining how and/or if the leadership traits are related to leadership effectiveness and whether there may be differences among the organization types has been limited.
The purpose of this study was to examine the relationship of four leadership traits from the Denison Leadership Development Survey (DLDS) with seven items measuring leadership 5
effectiveness. The Denison (1996) framework emphasizes four main leadership traits that were
examined in this study: involvement, consistency, adaptability, and mission. Additionally, this
study investigated if differences exist in the relationships of the traits and ratings of leadership
effectiveness among the sectors. The model measures leader effectiveness in ratings of overall
effectiveness, ability to be a role model, leadership potential, capability, ability to develop
relationships and being a change agent. Additionally, the data from DLDS have participants from
the private, public and nonprofit sectors and includes the sectors as a variable. The Denison
framework provides a viable comparative model across sectors.
Research Questions
This study seeks to address the following questions:
1. Are the leadership traits of adaptability, mission, consistency, and involvement significantly related to leadership effectiveness ratings?
2. Do leadership traits of adaptability, mission, consistency, and involvement significantly differ by sector?
3. Do the correlation coefficients of leadership traits with leadership effectiveness significantly differ by sector?
Significance of Study
The results of this study may have implications for the development and design of leadership programs for existing employees. If specific traits are related to leadership effectiveness within sector groups, leadership development programs can focus on the specific traits related to leadership effectiveness within that sector. This may be especially useful for development of individuals migrating from one sector group to another. Results from this study may also be utilized by hiring managers and human resource managers within the different 6 groups to develop interview questions focused on leadership traits, thus improving the match between applicants and positions. This study also provided empirical research for those studying leadership effectiveness and leadership traits in the private, public, and nonprofit organizations.
As noted in Chapter 2, empirical research studies, while growing, have been limited in regards to effectiveness leadership of various characteristics in the public versus nonprofit sectors. The deficit is even more pronounced in research comparing all three sectors together. While there is a considerable level of research investigating differences between two sectors at a time – most notably private and public sector comparisons – the research predominantly differentiates between organizational and management structures, rather than measuring the effects of culture and structure on leadership.
In times of economic downturn, there is compression in the employment market and individuals often need to change career paths. During high levels of employment, organizations and individuals have the luxury of job sorting to find the best match for both parties. However, during times of low employment, individuals may not have the full benefit of sorting, while organizations with openings are looking for the best fit. Therefore, the best match between organization and individual may not take place. For example, an experienced manager downsized from the private sector may consider working as a director of nonprofit agency, even though the pay level is considerably lower. The agency may feel fortunate to gain an individual with a high level of management and leadership experience. However, the individual may find it difficult to answer to multiple stakeholders, constantly worry about funding, and/or may not be committed to the agency’s mission. Once a more acceptable position in the private sector is available, the individual leaves the agency, creating turnover and inconsistency within the agency. Alternatively, the individual enters the public sector for a higher level of job security 7
only to find the bureaucratic processes intolerable. From a leadership perspective, the individual
may have been a very effective leader in the private sector, but as a leader in a nonprofit or
public organization may be perceived as very ineffective because the traits that made the
individual effective in the private sector do not translate as effective in another sector. If
differences in leadership traits and perceptions of leader effectiveness exist between the sectors,
this study sought to identify how the traits relate to items of leader effectiveness.
Definition of Terms
The following definitions were used for this study. The definitions utilized indicate the
meaning of the terms in relation to the context of this study.
360 - Degree Survey Instrument (360): A type of survey that links individuals’ skills/behaviors
to leadership/job effectiveness. The survey is designed to rate an individual’s skills/behaviors
based on self-response, follower responses, boss responses and peer responses.
Adaptability Trait: One of the four major leadership traits of the DLDS. The attributes of
creating change, emphasizing customer focus, and promoting organizational learning frame the
adaptability trait.
Consistency Trait: One of the four major leadership traits of the DLDS. The trait is comprised of defining core values, working to reach agreement, and managing coordination and integration attributes.
Denison Leadership Development Survey (DLDS): A diagnostic tool measuring aspects of leadership skills developed by Denison and Neale. The tool utilizes 96 items to determine a leader’s level of the four main traits of involvement, consistency, adaptability, and mission. The tool also provides ratings of perceived leadership effectiveness, based on seven items. The 8
diagnostic tool is a 360 survey, aggregating responses from bosses, peers, followers and self-
ratings.
Involvement Trait: One of the four leadership traits of the DLDS. The trait is comprised of the
attributes of developing organizational capacity, building team orientation, and empowering
people.
Leadership Effectiveness: For this study, leadership effectiveness is defined as an individual with high ratings of serving as a role model, developing relationships, communicating, implementing vision and change, and consistently having high performance. Leadership effectiveness will be based on responses from seven items on the DLDS instrument as rated by bosses, peers, followers, and self-response.
Mission Trait: One of the four major leadership traits of the DLDS. The mission trait is
comprised of the attributes of defining strategic direction and intent, defining goals and
objectives and creating shared vision.
Nonprofit Sector: Organizations that do not operate solely for the purpose of a profit, but to
provide a benefit or service to public.
Private Sector: Organizations run for private profit.
Public Sector: Organizations that are part of federal, state, or local governments funded by
taxpayers.
Data Sources
The sample of this study consisted of private, public, and nonprofit respondents who
completed the Denison Leadership Development Survey (DLDS) between 2001 and 2007. The
DLSD is a diagnostic instrument developed by Denison and Neale of Denison Consulting, an
international consulting firm based in Ann Arbor, Michigan, with offices in San Diego, Shanghai 9 and Zurich. The survey uses 96 items to define 12 separate indices of four leadership traits: involvement, consistency, adaptability, and mission. The database contains 8,651 respondents from 263 organizations (212 private, 19 public, 32 nonprofit). The Bowling Green State
University Human Subjects Review Board approval can be found in Appendix A. The Denison
Consulting Terms of Use and Database Agreement can be found in Appendix B.
Organization of the Study
For this study, Chapter 1 presents the introduction, the rationale, the purpose of the study, the research questions, and the significance of the study, definitions, data sources, and organization of this study. Chapter 2 reviews the literature on leadership effectiveness in the private, public, and nonprofit sector as well as comparisons of private and public sectors and private and nonprofit sectors. Chapter 3 explains the research methodology, data collection, aggregation of data, the statistical and research procedures, delimitations, and limitations.
Chapter 4 provides a narrative of the results of the study and an analysis of the data. Chapter 5 summarizes the major findings with implications for practitioners and policy makers along with recommendations for future research.
10
CHAPTER 2: LITERATURE REVIEW
This chapter presents the literature review which is organized in five sections. The first section offers a background of prominent leadership theory and a presentation of transformational, transactional, and situational leadership concepts and research. The next section examines the context of the organizational culture and how organizational context contributes to the cultures in the private, public, and nonprofit sectors. The characteristics of each sector are presented as well as an examination of sector comparison research. Assessing leadership effectiveness with focus on perceptions and outcomes is presented in the third section.
Given the lack of frameworks utilized in research comparing sectors, the next section examines extant literature utilizing the competing values framework and the multi-frame model. Finally the Denison framework utilized for this paper is presented. Each of the four trait variables and the leader effectiveness variable of the framework are discussed.
Organizational Leadership and Theory—Why Care?
Leadership, in its most basic form, has existed from the beginning of humankind.
Organizational leadership matters. In the educational leadership context, Louis, Leithwood,
Wahlstrom, and Anderson (2010) stated that their research “has uncovered many fine grained behaviors that are elements of being an effective leader and has pointed to the conditions that encourage or discourage these productive actions” (p. 282). However, Louis et al. found that relationships, interactions with other organizational leaders—regardless of level—and policies
“are intertwined in a complex and changing environment” (p. 282). In essence, leaders matter, but leadership, organizations and the environments in which they operate are complex.
Leadership programs contend that in spite of these complexities, leadership can be studied and leadership can be taught. 11
It is only in modern times that leadership, leadership effectiveness, and leader behavior has become a field of study and theory. Over time, the debate has moved from one of nature versus nurture to transformational versus transactional styles as shown in Table 1. Theorists and researchers have reviewed the early eras starting with inherited authority and then moving to the
“great man” theory (Burns, 1978; Van Wart, 2003; Yukl, 1981). By the twentieth century leadership theory moved to a discussion of traits, behaviors, and situational characteristics (Bass,
2008; Hersey, Blanchard & Johnson, 2001; Van Wart, 2003; Yukl, 1981). With the technology intensive environment and a service intense economy, contemporary leadership is more focused on establishing a sense of purpose within the organization while developing people for the betterment of the organization (Dhar & Mishra, 2001).
Table 1
Mainstream Leadership Theories
Era Prominence Characteristics Great Man Pre-1900 Emergence of great figures who have affected society Trait 1900-1948 Emphasis on individual traits Contingency 1948-1980’s Situational variables, task performance of followers, rewards based on performance Servant 1977-present Ethical responsibilities of leaders and followers Transformational 1978-present Leaders create change, visionary, overall organization culture Multifaceted 1990’s-present Integration of major theories, primarily of transactional and transformational Source: Adapted from Van Wart, 2003, p. 218
Theorists and researchers of leadership are numerous and varied. A plethora of literature investigated leader behaviors that tie rewards to performance, maintain the status quo, tend to be passive, and/or are motivated by self-interest (e.g., Bass, 1999; Bass & Avolio, 1993; Burns,
1978; Howell & Avolio, 1993; Shamir et al., 1993; Walumbwa, Wu, & Orwa, 2008;
Whittington, Coker, Goodwin, Ickes, & Murray, 2009). In contrast, researchers have also 12 advocated behaviors and traits that promote innovative thinking, empowerment, relationships – internal and external, and change (e.g., Bass, 1999; Bass, 2008; Bass & Avolio, 1993; Bennis &
Nanus, 1985; Burns, 1978; Howell & Avolio, 1993; Kouzes & Posner, 2002; Quinn, 2008). Still others have researched leadership characteristics based on situations and follower maturity (e.g.,
Bass, 2008; Farrow, Valenzi, & Bass, 1980; Hersey & Blanchard, 1996; Vroom & Jago, 2007;
Yukl, 1981) as well as contingent reward and management by exception leadership (e.g., Bass,
1999; Bass, 2008; Bass & Avolio, 1993; Burns, 1978; Deluga, 1990; Howell & Avolio, 1993;
Whittington et al., 2009). Each author has a varied or expanded examination of the key characteristics, behaviors and traits of leaders, situations, contingent reward, and management by exception leadership. “Most people would be hard pressed to define good leadership, but they know it when it’s there and they miss it when it’s not” (Denhardt & Denhardt, 2006, p. 7). In short, there is still not a consensus over a definition of leadership, but there has been agreement that leaders influence employees to work together to achieve the goals of the organization (Dhar
& Mishra, 2001).
Researchers have used the term transformational leadership to describe leader traits and behaviors. Transformational leaders have been described as having the ability to inspire a shared vision and turn that vision into reality, be agents of change, enable and empower followers, and develop followers (Bass, 2008; Bennis & Nanus, 1985; Burns, 1978; De Hoogh, Den Hartog, &
Koopman, 2005; Hooijberg & Denison, 1996; Howell & Avolio, 1993; Kouzes & Posner, 2002).
Transformational leadership also has been characterized as leadership that goes beyond self- interest, provides inspiration, intellectual stimulation, and idealized influence (Bass, 2008; Bass
& Avolio, 1993; Quinn, 2008). Shamir et al. (1993) found that leaders with a charisma trait were inclined to develop an emotional attachment of the followers, motivate followers, articulate the 13
mission, and develop follower self-esteem, as well as trust and confidence. Researchers focused
on transformational leadership affects also found support that leader traits embody group values
while also converting followers from self-interest to collective values and integrating procedures
and teams allows members to react to unexpected situations (Bass & Avolio, 1993; Hooijberg &
Denison, 1996; Shamir et al., 1993).
Contingency theories, also known as transactional theories, have provided perspective on
leadership effectiveness. Scholars and theorists have characterized transactional leaders as
working within the existing organizational culture and lead utilizing contingent reward,
management by exception, laissez-faire leadership and/or passive leadership while being
motivated by self-interest (Bass, 1999; Bass & Avolio, 1993; De Hoogh et al., 2005; Howell &
Avolio, 1993). Some research concentrated on the effectiveness of transactional leadership in
certain organization environments (De Hoogh et al., 2005; Denison & Mishra, 1995). Denison
and Mishra (1995) found the traits associated with consistency and mission, which related to
stability and direction, also contain transactional characteristics. Their study further determined
that organizations with highly consistent cultures tended to be more resistant to change and the
normative integrations caused organizations to become insular. However, other research found
although transactional leaders were more likely to work with the status quo, leaders with high
scores in agreeableness were rated as less charismatic (transformational) in dynamic
environments, but were rated more charismatic in stable environments (De Hoogh et al., 2005).
Burns (1978) and later Whittington et al. (2009) considered the relationship between power and
reciprocal benefits. Burns (1978) contended that, “the relations of most leaders and followers are
transactional—leaders approach followers with an eye to exchanging one thing for another; jobs for votes, or subsidies for campaign contributions” (p. 4). Simply stated, leadership can be 14 described as a transaction between leaders and followers, each wanting to satisfy their own self- interests (Burns, 1978; Whittington et al., 2009).
As a form of transactional leadership, researchers have also investigated contingent reward in relation to performance (Howell & Avolio, 1993; Mary, 2005; Walumbwa et al., 2008;
Whittington et al., 2009). Contingent reward leadership was linked to positive performance provided there was positive reinforcement and/or any negative feedback was perceived as fair, clarified performance, and/or modified behavior in a positive way (Howell & Avolio, 1993;
Mary, 2005; Whittington et al., 2009; Wilson, 1989). Walumbwa et al. (2008) considered how a climate of procedural justice—how a work group or unit, as a whole, believes it is being treated—contributes to perceptions of contingent reward leadership. When the leader was perceived as fair and consistent, there was satisfaction with contingent reward leadership
(Howell and Avolio, 1993: Walumbwa et al., 2008). A similar study by Whittington et al. (2009) investigated the level of agreement (between subordinate ratings and leader self-ratings) between leaders’ performance as transactional leaders versus transformational leaders. Utilizing the
Multifactor Leadership Questionnaire (MLQ) instrument, their study reported significantly more agreement with leaders’ transactional behavior compared to transformational behaviors.
Supporting the works of Howell and Avolio (1993) and Walumbwa et al. (2008), the results of the Whittington et al. (2009) study emphasized the need for clear communication of expectations and goals in order for the transactional leadership style to be effective. Contingent reward leadership had a negative impact on follower behavior when the negative feedback was perceived as criticism after the fact, not clear, or perceived as unfair (Howell & Avolio, 1993;
Mary, 2005). 15
Theorists (Bass, 1999; Bass & Avolio, 1993; Bennis & Nanus, 1985; Burns, 1978; Kouzes &
Posner, 2002) indicated a leader is either transformational or transactional, but other research
(Bass, 2008; Denison, Hooijberg & Quinn, 1995; Hersey & Blanchard, 1996; Yukl, 1981) posited that an effective leader is not necessarily completely one or the other, but needs to adapt and respond to their environments and the situations at any given time.
Situational Leadership
A leader’s traits and behaviors play a strong role in the effectiveness, but in addition, the situation and role also largely contribute (Bass, 2008; Farrow, Valenzi & Bass, 1980). Vroom and Jago (2007) determined that leadership was a variable in which the traits and behaviors of leaders became mediating variables between organization cultures and /or construct. Their studies of leaders given different situational scenarios, found leaders were affected by the environment as well as their own behaviors. The Vroom and Jago study determined situation accounted for about 30% of the variance whereas leader style accounted for only 8% to 10% of the total variance.
Other scholars and theorists constructed models based on levels of concern for people and productivity (Blake & Mouton, 1975; Blake & McCanse, 1991) and situational leadership life-cycles whereby leaders match behavior with performance needs of followers (Blanchard &
Hersey, 1996). Yukl (1981) though, argued situational leadership research needs to look more at the macro environment such as the type of organization and/or culture not just the specific situations.
Organizational Context
As individuals possess combinations of traits and behaviors that equate to perceived leader effectiveness, organizations are also different. Scholars of organizational culture advocate 16 that organizations are complex institutions made up of individuals with differing behaviors
(Bolman & Deal, 1991, 2008; Denison, 1997; Wilson, 1989; Yukl, 1981). Researchers have described organizations as open systems in which environments are changing, challenging and erratic (Bolman & Deal, 1991, 2008; Gallos, 2008). Wilson (1989) stated that, “every organization has a culture, that is, a persistent, patterned way of thinking about the central tasks of and human relationships within an organization. Culture is to an organization what personality is to an individual” (p. 91). Leadership and the constructs of leadership cannot be separated from the organization’s culture (Denison, 1997; Yukl, 1981). Bolman and Deal (2008) pointed out the controversy regarding the relationship between the organization culture and leadership—some believe leaders create the culture while others believe leaders are shaped by the culture. O’Toole
(2008) determined that leadership is not an individual trait, but actually is part of the institutional capacity or culture because many of the main responsibilities of leadership are institutionalized in the systems, practices and cultures of organizations. Denhardt and Denhardt (2006) assessed organizational culture by stating:
Different societies or cultures operate with differing time perspectives and with different
rhythms. But the same is true of groups and organizations. Various groups, organizations,
and societies display different time perspectives, they position themselves differently
with respect to their history and their development, and the resulting variations present
interesting problems as these groups attempt to reconcile their differences (p. 57).
Further, organization culture has been considered both a product and a process—as a product, culture is the accumulated wisdom from experience; as a process the culture renews itself and is recreated as new employees learn the ways of the organization and then become teachers
(Bolman & Deal, 2008; Gallos, 2008). 17
Other researchers and theorists suggest the leader defines the organization culture. In this viewpoint, the leader’s beliefs, values and assumptions that become the core of an organization’s culture. The leader instills the culture through training, development, role modeling, recruitment, promotions and hiring (Bass & Avolio, 1993; Bennis, 2003; Bennis & Nanus, 1985; Bolman &
Deal, 2008; Collins, 2001; Jaskyte, 2004; Kouzes & Posner, 2002). Bass and Avolio (1993) inferred organization culture and leadership was a constant interplay with leaders developing culture through the creation of mechanisms and the reinforcement of norms and behaviors.
Further, the behaviors of the leaders; their reaction to crises, what they give attention to, behaviors they role model and whom they attract to the organization create changes in the existing culture and gave rise to new cultural norms (Bass & Avolio, 1993).
Much of the literature regarding organizational culture associates the organization’s culture to performance and effectiveness. The organizational culture was found to be an integral part of the adaptation and the change process with the specific culture traits being predictors of performance and effectiveness (Bass & Avolio, 1993; Denison, 1997; Denison & Mishra, 1995).
In this body of research, researchers also considered the organization type/environment (e.g., level of bureaucracy, public or private) suggesting organizations with high levels of involvement also reported a higher level of effectiveness compared to low involvement organizations—such as bureaucracies—in which there was a limited ability to respond to the changing environment
(e.g., Bass & Avolio, 1993; Denison, 1997; Denison & Mishra, 1995; Yukl, 1981). Similarly, studies also found that highly effective organizational cultures were adaptable, able to develop norms and beliefs that supported the organization’s capacity to receive and interpret signals from its environment then translate those signals into internal behavioral, structural and cognitive changes (Bass, 2008; Bass & Avolio, 1993; Denison & Mishra, 1995; O’Toole, 2008). In 18
contrast, organizations with highly normative integration, such as bureaucracies, become
detached from the external environment and become insular and less likely to adapt (Bass &
Avolio, 1993; Denison & Mishra, 1995; Jaskyte, 2010). Researchers also reported organization
culture acted as a constraint to innovation since the organization’s culture was rooted in past
glories, symbols, ceremonies, and statements acting as a negative force (Bass & Avolio, 1993;
Bolman & Deal, 2008; Rainey & Steinbauer, 1999).
Organizational Effectiveness
Effectiveness of an organization has been measured via external metrics. External
measures not only differ between sectors but also within sectors. The private sector has typically
utilized quantifiable financial metrics such as profitability, share price, revenue generation and
market share (e.g., Collins, 2001; Denison, 1997; Denison & Mishra, 1995; Herman & Renz,
2008). Young (2002) pointed out, the public and nonprofit sector are accountable to citizens, each with their own idea of effectiveness. Within the public sector, public schools measure
effectiveness through performance indicators, such as proficiency test scores, No Child Left
Behind mandates and financial metrics (Chingos & West, 2011; Pilotin, 2010). Government
departments and agencies have shown a trend toward convergence with the private sector,
utilizing business practices that include outsourcing (Huque, 2009; Linkhorn, 2011). Similar to
public organizations, nonprofit agencies are accountable to multiple stakeholders, all with
different purposes (Young, 2002). For nonprofit social service agencies effectiveness measures
have been more difficult to quantify (Herman & Renz, 2008). Funders have developed outcome
models based on assessment of such quantitative measures as changes in client behaviors, classes
attended, number of counseling services, delivery of services, pre/post testing, self-sufficiency, or proficiency test scores (Bozzo, 2000; Ohio Department of Education, n.d.). Board members 19
of nonprofits consider effectiveness by grant acceptance and funding levels as well as operating
budgets (Herman & Renz, 2008; Mensah, Lam & Werner, 2008). Competing for resources and
seeking external legitimacy, there is evidence that nonprofits have started to adopt business-type
models (Tucker, 2010). On a different level, nonprofit hospitals insurance reimbursements, the
number and types of procedures performed, in patient and out patient census, and staff to patient
ratios have become external measures of effectiveness (Byrnes & Fifer, 2010; McDonagh, 2006;
Rushing, 1974; Yan, Y., Hsu, S. & Fahn, S., 2009). Additionally, internal performance measures
in the public and nonprofit sectors (employee and director expectations, case management
objectives) are typically different than outcome measurements (Young, 2002). Because effectiveness has been measured internally and externally in a variety of ways and the methods differ by organization, understanding the dynamics of the private, public and nonprofit sectors is critical.
Literature has also focused on each sector (private, public, nonprofit). The private sector literature is a mix of empirical research, and theory (e. g., Bennis, 2003; Collins, 2001; Peterson,
Walumbwa, Byron, & Myrowitz, 2007). Public sector literature has a limited but growing body of empirical studies and has been more theory and concept driven (e. g., Appleby, 1945;
Baldwin, 1987; Pfeiffer, 2011; Wright, 2007). There is a limited but growing body of literature focused on the nonprofit sector (e.g., Holzer, 2008; Morris et al., 2007; Wallis & Dollery, 2005).
Research in specific sectors has concentrated on specific dimensions such as employee motivation (e.g., Shamir et al., 1993; Wright, 2007), innovation and entrepreneurial orientation
(Jaskyte, 2004; Morris et al., 2007; Ruvio, Rosenblatt, & Hertz-Lazarowitz 2010), and
effectiveness of the organization (e.g., Denison, & Mishra, 1995; Hooijberg & Choi, 2001;
Walumbwa, Avolio, & Zhu, 2008). Studies examining multiple traits in relation to leadership 20
effectiveness have been limited (Hooijberg & Denison, 1996). Scholars such as Baldwin (1987)
and Wilson (1989) defined differences between public sector and private sector organizations.
Likewise, Jaskyte (2004) and Young (2002) identified key elements that differentiate nonprofit
organizations.
Private sector. The private sector (i.e., business and industry) has been well represented in the literature. Contemporary authors such as Bennis (2003), Collins, (2001), and Kouzes and
Posner (2002) offered suggestions to practicing leaders on how to improve bottom line effectiveness, sustainable shareholder value and/or improved efficiency. By their very existence, organizations in the private sector have identifiable products and services sold in the general marketplace. Unit costs can be calculated and the success of managers can be tracked through quantifiable measures such as units produced, gross and net margins, return on assets, return on equity, return on investment and net profit (Baldwin, 1987; Bennis, 2003; Collins, 2001). Goals and objectives are typically clear and measureable and strategic planning is continuous (Baldwin,
1987) with the main focus on making money (Baldwin, 1987; Ruvio et al., 2010).
Business organizations have identifiable employer-employee tension, power struggles between managers, power struggles between line and staff personnel, struggles with affiliations and expertise, and boundaries to get through (Ashkenas, Ulrich, Jick, & Kerr, 2008; Burns, 1978;
Sorensen, 2002). Leaders in the private sector need to be accountable to owners/shareholders for generation of profitability while being responsible to customers for quality and service and at the same time motivate employees (Young, 2002). Private sector leaders need to be adaptable and flexible in handling market forces and leaders need to know how to obtain financial and non- financial resources needed for production (Hooijberg & Choi, 2001). Because of the significance 21
of production, customers, disruptive innovations, and market forces, the for-profit organizations are more subject to economic pressures (Farrow et al., 1980).
Public sector. In contrast to private sector organizations, public sector agencies are known to have high executive leadership turnover, ambiguous goals, and yet offer job security
(Baldwin, 1987; Boyne, 2002; Wilson, 1989). Other research indicated the leader’s ability to give rewards and punishment was restricted due to formalized tenure, civil service rules, seniority rules and power differences (Farrow et al., 1980; Hooijberg & Choi, 2001).
Additionally, research indicated because public organizations offer little discretionary action, leaders may adopt different behaviors to motivate employees, such as delegation, negotiation, rewards, and/or sense of mission (Farrow et al., 1980; Hooijberg & Choi, 2001; Wilson, 1989).
Wilson (1989) described the public sector as more of a monopoly for providing services that are supported by legislative appropriations which is paid for by the taxpayers who may or may not use a particular service. More recent trends have explored the privatization of certain public services (e.g., waste disposal, prison operations, water services, charter schools,
Medicare) with the idea to improve operating efficiencies, reduce costs and improve service delivery (Bel & Fageda, 2008; Denhardt & Denhardt, 2007; Linkhorn, 2011; Robertson &
Seneviratne, 1995; Volokh, 2010). Even more timely, five legislatures (Idaho, Michigan, Ohio,
Tennessee, Wisconsin) have sought to either limit or eliminate collective bargaining rights of state public workers, which became a contentious battle (Greeley & Niquette, 2011; Olsen,
2011). In his seminal work, Wilson (1989) identified three main constraints making public organizations different from private organizations: 1) it is unlawful for government agencies to retain and devote earnings of the organization to the benefit of its members, 2) administrators do not have the option to allocate the factors of production in accordance to their performance, 3) 22
the agency must serve goals that are not necessarily of the agency’s choosing. However, in
public education, the movement has been to tie teacher compensation to accountability measures
such as student performance on standardized tests, grades, graduation rates, attendance and/or
student behavior (Olson, 2011). Feeney and Rainey (2010) suggested despite reforms, leaders
remained constrained to reward top performers and terminating poor performers.
As researchers have pointed out, the culture of government agencies is based on
procedures, rules, and formulated goals where consistency is prized and employees are organized more by purpose and process (Burns, 1978; Hooijberg & Choi, 2001). Structured as such, others
(Burns, 1978; Holzer, 2008; Van Wart, 2003; Young, 2002) suggest that public organizations have legal obligations to respond to clientele, stakeholders who can exert pressure such as
taxpayers and contractors, which make conflict in public organizations sharper. Further, Burns
(1978) emphasized the political nature of the public sector indicating the conflict is largely
influenced by the existing political climate and culture. As Burns (1978) underscored, the
challenge for leaders is how to handle the conflict, mitigate the intensity, how to channel it and
how to camouflage it. “Public bureaucracies participate in genuine leadership if, recognizing that
they themselves are instrumentalities to external ends, they respond to reciprocal relationship
with the individuals and groups they exist to serve” (Burns, 1978, p. 302). Scholars of public
administration contend bureaucracies, by their nature, are guided by higher public officials
appointed and elected; causing public administrators therefore to work under forces that are
beyond their control, often making the administrative leaders’ contribution insignificant
(Hooijberg & Choi, 2001; Van Wart, 2003; Wilson, 1989). In contrast, Denhardt and Denhardt
(2007) contend the model of the new public service affords public administrators the ability to
involve the citizens in the decision making process. 23
Lemay (2009) developed a model of public administration leadership in which the
leader’s accountability is linked to the level of leadership development. The Lemay model also
links the leadership style to alignment of leadership development and the position held. Further,
Lemay posits a collective and collaborative leadership in order to transform public
administration beyond the traditional and hierarchical form. Others (e.g., Bennis & Nanus, 1985:
Dull, 2009) suggested credibility is necessary for effective leaders in any sector, however, public
sector leaders face more scrutiny because there are numerous stakeholders (clients, legislators,
taxpayers, other agencies) paying attention to the agency and its output. However, Dull (2009)
also pointed out that public administration leaders may be limited in their ability to develop and
benefit from reputation based credibility due to the political environment. Further, because of the
high level of turnover at the elected and appointed executive levels in the public sector (Baldwin,
1987), a strong commitment to mission is a key aspect of leadership at the street level—desire to make a difference--exert influence in developing and implementing new possibilities (Buelens &
Van den Broeck, 2007; Rainey & Steinbauer, 1999; Wright, 2007). Although the public sector has been known for job security, a report by Challenger, Gray, and Christmas, Inc. (2011), indicated the public sector was the experiencing continued downsizing with 77,591 jobs cut through June 2011 with most of those being core positions such as police and fire.
The role of power in the context of public administration has also been studied. As Long
(1949) explained, power is the mainstay of public administration. In this context, power in organizations comes from authority which is linked to the position, not the individual (Colvard,
2008) and power is perceived as emanating from the executive branch (president) and Congress
(via legislation) down to the agency level. Burns (1978) contended that politics does not equal power as many presume, but power plays a role in politics and therefore power plays a key role 24
in leadership. Power has been identified as formal – within the formal structure of government
and/or politics – but also informal flowing from lobbyists, interest groups and even legislators
(Long, 1948; Rainey, Backoff, & Levine, 1976). It has also been suggested that leaders in the
public sector have minimal discretion due to the established rules and laws as well as the formal
and informal aspects of power (Hooijberg & Choi, 2001) Regardless of perceptions, a body of
research contends public organizations are often effective because of dedicated public servants
who are motivated by identification with the organization’s values and mission and not
motivated by profit or economic self-interest (Lipsky, 1980; Rainey & Steinbauer, 1999: Simon,
1998; Wright, 2007). Wright (2007) found within the public sector, organizations and leadership
had the ability to influence self-efficacy by job-goal specificity, job-goal difficulty, performance
feedback, and procedural constraints. Hooijberg and Choi (2001) found public sector leaders
took on the role of facilitator because of the need to manage conflict, build teams, listen carefully
to followers, and integrate differing but complimentary ideas.
Nonprofit sector. The nonprofit sector tends to attract workers highly committed to the agency and willing to accept lower compensation because workers’ values align with the organization’s mission and workers believe their efforts are actually helping meet altruistic goals
(Wallis & Dollery, 2005). Wallis and Dollery (2005) also found because workers are highly committed to the agency and are self-motivated the organization can realize cost savings in
management and monitoring of followers.
The need to develop relationships with multiple stakeholders—funders, clients, board
members, volunteers, and community members—in order to function as an agency makes
nonprofit organizations (NPO’s) distinct from other organization types (Farrow et al., 1980;
Holzer, 2008; Morris et al., 2007; Van Wart, 2003; Wallis & Dollery, 2005; Young, 2002). 25
Research has indicated nonprofits also tended to develop more short-term goals whereas for profit organizations developed long-term goals and strategies in part because there is not the same pressure to optimize long term profits, often needing to minimize any carry over from year to year (Farrow et al., 1980). Additionally, Farrow et al. suggested changes in resources, funding requirements, funding sources, intrusions in the goal setting process, difficulty in measuring results of the service oriented deliverables, and weaknesses or changes in client influences all make long term planning difficult.
Researchers also have considered the role of stakeholder groups (Farrow et al., 1980;
Morris et al., 2007; Young, 2002). Agencies receive funding from multiple sources—public sector grants, private grants, donations, fund raising activities, third party payers (Farrow et al.,
1980; Young, 2002). In general, boards of directors are self-appointed and self-perpetuating entrusted with advancing the mission and integrity of the agency, but board members are not responsible to any stakeholder group (Young, 2002). Adding to the challenge, agency clientele are typically very different from funders, board members, volunteers, and governing bodies
(Morris et al., 2007; Young, 2002). Determining clientele success is often difficult because there is a certain amount of subjectivity in success and different stakeholders have different objectives and different means of measurement (Farrow et al., 1980; Morris et al., 2007).
In regards to nonprofit leaders, research has supported the need for leaders to be transformational on multiple levels— to be visionaries, coaches, change agents, and strategists while advancing the agency’s mission and vision while also engaging internal and external stakeholders (Mary, 2005; Wallis & Dollery, 2005). However, in a study examining the relationship between transformational leadership, organizational culture, and innovativeness,
Jaskyte (2004) found no correlation between transformational leadership and innovativeness in 26
NPO’s. Sampling 19 Associations for Retarded Citizens (ARC’s) in Alabama, a strong
relationship was reported between leadership and organization culture (Jaskyte, 2004). However,
in another study, a contingent-reward (transactional) style was effective when expectations
needed clarification and followers wanted to know benefit to them if objectives are met (Mary,
2005). In the Mary study positive correlations (range of r .58 to .75) were reported between
transformational characteristics and agency success and contingent reward behaviors and agency
success (r = .75).
Sector comparison. Concepts and assertions regarding what makes public administration
(e.g., Appleby, 1945; Baldwin, 1987; Holzer, 2008), nonprofit, (e.g., Jaskyte, 2004; Mary, 2005;
Wallis & Dollery, 2005) and private organizations (e.g., Gregory, Harris, Armenakis & Shook,
2009; Kotter, 2007; Zheng, Yang & McLean, 2010) distinct have dominated the existing literature. However, empirical research and inquiry has been limited and the lack of rigorous research criticized, especially pertaining to public administration (Andersen, 2010; Hooijberg &
Choi, 2001). Some critics (e.g., Denhardt, 1984; Haque, 1996; Harmon & Mayer, 1986) made note that organizational and leadership theory treat sector context equally. Others have examined the diversity of sectors and studied how leadership and organization theory apply to the private, public, and nonprofit sectors (e.g., Andersen, 2010; Baldwin, 1987; Bolman & Deal,
1991; Hooijberg & Choi, 2001; Rainey et al., 1976; Rosenau & Linder, 2003).
Although Baldwin (1987) identified three main differences between the public and private sector, some researchers have examined the convergence of sectors (Baldwin, 1987;
Hooijberg & Choi, 2001; Rainey et al., 1976; Rosenau & Linder, 2003). Hooijberg and Choi and
Rainey et al. investigated whether organizational and leadership theories could be generic regardless of context. Research has indicated the private, public, and nonprofit sectors face many 27 of the same types of problems, challenges, and constraints, supporting convergence of sectors
(Hooijberg & Choi, 2001; Rainey et al., 1976; Rosenau & Linder, 2003). Likewise, Baldwin found that although there was significance for all three variables between the private and public sectors, when magnitude was tested, the impact of the differences was modest.
Not only has the lack of empirical research on public sector leadership been noted
(Andersen, 2010, Van Wart, 2003), but the dearth of empirical research comparing private, public, and nonprofit sectors has also been noted (Andersen, 2010; Farrow et al.,1980; Rainey,
1983; Rainey & Bozeman, 2000). Rainey further noted that a number of studies did not adequately define the characteristics of a public organization and even when “public” is defined, empirical studies are limited. Farrow et al. (1980) for example, compared leadership and situational characteristics among the private and nonprofit sectors, but the nonprofit sample was comprised of library personnel, county government personnel, and city government personnel.
Their sample included public administration employees that were tenured and civil servants; thereby conforming more to the public sector versus the nonprofit sector (Baldwin, 1987). There has been agreement (Rainey, 1983; Hooijberg & Choi, 2001) that the private sector represents a for-profit enterprise while the public sector refers to government agencies and bureaus.
Additionally, there is an absence of formal theories and frameworks exploring the differences among sectors (Bolman & Deal, 1991; Farrow et al., 1980; Hooijberg & Choi, 2001).
Bolman and Deal developed four frames for organizations and leadership perspicacity, thereby allowing for sector comparison. Hooijberg and Choi utilized the competing values framework to discern differences in leadership effectiveness between private and public organizations. The comparison literature has also been criticized for public sector samples being too small, utilizing policy makers and non-policy levels, and narrow samples (one city department, one state office) 28
making inferences about sector differences difficult (Farrow et al., 1980; Hooijberg & Choi,
2001; Noordegraaf & Steward, 2000; Rainey & Bozeman, 2000; Ruvio et al., 2010).
Assessing Leadership Effectiveness
Just as there have been many ways to define leadership, assessing leadership
effectiveness also has varied (Dhar & Mishra, 2001). Leadership effectiveness has been
investigated and measured in regards to an organization’s effectiveness and outcomes (Garnett,
Marlowe, & Pandey, 2008; Gregory et al., 2009; Menges, Walter, Vogel, & Bruch, 2008;
Motamedi, 1976, Peterson et al., 2007; Rainey & Steinbauer, 1999; Zheng, Yang, & McLean,
2010, Yukl, 2008). Other research has focused on job performance and motivation, particularly
of followers (Walumbwa, Avolio, & Hartnell, 2010; Wright, 2007) or job satisfaction
(Mancheno-Smoak, Endres, Polak, & Athanasaw, 2009). Some research looked at leadership in relation to organizational and follower innovation and creativity (Gumusluoglu & Ilsev, 2009).
However, research investigating leadership effectiveness correlated on multiple leader traits is limited (Hooijberg & Denison, 1996). There is also a body of scholarly work on the relation of leadership and power (Bass, 2008; Bass, 1999; Bass & Avolio, 1993; Blake & Mouton, 1975:
Blake & McCanse, 1991; Burns, 1978; Deluga, 1990; Howell & Avolio, 1993; McClelland &
Burnham, 2003; Whittington et al., 2009; Yukl, 1981).
In order to determine whether leadership traits of involvement, adaptability, mission, and consistency are significantly related to leadership effectiveness ratings, this study reviews
leadership effectiveness (e.g., Bennis & Nanus, 1985; Bolman & Deal, 1991, 2008; Burns, 1978;
Van Wart, 2003; Yukl, 1981) and specifically leadership effectiveness based on seven items
rating leadership effectiveness (Denison, 1997; Hooijberg & Denison, 1996). The seven items
evaluate ratings of effectiveness based on: overall effectiveness, style as a role model, potential 29
as a future leader, level of capability, ability to develop high quality internal and external
relationships, consistency as a high performer, and capability of being an agent of change
(Denison, 1997; Hooijberg & Denison, 1996).
Leadership has been defined in terms of individual traits, behavior, influence over people,
role relationships, position, and/or perceptions of legitimate influence and power (Bennis &
Nanus, 1985; Bolman & Deal, 1991, 2008; Burns, 1978; Denhardt & Denhardt, 2006; Van Wart,
2003; Yukl, 1981). In his seminal work, Burns (1978) defined effective leaders as being able to
induce followers that meet the needs, aspirations, and expectations of both the leaders and the
followers in a way that motivates and maintains values. In a similar approach, Van Wart (2003)
defined effective leadership as the ability to provide a high quality of goods and services with
efficient delivery while incorporating cohesiveness, personal development, high levels of
satisfaction, a sense of direction, vision, innovation, and resources needed to invigorate the
organization culture. Further, individuals may be enticed by financial rewards, goals, and reports,
but effective leaders are able to reach followers on an emotional basis and have shared values
(Denhardt & Denhardt, 2006).
Power and its relationship to effective leadership and leader behavior also has been investigated (Burns, 1978; Deluga, 1990; McClelland & Burnham, 2003; Yukl, 1981).
Leadership has also been assessed as a special form of power with leader behavior determined by superiors’ expectations since it is the superiors who hold the power (Burns, 1978; Yukl, 1981). A study of top level managers/leaders (McClelland & Burnham, 2003) revealed a high need for
power, but that to be effective, the need must be controlled and directed toward the benefit of the
organization. Other researchers considered how leaders utilize power to control followers (Bass,
2008; Deluga, 1990; Whittington et al., 2009), utilizing management by exception behavior 30
(transactional characteristics) over subordinates to monitor and sanction followers when
objectives were not met. At the other end of the power spectrum, leaders found to be reluctant or
unable to make decisions allowed subordinates to exert their own power and influence with
freedom of actions (Deluga, 1990); thereby abdicating their leadership role and power position
(Bass, 2008; Bass, 1999; Bass & Avolio, 1993; Blake & Mouton, 1975: Blake & McCanse,
1991; Deluga, 1990; Howell & Avolio, 1993).
Leadership effectiveness then becomes a composite of different characteristics in which
leaders perform, develop followers, align organizations, inspire a common goal, motivate,
influence, innovate, and make difficult decisions (Bennis, 2003; Bennis & Nanus, 1985; Burns,
1978; Kouzes & Posner, 2002; Van Wart, 2003; Yukl, 1981).
Perceptions of Effectiveness
It has been argued that leadership effectiveness is really based on perception of the individuals whether followers, superiors, or the leader him/herself (Hooijberg & Choi, 2001;
Hooijberg & Denison, 1996; Yukl, 1981). Quinn (2008) and Bolman and Deal (1991) argued that effective leaders need to utilize different behaviors/models even though the behaviors are different and often are of competing values. In this argument, leader effectiveness is determined by the context of the organization/department and by the relationship between leader and follower. For example, Howell and Avolio (1993) and Trottier, Van Wart and Wang (2008) elucidated that although transformational leadership behaviors were slightly more important in the perception of leader effectiveness and follower satisfaction in government organizations, federal managers/leaders were evaluated as better transactional leaders and did not rate well for inspirational motivation as a transformational behavior. Trottier, Van Wart and Wang also 31 indicated that government leaders needed to have traditional technical and transactional skills as well as transformational behaviors that emphasize mission, vision, and inspirational motivation.
Multi-source feedback. Researchers contend the perception of effectiveness is influenced by the relationship between the leader and the rater, as well as the organization context and the stakeholder perspective (Hooijberg & Choi, 2001; Hooijberg & Denison, 1996;
Yukl, 1981). Yukl explained that leadership has different meanings to different people. As
Hooijberg and Denison elucidated, the different ratings of leadership effectiveness from raters is due to the different raters using different definitions of effectiveness and not necessarily from differences in observed behaviors. In addition, researchers (e.g., Bolman & Deal, 1991;
Hooijberg & Choi, 2001; Hooijberg & Denison, 1996) found the organizational context influences perceptions of leader effectiveness as well as the rater relationship. Other research
(Antonioni & Park, 2001; Zammuto, London & Rowland, 1982) questioned the independence of
360-degree feedback ratings, finding support that the raters positive or negative opinions of the leader and relationship between rater and rate influenced ratings.
Outcomes. Although limitations in research have been noted, differences between sectors have been studied mostly in terms of job satisfaction (Maidani, 1991), motivation
(Baldwin, 1987; Rainey, 1983), job duties (Noordegraaf & Stewart, 2000), entrepreneurial orientation (Ruvio et al., 2010), task and efficiency performance (Rainey, 1983; Rosenau &
Linder, 2003), rewards (Baldwin, 1987; Rainey, 1983) goal setting and clarity (Baldwin, 1987;
Farrow et al., 1980; Rainey & Bozeman, 2000), and personnel (Baldwin, 1987; Farrow et al.,
1980; Rainey, 1983; Rainey & Bozeman, 2000). Studies examining leadership effectiveness among sectors has been limited (Hooijberg & Choi, 2001; Farrow et al., 1980; Noordegraaf &
Stewart, 2000). The existing research indicates effectiveness outcomes vary among sectors and 32 even within sectors. Therefore the differences in the private, public, and nonprofit sector environments, stakeholders, markets, purposes, and structures support the argument that the relationship between sector and leadership effectiveness is worthy of research (Hooijberg &
Choi, 2001; Noordegraaf & Stewart, 2000).
Hooijberg and Choi (2001) investigated how leadership effectiveness is impacted by organizational characteristics. Using a large sample from the public (175 upper level managers) and private (819 mid-level managers) sectors and utilizing the competing values framework, they assessed perceived leader effectiveness in terms of overall managerial success, overall leader effectiveness, achievement of performance standards, peer comparison, and capability as a role model. Their results found public sector leaders did not perceive a strong relationship between goal orientation roles and effectiveness, but subordinates and superiors indicated that goal orientation was as important a leadership role as did the private sector counterparts. The authors noted that although public sector followers and superiors stressed goal orientation as important, the public sector leaders believed their discretion was limited, which supports the concept that those in leadership roles have less discretion than their private sector counterparts (Rainey,
1983). Hooijberg and Choi also found that in the public sector there was a positive association between the monitoring role and leadership effectiveness, but in the private sector the association was negative. Hooijberg and Choi point to the implication that monitoring is defined differently
– the public sector relates monitoring with the adherence of rules and regulations whereas the private sector thinks of monitoring as the close supervision of people. In the public sector compliance to rules and regulations is standard and considered impersonal, therefore it may be perceived more favorably than the perception of close supervision (Hooijberg & Choi, 2001). 33
Andersen (2010) contended that although job duties and tasks may be the same, public sector and private sector leader behavior may be different and worthy of study. The study utilized four samples: 61 senior officials from regional social insurance offices; 176 principals and deputy principals from primary and secondary schools; 148 Swedish managers as rated by
1,561 subordinates; and 222 managers from eight manufacturing and service organizations. The
Andersen study examined leadership behavior differences based on leadership style, decision making style, and motivation profile. The study found significant differences in leadership behaviors between the public and private sectors, but no difference in the decision making style.
However, contrary to the findings of Rainey (1983), Baldwin (1987) and Maidani (1991) that reported no difference existed in motivation, the results from the Andersen study found significant differences in leadership behavior and motivation between the public and private sector samples. Additionally, Andersen indicated that public leaders, as a group, had similar behavioral patterns, utilizing a change-oriented leadership style, intuitive decision making, and were achievement motivated. Andersen’s findings supported Hooijberg and Choi’s (2001) contention of the perception that leaders in the public sector have less discretion than their counterparts in the private sector. Based on the Hooijberg and Choi research, the private sector indicated more leadership roles with significant impact on the perceptions of leader effectiveness than did the public sector sample.
Some research has focused on specific trait differences between sectors such as mission, entrepreneurial orientation, adaptability, and consistency. Noting that mission, as a motivator, has been found to differ between private, public, and nonprofit organizations, public and nonprofit worker motivation was linked more to the mission and obtainment of the mission of organization (Rainey & Steinbauer, 1999; Ruvio et al., 2010; Wright, 2007). Utilizing goal 34
theory, Wright (2007) confirmed individuals were motivated to achieve organization goals and
objectives if the employee believed the organization’s mission was important and in line with
their own values. However, Young (2002) pointed out that nonprofit leaders run the risk of
compromising the organization’s mission in effort to meet financial and economic expectations
that often come from the business community.
The concept of entrepreneurial leadership vision carried different meanings for profit and
nonprofit organizations (Ruvio et al., 2010). Whereas an entrepreneurial orientation in nonprofit
organizations was related to the social goals, inspiration and ideals of the agency, and
transformational leadership behaviors, in the private sector entrepreneurial orientation was more
conservative and flexible (Morris et al., 2007; Ruvio et al., 2010). Morris et al. further suggested
nonprofit leaders overly concentrated on the current mission may miss opportunities for innovative funding sources, finding unmet client needs, innovative approaches to delivery of client services, and leveraging of resources. In contrast, leaders with an entrepreneurial vision in the business sector tended to be more flexible and adaptable to changes in their internal and external environments (Ruvio et al., 2010).
The model of innovation in the for-profit sector was tied to value creation for customers
(Morris et al., 2007). In the nonprofit sector leadership, the concept of innovation was focused on creative delivering of services to clients (Jaskyte, 2004). In examining how the public sector differs, Hooijberg and Choi (2001) reported flexibility and adaptability were strong traits for effective leaders because of the changing coalitions, changing agendas, and changing political leaders. This study adds to limited research exploring leadership effectiveness in terms of leadership traits among the private, public, and nonprofit sectors. Further, large samples from 35 each sector are utilized and build on existing frameworks (Denison, 1996) as the theoretical basis for which traits correlate to effectiveness in each sector.
Leadership Frameworks
Prior researchers tended to look at one or two dimensions of leadership effectiveness, but not multiple dimensions (e.g., Blake & Mouton, 1975; Blake & McCanse, 1991; Blanchard &
Hersey, 1996). Other existing research investigated leadership effectiveness looking at specific measurements such as job performance (e.g., Walumbwa, Avolio & Hartnell, 2010) and motivation (e.g., McClelland & Burnham, 2003). Quinn’s (Denison, Hooijberg & Quinn, 1995) competing values framework, Denison’s (1996) leadership framework and Bolman and Deal’s
(2008) multi-frame model consider multiple role behaviors necessary for leadership effectiveness, based on organizational and follower context and the perceptions of multiple sources.
Research has determined that not only is leader effectiveness determined by an individual’s behavior, but also the organizational context, causing effective leaders to perform different roles, that are often contradictory (Blake & Mouton, 1975; Blake & McCanse, 1991;
Denison, Hooijberg & Quinn, 1995). Research utilizing the Denison el (1996) (see Figure 1), and the ratings of effectiveness has been limited (Hooijberg & Denison, 1996). However, a number of studies have utilized the competing values framework (e.g., Denison, et al., 1995; Gregory et al., 2009; Hooijberg & Choi, 2001) in explaining the differences in perceptions of effectiveness.
These studies tended to focus more on a single criterion and how the competing values framework domains related to organizational effectiveness, not necessarily multiple criteria of leader effectiveness. However, the competing values framework does support the idea that leader effectiveness is measured by the rater and organizational context. 36
The Bolman and Deal (1991) multi-frames study , which also incorporates internal,
external, flexible, and stable factors, examined perceptions of leadership effectiveness in
organizations in the private sector, higher education, school administration, and the public sector.
Their study contained two global ratings of perceived effectiveness: overall effectiveness as a
manager and overall effectiveness as a leader. Although the researchers purposely did not define
management or leadership, the perceived effectiveness from the respondents was highly
correlated. Their results, based on mean differences between groups, indicated that context
influenced how respondents interpreted the survey items. Results also indicated effectiveness as
leader and manager were not the same; that managerial effectiveness was consistently associated
with a structural orientation, whereas, leader effectiveness was associated with frames of
symbols and politics.
In a study also comparing perceived leadership effectiveness in the private and public
sectors, Hooijberg and Choi (2001) utilized the competing values framework. As with the
Bolman and Deal (1991) study, Hooijberg and Choi (2001) found differences in perceived
effectiveness between the groups. Specifically, multiple leadership roles and overall effectiveness were significantly related to perceptions of leadership effectiveness in the private sector organizations compared to the public sector (Hooijberg & Choi, 2001). Similar to the studies of Bolman and Deal (1991) and Hooijberg and Choi (2001), Denison (1997) and Denison and Mishra (1995) based perceptions of effective leadership on overall effectiveness, but also included: ability to serve as a role model, potential as a future leader, capability within the organization, ability to develop high quality internal and external relationships, consistent high performance, and ability to lead the organization through change.
37
Denison Leadership Effectiveness Framework
Hooijberg and Choi (2001) assessed leader effectiveness through five items and utilized the competing values framework to assess leadership roles1. As with the competing values framework, the DLDS traits fall within two of four quadrants – external or internal focus and flexibility or stability. Studies utilizing the Denison (1996) framework have been scant and focused on organizational effectiveness (Denison, 1997; Denison & Mishra, 1995). A limited number of studies investigated the traits of adaptability, consistency, involvement and mission
(Denison, 1997; Denison & Mishra, 1995), but those studies correlated the traits with organizational effectiveness, not perceptions of leadership effectiveness. Studies utilizing the
Denison framework for leadership effectiveness are limited to Hooijberg and Denison (1996).
Hooijberg and Denison examined the perceptions of multiple raters for three of the criteria for effectiveness in relation to the Denison framework of involvement, adaptability, consistency, and mission leadership traits. Leader effectiveness was evaluated by one item asking to rate overall effectiveness. Three other items (of the remaining six) were also used: ability as a role model, potential as a future leader, and ability to develop quality relationships. The study investigated the relationship between the effectiveness criteria and the leadership traits, but did not consider if perceptions differed by organization sector.
Because research examining perceived leadership effectiveness in relation to multiple leadership dimensions and organization context is limited, this study attempts to fill the gap by determining the relationship between ratings of leadership effectiveness and leadership traits of
1 CVF leadership roles are Innovator, Broker, Producer, Director, Coordinator, Monitor, Facilitator and Mentor. 38 adaptability, involvement, consistency and mission across the private, public and nonprofit sectors.
Leadership traits. The four traits of adaptability, involvement, consistency, and mission represent the components of The Denison Model of Leadership Traits framework (see Figure 1).
The framework also emphasizes the tensions between internal integration and external adaptation and between change and stability. Within the framework, adaptability and involvement relate to the capacity to change while consistency and mission relate to stability and predictability
(Beugelskijk, Koen, & Noorderhaven, 2006; Denison, 1997). In the model, each trait is balanced by other traits; for example an excessively high score in the involvement trait is balanced by a lack of another trait such as adaptability (Denison, 1997).
The Denison Model of Leadership Traits
Change & Stability & Flexibility Direction
External Orientation Adaptability Mission
Internal Involvement Consistency Integration
Figure 1. The relationship among the traits and external orientation and internal integration is indicated. Adapted from Corporate Culture and Organizational Effectiveness by D. R. Denison (1997).
39
Involvement. Developing organizational capability, building team orientation, and empowering people are attributes related to involvement in the Denison framework. Leaders rating high in the involvement trait have the ability to informally build and motivate work teams
(Hooijberg & Denison, 1996). Research has viewed involvement in terms of organizational growth. The involvement trait has also been considered in terms of organizational effectiveness and culture (Beugelskijk et al., 2006; Denison, 1997; Gregory et al. 2009; Howell & Avolio,
1993; Shadur, Kienzle & Rodwell, 1999). Bass and Avolio (1993) found in transformational organization cultures there is a sense of purpose and a feeling of family along with long term commitments.
Leaders shown to build human capability encourage and empower others and foster collaboration and commitment to team and organization goals and were thought of as moving the organization forward (Denison & Mishra, 1995; Hooijberg & Denison, 1996; Kouzes & Posner,
2002). The involvement trait was a strong indicator of growth and a high predictor of a leader as a role model (Denison & Mishra, 1995; Hooijberg & Denison, 1996). In support of Denison’s
(1997) hypothesis that organizational effectiveness was related to the framework’s involvement quadrant, Gregory et al. (2009) found organizations with a focus on teamwork, cohesion, and employee involvement tended to outperform organizations without such a focus.
Empowering people has been found to positively relate to shared values of the organization culture. In their study, Denison and Mishra (1995) found the involvement trait to be related to ratings of effectiveness; having a positive effect on the organization’s functioning.
However, the Denison and Mishra study also revealed that involvement combined with success led to a sense of entitlement, preoccupation with internal processes and ultimately had a negative impact on leadership effectiveness. 40
Other research has looked at involvement and innovation, which has produced mixed
results (Beugelskij et al., 2006; Howell & Avolio, 1993; Shadur et al., 1999). Innovative
oriented organizations were found to promote empowerment, team orientation, and motivation
because those characteristics were related to innovation (Beugelskij et al., 2006). Howell and
Avolio also found the relationship between transformational leadership and performance moderated support for innovation (or lack thereof) in an organization. However Shadur et al.
(1999) found that innovative climates were not positively related to involvement in decision making, teamwork, and communication. Specifically, their results questioned the relationship between teamwork and innovation.
Consistency. Consistency relates to a leader’s ability to coordinate and integrate, work to reach agreement, and define core values. Consistency provides the base for a strong culture by defining values, normative integration, internal governance, and consensus (Denison & Mishra,
1995; Hooijberg & Denison, 1996).Scholars have suggested consistency relates to values and beliefs which become internalized within the organization; becoming an element of the organization culture. This allows members to react in predictable and acceptable ways to unexpected situations (Bass, 2008; Bass & Avolio, 1993; Denison & Mishra, 1995; Hooijberg &
Denison, 1996; O’Toole, 2008). Jaskyte’s (2010) research utilizing 79 nonprofit organizations found a positive relationship between cultural consensus (employee agreement of values) and the leadership behaviors from Kouzes and Posner’s (2002) Leadership Practices Inventory of enabling others to act (r = .782, p < .01), encouraging the heart (r = .805, p< .01), inspiring a shared vision (r = .566, p < .01) and modeling the way (r = .648, p< .01). Scholars further contend that leaders promote consistency by developing a mindset of operations, central values, internal systems, and a set of do’s and don’ts as well as developing talent and promoting from 41
within the organization (Bass & Avolio, 1993; Bennis, 2003; Bennis & Nanus, 1985; Bolman &
Deal, 2008; Hooijberg & Denison, 1996; Jaskyte, 2004; Kouzes & Posner, 2002 ; O’Toole,
2008).
Researchers have suggested more consistent and stable organizations and/or more
hierarchical organizations (such as bureaucracies) tended to display transactional characteristics, while more dynamic organizations exhibited more transformational characteristics (Bass, 1999;
Bass & Avolio, 1993; De Hoogh et al., 2005). Supporting the idea that transactional leaders are more likely to reinforce consistency in stable environments, De Hoogh et al. (2005) found that leaders with high scores in agreeableness were rated as less transformational in dynamic environments, but were rated more charismatic in stable environments.
Adaptability. In the Denison framework, the adaptability trait encompasses three
attributes—creates change, emphasizes customer focus, and promotes organizational learning.
Hooijberg and Denison (1996) found perceived effective leaders with high adaptability skills
were able to respond to internal and external customers along with the external environment.
Their study suggested focusing on customers and competitors facilitated the restructuring and re-
institutionalizing a set of behaviors and processes that assisted employees and organization to
adapt to change. The trait was also found to be a strong predictor of organizational growth, but
research revealed the trait was a weak predictor of overall effectiveness and as a role model for
leadership (Denison & Mishra, 1995; Hooijberg & Denison, 1996). Jaskyte (2010) found strong
monocultural organizations had higher leadership scores with behaviors that challenged the
status quo, but leadership scores were lower in organizations considered pluralistic and
multicentric. 42
Adaptability has been viewed from the organizational level. However, as research has
indicated, the organizational environment has bearing on the performance of a leader and
leadership tends to be more institutional than just a sole individual trait (O’Toole, 2008).
Innovative organizational cultures have been linked to adaptability (Bass, 2008; Beugelskijk et
al., 2006; Denison, 1997; O’ Toole, 2008; Tuominen, Rajala & Möller, 2004). Further,
transformational leadership characteristics have been found to contribute to the follower’s creativity. Similarly, researchers indicated organizations formed stronger alliances and relationships with customers when the organizational culture was adaptive because the organization was more willing to perform innovative activities to better serve customers
(Beugelsdijk et al., 2006; O’Toole, 2008). Further, transformational leadership characteristics have been found to contribute to follower creativity (Gumusluoglu & Ilsev, 2009). Sorenson
(2003) suggested a volatile environment enabled learning by doing which allowed for greater adaptability (Sorenson, 2003).
Mission. Within the framework mission contains the attributes of defining strategic direction and intention, defining goals and objectives, and creating a shared vision. A sense of mission is achieved when the organization’s culture is shared and endorsed by workers and managers a like (Kouzes & Posner, 2002; Wilson, 1989). Mission has been considered as an organizational culture trait (Denison & Mishra, 1995; Garnett et al., 2008) and an individual leadership trait (Hooijberg & Denison, 1996; Kouzes & Posner, 2002; Peterson et al., 2007;
Wilson, 1989).
Leaders with high ratings of mission characteristics show more transformational behaviors (Bass, 1999; Hooijberg & Denison, 1996; Kouzes & Posner, 2002; Peterson et al.,
2007; Wilson, 1989). Further, some researchers found leaders rating high in a mission trait used 43
their beliefs and values to motivate and engage employees to envision a future of new directions
and created an organizational vision (Hooijberg & Denison, 1996; Kouzes & Posner, 2002;
Peterson et al., 2007; Wilson, 1989). Others looked at the how transformational leader behaviors
of hope and optimism provided belief in change, development and accomplishment of strategies,
and reinforcement of a positive future while inspiring a vision (Peterson et al., 2007).
Examining leadership effectiveness, researchers found mission was a strong predictor of
overall effectiveness (Denison & Mishra, 1995; Garnett et al., 2008; Hooijberg & Denison,
1996). Jaskyte (2010) found effectiveness ratings were higher for leaders displaying behaviors
that encouraged the values and mission in monoculture organizations (strong main culture).
However, the ratings were lower for leaders in pluralistic organizational cultures. Further,
Garnett et al. reported organizations with a highly oriented mission culture and a high level of
communication positively affected performance.
Effectiveness Constructs
Overall Effectiveness
Overall effectiveness has been related to transformational leadership characteristics
(Bass, 1999; De Vries, Bakker-Pieper & Oostenveld, 2010; Hooijberg & Denison, 1996). Traits of mission and adaptability – externally oriented traits – received higher ratings by supervisors
(Hooijberg & Denison, 1996). But in the same study direct reports gave the higher ratings to leaders with internally oriented traits (involvement and consistency), especially the involvement trait (Hooijberg & Denison, 1996). These findings indicate the need for effective leaders to assume multiple roles and behaviors that sometimes compete (Bolman & Deal, 1991; Denison,
Hooijberg & Quinn, 1995; Hooijberg & Denison, 1996; Hooijberg & Choi, 2001). 44
Results of effectiveness for leaders utilizing more transactional styles have been mixed.
While theories indicate effective leaders employ multiple roles (Bolman & Deal, 1991; Quinn,
2008), there have been indications that followers alter their behavior based on a leader’s style in
order to achieve overall effectiveness (Deluga, 1990). In one study, followers were found to alter
their behavior, taking a harder influence approach when leaders were perceived as being laissez- faire and utilized a rational (bargaining and reason) approach with transactional behaviors
(Deluga, 1990). The Deluga study also found when transactional leaders utilized contingent reward characteristics2, the rational approach was also employed by followers, but followers
utilized softer, friendlier approaches with leaders in a management-by-exception environment
(Deluga, 1990).
Contingent reward leadership has been also linked to effective leadership in terms of
satisfactory job performance (Howell & Avolio, 1993; Mary, 2005; Walumbwa, Wu & Orwa,
2008; Whittington et al., 2009). Studies indicated leadership was perceived as effective when
there was positive reinforcement and/or if negative feedback was perceived as fair, clarified
performance standards, or modified behavior in positive ways (Howell & Avolio, 1993; Mary,
2005; Shamir et al., 1993; Whittington et al., 2009; Wilson, 1989). Supporting the work of
Howell and Avolio (1993), Walumbwa, Wu and Orwa and Whittington et al. reported
satisfaction and agreement between subordinate ratings and leader self-ratings with transactional
leadership styles when the leader was perceived as fair and consistent and stated expectations
and goals clearly. Researchers (Howell & Avolio, 1993; Mary, 2005; Shamir et al., 1993) found
2 The characteristics were determined from the Multifactor Leadership Questionnaire-Form 5 (MLQ-5) developed by Bernard Bass in 1985. The MLQ is a multi-rater questionnaire. 45
if negative feedback was perceived as criticism after the fact, not clear, or perceived as unfair,
there was negative impact on follower behavior and perceptions.
Role Models
Leaders were perceived to be role models when transformational behaviors were
displayed, primarily characteristics of going beyond self-interest, providing inspiration,
intellectual stimulation, and idealized influence (Bass, 2008; Bass & Avolio, 1993; Quinn,
2008). When leaders displayed higher levels of efficacy, hope, optimism, and resilience –
exhibiting higher levels of psychological capital—the leaders were perceived as credible role
models (Walumbwa et al., 2010). The higher levels of psychological capital of leader behaviors
were also found to activate follower self-concepts which in turn, affected follower motivation and future motivational systems implemented by leaders (Shamir et al., 1993). In examining the private and public sector leaders, Hooijberg and Denison (1996) determined leaders from both sectors were perceived as effective role models when exhibiting traits of empowering individuals and building teams (involvement trait), but leaders reported as having an adaptive orientation
(change agents with high level of customer focus) were perceived as less effective role models.
Leadership Potential
Research regarding leadership potential has been centered on transformational behaviors
(e.g. de Vires et al., 2010; Hooijberg & Choi, 2001; Hooijberg & Denison, 1996).
Transformational behaviors related to adaptability (change agent, visionary, team building) was a strong predictor of leadership potential; strongly associated with leader assuredness and supportiveness (de Vires et al., 2010; Hooijberg & Denison, 1996). Utilizing the competing values framework and a multiple rater instrument, Hooijberg and Choi (2001) found that leaders 46
from both the private and public sectors with an adaptive orientation, especially the broker role
(exerting upward influence), were perceived as potential leaders.
Capability
Research has linked perceived effectiveness to levels of competence, capability, task
performance, and goal orientation (Hooijberg & Denison, 1996; Hooijberg & Choi, 2001;
Walumbwa, Avolio & Zhu, 2008). Walumbwa et al. found perceptions of effectiveness were higher when followers reported confidence in the leader’s abilities and followers believed there were adequate resources. In investigating leadership among private and public sectors, Hooijberg and Choi (2001) reported a strong association among task/goal orientation characteristics and leader effectiveness regardless of organization type. However, when their study compared results by rater, differences were found between the sectors with public sector leaders self-reporting not associating goal-orientation with perceptions of leader effectiveness, but private sector leaders did associate task/goal orientation with perception of effectiveness.
Developing Relationships
A leader’s ability to develop relationship has been investigated in terms of external and internal relationships as well as mentoring (Beugelskijk et al 2006; de Vries et al., 2006;
Hooijberg & Denison, 1996; Hooijberg & Choi, 2001). Leadership effectiveness was rated higher in organizations promoting higher levels of relationship skills, especially for internal relationships (Beugelskijk et al., 2006; de Vries et al., 2010; Hooijberg & Denison, 1996).
Hooijberg and Denison (1996) found the adaptability trait related to developing internal and external relationships and was a strong predictor of leadership effectiveness. Beugelskijk et al. found development of external relationships not related directly to perceived leadership effectiveness; however, the development of long term external relationships were more important 47
to organization performance than short-term/arms-length market ties. The Hooijberg and Choi
(2001) study determined leaders in the public sector fostering teamwork were perceived as effective, but in the private sector, leaders developing relationships in a mentor role were perceived as effective.
Change Agent
Scholars have attributed change creation to transformational leadership. Change occurs with a leader’s ability to encourage followers to focus on long term goals instead of short term gains thereby changing and aligning systems to meet the vision and long term goals (Bass, 1999;
Howell & Avolio, 1993). While utilizing the theories of Burns (1978) and Bass (1999), Shamir et al. (1993) contended that the theories of charismatic leadership did not explain follower motivation in order to account for the transformation of followers from an individual-oriented mode to the collective, moral, and value-oriented mode of operation. The Shamir et al. study indicated it was the leaders’ behaviors that activated follower self-concepts and thereby motivated followers to accept change and future motivational systems. Taking the Shamir et al. study a step further, Gilley, Dixon, and Gilley (2008) examined which characteristics were considered critical for leaders to be effective innovators and change agents. Their study, sampled from manufacturing, service sector, education, professional, public sector, and other types of organizations, identified four key characteristics significant for leader effectiveness: communication, motivation, involving others, and coaching. The study did not consider if or how the characteristics for effectiveness differed by organizational type or sector.
Summary
Leader effectiveness has been defined in a variety of ways. Theorists have considered leadership in broad terms – transformational, transactional – in which characteristics are same 48
regardless of organization context (Bass, 1999; Bass & Avolio, 1993; Burns, 1978; De Hoogh et
al., 2005 Whittington et al., 2009). Others have investigated the effect of the situation on leader
behavior (e.g., Hersey & Blanchard, 1996; Vroom & Jago, 2007; Yukl, 1981). While scholars
focused on the micro environment and specific situations such as follower readiness; Yukl
(1981) advocated a macro view whereby situational leadership research needs to consider organization type and culture. Additionally, the existing research on leadership effectiveness has been limited to one or two dimensions, not multiple roles.
While the concepts and theories of which characteristics make-up a leader, leader
effectiveness is based on the rater. Yukl (1981) contented different people have different
meanings of leadership. Likewise, Hooijberg and Denison (1996) suggested that ratings of
effective leadership differ from rater to rater because each rater uses a different meaning of
effectiveness, which is not necessarily based on observed behaviors. For the most part, research
suggests high ratings for perceived effectiveness have been associated with more
transformational characteristics (de Vries et al., 2010; Hooijberg & Choi, 2001; Hooijberg &
Denison, 1996). However, some studies have indicated in certain organizational environments
transactional leader characteristics (primarily contingent-reward) were perceived as effective
(Howell & Avolio, 1993; Mary, 2005; Walumbwa et al., 2008; Whittington et al., 2009).
Scholars such as Denison (1997), O’Toole (2008) and Yukl (1981) contended constructs of leaders and the organization’s culture cannot be separated. The organization’s culture has been related to an individual’s personality – unique and continually evolving. Bolman and Deal (2008) referenced the controversy of whether leaders create the organization culture or the culture shapes leaders. Since the organization plays a key role in leadership effectiveness, research and theory has concentrated on the dimensions of the private, public, and nonprofit sectors. Literature 49
targeted for the private sector has ranged from empirical studies (e.g., Gregory et al. 2009;
Howell & Avolio, 1993) as well contemporary readings (e.g., Bennis, 2003; Collins, 2001;
Kouzes & Posner, 2002). Public sector works have been largely conceptual and theoretical (e.g.,
Appleby, 1945; Baldwin, 1987; Colvard, 2008; Lipsky, 1980) although there has been a growing interest in empirical research (e.g., Dull, 2009; Garnett et al., 2008; Maidani, 1991). There has also been a growing body of research investigating the nuances of nonprofit organizations (e.g.,
Holzer, 2008; Jaskyte, 2004; Wallis & Dollery, 2005). Within the bodies of research for each sector, scholars have concentrated on specific dimensions such as motivation, organization effectiveness, entrepreneurial orientation, or organizational performance. Studies investigating multiple traits in relation to leadership effectiveness across the different sectors are limited
(Bolman & Deal, 1991; Hooijberg & Choi, 2001).
Many have pointed out that the private, public, and nonprofit sectors are different, but what makes each sector and subsector distinct is less concrete. Denhardt (1984) criticized the body of leadership and organization theory for assuming the concepts applied equally to the different sectors. However, research comparing differences among the sectors has been mixed with some researchers emphasizing differences while others suggesting similarities with any distinctions low in magnitude. How the public and nonprofit sectors are defined has also made the discovery of differences more difficult with research considering nonprofit organizations as part of the public sector (e.g., Farrow et al., 1980). Additionally, subsectors within each group, such as public schools or nonprofit hospitals, have their own characteristics compared to other entities within the group. The research comparing sectors typically has been limited to comparing just two sectors at a time (predominantly private versus public), utilized small and narrow sample sizes in the public sector, and has lacked formal theories and frameworks. 50
Frameworks considering multiple roles or dimensions of a leader are primarily limited to
the Competing Values Framework (Denison, Hooijberg & Quinn, 1995), Bolman and Deal’s
Multi-frame model (2008) and Denison’s Leadership Traits model (1996). Each incorporates
internal/external and flexibility/stability factors and considers that leaders utilize multiple roles
and behaviors based on the situation and organization context. The models also evaluate
perceptions of leader effectiveness based on ratings of multiple sources (subordinates, peers, supervisors, self). These models suggest leaders elicit different behaviors, often contradictory, based on context, and that effectiveness is determined by the perceptions of the raters.
Despite limitations in research comparing the sectors, the differences warrant continued
empirical research on leadership effectiveness. Hooijberg and Choi (2001) studied the
association between leadership roles and perceptions of leadership effectiveness within the
private and public sectors utilizing a larger and more diverse sample. Andersen (2010) found
differences in leadership style and motivation between the public and private sectors. However,
studies comparing the traits of adaptability, mission, involvement, and consistency in relation to
ratings of perceived leadership effectiveness among the private, public, and nonprofit sector are
not available.
Given the lack of comparison research utilizing multiple dimensions and an established
framework, this study seeks to add to the limited body of literature utilizing the Denison (1996)
Model of Leadership Traits and incorporates the relationship between the traits and ratings of
leadership effectiveness. Further, by examining the traits and the relation between the traits and
leader effectiveness in each of the sectors, this study contributes to the sector comparison
literature. Whereas existing comparison literature only looks at two sectors at a time, this study
provides a comparison of the private, public, and nonprofit sectors together. The current study 51 also utilizes a large sample among the sectors, mitigating criticisms of small and concentrated samples.
Chapter 3 offers a methodology to answer the research questions. The next chapter discusses the data source, the instrument used, the reliability and validity of the instrument, as well as the methods used to answer the research questions.
52
CHAPTER 3: METHODOLOGY
The purpose of this study was to examine the relationship between constructs of
involvement, consistency, adaptability, and mission and leadership effectiveness ratings across
private, public, and nonprofit sectors. The study first examined whether the leadership traits
relate to effectiveness ratings. Then it examined whether the traits are significantly different as a function of private, public, and nonprofit sectors. Finally, this study investigated the correlation between leadership traits and leadership effectiveness ratings and examines if the relationship is significantly different based on organization sector.
This chapter discusses the research method utilized in the context of this study, discussing the data sources, the instrumentation of the Denison Leadership Development Survey
(DLDS), including its validity and reliability. This chapter also illustrates and explains the broad methodological approach and specific statistical models used in determining the relationship between the constructs of involvement, consistency, adaptability, and mission and perceived leadership effectiveness ratings across private, public, and nonprofit sectors. A description of how variables were operationalized is provided.
Data Sources
The data utilized in this study consisted of the universe of respondents who completed the
Denison Leadership Development Survey (DLDS) between 2001 and 2007. Represented in the dataset are private sector organizations, public sector organizations, and non-profit sector organizations. The data set for this study was collected and maintained by Denison Consulting.
The Leadership Development survey was confidentially administered confidentially by Denison
Consulting via the internet or paper for self, direct reports, bosses, and peers. Participants (self- reports) in the Denison Leadership Survey submitted a list of potential respondents (direct 53 reports, bosses, peers) including email and name to Denison Consulting. Denison consulting created a personalized website for each potential respondent and potential respondents were sent a personal invitations to participate (URL link to survey included). Reminders were sent to all potential respondents (self-reports, direct reports, bosses, peers). Completed surveys were returned to Denison Consulting for confidential input. There were 8,651 participants representing managers and staff workers from a variety of private, public and nonprofit sector organizations.
Scores were aggregated by self-evaluation, subordinate responses, peer responses, and boss responses for each index. These aggregate scores were then recorded for each focal employee.
Instrumentation
The Denison Leadership Development survey (DLDS) was developed to provide a comparative measurement of leadership effectiveness. The instrument uses 96 survey items to determine levels of leadership traits of consistency, involvement, adaptability, and mission. Each of the four traits also contains three indices to measure specific aspects, such as adaptability and mission (see Figure 2). Leadership researchers contend effective leaders display behaviors associated with the traits of involvement, adaptability, consistency, and mission (Bass, 2008;
Bennis, 2003; Burns, 1978; Collins 2001; Hooijberg & Denison, 1996; Kotter, 2007). The organizational culture created by effective leaders promotes risk taking, teamwork, personnel development, and shared values (Collins, 2001; Goleman, 1998; Kotter, 2007; Kouzes and
Posner, 2002). Items on the instrument are all rated on a seven point Likert scale ranging from strongly agree to strongly disagree. Leadership effectiveness is also measured using seven questions with the items based on a seven-point Likert scale ranging from strongly agree to strongly disagree. The seven questions are: 1) Overall, this individual is a highly effective leader;
2) This individual’s leadership style serves as a role model for others in the organization; 3) This 54 individual has great potential as a future leader in our organization; 4) Overall, this individual is one of the most capable leaders in our organization; 5) This individual develops high quality relationships with internal and external customers; 6) This individual and his/her organization are consistently high performers; and 7) This individual is capable of leading the organization through future changes and transitions. Demographic items include the following: age, sex, education, job function, organization level, years with the organization, salary, and ethnic background and were operationalized as categorical data.
55
Figure 2. Denison Leadership Development Survey (DLDS) ©. This figure displays the attributes of each trait within the 360 degree instrument model. Adapted from Hooijberg & Denison, 1996. Validity and Reliability
Validity relates to whether the instrument measures what it is supposed to measure
(Davis, 2005; Mertler & Charles, 2008). The DLDS was tested for construct validity utilizing
confirmatory factor analysis. In confirmatory factor analysis, the relationships among variables
are specifically structured to confirm a pre-specified model (Mertler & Vannatta, 2005;
Tabachnick & Fidell, 2007). Confirmatory factor analysis revealed that the appropriate items fit 56
into each index as hypothesized and the twelve indices fit into the four traits defined by the
model (Hooijberg & Denison, 1996). Hooijberg and Denison (1996) tested for the presence of
three separate indices for each of the leadership traits. Results indicated the three-factor model fit
better for each trait than did a one-factor model. For the traits, the four factor model provided a
better fit than the one factor model (Hooijberg & Denison, 1996). All together, these results are
supportive of the hierarchical measurement model specifying 12 indices that form the four higher
order traits.
Reliability was determined by alpha coefficients. Reliability speaks to the consistency
among each item measuring the variables (Davis, 2005). Reliability can be measured via different techniques under three basic categories: test-retest, alternative forms and internal consistency (Davis, 2005; Mertler & Charles, 2008). Internal consistency, measured by
Cronbach’s alpha, is calculated from pairwise correlations (Davis, 2005). The coefficient alpha is typically the most common test for reliability (Henson, 2001; Peterson, 1994). Item homogeneity, or the degree to which items measure the appropriate construct, can be determined by internal consistency (Davis, 2005; Henson, 2001; Peterson, 1994). A high coefficient alpha implies consistency and that repeated administration of the instrument will yield the same or very similar results. The value of the coefficient ranges from 0 to 1.0. The higher the coefficient level,
a greater level of reliability (Davis, 2005).
Each trait of the DLDS was tested for reliability utilizing internal consistency in SPSS
PASW Statistics version 17. To determine the internal consistency of each trait, each trait was
segregated by rater. Reliability was also measured for combined rater scores. The mean for each trait by rater, including the combined scores, were also determined. The alpha coefficients for the traits range from .81 to .98 (see Table 2), indicating the instrument is reliable (Davis, 2005). 57
Effectiveness for self-report is possibly lower as individuals do not necessarily perceive themselves as having higher ratings on all effectiveness items. Other possible reasons may be self-raters tend to see themselves lower or have a different interpretation of items.
Table 2
Reliability Coefficients of Leadership Traits
Leadership Roles Self Direct Report Peer Boss Combined M Involvement .92 .97 .97 .96 .97 .96 Consistency .92 .97 .97 .96 .97 .96 Adaptability .92 .96 .96 .94 .96 .95 Mission .95 .98 .98 .97 .98 .97 Effectiveness .81 .96 .95 .93 .96 .92
Research Design
This study utilized a correlational research design to determine if relationships exist between leadership traits and leadership effectiveness ratings and if this relationship between traits and effectiveness varies among sectors. The study examined the relationship between four leadership traits (consisting of 12 subscale attributes) and seven items of leadership using an overall effectiveness score across the private sector, public sector, and nonprofit sector. This study also investigated if the relationship varies by sector. Although survey respondents participated at different times, the survey data from a particular leader was all collected at one point in time.
Data Analysis
Descriptive statistics were utilized to describe the mean and standard deviation of the four leadership traits and leadership effectiveness by sector. Frequencies of demographic information by sector group were determined by cross-tab descriptive statistics. Inferential statistics of analysis of variance (ANOVA), Pearson’s Product Moment Correlational Analysis, and Steiger’s (1980) test of significant different correlations were used to test hypothesized 58 relationships (see Table 3). Differences in leadership effectiveness among sectors were determined using ANOVA. The relationship of the four leadership traits (independent variable) to leadership effectiveness ratings (dependent variable) was used to analyze differences by sector for correlation coefficients between the four leadership traits and leadership effectiveness.
Table 3
Variables and Analysis by Research Question
IV DV Data Analysis RQ1 Leadership Traits-Quantitative Leadership Effectiveness – Pearson Quantitative Correlation RQ2 Sector Groups – Categorical Leadership Traits and Leadership ANOVA Effectiveness – Quantitative RQ3 Sector Group – Categorical Correlation Coefficients of Traits and Fisher’s Z Effectiveness
Differences in traits and leadership effectiveness ratings among groups were determined by utilizing analysis of variance (ANOVA). Because ANOVA compares the means of more than two groups (Tabachnick & Fidell, 2007), it was used for this study. Andersen (2010) utilized a pairwise t-Test to determine differences in leadership style between managers in private and public organizations. Since this study examined the differences in leadership traits among three organization types (private, public, and nonprofit), a one-way analysis of variance (ANOVA) was utilized with each group acting as the independent variable and each trait as a dependent variable. An ANOVA was conducted for each dependent variable (involvement trait, consistency trait, adaptability trait, and mission trait) to evaluate significant differences for each independent variable (private sector, public sector, and nonprofit sector).
Correlations between the four trait ratings and the leadership effectiveness ratings scaled from -1.0 (strong negative correlation) to +1.0 (strong positive correlation). Bivariate correlation 59
determined the relationship between the continuous ratings variables of trait ratings and
leadership effectiveness. The Pearson correlation coefficient is considered the most commonly
used test for relationship (Mertler & Vannatta, 2005). In a study examining the relationships
among organizational innovativeness and transformational leadership subscales, Jaskyte (2004)
utilized bivariate correlation. To test if the leadership effectiveness and leadership traits
correlation coefficients significantly differ by sector, Fisher’s Z transformation was conducted.
To transform correlation coefficients to Z scores the formula is:
2 Zr1-r = 𝑍𝑍1 − 𝑍𝑍 2
1 1 ��𝑛𝑛1 − 3� + �𝑛𝑛2 − 3� Fisher’s Z allows testing for the equality of the correlation coefficients from two independent samples (Marascuilo & Serlin, 1988; Wuensch, 2013). Considered a transformed
correlation, Fisher’s Z is primarily utilized to (1) test if observed correlations differ significantly from a theoretical value; (2) test if two observed correlations are significantly different; (3)
combine a number of independent estimates of a correlation into an improved estimate; and (4)
in situation 1 and 2 with average values (Fisher, 1970).
Summary
This chapter discussed the methodology used to analyze the research questions. The
instrument and its reliability and validity and data source are explained. For each research
question and statistical test, the dependent and independent variables were identified. Data
analysis and reasoning for each test statistic was explained. Particular attention was given to the
use of Fisher’s Z transformation. This methodology provides a narrative for reporting the results
in Chapter 4.
60
CHAPTER 4: RESULTS
Overview
The purpose of this study was to research the relationship of four primary leadership traits with ratings of leadership effectiveness and to determine if the traits and the relationship between traits and leader effectiveness differs among private, public, and nonprofit sectors. The
trait constructs of involvement, adaptability, consistency, and mission were measured via the
Denison Leadership Development Survey, an instrument developed by Denison and Neale
(1996). Specifically, this study investigated the correlation between the traits and leadership
effectiveness ratings based on the aggregated responses from the multi-rater instrument (See
Appendix C). Further, this study compared the means of the traits of the private, public, and
nonprofit sectors. Finally, the correlations between the traits and effectiveness were compared by each sector.
This chapter describes the procedures utilized to prepare the data for analysis then reports and discusses the findings in terms of the research questions. The chapter is organized into the following sections: data clean-up, descriptive analysis, and results. Reliability of the major study variables is also summarized. Finally, correlation analysis was utilized to determine the
significance and strength of the relationship between the traits and ratings of leadership
effectiveness. Analysis of variance testing investigates if statistically significant differences exist
among the sectors for each trait. The strength of correlations between the traits and effectiveness
ratings were then compared among the three sectors to determine if the relationship was stronger
in some sectors than others.
61
Data Screening
The data were screened following the protocol described by Tabachnick and Fidel (2007)
and Mertler and Vannatta (2005). Prior to screening, the variable for organization type was
consolidated from nine organization types (publicly listed, publicly listed subsidiaries, private
company, college or university, primary and secondary schools, U.S. Federal Government, U.S.
state and local government, nonprofit, unknown) to three – private, public, and nonprofit.
Organization types were consolidated utilizing SPSS versions 17, 21, and 22. A transformation
recode to a new variable was applied. Additionally, the seven items measuring leader
effectiveness (overall effectiveness, role model, potential as a future leader, capability, relational, consistent performers, and change agent) were aggregated into one variable representing the mean of the seven items. For the screening process, first the data set was examined for out of range values, missing values and outliers using SPSS Frequencies. Frequency tables for each
item of the combined trait variable and combined effectiveness variable were reviewed for valid ranges and missing data. Normality of the distributions was inspected through a visual review of histograms for each item (Appendix D). Missing value analysis in SPSS was used to examine missing data by case. Cases were evaluated to determine if data were missing from all the variables or a single variable. Cases were also evaluated for the randomness of missing data or if specific patterns existed. Upon review of the missing value analysis, 645 (7%) cases were identified with missing values on involvement, adaptability, consistency, mission, and effectiveness. Since data were missing for all variables, the cases were deleted. Further, another
440 (5%) cases missing values for the seven effectiveness items were deleted. After the elimination, 7,570 (88%) cases remained. Because the percentage of cases missing data was 62 relatively small in comparison to the dataset, deleting the missing cases was deemed acceptable
(Tabachnick & Fidell, 2007).
Next, the data were examined for normality for each trait and the ratings of effectiveness variable. Analysis indicated levels of skewness and leptokurtosis of the traits. Because of the large sample size, skewness and kurtosis were based more on visual appearance of the distribution than the level of significance. With large samples, skewness and kurtosis standard errors decrease; likewise the significance level is less relevant than the shape of the distribution or the actual skewness or kurtosis value (Tabachnick & Fidell, 2007). Finally, an analysis was performed on the dataset prior to the elimination of cases as well as after data clean-up.
Correlations and ANOVAs performed on the database prior to screening were compared to results post screening. The comparison indicated no difference in the statistical significance of the results.
Descriptive Analysis
Because the purpose of this research was to investigate leadership traits and effectiveness among the private, public, and nonprofit sectors, the descriptive analysis of the sample focused on the characteristics by sector. Appendix E provides information based on the non-segregated data set. Frequency reports indicated 78.7% of the organizations represented were private sector organizations with 13.7% reported as public organizations and 7.6% as nonprofits as indicated in
Appendix F. Of the 7,570 cases, ages of the respondents ranged from 20 to over 60. Within the age range, 41% were between 40 and 49 and 31.7% were between 30 and 39. Males represented
70% of the respondents and females 24% with 6% opting not to respond. Further, 72.8% were
White, 5.1% Asian, 2.6% Hispanic, 1.4% African American, 3.6% other, and 14.4% chose not to respond. Survey participants were reported primarily to be in middle management (29.2%), 63 senior management (23%), and line management (22.7%). Years with organization ranged from less than six months to more than 15 years, with the highest percentage at 20.5% serving more than 15 years. Education levels ranged from high school graduate to doctoral degree attainment.
The majority of respondents held bachelor degrees at 29.1% while 26.8% reported holding a master’s degree. A summary of the cases is detailed in Appendix E.
Demographics by Sector
The Chi-square test for independence examined if there were relationships between the variables (Gravetter & Wallnau, 2008). The demographic data showed a significant difference in the demographic characteristics among the private, public, and nonprofit sectors. In examining the demographic characteristics segregated by sector (Table 4), there was a notable difference in the salary range, χ2 (18, n = 18,042) = 611.7, p<.001. For the private and public sectors, the highest percentage of respondents was in the $100,001 to $150,000 range (21.9% and 28.5% respectively). In contrast, the highest percentage of respondents from the nonprofit sector was in the $50,000 to $75,000 salary range at 26.5%. The analysis indicated that job function also differed by sector, χ2 (22, n=18,030) = 1,339, p<.001. For the private sector, the majority of respondents (19.4%) were in sales and marketing functions. In the public and nonprofit sectors, the majority of respondents classified their job function as professional staff (22.9% and 30.9% respectively). Table 4 displays salary, job function, and organization level by sector.
64
Table 4
Participant Characteristics by Sector
Private Public Nonprofit Χ2 Characteristics (n = 4,916) (n = 507) (n = 500) Salary 612 25,000 or less .4 - .2 25,001 to 35,000 1.0 .4 .6 35,001 to 50,000 4.0 3.2 7.4 50,001 to 75,000 12.6 16.8 26.5 75,001 to 100,000 16.2 18.6 23.0 100,001 to 150,000 21.9 28.5 12.0 150,001 to 200,000 9.8 8.7 4.6 200,001 plus 9.4 6.1 5.6 No response 24.7 17.8 20.0 Function 1,339 Administration 6.0 14.2 23.8 Engineering 7.9 5.7 2.2 Finance and Accounting 10.8 11.2 7.8 Human Resources 4.8 7.3 5.0 Manufacturing and Production 10.2 4.3 2.0 Professional Staff 14.5 22.9 30.9 Purchasing 2.1 .8 .2 Research and Development 7.9 7.1 2.2 Sales and Marketing 19.4 14.4 9.0 Support Staff 4.3 3.0 2.6 Organizational Level 108 Non-management 3.7 5.7 3.4 Line management 23.5 23.7 24.4 Middle management 29.7 29.8 29.4 Senior management 22.3 20.7 18.6 Executive/Senior Vice 9.1 11.0 11.0 CEO/President 2.5 2.4 2.4 Owner 1.5 .6 - No Response 7.6 5.2 10.8 X2 p <.001 65
Table 5 provides the details of age, gender, ethnicity, years with the organization and
education. Age was concentrated in the 40 to 49 category for the private (41.0%) and nonprofit
sectors (39.6%), but for the public sector 33.9% were in the 30 to 39 age group, χ2(12, n=18,082)
= 327, p <001. Respondents for all three sectors were predominantly male, white, with over 15 years tenure with the organization, and at least a bachelor’s degree.
A closer review of the data contained in Table 5 disclosed trends within the demographics. Tenure within the organization was the highest for the public sector with 24.3% of the sample with more than 15 years. This compared to 19.7% for the private sector and 19.0% for the nonprofit sector with more than 15 years with the organization, χ2 (18, n=18,079) = 75,
p<.001. Of note was the gender mix of the nonprofit sector compared to the private and public
sectors. Although not a majority, the nonprofit sector had a higher percentage of female
respondents than the private and public sectors, χ2 (6, n=18,080) = 278, p<.001.
66
Table 5
Demographics Characteristics by Sector (Percentages)
Private Public Nonprofit X2 Characteristics (n = 4,916) (n = 507) (n = 500) Age 327 20-29 3.8 3.7 1.0 30-39 32.8 33.9 19.4 40-49 41.0 19.5 39.6 50-59 15.7 18.9 27.8 60 or over .8 1.4 2.8 No response 6.0 5.1 9.4 Gender 278 Female 22.3 27.8 39.4 Male 71.7 67.5 51.4 No Response 6.0 4.7 9.2 Ethnic Background 141 Asian 5.2 4.3 5.4 African American 1.3 2.6 1.6 Hispanic 3.0 1.2 .2 White/Caucasian 72.0 76.5 74.6 Other 4.0 7.9 2.4 No response 14.6 12.8 15.7 Years with Organization 75 Less than 6 months 2.3 .8 1.6 6 months to 1 year 4.5 3.6 5.4 1 to 2 years 9.3 7.1 9.4 2 to 4 years 15.9 17.4 15.8 4 to 6 years 13.6 14.4 11.2 6 to 10 years 14.7 15.0 16.0 10 to 15 years 14.1 13.0 12.4 More than 15 years 19.7 24.3 19.0 No response 6.0 4.5 9.2 Education 250 High school 4.0 5.9 2.6 Some College 11.2 7.1 8.4 Associate’s/Technical 4.3 4.5 7.4 Bachelors 28.8 32.1 26.4 Some graduate work 6.9 13.8 10.2 Master’s degree 27.0 22.9 25.2 Doctoral degree 10.3 8.1 8.0 Other 1.3 .8 1.8 No response 6.0 4.7 1.0 Χ2 p < .001
67
The means and standard deviations for each trait variable and the effectiveness variable
are reported in Tables 6 and 7. Table 6 indicated the descriptive statistics of the variables for the
data without segregation by sector. In contrast, Table 7 displays the means and standard
deviations of the variables separated by sector.
Table 6
Descriptive Statistics of Traits and Effectiveness
Variable N M SD Combined Other Involvement 7,432 5.62 .52 Combined Other Consistency 7,441 5.70 .48 Combined Other Adaptability 7,438 5.66 .46 Combined Other Mission 7,408 5.56 .51 Combined Other Effectiveness 7,568 5.59 .70
Table 7
Descriptive Statistics of Traits and Effectiveness Segregated by Sector
Variable Private Sector Public Sector Nonprofit Sector N M SD N M SD N M SD Involvement 5,469 5.61 .50 960 5.69 .56 530 5.73 .52 Consistency 5,476 5.69 .47 962 5.75 .51 530 5.82 .49 Adaptability 5,474 6.86 .45 962 5.72 .49 529 5.77 .46 Mission 5,449 5.54 .50 956 5.60 .55 530 5.69 .51 Effectiveness 5,581 5.57 .69 973 5.63 .72 541 5.71 .70
Reliability Analysis
The DLDS instrument was subjected to reliability testing using Cronbach’s coefficient
Alpha (α). Cronbach’s Alpha was used to determine levels of reliability due to its robustness and consistency regardless of research design (Peterson, 1994). It is an internal consistency technique to determine reliability and is widely used in research (Cronbach, 1951; Davis, 2005;
Henson, 2001; Peterson, 1994). As Cronbach stated, “A reliability coefficient demonstrates whether the test designer was correct in expecting a certain collection of items to yield 68
interpretable statements about individual differences” (p. 297). The coefficient alpha computes
the mean reliability coefficient estimates for all possible ways of splitting a set of items in half
(Cronbach, 1951; Davis, 2005; Fraenkel & Wallen, 2009). In this study, Cronbach’s α tested whether the DLDS items were sufficiently interrelated to justify their combination in the scale. If the individual items were highly correlated, then there was strong evidence that the items were
measuring the same underlying trait and therefore the scales had a high (or good) reliability. The
higher the coefficient level the greater the reliability. Cronbach (α) coefficient ranged from 0 to
1.0 with 0 being no consistency among items and 1.0 being perfectly reliable (Davis, 2005;
Mertler & Charles, 2008). The reliability coefficients are displayed in Table 8.
Table 8.
Reliability Coefficients of Leadership Traits and Effectiveness
Leadership Roles Self Direct Report Peer Boss Combined M Involvement .92 .98 .97 .96 .98 .96 Consistency .91 .97 .97 .96 .97 .95 Adaptability .92 .97 .96 .94 .96 .95 Mission .95 .98 .98 .97 .98 .97 Effectiveness .80 .96 .95 .93 .96 .91
The reliability coefficients for each trait and effectiveness scales were calculated for each
respondent group as well as aggregated. The alpha values for the respondent groups ranged from
.80 to .98, all indicating good internal consistency reliability. The respondent groups’ combined
alpha values ranged from .96 to .98 for the leadership traits, similar to the initial reliability
analysis as indicated in Table 2 in Chapter 3. All alpha values were .80 or higher, indicating
strong internal consistency. The reliability coefficient for effectiveness for the self-rating was the lowest at .80. The alpha coefficients were considered within the minimum recommended reliability level of .80 for basic research (Cronbach, 1951; Peterson, 1994). 69
Inferential Statistics
In order to answer the three research questions a series of correlations, ANOVAs and independent samples comparisons of the correlation coefficients were tested. Table 9 identifies the research questions, independent variables, dependent variables, and statistical analysis.
Table 9
Variables and Analysis by Research Question IV DV Data Analysis RQ1 Leadership Traits- Leadership Effectiveness – Pearson Correlation Quantitative Quantitative RQ2 Sector Groups – Leadership Traits and Leadership ANOVA Categorical Effectiveness – Quantitative RQ3 Sector Group – Correlation Coefficients of Traits Fisher’s Z Categorical and Effectiveness
Research Question 1: Are the leadership traits of adaptability, mission, consistency, and
involvement significantly related to leadership effectiveness ratings?
To answer the first research question; Pearson product-moment correlation coefficient
(often referred to as Pearson’s r or Pearson’s correlation) was utilized. Pearson’s r takes two
variables and describes the strength of the relationship (Gravetter & Wallnau, 2008; Mason,
1986). As a numerical value, the correlation (r) characterizes the relationship three ways: (1)
the direction; (2) linear form; and (3) the strength or consistency (Gravetter & Wallnau, 2008).
As the characteristics pertain to direction, the variables in a positive correlation move in the same
direction. If the variables move in opposite directions, there is a negative correlation or an
inverse relationship. The form characterizes the linearity, or how the variable points cluster
around a straight line. Finally, a numeric value describes the strength of the correlation. A value
of 1.00 (either +1.00 or -1.00) indicates a perfect correlation whereas a value of 0 indicates no
relationship (Gravetter & Wallnau, 2008). 70
As seen in table 10, leadership effectiveness was highly and positively correlated with
each of the traits. As table 10 indicates, the correlations range between .817 and .834 (p <.01). It
is interesting to note that the traits were also highly and positively correlated with each other.
The consistency trait and the involvement trait had the highest correlation (r=.884, p< .001 significance level).
Table 10 Correlation Results between Traits and Ratings of Effectiveness
Variable Effectiveness Mission Adaptability Consistency Involvement Effectiveness .827* .817* .834* .828* Mission .863* .836* .858* Adaptability .841* .823* Consistency .884* *Correlation is significant at the 0.01 level (2-tailed). Mission n = 7,406, adaptability n = 7,435, consistency n = 7,439, involvement n = 7,430.
Research Question 2: Do leadership traits of adaptability, mission, consistency and
involvement significantly differ by sector?
This research question was answered by analysis of variance (ANOVA) with each trait as
the dependent variable and the sector type as the independent variable. The purpose was to test
for significant differences of the traits among the sectors. Separate ANOVAs were conducted for
involvement, consistency, adaptability and mission. Post hoc testing was further utilized to
determine which of the sectors were significantly different within each trait.
ANOVA determines how different scores are from each other for two or more groups
(Davis, 2005). The test statistic used for ANOVA is the F-ratio which is based on the between
group and within group variance. When the F-ratio value is larger, the ratio of between group
variance over within group variance is large, therefore, more between group variance, resulting
in a larger effect. The size of the effect combined with sample size determines if mean difference 71
is due to chance alone (Gravetter & Wallnau, 2008). The total variance is determined by the
between group variance and the within group variance. The differences between the sample
means of the groups is the between group variance. The variance measured inside each group
determines the within-group variance (Davis, 2005; Gravetter & Wallnau, 2008). The within
group variance estimates how much of the total variance (or difference) is due to chance in each
sample.
An advantage of ANOVA is that it allows for comparison of samples that are of different
size (Gravetter & Wallnau, 2008). It needs to be noted that when ANOVA is used for
independent measures, as in this study, three assumptions need to be met: (1) the samples must
be independent; (2) the populations from which the samples are taken need to be normal; and (3) the populations of the samples must have homogeneity of variance (Gravetter & Wallnau, 2008;
Mason, 1986). Because of the large sample size of this study, normality is not of concern
(Gravetter & Wallnau, 2008). With large sample sizes for grouped data, the Central Limit
Theorem allows researchers to assume a normal distribution (Tabachnick & Fidell, 2007). The
Central Limit Theorem states if the sample size is sufficiently large a sampling distribution of the means will approximate normal distribution even if the population is not normally distributed
(Mason, 1986; Tabachnick & Fidell, 2007). The distribution of the sample mean moves closer to a normal distribution (bell-shaped) as the sample size increases (Mason, 1986). Because the samples are segregated by sector, the independence of samples assumption is met. Levene,
Welch, and Brown-Forsythe tests were used to test homogeneity (Appendix G). Each of the tests indicated the homogeneity assumption failed. If any of the assumptions of ANOVA cannot be met, the Kruskal-Wallis one-way analysis of variance by ranks can be used. For the present 72
study, the Kruskal-Wallis analysis of variance was utilized as a comparative test to the ANOVA
results. As with ANOVA, Kruskal-Wallis is not without limitations.
The only caveat with Kruskal-Wallis is that all samples from the population need to be
independent and therefore can be used if homogeneity of variance is violated (Lowery, nd;
Mason, 1986). Additionally, the Kruskal-Wallis test assumes the populations of each group have
the same shape therefore if the groups have different shapes (one skewed to the right, one
skewed to the left) the Kruskal-Wallis test results may be inaccurate (Van Hecke, 2010). In the
case of this study, the dependent variable has the same shape across the sectors.
The test combines the sample values then orders the combined values from low to high.
Finally, the ranks starting with 1 for the smallest value replace the ordered values (Lowery, nd).
If each sample size is at least five, the H statistic is close to the chi-square distribution with k – 1
degrees of freedom. When this is the circumstance, the chi-square can be used to formulate the
decision rule (Mason, 1986). The H statistic formula is:
2 12 (Tg)
H = — 3(N+1)
( ) N(N+1) ng
If the H value is higher than the critical value for the appropriate level of degrees of freedom at
the p < .05 level, the means of the groups are significantly different.
For this study, ANOVAs were utilized to determine if the four traits are significantly
different by each sector. The ANOVA results were all significant at the p < .001 level with
results summarized in Table 11. Table 12 provides the means for each trait by sector. This provides an affirmative response to research question two: significant differences do exist in 73 leadership traits among the private, public, and nonprofit sectors. Bonferroni post hoc tests were conducted to determine which sectors were significantly different for each of the traits. The
Bonferroni adjustment was chosen because it can be used when sample sizes differ and the family-wise α level is maintained for each sample, thereby reducing the risk of a type I error
(Castañeda, Levin & Dunham, 1993; Harris, 1995). Results revealed that for the involvement trait, the private sector was significantly different from the public (p <.001), with the public sector having the higher mean score. There was a significant difference between the private and nonprofit sectors (p <.001) with the nonprofit sector having the higher mean score. However, there was no significant difference in the involvement trait between the public and nonprofit sectors. The Bonferroni post hoc test indicated the private and public sectors significantly differed from each other for the consistency trait (p <.001) with the public sector having the higher mean score. The private and nonprofit sectors significantly differed from each other for the consistency trait (p <.001) with the nonprofit sector having the higher mean score. The public and nonprofit sectors significantly differed from each other for the consistency trait (p =
.02) with the nonprofit sector having the higher mean score. Similarly to the involvement trait, the post hoc test indicated that for the adaptability trait, the private sector differed significantly from the public (p <.001) with the public sector having the higher mean score. The private and nonprofit sectors differed significantly (p <.001) with the nonprofit sector having the higher mean score. There were no significant differences between the public and nonprofit sectors. A significant difference was indicated for the mission trait for the private sector and the public sector (p = .02) with the public sector having the higher mean score. There was significant difference in the mission trait between the private and nonprofit sectors (p<.001) with the 74
nonprofit sector having the higher mean score. There was also significant difference between the
public and nonprofit sectors (p<.003); the nonprofit sector having the higher mean score.
Table 11
ANOVA Results for Traits
Source SS df SS df MS F p ES Between Within Involvement 10.44 2 1,825.51 6,965 5.22 19.88 <.001ab .06 Consistency 10.80 2 1,589.27 6,965 5.40 23.64 <.001abc .07 Adaptability 10.11 2 1,444.04 6,962 5.05 24.36 <.001ab .07 Mission 13.26 2 1,796.27 6,932 6.63 25.60 <.001abc .07 p < .05 aIndicates significant difference among private and public sectors bIndicates significant difference among private and nonprofit sectors cIndicates significant differences among public and nonprofit sectors
Table 12
Trait Means by Sector
Private Public Nonprofit Trait N M SD N M SD N M SD Involvement 5,469 5.6 0.5 960 5.7 0.6 530 5.7 0.5 Consistency 5,476 5.7 0.5 962 5.8 0.5 530 5.8 0.5 Adaptability 5,474 5.7 0.5 962 5.7 0.5 529 5.8 0.5 Mission 5,449 5.5 0.5 956 5.6 0.6 530 5.7 0.5 p<.05
Because of the aforementioned violation of the homogeneity assumption, the Kruskal-
Wallis test was also used to verify the statistical significance among the sectors for each trait. To corroborate the results from the ANOVAs, the Kruskal-Wallis one-way analysis of variance by ranks (Kruskal-Wallis) was utilized to examine if there were significant differences between the traits and the different sectors. When investigating the second research question – do the traits differ by sector; the results from the ANOVA and Kruskal-Wallis indicated the traits are significantly different by the private, public, and nonprofit sectors. 75
The Kruskal-Wallis testing results supported the ANOVA results that significant
differences exist among the sectors for each trait. These results are summarized in Appendix H.
The same patterns emerged with the Kruskal-Wallis test as with the ANOVA testing. Research
question two, therefore, has been answered in the affirmative – leadership traits of involvement,
consistency, adaptability and mission do differ significantly among the private, public and
nonprofit sectors.
Although the ANOVA homogeneity assumption failed, ANOVA results are reported for four main reasons. First, the ANOVA and Kruskal-Wallis results are comparable. Second, because the Kruskal-Wallis test uses the median and not the means of a sample, there is no post hoc testing to determine how the groups significantly differ (Van Hecke, 2010). Third, ANOVA is a robust test therefore with large sample sizes the ANOVA test is valid and not as sensitive to heterogeneity of variance with large sample sizes (Gravetter & Wallnau, 2008; McGuinness,
2002).
Research Question 3: Do the correlation coefficients of leadership traits with leadership effectiveness significantly differ by sector?
For the third and final research question, the relationship between the leadership traits and ratings of leader effectiveness were examined to determine if significant differences in the correlations exist among the private, public and nonprofit sectors. In order to ascertain if there are differences by sector in the correlations, the correlation coefficients determined from research question one were transformed into z- scores using Fisher’s z transformation (also known as Steiger’s transformation). By transforming the coefficient to a z score, two correlations from two independent samples with different sample sizes, can be tested for significance (Wuensch, 2013). 76
Fisher’s z transformation is used to determine confidence intervals on the difference between two correlations. In the case of this study the transformation was used to compare the
correlations of traits and leader effectiveness for each sector. For example, the correlation between the involvement trait and leader effectiveness ratings was compared by the private and
public sector, the private and nonprofit sector and the public and nonprofit sector. By
transforming the correlations, significant differences among the sectors can be determined.
In its basic form, the Fisher r transformation takes the correlation coefficient (r) and calculates a
z-value. Once calculated the z-value can be used to determine if significant differences are found
in two independent samples. The correlation coefficient (r) for each trait and ratings of
effectiveness for each sector is transformed into a z-score with the formula:
=
𝟏𝟏 𝟏𝟏+𝒓𝒓 The correlation coefficients for each 𝒛𝒛trait/effectiveness𝟐𝟐 𝐥𝐥𝐥𝐥 𝟏𝟏−𝒓𝒓 were compared to the critical value of ±1.96 two sectors at a time. For example, the transformed r for the private sector for the
trait/effectiveness of involvement was compared to the transformed r for the public sector
trait/effectiveness of involvement. The result was the Fisher’s z test value. The test value was compared to the critical value (Figure 3) for z scores for α of .05 (two tailed). First, each
correlation coefficient was converted into a z-score using Fisher's r-to-z transformation. Then,
using the sample size from each coefficient, the z-scores were compared using formula 2.8.5
from Cohen and Cohen (1983, p. 54). The Fisher’s test value was calculated by:
~ 𝒛𝒛𝟏𝟏 + −𝒛𝒛𝟐𝟐 𝒛𝒛 𝟏𝟏 𝟏𝟏 �� �𝒏𝒏𝟏𝟏 − 𝟑𝟑� � �𝒏𝒏𝟐𝟐 − 𝟑𝟑� 77
Where z1 was the transformed correlation coefficient for the first group (e.g., private sector) for a particular trait (e.g., involvement) and, z2 was the transformed correlation coefficient of the second group (e.g., public sector) for the same trait (e.g., involvement).
Figure 3. The normal distribution curve showing standard z scores with the critical values of ±1.96 with α = .05, two tailed.
Based on the transformation, there were significant differences in the correlation coefficients of traits and effectiveness by sector. Table 13 presents the sector comparisons of the correlations between the traits and effectiveness and any significant difference of the correlations from sector to sector. The results indicated no significant difference existed for the involvement trait among the private, public and nonprofit sectors. The z values for correlation comparisons were below the critical value of ±1.96, α = .05 (two tailed).
Table 13
Fisher’s Z Test Values
Correlations Sector Samples Private/Public Private/Nonprofit Public/Nonprofit Involvement- Effectiveness -0.91 -0.28 .36 Consistency- Effectiveness -3.37 * -0.78 1.52 Adaptability- Effectiveness -3.69 * .92 3.16 * Mission- Effectiveness -3.46 * -.20 2.07 * *p<.05
The consistency trait/effectiveness correlation indicated a significant difference between the private and public sectors with a z value of -3.37 which was greater than the critical value of 78
±1.96, α =.05 ( two tailed). The value of -3.37 indicates the relationship is stronger for the public
sector than for the private sector. However, the correlations from the private and nonprofit sectors and the public and nonprofit sectors for the consistency trait were not significantly different with a -.78 z value, and a 1.52 z value, respectively, which were less than the critical value of ±1.96, α = .05.
The correlations for the trait of adaptability differed significantly among the private and public sectors and the public and nonprofit sectors. The z test value for the private and public sectors was -3.69, greater than the critical value of ±1.96, α = .05. Because the value is a negative, the public sector’s relationship was stronger than the private sector’s. Between the private and nonprofit sectors the z test value was .92, less than the critical value of ±1.96, α =
.05, indicating no significance. There was a significant difference between the public and nonprofit sectors with a z value of 3.16, greater than the critical value of ±1.96, α = .05. The positive value indicated the relationship was stronger for the public sector.
As with the adaptability trait, mission was significantly different among the private and
public sectors and the public and nonprofit sectors. Between the private and public sectors, the z
value was -3.46, greater than the critical value of ±1.96, α = .05, with the public sector
relationship greater than the private sector. The z value for the private and nonprofit sectors was
not significant at .20, critical value of ± 1.96, α = .05. The correlation of the mission trait was
also significantly different for the public and nonprofit sectors with a z value of 2.07, critical
value of ± 1.96, α = .05, indicating a stronger relationship at the public sector.
The results from research question three yielded mixed results. The relationship between
adaptability and leadership effectiveness and mission and leadership effectiveness significantly
differed among the private and public and public and nonprofit sectors. However, as displayed in 79
Table 13, the z values between involvement and leader effectiveness indicated no significant
difference in the relationship among the sectors. The consistency trait and effectiveness
correlations showed a significant difference between the private and public sectors, but no
significant difference between the private and nonprofit sectors and the public and nonprofit
sectors. The relationship between consistency and leadership effectiveness was significant and
stronger for the public sector than for the private sector. The correlation between adaptability and
effectiveness was significantly stronger for the public sector than for the private sector. The
nonprofit sector correlation was also significantly stronger than the private sector for the
adaptability and effectiveness correlation. For the mission-effectiveness correlation, the
relationship was stronger for the public sector than the private sector. The mission and
effectiveness correlation was significantly stronger for the public sector than the nonprofit sector.
Tables 14, 15 and 16 summarize the correlations by sector, indicating significance.
Table 14
Correlations for Private Sector
Variable Involvement Consistency Adaptability Mission (n = 5,467) (n = 5,474) (n = 5,472) (n = 5,447) Effectiveness .824 .827a .810ab .820a Involvement .880 .811 .854 Consistency .835 .828 Adaptability .848 a Indicates significance with public sector b Indicates significance with nonprofit sector *Correlation is significant at the 0.01 level (2-tailed).
80
Table 15
Correlations for Public Sector
Variable Involvement Consistency Adaptability Mission (n = 960) (n = 962) (n = 962) (n = 956) Effectiveness .834 .860b .850bc .856bc Involvement .898 .865 .873 Consistency .882 .875 Adaptability .908 b Indicates significance with private sector, c Indicates significance with nonprofit sector, *Correlation is significant at the 0.01 level (2-tailed).
Table 16
Correlations for Nonprofit Sector
Variable Involvement Consistency Adaptability Mission (n = 530) (n = 530) (n = 529) (n = 530) Leadership .828 .837 .795a .823a Effectiveness Involvement .894 .837 .868 Consistency .825 .847 Adaptability .883 a Indicates significance with public sector, *Correlation is significant at the 0.01 level (2-tailed).
Summary
The purpose of this study was to determine if there were differences in leadership traits among the private, public and nonprofit sectors. Results suggest there were significant differences in ratings of leadership traits among the private, public and nonprofit sectors. Results from the Pearson correlations confirmed the traits are highly correlated with ratings of leadership effectiveness, answering the first research question. To answer the second research question, the results from the ANOVAs showed significant differences for each trait among each of the sectors. Although significant differences were found for research question three results, the sector to sector comparison results showed some convergence among sectors exists.
For research question 1, the bivariate correlations between the traits and leadership 81
effectiveness ratings ranged from .817 between adaptability and effectiveness to .834 between
consistency and effectiveness. These findings suggest an affirmative answer to the research
question; there is a strong positive relationship between the traits of involvement, consistency,
adaptability and mission and ratings of leadership effectiveness.
In order to answer the second research question: do leadership traits of adaptability,
mission, consistency and involvement significantly differ by sector; a one-way analysis of
variance was conducted with the sectors as the independent variables and the traits as the
dependent variables. The results of the ANOVA indicated significant differences among the
sectors for each trait. More specifically, the Bonferroni post hoc adjustment indicated
significantly greater mean differences for the public and nonprofit sectors for the involvement
trait than the private sector. The same trend was reported for the adaptability trait. The post hoc
tests also indicated significant differences among the private, public and nonprofit sectors for the
consistency trait. Similarly, the post hoc comparisons found significant differences for the
mission trait among all the sectors.
Research question three investigated if the correlations between the traits and ratings of
leader effectiveness (from research question one) differed by sector. The results were mixed. The
results indicated no significant difference among the sectors for the involvement-effectiveness
relationship. The z values for the consistency-effectiveness correlation indicated a significant difference between the private and public sectors. There were significant differences among the
private and public and public and nonprofit sectors for the adaptability-effectiveness. Likewise,
the mission-effectiveness relationships indicated significant differences among the private and public sectors and the public and nonprofit sectors.
In summary, the results from this study indicate that differences regarding leadership 82 traits and effectiveness exist among the private, public and nonprofit sectors. As expected, there was a high, positive correlation between leadership traits and ratings of leadership effectiveness.
Likewise, the results from ANOVA testing supported differences between the sectors for each of the traits. Similarly, correlations between traits and effectiveness by sector indicated differences do exist in a sector by sector comparison, although not across the board.
The next chapter summarizes the findings detailed in this chapter and how the results compare to existing literature. There is also a discussion of the implications of these findings for practitioners and researchers. Additionally, considerations for future research are presented.
83
CHAPTER 5: DISCUSSION, RECOMMENDATIONS AND CONCLUSION
Introduction
This chapter summarizes the purpose of the study and its contribution to the existing literature as well as discusses the findings and implications for leadership practice, offers recommendations for future research, and draws conclusions. Utilizing data from the DLDS and the Denison framework, three research questions focused on leadership traits and ratings of leader effectiveness were investigated. The first section provides a review of the study including the significance for research and practice. This is followed by a discussion of the findings from the statistical analysis and includes interpretation of the findings in relation to the literature, as well as, inferences drawn from the results. Implications for leadership practice—
personnel development, hiring practices, and use of leadership models— are contained in the next section. Limitations of this study and recommendations for future research are discussed following. The last section provides conclusions drawn from the research.
Summary of the Study’s Purpose and Importance
As a reminder to the reader, the purpose of this study was to examine the relationship between leadership traits and ratings of leadership effectiveness and to determine if the relationship differed among the private, public, and nonprofit sectors. Utilizing the Denison
(1996) framework and the multi-rater instrument developed for the framework, this study investigated aggregated ratings of leadership traits of involvement, consistency, adaptability, and mission as well as ratings of leadership effectiveness. From a data set of participants of the
Denison Leadership Development Survey questionnaire, 7,570 cases were analyzed. The respondents represented leaders, peers, followers, and bosses working within private, public, and nonprofit organizations. 84
Although the definition of leadership and leader effectiveness remains varied, this study
indicates that there is a relationship between leadership traits of involvement, adaptability,
consistency, and mission and leadership effectiveness. The findings from this study are consistent with existing comparative research such as investigating leader behaviors, decision making, and employee motivation providing empirical support that leadership and leader effectiveness differs among the private, public, and nonprofit sectors (Andersen, 2010; Hooijberg
& Choi, 2001; Noordegraaf & Stewart, 2000). Comparative research is sparse and limited to comparing the private and public and/or nonprofit sectors. The existing literature has also not differentiated between the public and nonprofit sectors. Rainey (1983) and Rainey and Bozeman
(2000) criticized comparative research for having too small and narrow of samples (particularly the public sector), lack of utilization of formal theories and framework, and not properly defining and differentiating the public sector. Mitigating the criticisms of existing empirical research, the present study utilized a large sample size, defined each of the three sectors, and utilized a formal framework characterizing leadership traits and leadership effectiveness. The study contributes to the comparative literature by examining leadership in the private, public, and nonprofit sectors in one study, thereby addressing this gap.
Findings from the study provide empirical support to the assertion that leadership traits and leader effectiveness differ among the private, public, and nonprofit sectors. These findings can be beneficial to organizations when hiring and developing personnel migrating from one sector to another. Additionally, even though the findings suggest differences, some similarities were also reported. This can be of benefit to leaders when relating to board members, funders, and staff members while improving leader effectiveness.
85
Discussion of Findings
This section presents a summary of findings from this study, detailed in Chapter 4. The section is divided by research question first addressing the relationship between each trait and ratings of effectiveness and how the results compare with existing literature. Next, how the traits differ among the sectors and the relevance to prior research will be discussed. Finally, how the relationship between traits and effectiveness differs by sector will be summarized.
Traits and Ratings of Effectiveness
Are the leadership traits of adaptability, mission, consistency and involvement
significantly related to leadership effectiveness ratings? As expected, the results from the
correlation analysis in Chapter 4 revealed a strong positive relationship between the traits of the
Denison (1996) framework and respondents’ ratings of leadership effectiveness (RQ1). This
study supports the research of Hooijberg and Denison (1996) and Hooijberg and Choi (2001),
correlating multiple leader traits with leadership effectiveness ratings. Whereas the Hooijberg and Denison study considered three leadership effectiveness items, and Hooijberg and Choi
(2001) considered five effectiveness items. The present study utilized the mean of seven effectiveness items.
The high level of correlation can be partially explained by the dynamics of the framework. Instead of measuring leadership in terms of transformational, transactional, contingent, situational, and/or laissez-faire behaviors, the leadership traits in this study combine transformational and transactional characteristics (Denison & Mishra, 1995). Interestingly, despite contemporary theory of the effectiveness of transformational leaders over transactional behaviors, the results from this study support the research indicating that effective leaders are not 86
necessarily all one or all the other (Bass, 2008; Denison et al., 1995; Hersey & Blanchard, 1996;
Yukl, 1981).
Even though the study of leadership has existed for centuries, as noted in Chapter 2, there
is still no agreement on what characteristics define leadership and what determines an effective
leader. The link between a leader’s behaviors and effectiveness has been focused on what some
researchers such as Bass (2008), Burns (1978), Howell and Avolio (1993), and Kouzes and
Posner (2002) termed transformational. These behaviors have been measured through
instruments such as the Multiple Leadership Questionnaire (MLQ) and the Leadership Practices
Inventory (LPI). Such instruments rate a leader as either transformational or transactional. The
implication from such studies has been effective leaders practice transformational behaviors
while those scoring high in transactional behaviors are less effective (Bass, 1999, 2008; Bass &
Avolio, 1993; Burns, 1978; Howell & Avolio, 1993; Kouzes & Posner, 2002).
A movement in the study of leadership considered leader effectiveness with followers’
needs and productivity/people balance (Blake & McCanse, 1991; Blake & Mouton, 1975; Hersey
& Blanchard, 1996). However, these studies did not investigate effectiveness relative to the
sectors. Others such as Denison et al. (1995), Blanchard and Hersey (1996), Hooijberg and
Quinn (1995), Vroom and Jago (2007), Yukl (1981) argued leader effectiveness was related to the leader’s situation and/or environment. The present study supports the prior research that the relationship between leadership traits and effectiveness ratings differed by sector. Effective leaders utilized different behaviors depending on the situation and/or stakeholder (Denison et al.,
1995; Hooijberg & Quinn, 1995; Vroom & Jago, 2007; Yukl, 1981). Additionally, leaders in more normative and procedural environments, such as the public sector, received higher 87
effectiveness ratings when transactional leadership behaviors were used (Blanchard & Hersey,
1996). .
One explanation for the high correlation between the traits and leader effectiveness is the theory that effective leaders possess multiple characteristics (Bennis, 2003; Bennis & Nanus,
1985; Kouzes & Posner, 2002; Van Wart, 2003; Yukl, 1981). The research focusing on multiple dimensions of leadership and the relationship to leadership effectiveness, although limited, was further explored by Bolman and Deal (1991) and Hooijberg and Choi (1998, 2001). The results of the present study support the research Bolman and Deal (1991) and Hooijberg and Choi
(1998, 2001), who also found specific factors/frames and leader values highly correlated to ratings of leader effectiveness. Additionally, the research by Bolman and Deal and Hooijberg and Choi investigated the relationship utilizing samples from various sectors.
Trait Differences Among Sectors
Do leadership traits of adaptability, mission, consistency and involvement significantly differ by sector? The results from research question 2 indicate there are significant differences between the sectors for the leadership traits. Worth noting, the post hoc adjustments indicated that not all sectors significantly differed for each trait (Table 17). The private sector differed significantly from the public and nonprofit sectors for all traits. However, significant differences did not exist for involvement and adaptability when examining the post hoc adjustments between the public and nonprofit sectors. One reason for the lack of statistical significance between the public and nonprofit sectors for the involvement and adaptability traits may be funding and compliance policies required for public funds to the nonprofit sector (Farrow et al., 1980).
Leaders working in the nonprofit sector adhere to policies established by the public sector in order to be eligible for public funds (Farrow et al., 1980; Morris et al., 2007; Young, 2002). For 88
example, hospitals and health care providers need to comply with standards of care to receive
Medicare and Medicaid reimbursements. As with the public sector, there is less discretion to
make decisions and administer programs and services (Hooijberg & Choi, 2001).
Table 17
Summary of Sector Significance with Post Hoc
Trait ANOVA Post hoc Post hoc Post hoc Private/Public Private/Nonprofit Public/Nonprofit Involvement Significant Significant Significant Not Significant Consistency Significant Significant Significant Significant Adaptability Significant Significant Significant Not Significant Mission Significant Significant Significant Significant
Results from this study do not conclusively refute the idea of generic leadership theories–
a general theory can apply equally to any organization type. Likewise, this study does not completely support leadership theories and traits unique to organizational sectors. However, the
results of the study partially support some degree of convergence among the sectors (Baldwin,
1987; Hooijberg & Choi, 2001; Rainey et al. 1976; Rosenau & Linder, 2003). Not surprising, the
findings are consistent with research supporting significant differences in leadership traits and
effectiveness among the sectors (Bolman & Deal, 1991; Hooijberg & Choi, 2001). This study
does find a significant difference among the sectors for each of the traits tested.
Findings from the ANOVAs and the independent samples testing from the correlation
transformation (RQ3) support the arguments of scholars such as Denhardt (1984), Hooijberg and
Choi (2001), and Rainey et al. (1976) that leadership theories need to treat the private, public,
and nonprofit sectors differently. However, the results indicate that when the correlations
between the traits and ratings of leadership effectiveness are compared on a sector by sector
basis, the nonprofit sector may share more with the private sector than expected. It could also be 89
an indication that there is more cross-over from the private sector to the nonprofit sector and/or
vice versa. Regardless of the mixed results, this study confirms that leadership characteristics
and effectiveness are defined differently among the sectors and the purpose of the organization is
an important differentiation. The results from the ANOVA for each trait are discussed in further
detail.
Involvement. While not surprising that the involvement trait differs significantly across
the sectors, the ANOVA results indicated a lack of significance between the public and nonprofit
sectors when the post hoc test was examined. This could be partially explained by the premise
that involvement contributes to organization growth and effectiveness (Beugelskijk et al., 2006;
Denison, 1997; Denison & Mishra, 1995; Gregory et al., 2009; Hooijberg & Denison, 1996;
Howell & Avolio, 1993; Kouzes & Posner, 2002; Shadur e al., 1999). Involvement creates a
sense of empowerment and team orientation, which are also characteristics of an innovative
culture (Beugelskij et al., 2006; Howell & Avolio, 1993). Public sector bureaucracies have
limited ability to respond to changing environments and be innovative in delivery of services
(Bass & Avolio, 1997; Denison & Mishra, 1995). Likewise, nonprofit organizations are
constrained by funders – often at the state and federal level and the necessity to meet specific
guidelines and compliance mandates. The ANOVA post hoc results did not indicate significance
between the public and nonprofit sectors nor did the z value of involvement and leadership effectiveness (RQ 3). The ANOVA results support Rainey’s (1983) assessment that there is a lack of defining public and nonprofit organizations in the literature. There is also an indication of possible blending among the sectors have an effect on the leader involvement characteristic.
Consistency. The post hoc test for the consistency trait indicated the trait differs across all three sectors. The results confirm the researcher’s expectation. The consistency trait includes 90 the defining of values, normative integration, internal governance and consensus. Public sector organizations tend to be less dynamic, stressing consistency, and internal systems (Burns, 1978;
Feeney & Rainey, 2010; Hooijberg & Choi, 2001). In short, public organizations are based on rules and procedures, where consistency is prized (Burns, 1978; Hooijberg & Choi, 2001).
The private sector counterparts, however, are often more dynamic, constantly looking forward with long range strategies and goals which are evaluated and changed continually
(Farrow et al., 1980). The nonprofit sector, because of multiple stakeholders and constant changes in funding streams need to be more adaptive and incongruous (Farrow et al., 1980;
Holzer, 2008; Morris et al., 2007; Van Wart, 2003; Wallis & Dollery, 2005; Young, 2002). Yet at the same time, the nonprofit sector leaders, as Jaskyte (2010) pointed out, reinforced core values, built consensus, and promoted shared culture. Contrary to the private sector’s practice of long-term goals and strategies, the nonprofit sector tends to develop short-term goals, often to match funding streams (Farrow et al., 1980). Although it may be counterintuitive to think of short-term planning and goals as related to consistency, grant parameters and funding cycles are typically prescriptive, methodological, and predictable in the nonprofit environment.
Adaptability. The adaptability trait includes factors such as customer focus, change, and organizational learning. The private sector has more resources to initiate development programs and alter or completely change products, services, and delivery. There is a high level of focus on ever changing market conditions, global influences, the diffusion of disruptive technologies, and products (Bennis, 2003). The public sector is considered to be more rigid, having less ability to adapt, change process, and procedures (Burns, 1978; Hooijberg & Choi, 2001; Van Wart, 2003;
Young, 2002). Public organizations often need votes of elected officials or charter changes to make any significant changes in programs and the delivery of services. However, for nonprofit 91
organizations, adaptability is related to social goals, and forwarding the ideals of the agency
(Ruvio et al., 2010). Somewhat similar to the private sector, adaptability, innovation, and creativity are related to meeting client needs and developing creative ways to deliver services to clients (Jaskyte, 2004).
The post hoc tests indicated no significant difference between the public and nonprofit
sectors for the adaptability trait. The research of Mary (2005) and Wallis and Dollery (2005)
indicated the nonprofit sector needs to interact with multiple stakeholders and operate with
vision, strategy, and have the ability to modify and change, which indicates similarities to the
private sector. The results also support researchers such as Rainey and Steinbauer (1999) that
traits have different meanings based on the sector. In the case of adaptability, the lack of
statistical significance between the public and nonprofit sector could be an indication of the trait
being interpreted by respondents using similar criteria.
Mission. As anticipated, the mission trait was significantly different for all three sectors.
The results support the theory that mission has different meanings in nonprofit, public, and private sectors (Rainey & Steinbauer, 1999; Ruvio et al., 2010; Wright, 2007). Private sector organization missions focus on financial metrics and shareholder value. For the public and nonprofit organizations, mission means providing services and programs to support communities. Baldwin (1987) pointed out those in public service display a desire to make a
difference and a strong commitment to the mission. Likewise, those serving in the nonprofit
sector do so because of an alignment of personal values and agency mission (Wallis & Dollery,
2005). However, the mission trait was significantly different between the public and nonprofit
sectors. The difference between the public and nonprofit sectors may reflect a difference between
the desire to serve in the public sector – becoming a career bureaucrat – being motivated to do so 92
and by the context of the position(s) (Appleby, 1945; Willem et al., 2010; Wright, 2007). At the
lower levels, individuals may choose the public sector, not because of the desire to serve, but as
supported by Borjas (2002), Luechinger, Stutzer, and Winkelmann (2006), and Pfeifer (2011),
because of better job security and higher retirement benefits. The difference in mission between
the public and nonprofit sectors may be those working in the nonprofit sector, at all levels, do so
because of the value of the work and a passion for the mission, which confirms Johnson’s (2009)
premise. Further confirming the findings of this study, Rawls et al. (1975) indicated those in the
nonprofit sector have less of a need for security compared to those in the public sector. Instead,
Rawls et al., posited a desire for social status and power was more important to individuals
working in the nonprofit sector. In contrast to the public and nonprofit sectors, individuals in the
private sector may not experience a personal connection to the organization’s mission and the
work.
Relationship between Traits and Effectiveness Sector Comparison
Do the correlation coefficients of leadership traits with leadership effectiveness
significantly differ by sector? This research question was addressed by comparing the
correlation coefficients so that the relationship between traits and effectiveness could be
examined across sectors. While the results of the study show statistically significant differences
in the relationship between leadership traits and leader effectiveness among the private, public,
and nonprofit sectors, the tests at significantly different correlations yielded mixed results.
Research examining convergence among the sectors examines the extent to which generic leadership theory can be applied to each sector (Baldwin, 1987; Hooijberg & Choi, 2001;
Rainey et al., 1976; Rosenau & Linder, 2003). Support for convergence has been evident within the public and nonprofit organizations which are now measured by financial metrics, 93
performance indicators (such as proficiency test scores), and the use of outsourcing and business
models (Chingos & West; Huque, 2009; Linkholm, 2011; Pilotin, 2010; Tucker, 2010). The idea
of convergence among sectors may be a partial explanation of why the results of the current
study were mixed. Even though Baldwin (1987) found three primary differences between the
public and private sectors (goal clarity, leadership turnover, and job security), when magnitude
was considered, the impact of the difference was only modest. Although beyond the scope of the
current research, Baldwin’s findings could translate to the attributes which comprise the traits of
the framework for this study.
Examination of the result for the correlation between the involvement trait and effectiveness indicated no significant difference among the private, public, and nonprofit sectors.
The relationship differences for consistency-effectiveness and the sectors were only significant
between the private and public sectors (z = -3.37, p< .05). However, the correlations for
adaptability-effectiveness and mission-effectiveness differed significantly among the private and
public sectors and the public and nonprofit sectors. The significance of mission-effectiveness
further supports the findings of other researchers such as Rainey and Steinbauer (1999), Ruvio et
al. (2010) and Wright (2007) that mission has a different definition to those in the private, public,
and nonprofit sectors and that difference relates not only to a leader’s traits, but how
effectiveness is rated. It should be emphasized that correlation does not mean causation. The
results cannot and do not determine if one trait causes leadership effectiveness or that the
differences in the significance among the sectors means one sector or trait-leadership effectiveness is better than another 94
Table 18 summarizes how the trait-effectiveness correlations differ significantly in sector
comparisons. A discussion of each of trait-effectiveness correlation in relation to each sector follows.
Table 18
Summary of Trait-Effectiveness Significance by Sector
Correlations Private/Public Private/Nonprofit Public/Nonprofit Involvement- Effectiveness Not Significant Not Significant Not Significant Consistency- Effectiveness Significant Not Significant Not Significant Adaptability- Effectiveness Significant Not Significant Significant Mission- Effectiveness Significant Not Significant Significant p<.05
Involvement-effectiveness. The results of the independent samples of the correlation
between involvement and ratings of effectiveness did not significantly differ from each other
across the sectors. Hooijberg and Denison (1996) found leaders from both the private and public
sector were rated as effective leaders when the leaders exhibited characteristics of the
involvement trait such as empowering staff and team building which supports the results of the
current study. Overall effectiveness, a component of the aggregated effectiveness variable, was
found to have higher ratings with internally oriented traits of involvement and consistency
(Hooijberg & Denison, 1996). Although rater group constructs were beyond the scope of this
study, the Hooijberg and Denison study also found direct reports rated leaders possessing the
involvement trait as highly effective. The implication of the findings suggests that regardless of
the sector, effective leaders need to assume multiple roles and behavior, which may compete
(Bolman & Deal, 1991; Denison, Hooijberg & Quinn, 1995; Hooijberg & Choi, 1998; Hooijberg
& Denison, 1996).
Whereas the current study segregated the public and nonprofit sectors, other researchers
have typically considered the public and nonprofit sectors as one. Therefore, literature 95 differentiating between the public and nonprofit sectors is sparse (Rainey, 1983). One possibility for the lack of significance among the sectors may be the inherent nature of the sectors. For example, leaders in the public realm have limited control and ability to make leadership contributions because guidance comes from higher levels (Hooijberg & Choi, 2001; Van Wart,
2003). As Askhenas, Ulrich, Jick, and Kerr (2008) pointed out; private sector leaders also have boundaries. Lower level managers are accountable to leaders at the higher levels and executive leaders are accountable to shareholders (Young, 2002). In contrast, nonprofit workers are focused on clientele and the agency mission (Wallis & Dollery, 2005). Even beyond the mission component, nonprofit leaders develop more short term goals that mirror funding streams versus the longer goals and strategies of for profit organizations (Farrow et al., 1980). The elements of involvement – developing organizational capability, team building, and empowerment are necessary traits for effectiveness regardless of the sector.
Consistency-effectiveness. When the correlation between consistency and leader effectiveness was compared by sector, the private sector and the public sector differed significantly. However, unexpected was the lack of significance between the private and nonprofit sectors. The findings suggest convergence among the private and nonprofit sectors may exist. As mentioned earlier, nonprofit boards are comprised of individuals from the private sector, each bringing their experiences from their organizations. Additionally, as Tucker (2010) indicated, nonprofits are adopting business-type models in order to compete for resources.
Consistency also allows leaders and followers to react to unexpected situations in a predictable and acceptable manner (Bass, 2008; Bass & Avolio, 1993; Denison & Mishra, 1995; Hooijberg
& Denison, 1996; O’Toole, 2008). Within dynamic environments such as private and nonprofit organizations, leaders rely on the internalized values and beliefs to handle crisis and unexpected 96
situations (Bass, 2008; Bass & Avolio, 1993; Denison & Mishra, 1995; Hooijberg & Denison,
1996; O’Toole, 2008). Bureaucracies tend to be more consistent and stable environments
(DeHoogh et al., 2005). Leaders within such environments are more likely to reinforce
consistency (De Hoogh et al., 2005).
An explanation for the reported results may be how consistency is interpreted. As noted,
research suggests that private and nonprofit leaders use the element of core values, containing
elements of consistency, to deal with unforeseen situations (Bass, 2008; Bass & Avolio, 1993;
Denison & Mishra, 1995; Hooijberg & Denison, 1996; Jaskyte, 2010; O’Toole, 2008). Public
administrators rely on established policies and procedures to provide stability and direction
(Burns, 1978; Hooijberg & Choi, 2001). Additionally, public leaders, similar to nonprofit
leaders, utilize core values of the organization to motivate followers. Similarly, because public
sector leaders are limited in discretionary action, motivation may be in the form of delegation
and consensus building (Farrow et al., 1980; Hooijberg & Choi, 2001; Wilson, 1989). There is a
heavy reliance on the policies, procedures, and processes that are guided by higher public
officials. The implication is public sector leaders are rated as effective when the policies and
procedures are enforced.
Consistency, as well as involvement, is considered an internal trait in the framework. A subscale of ratings of leader effectiveness—overall effectiveness—includes consistency as an element. For overall effectiveness, direct reports gave higher ratings of effectiveness to leaders showing involvement and consistency (Hooijberg & Denison, 1996). Again, the ability of leaders to take on multiple roles, even if those roles and behaviors compete, is perceived as effective leadership (Bolman & Deal, 1991; Denison, Hooijberg, & Quinn, 1995; Hooijberg & Denison;
Hooijberg & Choi, 1998). Even within the public sector, leaders accept roles such as facilitator, 97
broker, or reformer (Denhardt & Denhardt, 2007). When leaders were perceived to be fair and
consistent and goals were stated clearly, followers gave leaders higher ratings (Howell & Avolio,
1993; Mary, 2005; Shamir et al., 1993). Public organizations, however, are known for vague
and/or ambiguous goals (Baldwin, 1987; Boyne, 2002; Wilson, 1989), unlike the private sector
which tends to have clear objectives, contributing to the significant difference between the
private and public sectors.
Another possible reason for the significant difference between the private and public
sectors relates to perceived capability – a subscale of leadership effectiveness. Since in the
public sector goals tend to be vague and ambiguous, consistency is associated with capability
(Hooijberg & Denison, 1996). In fact, researchers found goal orientation (focusing on tasks to
achieve desired results) was not considered effective leadership (Hooijberg & Choi, 2001). The
present study supports research findings that consistent behavior along with adherence to the
rules and regulations was more important in perceptions of effective leaders than goal
achievement. This is opposite of the private sector where goal obtainment is considered vital.
Capability and task performance have been linked to perceived leader effectiveness
(Hooijberg & Denison, 1996; Hooijberg & Choi, 2001; Walumbwa, Avolio, & Zhu, 2008).
However, how capability is defined differs among the sectors. While, as discussed, in the public sector consistency is an indication of capability, in the nonprofit and private sectors, capability does not necessarily equate to consistency. The private and nonprofit sectors tend to be task and goal oriented, with the private sector focused on long – term strategies and goals. In the nonprofit sector, capability, and consistency have different meanings based on the key stakeholders
(Farrow et al., 1980; Morris et al., 2007; Young, 2002). The lack of significance between the private and nonprofit sectors supports the research of convergence between sectors (Hooijberg & 98
Choi, 2001; Rainey et al., 1976; Rosenau & Linder, 2003). As indicated in the discussion of
nonprofit organizations in Chapter 2, nonprofit board members are often from the private sector,
bringing their business knowledge, and business models (Herman & Renz, 2008; Mensah, Lam
& Werner, 2008). If influence from the private sector is filtering into the nonprofit sector, this
can explain the lack of significance (Herman & Renz, 2008; Tucker, 2010).
Between the public and nonprofit sectors, the lack of significance may understandable.
The nonprofit sector, as noted, has multiple and diverse stakeholders, including stakeholders
from the public sector. Nonprofit organizations may receive funding from public entities. That
funding comes with specific policies and regulations. Compliance with those regulations is
necessary for continued funding. Public sector entities may also place mandates on nonprofit
organizations. The result – leaders in nonprofit organizations adopt behaviors to meet
stakeholder expectations. As stated earlier, the public sector emphasizes processes, procedures,
and compliance with stated rules. Therefore, nonprofit leaders focusing on consistent
compliance, processes, and procedures, are rated effective. Within the competing values
framework, nonprofit leaders adopt behaviors more in line with public administrators when
dealing with public funding and compliance (Denison, Hooijberg, & Quinn, 1995; Hooijberg &
Choi, 1998; Hooijberg & Denison, 1996;).
Adaptability-effectiveness. Not surprising, the private and public sectors and the public
and nonprofit sectors significantly differed for the relationship between the adaptability trait and
ratings of leader effectiveness. The results support research findings that differences in
leadership effectiveness and behaviors do indeed exist among the different sectors.
When considered in relation to leader effectiveness, the adaptability trait is also related to
the development of internal and external relationships (Hooijberg & Denison, 1996). Developing 99 strong relationships has been found to be a strong predictor of leadership effectiveness
(Hooijberg & Denison, 1996). In organizations promoting higher levels of relationship, leaders were rated higher for effectiveness (Beugelskijik et al., 2006; de Vries et al., 2010; Hooijberg &
Denison, 1996). Further, developing relationships both internally and externally was a strong predictor of leader effectiveness and related to the adaptability trait (Hooijberg & Denison,
1996).
The significant differences found in this study suggests development of relationships by leaders also differs by sector. The findings of the study not only support differences existing in leadership traits and effectiveness but also support the work of Hooijberg and Choi (2001). In their research, private sector leaders were perceived as effective when leaders utilized a mentoring type of role and developed relationships. In contrast, public sector leaders were perceived as effective when fostering teamwork. This supports public administration research findings that due to limited discretionary action, effective public administrators adopt behaviors to motivate employees, including team building, facilitation during conflict, and active listening
(Farrow et al., 1980; Hooijberg & Choi, 2001; Lemay, 2009; Wilson, 1989). Further, as the findings of this study suggest, effective nonprofit leaders develop relationships with multiple stakeholders, internal and external (Farrow et al., 1980; Holzer, 2008; Morris et al., 2007; Van
Wart, 2003; Wallis & Dollery, 2005; Young, 2002). As the research indicates from Chapter 2, the nonprofit stakeholders have different objectives from each other (Farrow et al., 1980). Unlike the private sector in which the ultimate objective of the board of directors, executive management, and lower level leaders is profitability; there is no one main objective of the multiple stakeholders in the nonprofit sector. For example board members consider the integrity, continuation of the agency, and advancement of the mission key objectives. Funder objectives 100
relate to measurable outcomes. As Mary (2005) and Wallis and Dollery (2205) pointed out,
effective nonprofit leaders need to be visionaries, coaches, change agents, and strategists and at the same time develop relationships and engage the internal and external stakeholders. As noted earlier, developing relationships is one of the seven items measuring perceived leader effectiveness in the Denison framework.
The results from this study support research findings that ratings for leader effectiveness were higher when the organization promoted higher levels of relationship skills, especially internal relationships (Beugelskijk et al., 2006; de Vries et al., 2010; Hooijberg & Denison,
1996). Although beyond this study, Hooijberg and Denison (1996) reported supervisors gave
higher ratings to leaders possessing external traits such as adaptability. However, as noted
earlier, direct reports rated leaders lower on the external traits. There is the implication that
bosses consider being an agent of change as an important characteristic of effective leadership,
whereas followers may be less inclined to view change as an effective quality.
The lack of significance between the private and nonprofit sector supports possible
convergence (Hooijberg & Choi, 2001; Rainey et al., 1976; Rosenau & Linder, 2003). As
indicated in the discussion of involvement-effectiveness, nonprofit boards consist of individuals
from the private sector. Additionally, stakeholders require outcome metrics and models adapted
from the private sector (Tucker, 2010).
Mission-effectiveness. Similar to adaptability-effectiveness, the independent samples tests for the correlations among the sectors revealed significant differences among the private and public sectors and the public and nonprofit sectors for the mission trait. This further supports the work of researchers such as Rainey and Steinbauer (1999) contending that mission has different meanings in the sectors. For leadership in the private sector, mission equates to 101
profitability, increasing shareholder value, and value-add for customers (Morris et al., 2007).
Mission for the public sector means providing public services, public safety, public welfare, fulfilling legislative mandates, and maintain democracy (Denhardt & Denhardt, 2007; Rainey &
Steinbauer, 1999; Simon, 1998; Wright, 2007). At the street level there is the desire to make a difference and employees are not motivated by profit (Lipsky, 1980). Nonprofit leaders and followers tend to be committed to the agency and its mission, having altruistic goals (Wallis &
Dollery, 2005). While the public sector general mission is to provide public services, nonprofit organizations typically have missions targeting specific issues (i.e., homelessness, health care, poverty, diseases). Therefore, mission equates to helping clientele, making a difference in the community, and helping people (Wallis & Dollery, 2005). As a trait in the Denison framework, mission entails strategic planning, goals and objectives, and a shared vision. When leaders and followers support the organization’s culture then a sense of mission is achieved (Kouzes &
Posner, 2002). Further, researchers have viewed mission as an organizational cultural trait
(Denison & Mishra, 1995; Garnett et al., 2008) while others such as Hooijberg and Denison
(1996), Kouzes and Posner (2002), and Peterson, et al., (2008) have considered mission a trait of individual leaders. The results of the mission-leadership effectiveness independent sample also confirms studies indicating leaders need to take on multiple roles and behaviors, which may compete with one another (Bolman & Deal, 1991; Denison, Hooijberg & Quinn, 1995;
Hooijberg & Choi, 1998; Hooijberg & Denison, 1996). Public sector leaders have limited discretion; therefore, leaders adopt different behaviors to motivate employees such as focusing on a sense of mission (Farrow et al., 1980; Hooijberg & Choi, 2001; Wilson, 1989). As indicated in prior discussion, nonprofit leaders interact with multiple stakeholders, each with their own sense of mission and interest in the organization. Because of divergent missions among 102
the private and nonprofit sectors significance was expected. The lack of significance may
confirm suggestions of convergence among the sectors (Hooijberg & Choi, 2001; Rainey et al.,
1976; Rosenau & Linder, 2003).
The results of this study indicate leadership traits and perceptions of leader effectiveness
are significantly different among the private, public, and nonprofit sectors. However, the results
also indicate the presence of convergence among some of the sectors within certain traits and effectiveness. This was especially noticeable for the involvement-effectiveness and consistency-
effectiveness variables. As indicated in this paper, there is movement in the public and nonprofit
sectors to adopt business-style models. The results also confirm leadership theory is not
necessarily generic; one theory does not fit all situations, sectors and/or environments. The
implications for practice for each sector as well as recommendations for future research are
discussed in the following sections.
Implications for Leadership Practice
The results of this study point to a number of implications for practicing leaders,
leadership development, leadership selection, and leadership studies. As this study supports, not
only do leadership traits relate to leader effectiveness, but the organizational sector also
determines how leader traits differ in leader effectiveness among each sector. Leaders, through
their behaviors such as role modeling, training, recruitment, and staff development promote the
organization’s capacity (Bass & Avolio, 1993; Bennis, 2003; Bennis & Nanus, 1985; Bolman &
Deal, 2008; Collins, 2001; Jaskyte, 2004; Kouzes & Posner, 2002, O’Toole, 2008). Leaders
from all sectors are challenged as individuals migrate from one sector to another and internal and
external forces compel leaders to adapt to models and metrics originating from other sectors. In
an effort to explore divergence of leadership theory based on organization typology, this study 103
set out to investigate the differences among sectors when leadership traits of involvement,
adaptability, consistency, and mission, and the correlation of each trait to ratings of leader effectiveness are considered. The results of this study have implications for leaders at every level within the private, public, and nonprofit sectors.
The direct implications from the findings of this study can assist leaders in each sector and individuals migrating from one sector to another (such as from public sector to private sector). For practicing leaders, the results of the current study offer a better understanding of how leader behaviors relate to leader effectiveness within the organization’s sector. Primary areas of implications for leaders and practitioners include current leader practice, leadership development, leadership selection, and leadership study programs.
Current Leadership Practice
The premise of this study is based on the concept that leadership behaviors and ratings of
effectiveness are different for the private, public, and nonprofit sectors. This study highlights to
leaders the traits that relate to effectiveness specified by the sector in which the leader practices.
For leaders in the private sector the results of the study indicate leadership traits of adaptability,
consistency, and mission are behaviors related to effectiveness; but different from the public and
private sectors. As the study found, the private sector was significantly different for the
relationship between those traits and ratings of effectiveness. How the traits are defined within
the sector may partially explain the difference (Hooijberg & Denison, 1996). Leaders are
cautioned to not only examine their own traits, but how those traits are defined within their
organizations. For leaders migrating from the public and/or nonprofit sector to the private sector,
there is a need to be cognizant that traits are defined differently and the leader’s effectiveness is
sensitive to that definition. As an example, an effective leader advances the organization’s 104
mission and strategic plans (Kouzes & Posner, 2002). However, as Baldwin (1987), Ruvio et al.,
(2010) and Young (2002) concur, the mission of private sector organizations equates to financial
metrics, market placement, market share, and increasing shareholder value; in other words—
making money. In contrast the mission for the public and nonprofit sectors focuses on serving
the clientele, providing services to the public for the betterment of the community (Lipsky, 1980;
Rainey & Steinbauer, 1999: Simon, 1998; Wright, 2007).
The public sector tends to be more transactional and more structured (Burns, 1978;
Hooijberg & Choi, 2001). Additionally, leaders have less discretion with staff. The results of the
ANOVA and independent samples confirm the public sector differs in consistency, adaptability,
and mission. This is particularly evidenced among the public and private sectors. Leaders in the
public sector should evaluate their levels of consistency, adaptability, and mission in relation to
their effectiveness. This supports the research of Hooijberg and Choi (2001) suggesting leaders
in the public sector focus their behaviors on areas of consistency, involvement and mission.
Results of this study also confirm leaders in the public sector would do well to assess their own
knowledge of procedures, processes, mandates, rules, and laws which are aspects of consistency.
Leaders in the public sector should evaluate their abilities to use teambuilding, participate in
active listening, and facilitate conflict/work towards conflict resolution. As the multiframe model
(Bolman & Deal, 2008) and competing values frameworks (Denison, Hooijberg, & Quinn, 1995)
suggest, leaders may need to take more of an internal versus external focus to achieve ratings of
effectiveness in the public sector.
Due to multiple stakeholder groups, each with its own objectives, involved in the nonprofit sector (Young, 2002), leaders may find it necessary to adapt their behaviors and traits
to form relationships and achieve effectiveness within each stakeholder group. Even though total 105
convergence between the private and nonprofit sectors was not indicated, leaders in the nonprofit
sector should be cognizant of private sector influences, particularly from board members and
private funders. The results from this study indicate the adaptability-effectiveness relationship significantly differs from the other sectors. As Young (2002) intimated, leaders in nonprofit organizations serve multiple stakeholders. Board members, often from the private sector, utilize business models and metrics to measure outcomes. Meanwhile, agency staff members are focused more on client outcomes and the mission of the agency. Staff members are often not familiar with strategies that include right-sizing, restructuring of the organization and/or changes in job duties. The key for leader effectiveness in the nonprofit sector is to evaluate leader behaviors in relation to mission and involvement traits. That self-evaluation then should be considered in terms of stakeholders. Nonprofit leaders, to maintain effectiveness, need to reflect and communicate how any change ties to the mission of the organization. Change is inevitable with constantly changing client and community needs, funding streams, outcome models and funding mandates.
Leadership Development
Organization context and culture have implications for leadership training, development programs, and leadership programs in higher education. Dhar and Mishra (2001) confirmed the necessity of leadership development for the advancement of the organization, even more so in today’s technological and service-focused environment. As an example, the study indicates with more structure and normative processes, such as those in the public sectors, leadership training and development focusing on traits of consistency and mission relate to leader effectiveness. In contrast, development programs focused on adaptability and involvement, where innovation, goal-setting and internal and external relations are part of the private sector culture, contribute to 106 leader effectiveness. This study noted, as the economy changes and with it the job market, individuals migrate from one sector to another. Utilizing the results of this study, development program directors can customize curriculum based how the current organization defines and focuses on traits resulting in effectiveness versus the new employee’s former organization.
Mission, for example, has a different interpretation in the private sector, where financial goals are emphasized, than it does in the public and nonprofit sectors, which focuses on the betterment of communities.
Using a framework, such as the Denison model, allows leadership training personnel understand their own organizations. Using the leadership trait framework, trainers, human resource staff, leaders, and staff can identify their organization’s strengths and weaknesses in relation to the framework (Bolman & Deal, 1992). It is also worthy to understand that all four traits are important, but the influence is based on the sector (Bolman & Deal; Denison, Hooijberg
& Quinn, 1995). Further, internal development programs can use the framework to develop leadership competencies that are essential to the organization.
As a development tool, the 360 instrument utilized in this study (or a similar 360 tool) determines a leaders traits and attributes which then allows for targeted leadership development.
Critics of 360 multi-rater instruments contend there is a lack of independence making the responses potentially biased because of the relationship between the leader and the follower
(Antonioni & Park, 2001; Zammuto et al., 1982). However, there is benefit because perceptions of leader effectiveness are influenced not only by the relationship of the rater, but also influenced by organizational context (Bolman & Deal, 1991; Hooijberg & Choi, 2001; Hooijberg &
Denison, 1996). 107
Further, there is the implication that curricula of leadership programs and/or leadership
courses within programs (such as public administration) benefit by not treating leadership theory
in a generic manner. Course content may benefit students by focused study related to how
leadership behavior and effectiveness differs among the sectors. The results from this study
support the contention that organizational context is a factor in perceptions of leadership
effectiveness.
As discussed previously, the comparison literature of leadership characteristics and effectiveness is limited (Andersen, 2010; Farrow et al., 1980; Rainey, 1983; Rainey & Bozeman,
2000), especially when considering the private, public, and nonprofit sectors together. This
current research contributes to the comparative literature; comparing differences among the three
sectors in one study. In addition, this study supports the theory that leadership effectiveness and
leadership traits are different based on organizational context. The concept that leadership theory
and models are generic was not supported. If anything, the study supports the need for continued
research comparing leadership and leader effectiveness across all sectors.
Leadership Selection
Awareness of leadership traits and effectiveness can help human resource departments and hiring managers and/or committees to hire a best fit by focusing interview questions on the traits relating to effectiveness for that organization. Organizations, such as the in the private sector, that focus leadership as creating vision, change, empowerment, development, and organization learning can benefit from concentrating interview questions that vet those qualities in a candidate. Similarly, hiring managers in the public sector will benefit from concentrating on consistency traits and a mission to serve the public. Likewise, for nonprofits, belief in the mission is related to ratings of leader effectiveness. Approaches such as hiring for the 108
organizational culture not merely skills and experience improve employee morale (Bowen,
Ledford, & Nathan, 1991). Hiring activities to determine a best fit with the organizational culture may include pre-hiring training programs, job simulations, multiple interviews and interviewers, and personality tests (Bowen et al.). Although the hiring process takes more time and rigor, the benefits can include favorable employee attitudes, less absenteeism, better job performance, reinforcement of the organization culture (Bowen et al.)
Also, leadership at all levels can benefit from an understanding of leadership models and how to use the models to be more successful in implementing changes within the organization. In summary, it is important for leaders to understand the contextual aspects of their organizations and how to use those aspects to develop leaders within the frame of the organization and hire those that can adapt to the organizational culture.
Limitations and Future Research
This study presented contributions to the existing literature on leadership effectiveness
across the private, public, and nonprofit sectors. There are also some limitations regarding the
findings this study as well as opportunities for future research.
Limitations of the Study
This study utilized a convenience sample of private, public, and nonprofit sector respondents to the DLDS instrument. Although a truly random sample from the population offers the ability for generalization to the population, randomization from the population cannot guarantee the needed characteristics will be present in the sample and cannot ensure
representation (Creswell, 2003).
This study used aggregated data for the four main traits and did not specifically look at
the 12 indices. Further, the study only examined the aggregated scores across self-response, 109 subordinates, peers and supervisors and did not segregate the results out by type of respondent.
Aggregating the data provided some advantages. There has been criticism of small and concentrated sample sizes, especially in the public/nonprofit sectors (Farrow et al., 1980;
Hooijberg & Choi, 2001; Noordegraaf & Steward, 2000; Rainey & Bozeman, 2000; Ruvio et al.,
2010). Aggregating respondent groups within each sector allowed for larger samples among each sector thereby mitigating that criticism. Additionally, there are existing studies concentrating on how rater groups evaluated leaders (e.g., Bolman & Deal, 1991; Hooijberg & Choi, 2001;
Hooijberg & Denison, 1996) and others (Bolman & Deal, 1991; Hooijberg & Choi, 2001) have evaluated how ratings differ between the private and public sector. This study concentrates on the differences among the private, public, and nonprofit sectors in order to fill the gap in empirical research on leadership effectiveness among the sectors.
This study assumes the subjects completing the questionnaire did so voluntarily and completed the survey honestly. The participants for this study are individuals participating in the
DLDS from organizations that have engaged Denison Consulting. The participants in the database are intended to be representative of members of the different sectors; therefore giving the study generalizability. However, because this is a convenience sample, the study may not be representative of the larger population. The limitation of generalizability can be mitigated with the argument that field samples tend to be derived from one or a few organizations and/or defined group (i.e. males, management level) possessing their own culture and customs (Dipboye
& Flanagan, 1979; Highhouse & Gillespie, 2009). Dipboye and Flanagan (1979) further argued that it is just as important to determine the types of organizations included in the research for generalizability. The behavioral sciences rely on substantive theory, assuming there are certain regularities in the human behavior making convenience samples generalizable (Farber, 1952; 110
Highhouse & Gillespie, 2009). It should also be noted that correlation only determines to what degree a relationship exists and therefore does not indicate causation (Mertler & Vannatta,
2005). Additionally, effectiveness can be measured in a number of ways organizationally and by external outcomes. Because effectiveness measures vary greatly, not only among each sector, but also within the sectors, one effectiveness measure is provided using the same methods as the traits assessment.
Perceptions of leadership and effective leadership—how the respondents answered items on the survey, may be different based on how the respondent defines or perceives leadership.
Because the survey was a 360 instrument, with multiple respondent groups and the scores were aggregated for this study, it is not certain if there was any difference in the assessment of the leadership traits and ratings of leader effectiveness due to rater groups within each sector.
The results should be considered cautiously regarding the relationships between the traits and ratings of effectiveness. The correlations between the traits and ratings of effectiveness do not equate to cause and effect. The high correlations between each trait and leader effectiveness items describes a positive relationship, but does not guarantee a leader possessing a high rating for a trait causes that leader to be any more effective than another leader.
Future Research
Consistent with suggestions by Hooijberg and Choi (2001) and Rainey (1983) this study utilized a large sample across the three sectors and dissimilar organizations. This study contributes to that gap in the literature, and future researchers should consider larger samples from diverse organizations. As discussed previously, the comparison literature of leadership characteristics and effectiveness is sparse (Andersen, 2010; Farrow et al., 1980; Rainey, 1983;
Rainey & Bozeman, 2000), especially when considering the private, public, and nonprofit sectors 111 together. This current research contributes to the comparative literature and takes comparative research a step further by investigating differences among the three sectors in one study. In addition, this study supports the theory that leadership effectiveness and leadership traits are different when organizational context is considered. This study supports the idea that leadership theory and models are not generic regarding organization sector.
Since this study utilized aggregated data for the traits and leader effectiveness, future research should expand the study by investigating data without aggregation. The current study can be expanded to investigate significance of each of the indices composing the traits. By examining the indices more specific differences among the sectors could be revealed.
Additionally, since the seven items measuring ratings of leadership effectiveness were aggregated for the current study, there may be benefit from further research examining each of the leader effectiveness items.
Although there have been studies examining how different rater groups evaluate leadership characteristics and leader effectiveness, (e.g., Hooijberg & Choi, 2001), this study did not focus on differences by rater group. To better understand differences among the sectors, it may also be beneficial to investigate how the rater groups within each sector rate leader traits and effectiveness. The limited studies that have compared rater responses combined with comparing sectors only investigated two sectors at a time. Future researchers contributing to the comparative literature should also consider multiple rater responses among the three sectors.
Additionally, because the participant roles were not considered for the current study, future research may have benefit investigating any impact the roles of the participants play.
Finally, future research based on this sample should consider other demographic variables. Although other researchers suggested using larger and diverse samples, this study may 112 also offer insight into leadership effectiveness within sub-populations. Utilizing the sample from the current study, there may be benefit from examining if differences exist between sub-sectors, such as public education, higher education, municipalities, counties, state level public organizations and/or manufacturing, service or retail for private organizations and/or nonprofit hospitals, and social service agencies for the nonprofit sector. There is a variety of organizations within each sector. By examining sub-sectors, there may be a benefit to understanding how leadership traits relate to effectiveness at a more specific organizational context level. Similarly, there may be benefit to exploring ratings of effectiveness based on variables such as time in organization, job level, gender, age, and education and if those variables differ in ratings of effectiveness among the different sectors. For example, does a career bureaucrat rate a leader differently than a middle manager with the same years of service in the private sector and on what items?
Conclusions
In conclusion, leadership theories and models serve as a starting point to exploring differences of leadership traits and effectiveness ratings among the different sectors. As this study confirmed, there are unique characteristics of organizations in each sector that make generic leadership models ineffective or at least worthy of expanding. This study has added to the limited, but growing, comparative sector research, confirming the need to consider organizational differences and sector differences in leadership theories. This study contributed to the leadership by sector comparative literature, and expanded the literature to include comparison of leadership traits and effectiveness across the private, public, and nonprofit sectors.
113
REFERENCES
Anderson, J. A. (2010). Public versus private managers: How public and private managers differ
in leadership behavior. Public Administration Review, 71(1), 131-141.
Antonioni, D., & Park, H. (2001). The relationship between rater affect and the three sources of
360-degree feedback ratings. Journal of Management, 27(4), 479-495.
Appleby, P. (1945). Government is different. In J. M. Shafritz & A. C. Hyde (Eds.), Classics of
public administration (6th ed.) (pp. 119-123). Boston, MA: Wadsworth.
Ashkenas, R., Ulrich, D, Jick, T., & Kerr, S. (2008). The boundaryless organization. In J. V.
Gallos (Ed) Business leadership (2nd ed) (199-220). San Francisco, CA: Jossey-Bass.
Baldwin, J. N. (1987). Public versus private: Not that different, not that consequential. Public
Personnel Management, 16(2), 181-193.
Bass, B. M. (1999). Two decades of research and development in transformational leadership.
European Journal of Work and Organizational Psychology, 8(1), 9-32.
Bass, B. M. (2008). The Bass handbook of leadership (4th ed). New York, NY: Free Press.
Bass, B. M., & Avolio, B. J. (1993). Transformational leadership and organizational culture.
Public Administration Quarterly, 17(1), 112-121.
Bel, G., & Fageda, X. (2008). Reforming the local public sector: Economic and politics in
privatization of water and solid waste. Journal of Economic Policy Reform, 11(1), 45-65.
Bennis, W. (2003). On becoming a leader. New York, NY: Basic Books.
Bennis, W., & Nanus, B. (1985). Leaders: The strategies for taking charge. New York, NY:
Harper & Row.
Beugelsdijk, S., Koen, C. I., & Noorderhaven, N. G. (2006). Organizational culture and
relationship skills. Organization Studies, 27(6), 833-854. 114
Blake, R. R., & McCanse, A. A. (1991). Leadership dilemmas-grid solutions. Houston, TX: Gulf
Publishing.
Blake, R. R., & Mouton, J. (1975). An overview of the gird. Training and Development Journal,
29(5), 29-37.
Blanchard K. H., & Hersey, P. (1996). Great ideas revisited. Training & Development, 50(1), 42-
47.
Bolman L. G., & Deal, T. E. (2008). Reframing organizations. San Francisco CA: Jossey-Bass.
Bolman, L. G., & Deal, T. E. (1991). Leadership and management effectiveness: A multi-frame,
multi-sector analysis. Human Resource Management, 30(4), 509-534.
Borjas, G. J. (2002). The wage structure and the sorting of workers into the public sector
(Working Paper No. 9313). Cambridge, MA:National Bureau of Economic Research
Retrieved June 20, 2011 from http://www.nber.org/papers/w9313.
Bowen, D. E., Ledford, G. E., & Nathan, B. R. (1991). Hiring for the organization, not the job.
Academy of Management Executive, 5(4), 35-51.
Boyne, G. A. (2002). Public and private management: What’s the difference? Journal of
Management Studies, 39(1), 97-122.
Bozzo, S. L. (2000). Evaluation resources for nonprofit organizations. Nonprofit Management &
Leadership, 10(4), 463-472.
Buelens, M., & Van den Broeck, H. (2007). An analysis of differences in work motivation
between public and private sector organizations. Public Administration Review, 67(1),
65-74.
Burns, J. M. (1978). Leadership. New York, NY: Harper Perennial. 115
Byrnes, J., & Fifer, J. (2010). A guide to highly effective quality programs. Healthcare Financial
Management, 64(1), 80-87.
Castañeda, M. B., Levin, J. R., & Dunham, R. B. (1993). Using planned comparisons in
management research: A case for the Bonferroni procedure. Journal of Management,
19(3), 707-724.
Challenger, Gray, & Christmas, Inc. (2011, July). Job cuts see second consecutive increase: June
job cuts reach 41,432: mid-year total of 245,806 is lowest in 11 years. Retrieved
from http://www.challengergray.com/press/press.aspx.
Chingos, M. M., & West, M. R. (2011). Promotion and reassignment in public school districts:
How do schools respond to differences in teacher effectiveness? Economics of Education
Review, 30(3), 419-433.
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis. Mahwah, NJ:
Lawrence Earlbaum Associates, Inc.
Collins, J. (2001). Good to great. New York, NY: Harper.
Colvard, J. E. (2008). Developing future leaders. In R. S. Morse & T. F. Buss (Eds), Innovations
in public leadership development (pp 50-60), Armonk, NY: M.E. Sharpe.
Creswell, J. W. (2003). Research design (2nd ed). Thousand Oaks, CA: Sage Publications.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16 (3), 297- 334).
Davis, D. (2005). Business research (6th ed). Belmont, CA: Thomason Brooks/Cole.
De Hoogh, A. H. B., Den Hartog, D. N., & Koopman, P. L. (2005). Linking the big five-factors
of personality to charismatic and transactional leadership; perceived dynamic work
environment as a moderator. Journal of Organizational Behavior, 26(7), 839-865. 116
Deluga, R. J. (1990). The effects of transformational, transactional, and laissez faire leadership
characteristics on subordinate influencing behavior. Basic and Applied Social
Psychology, 11(2), 191-203.
Denhardt, J. V., & Denhardt, R. B. (2007). The new public service. Armonk, NY: M.E. Sharpe.
Denhardt, R. B. (1984). Theories of public organization. Pacific Grove, CA: Brooks/Cole.
Denhardt, R. B., & Denhardt, J. V. (2006). The dance of leadership. Armonk, NY: M.E. Sharpe.
Denison, D. R. (1997). Corporate culture and organizational effectiveness. New York, NY:
Wiley.
Denison, D. R., Hooijberg R., & Quinn, R. E. (1995). Paradox and performance: Toward a
theory of behavioral complexity in managerial leadership. Organization Science, 6(5),
524-540.
Denison, D. R., & Mishra, A. K. (1995). Toward a theory of organizational culture and
effectiveness. Organization Science, 6(2), 204-223.
Denison, D. R., & Neale, W. (1996). The Denison leadership development survey. Ann Arbor,
MI: Aviat. de Vries, R. E., Bakker-Pieper, A., & Oostenveld, W. (2010). Leadership = Communication?
The relations of leaders’ communication styles with leadership styles, knowledge sharing
and leadership outcomes. Journal of Business Psychology, 25(3), 367-380.
Dhar, U., & Mishra, P. (2001). Leadership effectiveness. Journal of Management Research, 1(4),
254-266.
Dipboye, R. L., & Flanagan, M. F. (1979). Are findings in the field more generalizable than in
the laboratory? American Psychologist, 34(2), 141-150. 117
Dull, M. (2009). Results-model reform leadership: Questions of credible commitment. Journal of
Public Administration Research and Theory, 19(2), 255-284.
Farber, M. (1952). The college student as laboratory animal. American Psychologist, 7(3), 102.
Farrow, D. L., Valenzi, E. R., & Bass, B.M. (1980). A comparison of leadership and situational
characteristics within profit and non-profit organizations. Academy of Management
Proceedings (00650668), 334-338.
Feeney, M. K., & Rainey, H. G. (2010). Personnel flexibility and red tape in public and nonprofit
organizations: Distinctions due to institutional and political accountability. Journal of
Public Administration Research and Theory, 20(4), 801-826.
Fisher, R. A. (1970). Statistical methods for research workers. New York, NY: Hafner Press.
Fraenkel, J. R., & Wallen, N. E. (2009). How to design and evaluate research in education.
Boston, MA: McGraw-Hill.
Gallos, J. V. (2008). Making sense of organizations: Leadership, frames, and everyday theories
of the situation. In J. V. Gallos (Ed) Business leadership (2nd ed.) (161-179). San
Francisco, CA: Jossey-Bass
Garnett, J. L., Marlowe, J., & Pandey, S. K. (2008). Penetrating the performance predicament:
Communication as a mediator or moderator of organizational culture’s impact on public
organizational performance. Public Administration Review, 68(2), 266-281.
Gilley, A., Dixon, P., & Gilley, J. W. (2008). Characteristics of leadership effectiveness:
Implementing change and driving innovation in organizations. Human Resource
Development Quarterly, 19(2), 153-169.
Goleman, D. (1998). Working with emotional intelligence. New York, NY: Bantam Books. 118
Goulet, L. R., & Frank, M. L. (2002). Organizational commitment across three sectors: Public,
non-profit, and for-profit. Public Personnel Management, 31(2), 201-210.
Gravetter, F. J., & Wallnau, L. B. (2008). Essentials of statistics for the behavioral sciences.
Belmont, CA: Thomas- Wadsworth.
Greeley, B., & Niquette, M. (2011, February). The Union, Jacked. Bloomberg
Businessweek,(4218), 8-9.
Gregory, B. T., Harris, S. G., Armenakis, A. A., & Shook, C. L. (2009). Organizational culture
effectiveness: A study of values, attitudes, and organizational outcomes. Journal of
Business Research, 62(7), 673-679.
Gumusluoglu, L., & Ilsev, A. (2009). Transformational leadership, creativity, and organizational
innovation. Journal of Business Research, 62(4), 461-473.
Haque, M. S. (1996). The intellectual crisis in public administration in the current epoch of
privatization. Administration & Society, 27(4), 510-536.
Harmon, M. M., & Mayer, R. T. (1986). Organization theory for public administration. Boston,
MA: Little, Brown.
Harris, M. B. (1995). Basic statistics for behavioral science research. Boston, MA: Allyn and
Bacon.
Henson, R. K. (2001). Understanding internal consistency reliability estimates: A conceptual
primer on coefficient alpha. Measurement and Evaluation in Counseling and
Development, 34(3), 177-189.
Herman, R. D., & Renz, D. O. (2008). Advancing nonprofit organizational effectiveness research
and theory. Nonprofit Management & Leadership, 18(4), 399-415 119
Hersey, P., & Blanchard, K. H. (1996). Great ideas revisited. Training and Development, 50(1),
42-47.
Hersey, P., Blanchard, K. H., & Johnson, D. E. (2001). Management of organizational behavior
(8th ed). Upper Saddle, NJ: Prentice-Hall.
Highhouse, S., & Gillespie, J. Z. (2009) Do samples really matter that much? In C.E. Lance & R.
J. Vandenberg (Eds.) Statistical and methodological myths and urban legends: Received
Doctrine, verity, and fable in the organizational and social sciences (247-262). New
York, NY: Routledge, Taylor & Francis Group
Holzer, M. (2008). Culture and leadership. In R. S. Morse & T. F. Buss (Eds.) Innovations in
public leadership development (pp 21-32).
Hooijberg, R., & Choi, J. (2001). The impact of organizational characteristics on leadership
effectiveness models: An examination of leadership in a private and a public sector
organization. Administration & Society, 33(4), 403-431.
Hooijberg, R., & Denison, D. R. (1996). What makes leader effective? A stakeholder approach
to leadership effectiveness. Retrieved from
http://www.denisonconsulting.com/resource-library/what-makes-leader-effective-
stakeholder-approach-leader-effectiveness.
Howell, J. M., & Avolio, B. J. (1993). Transformational leadership, transactional leadership,
locus of control, and support for innovation: Key predictors of consolidated-business-unit
performance. Journal of Applied Psychology, 78(6), 891-902.
Huque, A. S. (2009). Does ideology matter? Incentive, efficiency and management in the public
sector. International Journal of Public Administration, 32(11), 929-950. 120
Jaskyte, K. (2004). Transformational leadership, organizational culture, and innovativeness in
nonprofit organizations. Nonprofit Management & Leadership, 15(2), 153-168).
Jaskyte, K. (2010). An exploratory examination of correlates of organizational culture.
Administration in Social Work, 34(5), 423-441.
Johnson, J. L. (2009). The nonprofit leadership deficit. Nonprofit Management & Leadership,
19(3), 285-304.
Kotter, J. P. (2007). Leading change: Why transformation efforts fail. Harvard Business Review,
8(1), 96-103.
Kouzes, J. M., & Posner, B. Z., (2002). The leadership challenge (3rd ed). San Francisco, CA:
Jossey-Bass.
Lemay, L. (2009). The practice of collective and strategic leadership in the public sector. The
Innovation Journal: The Public Sector Innovation Journal, 14(1), 1 -19.
Linkhorn, T. (2011, July 6). Toledo-Lucas county trash deal in effect. The Blade, Retrieved
from http://www.toledoblade.com.
Lipsky, M. (1980). Street-level bureaucracy: The critical role of street-level bureaucrats. In J. M.
Shafritz, & A. C. Hyde (Eds.), Classics of public administration (6th ed.) (pp. 404-411).
Boston, MA: Wadsworth.
Long, N. E., (1949). Power and administration. Public Administration Review, 9(4), 257-264.
Louis, K. S., Leithwood, K., Wahlstrom, K. L., & Anderson, S. E. (2010). Learning from
Leadership: Investigating the Links to Improved Student Learning. University of
Minnesota: Center for Applied Research and Educational Improvement.
Lowery, R. (nd). The Kruskal-Wallis Test. Vasarstats.net. retrieved
from, http://vassarstats.net/textbook/ch14a.html. 121
Luechinger, S., Stutzer, A., & Winkelmann (2006). The happiness gains from sorting and
matching in the labor market (Working Paper No. 275), Zurich:Institute for Empirical
Research in Economics.
Maidani, E. (1991). Comparative study of Herzberg’s two-factor theory of job satisfaction
among public and private sectors. Public Personnel Management, 20(4), 441-448.
Mancheno-Smoak, L., Endres, G. M., Polak, R., & Athanasaw, Y. (2009). The individual
cultural values and job satisfaction of the transformational leader. Organization
Development Journal, 27(3), 9-21.
Marascuilo, L. A., & Serlin, R. C. (1988). Statistical methods for the social and behavioral
sciences. New York, NY: W. H. Freeman and Company
Mary, N. L. (2005). Transformational leadership in human service organizations. Administration
in Social Work, 29(2), 105-118.
Mason, R. D. (1986). Statistical techniques in business and economics 6th edition. Homewood,
IL: Irwin.
McClelland, D. C., & Burnham, D. H. (2003). Power is the great motivator. Harvard Business
Review, 73(1), 126-139.
McDonagh, K. J. (2006). Hospital governing boards: A study of their effectiveness in relation to
organizational performance. Journal of Healthcare Management, 51(6), 337-391.
McGuinness, K.A. (2002). Of rowing boats, ocean liners, and tests of the ANOVA homogeneity
of variance assumption. Austral Ecology, 27, 681-688.
Menges, J. I., Walter, F., Vogel, B., & Bruch, H. (2008). Mechanisms and boundary conditions
for performance effects of transformational leadership climate. Academy of Management
Annual Meeting Proceedings, 1-6. Retrieved from EBSCOhost. 122
Mensah, Y. M., Lam, K. C.K., & Werner, R. H. (2008). An approach to evaluating relative
effectiveness in non-profit institutions. Journal of Public Budgeting, Accounting &
Financial Management, 20(3), 324-354.
Mertler, C. A., & Charles, C. M. (2008). Introduction to educational research (6th ed). Boston,
MA: Pearson.
Mertler, C. A., & Vannatta, R. A. (2005).Advanced and multivariate statistical methods (3rd ed).
Glendale, CA: Pyrczak Publishing.
Morris, M. H., Coombes, S., Schindehutte, M., & Allen, J., (2007). Antecedents and outcomes of
entrepreneurial and market orientations in a non-profit context: theoretical and empirical
insights. Journal of Leadership and Organizational Studies, 13(4), 12-39.
Motamedi, K. K. (1976). Adaptability and copability: A study of organization/environment
contingencies. Academy of Management Proceedings (00650668), 383-388. Retrieved
from EBSCOhost.
Noordegraaf, M., & Stewart, R. (2000). Managerial behavior research in private and public
sectors: Distinctiveness, disputes and directions. Journal of Management Studies, 37(3),
427-443.
Ohio Department of Education Report Card (n.d.). Retrieved
from http://reportcard.education.ohio.gov/Pages/default.aspx.
Olsen, E. G. (2011, March). American teachers under attack. Fortune. Retrieved
from http://management.fortune.cnn.com/2011/03/23/american-teachers-under-attack/.
O’Toole, J. (2008). When leadership is an organizational trait. In J. V. Gallos (Ed), Business
leadership (2nd ed.) (pp. 50-60). San Francisco, CA: Jossey-Bass. 123
O’Toole, L. J. Jr., & Meier, K. J., (1999). Modeling the impact of public management:
Implications of structural context. Journal of Public Administration Research and
Theory, 9(4), 505-526.
Peterson, R. A. (1994). A meta-analysis of cronbach’s coefficient alpha. Journal of Consumer
Research, 2 (2), 381-391.
Peterson, S. J., Walumbwa, F. O., Byron, K., & Myrowitz (2007). Transformational leadership,
positive psychological traits, and firm performance. Academy of Management Annual
Meeting Proceedings, 1-5.
Pfeifer, C. (2011). Risk aversion and sorting into public sector employment. German Economic
Review 12(1), 85-99.
Pilotin, M. (2010). Finding a common yardstick: Implementing a national student assessment
and school accountability plan through state-federal collaboration. California Law
Review, 98(2), 545-574.
Quinn, R. E. (2008). Moments of Greatness. In J. V. Gallos (Ed), Business leadership (2nd ed)
(pp 142-154). San Francisco, CA: Jossey-Bass.
Rainey, H. G. (1979). Reward expectancies, role perceptions and job satisfaction among
government and business managers: Indicators of commonalities and differences.
Academy of Management Proceedings, 357-361.
Rainey, H. G. (1983). Public agencies and private firms: Incentive structures, goals, and
individual roles. Administration & Society, 15(2), 207-242.
Rainey, H. G. (1989). Public management: Recent research on the political context and
managerial roles, structures, and behaviors. Journal of Management, 15 124
Rainey, H. G., Backoff, R. W., & Levine, C. H. (1976). Comparing public and private
organizations. Public Administration Review, 36(2), 233-244.
Rainey, H. G., & Bozeman, B. (2000). Comparing public and private organizations: Empirical
research and the power of the a priori. Journal of Public Administration Research and
Theory, 10(2), 447-469.
Rainey, H. G., & Steinbauer, P. (1999). Galloping elephants: Developing elements of a theory of
effective government organizations. Journal of Public Administration Research and
Theory, 9(1), 1-32.
Rawls, J. R., Ullrich, R. A., & Nelson, O. T. (1975). A comparison of managers entering or
reentering the profit and nonprofit sectors. Academy of Management Journal, 18(3), 616-
623.
Robertson, P. J., & Seneviratne, S. J. (1995). Outcomes of planned organizational change in the
public sector: A meta-analytical comparison to the private sector. Public Administration
Review, 55(6), 547-558
Rosenau, P. V., & Linder, S. H. (2003). Two decades of research comparing for-profit and
nonprofit health provider performance in the United States. Social Science Quarterly,
84(2), 219-241.
Rushing, W. (1974). Differences in profit and nonprofit organizations: A study of effectiveness
and efficiency in general short-stay hospitals. Administrative Science Quarterly, 19(4),
474-484.
Ruvio, A., Rosenblatt, Z., & Hertz-Lazarowitz (2010). Entrepreneurial leadership vision in
nonprofit vs. for-profit organizations. The Leadership Quarterly, 21(1), 144-158. 125
Shamir, B., House, R. J., & Arthur, M. B. (1993). The motivational effects of charismatic
leadership: A self-concept based theory. Organization Science, 4(4), 577- 594).
Shadur, M. A., Kienzle, R., & Rodwell, J. J. (1999). The relationship between organizational
climate and employee perceptions of involvement. Group & Organization Management,
24(4), 479-503.
Simon, H. A. (1998). Why public administration? Journal of Public Administration Research
and Theory, 8(1), 1-11.
Sorensen, J. (2002). The strength of corporate culture and reliability of firm performance.
Administrative Science Quarterly, 47(1), 70-91.
Sorenson, O. (2003). Interdependence and adaptability: Organizational learning and the long-
term effect of integration. Management Science, 49(4), 446-463.
Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological
Bulletin, 87(2), 245-251.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed). Boston, MA:
Pearson.
Trottier, T., Van Wart, M., & Wang, X (2008). Examining the nature and significance of
leadership in government organizations. Public Administration Review, 68(2), 319-333.
Tucker, B. (2010). Through which lens? Contingency and institutional approaches to
conceptualizing organizational performance in the not-for-profit sector. Journal of
Applied Management Accounting Research, 8 (1), 17-33.
Tuominen, M., Rajala, A., & Möller, K. (2004). How does adaptability drive firm
innovativeness? Journal of Business Research, 57(5), 495-506. 126
Van Hecke, (2010). Retrieved
from http://interstat.statjournals.net/YEAR/2010/articles/1011002.pdf.
Van Wart, M. (2003). Public-sector leadership theory: An assessment. Public Administration
Review, 63(2), 214-228.
Volokh, A. (2010). Privatization, free riding, and industry-expanding lobbying. International
Review of Law & Economics, 30(1), 62-70.
Vroom, V. H., & Jago, A. G. (2007). The role of the situation in leadership. American
Psychologist, 62(1), 17-24.
Wager, L. W. (1965). Leadership style, hierarchical influence, and supervisory role obligations.
Administrative Science Quarterly, 9(4), 391-420.
Wallis, J., & Dollery, B. (2005). Leadership and economic theories of nonprofit organizations.
Review of Policy Research, 22(4), 483-499).
Walumbwa, F. O., Avolio, B. J., & Hartnell, C. A. (2010). An investigation of the relationships
among leader and follower psychological capital, service climate, and job performance.
Personnel Psychology, 63(4), 937-963.
Walumbwa, F. O., Avolio, B. J., & Zhu, W. (2008). How transformational leadership weaves its
influence on individual job performance: The role of identification and efficacy beliefs.
Personnel Psychology, 61(4), 793- 825.
Walumbwa, F. O., Wu, C., & Orwa, B. (2008). Contingent reward transactional leadership, work
attitudes, and organizational citizenship behavior: The role of procedural justice climate
perceptions and strength. The Leadership Quarterly, 19(3), 251-265.
Weber, M. (1922). Bureaucracy. In J. M. Shafritz & A. C. Hyde (Eds.), Classics of public
administration (6th ed.) (pp. 43-48). Boston, MA: Wadsworth. 127
Whittington, J. L., Coker, R. H., Goodwin, V. L., Ickes, W., & Murray, B. (2009). Transactional
leadership revisited: Self-other agreement and its consequences. Journal of Applied
Social Psychology, 39(8), 1860-1886.
Willem, A., De Vos, A., & Buelens, M. (2010). Comparing private and public sector employees’
psychological contracts. Public Management Review, 12(2), 275-302.
Wilson, J. Q. (1989). Bureaucracy. New York, NY: Basic Books.
Wilson, W. (1887). The study of administration. In J. M. Shafritz, & A. C. Hyde (Eds.), Classics
of public administration (6th ed.) (pp. 1627). Boston, MA: Wadsworth.
Wright, B. E. (2007). Public service and motivation: Does mission matter? Public Administration
Review, 67(1), 54-64.
Wuensch, K. L. (2013). Comparing Correlation Coefficients, Slopes, and Intercepts. Retrieved
from http://core.ecu.edu/psyc/wuenschk/docs30/CompareCorrCoeff.pdf.
Yan, Y., Hsu, S., & Fahn, S. (2009). The viable measure for hospitals? Healthcare expenditure
forecasting under the global budget system. China-USA Business Review, 8(3), 13-20.
Young, D. R. (2002). The influence of business on nonprofit organizations and the complexity of
nonprofit accountability. American Review of Public Administration, 32(1), 3-19.
Yukl, G. A. (1981). Leadership in organizations. Englewood Cliffs, NJ: Prentice-Hall.
Yukl, G. A. (2008). How leaders influence organizational effectiveness. The Leadership
Quarterly, 19(6), 708-722.
Zammuto, R. F., London, M., & Rowland, K. M. (1982). Organization and rater differences in
performance appraisals. Personnel Psychology, 35(3), 643-658. 128
Zheng, W., Yang, B., & McLean, G. N. (2010). Linking organizational culture, structure,
strategy, and organizational effectiveness: Mediating role of knowledge management.
Journal of Business Research, 63(7), 763-771.
129
APPENDIX A: HSRB APPROVAL LETTER
130
DATE: October 15, 2012
TO: Ruth Ann Petroff, Ed.D
FROM: Bowling Green State University Human Subjects Review Board
PROJECT TITLE: [383674-1] The Relationship Between Leadership Traits and Effectiveness Among the Private, Public and Non-Profit Sectors
SUBMISSION TYPE: Continuing Review/Progress Report
ACTION: APPROVED
APPROVAL DATE: October 21, 2012
EXPIRATION DATE: October 20, 2013
REVIEW TYPE: Expedited Review
REVIEW CATEGORY: Exempt review category # 4
Thank you for your submission of Continuing Review/Progress Report materials for this project. The Bowling Green State University Human Subjects Review Board has APPROVED your submission. This approval is based on an appropriate risk/benefit ratio and a project design wherein the risks have been minimized. All research must be conducted in accordance with this approved submission.
Please note that you are responsible to conduct the study as approved by the HSRB. If you seek to make any changes in your project activities or procedures, those modifications must be approved by this committee prior to initiation. Please use the modification request form for this procedure.
All UNANTICIPATED PROBLEMS involving risks to subjects or others and SERIOUS and UNEXPECTED adverse events must be reported promptly to this office. All NON-COMPLIANCE issues or COMPLAINTS regarding this project must also be reported promptly to this office.
This approval expires on October 20, 2013. You will receive a continuing review notice before your project expires. If you wish to continue your work after the expiration date, your documentation for continuing review must be received with sufficient time for review and continued approval before the expiration date.
Good luck with your work. If you have any questions, please contact the Office of Research Compliance at 419-372-7716 or [email protected]. Please include your project title and reference number in all correspondence regarding this project.
This letter has been electronically signed in accordance with all applicable regulations, and a copy is retained within Bowling Green State University Human Subjects Review Board's records.
131
DATE: September 5, 2013
TO: Ruth Ann Petroff, Ed.D
FROM: Bowling Green State University Human Subjects Review Board
PROJECT TITLE: [383674-2] The Relationship Between Leadership Traits and Effectiveness Among the Private, Public and Non-Profit Sectors
SUBMISSION TYPE: Continuing Review/Progress Report
ACTION: APPROVED
APPROVAL DATE: September 4, 2013
EXPIRATION DATE: September 3, 2014
REVIEW TYPE: Exempt Review
REVIEW CATEGORY: Exempt review category # 4
Thank you for your submission of Continuing Review/Progress Report materials for this project. The Bowling Green State University Human Subjects Review Board has APPROVED your submission. This approval is based on an appropriate risk/benefit ratio and a project design wherein the risks have been minimized. All research must be conducted in accordance with this approved submission.
Please note that you are responsible to conduct the study as approved by the HSRB. If you seek to make any changes in your project activities or procedures, those modifications must be approved by this committee prior to initiation. Please use the modification request form for this procedure.
All UNANTICIPATED PROBLEMS involving risks to subjects or others and SERIOUS and UNEXPECTED adverse events must be reported promptly to this office. All NON-COMPLIANCE issues or COMPLAINTS regarding this project must also be reported promptly to this office.
This approval expires on September 3, 2014. You will receive a continuing review notice before your project expires. If you wish to continue your work after the expiration date, your documentation for continuing review must be received with sufficient time for review and continued approval before the expiration date.
Good luck with your work. If you have any questions, please contact the Office of Research Compliance at 419-372-7716 or [email protected]. Please include your project title and reference number in all correspondence regarding this project.
This letter has been electronically signed in accordance with all applicable regulations, and a copy is retained within Bowling Green State University Human Subjects Review Board's records
132
DATE: September 4, 2014
TO: Ruth Ann Petroff, Ed.D
FROM: Bowling Green State University Human Subjects Review Board
PROJECT TITLE: [383674-3] The Relationship Between Leadership Traits and Effectiveness Among the Private, Public and Non-Profit Sectors
SUBMISSION TYPE: Continuing Review/Progress Report
ACTION: DETERMINATION OF EXEMPT STATUS
DECISION DATE: September 2, 2014 REVIEW CATEGORY: Exemption category # 4
Thank you for your submission of Continuing Review/Progress Report materials for this project. The Bowling Green State University Human Subjects Review Board has determined this project is exempt from IRB review according to federal regulations AND that the proposed research has met the principles outlined in the Belmont Report. You may now begin the research activities.
Note that an amendment may not be made to exempt research because of the possibility that proposed changes may change the research in such a way that it is no longer meets the criteria for exemption. A new application must be submitted and reviewed prior to modifying the research activity, unless the researcher believes that the change must be made to prevent harm to participants. In these cases, the Office of Research Compliance must be notified as soon as practicable. We will retain a copy of this correspondence within our records.
If you have any questions, please contact Kristin Hagemyer at 419-372-7716 or [email protected]. Please include your project title and reference number in all correspondence with this committee.
This letter has been electronically signed in accordance with all applicable regulations, and a copy is retained within Bowling Green State University Human Subjects Review Board's records.
133
APPENDIX B: DENISON CONSULTING TERMS OF USE AND DATABASE AGREEMENT
134
135
APPENDIX C: DENISON LEADERSHIP DEVELOPMENT SURVEY INSTRUMENT
136
137
138
APPENDIX D: VISUAL INSPECTION OF MEANS FOR SKEWNESS AND KURTOSIS
Involvement Trait Skewness and Kurtosis
Private Sector Public Sector Non-Profit Sector
Consistency Skewness and Kurtosis
Private Sector Public Sector Non-Profit Sector
139
Adaptability Trait Skewness and Kurtosis
Private Sector Public Sector Non-Profit Sector
Mission Trait Skewness and Kurtosis
Private Sector Public Sector Non-Profit Sector 140
APPENDIX E: DESCRIPTIVE STATISTICS OF TRAITS AND EFFECTIVENESS NOT NOT BY SECTOR
Variable N Mean SD Combined Other Involvement 7,432 5.62 .52 Combined Other Consistency 7,441 5.70 .48 Combined Other Adaptability 7,438 5.66 .46 Combined Other Mission 7,408 5.56 .51 Combined Other Effectiveness 7,568 5.59 .70 141
APPENDIX F: SUMMARY OF CASE CHARACTERISTICS
Demographic Characteristics
Characteristic N Percent Organization Type Private 5,583 78.7 Public 973 13.7 Non-Profit 541 7.6 Age 20-29 212 3.3 30-39 2,016 31.7 40-49 2,611 41.0 50-59 1,079 17.0 60 or over 62 1.0 No response 384 6.0 Gender Female 1,549 24.3 Male 4,429 69.6 No Response 385 6.1 Ethnic Background Asian 319 5.1 African American 89 1.4 Hispanic 165 2.6 White/Caucasian 4,562 72.8 Other 224 3.6 No response 904 14.4 Organizational Level Non-management 230 3.7 Line management 1,414 22.7 Middle management 1,821 29.1 Senior management 1,433 23.0 Executive/Senior Vice President 614 9.9 CEO/President 165 2.6 Owner 82 1.3 No Response 474 7.6 Years with Organization Less than 6 months 130 2.0 6 months to 1 years 285 4.5 1 to 2 years 579 9.1 2 to 4 years 1,007 15.8 4 to 6 years 849 13.3 6 to 10 years 951 14.9 10 to 15 years 874 13.7 More than 15 years 1,307 20.5 No response 382 6.0
142
Characteristic N Percent Education High school 262 4.1 Some College 659 10.4 Associates/Technical Degree 286 4.5 Bachelors 1,850 29.1 Some graduate work 495 7.8 Master’s degree 1,707 26.8 Doctoral degree 632 9.9 Other 80 1.3 No response 394 6.2 Salary 25,000 or less 21 .3 25,001 to 35,000 55 .9 35,001 to 50,000 258 4.1 50,001 to 75,000 870 13.7 75,001 to 100,000 1,075 16.9 100,001 to 150,000 1,352 21.3 150,001 to 200,000 625 9.8 200,001 plus 583 9.2 No response 1,509 23.8 Function Finance and Accounting 670 10.8 Engineering 441 7.1 Manufacturing and Production 554 8.9 Research and Development 461 7.4 Sales and Marketing 1,120 18.0 Purchasing 107 1.7 Human Resources 316 5.1 Administration 531 8.5 Support Staff 243 3.9 Professional Staff 1,037 16.7 No Response 739 11.9
143
APPENDIX G: SUMMARY OF HOMOGENEITY TESTS
Trait Test Statistic df1 df2 Sig Involvement Levene 7.06 2 6,056 .001 Brown-Forsythe 18.26 2 1,692 .000 Welch 18.73 2 1,091 .000 Consistency Levene 5.28 2 6,965 .005 Brown-Forsythe 21.83 2 1,662 .000 Welch 22.38 2 1,093 .000 Adaptability Levene 4.08 2 6,962 .017 Brown-Forsythe 22.66 2 1,708 .000 Welch 23.57 2 1,094 .000 Mission Levene 4.37 2 6,932 .013 Brown-Forsythe 24.12 2 1,702 .000 Welch 25.28 2 1,096 .000
144
APPENDIX H: RESULTS OF KRUSKAL-WALLIS TEST
Trait df χ² p M SD Mean rank low Mean rank high Involvement 2 58.07 .001 5.62 .518 3,385 3,915 Consistency 2 67.32 .001 5.70 .484 3,388 4,044 Adaptability 2 65.02 .001 5.66 .456 3,385 3,991 Mission 2 69.43 .001 5.56 .513 3,372 4,053