an examination of the relationship between emotional intelligence

An Examination of the Relationship between Emotional Intelligence, Leadership

Style and Perceived Leadership Outcomes in Australian Educational Institutions

by Paul Grunes

Presented to The School of Management, Faculty of Business, Queensland University

of Technology, for fulfillment of the requirements of the degree of Doctor of

Philosophy

Principal Supervisor: Dr Amanda Gudmundsson

Associate Supervisor: Dr Bernd Irmer

Date: 3, March 2011

ii

Abstract

In the field of leadership studies transformational leadership theory (e.g., Bass, 1985;

Avolio, Bass, & Jung, 1995) has received much attention from researchers in recent

years (Hughes, Ginnet, & Curphy, 2009; Hunt, 1999). Many previous studies have

found that transformational leadership is related to positive outcomes such as the

satisfaction, motivation and performance of followers in organisations (Judge &

Piccolo, 2004; Lowe, Kroeck, & Sivasubramaniam, 1996), including in educational

institutions (Chin, 2007; Leithwoood & Jantzi, 2005). Hence, it is important to

explore constructs that may predict leadership style in order to identify potential

transformational leaders in leadership assessment and selection procedures.

Several researchers have proposed that emotional intelligence (EI) is one

construct that may account for hitherto unexplained variance in transformational

leadership (Mayer, 2001; Watkin, 2000). Different models of EI exist (e.g., Goleman,

1995, 2001; Bar-On, 1997; Mayer & Salovey, 1997) but momentum is growing for

the Mayer and Salovey (1997) model to be considered the most useful (Ashkanasy &

Daus, 2005; Daus & Ashkanasy, 2005). Studies in non-educational settings claim to

have found that EI is a useful predictor of leadership style and leader effectiveness

(Harms & Crede, 2010; Mills, 2009) but there is a paucity of studies which have

examined the Mayer and Salovey (1997) model of EI in educational settings.

Furthermore, other predictor variables have rarely been controlled in previous studies

and only self-ratings of leadership behaviours, rather than multiple ratings, have

usually been obtained. Therefore, more research is required in educational settings to

answer the question: to what extent is the Mayer and Salovey (1997) model of EI a

useful predictor of leadership style and leadership outcomes?

This project, set in Australian educational institutions, was designed to move

iii

research in the field forward by: using valid and reliable instruments, controlling for

other predictors, obtaining an adequately sized sample of real leaders as participants

and obtaining multiple ratings of leadership behaviours.

Other variables commonly used to predict leadership behaviours (personality

factors and general mental ability) were assessed and controlled in the project.

Additionally, integrity was included as another potential predictor of leadership

behaviours as it has previously been found to be related to transformational leadership

(Parry & Proctor-Thomson, 2002). Multiple ratings of leadership behaviours were

obtained from each leader and their supervisors, peers and followers. The following

valid and reliable psychological tests were used to operationalise the variables of

interest: leadership styles and perceived leadership outcomes (Multifactor Leadership

Questionnaire, Avolio et al., 1995), EI (Mayer–Salovey–Caruso Emotional

Intelligence Test, Mayer, Salovey, & Caruso, 2002), personality factors (The Big Five

Inventory, John, Donahue, & Kentle, 1991), general mental ability (Wonderlic

Personnel Test-Quicktest, Wonderlic, 2003) and integrity (Integrity Express, Vangent,

2002).

A Pilot Study (N = 25 leaders and 75 raters) made a preliminary examination

of the relationship between the variables included in the project. Total EI, the

experiential area, and the managing emotions and perceiving emotions branches of EI,

were found to be related to transformational leadership which indicated that further

research was warranted.

In the Main Study, 144 leaders and 432 raters were recruited as participants to

assess the discriminant validity of the instruments and examine the usefulness of EI as

a predictor of leadership style and perceived leadership outcomes. Scores for each

leadership scale across the four rating levels (leaders, supervisors, peers and

iv

followers) were aggregated with the exception of the management-by-exception

active scale of transactional leadership which had an inadequate level of interrater

agreement. In the descriptive and measurement component of the Main Study, the

instruments were found to demonstrate adequate discriminant validity. The impact of

role and gender on leadership style and EI were also examined, and females were

found to be more transformational as leaders than males. Females also engaged in

more contingent reward (transactional leadership) behaviours than males, whilst

males engaged in more passive/avoidant leadership behaviours than females. In the

inferential component of the Main Study, multiple regression procedures were used to

examine the usefulness of EI as a predictor of leadership style and perceived

leadership outcomes. None of the EI branches were found to be related to

transformational leadership or the perceived leadership outcomes variables included

in the study. Openness, emotional stability (the inverse of neuroticism) and general

mental ability (inversely) each predicted a small amount of variance in

transformational leadership. Passive/avoidant leadership was inversely predicted by

the understanding emotions branch of EI. Overall, EI was not found to be a useful

predictor of leadership style and leadership outcomes in the Main Study of this

project. Implications for researchers and human resource practitioners are discussed.

v

Table of Contents

Abstract ii

Table of Contents v

List of Tables x

Statement of Original Authorship xii

Acknowledgements xiii

Chapter 1: Introduction 1

Chapter Synopsis 5

Chapter 2: Leadership, Leadership Style, Leader Effectiveness, and Emotional

Intelligence 9

Introduction 9

Leadership 11

The Leadership Function 11

Educational Leadership 12

Successful School Leadership 14

Leadership Theories 15

Trait Theory 15

Contingency Theory 16

Instructional Leadership 17

Transformational Leadership Theory 18

Full Range Leadership 19

Full Range Leadership and Leader Effectiveness 21

Transformational Leadership in Educational Settings 23

vi

Predicting Leadership Behaviours and Leader Effectiveness 28

General Mental Ability 30

Personality Factors 31

Integrity 35

Gender 37

Emotional Intelligence 38

Intelligence 38

EI Models 40

Mayer and Salovey’s Model of EI 40

Goleman’s Model of EI 43

Bar-On’s Model of EI 45

Comparison of EI Models and the Case for the Abilities Model 46

Relationship between EI and Performance Outcomes 48

Relationship between EI and Leadership 49

Relationship between the Mayer and Salovey (1997) Model of EI, Leadership

Style and Leadership Outcomes in Non-educational Settings 50

Relationship between EI, Leadership Style and Leadership Outcomes, and the

Impact of Gender in Non-Educational Settings 58

Relationship between EI, Leadership Style and Leadership Outcomes in

Educational Settings 59

Critique of Previous Research 61

Direction for Future Research 63

Conclusion 67

Chapter 3: Project Design 69

vii

Introduction 69

Selection of a Research Paradigm 70

Psychological Tests 74

Multiple Ratings of Leadership Behaviours 77

Educational Leadership in Australia 81

Role of School Leaders 83

Selection of School Leaders 85

Research Aims 88

Ethical Considerations 90

Conclusion 91

Chapter 4: Pilot Study 93

Introduction 93

Independent Variables and Dependent Variables 94

Research Questions and Hypotheses 95

Methodology 96

Participants and Procedure 96

Instruments 98

Multifactor Leadership Questionnaire 98

Mayer–Salovey–Caruso Emotional Intelligence Test 101

The Big Five Inventory 105

Wonderlic Personnel Test-Quicktest 107

Integrity Express 109

Results 111

Data Screening 113

viii

Descriptive Statistics 113

Bivariate Analysis 115

Discussion 127

Conclusion 130

Chapter 5: Main Study - Descriptive and Measurement Component 132

Introduction 132

Independent Variables and Dependent Variables 132

Research Questions and Hypotheses 133

Methodology 134


Instruments 135

Results 136

Data Screening 139



Discussion 157

Conclusion 161

Chapter 6: Main Study - Inferential Component 163

Introduction 163

Independent and Dependent Variables 163

Research Questions 164

Methodology 165


ix

Instruments 165

Results 165

Data Screening 166



Multivariate Analysis 168

Results 168

Discussion 180

Conclusion 185

Chapter 7: Discussion, Limitations and Recommendations 187

Introduction 187

Discussion 188

Limitations 195

Recommendations 197

Conclusion 201

References 206

Appendix A: Example Invitation

Appendix B: Example Instructions for Leader

Appendix C: Example Instructions for Rater

x

List of Tables

Table 1: Full Range Leadership: Styles, Scales and Example Behaviours

Identified by Avolio (1999) and Bass (1999) 21

Table 2: Factors and Domains of Costa and McCrae‟s (1995) Five-Factor

Model of Personality 32

Table 3: Areas, Branches and Abilities of Mayer and Salovey‟s (1997) 42

Model of Emotional Intelligence

Table 4: Domains and Competencies of Goleman‟s (2001) Model of 44

Emotional Intelligence

Table 5: Components and Competencies of Bar-On‟s (2006) Model of 46


Table 6: Summary of Research Questions and Hypotheses 66

Table 7: Duties of the Principal, Deputy Principals and Heads of Department

in Public Schools in Queensland, Australia 84

Table 8: Selection Criteria for Principal, Vice-Principal and Head of

Department in Public Schools in Queensland, Australia 87

Table 9: Independent and Dependent Variables 95

Table 10: Descriptive Statistics for Pilot Study Variables 114

Table 11: Inter-correlations between Pilot Study Variables 116

Table 12: Descriptive Statistics for Main Study Variables 142

Table 13: Inter-correlations between Main Study Variables 144

Table 14: Summary of Regression Model 1 for Variables Predicting

Transformational Leadership 170


Satisfaction (of Followers) 172

xi


Effectiveness (of Individual/Group) 174


Extra Effort (of Followers) 175


the Contingent Reward Scale of Transactional Leadership 177


Passive/Avoidant Leadership 179

Table 20: Summary of Research Questions, Hypotheses and Findings 190

of Each Study

xii

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet

requirements for an award at this or any other higher educational institution. To the

best of my knowledge and belief, the thesis contains no material previously published

or written by another person except where due reference is made.

Signature: Paul Grunes

Date: 3, March 2011

xiii

Acknowledgements

I thank my Principal Supervisor, Dr Amanda Gudmundsson, and my

Associate Supervisor, Dr Bernd Irmer, for the part they played in guiding me through

the PhD process. I also thank my Protem Supervisor, Dr Kym Irving. Additionally, I

am grateful for the scholarship funding provided to me by Queensland University of

Technology which enabled me to undertake this project.

1

An Examination of the Relationship between Emotional Intelligence, Leadership

Style and Perceived Leadership Outcomes in Australian Educational Institutions

Chapter 1: Introduction

This is an international “golden age” of school leadership (Leithwood & Day,

p. 1, 2007). A body of international empirical research now exists which confirms the

importance of effective school leadership (Leithwood & Jantzi, 2005; Leithwood,

Seashore Louis, Anderson, & Wahlstrom, 2004; Leithwood, Day, Simmons, Harris, &

Hopkins, 2006). Influenced by this body of work, governments around the world are

allocating considerable resources to the assessment, selection and development of

school leaders as effective leadership is deemed vital if policy reforms are to be

implemented successfully (Mulford, 2007). Current trends in school leadership

include an ongoing move towards the self-management of schools and the distribution

of leadership within schools. Also, the performance of educational institutions,

highlighted by quality indicators such as league tables and lists of characteristics of

effective schools, has become much more prominent in recent years (Christie &

Lingard, 2001). Furthermore, there is an ongoing desire to reduce the disparities in

educational performance between various social and ethnic groups (Robinson, Lloyd,

& Rowe, 2008). In an attempt to meet these challenges the role of the educational

leader has changed. The importance of leadership rather than traditional educational

functions such as instruction is now emphasised (Christie & Lingard, 2001). Christie

and Lingard (2001) propose that the increase in the prominence of institutional

performance has created a new discourse of effectiveness, efficiency and

accountability. This emphasis on performance is the outcome of economic rationalism

and is related to corporate managerialism (Christie & Lingard, 2001). Hence, school

leaders are under unprecedented pressure to meet performance targets as in the realms

2

of the corporate world. This has led to a growing interest in cross-disciplinary

approaches to educational leadership. Educational researchers have become more

interested in leadership theories such as transformational leadership (Bass, 1985)

which originated in the management literature, whilst human resource practitioners in

educational settings have become more interested in the assessment and selection

methods used in corporate domains. According to Leithwood and Sleegers (2006)

future research which explores transformational leadership is especially timely as

questions about the relative value of various approaches to school leadership are being

raised by researchers and human resource practitioners who are aiming to meet the

mandates of reform-seeking policy makers. It is within this context that this

leadership project is based.

Leadership is considered by many to be an essential function in organisations

and as such it attracts ongoing research interest. Several leadership theories exist but

transformational leadership (Bass, 1985) has emerged as one of the most widely

researched theories in the field (Hughes, Ginnet, & Curphy, 2009; Hunt, 1999). Many

studies have found that transformational leadership is related to positive outcomes

such as the satisfaction, motivation and performance of followers in organisations

(Judge & Piccolo, 2004; Lowe, Kroeck, & Sivasubramaniam, 1996), including

educational institutions (Chin, 2007; Leithwoood & Jantzi, 2005). Hence, it is

important to explore constructs which may predict leadership style. Several

researchers have proposed that the emotional intelligence (EI) construct is worthy of

further investigation in this capacity (Ashkanasy & Daus, 2005; Daus & Ashkanasy,

2005). Interest in EI generates from the possibility that it may account for aspects of

workplace performance that cannot be accounted for by other constructs (Mayer,

2001; Watkin, 2000). Alternative concepts of EI have been developed by: Mayer and

3

Salovey (1990, 1997), Goleman (1995, 2001) and Bar-On (1997). There have been

premature attempts to apply EI concepts in the workplace (Antonakis, Ashkanasy, &

Dasborough, 2009) but more empirical research needs to be undertaken to assess the

EI construct prior to its further application (Ashkanasy & Daus, 2005; Daus &

Ashkanasy, 2005). Furthermore, claims about the significance of EI made by

Goleman (1995) have not been supported by empirical studies and have tarnished the

reputation of the construct (Mayer, Salovey, & Caruso, 2004). However, momentum

is now growing for the Mayer and Salovey (1997) 'abilities' model to be considered

the most useful model of EI (Ashkanasy & Daus, 2005; Daus & Ashkanasy, 2005),

and this model is considered to be worthy of further investigation (Van Rooy &

Viswesvaran, 2004).

Several studies based in non-educational settings have found that EI is a useful

predictor of leadership style and leader effectiveness (e.g., Coetzee & Schaap, 2005;

Kerr, Garvin, Heaton, & Boyle, 2006; Leban, 2003; Srivsastava & Bharamanaikar,

2004), but as EI has rarely been compared with other predictors in these studies

questions related to the divergent and incremental validity of EI remain unanswered.

Also, although several studies in educational settings have employed the Goleman

(1995) and Bar-On (1997) models of EI, there is a paucity of studies which have

examined the relationship between EI and leadership styles using the Mayer and

Salovey (1997) model in this context. Furthermore, as almost all previous studies

have only obtained self-ratings of leadership behaviours, rather than multiple

independent ratings, self-serving bias is likely to have resulted in an overestimation of

positive leadership behaviours and an inflation of the association between EI and self-

rated leadership behaviours due to common method variance. This has limited the

validity of the findings of previous studies. Therefore, there is scope for further

4

research in educational institutions that applies a high level of methodological rigor to

address the question: to what extent is the Mayer and Salovey (1997) model of EI a

useful predictor of leadership style and leadership outcomes? This overarching

question may be broken down into a series of questions such as: Is the Mayer and

Salovey (1997) model of EI related to leadership style and leadership outcomes? Does

the Mayer and Salovey (1997) model of EI have divergent validity from general

mental ability (GMA) and personality factors? Is the Mayer and Salovey (1997)

model of EI able to predict leadership style and leadership outcomes when multiple

ratings of leadership behaviours are obtained? Does the Mayer and Salovey (1997)

model of EI have incremental validity above other predictors of leadership style and

leadership outcomes? These and other questions will be examined in this project.

The project replicates previous research in the field by examining the

relationship between EI, leadership style and perceived leadership outcomes, and by

assessing whether EI has discriminant validity from established predictors of job

performance, and incremental validity above these constructs. Predictors are selected

from individual difference variables commonly used to predict leadership behaviours

and leader effectiveness (GMA and personality factors). The project advances

research in the field by obtaining multiple ratings of leadership behaviours and by

including integrity as an additional potential predictor. The impact of role and gender

on leadership style and EI are also examined. The following variables are

operationalised using valid and reliable psychological tests: leadership styles and

perceived leadership outcomes (Multifactor Leadership Questionnaire, Avolio, Bass,

& Jung, 1995), EI (Mayer–Salovey–Caruso Emotional Intelligence Test, Mayer,

Salovey, & Caruso, 2002), personality factors (The Big Five Inventory, John,

Donahue, & Kentle, 1991), GMA (Wonderlic Personnel Test-Quicktest, Wonderlic,

5

2003) and integrity (Integrity Express, Vangent, 2002a).

Initially, a Pilot Study (N = 25 leaders and 75 raters) is undertaken to make a

preliminary examination of the relationship between EI and leadership style, and EI

and perceived leadership outcomes, and investigate whether further research is

warranted. Then, in the descriptive and measurement component of the Main Study

(N = 144 leaders and 432 raters) the discriminant validity of the instruments selected

for the project is assessed using bivariate analysis. The impact of role and gender are

also examined. Subsequently, in the inferential component of the Main Study multiple

regression procedures are used to examine the usefulness of EI as a predictor of

leadership style and perceived leadership outcomes, and to determine whether or not

EI is able to explain additional variance when other predictor variables are controlled.

The findings of the project will increase the theoretical understanding of the

relationship between EI, leadership style and leadership outcomes, and contribute to a

body of literary work assessing the usefulness of EI as a predictor of leadership style

and leadership outcomes. Further knowledge related to the antecedents of

transformational leadership will be gained by the examination of the other predictors

included in the project. Feedback will be offered to participants and represents an

intervention that may contribute to their development as leaders. The project also

aims to provide human resource practitioners with an empirical platform on which to

base their decisions to introduce, or relinquish, EI measures as part of leadership

assessment and selection procedures in Australian educational institutions.

Chapter Synopsis

Chapter 2 commences by reviewing the literature related to the most important

leadership theories and highlights the benefits of transformational leadership in

organisations, including schools. Established predictors of leadership behaviours and

6

leader effectiveness are presented from the literature, and the need to continue to

explore other potential predictors such as EI is noted. Then, the three main EI

concepts are described, compared and assessed, and a case for the superiority of the

'abilities' model is presented. Subsequently, the literature is reviewed based on

empirical studies which have employed a psychological testing approach to examine

the relationship between EI, leadership style and leadership outcomes. Finally, a

research project set in Australian educational institutions is proposed to address the

main research question: to what extent is the Mayer and Salovey (1997) model of EI a

useful predictor of leadership style and leadership outcomes? Hypotheses and

research questions are presented.

Chapter 3 presents a design framework for a research project set in Australian

educational institutions that addresses the main research question: to what extent is

the Mayer and Salovey (1997) model of EI a useful predictor of leadership style and

leadership outcomes? Initially, an explanation is made for the selection of a

quantitative research methodology which uses psychological testing, and the strengths

and weaknesses associated with this method are highlighted. The importance of

collecting data related to leadership behaviours from multiple sources is discussed.

Then, the role of the school leader in Australia is outlined and selection criteria for the

role are presented. Subsequently, the project aims are identified. Finally, ethical

considerations related to the project are noted.

Chapter 4 reports on a Pilot Study that makes an examination of the

relationship between EI and leadership style, and EI and perceived leadership

outcomes, and investigates whether further research is warranted. The independent

and dependent variables examined in the Pilot Study are presented, followed by the

research questions and hypotheses formulated to test the relationships between the

7

variables. The methodology for undertaking the Pilot Study is outlined with reference

to the procedure, participants and instruments selected. Each instrument is described

and evaluated in terms of its purpose, development, administration and psychometric

properties. Then, methods for data entry and the data screening process are described.

Subsequently, descriptive statistics and the results of correlation and difference

between the means procedures undertaken are reported and discussed. Finally, the

methodology used in the Pilot Study is discussed with regard to its suitability for use

in a further study.

Chapter 5 reports on the descriptive and measurement component of the Main

Study. Initially, research questions and hypotheses formulated to test the discriminant

validity of the instruments selected for the project are presented. The impact of role

and gender on leadership style and EI are also examined. The methodology for the

Main Study is outlined with regards to the procedure, participants and instruments

selected. Then, the data entry and data screening processes are described.

Subsequently, descriptive statistics and the results of correlation and difference

between the means procedures undertaken are presented. Finally, the results from the

descriptive and measurement component of the Main Study are discussed and the

methodology is assessed.

Chapter 6 reports on the inferential component of the Main Study which

examines the usefulness of EI as a predictor of leadership style and perceived

leadership outcomes. Initially, the research questions formulated to be examined in

the inferential component of the Main Study are presented. Then, the methodology is

outlined with regard to the procedure, participants and instruments selected. Methods

for data entry, data screening and the results of multivariate analysis are presented.

Finally, the methodology and results from the inferential component of the Main

8

Study are discussed.

Lastly, in Chapter 7, the findings of the project are discussed and the

implications for researchers and human resource practitioners in Australian

educational institutions are reported. The limitations of the project are noted and

recommendations are made for further research in the field.

9

Chapter 2: Leadership, Leadership Style, Leader Effectiveness and Emotional

Intelligence

Introduction

Leadership is considered by many to be an essential function in organisations,

including educational institutions, hence it attracts ongoing research interest. Several

leadership theories exist but transformational leadership theory has emerged as one of

the most widely researched theories in the field (Hughes et al., 2009; Hunt, 1999).

Many studies have found that transformational leadership is related to positive

performance outcomes in organisations (Chin, 2007; Judge & Piccolo, 2004;

Leithwoood & Jantzi, 2005; Lowe et al., 1996), hence, it is important to explore

constructs that may predict leadership style and that may ultimately contribute to

improved methods of leadership assessment and selection in educational institutions.

Emotional Intelligence (EI) is thought by several researchers (Ashkanasy & Daus,

2005; Daus & Ashkanasy, 2005) to be worthy of further investigation in this capacity

as it may account for variance in workplace performance that cannot be accounted for

by other constructs (Mayer, 2001; Watkin, 2000). Alternative concepts of EI have

been developed by: Mayer and Salovey (1990, 1997), Goleman (1995, 2001) and Bar-

On (1997). Momentum is now growing for the Mayer and Salovey (1997) 'abilities'

model to be considered the most useful model of EI (Ashkanasy & Daus, 2005; Daus

& Ashkanasy, 2005) and this model is considered to be worthy of further

investigation (Van Rooy & Viswesvaran, 2004). Premature attempts to apply EI

theories in the workplace have been made (Antonakis et al., 2009) but more empirical

research which examines the usefulness of the EI construct is required before further

attempts are made.

One important question that remains unanswered is: to what extent is the

10

Mayer and Salovey (1997) model of EI a useful predictor of leadership style and

leadership outcomes? This overarching question may be broken down into a series of

related questions: Is the Mayer and Salovey (1997) model of EI related to leadership

style and leadership outcomes? Does the Mayer and Salovey (1997) model of EI have

divergent validity from GMA and personality factors? Is the Mayer and Salovey

(1997) model of EI able to predict leadership style and leadership outcomes when

multiple ratings of leadership behaviours are obtained? Does the Mayer and Salovey

(1997) model of EI have incremental validity above other predictors of leadership

style and leadership outcomes?

Although several studies in non-educational settings have found that EI is a

useful predictor of leadership style and leader effectiveness (e.g., Coetzee & Schaap,

2005; Kerr et al., 2006; Leban, 2003; Srivsastava & Bharamanaikar, 2004), the impact

of other predictors has rarely been examined in these studies which limits the validity

of their findings. Additionally, multiple independent ratings of leadership behaviours,

rather than self-ratings have rarely been obtained. Furthermore, although several

studies in educational settings have employed the Goleman (1995) and Bar-On (1997)

models of EI, there are few studies which have examined the relationship between EI

and leadership styles using the Mayer and Salovey (1997) model in this context.

Therefore, more research is required in order to determine whether or not the Mayer

and Salovey (1997) model of EI is a useful predictor of leadership style and

leadership outcomes in educational institutions.

This chapter commences by highlighting the importance of leadership in

organisations, including in schools. Then, the components of the most significant

leadership theories are described, including full range leadership (Avolio, 1999; Bass,

1999) which forms the basis of the theoretical framework for this project, and the

11

benefits of transformational leadership style (Bass, 1985) are highlighted. Established

predictors of leadership behaviours and leader effectiveness based on individual

differences are then presented from the literature. Subsequently, the three main

conceptualisations of the EI construct are described, compared and assessed, and a

case for the superiority of the 'abilities' model is presented. Then, empirical studies are

reviewed which have employed psychological testing methods to examine the

relationship between EI, leadership style and leadership outcomes. Finally, a research

project set in Australian educational institutions is proposed that uses psychological

testing methods to answer the main research question: to what extent is the Mayer and

Salovey (1997) model of EI a useful predictor of leadership style and leadership

outcomes? Specific research questions and hypotheses are presented for investigation.

Leadership

The Leadership Function

Leadership is considered by many to be an essential function in organisations

and it attracts ongoing research interest in many settings, including in educational

institutions. The complexity of leadership has led to it being defined in many different

ways. Fiedler (1967, p. 147) defines a leader as “the person in a group who directs

and coordinates task-oriented group activities.” According to Yukl (2002, p. 7)

“leadership is the process of influencing others to understand and agree about what

needs to be done and how it can be done effectively, and the process of facilitating

individual and collective efforts to accomplish shared objectives". Whereas, Roach

and Behling (1984, p. 46) propose that “Leadership is defined as the process of

influencing the activities of an organised group toward goal achievement.”

Just as the definitions of leadership vary so does the domain in which it is

thought to be based as leadership is often considered to be both a science and an art

12

(Hughes et al, 2009). As with any emerging science leadership researchers are still

attempting to discover the important questions and find conclusive answers to them.

However, even leaders with extensive knowledge of existing leadership research may

be poor at practicing leadership. Hence, the art of leadership concerns the skill of

understanding leadership situations and influencing others to accomplish group goals

(Hughes et al., 2009). Sometimes leadership may be accomplished through rational,

explicit rule based methods of assessing situations and determining actions. However,

as leadership is a social process shared among all members of a group, leaders must

also consider the emotional consequences when attempting to influence others.

Hence, leaders are often most effective when they affect people at both the emotional

and rational level (Hughes et al., 2009).

Leadership is often confused with management (Yukl, 2002) but they are

diverse roles which can be both contradictory and complementary (Kotter, 2001).

Kotter (2001) suggests that many organisations are overmanaged and underled.

Managers focus on planning, controlling and organising in order to promote stability.

Whereas, leaders focus on direction setting, developing a vision for the future and

producing change. Furthermore, Kotter (2001) argues that leaders should inspire,

develop and empower their followers. Avolio (1999) proposes that when a leadership

system is 'optimised' the quality of the relationships among leaders, peers and

followers are enhanced, resulting in benefits for both the individual and the

organisation. Therefore, as leadership is an important and unique function, effective

methods of leadership selection and assessment need to be conducted by

organisations.

Educational Leadership

Many researchers argue that successful schools are headed by principals who

13

are effective leaders and who have a clear sense of direction for their schools (Waters,

Marzano, & McNultry, 2003). There is also a considerable amount of research which

confirms that the achievements of students increase when effective leadership is

practiced in schools (Waters et al., 2003). Andrews and Soder (1987) completed a

two-year study that evaluated the relationship between principal leadership and

student achievement in Seattle, Washington, United States of America (USA). A

questionnaire was administered to all district instructional staff to measure 18

strategic interactions between principals and teachers in relation to the principal as: a

resource provider, an instructional resource, a communicator and a visible presence.

Scores for students on the California Achievement Test were used as a measure of

academic performance. Andrews and Soder (1987) found that the gains for students in

total reading and total mathematics were significantly higher in schools with strong

leaders compared to the gains achieved by students in schools rated as having average

or weak leaders. The relationship between gains in student performance and schools

with strong principal leadership was even greater in schools that had a high proportion

of minority students.

In a further meta-analysis conducted in 1998 by the Mid-continent Research

for Education and Learning in the USA, the effects of instruction and schooling on

student achievement were analysed. The meta-analysis included studies undertaken

over a thirty-year period. Characteristics of students, practices of teachers and school

practices associated with school effectiveness were analysed. Researchers identified

21 leadership responsibilities that were significantly associated with student

achievement. Most importantly, researchers found that principals who improved on

these 21 leadership responsibilities had a significant positive effect on student

achievement in their schools (Waters et al., 2003). Hence, effective leadership in

14

schools is considered to have positive performance outcomes. Therefore, it is

important to be able to identify potentially effective leaders in assessment and

selection procedures in order to ensure that more schools are led by effective leaders.

Successful School Leadership

Leithwood, Harris and Hopkins (2007) summarised the main findings from the

international literature related to successful school leadership. Based on empirical

evidence, the authors presented seven strong claims related to school leadership.

Firstly, the authors considered school leadership to be second only to classroom

teaching as an influence on student learning. Secondly, almost all successful leaders

were considered to use the same basic leadership practices, specifically: building

vision and setting directions, understanding and developing people, redesigning the

organisation, and managing the teaching and learning program. Thirdly, the ways in

which leaders were thought to apply these leadership practices demonstrated

responsiveness to the contexts in which they work. Fourthly, Leithwood et al. (2007)

suggested that school leaders were thought to improve teaching and learning

indirectly and most powerfully through their influence on staff motivation,

commitment and working conditions. Fifthly, school leadership was thought to have a

greater influence on schools and students when it was distributed. Sixthly, some types

of distribution were thought to be more effective than others. Lastly, Leithwood et al.

(2007) proposed that a few personal traits were thought to explain a high proportion

of the variation in leadership effectiveness.

Whilst the importance of leadership in schools has been widely acknowledged

and claims have been made regarding how successful school leadership is applied, it

is important to be able to identify what makes an effective leader. This requires an in-

depth analysis of the leadership process. Several theories have been developed in an

15

attempt to conceptualise and explain leadership.

Leadership Theories

Leadership theories such as trait theory (e.g., Mann, 1959; Stogdill, 1948),

contingency theory (e.g., Evans, 1970; Fiedler, 1967; Hersey & Blanchard, 1969;

Vroom & Yetton, 1973) and transformational leadership theory (e.g., Bass, 1985)

have all made an important contribution to the field. Each of these theories

emphasises the importance of individual differences in the leadership process.

Trait Theory

Traits are enduring aspects of personality that are often used to categorise

individuals. Trait theorists argue that certain personality characteristics predispose

individuals to emerge as leaders (Northouse, 1997). Prior to the emergence of a

widely accepted model of personality, early research that attempted to use traits to

identify leaders (e.g., Mann, 1959; Stogdill, 1948) often used poorly defined traits and

underdeveloped measures (Lord, DeVader, &Alliger, 1986). Stogdill (1948)

summarised the results of studies which had examined whether certain personality

traits, physical attributes, intelligence or personal values differentiated leaders from

followers. Stogdill (1948) concluded that whilst leaders were not quantitatively

different from followers in many respects (e.g., height, level of outgoingness), some

characteristics such as intelligence, initiative, stress tolerance, responsibility,

friendliness and dominance were moderately related to leadership success. However,

whilst attributes such as personality and intelligence were considered to help a leader

influence a group towards accomplishing goals they did not guarantee success. The

situation was thought to dictate which personality traits or components of intelligence

positively affect a leader's ability to build a team or achieve results through others.

Interest in trait theory waned as a result of poorly defined traits and underdeveloped

16

measures (Lord et al., 1986). However, since the development of the five-factor

model of personality, and valid and reliable instruments, interest in research related to

traits has been rekindled.

Contingency Theory

Contingency theorists propose that leader effectiveness is dependent on the

interaction between the personal characteristics of the leader and the situation in

which the leader is based (Fiedler & Chemers, 1974). The degree of control the leader

has over a given situation is considered to be a mediating factor that determines the

effectiveness of the leader. Several contingency theories exist including: the

normative decision model (Vroom & Yetton, 1973), the situational leadership model

(Hersey & Blanchard, 1969), the contingency model (Fiedler, 1967) and the path-goal

theory (Evans, 1970).

Chemers (1984) proposed that these four models shared more similarities than

differences. Contingency theorists assert that leaders should be matched with

particular situations based on their personal characteristics in order to increase leader

effectiveness (Northouse, 1997). Chemers (1984) argued that the models differed

primarily in terms of the types of situation and follower characteristics upon which

leader behaviours should be contingent. All four models address certain aspects of the

leader, the followers and the situation. All of the models specify that leaders should

make their behaviours contingent on certain aspects of the followers, or the situation,

in order to improve leadership effectiveness. Additionally, all four models assume

that leaders can accurately assess important follower and situational factors. Apart

from in Fiedler's (1967) model, leaders are assumed to be able to act in a flexible

manner which enables them to alter their behaviours when situational and follower

characteristics change. Furthermore, a correct match between situational and follower

17

characteristics is assumed to have a positive effect on group or organisational

outcomes (Chemers, 1984).

It has proved difficult and impractical to replicate these assumptions in applied

settings (Korman, 1973), hence the validity of contingency theory remains relatively

unproven (Peters, Hartke, & Polemann, 1985). In practice different leaders in the

same situation may reach entirely different conclusions about: followers' levels of

knowledge, the strength of leader-follower relationships, the degree of task structure

and the level of role ambiguity experienced by followers. These differences in the

perception of the leaders may result in different conclusions about the situation being

reached which may cause the leaders to take different actions in response to the

situation. These actions may be in accordance with, or in conflict with, the content of

the four contingency models. This may explain why these four models have reported

conflicting findings in field settings (Hughes et al., 2009). None of the contingency

models take into account how levels of stress, working conditions, technology,

economic conditions and types of organisational culture, climate, or design, affect the

leadership process (Hughes et al., 2009). Another reason why contingency theories

have found limited support in field settings is the fact that they are fairly limited in

scope. Many of the factors that affect leader and follower behaviours in work settings

are not present in laboratory studies. Nevertheless, contingency theories have been the

subject of considerable research and this research has added to the body of knowledge

about leadership.

Instructional Leadership

One form of leadership specific to educational settings is instructional

leadership. The concept emerged in the early 1980s when it was proposed that

principals of effective schools emphasised the importance of instructional, or

18

academic, leadership rather than administrative leadership. Instructional leadership is

practised when actions that promote the growth of student learning are prioritised.

These actions may include: clear goal setting, allocating resources to instruction,

managing the curriculum, evaluating teachers and monitoring lesson plans (Lashway,

2002). The principal focuses on improving teaching and learning rather than on

administrative tasks. More recently, the concept has evolved to emphasise: learning

rather than teaching (DuFour, 2002), more sophisticated professional development

and the use of data to make decisions (King 2002). In practice instructional leadership

has proved difficult to achieve as it requires the role of the principal to be redefined

and bureaucratic structures that are considered to be barriers to leadership need to be

removed. Also, as the focus is on teaching and learning staff and administrative tasks

may be neglected. Hence, instructional leadership has not proven to be totally

satisfactory as a form of educational leadership.

Transformational Leadership Theory

The transformational leadership construct was initially proposed by Burns

(1978) following a qualitative analysis of the biographies of political leaders.

Subsequently, many other researchers have developed the construct (e.g., Bass 1985;

Conger & Kanungo, 1987; Podsakoff, McKenzie, Moorman, & Fetter, 1990; Yukl,

1989). Burns (1978) proposed that leaders could be classified as either

transformational or transactional and considered the two styles to be distinct. Burns

(1978) suggested that transactional leaders exchanged rewards contingent upon a

display of desired behaviors. Whereas, the engagements between transformational

leaders and followers transcended individual objectives, and led to the formation of

collective goals that resulted in increased work effectiveness.

In comparison with Burns (1978), Bass (1985) viewed transformational

19

leadership and transactional leadership as complementary rather than polar constructs.

Bass (1985) recognised that both styles may be linked to the achievement of

organisational goals and suggested that transformational leadership augmented

transactional leadership. This led to the development of the full range leadership

model (Avolio, 1999; Bass, 1999).

Full Range Leadership

Full range leadership (Avolio, 1999; Bass, 1999) was developed from

transformational leadership theory (e.g., Bass, 1985; Avolio et al., 1995) and has

generated a considerable amount of confirmatory research. Avolio (1999) bases his

framework for full range leadership development on: people, timing, resources, the

context of interaction, and the expected results in performance and motivation. The

full range leadership model (Avolio, 1999; Bass, 1999) identifies three contrasting

leadership styles; transformational, transactional and passive/avoidant.

Transformational leadership is characterised by: idealised attributes, idealised

behaviours, inspirational motivation, intellectual stimulation and individualised

consideration (Bass, 1990a). Leaders who exhibit idealised attributes and idealised

behaviours instill admiration, trust and respect in their followers, and set high ethical

standards through outstanding accomplishments (Bass, 1985). They are considered to

be: outgoing, sociable, insightful and inspiring (Atwater, Penn, & Rucker, 1993).

Leaders who engage in inspirational motivation encourage their followers to

enthusiastically commit themselves to organisational goals and work as a team (Bass,

1985). Inspirational motivation is practiced by leaders who set high standards for

performance, and display confidence and energy when communicating the

organisational vision to followers (Bass, 1985; Bass, 1990b). The idealised influence

and inspirational motivation dimensions may be combined to form a measure of

20

charisma (Bass, 1998). Intellectual stimulation is demonstrated by leaders who

challenge, support and foster the development of creative thinking among their

followers (Bass, 1985). Lastly, leaders who engage in individualised consideration

treat their followers as individuals, interact with them in a consistent manner, express

genuine concern for their welfare (Bass, 1985; Bass, 1990b) and guide them to reach

their fullest potential (Bass, 1985).

In contrast, transactional leadership is based on contingent rewards and

management-by-exception active (Bass, 1990a). Unlike transformational leaders,

transactional leaders tend to engage in behaviours that may enhance their own status,

and may use followers for their own advancement (Northouse, 1997; Bass & Avolio,

1994). A leader engages in contingent reward by rewarding followers for acceptable

behaviours and penalising them for unacceptable behaviours (Bass, 1990b). This type

of leadership is contingent upon an exchange of rewards between a leader and their

followers (Bass, 1990b). Typically, leaders who engage in management-by-exception

active accept traditional methods of work and do not encourage their followers to

engage in innovative problem solving activities (Bass, 1985).

The passive/avoidant leadership style consists of two recognised factors: the

laissez-faire approach and management-by-exception passive. The laissez-faire

approach is characterised by the abdication of responsibility and avoidance in

decision making (Bass, 1990a), whereas management-by-exception passive is a form

of non-leadership and occurs when a leader chooses to avoid leadership duties

altogether (Avolio, Bass, & Jung, 1999).

Avolio et al. (1999) propose that all leaders display aspects of each leadership

style but leaders with the optimal profile display aspects of transformational

leadership most frequently and passive/avoidant leadership least frequently. The full

21

range leadership styles, scales and example behaviours identified by Avolio (1999)

and Bass (1999) are presented in Table 1.

Table 1

Full Range Leadership Styles, Scales and Example Behaviours Identified by Avolio

(1999) and Bass (1999)

Leadership Style Scales Example Behaviours

Transformational leadership Idealised attributes Committed and trustworthy

Idealised behaviours Ethical consequences of decisions are

considered important

Inspirational motivation Confident, articulates vision of future

and encourages others

Intellectual stimulation Questions the norm and facilitates

expression of ideas

Individualised consideration Considers individual abilities, needs

and aspirations

Transactional leadership Contingent reward Negotiates for resources and rewards

achievements

Management-by-exception

active

Takes action following mistakes

Passive/avoidant leadership Management-by-exception

passive

Does not take action until mistakes

are noticed and problems escalate

Laissez-faire Unwilling to accept responsibilities

and not present when needed

Full Range Leadership and Leader Effectiveness

Many studies have found that transformational leadership style is positively

related to the satisfaction, motivation and performance of followers (Judge & Piccolo,

2004; Lowe et al., 1996), and increased productivity and innovation in organisations

22

(Bass, 1999). Consequently, transformational leaders are highly sought after in many

types of organisations and the importance of transformational leadership in

educational settings is well established (Chin, 2007; Leithwoood & Jantzi, 2005;

Sergiovanni, 1984, 1990).

Transformational leadership has been linked with many positive outcomes in

organisations, such as: enhanced job satisfaction, increased commitment, increased

productivity and decreased stress levels among followers (Northouse, 1997).

Transformational leadership may also have a positive effect on organisational culture

by engaging followers to work towards common organisational goals (Kickul &

Neuman, 2000). Transformational leadership is considered to have a positive impact

on organisational effectiveness, irrespective of whether effectiveness is determined by

the perceptions of followers or by organisational measures (Lowe et al., 1996).

Judge and Piccolo (2004) conducted a meta-analysis that tested the validity of

transformational, transactional and passive/avoidant leadership. Using regression

analysis, the authors assessed the contribution of each leadership style to the

prediction of criteria related to organisational leadership. The criteria were: follower

job satisfaction, follower satisfaction with leader, follower motivation, leader job

performance, leader effectiveness and group or organisation performance. Results

were based on 626 correlations from 87 sources. Participants in these studies included

business professionals, college students, members of the military and public servants.

Transformational leadership demonstrated an overall validity of .44 with the

organisational leadership criteria. Differences among each organisational setting were

not significant. The contingent reward (ρ = .39) and laissez-faire (ρ = -.37)

dimensions had the next highest overall relations with the organisational leadership

criteria, while management-by-exception active and management-by-exception

23

passive were inconsistently related to the criteria. This meta-analysis presents strong

evidence for the ability of transformational leadership to impact on organisational

leadership outcomes which underlines its position as the dominant leadership theory.

In some circumstances, such as when stability rather than change is required,

transactional leadership may also be positively related to organisational effectiveness.

In contrast, passive/avoidant leadership is not positively related to leader effectiveness

(Judge & Piccolo, 2004; Lowe et al., 1996). Avolio et al. (1999) argue that it is

possible for leaders to develop a transformational leadership style. Furthermore, as

Transformational leadership theory (Bass, 1985; Avolio et al., 1995) has been the

subject of a considerable amount of confirmatory research (Hughes et al., 2009; Hunt,

1999) it is important for researchers to explore constructs that may impact on and

predict leadership style and outcomes.

Transformational Leadership in Educational Settings

Transformational leadership theory (Bass, 1985; Avolio et al., 1995) has been

the subject of considerable interest from both researchers and human research

practitioners in the field of educational leadership. Traditionally, the implementation

of instructional and transactional leadership methods had been popular in educational

settings. Instructional leadership has been described as a 'top-down' hierarchical style

that focuses on the growth of students, but not on the growth of teachers (Liontos,

1992). Whereas, transactional leadership involves an exchange of services for various

rewards which are controlled, and may be manipulated, by the leader (Bass, 1985).

The limitations of instructional and transactional leadership led to interest in the

application of transformational leadership in schools. Subsequently, many researchers

in the field of educational leadership have found that transformational leadership has

considerable advantages when compared with instructional or transactional leadership

24

(Liontos, 1992).

Sergiovanni (1984, 1990) argued that transactional leadership does not

stimulate improvement in schools and that student achievement can be remarkably

improved by transformational leadership. Sergiovanni (1984, 1990) proposed that

several alternative dimensions of transformational leadership were relevant in schools,

notably: technical leadership (sound management techniques), human leadership

(harnessing social and interpersonal potential), educational leadership (principal

demonstrates expert knowledge), symbolic leadership (modeling of important

behaviours) and cultural leadership (principal defines, strengthens and articulates

values and beliefs that gives the school its cultural identity). Sergiovanni (1990)

suggested that the technical, human and educational dimensions contribute to school

effectiveness, whilst the symbolic and cultural dimensions enable schools to achieve

excellence and distinguish transformational leadership from instructional leadership.

Leithwood (1994) also found that the effects of transformational leadership in

schools were positive, especially when applied to school restructuring, or in a climate

characterised by change. Leithwood (1994) proposed that transformational leadership

increases employee motivation and commitment, which leads to the extra effort

required to induce significant change in schools. According to Leithwood (1994),

school restructuring requires changes to the both the organisation and its core

technology which can be achieved by transformational leadership but not by

instructional leadership. Leithwood (1994) also suggested that secondary schools are

particularly suited to transformational leadership methods as their size and complexity

enables them to benefit more from the empowerment of staff and dispersed influence.

Leithwood (1994) highlighted practical differences in the application of

transformational leadership in schools compared with other organisational settings.

25

Leithwood (1994) proposed that principals who are transformational leaders pursue

their goals by: helping staff to develop and maintain a collaborative school culture,

fostering teacher development and helping teachers to solve problems more

effectively. Additionally, Leithwood (1994) suggested that transformational

leadership in schools does not emphasise charisma, but places greater emphasis on

symbolic language, rituals and culture, and may even include a dimension of

traditional instructional leadership.

Leithwoood and Jantzi (2005) conducted a meta-analysis of 33 empirical

studies that examined transformational leadership in schools. The nature of

transformational leadership, its antecedents, and the variables that moderate and

mediate its effects on students were analysed. Twenty seven quantitative studies, five

qualitative studies and one mixed-methods study published between 1996 and 2005

were included in the meta-analysis which used a vote counting method to summarise

results. Transformational leadership had been operationalised using the Multifactor

Leadership Questionnaire (MLQ) (Avolio & et al., 1995) in nine of these studies.

Nine studies had examined the antecedents of transformational leadership.

These studies reported five antecedents that had a meaningful influence on

transformational leadership practices, specifically: organisational bureaucracy (in one

study), organisational values (in one study), school reform initiatives (in three

studies), leaders‟ proactivity (in one study) and formal training experiences (in two

studies). Four broad categories of variables were found to moderate the impact of

transformational leadership, namely: characteristics of leaders‟ colleagues,

characteristics of leaders, characteristics of students, and organisational structures and

processes. The effect of transformational leadership was found to be augmented by:

prior student achievement, family educational culture, organisational culture, shared

26

school goals, and coherent plans and policies. No meaningful effects were reported

regarding the age, gender and years of experience of the teacher (Leithwoood &

Jantzi, 2005).

Twenty nine studies included in the meta-analysis (Leithwoood & Jantzi,

2005) assessed mediating variables through which leaders exercise their influence.

Transformational school leadership had uniformly positive effects on the following

mediators: school culture (in eight studies), organisational commitment (in six

studies), job satisfaction (in five studies), changed teacher practices (in five studies),

planning and strategies for change (in five studies), information collection and

decision-making processes (in five studies), participatory decision-making structures

(in five studies), school policies and procedures (in five studies), pedagogical or

instructional quality (in four studies), organisational learning (in three studies) and

collective teacher efficacy (in two studies).

Fifteen studies in the meta-analysis (Leithwoood & Jantzi, 2005) had

examined the impact of transformational leadership on students. The dependent

variable in nine of these studies was academic achievement and in the other six

studies it was engagement (student participation and identification). Six out of the

nine studies reported significant relationships between transformational leadership

and some measure of academic achievement. Five out of the other six studies reported

significant positive indirect or direct effects for transformational leadership on student

engagement.

Leithwoood and Jantzi (2005) reached several important conclusions based on

the meta-analysis. Firstly, the authors asserted that the effects of transformational

leadership on perceptions of organisational effectiveness were large. Secondly, the

effects of transformational leadership on objective measures of organisational

27

effectiveness were less well known, but the existing studies reported positive effects

which were modest in size. Thirdly, the authors reported that the effect of

transformational leadership on independently measured student outcomes was

promising but only a limited number of studies existed. Lastly, Leithwood and Jantzi

(2005) reported that recent evidence about the effect of transformational leadership on

student engagement was uniformly positive but also limited by the number of studies

that existed. Leithwood and Jantzi (2005) proposed that these conclusions justified

further research into transformational leadership in schools.

Chin (2007) conducted a further meta-analysis of studies based in Taiwanese

and American schools that investigated the relationship between transformational

leadership and three outcome measures, specifically: the job satisfaction of teachers,

school effectiveness and student achievement. The meta-analysis consisted of data

from 28 studies which had used the MLQ (Avolio et al., 1995). Results from three

meta-analyses undertaken by Chin (2007) indicated that transformational leadership

has a positive impact on: the job satisfaction of teachers (k = 21, N = 10,042, r = .71),

school effectiveness as perceived by teachers (k = 13, N = 5,713, r = .70) and student

achievement (k = 11, N = 6.558, r = .49). The values of three mean effect sizes

demonstrated a high effect. Chin (2007) also reported that effect sizes were higher in

elementary schools than in secondary schools for the relationships between

transformational leadership and teacher job satisfaction, and for school effectiveness

as perceived by teachers. Whereas, effect sizes in secondary schools were higher than

in elementary schools for the relationship between transformational leadership and

student achievement. Chin (2007) noted that the studies conducted in Taiwan had

lower average effect sizes than those in the USA. Chin (2007) suggested that this may

reflect the more centralised system of schooling in Taiwan compared with the USA.

28

Hence, the Taiwanese system may provide less opportunity for demonstrating

transformational leadership at the individual school level. Chin (2007) concluded by

proposing that a high degree of transformational leadership is positively viewed by

school teachers, which in turn promotes satisfaction with the leadership of the

principal. Subsequently, school teachers perceive a heightened perception of

effectiveness which ultimately produces a higher student achievement.

The findings of empirical research clearly support the use of transformational

leadership in the field of educational leadership. As transformational leadership is

considered to be an effective form of school leadership, human resource practitioners

need to devise ways of seeking out leaders whose dominant leadership style will be

transformational. This may be achieved through effective selection and assessment

processes, or by training. As training is costly, complex and has uncertain outcomes,

identifying potential transformational leaders prior to their engagement is arguably the

most efficient method of ensuring that the dominant leadership style of more

educational leaders is transformational. In order to achieve this goal human resource

practitioners need to be able to predict leadership style.

Predicting Leadership Behaviours and Leader Effectiveness

Predicting leadership behaviour and leader effectiveness are important tasks

for human resource practitioners in all types of organisations, including in educational

institutions. Although many studies have assessed the outcomes of transformational

leadership style in the workplace (Chin, 2007; Judge & Piccolo, 2004; Lowe et al.,

1996), the antecedents of transformational leadership have received less attention

from researchers. Yet, it is important to identify the antecedents of transformational

leadership behaviours in order to be able to predict transformational leadership. The

antecedents of leadership behaviours can be divided into three domains: leader-

29

focused (e.g., personality), follower-focused (e.g., follower efficacy) and situation-

focused (e.g., organisational culture). As leader-focused antecedents are relatively

stable they are considered to have more influence on leadership behaviours than

antecedents from the other domains (Rubin, 2003).

Leader-focused leadership selection processes normally assess individual

differences by including both cognitive and non-cognitive components of assessment.

Many empirical studies have found that cognitive ability, also referred to as 'g' or

general mental ability (GMA), is a strong predictor of job performance. This is

especially true for jobs requiring complex tasks and leadership is considered to be a

complex task (e.g., developing strategies, solving problems, motivating employees).

In a meta-analysis of job performance predictors, Schmidt and Hunter (1998) reported

that GMA was the best predictor of job performance (r = .51). However, Goldstein,

Zedeck and Goldstein, (2002) argue that personnel selection processes often

overemphasise the importance of GMA and suggest that researchers need to design

and test alternative measures of intelligence whilst continuing to explore the

predictive ability of non-cognitive measures. Other cognitive components under

investigation include multiple intelligences (Gardner, 1983).

Research related to non-cognitive constructs and job performance has

highlighted the importance of predictors such as: personality factors (especially

conscientiousness) (Judge, Bono, Ilies, & Gerhardt, 2002) and integrity (Schmidt &

Hunter, 1998). Robertson and Kinder (1993) reported that personality factors had

incremental validity over GMA in predicting job competencies, whereas Kanfer and

Kantrowitz (2002) reported that a combination of personality factors and GMA

provided the highest level of prediction for job performance. Other predictors based in

the individual differences domain include tests of physical abilities (e.g., psychomotor

30

tests) and interests. However, as tests of physical abilities are not relevant for the

selection of school leaders they will not be given further consideration in this project.

Also, Schmidt and Hunter (1998) reported that although an individual may be

interested in something they are good at, interests are not good predictors of job

performance (r = .10). Therefore, the impact of interests will also not be given further

consideration in this project.

Among the other valid predictors of job performance reported by Schmidt and

Hunter (1998) were: structured interviews (r = .51), job knowledge tests (r = .48) and

biodata (r = .35). However, as these predictors are not based in the individual

differences domain they are beyond the boundaries set for this project and their

impact will not be examined. In the following section, the literature related to

established individual differences-based predictors of leadership behaviour and leader

effectiveness will be presented and examined. The impact of gender on leadership

behaviours will also be assessed.

General Mental Ability

The tasks performed by leaders are generally considered to be complex.

Therefore, many researchers have proposed that GMA should be positively related to

leader effectiveness. Locke (1991) argued that GMA “is an asset to leaders because

leaders must gather, integrate, and interpret enormous amounts of information” (p.

46). Lord et al. (1986) conducted a meta-analysis to determine the relationship

between traits and perceptions of leadership. The traits included were: intelligence,

masculinity - femininity, adjustment, dominance, extroversion - introversion, and

conservatism. Lord et al. (1986) reported that intelligence had the strongest

correlation with leadership (r = .50). Lord et al. (p. 407, 1986) asserted that

“Intelligence is a key characteristic in predicting leadership perceptions”. This meta-

31

analysis had several limitations. Notably, the results were based on a relatively small

number of correlations (k = 18) and pertained to leadership perceptions rather than

leader effectiveness. Hence, Lord et al. (1986) suggested that future research should

examine the relationship between intelligence and objective measures of leader

effectiveness.

Judge, Ilies and Colbert (2004) conducted a meta-analysis of 96 studies that

examined the relationship between GMA and leadership behaviours. Results indicated

that the correlation between GMA and leadership was .21 (.27 corrected for range

restriction). GMA correlated equally with objective and perceptual measures of

leadership. The findings of the meta-analysis indicated that the relationship between

GMA and leadership may be lower than previously thought (Judge et al., 2004).

Therefore, although GMA seems to be a useful predictor of leadership behaviours

more research is required to assess the usefulness of other constructs that may account

for additional variance.

Personality Factors

Many theories of personality have been proposed and researchers are still to

reach a consensus regarding how to define personality (Burger, 1997). Personality can

be described as a set of factors within an individual that explain behaviour, or an

individual‟s distinctive interpersonal characteristics that remain consistent across

situations and contexts (Burger, 1997). Empirical research related to personality traits

found that personality can be measured effectively using a five-factor model that

consists of five dimensions, namely: neuroticism, extroversion, openness to

experience, agreeableness and conscientiousness (Barrick & Mount, 1991; Tett,

Rothstein, & Jackson, 1991). Several meta-analyses have supported this model of

personality (Barrick & Mount, 1991; Tett et al., 1991). The domains of the five-factor

32

model proposed by Costa and McCrae (1995) are presented in Table 2.

Table 2

Factors and Domains of Costa and McCrae’s (1995) Five-Factor Model of

Personality

Factor Domains

Agreeableness (versus antagonism) Trust, Straightforwardness, Altruism, Compliance,

Modesty and Tender-mindedness

Neuroticism (versus emotional stability) Anxiety, Angry hostility, Depression, Self-

consciousness, Impulsiveness and Vulnerability

Extraversion (versus introversion) Warmth, Gregariousness, Assertiveness, Activity,

Excitement seeking and Positive emotions

Conscientiousness (versus lack of direction) Competence, Order, Dutifulness, Achievement

striving, Self-discipline and Deliberation

Openness to experience (versus closedness to

experience)

Fantasy, Aesthetics, Feelings, Actions, Ideas and

Values

Neuroticism refers to the tendency to experience negative affect (e.g., anxiety,

depression, hostility). Extraversion refers to the quantity and intensity of interpersonal

interactions. Extraverts are affectionate, friendly, optimistic, assertive, and have the

ability to form close attachments (Costa & McCrae, 1995). An appreciation of new

experiences is characteristic of the openness to experience dimension. Individuals

who display high levels of openness to experience have a vivid imagination, prefer

variety as opposed to routines, are intellectually curious, and appreciate art and

beauty. Agreeableness refers to the quality of interpersonal interactions along a

continuum from compassion to antagonism. Individuals who display high levels of

agreeableness are: kind, likeable and considerate. Lastly, conscientiousness refers to

the amount of persistence, organisation and motivation demonstrated in goal-directed

behaviours (Costa & McCrae, 1995; Piedmont & Weinstein, 1994).

33

The five-factor model is widely used to assess personality in many fields,

including the prediction of leadership behaviours (Barrick & Mount, 1991). Many

early studies which attempted to investigate the relationship between leadership

behaviour and personality employed a number of poorly defined traits (Lord et al.,

1986). However, interest in this area has grown substantially since the development of

the five-factor model and valid and reliable instruments.

Judge and Bono (2000) examined the relationship between the five-factor

model of personality and transformational leadership. Participants were enrolled in

community leadership programs and completed measures of personality, leadership

style and perceived leadership outcomes. Results based on 14 samples found that

agreeableness and extraversion were the most useful predictors of transformational

leadership. Openness to experience was also found to be positively related to

transformational leadership but was not influential when other traits were controlled.

Neuroticism and conscientiousness were not positively related to transformational

leadership. Transformational leadership style also predicted leadership effectiveness

when transactional leadership style was controlled.

Judge et al. (2002) conducted a qualitative review of leadership research based

on traits, followed by a meta-analysis of leadership research which had used the five-

factor model of personality. The reported correlations of each factor with leadership

criteria (a combination of leader emergence and effectiveness) were: extraversion (r =

.31), openness to experience (r = .24), agreeableness (r = .08) and conscientiousness

(r = .28). Surprisingly, neuroticism also correlated positively with leadership (r = .24).

Extraversion was the most consistent correlate of leader emergence and leader

effectiveness across study settings. Overall, the five-factor model had a multiple

correlation of .48 with leadership, indicating strong support for the relationship

34

between leadership and personality. Judge et al. (2002) reported that the five-factor

model of personality explained 28% of the variability among ratings of leadership

emergence and 15% of the variability among ratings of leadership effectiveness. In

the meta-analysis based on 73 samples that examined the relationship between

personality and leader effectiveness using multiple ratings in three different settings

(industrial, military/government, student), Judge et al. (2002) found that the

importance of each personality factor for predicting leader effectiveness was

contextual. In industrial settings, emotional stability (the inverse of neuroticism),

extraversion and openness to experience were linked to leader effectiveness.

However, conscientiousness was also found to be a useful predictor of leader

effectiveness in military/government settings. Therefore, Judge et al. (2002)

concluded that more research is required to assess the relationship of each factor of

the five-factor model of personality with leader effectiveness in various vocational

contexts.

In a further meta-analysis, Bono and Judge (2004) analysed the relationship

between personality and ratings of transformational and transactional leadership

behaviors. Using a five-factor model of personality as a framework the authors

examined 384 correlations from 26 studies. The self-report version of the MLQ

(Avolio et al., 1995) was the most commonly used measure of leadership in these

studies. Bono and Judge (2004) reported that personality traits were related to several

dimensions of transformational leadership, specifically: idealised influence,

inspirational motivation, intellectual stimulation and individualised consideration.

Extraversion was the strongest correlate of transformational leadership (r = .24).

Correlations between the other personality factors and transformational leadership

were modest (neuroticism, r = -.17; openness to experience, r = .15; agreeableness, r

35

= .14; conscientiousness, r = .13). Overall, the five-factor model of personality

explained 12% of the variability in ratings of idealised influence and inspirational

motivation, 5% of the variability in intellectual stimulation and 6% of the variability

in individualised consideration. Personality traits also shared small correlations with

the contingent reward and active management-by-exception active dimensions of

transactional leadership, and with passive-avoidant leadership (extraversion, r = -.09;

neuroticism, r = .05; openness to experience, r = .04; agreeableness, r = -.12;

conscientiousness, r = -.11).

Inconsistencies in the design and methods used in previous studies have made

it difficult to reach a consensus regarding which specific factors of the five-factor

model of personality are associated with leadership behaviours and leader

effectiveness. Furthermore, there is a paucity of studies which have collected multiple

ratings of leadership behaviours which limits the validity of the existing studies.

Therefore, although the findings of empirical studies have indicated that the five-

factor model is definitely a useful predictor of transformational leadership style more

research is required to assess the predictive validity of each individual factor in

different workplace contexts.

Integrity

Although integrity is considered to be a useful predictor of job performance

(Schmidt & Hunter, 1998), little is known about its impact on leadership behaviours.

Integrity tests attempt to gauge honesty or good character. However, they have also

been found to predict job performance, and assess dependability and

conscientiousness (Ones, Viswesvaran, & Schmidt, 1993; Schmidt & Hunter, 1998).

Two broad classes of integrity tests exist, namely: overt tests and covert tests. Overt

tests openly tap honesty behaviours, whilst covert tests tap into tendencies towards

36

anti-social behaviours that may be precursors of dishonesty (Sackett & Harris, 1984;

Sackett, Burris, & Callahan, 1989). Several theorists have proposed that covert

integrity tests represent a superordinate personality factor consisting of:

agreeableness, conscientiousness and emotional stability (Ones et al., 1993). Ones et

al. (1993) reported that integrity tests were very useful predictors of job performance

(r = .41) in a meta-analysis based on 23 samples of supervisory ratings (N = 7,750).

Schmidt and Hunter (1998) reported a similar result in their meta-analysis of job

performance predictors (r = .41). Furthermore, a combination of GMA and an

integrity test provided the highest correlation of any two predictors with job

performance (r = .65) (Schmidt & Hunter, 1998).

Taking into account the usefulness of integrity as a predictor of job

performance it is worth examining the impact of integrity on leadership behaviours

and leader effectiveness. The conceptualisation of integrity is ongoing in the

leadership literature hence it has several meanings. Palanski and Yammarino (2007)

propose that there are four behavioural aspects of integrity consisting of: integrity as

consistency of words and actions, integrity as consistency in adversity, integrity as

being true to oneself, and integrity as moral/ethical behavior. Overt tests of integrity

are most closely aligned to the conceptualisation of integrity as moral/ethical

behaviour.

Currently, there is a paucity of empirical research which has linked integrity to

leadership. Parry and Proctor-Thomson (2002) assessed the relationship between

perceived leader integrity, defined as the absence of unethical behavior, and

transformational leadership using a revised version of the Perceived Leader Integrity

Scale (Craig & Gustafson, 1998, cited in Parry & Proctor-Thomson, 2002) and the

37

MLQ (Avolio et al., 1995). Peers and followers measured the perceived integrity of

leaders in a sample of 1,354 managers in New Zealand. Parry and Proctor-Thomson

(2002) found a moderate to strong positive relationship between perceived integrity

and the demonstration of transformational leadership behaviours. Perceived integrity

also correlated positively with leader effectiveness and organisational effectiveness.

The lowest perceptions of integrity were linked to the laissez-faire dimension of

passive-avoidant leadership. Parry and Proctor-Thomson (2002) proposed that further

development of integrity measures was required in order to examine the relationships

between integrity and other variables more effectively. Therefore, further research

into the relationship between leadership behaviours and integrity in organisations is

warranted.

Gender

There is considerable disagreement among researchers concerning the extent

to which the leadership behaviours of men and women differ. Several researchers

have concluded that there has been a male gender bias in the construction of

leadership theories and in the interpretation of the findings of studies that have

compared the leadership behaviours of men and women. However, several studies in

organisational settings have found that female leaders may be more transformational

than males (Bass & Avolio, 1994; Bass, Avolio, & Atwater, 1996).

Eagly, Johannesen-Schmidt and van Engen (2003) undertook a meta-analysis

of gender differences using the normative data from the MLQ (Avolio et al., 1995).

Results indicated that females were perceived to be more transformational than males.

Females also scored more highly than males on the contingent rewards scale of

transactional leadership, whilst males scored more highly on the management-by-

exception active scale of transactional leadership. Males scored more highly on the

38

management-by-exception scale passive of passive/avoidant leadership. Furthermore,

several other studies which have examined gender and leadership style using feedback

from multiple raters have found that women are perceived as being significantly more

transformational than men (Bass & Avolio, 1994).

Yukl (2002) has questioned the extent to which conclusions about the

interaction of gender and leadership can be drawn as many leadership studies do not

report the gender of leaders, making it difficult to conduct meta-analyses of this

interaction. Therefore, there is still some disagreement regarding the impact of gender

on leadership behaviours and more research is required in this area.


EI is attracting research interest as an individual difference variable that

examines the way individuals perceive, understand, and manage their emotions

(Ashkanasy & Daus, 2005). EI is dominated by psychological theories as a result of

its cognitive and physiological associations (Opengart, 2005). In the field of human

resource management, interest in EI has stemmed from the possibility that it may

account for aspects of workplace performance including variance in leader

effectiveness that cannot be accounted for by other constructs (Mayer, 2001; Watkin,

2000). In this section, the notion of intelligence is briefly discussed. Then, the three

main EI concepts are described, compared and assessed, and a case for the superiority

of the 'abilities' model is presented.

Intelligence

An American Psychological Association taskforce (Neisser, Boodoo,

Bouchard, Boykin, Brody, Ceci, et al., 1996, p. 77) given the objective of defining

intelligence proposed that “Individuals differ from one another in their ability to

understand complex ideas, to adapt effectively to the environment, to learn from

39

experience, to engage in various forms of reasoning, to overcome obstacles by taking

thought. Although these individual differences can be substantial, they are never

entirely consistent: a given person‟s intellectual performance will vary on different

occasions, in different domains, as judged by different criteria. Concepts of

"intelligence" are attempts to clarify and organize this complex set of phenomena”.

The study of intelligence usually employs either a psychometric or cognitive

psychology approach. The psychometric approach emphasises measuring intelligence

and attempting to discover why levels of intelligence vary among individuals. In

contrast, the cognitive approach focuses on the information processing strategies

which underlie intelligence and attempts to discover how individuals use their

intelligence. Supporters of the cognitive psychology approach consider cognition to

be a process, whereas supporters of the psychometric approach consider cognition to

be a collection of abilities. The psychometric approach measures differences in human

cognition by performance on intelligence tests and is considered to be the most

suitable approach to assessment when a quantifiable measure of intelligence is

required (Hunt, 1995).

Initial measures of intelligence were developed during the early part of the

twentieth century using a psychometric approach. Binet developed a measure of the

mental age of children which enabled the level of test performance to be interpreted as

an intelligence quotient (IQ) (Myers, 1998). Subsequent research has linked IQ with

potential for success in leadership (Lord et al., 1986). However, IQ tests have been

consistently challenged for their failure to assess the impact of situational factors

(e.g., cultural settings) (Riggio, Murphy, & Pirozzolo, 2002). Furthermore, several

theorists have proposed that cognitive intelligence, as measured by IQ tests, does not

encompass intelligence in its entirety and that several types of intelligence actually

40

exist. Thorndike (1920, cited in Stys & Brown, 2004) argued for the existence of a

social intelligence that involved the ability to understand and manage others, and act

wisely in human relations. More recently, Gardner (1983) revived the notion of

multiple intelligences by proposing that individuals possess aptitudes in several areas

including: verbal, mathematical, musical, spatial, movement oriented, environmental,

intrapersonal (examination and knowledge of one's own feelings) and interpersonal

(ability to read the moods, intentions, and desires of others). Subsequently, other

forms of intelligence such as EI (Salovey & Mayer, 1990) have been proposed and

continue to be investigated. A number of EI models have been developed and provide

alternative theoretical frameworks for conceptualising the construct.

EI Models

The original EI concept is credited to Salovey and Mayer (1990). According

to Salovey and Mayer (1990), EI subsumes Gardner's (1983) interpersonal and

intrapersonal intelligences. There are three main models of the EI construct developed

by: Goleman (1995, 2001), Bar-On (1997), and Salovey and Mayer (1990, 1997).

Mayer, Salovey and Caruso (2000) have separated these models into two categories,

namely: 'ability' and 'mixed' models. The Mayer and Salovey (1997) model is

categorised as an 'abilities' model as it meets the criteria for a traditional intelligence

and focuses on emotions and their interactions with thought. The Goleman (1995,

2001) and Bar-On (1997) models are categorised as 'mixed' models as they describe

EI as a conception of emotion related abilities drawn from personality traits and

dispositions.

Mayer and Salovey’s Model of EI

Salovey and Mayer‟s (1990) model of EI integrates key ideas from the fields

of intelligence and emotion. Mayer and Salovey (1993) argue that there are individual

41

differences in EI which are accounted for by differences in our ability to appraise our

own emotions and those of others. Salovey and Mayer originally defined EI as “the

ability to monitor one‟s own and others‟ feelings and emotions, to discriminate among

them and to use this information to guide one‟s thinking and actions” (1990, p.189).

Salovey and Mayer‟s (1990) initial framework proposed that the mental processes

involving emotional information included: the appraisal and expression of emotion,

regulation of and adaptive use of emotions, and personality traits.

Mayer and Salovey (1997) revised the model by separating the concept of EI

from personality traits and confining it to a mental ability. The revised model

emphasises the cognitive components of EI and highlights the potential for emotional

growth. Mayer and Salovey (1997, p. 10) now believe EI involves “abilities to

perceive, appraise, and express emotion; to access and/or generate feelings when they

facilitate thought; to understand emotion and emotional knowledge; and to regulate

emotions to promote emotional and intellectual growth”. The dimensions of the

revised model and the emotional abilities they encompass are presented in Table 3.

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Table 3

Areas, Branches and Abilities of Mayer and Salovey’s (1997) Model of Emotional

Intelligence

Total EI EI area and branch

Emotional abilities

Experiential area

Perceiving emotions branch

The perception and appraisal of emotion.

Assessed by how well emotions and

emotional content can be identified

Experiential area

Using emotions branch

The emotional facilitation of thinking.

Describes emotional events that assist

intellectual processing

Total EI Strategic area

Understanding emotions branch

Assessed by how well emotions are

understood and analysed. Requires the ability

to recognise and interpret emotions

Strategic area

Managing emotions branch

Requires conscious regulation of emotions to

promote emotional and intellectual wellbeing

According to Mayer and Salovey (1997), total EI is comprised of two areas:

experiential and strategic. The experiential area concerns the ability to perceive,

respond and manipulate emotional information without necessarily understanding it.

Whereas, the strategic area involves the ability to understand and manage emotions

without necessarily perceiving feelings well or experiencing them fully. Mayer and

Salovey (1997) divide the experiential and strategic areas into two further branches

which consist of psychological processes ranging from basic to complex. Each stage

of the model includes levels of abilities that are completed in sequence before

progression to the next branch occurs (Mayer & Salovey, 1997). The first branch

involves emotional perception or the ability to be self-aware of emotions, to express

emotions and emotional needs accurately to others, and to distinguish between honest

43

and dishonest expressions of emotion. The second branch is related to facilitating

thought or the ability to distinguish among different personal emotions and to identify

the emotions which are influencing thought processes. The third branch involves

emotional understanding or the ability to understand complex emotions such as

feeling multiple emotions and the ability to recognise transitions from one emotion to

another. Lastly, the fourth branch relates to emotion management or the ability to

connect or disconnect from an emotion depending on its usefulness in a situation

(Mayer & Salovey, 1997).

Mayer and Salovey (1990) propose that although an individual‟s level of EI is

unlikely to increase, an individual‟s emotional knowledge can be increased. This is

consistent with cognition-based definitions of intelligence and knowledge. Salovey

and Mayer (1990) consider emotional knowledge to be the level of perception and

assessment that an individual has of their emotions. The 'abilities' model may be

operationalised using the Mayer–Salovey–Caruso Emotional Intelligence Test

(MSCEIT; Mayer et al., 2002).

Goleman’s Model of EI

Goleman was influenced by Salovey and Mayer‟s (1990) work on EI whilst

writing a book about emotional literacy in education (Ashkansy & Daus, 2005).

Goleman gave his book the title „Emotional Intelligence: Why It Can Matter More

Than IQ‟. Goleman‟s (1995) book became a bestseller and brought EI to the forefront

of public attention. Hence, Goleman's (1995) model has received more attention in the

field of education than the other models of EI. Goleman's (2001) 'mixed' model

emphasises how abilities and personality factors determine success in the workplace.

Goleman (1998) expanded Mayer and Salovey‟s (1997) definition of EI by

incorporating personal and social competencies and defined EI as “the capacity for

44

recognising our own feelings and those of others, for motivating ourselves, and for

managing emotions well in ourselves and our relationships” (1998, p. 317).

Following statistical analysis, Goleman (2001) reduced the number of

competencies in his original model from 25 to 20, and reduced the number of domains

from 5 to 4. According to Goleman (1995) individuals are born with a general EI

which determines their potential for learning emotional competencies. Goleman

(2001) proposes that each of the 20 emotional competencies included in the model is a

job skill that can be learned, although this claim is still awaiting empirical

confirmation. Goleman's (1995) model may be operationalised using the Emotional

Competence Inventory (ECI; Boyatzis, Goleman, & Rhee, 2000). The domains and

competencies included in Goleman's (2001) revised model of EI are presented in

Table 4.

Table 4

Domains and Competencies of Goleman’s (2001) Model of Emotional Intelligence

Emotional intelligence domains Emotional competencies

Personal competencies

Self-awareness

Emotional awareness, self-confidence and accurate self-

assessment

Self-management

Adaptability, self-control, trustworthiness,

conscientiousness, achievement drive and initiative

Social competencies

Social awareness Empathy, service orientation and organisational

awareness

Relationship management

Developing others, conflict management, influence,

communication, leadership, change catalyst, building

bonds, and teamwork and collaboration

45

Bar-On’s Model of EI

Bar-On‟s (1997) model of EI consists of “a cross-section of interrelated

emotional and social competencies, skills and facilitators that determine how

effectively we understand and express ourselves, understand others and relate with

them, and cope with daily demands” (Bar-On, 2006, p. 15). Bar-On‟s (1997) model of

EI is based within the context of personality theory. Bar-On (2006) emphasises the

co-dependence of the ability aspects of EI with personality traits and their application

to personal well-being. The model focuses on emotional and social abilities,

specifically: the ability to be aware of, understand and express oneself, the ability to

be aware of, understand and relate to others, the ability to deal with strong emotions,

and the ability to adapt to change and solve problems of a social or personal nature.

Bar-On (2006) outlines five components of EI, namely: intrapersonal, interpersonal,

adaptability, stress management and general mood. Each component also has sub-

components.

Bar-On (2006) argues that EI develops over time and can be improved through

training. Bar-On (2006) asserts that individuals with above average levels of EI are

generally more successful in meeting environmental demands and pressures, and that

a deficiency in EI can result in a lack of success and emotional problems. Bar-On

(2006) considers EI and cognitive intelligence to contribute equally to a person‟s

overall intelligence. This model of EI may be operationalised using the Emotional

Quotient Inventory (EQ-i) (Bar-On, 1997). The components and competencies

included in Bar-On‟s (2006) model of EI are presented in Table 5.

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Table 5

Components and Competencies of Bar-On’s (2006) Model of Emotional Intelligence

EI components Emotional competencies

Intrapersonal skills Personal awareness and understanding. An ability to

express feelings and ideas. To be self-reliant and

strive for self-actualisation

Interpersonal skills An awareness, understanding and appreciation of

other‟s feelings. An ability to establish and maintain

satisfying relationships

Adaptability

The ability to verify feelings with external cues,

evaluate current situations. Flexibility in altering

feelings and thoughts when situations change, and

solving problems

Stress management To be able to cope with stress and control emotions

General mood Ability to be optimistic. Feel and express positive

emotions

Comparison of EI Models and the Case for the ‘Abilities’ Model

Mayer, Caruso and Salovey (1999) have asserted that any conceptualisation of

EI must meet certain criteria. Specifically, the conceptualisation must reflect an

ability to perform in the workplace rather than reflecting preferred ways of behaving.

Also, it should encompass a set of related abilities that are distinct from already

established psychological constructs. Additionally, the conceptualisation should

develop with age and be able to be enhanced through training. These criteria need to

be addressed in order to determine which of the three EI models is the most useful.

There are theoretical and statistical similarities between the three EI models

described. All of the models attempt to understand the elements involved in the

47

recognition and regulation of personal emotions and the emotions of others. Also,

each model highlights key components of EI and there is some consensus regarding

the nature of the components (e.g., each model considers the management of emotions

to be a key component). However, the models also have several significant

differences. Many of the attributes of Goleman‟s (1995, 2001) and Bar-On‟s (1997)

models of EI extend beyond what is normally considered to be part of emotion, or

intelligence theory, by drawing heavily on personality traits and dispositions. For

example, Goleman's (2001) model includes: trustworthiness, conscientiousness,

adaptability and empathy. Similarly, Bar-On‟s (1997) model includes components of:

assertiveness, empathy, and impulse control. However, McCrae (2000) has mapped

these variables onto the five-factor model of personality and argues that these two

models of EI simply describe a broad range of personality traits relabeled as EI

competencies. Therefore, as Mayer and Salovey (1997) assert that a conceptualisation

of EI is only useful if it is separated from personality domains and confined to a

mental ability, the 'mixed' models fail to meet this requirement. Also, in empirical

studies 'mixed' models have consistently failed to demonstrate adequate discriminant

validity from personality factors (Van Rooy & Viswesvaran, 2004). Furthermore,

taking into account the breadth of the competencies included in Goleman‟s (2001)

model it is unlikely that individuals can score highly on all dimensions of the model,

or that all dimensions contribute to workplace performance. Locke (2005) argues that

the EI concept as proposed by Goleman, Boyatzis and McKee (2002) is so broad that

any relationship found between EI and leader effectiveness would be meaningless.

Therefore, there is a strong argument to suggest that the Goleman (1995) and

Bar-On (1997) 'mixed models' do not match the criteria for a sound conceptualisation

of the EI construct. Furthermore, empirical studies have found that convergent

48

validity between the 'mixed' models and the 'abilities' model is low enough to suggest

that they may be measuring different constructs altogether (Matthews, Zeidner, &

Roberts, 2002).

The popularity of EI has highlighted its potential contribution to workplace

performance. However, some claims about the significance of EI made by Goleman

(1995) in his popular book have not been confirmed by empirical research (Mayer,

Salovey, & Caruso, 2004). However, momentum is now growing for the Mayer and

Salovey (1997) model to be considered the most useful model of the construct

(Ashkanasy & Daus, 2005; Daus & Ashkanasy, 2005) and the 'abilities' model is

considered to be worthy of further empirical investigation (Van Rooy & Viswesvaran,

2004). Therefore, further research is required in order to establish the extent of the

predictive validity of the 'abilities' model of EI.

Relationship between EI and Performance Outcomes

Several studies have examined the relationship between EI and performance

outcomes. Van Rooy and Viswesvaran (2004) examined the relationship between EI

and work or academic performance outcomes in a meta-analysis of 57 studies (N =

12,666) that reported correlations between performance and EI or other variables

(e.g., GMA). The authors also analysed various moderating influences such as: the

measure used to operationalise each EI model, dimensions of EI, scoring methods and

criterion, and subgroup analyses. Notably, no studies were available which had used

the MSCEIT (Mayer et al., 2002) to operationalise EI at this time. Results indicated

that across criteria EI had a predictive validity of .23 (k = 59, N = 9,522). EI

correlated .22 with GMA (k = 19, N = 4,158) and .23 (agreeableness and openness to

experience; k = 14, N = 3,306) to .34 (extraversion; k = 19, N = 3,718) with the five

factors of personality. Overall, EI demonstrated incremental validity over personality

49

as a predictor of performance outcomes. Therefore, it is possible that EI may explain

variance in performance that is not accounted for by personality. EI did not

demonstrate incremental validity over GMA. This indicates that GMA explain

variance in performance that EI cannot, although further research is required. The

findings of this meta-analysis indicate that EI should be considered a valuable

potential predictor of work or academic performance.

In a study of analysts and clerical employees (N = 44) from the finance

department of an insurance company in the USA, Lopes, Grewal, Kadis, Gall and

Salovey (2006) examined the relationship between EI and positive workplace

outcomes. EI was operationalised using the MSCEIT (Mayer et al., 2002) and positive

workplace outcomes were company indicators of work performance (salary, percent

merit increase and company rank). Participants‟ affect and attitudes at work were

assessed by levels of job satisfaction, mood and stress tolerance. In order to measure

the interpersonal sensitivity of each participant, peers and supervisors completed the

empathy and social responsibility scales from the EQ-i (Bar-On, 1997). Peers and

supervisors also completed ratings of participants‟ interpersonal facilitation skills. The

study found that individuals with higher levels of EI received greater merit increases

and held higher company rank than their counterparts. They also received better peer

and supervisor ratings of interpersonal facilitation and stress tolerance than their

counterparts. Therefore, there is a growing link between EI and positive performance

outcomes demonstrated by the findings of empirical studies.

Relationship between EI and Leadership

Several researchers have proposed that there is a relationship between EI and

leadership (Prati, Douglas, Ferris, Ammeter, & Buckley, 2003). George (2000)

proposed that moods and emotions play an important role in the leadership process

50

and that EI contributes to leader effectiveness. George (2000) proposed that

leadership is a process laden with emotions from the perspective of both the leader

and follower. George (2000) highlighted major aspects of EI such as: appraisal and

expression of emotion, use of emotion to enhance cognitive processes and decision

making, knowledge about emotions, and management of emotions. George (2000)

suggested how EI contributes to effective leadership by focusing on important

elements of leader effectiveness such as: the development of collective goals,

instilling in others an appreciation of the importance of work activities, generating

enthusiasm and trust, encouraging flexibility in decision making, and establishing and

maintaining a meaningful identity for an organisation. George (2000) suggested that

further empirical research is required to investigate exactly how EI contributes to

leadership effectiveness.

Relationship between the Mayer and Salovey (1997) Model of EI, Leadership Style

and Leadership Outcomes in Non-educational Settings

Several studies have explored aspects of the relationship between the Mayer

and Salovey (1997) model of EI, leadership style and leadership outcomes in non-

educational settings. Taking into account the limited amount of research that has been

conducted in an educational context, it is useful to assess the methodology and

findings of these studies even though they were not undertaken in educational

institutions.

In a study based on 24 projects in 6 organisations in the USA, Leban (2003)

examined the relationship between leadership behaviours, EI and the success of work

projects. Leban (2003) used the MLQ5X (Avolio et al., 1995) to operationalise

leadership style and perceived leadership outcomes, and the MSCEIT (Mayer, et al.,

2002) to operationalise EI. Participants were executives, project managers, team

51

members and other stakeholders who responded to questions related to the relevant

project. Results indicated that total EI, transformational leadership and laissez-faire

leadership were related to project performance. Total EI and the understanding

emotions branch of EI were also found to be related to the inspirational motivation

scale of transformational leadership. Additionally, Leban (2003) found that the

strategic area of EI was related to the idealised attributes and individual consideration

scales of transformational leadership. Transformational leadership was found to

enhance project performance to a greater degree than transactional leadership. The

results of Leban‟s (2003) study highlight the differences in the relationship between

the individual branches of EI and each leadership style, suggesting that further

research which examines the individual branches of the construct is warranted.

Notably, Leban (2003) did not include other variables (e.g., GMA and personality

factors) in the project which are known to predict performance outcomes.

Consequently, it is not possible to compare the findings related to the impact of EI on

leadership style and outcomes with other predictors in this project.

The importance of controlling for established predictors was highlighted by

the findings of a study by Schulte (2003) which examined the relationship between

EI, personality factors, GMA and leadership styles. Participants were 103 college

students. Schulte (2003) employed valid and reliable measures to operationalise each

construct, namely: Avolio et al.'s (1995) MLQ5X for transformational leadership, the

MSCEIT (Mayer et al., 2002) for EI, and Costa and McCrae's NEO-FFI (1992) for the

five-factor model of personality. The instrument used to collect data for GMA was the

Wonderlic Personnel Test (Wonderlic, 2000). Schulte (2003) analysed the

relationships between the variables using correlation and multiple regression

procedures. The author found small significant correlations between EI and

52

transformational leadership (r = .28) and EI and perceived leadership outcomes (r =

.23). A moderate significant correlation was found between EI and passive-avoidant

leadership (r = .31). EI also shared small significant correlations with four of the five

personality factors (agreeableness r = .26; openness to experience r = .26;

conscientiousness, r = .21; and neuroticism r = -.27) and had a moderate significant

correlation with GMA (r = .45). In regression model 1, GMA predicted 2% of the

variance in transformational leadership. In regression model 2, GMA and personality

factors predicted 46 % of the variance in transformational leadership. In regression

model 3, the addition of EI to personality and GMA did not increase the amount of

variance predicted in transformational leadership which remained at 46%. Hence,

Schulte concluded that EI may not be able to account for variance in transformational

leadership that cannot be accounted for by personality factors and GMA. Although

this study has some methodological weaknesses (participants were not practicing

leaders and rated themselves on leadership style as no ratings were obtained from

peers, followers or supervisors), it raises questions about the ability of EI to predict

transformational leadership style, above and beyond established predictors.

Coetzee and Schaap (2005) examined the relationship between leadership

behaviours, leadership outcomes and EI among managers in South Africa (N =100).

EI was operationalised using the Multifactor Emotional Intelligence Scale (MEIS,

Mayer, Salovey, & Caruso, 1999), which is a forerunner of the MSCEIT (Mayer, et

al., 2002). Leadership behaviours and outcomes were operationalised using the MLQ

(Avolio et al.. 1995). The results of correlation analysis revealed significant positive

correlations between transformational leadership and total EI (r = .27), and between

transformational leadership and the identifying emotions (r = .28) and managing

emotions (r = .30) branches of EI. A small significant positive correlation was found

53

between transactional leadership and managing emotions (r = .21), and a small

significant negative correlation was found between laissez-faire leadership and using

emotions (r = -.20). Management-by-exception passive shared small significant

negative correlations with identifying emotions (r = -.22) and using emotions (r = -

.30), and a moderate significant negative correlation with understanding emotions (r =

-.32). Lastly, laissez-faire leadership had a small significant negative correlation with

using emotions (r = -.20). Following multiple regression analysis, the authors found

that there was a significant correlation between EI scores and the „effective

leadership‟ and „ineffective leadership‟ scores of the sample group. A positive

significant relationship existed between EI and „effective leadership‟ (t = 2.36) and a

negative significant relationship existed between EI and „ineffective leadership‟ (t = -

2.65). However, as the authors only used self-ratings of leadership rather than

multiple ratings in this project the relationships between the variables may have been

inflated as a result of common method variance. Furthermore, other known predictors

of leadership behaviours were not controlled in this study.

A study by Srivsastava and Bharamanaikar (2004) examined the relationship

between EI, leadership effectiveness, success, and job satisfaction. Using structured

interviews, Srivsastava and Bharamanaikar (2004) collected data from Indian army

officers (N = 291). EI was measured using the Work Profile Questionnaire EI version

(Camaron, 1999, cited in Srivsastava & Bharamanaikar, 2004), and leadership

effectiveness and style were assessed using the MLQ5X (Avolio et al., 1995). The

authors found that EI was significantly related to transformational leadership. EI was

also found to be related to success, but not to job satisfaction. Additionally, EI

differed across age but not across rank or length of service. The authors recommended

that top management and policy makers should use EI to identify and develop

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effective leaders. The findings of this study provide some indication that the

relationship between EI and leader effectiveness transcends cultural boundaries.

However, whilst the measure used to assess leadership effectiveness is the valid and

reliable MLQ5X (Avolio et al., 1995), the measure used to assess EI has

comparatively unproven psychometric properties. Furthermore, the authors did not

control for other predictors of leadership behaviours in this study.

In a study which controlled for established predictors, Rosete and Ciarrochi

(2005) investigated the relationship between EI, personality, GMA and leader

effectiveness. Participants were Australian senior executives (N = 41) who completed

the MSCEIT (Mayer et al., 2002). Leader effectiveness was assessed using an

objective measure of performance and a multi-rater assessment involving the

followers and supervisor of each leader (N = 149). Correlation and regression

analyses revealed that higher EI was associated with higher leader effectiveness, and

that EI explained variance which was not explained by either personality or GMA.

This study establishes a link between EI and leader effectiveness when GMA and

personality are controlled. However, as the performance outcomes used to assess

leadership effectiveness were specific to this study it is not possible to directly

compare the findings with other studies.

Similarly, Kerr et al. (2006) examined the relationship between EI and leader

effectiveness in a study of supervisors (N = 38) in a large manufacturing organisation

in Ireland. EI was operationalised using the MSCEIT (Mayer et al., 2002) and

supervisory leadership effectiveness was assessed using ratings of followers (N =

1,258) on an attitudinal survey of supervisor performance. Results indicated that

15.2% of the variance in supervisor ratings was predicted by the total EI score. The

perceiving emotions and using emotions branches of EI had the greatest overall

55

impact on supervisor ratings. However, there was no significant correlation between

the managing emotions branch of EI and supervisor ratings (though non-significant,

the correlation was negative). The understanding emotions branch scores had a non-

significant positive correlation with supervisor ratings. One possible explanation for

this is offered by Matthews et al. (2002) who propose that expert knowledge of

appropriate emotional behaviour does not necessarily translate into the application of

emotionally appropriate behaviour. These findings support the usefulness of EI as a

predictor of leader effectiveness. However, the findings also raise questions about the

conceptual validity of the managing emotions branch of the Mayer and Salovey

(1997) model of EI. Notably, other predictors of leader effectiveness were not

controlled in this study.

A meta-analysis of 48 studies with a total of 7,343 participants was conducted

by Mills (2009) to ascertain if there was enough empirical evidence to support the

inclusion of EI as a component of leader effectiveness. Studies which represented all

of the main conceptualisations of EI, including the Mayer and Salovey (1997) model,

were included. Unpublished dissertations and theses made up 56% of the studies in

the meta-analysis. The meta-analysis yielded a combined effect of .38 which can be

interpreted as a moderate relationship between EI and leader effectiveness.

Consequently, Mills (2009) advocated the inclusion of EI in the curriculum of

educational leadership preparation programs.

Harms and Crede (2010) conducted a meta-analysis to assess claims that EI is

significantly related to the full-range of leadership behaviours (Avolio, 1999; Bass,

1999). Sixty two independent studies consisting of data from 7,145 leaders were

included in the meta-analysis. Several different measures had been used in the studies

but the MSCEIT (Mayer et al., 2002) was the most frequently used measure of EI (k =

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12) and the MLQ (Avolio et al., 1995) was the most frequently used measure of

leadership behaviours (k = 39).

Harms and Crede (2010) reported that the relationship between EI and

transformational leadership was strong (k = 62, N = 7,145, ρ = .41). However, the

analysis indicated that the validity estimate was much higher (k = 47, N = 4,994, ρ =

.59) when ratings of EI and leadership behaviors were provided by the same source

(e.g., both self-report) compared with when ratings of the constructs were derived

from different sources (e.g., self, peer, supervisor, follower) (k = 22, N = 2,661, ρ =

.12). Agreement between same-source and multi-source ratings was low for both

transformational leadership (ρ = .14) and EI (ρ = .16).

Harms and Crede (2010) also performed separate analyses to assess the

relationship between transformational leadership and the different EI measures. Trait

measures of EI demonstrated higher validities than ability-based measures of EI.

Notably, the relationship between EI and transformational leadership was

significantly weaker for the MSCEIT (Mayer et al., 2002) than for the other measures.

Harms and Crede (2010) conducted further meta-analyses for studies which

had used same-source ratings and multi-source ratings. Both ability-based and trait-

based measures of EI demonstrated lower validity estimates when multi-source

ratings were used. Trait-based measures of EI demonstrated a strong relationship

between EI and transformational leadership when same-source ratings were used (k =

38, N = 4,424, ρ = .66), and a weak relationship when multi-source ratings were used

(k = 20, N = 2,491, ρ = .11). Ability-based measures of EI demonstrated lower

validity estimates than trait-based measures when same-source ratings were used (k =

10, N = 1,066, ρ = .24) and had no relationship with transformational leadership when

multi-source ratings were used (k = 4, N = 441, ρ = .05).

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The authors also conducted meta-analyses of the studies which assessed the

relationship between EI and the MLQ (Avolio et al., 1995). The relationship was

moderate in strength for same-source ratings (k = 33, N = 3,999, ρ = .54), and weak

for multi-source ratings (k = 14, N = 1,549, ρ = .09).

Regarding transactional leadership, Harms and Crede (2010) reported that EI

had a positive relationship with the contingent reward dimension for same-source

ratings (k = 12, N = 1,272, ρ = .35) and a weak relationship for multi-source ratings (k

= 6, N = 622, ρ = .13). There was no significant relationship between EI and

management-by-exception active. Both dimensions of passive/avoidant leadership

were negatively related to EI. Notably, EI demonstrated a moderate negative

relationship with the management-by-exception passive dimension for same-source

ratings (k = 10, N = 871, ρ = –.22) and a weak relationship for multi-source ratings (k

= 3, N = 333, ρ = –.12). EI also demonstrated a moderately strong negative

relationship with the laissez-faire dimension of passive/avoidant leadership for same-

source ratings (k = 14, N = 1,304, ρ = –.36) and a weak relationship for multi-source

ratings (k = 8, N = 617, ρ = –.17). Above all, this meta-analysis demonstrates the

importance of using multi-source ratings of leadership behaviours, rather than same-

source ratings, in order to avoid an overestimation of positive leadership behaviours

caused by common method variance and self-serving bias.

Although the findings of some empirical studies in non-educational settings

have suggested that the Mayer and Salovey (1997) model of EI is a useful predictor of

leadership style and leadership outcomes, methodological limitations in the design of

these studies have decreased the validity of the findings and the potential to apply

them. Therefore, further empirical research is required which addresses these

limitations by including sound predictors of leadership style and leader effectiveness,

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and comparing their predictive validity with the predictive ability of EI. Multiple

ratings of leadership behaviours also need to be collected. Consequently, a greater

understanding of the relationship between EI, leadership style and leadership

outcomes, and other predictors will be obtained.

Relationship between EI, Leadership Style and Leadership Outcomes and the Impact

of Gender in Non-Educational Settings

Such is the paucity of studies which have employed the 'abilities' model of EI

to investigate gender that it is worth presenting the findings of a study which used a

'mixed' model of EI and reported gender differences. In a study of 13 male and 19

female managers (N = 32), Mandell (2003) examined the relationship between EI and

transformational leadership style, and the impact of gender differences.

Transformational leadership was operationalised using the MLQ5X (Avolio et al.,

1995) and EI was operationalised using the EQ-i (Bar-On, 1997). Mandell (2003)

used regression analysis to examine the relationship between the variables, and

conducted independent t-tests to determine gender differences in the EI scores and

leadership styles of the participants. A significant predictive relationship was found

between transformational leadership style and EI. Mandell (2003) found no

significant interaction between gender and EI while predicting transformational

leadership style. No significant difference was found for scores of transformational

leadership between male and female managers. However, the author did find the mean

total of EI scores of females was significantly higher than for males. Therefore,

Mandell (2003) suggested that females may be better at managing their own emotions

and the emotions of others in comparison to males.

Mayer and Geher (1996) and Mayer, Caruso, & Salovey (1999) found similar

results, with females scoring higher on measures of EI. No gender differences were

59

found for the transformational leadership scores of male and female managers, which

indicated that males were as transformational in their leadership style as females.

However, as the findings of many previous studies related to gender and leadership

have been inconclusive further research is required.

Relationship between EI, Leadership Style and Leadership Outcomes in Educational

Settings

Few studies have explored aspects of the relationship between EI, leadership

style and leadership outcomes in educational settings. Some of the existing studies

have employed a „mixed‟ model of EI rather than the „ability‟ based Mayer and

Salovey (1997) model. Goleman's (1995) claims regarding the usefulness of EI in

educational settings have ensured that the 'mixed' models have received more research

attention than the 'abilities' model in this context. Although the 'mixed' models are

now considered by some to be conceptually weaker than the 'abilities' model

(Ashkanasy & Daus, 2005; Daus & Ashkanasy, 2005), such is the paucity of studies

which have employed the 'abilities' model in an educational context that some of the

findings from empirical research undertaken using 'mixed' models will be presented in

this section.

Sivanathan and Fekken (2002) undertook an examination of the relationship

between transformational leadership, EI, moral reasoning and leader effectiveness in a

university in Ontario, Canada. Fifty eight dons completed the EQ-i (Bar-On, 1997)

and the Defining Issues Test (Rest, 1990, cited in Sivanathan & Fekken, 2002). Raters

were 12 supervisors and 232 residents who completed the MLQ5X (Avolio et al.,

1995). Leaders reporting greater EI were perceived by the residents to display more

transformational leadership behaviours. They were also perceived to be more

effective leaders.

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In another Canadian study, Stone, Parker and Wood (2005) reported on the

Ontario Principals‟ Council leadership study which explored the relationship between

EI and school leadership. The authors sought to identify key emotional and social

competencies required by successful school administrators. Principals and vice-

principals (N = 464) from nine school boards completed an online version of the EQ-i

(Bar-On, 1997). Leadership skills were rated by the immediate supervisor, peers and

followers of each participant using a 21-item leadership abilities questionnaire.

Consistent with previous research using the EQ-i (Bar-On, 1997), women were found

to score higher than men on the interpersonal dimension. However, no differences in

EQ-i (Bar-On, 1997) scores were found between principals and vice-principals. The

authors found that men and women did not differ on any of the leadership ratings.

However, principals were rated higher than vice-principals by their supervisors on

task oriented leadership, relationship oriented leadership and total leadership. Vice-

principals were rated higher by their staff on relationship oriented leadership. The

authors highlighted key emotional and social competencies that differentiate between

administrators identified by both supervisors and staff as either above average or

below average in leadership abilities. The authors suggested that educational boards

should consider the use of EI measures in the recruitment process for new school

administrators and in succession planning. However, the psychometric properties of

the leadership measure used in this study are comparatively unproven and a „mixed‟

model of EI was operationalised. Additionally, the effects of other predictors of

leadership behaviours and leader effectiveness were not controlled in this study.

Bardoch (2008) explored the relationship between the EI of principals (N =

50) and the performance of middle-schools in Maryland, USA, for the 2006-2007

school year. EI was measured using the MSCEIT (Mayer et al., 2002) and the

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performance of each school was measured by whether or not it met Adequate Yearly

Progress goals as defined by the aggregate student scores of annual measurable

objectives in reading, mathematics and attendance. Using logistic regression, the

Adequate Yearly Progress status of each school was compared to its principal‟s scores

from the MSCEIT (Mayer et al., 2002). Two demographic variables were controlled

(minority levels, and levels of free and reduced meal service). Bardoch (2008) found

that for every one point increase in a principal's total EI score the school was .06%

more likely to successfully meet its Adequate Yearly Progress goals. Similar

significant relationships were found between principals‟ experiential area EI score and

the Adequate Yearly Progress status of a school, and between principals‟ perceiving

emotions EI branch scores and Adequate Yearly Progress status. Bardoch (2008)

acknowledged that other variables such as the value of parental involvement in school

settings and the EI levels of teaching staff could be controlled in future studies.

Bardoch (2008) concluded by proposing that school systems should seek out and

utilise principals with higher levels of EI for leadership positions in public middle

schools in an effort to promote better school performance. Notably, Bardoch (2008)

only assessed student scores and did not assess the wellbeing of staff or other

stakeholders in this study.

More research which employs the more conceptually sound „ability‟ based

Mayer and Salovey (1997) model of EI is required in order to continue to examine the

relationship between EI, leadership style and leadership outcomes in educational

settings.

Critique of Previous Research

The choice of instruments used to operationalise EI has been far from ideal in

many studies. Some researchers (e.g., Mandell, 2003; Sivanathan & Fekken, 2002;

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Stone et al., 2003) have used instruments measuring „mixed‟ models of EI rather than

the conceptually superior „abilities‟ model. Srivsastava and Bharamanaikar (2004)

used a relatively unknown EI instrument, and Coetzee and Schaap (2005) used the

outdated and outmoded MEIS (Mayer et al., 1999).

Furthermore, many studies (e.g., Coetzee & Schaap, 2005; Kerr et al., 2006;

Leban, 2003; Stone et al., 2003) have not controlled for established predictors of

leadership behaviours and leader effectiveness such as GMA and personality factors.

Hence, these studies may have overestimated the amount of variance in leadership

behaviours and leader effectiveness thought to be accounted for by EI.

Several studies have used different approximations of leader effectiveness

(e.g., Kerr et al., 2006; Rosete & Ciarrochi, 2005). However, the construct validity of

these approximations is questionable as it is not possible to tell whether or not they

are really measuring leader effectiveness.

Schulte (2003) used valid and reliable instruments including the MLQ (Avolio

et al., 1995). However, Schulte (2003) used students instead of real leaders as

participants in the study, yet the MLQ (Avolio et al., 1995) was designed to test real,

practicing leaders. Furthermore, the MLQ (Avolio et al., 1995) is designed to measure

leadership style and perceived leadership outcomes by combining the scores from

multiple ratings. However, Schulte (2003) only used self-ratings of leadership.

Although the leader may be one of several raters, self-ratings of leadership alone are

not recommended by the publisher of the MLQ (Avolio et al., 1995), Mind Garden

Inc., as a valid means of measuring leadership style and leadership outcomes.

Furthermore, the meta-analysis by Harms and Crede (2010) reported large

discrepancies in the results between the few studies which had used multiple rating

sources of leadership behaviours to predict transformational leadership compared with

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studies which had used self-ratings. Notably, there is a shortage of research in the

field which has obtained multiple ratings of leadership behaviours, particularly in

studies which have used the MSCEIT (Mayer et al., 2002) to operationalise EI.

Taking into account the conceptual difference in the main models of EI, the

meta-analysis of EI and leader effectiveness by Mills (2009) was an extremely broad

undertaking. Matthews et al., (2002) reported that the convergent validity between the

'mixed' models and the 'abilities' model is low enough to suggest that they may be

measuring different constructs altogether.

Overall, shortcomings in the methodology of previous research in the area of

leadership and EI have reduced the validity of the findings of these studies.

Consequently, many questions about the ability of the Mayer and Salovey (1997)

model of EI to predict leadership behaviours and leader effectiveness remain

unanswered. Therefore, further empirical studies using a more rigorous methodology

are required.

Direction for Future Research

In order to build on the findings of previous studies which have examined the

relationship between EI, leadership styles and leadership outcomes, future studies

should continue to take a psychological testing approach. Antonakis et al. (2009)

argue that the instruments used in future projects must have demonstrated construct

validity by measuring what they are supposed to be measuring. Also, the constructs

included in the project must be able to predict a useful outcome. Additionally, the

instruments must demonstrate convergent validity by correlating strongly with other

instruments which measure a similar construct.

As a result of the conceptual weaknesses of the 'mixed' models of EI, future

research of the construct should be based on the Mayer and Salovey (1997) 'abilities'

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model (Ashkanasy & Daus, 2005). Landy (2005), Antonakis (2005) and Antonakis et

al. (2009) assert that future studies in this domain must control for established

performance predictors in order to assess whether EI has discriminant validity from,

and incremental validity above, these constructs. Landy (2005) suggests that in

addition to GMA and personality factors, other predictors of leadership behaviours

should be considered. As it would be impracticable for a single study to examine the

effect of every possible predictor of leadership behaviours, future studies could focus

on predictors from a single domain (e.g., individual differences). Taking into account

the importance of integrity as a predictor of job performance (Schmidt & Hunter,

1998) and the link between integrity and transformational leadership found by Parry

and Proctor-Thomson (2002), integrity would be a worthwhile inclusion as a potential

predictor of leadership behaviours. Multiple ratings of leadership behaviours should

be obtained from each leader‟s peers, followers and supervisors to avoid self-serving

bias (Antonakis et al., 2009). Additionally, a large enough sample of practicing

leaders, rather than students, should be obtained. The relationship between gender and

leadership style remains inconclusive, hence future studies should investigate the

effect of gender. Future research in educational institutions would be useful as the

ability to predict transformational leadership is important for both researchers and

human resource practitioners in educational settings.

Therefore, further research is required to answer the question: to what extent is


leadership outcomes? This overarching question can be divided into several related

questions such as: Is the Mayer and Salovey (1997) model of EI related to leadership

style and leadership outcomes? Does the Mayer and Salovey (1997) model of EI have

divergent validity from GMA and personality factors? Is the Mayer and Salovey

65

(1997) model of EI able to predict leadership style and leadership outcomes when

multiple ratings of leadership behaviours are obtained? Does the Mayer and Salovey

(1997) model of EI have incremental validity above other predictors of leadership

style and leadership outcomes? Table 6 presents the specific research questions and

hypotheses that have been formulated to answer these questions. The impact of

gender and role on leadership style will also be examined. Taking into account the

findings of previous studies it is predicted that support will be found for the

hypotheses presented in Table 6 in future studies. As there is insufficient literature in

some areas of interest to develop specific hypotheses, research questions have also

been formulated for examination.

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Table 6

Summary of Research Questions and Hypotheses

Study Research questions and hypotheses

Pilot study

Hypothesis 1. EI will have discriminant validity from GMA.

Hypothesis 2. EI will have discriminant validity from personality factors.

Hypothesis 3. Total EI scores will be significantly higher for females than for males.

Hypothesis 4. Transformational leadership scores will be significantly higher for females than for males.

Research question 1. Investigate whether there is a positive relationship between EI and transformational leadership.

Research question 2. Investigate whether there is a positive relationship between EI and perceived leadership outcomes.

Research question 3. Investigate whether there is a relationship between EI and transactional leadership (contingent reward and management-by-exception active).

Research question 4. Investigate whether there is a negative relationship between EI and passive/avoidant leadership.

Research question 5. Investigate whether integrity has discriminant validity from personality factors.

Main study – descriptive and

measurement component

Hypothesis 1. Total EI will have discriminant validity from personality factors.

Hypothesis 2. Total EI will have discriminant validity from GMA.

Hypothesis 3. Total EI scores will be significantly higher for females than for males.


Hypothesis 5. Scores for the contingent reward scale of transactional leadership will be significantly higher for females than for males.

Hypothesis 6. Scores for the management-by-exception active scale of transactional leadership will be significantly higher for males than for females.

Hypothesis 7. Passive/avoidant leadership scores will be significantly higher for males than for females.

Research question 1. Investigate whether scores of transformational leadership vary according to the role of the leader.

Research question 2. Investigate whether scores of total EI vary according to the role of the leader.


Main study – inferential component Research question 4. Investigate whether EI predicts transformational leadership.

Research question 5. Investigate whether EI has incremental validity above GMA in predicting transformational leadership.

Research question 6. Investigate whether EI has incremental validity above personality factors in predicting transformational leadership.

Research question 7. Investigate whether EI has incremental validity above integrity in predicting transformational leadership.

Research question 8. Investigate whether EI predicts satisfaction (of followers).

Research question 9. Investigate whether EI predicts effectiveness (of leader/group).

Research question 10. Investigate whether EI predicts extra effort (by followers).

Research question 11. Investigate whether EI predicts the contingent reward scale of transactional leadership.

Research question 12. Investigate whether EI predicts the management-by-exception active scale of transactional leadership.

Research question 13. Investigate whether EI predicts passive/avoidant leadership.

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Conclusion

This chapter has reviewed the literature related to: leadership, predictors of

leadership behaviours and leader effectiveness, EI models, and EI and leadership

research in various settings. The importance of leadership in organisations, including

educational institutions, has been highlighted and the benefits of transformational

leadership have been noted. As transformational leaders are highly sought after

researchers continue to explore constructs which may predict leadership style, and

which may ultimately contribute to improved methods of leadership assessment and

selection. Of the leader-focused antecedents of leadership behaviours, GMA has been

highlighted as a predictor (Judge et al., 2004) but more research is required to

determine which other predictors, such as specific personality factors, are useful

predictors of leadership style and leader effectiveness.

It was noted that several researchers have proposed that there is a relationship

between EI and leadership (George, 2000; Prati et al., 2003), and between EI,

transformational leadership and leadership outcomes (Ashkanasy & Daus, 2005; Daus

& Ashkanasy, 2005). Following an assessment of the three main conceptualisations of

EI, it was argued that the 'mixed' models by Goleman (1995, 2001) and Bar-On

(1997) have considerable conceptual weaknesses, mainly because they draw too

heavily on personality traits and dispositions. Therefore, the ability to apply the

findings of studies which have employed 'mixed‟ models is very limited. However, as

the Mayer and Salovey (1997) „abilities‟ model is considered to be worthy of further

investigation (Van Rooy & Viswesvaran, 2004) it is suggested that future research

should be based on this model. An assessment of the empirical studies which have

employed a psychological testing approach to examine the relationship between EI,

leadership style and leadership outcomes revealed that although several studies have

68

found that EI is a useful predictor (Coetzee & Schaap, 2005; Kerr et al., 2006; Leban,

2003; Srivsastava & Bharamanaikar, 2004), the methodology of some of these studies

is lacking in rigor. Hence, the validity of these findings is limited.

It is proposed that future studies which examine the relationship between EI,

leadership style and leadership outcomes should control for established predictors of

leadership behaviours from the individual differences domain in order to assess

whether EI has discriminant validity from, and incremental validity above, these

constructs. Only instruments with established psychometric properties should be used.

Furthermore, the importance of obtaining an adequately sized sample of real leaders

and multiple ratings of leadership behaviours has been noted.

Taking into account the findings of empirical research, EI has been

prematurely applied as a personnel selection tool by some human resource

practitioners in the workplace (Antonakis et al., 2009) and more research is required

in order to determine if EI should be used in this capacity. Therefore, further research

is required that builds on the findings of previous empirical studies by taking a

psychological testing approach to answer the question: to what extent is the Mayer

and Salovey (1997) model of EI a useful predictor of leadership style and leadership

outcomes? Research questions and hypotheses to be tested in this project have been

presented.

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Chapter 3: Project Design

Introduction

The preceding chapter highlighted the importance of transformational

leadership in organisations (Judge & Piccolo, 2004; Lowe et al., 1996), including

schools (Chin; 2007; Leithwood & Jantzi, 2005), and the need to continue to explore

constructs such as EI that may predict leadership style and leader effectiveness. It was

proposed that further research is required to answer the question: to what extent is the

Mayer and Salovey (1997) model of EI a useful predictor of leadership style and

leadership outcomes? Research questions and hypotheses to be tested in this project

were presented.

In this chapter, the decision to use a quantitative research process is discussed

in accordance with the purpose, process, logic and required outcomes of the research.

The psychological testing method selected is described with reference to test

categories, psychometrics, and the strengths and limitations of this method. Then, the

importance of collecting multiple ratings of leadership behaviours is highlighted.

Subsequently, the role of school leaders in Australia is described and the criteria

currently used to select school leaders are presented. Then, the project aims are

presented. The project aims to replicate and expand on previous research by

examining the relationship between EI, leadership style and perceived leadership

outcomes, and by assessing whether EI has discriminant validity from established

predictors of job performance, and incremental validity above these constructs. The

project also aims to use a more rigorous methodology than in many previous studies

in the field. Finally, ethical considerations for the project are noted.

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Selection of a Research Paradigm

Research is often classified into different paradigms using a framework that

denotes its: purpose, process, logic and outcomes (Hussey & Hussey, 1997). The

purpose of research may be: exploratory, descriptive, analytical or predictive.

Exploratory research is undertaken when information about a problem or issue is

limited and insight is sought prior to undertaking more rigorous investigations at a

later stage. In comparison, descriptive research is used to identify and obtain

information about the characteristics of a particular problem or issue. In descriptive

research, quantitative data is usually collected and summarised using statistical

techniques. Analytical research moves beyond descriptive research by discovering

causal relationships through the analysis of why, or how, the problem occurred. In

analytical research, variables are identified and controlled. Lastly, predictive research

predicts phenomena on the basis of hypothesised relationships. This enables the

solution to a particular problem to be applied to a problem elsewhere. Hence,

predictive research aims to provide solutions to both current and future events

(Hussey & Hussey, 1997). Whilst some knowledge of the relationship between

leadership and EI exists, as presented in the literature review, this knowledge is

limited. Therefore, future research related to leadership and EI may have several

purposes according to the research objectives.

The research process refers to the method of data collection and analysis. The

two main paradigms, quantitative and qualitative, are regarded as two extremes on a

continuum. Quantitative researchers normally take a positivist approach and view

human behaviour from a technocratic perspective. In comparison, qualitative

researchers normally take an interpretivist approach and view human behaviour from

a transcendent perspective. The paradigms differ according to several assumptions

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related to: ontology, epistemology, axiology, rhetoric and method. The ontological

assumption refers to the researcher's view of the nature of reality. Quantitative

researchers view the world as objective and external to the researcher, whereas

qualitative researchers consider the world to be socially constructed and examine the

perceptions of the human actors (Hussey & Hussey, 1997). The epistemological

assumption refers to the researcher's view of what constitutes acceptable knowledge.

Positivists only regard observable and measurable phenomena as knowledge. Hence,

concepts take the form of distinct variables and the quantitative researcher generates,

and then tests, hypotheses or objectives. In comparison, interpretivists focus on

contextual details, motivating actions and subjective meanings. For the qualitative

researcher, concepts take the form of themes, motifs, generalisations and taxonomies

(Hussey & Hussey, 1997). The axiological assumption refers to the role of values.

Positivists believe that science and the process of research is value free. Hence, the

quantitative researcher is detached from the research, and the research phenomena are

considered to be objects. Quantitative researchers are interested in the

interrelationship of the objects they are studying. In comparison, interpretivists

believe that the researcher has values, even if they have not been made explicit, and

that the researcher is involved with the phenomena being investigated (Hussey &

Hussey, 1997). The rhetorical assumption refers to the research language. Positivists

use formal language and a passive voice. Whereas, interpretivists write in a style

which demonstrates the researcher's involvement. Finally, the methodological

assumption refers to the process selected. Quantitative researchers follow a deductive

cause and effect process. The research design is static and categories are isolated

before they are studied. Generalisations lead to prediction, explanation and

understanding, whilst accuracy is assessed by validity and reliability. In quantitative

72

research, data collection measures are created in order to collect data in numeric form,

and research procedures are standardised and replicated. Statistics are used for data

analysis and the results are discussed in terms of how they relate to the explicit

hypotheses or objectives of the research (Neuman, 2003). Quantitative methodologies

include: cross-sectional studies, longitudinal studies, experimental studies and

questionnaires. In comparison, qualitative researchers follow an inductive process.

The research design emerges and categories are identified during the research process.

Contextual patterns and theories are developed to enhance understanding, and

accuracy is assessed through verification. In qualitative research, ad-hoc data

collection measures are created that may be specific to the individual research context.

Data are collected in the form of words and images from documents and observations.

The researcher may collect the data and subsequently discover its meaning. Research

procedures are unstandardised and their replication may be rare. In the data-analysis

process, themes and generalisations are extracted from the data in order to present a

coherent picture. Qualitative methodologies include: case studies, ethnography,

grounded theory, hermeneutics and participative inquiry (Neuman, 2003). Although

quantitative and qualitative research differs in many ways they also have much in

common and may complement each other or be combined to form mixed

methodologies. The decision to use a quantitative or qualitative style of research

depends on the: topic, purpose of the research, intended use of the results and

orientation towards human behaviour adopted by the researcher (Neuman, 2003).

Taking into account these differences in the research process, a quantitative

process is deemed suitable for this project. Previous studies in the field have used

quantitative methodologies and this project seeks to replicate and expand on previous

studies. Therefore, the measures used to collect data must have adequate validity and

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reliability, which is a feature of the quantitative process, rather than be of the ad-hoc

nature commonly used in the qualitative process. Ontologically, the project will take

an objective, rather than subjective, view of the issues in common with the view of

reality shared by the research team. Regarding epistemology, measurable phenomena

in the form of variables will be tested using hypotheses and objectives. As in previous

studies in the field statistics will be used for data analysis. Whilst contextual details

may be lost in the quantitative process, it is considered a worthwhile trade-off in order

to accurately measure the phenomena under observation. Axiologically, the research

team will be detached from the research. Hence, the project will be written in a

passive voice synonymous with quantitative rhetoric. As a generalisation of the results

is sought a standardised research methodology is required. The flexibility in the

research design offered by the qualitative process is not required for this project as a

Pilot Study will be undertaken allowing alterations to the project design to be made as

necessary.

The research logic is described as either deductive or inductive. In deductive

research a conceptual and theoretical structure is developed and tested by empirical

observation. Hence, particular inferences are deduced from general inferences.

Deductive logic is synonymous with quantitative research. Whereas, in inductive

research a theory is developed from the observation of empirical reality and general

inferences are induced from particular instances. Inductive logic is synonymous with

qualitative research (Hussey & Hussey, 1997). The research logic of this project will

be deductive as particular inferences will be sought from general inferences.

The outcome of the research is described as applied or basic. This refers to

whether the research will solve a particular problem or make a general contribution to

knowledge. The findings of applied research are used to solve specific problems.

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Whereas, basic research is conducted to increase the understanding of general issues

or problems and the findings are not necessarily applied immediately. Hence, the

short term outcomes of this research project are basic but the medium and long term

outcomes are likely to be applied.

Of the various types of research methodology used in the quantitative

paradigm, tests, otherwise known as questionnaires or surveys, are the selected

method for this project. Tests are commonly used in research which takes the

deductive approach. Taking into account the professional background and

qualifications in psychology held by the research team psychological testing methods

are considered appropriate for this project.

Psychological Tests

Psychological tests are among the most significant tools for both researchers

and practitioners in the field of personnel psychology. Kaplan and Saccuzzo (2005, p.

6) define a psychological test as “a set of items that are designed to measure

characteristics of human beings that pertain to behaviour.” Psychological tests are

used to evaluate individual differences by quantifying overt and/or covert behaviour.

They are useful tools for practitioners and researchers who seek to predict or increase

their understanding of behaviour (Kaplan & Saccuzzo, 2005).

The origins of testing can be traced back more than four-thousand years to the

Chinese Civil Service. However, most of the major test developments have occurred

over the last century, especially in the USA. Statistical techniques such as correlation

and regression procedures were developed in the same era as the first modern tests,

such as the 1905 Binet-Simon scale, and enabled researchers to analyse test data more

effectively (Kaplan & Saccuzzo, 2005). Psychological tests are now used as tools in

many different fields and settings.

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The two main categories of psychological tests are ability tests and personality

tests. Ability tests measure skills in terms of speed and/or accuracy. One subgroup of

ability tests are intelligence tests, which measure an individual's potential to solve

problems, adapt to changing circumstances and learn from experience. Personality

tests measure typical 'normal' behaviour (traits, temperaments and dispositions) using

objective or projective means (Kaplan & Saccuzzo, 2005).

The field of psychological measurement is known as psychometrics. In this

field, human behaviour is scientifically measured by systematically analysing,

categorising and quantifying observable phenomena (Urbina, 2004). Test outcomes

are almost always represented by numerical scores which are evaluated using

statistical procedures. Scales which relate raw scores on test items to a defined

empirical distribution are used to deal with problems of interpretation. Descriptive

statistics are used to describe a collection of quantitative data and evaluate

observations relative to others. Whereas, inferential statistics are used to make

inferences about events from observations of a small group of people (a sample) to a

larger group of people (a population). Norms relate scores to a particular distribution

for a subgroup of a population (Kaplan & Saccuzzo, 2005). A psychological test must

meet certain reliability and validity criteria in order to be considered a useful tool

(Shum, Gorman, & Myors, 2006). Reliability refers to “the accuracy, dependability,

consistency, or repeatability of test results” (Kaplan & Saccuzzo, 2005, p. 10). The

level of test reliability determines the degree to which test scores are free from

measurement errors. The internal consistency of a test can be assessed by calculating

its split-half reliability (scores on half-tests are correlated with each other and the

mean of all split-half coefficients). Test-retest reliability is often used to assess the

consistency of a test by calculating the Pearson product-moment correlation

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coefficient (r) which is a “mathematical index that describes the direction and

magnitude of a relationship” (Kaplan & Saccuzzo, 2005, p. 65).

Validity refers to the meaning and usefulness of test results or “the degree to

which a certain inference or interpretation based on a test is appropriate” (Kaplan &

Saccuzzo, 2005, p. 10). There are several types of validity. Criterion-related validity

refers to the ability of a test to estimate a respondent‟s performance on a selected

outcome (Gregory, 2004). The relationship between a test and a criterion when both

are measured at the same time is referred to as concurrent validity (Kaplan &

Saccuzzo, 2005), whereas the ability of a test to forecast a respondent‟s performance

at a later date is known as predictive validity. Evidence for the construct validity of a

test is determined by the degree to which the underlying characteristics of the test are

accurately inferred. A test demonstrates convergent validity when it correlates highly

with other variables that are hypothetically related to the underlying construct.

Conversely, discriminant validity is demonstrated when a test does not correlate

highly with variables from which it is meant to differ (Gregory, 2004). Finally, the

incremental validity of a test is determined by the amount of information it

contributes beyond that contributed by another method used for making the same

prediction (Kaplan & Saccuzzo, 2005).

The objectivity of the psychological testing method appeals to researchers who

seek to generalise the findings of their studies. Test materials, administration

processes and scoring procedures are the same for all test takers. Also, standards

based on empirical data are used to evaluate test results which can be described

precisely using quantitative summaries. Therefore, the level of objectivity provided by

psychological testing is potentially high in comparison with other research methods.

However, psychological tests have limitations as measurement tools and

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margins of error must be estimated and communicated with test results. Also, as

psychological tests often attempt to measure hypothetical constructs that are not

expressed directly by behaviour, it is important to recognise that differences

highlighted by the findings of a test do not necessarily reflect actual individual

differences (Urbina, 2004). Furthermore, despite ongoing advances in the theory of

psychological testing issues such as cultural or language bias continue to be debated

and addressed (Shum, Gorman, & Myors, 2006). Therefore, it is important to

recognise that psychological tests are only tools to be used in decision-making

processes. Overall, as many of the concepts of interest in this project are not readily

observable and psychological testing provides an objective approach which enables

findings to be generalised, it is considered to be a suitable method for use in this

project.

Multiple Ratings of Leadership Behaviours

The validity of data collected from abilities tests such as those used to measure

intelligence is high, however, the validity of self report data collected from

behavioural measures varies immensely as a result of self-serving bias and common

method variance (Atwater, 1998). Self-serving bias may has been observed regardless

of whether ratings are based on performance, skills, behaviors or traits (Harris &

Schaubroeck, 1988). Collecting data related to leadership behaviours from the leader

alone is far from ideal as self-ratings tend to provide inflated estimates of behaviours

that the leader considers to be positive (Atwater, 1998). However, self-serving bias

can be countered by collecting ratings from multiple sources. Harris and Schaubroeck

(1988) argue that individuals are not good at evaluating themselves objectively and

that anonymous feedback provided by others helps leaders to view themselves as

others view them, and provides them with useful information which can be used for

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self-development. The multiple ratings process also permits a comparison to be made

between the various rating levels.

The rating of a leader by his/her peers, supervisor and followers may vary

according to: interpersonal interactions, shared feedback (Ashford, 1989), the

perspective taken by each rater and the opportunity to observe the leader as afforded

by role. Supervisors are considered to be a useful source of rating information as they

are able to closely observe the leader‟s behaviour and evaluate his/her contribution to

the organisation. Peer ratings are also useful as peers are more likely to interact with

the leader on a regular basis which enables them to assess typical behaviours

including how the leader interacts with others (Latham, 1986, cited in Landy & Conte,

2006). In their meta-analysis of job performance predictors, Schmidt and Hunter

(1998) reported that peer ratings were useful predictors of job performance (r = .49).

Ratings by followers are also useful, but it is crucial that the feedback remains

anonymous to prevent the possibility of retaliation from the leader if the feedback is

negative (Hedge & Borman, 1995). Empirical studies have demonstrated that certain

characteristics and behaviors displayed by a leader may influence the perceptions of

followers (Zaccaro, Foti, & Kenny, 1991). The relationship between leaders and

followers is impacted by the personality traits of the leader and other variables such as

the followers‟ perceptions of what represents ideal leader behaviour (Conger &

Kanungo, 1994), and the perceived intelligence of the leader (Allinson, Armstrong, &

Hayes, 2001). Self-ratings are also considered to be valuable when collecting

information about leadership behaviours or performance. Although self-ratings may

be less valid and reliable than other-ratings, and may account for less variance in

certain criteria (Podsakoff & Organ, 1986), they are nevertheless useful (Harris &

Schaubroeck, 1988).

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Harris and Schaubroeck (1988) conducted a meta-analysis to assess the

relationship between self-supervisor, self-peer and peer-supervisor ratings in the

workplace. The meta-analysis included 36 independent self-supervisor correlations,

23 independent peer-supervisor correlations, and 11 independent self-peer

correlations. The authors reported a relatively high correlation between peer and

supervisor ratings (ρ = .62), and a moderate correlation between self-supervisor (ρ =

.35) and self-peer ratings (ρ = .36). The results indicated that self-ratings differ

considerably from peer and supervisor ratings. Harris and Schaubroeck (1988)

suggested that the differences in the strength of the relationships may be the result of

the relatively different perspectives held by the self and relevant others. Hence, the

authors concluded that it is important to collect leadership ratings from various

sources and not solely from the leader in order to obtain a more valid view of the

leader's behaviours.

In another meta-analysis conducted by Atwater, Ostroff, Yammarino &

Fleenor (1998) data was collected from 1,464 managers who participated in

leadership development programs. As part of each program, a multi-rater feedback

instrument was completed by the manager, and his/her peers and followers. The

effectiveness of each manager was rated by his/her direct supervisor. Results from

polynomial regression analyses indicated that both self-rating and other-rating sources

were related to performance outcomes. Notably, self-rating and other-rating sources

did not correlate strongly with each other (self-follower, r = .25; self-peer, r = .26;

self-supervisor, r = .25). Atwater et al. (1998) suggested that the unique perspectives

at each level diminish the likelihood of the self and other rating sources working

interactively. Atwater et al. (1998) concluded that simultaneous consideration of both

self and other rating sources is important for explaining managerial effectiveness.

80

The limitations of using self-ratings alone explain why human resource

practitioners and researchers prefer to use multiple rating sources when collecting data

related to leadership behaviours or performance. This data is usually collected by

administering surveys to relevant stakeholders such as the leader and his/her peers,

supervisor and followers. An average score of the ratings collected is normally used to

measure the leader's behaviour or performance on a particular criterion (Atwater et al.,

1998). This results in a form of 360-degree feedback which is considered to be

appropriate when assessing behaviours or variables that may not be readily observable

to all.

Collecting multiple ratings from a large sample is undoubtedly a difficult task

for researchers, which explains why many previous leadership studies have only used

self-ratings of leadership behaviours. Logistically, it requires considerable effort to

coordinate the collection of the data from multiple raters. If the data is being collected

using a commercial measure, such as the MLQ (Avolio et al., 1995), the financial

implications also need to be considered as money is expended every time a rater

completes the measure. Potential raters may not be forthcoming as they may need to

be convinced that their ratings will remain confidential and this may not be an easy

task if the researcher is unknown to the raters. Additionally, some potential raters

simply may not have enough time to complete the rating within the time-frame set by

the researcher. Nominating a rater who fulfills the role of supervisor may be

particularly difficult as some participants may hold the highest position within their

organisation. These issues go some way to explaining why research projects using

multiple ratings are uncommon in the leadership literature and virtually non-existent

in previous studies of leadership and EI. However, the validity of research projects

which have used self-ratings alone remains questionable at best, hence leadership and

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EI research needs projects which have obtained leadership ratings from multiple

sources in order to answer the important questions and expand knowledge in this area.

As multiple ratings are considered to be the most valid form of assessing

leadership behaviours (Landy & Conte, 2006) this project will attempt to collect

ratings data from each leader that participates in the project, and from one each of

his/her peers, supervisors and followers. The demands of collecting data from more

than one rater at each level are considered to be beyond the scope of this project.

Having determined that a quantitative, psychological testing methodology will

be used in this project and that multiple ratings of leadership behaviours will be

collected, it is important to clarify which leaders will be suitable participants for the

project sample. This requires an analysis of the roles of educational leaders in

Australia. Furthermore, it is worth acknowledging current methods of assessment and

selection for educational leaders. These issues are outlined in the following section.

Educational Leadership in Australia

Role of School Leaders

In Australia, education is governed at the federal level by the Department of

Education, Employment and Workplace Relations. Each state or territory has its own

department which provides funding, sets the curriculum and regulates both public and

private schools within its boundaries. The education system consists of three tiers:

primary schools, secondary/high schools and tertiary institutions (universities and

TAFE institutions). Pre-school education is not compulsory. Education is compulsory

from the age of five years up to an age specified by each state or territory which is

generally 15-17 years old. Post-compulsory education is regulated within the

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Australian Qualifications Framework which is a unified system of national

qualifications in schools, vocational colleges and the higher education sector.

Universities set their own curriculum but they are partially funded by the federal

government (Department of Immigration & Citizenship, 2010).

Principals, otherwise known as the head of school or head of campus, are

responsible for leading schools. The role of the school principal can be described by

outlining the work practices that he/she undertakes. Spillane, Camburn and Pareja

(2007) studied the work practices of principals in the USA and found that they spent

their time undertaking the following activities: administrative (63.45%), instruction

and curriculum (22.20%), professional growth (5.80%) and fostering relationships

(8.70%). Bristow, Ireson and Coleman (2007) found similar patterns in the

distribution of the work practices of 34 principals in the United Kingdom. The

principals' work consisted of: administration (24%), meeting the demands of external

stakeholders (17%), management (15%), meeting the demands of internal

stakeholders (9%), continuous professional development (9%), strategic leadership

(7%), personal issues (4%) and other tasks (14%). In a similar study of 200 principals

in Victoria, Australia, Gurr et al. (2006) found that principals' time was divided

amongst: administration (26.30%), alone (14.10%), working with teachers (11.60%),

working with students (9.30%), teaching (9.10%), with parents (7.70%), working with

the leadership team (7.50%), working with non-teaching staff (6.80%), walking

around school (6.60%), working with external groups (4.80%), professional learning

(3.90%), school board (3.90%) and unspecified (10.70%) (as some categories

overlapped in this study the total percentage of how principals spent their time does

not add up to 100%).

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It is possible to gain a deeper insight into the work practices of school leaders

in Australia by examining their role as outlined in job descriptions. For example, the

duties of the principal, deputy principals and heads of department in public schools in

Queensland, Australia, are presented in Table 7 (Department of Education &

Training, 2010).

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Table 7

The Duties of the Principal, Deputy Principals and Heads of Department in Public Schools in Queensland,

Australia

This table is not available online. Please consult the hardcopy of the thesis available from the QUT Library.

Note. The Duties of the Principal, Deputy Principals and Heads of Department in Public Schools in Queensland, Australia. Adapted from “Teaching role descriptions: Stream 3”, by Department of Education & Training, 2010.

85

Whilst these duties are only representative of one state they are generally

typical of those required by school leaders in Australia. It is fitting to note that the

duties include the requirement to “Lead the school community (or department) to

develop, articulate and commit to a shared educational vision”, which describes an act

of transformational leadership in practice. Furthermore, school leaders are expected to

“Uphold the role of principalship (or deputy principalship) as an ethical and moral

activity” and “Place socially just practices in everyday school life.” It is reasonable to

assume that these duties require leaders with high levels of integrity.

Analysis of Table 7 confirms that school leadership is considered to be a

distributed task which involves the principal and other key figures. This is confirmed

by Spillane et al. (2007) who found that principals spent two thirds of their time

leading whilst the remaining one third was spent in co-leading situations. This

highlights the importance of the contribution to school leadership made by others,

notably; administrators, vice-principals and heads of department. In Australia,

administrators of public schools are employed at a higher organisational level than the

principal by the state or territory government. In private schools governors fulfill a

similar role. In public and private schools it is normal practice to employ at least one

vice-principal at a lower organisational level than the principal, and several heads of

department at lower organisational levels than the vice-principal. These positions may

have various titles as the roles are often defined by administrative or curriculum-based

activities (Department of Immigration & Citizenship, 2010).

Selection of School Leaders

It is important to acknowledge how school leaders are currently assessed and

selected in Australia. Generally, the selection procedure for each school leadership

86

role involves an interview by a panel, an assessment of formal qualifications and

experience, and the provision of suitable references (Department of Education &

Training, 2010). Psychological testing is not normally undertaken. Furthermore, the

completion of an EI test is not normally required. However, candidates may have

completed an off-the-shelf EI test in courses as part of their professional development,

or they may have completed tests that included an EI component as part of leadership

training. However, as interest in leadership concepts and theories from outside the

current boundaries of educational leadership grows, more educational organisations

are taking an interest in cross-disciplinary measures of selection and assessment.

Examples of the selection criteria for the roles of principal, vice-principal and head of

department in public schools in Queensland, Australia, are presented in Table 8

(Department of Education and Training, 2010).

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Table 8

Selection Criteria for the Roles of Principal, Vice-Principal and Head of Department in Public Schools

in Queensland, Australia

This table is not available online. Please consult the hardcopy of the thesis available from the QUT Library.

Note. Selection Criteria for the Roles of Principal, Vice-Principal and Head of Department in Public Schools in Queensland,

Australia. Adapted from “Teaching role descriptions: Stream 3”, by Department of Education & Training, 2010.

With reference to Table 8, it is reasonable to assume that in order to meet the criteria

for “Demonstrated interpersonal skills and the ability to develop and maintain

relationships with stakeholders” the candidate would require emotional knowledge or

a reasonable level of EI. Also, the “Capacity to manage human, (financial and

physical) resources to achieve positive organisational outcomes” and the “Capacity to

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support, develop and maintain an organisational culture based on ethical behaviours

and corporate values” would require candidates with substantial integrity. Hence,

these statements go some way to supporting the inclusion of these variables for

examination in this project.

Research Aims

The overall aim of this project is to answer the main research question: to what

extent is the Mayer and Salovey (1997) model of EI a useful predictor of leadership

style and leadership outcomes? This overarching question has been broken down into

a series of questions, specifically: Is the Mayer and Salovey (1997) model of EI

related to leadership style and leadership outcomes? Does the Mayer and Salovey

(1997) model of EI have divergent validity from GMA and personality factors? Is the

Mayer and Salovey (1997) model of EI able to predict leadership style and leadership

outcomes when multiple ratings of leadership behaviours are obtained? Does the

Mayer and Salovey (1997) model of EI have incremental validity above other

predictors of leadership style and leadership outcomes? These questions have been

further sub-divided to create the specific research questions and hypotheses that will

be examined in this project (Refer to Table 6).

Participants for the project will be leaders based in Australian educational

institutions. The project will examine whether EI has discriminant validity from, and

incremental validity above, individual differences based predictors of leadership style

and leader effectiveness. The project will include predictor variables which represent

the antecedents of leader-focused behaviours, rather than follower-focused and

situation-focused variables. The usefulness of EI as a predictor will be compared with

established predictors from this domain. The project does not aim to provide a

comprehensive assessment of the impact of leadership antecedents from other

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domains. Therefore, in keeping with an individual differences approach only the

predictors which represent the traits and abilities commonly measured in the field of

personnel selection will be examined. The project will also continue the process of

assessing the construct validity of the Mayer and Salovey (1997) model of EI.

As many previous studies have found that GMA is the most effective predictor

of job performance (Schmidt & Hunter, 1998) and a useful predictor of leadership

behaviours (Judge et al., 2004), GMA will be included as a predictor in this project.

As personality factors are known to predict leadership behaviours and leader

effectiveness (Bono & Judge, 2004; Judge et al., 2002) their effect will also be

examined. The project will take a trait-based approach to personality and employ a

measure of the five-factor model as commonly practiced in personnel selection

procedures. Landy (2005) and Antonakis (2009) suggest that in addition to GMA and

personality factors, other predictors should also be included in future studies. Further

research related to the impact of integrity on leadership behaviours is warranted

(Parry & Proctor-Thomson, 2002). Therefore, as integrity is also a well established

predictor of job performance (Schmidt & Hunter, 1998) that is based in the individual

differences domain it will be assessed in this project. Finally, as there is still

considerable disagreement regarding the effect of gender on leadership behaviours,

the relationship between gender and EI, and gender and leadership style will be

examined.

The project will employ a cross-sectional design and use quantitative,

psychological testing methods in order to build on previous research in the field. Tests

will be used in their standard „off-the-shelf‟ form as they would be by human resource

practitioners in the workplace. Hence, human resource practitioners who seek to apply

the findings of the project will be able to use these tests without having to make any

90

alterations. Multiple ratings of leadership behaviours will be obtained from each

leader and other relevant stakeholders. Following the coding of data, correlation,

multiple regression and difference between the means procedures will be undertaken

to enable the statistical relationships between the variables to be analysed. Initially, a

Pilot Study will be undertaken to make a preliminary examination of the relationship

between the variables of interest and determine whether further investigation is

warranted. Subsequently, a Main Study with a larger sample will follow.

The findings of the project may result in an increase in the theoretical

understanding of the relationship between EI, leadership style and leadership

outcomes, and contribute to a body of literature assessing the usefulness of EI as a

predictor of leadership style and leadership outcomes. The project also aims to

provide human resource practitioners in Australian schools with an empirical platform

on which to base their decisions to introduce, or relinquish, the use of EI measures in

their leadership assessment and selection procedures.

Ethical Considerations

Prior to commencing the Pilot Study, approval was obtained from the

University Human Research Ethics Committee at Queensland University of

Technology (QUT) for Level 1 Low Risk Ethical Clearance. The project aimed to

comply with the National Statement for the Ethical Conduct of Research Involving

Humans regarding principles of: integrity, respect, beneficence, justice, consent,

research merit and safety. The project also aimed to comply with the QUT Code of

Conduct of Research regarding; responsible practice, storage of data, confidentiality,

authorship, publication, disclosure of conflicts of interest and procedures for dealing

with allegations of misconduct. Efforts to apply these principles would include

obtaining informed consent from educational leaders and their followers, peers and

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supervisors who participate in the project. A written explanation of how

confidentiality would be maintained would be provided to each participant. In order to

maintain confidentiality, an individual numeric code would be allocated to each leader

and their followers, peers and supervisors, and included on response sheets. The

primary research data would be stored securely for a minimum period of five years at

QUT. Participants would be provided with the opportunity to withdraw from the

project at any point. Feedback would be offered to each leader by the research team

all of whom have appropriate qualifications in psychology. Finally, each leader would

be offered debriefing which would take place over the telephone if requested.

Conclusion

This chapter has presented the aims of a project which will attempt to answer

the main research question: to what extent is the Mayer and Salovey (1997) model of

EI a useful predictor of leadership style and leadership outcomes? The project will

examine whether EI has discriminant validity from, and incremental validity above,

individual difference based predictors of leadership style and leader effectiveness

(GMA and personality factors). The impact of integrity on leadership behaviours will

also be assessed. Multiple ratings of leadership behaviours will be collected to

increase the validity of the leadership data. Additionally, the relationship between

gender and EI, and gender and leadership style will be examined. The project will

continue the process of assessing the construct validity of the Mayer and Salovey

(1997) model of EI. A quantitative, psychological testing method has been selected

for the project. This method was described with reference to its strengths and

limitations, test categories, and psychometric properties such as reliability and

validity. The project will employ a cross-sectional design consisting of a Pilot Study

followed by a Main Study if warranted. The role of school leaders in Australia was

92

described and an example of the criteria currently used to select leaders was

presented. A research proposal was submitted and approved by the University Human

Research Ethics Committee at QUT in order to obtain ethical clearance to undertake

the project. The project aims to add to a theoretical body of work in the field and

provide human resource practitioners in Australian educational institutions with an

empirical platform on which to base their decisions to introduce, or relinquish, the use

of EI measures in their leadership assessment and selection procedures.

93

Chapter 4: Pilot Study

Introduction

A Pilot Study was undertaken to commence the investigation of the main

research question: to what extent is the Mayer and Salovey (1997) model of EI a

useful predictor of leadership style and leadership outcomes? The Pilot Study

presented an opportunity to make a preliminary examination of the relationship

between the variables of interest, assess the methodology selected for the project and

ascertain whether further investigation was warranted. In this chapter, the independent

and dependent variables examined in the Pilot Study are presented, followed by the

research questions and hypotheses formulated to test the relationship between EI, and

leadership style and perceived leadership outcomes. The impact of gender is also

examined.

The methodology for undertaking the Pilot Study is outlined with reference to

the procedure, participants and instruments selected to operationalise the conceptual

variables. Participants were 25 educational leaders (10 male and 15 female) and 75

peers, followers and supervisors nominated as raters by the leaders. Each instrument

selected for the study is described and evaluated in detail with regard to its purpose,

development, administration and psychometric properties. The Pilot Study provided

an opportunity to examine the discriminant validity of the instruments and assess the

efficacy of their online testing platforms. Methods for data entry using SPSS version

15.0 (SPSS, 2007) and the data screening process are described. Then, descriptive

statistics and the results of bivariate statistical analysis consisting of correlation and

difference between the means procedures undertaken are presented. Finally, the

methodology of the Pilot Study is assessed in relation to its suitability for use in a

further study.

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Independent Variables and Dependent variables

The following independent variables were measured and their effect on the

dependent variables was measured: total EI, strategic EI, experiential EI, perceiving

emotions, using emotions, understanding emotions, managing emotions, general

mental ability, neuroticism, extraversion, openness, conscientiousness, agreeableness

and integrity.

The dependent variables were: transformational leadership, contingent reward

(transactional leadership), management-by-exception active (transactional leadership),

passive/avoidant leadership, satisfaction, extra effort and effectiveness (each self-

rated and rated by one follower, one peer and one supervisor per leader). The

independent variables and dependent variables are presented in Table 9.

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Table 9

Independent Variables and Dependent Variables

Independent variables Dependent variablesa

Total EI

Experiential EI

Strategic EI

Perceiving emotions

Using emotions

Understanding emotions

Managing emotions

General mental ability

Neuroticism

Extraversion

Openness

Conscientiousness

Agreeableness

Integrity

Transformational leadership

Contingent reward (transactional leadership)

Management-by-exception active (transactional

leadership)

Passive/avoidant leadership

Satisfaction (with leader)

Extra effort (by followers)

Effectiveness (of individual/group)

aSelf-rated and rated by one follower, one peer and one supervisor per leader

Research Questions and Hypotheses

Taking into account the findings of previous studies it is predicted that support

will be found for the following hypotheses which will be tested in the Pilot Study:

Hypothesis 1. EI will have discriminant validity from GMA (Refer to Van

Rooy & Viswesvaran, 2004).

Hypothesis 2. EI will have discriminant validity from personality factors

(neuroticism, extraversion, openness, conscientiousness and agreeableness)

(Refer to Van Rooy & Viswesvaran, 2004).

Hypothesis 3. Total EI scores will be significantly higher for females than for

males (Refer to Mayer & Geher, 1996; Mayer, Caruso, & Salovey, 1999;

96

Mayer, Salovey, & Caruso, 2004).

Hypothesis 4. Transformational leadership scores will be significantly higher

for females than for males (Refer to Bass & Avolio, 1994; Bass et al., 1996;

Eagly et al., 2003).

As there is insufficient literature in some areas of interest to develop specific

hypotheses the following research questions have been formulated for the Pilot Study:

Research question 1. Investigate whether there is a positive relationship

between EI and transformational leadership.


between EI and perceived leadership outcomes (satisfaction, extra effort and

effectiveness).

Research question 3. Investigate whether there is a relationship between EI

and transactional leadership (contingent reward and management-by-exception

active).

Research question 4. Investigate whether there is a negative relationship

between EI and passive/avoidant leadership.

Research question 5. Investigate whether integrity has discriminant validity

from personality factors (neuroticism, extraversion, openness,

conscientiousness and agreeableness).

Methodology

Participants and Procedure

Two hundred and forty leaders (heads of schools, course coordinators, unit

coordinators) from an Australian university, ten heads of departments from Australian

schools and five administrators from The Department of Education and Training in

Queensland were invited to participate as leaders in the Pilot Study. Each leader was

97

responsible for several staff. University course coordinators are responsible for a

program (e.g., Bachelor of Psychology) and the teaching and administrative staff that

work within that program. Whereas, unit coordinators are responsible for at least one

unit (e.g., Developmental Psychology) and the teaching staff related to that unit.

Invitations containing preliminary information about the project were sent to the

leaders by email (Refer to Appendix A). Those who responded and expressed an

interest in participating in the study were sent instructions regarding how to

participate in a further email (Refer to Appendix B). In order to maintain

confidentiality, participants were provided with individual codes which would be used

to identify them throughout the project. Each code consisted of three letters and two

numbers (e.g., dhf36). The first two letters consisted of the participant‟s initials whilst

the third letter represented gender; „m‟ for male or „f „for female. The two numbers

were the age in years of the participant. Participants used their codes to identify

themselves when accessing the five websites necessary to complete the

questionnaires. Participants were requested to complete the questionnaires online at

any location within a two-week period. Those who had not completed the task within

two weeks were sent a reminder by email and provided with extra time.

Initially, twenty eight leaders agreed to participate in the Pilot Study.

Additionally, each leader provided the contact details of one supervisor, one peer and

one follower, all of whom had agreed to complete online ratings of the leader (Refer

to Appendix C). In return for participating in the Pilot Study, each leader was offered

feedback related to the project and his/her individual results from the leadership, EI

and personality questionnaires. Raters‟ responses to the qualitative items from the

leadership questionnaire were also offered as feedback. One respondent did not

complete all of the requirements for participation. Therefore, the sample was reduced

98

to 27 leaders (11 men and 16 women) and 81 raters. Ten of the leaders were heads of

schools, four were course coordinators, eight were unit coordinators and five were

administrators. The mean age of the participants was 43 years.

Instruments

The conceptual variables were operationalised using online questionnaires.

The instrument selected to test leadership styles and perceived leadership outcomes

was the MLQ5X (Avolio et al., 1995). EI was assessed using the MSCEIT (Mayer et

al., 2002). Personality factors were operationalised by The Big Five Inventory (BFI,

John et al., 1991). GMA was tested by the Wonderlic Personnel Test – Quicktest

(WPT-Q, Wonderlic, 2003) and integrity was assessed using Integrity Express

(Vangent, 2002a). In the following section each of the selected instruments is

described and evaluated in relation to its purpose, development, administration and

psychometric properties.

Multifactor Leadership Questionnaire (MLQ)

The MLQ (Avolio et al., 1995) is designed to assess the full-range of

leadership behaviours of practicing leaders in organisations. Since its introduction in

1985 the MLQ (Avolio et al., 1995) has been the subject of considerable empirical

research and revision. The MLQ (Avolio et al., 1995) measures the degree to which

the leader uses: transformational leadership (idealised attributes, idealised behaviours,

inspirational motivation, intellectual stimulation and individualised consideration),

transactional leadership (contingent reward and management by exception active) and

passive/avoidant leadership (laissez-faire and management by exception passive). The

test also measures the performance of the leader as rated by their followers, peers and

supervisors in relation to: satisfaction with the leader, extra effort by followers, and

individual and group effectiveness (Kirnan & Snyder, 1995). Using multiple ratings

99

of leadership behaviours is recommended by the publisher, Mind Garden Inc., to

maximise validity. The current version is the MLQ5X (Avolio et al., 1995) which

consists of 45 items rated on a 5-point Likert-type scale. Ratings are based on the

frequency with which the leader is considered to demonstrate the behaviours

described in each item (not at all, once in a while, sometimes, fairly often, frequently

if not always). The self-rating form contains statements that describe the leader‟s

behaviour such as These test items are not available online. Please consult the

hardcopy of the thesis available from the QUT Library. Note. Copyright 1995 by

B. J. Avolio and B. M. Bass. All rights reserved. Mind Garden Inc.

www.mindgarden.com. Reprinted with permission. Whereas, the rater form contains

statements about the leader‟s behavior to be answered by peers, followers and

supervisors, such as These test items are not available online. Please consult

the hardcopy of the thesis available from the QUT Library. Note. Copyright

1995 by B. J. Avolio and B. M. Bass. All rights reserved. Mind Garden Inc.

www.mindgarden.com. Reprinted with permission. The questionnaire takes

approximately 15 minutes to complete. Data sets are provided by the publisher for

each respondent when the online administration method is selected.

Reliability for the test is acceptable. Alpha coefficients for the self-rating form

range from .60 to .98, and .77 to .95 for the rater form (Kirnan & Snyder, 1995). Test-

retest reliabilities over a six-month period for the factor scales are barely adequate for

the self-rating form ranging from .44 to .74, and adequate for the rater form ranging

from .52 to .85 (Kirnan & Snyder, 1995). Adequate validity has also been

demonstrated using factor inter-correlations consistent with theory. Evidence of

criterion related validity has been provided through the correlation of the factors with

rated outcomes (Kirnan & Snyder, 1995). Many studies have used the MLQ (Avolio

100

et al., 1995) to investigate transformational and transactional leadership across a wide

variety of situations. Results indicate that transformational leadership can be observed

in many different countries, cultures, organisations and at all organisational levels. As

highlighted in the literature review, there is considerable evidence that

transformational leadership is a significantly better predictor of organisational

effectiveness than transactional leadership or passive-avoidant leadership (Judge &

Piccolo, 2004; Lowe et al., 1996) and the results of training programs provide

evidence that it is possible to develop transformational and transactional leadership

skills (Avolio & Bass, 1999). Norms are based on data from self-ratings of leaders (N

= 251), supervisee ratings of those leaders (N =1,006), self-ratings of peer leaders (N

= 169) and peer ratings of peer leaders (N = 474) (Kirnan & Snyder, 1995).

Overall, the MLQ5X (Avolio et al., 1995) is a sound test of the full-range of

leadership behaviours that has adequate reliability and is strongly recommended for

use in research settings. Several researchers have argued that the scales representing

transformational leadership are best represented as a single transformational

leadership scale (e.g., Yammarino & Dubinsky, 1994; Tracey & Hinkin, 1998;

Carless, 1998). Hence, in this project the five scales representing transformational

leadership will be aggregated. Furthermore, as the distinction between the

passive/avoidant scales (management-by-exception passive and laissez-faire) is not

clear (Den Hartog, Van Muijen, & Koopman, 1997) these scales can be represented as

a single passive/avoidant scale. Therefore, the two scales representing

passive/avoidant leadership will also be aggregated in this project. Finally, the two

scales representing transactional leadership (management-by-exception active and

contingent reward) will be analysed separately as they are considered to be

substantially different (Avolio et al., 1995). The structure selected to represent the

101

MLQ (Avolio et al., 1995) in this project as described above is in-line with the

recommendations made in a personal email from the co-author of the test B. J. Avolio

(personal communication, April 11, 2010).

Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT)

The MSCEIT (Mayer et al., 2002) is a self-report, ability-based measure of EI

for adults. The test is suitable for use in a variety of contexts including research and

educational settings. It consists of 141 items and takes 30-45 minutes to complete.

The test may be administered by computer and answer sheets are scored by the

publisher Multi-Health Systems Inc. (Leung, 2005).

Initially, Salovey and Mayer (1990) developed the 30-item Trait Meta Mood

Scale (TMMS) to measure attitudes related to emotions and mood. However, as the

TMMS (Salovey & Mayer, 1990) does not measure actual performance of emotional

abilities Mayer and Salovey (1997) developed a performance-based measure, the 402-

item MEIS, (Mayer, Salovey, & Caruso, 1999), in order to assess their EI model more

comprehensively. Eventually, the MEIS was revised to become the 294-item MSCEIT

RV1.1 (Mayer, Salovey, & Caruso, 1999). The current version, the 141-item MSCEIT

2.0 (Mayer et al., 2002), was developed in order to reduce the total number of items

and strengthen the reliability of the subscales (Leung, 2005).

The MSCEIT (Mayer et al., 2002) uses two-tasks to assess each of the four

branches of the Mayer and Salovey (1997) model of EI. The perceiving emotions

branch is assessed by a face task (emotions have to be identified from facial

expressions) and a picture task (pictures of ambiguous stimuli have to be identified).

The following is a sample item of the face task (a picture of a face would be

included):

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This test item is not available online. Please consult the hardcopy of the thesis

available from the QUT Library.

Note. Copyright 2002 by Multi Health Systems Inc. www.mhs.com. All Rights

Reserved. Reprinted with permission.

The facilitating thoughts branch is assessed by a sensation task (test takers

compare emotions with sensations expressed through modalities such as temperature

and colour) and a facilitation task (test takers have to identify emotions that would

facilitate various cognitive and interpersonal tasks). The following is a sample item of

the facilitation task:



Note: Copyright 2002 by Multi Health Systems Inc. www.mhs.com. All Rights


The understanding emotions branch is assessed using a blends task (test takers

are required to identify different emotions that may co-exist in a single scenario) and a

changes task (test takers are required to identify chains of related emotions differing

103

in intensities and situations that may cause transitions of emotions through these

chains). For example:





Finally, the managing emotions branch is assessed by an emotion management

task and an emotional relations task (related to emotion management and coping

strategies in interpersonal situations which involve emotions). For example:





104

The tasks form eight subscales which generate four branch scores, two area

scores and a total EI score (Leung, 2005). The mean score for each scale is 100 with a

standard deviation of 15. Test scores are generated using either the general consensus

or expert consensus method. The general consensus method compares the responses

of the test taker to those in the normative sample (N = 5000). The score assigned to

each possible response for an item is represented by the proportion of individuals in

the normative sample who considered the same response to be correct. The expert

consensus method compares the responses of the test takers to the responses of 21

international experts on emotions. Correlation coefficients between scores derived

from the two methods for the overall branch, area and task scores range from .93 to

.99 (Leung, 2005). Consensus scores are normally used by researchers.

Regarding the psychometric properties of the instrument, confirmatory factor

analysis has supported the four-branch model of EI (Leung, 2005) although some

researchers have expressed concerns about the absence of scientific standards for

determining the accuracy of consensus and expert scores. Initial findings are generally

supportive of the convergent and discriminant validity of the MSCEIT (Mayer et al.,

2002), and suggest that the test provides discriminant ability from personality and has

predictive validity in field tests (Mayer et al., 2004). Test-retest reliability for the

MSCEIT (Mayer et al., 2002) is high (.82, N = 62) and estimates of split-half

reliability for the total area and branch scores range from .79 to .93 for general

scoring, and .76 to .91 for expert scoring (Mayer, Salovey, Caruso, & Sitarenios,

2003). Internal consistency for the eight task scores ranges from .64 to .88 (M = .71)

for general scoring and .56 to .87 (M = .68) for expert scoring (Leung, 2005).

Matthews, Zeidner and Roberts (2002) argue that the reliabilities of the subscales are

far from optimal for an ability measure. However, preliminary evidence related to

105

other forms of reliability is promising. Incremental validity of the original MSCEIT

RV1.1 over GMA was considered to be minimal (Van Rooy & Viswesvaran, 2004)

but the initial data for the MSCEIT V.2 (Mayer et al., 2002) is much more promising

in this respect. Additional empirical evidence for the validity of the MSCEIT V.2

(Mayer et al., 2002) is still required and one of the aims of this project is to contribute

to a body of work which will be used for this purpose. Overall, The MSCEIT V.2

(Mayer et al., 2002) is based on a clear theoretical structure of EI and is considered

suitable for conceptualising the abilities model of EI in this project. As the consensus

scoring method is recommended for research use (Mayer et al., 2002) it will be used

in this project.

The Big Five Inventory (BFI)

The Big Five Inventory (BFI) (John et al., 1991) is a short measure of

personality that measures five broad and relatively stable dimensions of personality,

namely: extraversion, agreeableness, conscientiousness, neuroticism and openness.

The five-factor structure has been extensively researched and offers a descriptive

model of personality. The model was developed using a lexicon approach in which

factor analysis was conducted on thousands of adjectives which were considered to be

representative of personality traits. The BFI (John et al., 1991) uses short phrases

based on the trait adjectives which are known to be prototypical markers of the five-

factor model of personality (John, 1989, 1990). Examples of the short phrasing can be

found in the following items from the instrument: These test items are not

available online. Please consult the hardcopy of the thesis available from the

QUT Library. Note. Copyright 1991 by O. P. John. Reprinted with permission.

Hence, the items from the BFI (John et al., 1991) retain the advantage of adjectival

items, such as brevity, and avoid some of their shortcomings, such as ambiguity.

106

The instrument is suitable for adults and may be self-administered either

individually or in groups. The BFI (John et al., 1991) may be administered by pencil

and paper or, with the permission of the authors, loaded onto a website and

administered by computer. The instrument takes only five minutes to complete and is

hand-scored. Test-takers address the statement “I see myself as someone who...” by

responding to 44 items using a five-point Likert-type response scale with responses

from “Disagree Strongly” to “Agree Strongly” (John et al., 1991).

Each scale consists of only eight to ten items. Benet-Martinez and John (1998,

p. 730) suggest that extraversion “summarises traits related to activity and energy,

dominance, sociability, expressiveness, and positive emotions”. Whereas,

agreeableness “contrasts a pro-social orientation toward others with antagonism and

includes traits such as altruism, tender mindedness, trust, and modesty” (Benet-

Martinez & John, 1998, p. 730). Benet-Martinez and John (1998, p. 730) state that

conscientiousness “describes socially prescribed impulse control that facilitates task-

and goal-directed behaviour”. Whereas, neuroticism is thought to “contrast emotional

stability with a broad range of negative affects, including anxiety, sadness, irritability,

and nervous tension” (Benet-Martinez & John, 1998, p. 730). Finally, openness

“describes the breadth, depth, and complexity of an individual's mental and

experiential life” (Benet-Martinez & John, 1998, p. 730).

Normative data for the BFI (John et al., 1991) is based on a sample of 711

people in the USA. In American and Canadian samples, the alpha reliabilities of the

scales range from .75 to .90, and average above .80. Three-month test-retest

reliabilities range from .80 to .90, with a mean of .85 which is impressive for a

relatively short measure (John & Srivastava, 1999). Evidence of validity includes

substantial convergent and divergent relations with other five-factor personality

107

instruments, as well as with peer ratings. Convergence between the BFI and the well

known NEO-FFI (Costa & McCrae, 1995) is substantial (mean corrected for

attenuation = .93) (John & Srivastava, 1999). Although the five-factor model is not

the only approach to personality, construct validity is considered to be high. Notably,

response bias controls are not included in the test. However, McCrae and Costa

(1983b, cited in Leong & Dollinger, 1991) argue that social desirability should be

viewed as a substantive trait rather than a response style needing to be controlled.

Overall, the BFI (John et al., 1991) is considered suitable for this project as it is

recommended as an instrument for assessing personality when the time available for

testing is limited and when information on global aspects of personality is required.

Wonderlic Personnel Test-Quicktest (WPT-Q)

The Wonderlic Personnel Test-Quicktest (WPT-Q) (Wonderlic, 2003) is a

short measure of cognitive ability, or GMA, which measures the level at which

individuals learn, understand instructions and solve problems. The first version of the

Wonderlic Personnel Test (WPT) was published in 1937 (Schraw, 2001) and was

designed for use in the selection of business personnel and for vocational guidance.

The instrument purports to measure how easily individuals can be trained, how well

they can adjust to and solve problems on the job, and how satisfied they are likely to

be by the demands of the job (Wonderlic, 1992). The WPT-Q (Wonderlic, 2003) is a

shorter version of the benchmark WPT (Wonderlic, 1992). The WPT-Q (Wonderlic,

2003) has an eight-minute time limit and consists of thirty multiple-choice items. The

instrument is only administered by computer and scoring is undertaken by the

publisher Wonderlic Inc..

The strength of the correlation between the two questionnaires enables

Wonderlic Inc. to accurately calculate test-takers‟ predicted WPT (Wonderlic, 1992)

108

scores based on their WPT-Q (Wonderlic, 2003) scores. Content includes items

related to: word comparison, disarranging sentences, sentence parallelism, number

comparison, number series and word problems requiring mathematical or logical

solution. The following two items are representative of those included in the WPT-Q

(Wonderlic, 2003):

These test items are not available online. Please consult the hardcopy of the

thesis available from the QUT Library.

(Wonderlic, 1992, cited in Chappell, 2006).

The WPT-Q (Wonderlic, 2003) raw score is converted to a WPT-Q adjusted

score using a regression equation. Then, the WPT-Q (Wonderlic, 2003) adjusted score

is used to predict a full WPT (Wonderlic, 1992) score (Anonymous, 2004). In a

sample of 201, the mean WPT (Wonderlic, 1992) score was 22.2 and 21.9 for the

WPT-Q (adjusted score) (Wonderlic, 2003).When both instruments are corrected for

unreliability, the corrected correlations approach a perfect 1.00, which suggests that

the two instruments are measuring the same underlying construct of cognitive ability

(Anonymous, 2004).

Based on a sample of 201, the reliability of the WPT-Q (Wonderlic, 2003) and

the WPT (Wonderlic, 1992) were found to be quite similar. The Cronbach Alpha

measure of internal consistency for the WPT (Wonderlic, 1992) was .85, and .81 for

the WPT-Q (Wonderlic, 2003) raw score (Anonymous, 2004).

As the WPT-Q (Wonderlic, 2003) is a relatively recent development of the

WPT (Wonderlic, 1992) validity and reliability data for the instrument is limited.

However, there is a substantial amount of psychometric data related to the WPT

109

(Wonderlic, 1992). Longitudinal reliability is estimated at .94 (Dodrill, 1983, cited in

Murphy, 1984). Overall, validity for the WPT (Wonderlic, 1992) is also acceptable.

Predictive validity coefficients are in the range of .22 to .67 (M = .39) across

occupations, with the higher correlations relating to managerial positions (Geisinger,

2001). The normative sample size (N = 370,000) is extremely large and includes data

from applicants for over 700 different occupations in more than 1,000 organisations

(Murphy, 1984). Overall, the brevity of the WPT-Q (Wonderlic, 2003) and its

similarity to the longer WPT (Wonderlic, 1992) make the WPT-Q (Wonderlic, 2003)

suitable for conceptualising GMA in this project.

Integrity Express

Integrity Express (Vangent, 2002a) is an overt integrity test designed to

measure attitudes towards dishonest behaviours and to predict overall job

performance. Integrity tests have previously been found to assess dependability and

conscientiousness, and to predict job performance (Ones et al., 1993; Schmidt &

Hunter, 1998). Although integrity is considered to be a very useful predictor of job

performance, little is known about its impact on leadership behaviours.

Overt integrity tests seek to uncover previous illegal activities (One et al.,

1993). Whereas, personality-based integrity tests measure the individual differences

which underlie counterproductive behaviors such as: substance abuse, absenteeism

and passive aggression. There is more convergence between personality-based

integrity tests and personality factors than there is between overt integrity tests and

personality factors (Ones et al., 1993). Therefore, as a personality measure will also

be included in this project, an overt measure of integrity has been selected.

The publisher of the instrument, Vangent Inc., offer the Integrity Express (Vangent,

2002a) scale as a shorter, alternative version of the integrity attitudes section of their

110

benchmark integrity test, The Reid Report (Vangent, 2002b). Integrity Express

(Vangent, 2002a) was created using the items from The Reid Report (Vangent,

2002b) that have proved to be the strongest predictors of employee theft and overall

job performance in previous validation studies. Hence, correlations between Integrity

Express (Vangent, 2002a) and the integrity attitudes section of The Reid Report

(Vangent, 2002b) are very high (r = .84) (Cunningham, 2007). Regarding reliability,

the internal consistency of Integrity Express (Vangent, 2002a) is considered to be

acceptable (.73) (Cunningham, 2007).

Integrity Express (Vangent, 2002a) is suitable for adults and may only be

administered by computer and scored by the publisher. Raw scores are converted into

percentiles by the publisher and forwarded to the test administrator. Raw scores are

also available for research purposes. Each percentile is based on the respondent‟s

score compared to the normative sample. The measure consists of 16 items and

responses are in the forced choice “yes” or “no” format (Vangent, 2002a). Three of

the items from the instrument are presented as examples below:

These test items are not available online. Please consult the hardcopy of the

thesis available from the QUT Library.

111

Note. Copyright 2002 by Vangent Inc. www.vangent.com. All Rights Reserved.

Reprinted with permission.

The overt nature of the instrument, its psychometric properties and its brevity

make Integrity Express (Vangent, 2002a) suitable for inclusion as a measure of

integrity in this project.

In summary, the instrument selected to test leadership styles and perceived

leadership outcomes was the MLQ5X (Avolio et al., 1995). EI was assessed using the

MSCEIT (Mayer et al., 2002). Personality factors were operationalised using The BFI

(John et al., 1991). GMA was tested using the WPT-Q (Wonderlic, 2003) and

integrity was assessed using Integrity Express (Vangent, 2002a). The instruments

were used in their standard „off-the-shelf‟ form as they would be by human resource

practitioners in the workplace. This will allow human resource practitioners who seek

to apply the findings of the project to use these tests without having to make any

modifications. As in previous studies in the field of EI and leadership a cross-

sectional design was used. The adequate reliability of the instruments selected makes

a cross-sectional design acceptable.

Results

Taking into account the relatively large number of variables that would have

been produced if the data for each MLQ scale (Avolio et al., 1995) had been analysed

at each of the four rating levels, using aggregated ratings for each scale was

considered to be preferable as it would result in a more parsimonious outcome. In

order to assess whether or not levels of interrater agreement for each of the MLQ

112

(Avolio et al., 1995) scales were sufficient to justify the aggregation of ratings rwg(j)

(James, Demaree, & Wolf, 1984) estimates were calculated. The rwg(j) (James et al.,

1984) assesses interrater agreement on a single target using multi-item rating scales.

The rwg(j) (James et al., 1984) has values ranging from .00 which denotes perfect lack

of agreement, to 1.00 which denotes perfect agreement. Aggregate scores from each

of the four raters were calculated for each item from each MLQ (Avolio et al., 1995)

scale. In accordance with the recommendations of James et al. (1984), negative values

and values exceeding 1.00 were considered to be the result of sampling error and were

reset to .00 to indicate a complete lack of agreement. The mean rwg(j) estimate for each

MLQ (Avolio et al., 1995) scale was used to assess whether or not ratings should be

aggregated. This replicates the method previously used by several researchers (e.g.,

Hoffman & Frost, 2006; Judge & Bono, 2000; Ostroff & Schmitt, 1993) who used the

mean rwg estimate to determine whether or not to aggregate ratings for leadership

scales. LeBreton and Senter (2008) advocate that even if a proportion of the rwg(j)

estimates fall below the cut-off it may still be justifiable to aggregate the data as

judgments should be made based on the pattern and magnitude of rwg(j) values.

Using the standards for interpreting interrater agreement estimates suggested

by LeBreton and Senter (2008), the mean rwg(j) estimates for each of the MLQ (Avolio

et al., 1995) scales, except management-by-exception active, demonstrated strong (.71

to .90) or very strong (.91 to 1.00) levels of interrater agreement. The mean rwg(j)

estimate for management-by-exception active was .50 which is lower than the .70 cut-

off used as a rule of thumb to justify the aggregation of ratings (LeBreton & Senter,

2008). Therefore, data for the management-by-exception active scale was not

aggregated in the Pilot Study. Rather, data was reported for each of the four rating

levels (self-ratings, supervisor ratings, peer ratings and follower ratings). The data for

113

all of the other MLQ (Avolio et al., 1995) scales was reported as the aggregate of

ratings across the four rating levels.

Data Screening

Data from the completed questionnaires was entered into SPSS Version 15

(SPSS, 2007) and checked for entry errors and omissions prior to analysis.

Scatterplots were generated in SPSS (2007) to check the linearity of each independent

variable with each of the dependent variables, and to assess levels of

homoscedasticity. Normality was assessed using boxplots generated by SPSS (2007)

for each variable. Each boxplot was screened for the presence of outliers. A score was

considered to be an outlier if it extended three box-lengths or more from the edge of

the box. Two outliers were detected. Both cases had extremely low scores on the

variable satisfaction (of followers). One of these two cases also had an extremely low

score on transformational leadership. These outliers were not part of the population of

interest. Therefore, these two outliers were deleted in order to make the distribution of

transformational leadership and satisfaction (of followers) normal. Twenty five cases

remained (fifteen females and ten males). All of the other variables in the Pilot Study

were normally distributed and achieved the significance value of > .05 for the

Kolmogorow-Smirnov statistic for normality of distribution. No problems were found

with the independence of residuals. There were no cases with missing data.

Descriptive Statistics

The descriptive statistics for the Pilot Study variables are presented in Table

10.

114

Table 10

Descriptive Statistics for Pilot Study Variables

Variable Mean Standard

deviation

Minimum Maximum Range Cronbach‟s

alpha

rwg(j) Sample

size

Age 43.28 7.61 26.00 57.00 31.00 25

Total EI 102.29 10.44 78.76 130.04 51.28 25

Experiential EI 100.32 14.12 75.87 129.39 53.52 25

Strategic EI 102.71 7.80 86.36 116.40 30.04 25

Perceiving emotions 100.91 17.32 70.45 132.28 61.83 25

Understanding emotions 101.48 9.59 80.65 118.35 37.67 25

Managing emotions 101.96 7.51 87.83 115.44 27.61 25

Using emotions 101.34 11.89 82.04 128.49 46.45 25

Openness 4.08 .61 2.70 4.80 2.10 .83 25

Neuroticism 2.64 .96 1.00 4.63 3.63 .91 25

Extraversion 3.57 .82 2.25 5.00 2.75 .86 25

Conscientiousness 4.35 .57 2.89 5.00 2.11 .82 25

Agreeableness 4.02 .71 2.56 5.00 2.44 .87 25

GMA 25.88 3.82 13.00 31.00 18.00 25

Integrity 12.08 2.29 6.00 16.00 10.00 25

Transformational leadershipa 3.28 .22 2.77 3.64 .87 .87 .98 100

Idealised attributesb 3.32 .26 2.75 3.81 1.06 .58 .91 100

Idealised behavioursb 3.30 .24 2.81 3.75 .94 .36 .90 100

Inspirational motivationb 3.27 .38 2.38 3.88 1.50 .86 .90 100

Intellectual stimulationb 3.14 .35 2.42 3.75 1.33 .80 .89 100

Individualised considerationb 3.40 .25 2.75 3.88 1.13 .47 .84 100

Contingent rewardb 3.29 .39 1.96 3.88 1.92 .59 .84 100

Management-by-exception active self-

ratings

1.70 .89 .00 3.25 3.25 .82 25

Management-by-exception active

supervisor ratings 1.70 1.14 .00 3.67 3.67 .82 25

Management-by-exception active peer

ratings

1.92 .93 .00 3.50 3.50 .80 25


follower ratings

1.70 .88 .00 3.00 3.00 .61 25

Passive/avoidant leadershipc .46 .16 .16 .73 .57 .13 .92 100

Management-by-exception passiveb .55 .25 .08 1.13 1.04 .28 .80 100

Laissez-faireb .36 .23 .00 .88 .88 .52 .83 100

Satisfaction (of followers)b 3.58 .27 2.88 4.00 1.13 .64 .85 100

Effectiveness (of individual/group)b 3.51 .23 3.00 3.88 .88 .57 .91 100

Extra effort (of followers)b 2.95 .30 2.17 3.50 1.33 .29 .74 100

aAll four rating levels and the five transformational scales combined. bAll four rating levels combined. cAll four rating levels and the two passive/avoidant scales combined.

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Bivariate Analysis

Correlation analysis was used to examine linear relationships between the

variables of interest in the study. Descriptions of correlations were based on the

guidelines suggested by Cohen and Cohen (1983). According to these guidelines

effect sizes for correlations are as follows: r = .10 (classified as weak), r = .30

(classified as moderate), and r = > .50 (classified as strong). Two-tailed tests were

used in this and all subsequent analyses.

Tests were undertaken to check that the assumptions of the correlation

procedure had not been breached regarding: normality, linearity, homoscedasticity,

minimal measurement error and unrestricted variance. A correlation matrix was

formulated and scatterplots were generated in SPSS (2007) to assess whether scores

on pairs of variables co-varied. Pearson product moment correlation coefficients were

computed using SPSS (2007). The strength of the relationship varies from 1 (perfect

linear relationship) to -1 (perfect negative linear relationship) and is interpreted as the

percentage of variance explained. The significance of each relationship was also

computed by SPSS (2007). Regarding difference between the means procedures the

effect size, or proportion of variance in the dependent variable explained by the

independent variable, was determined by Eta squared using the guidelines proposed

by Cohen (1988): .01 = small effect, .06 = moderate effect, .14 = large effect. The

inter-correlations for the variables in the Pilot Study are presented in Table 11.

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Table 11

Inter-correlations between Pilot Study Variables

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

1. Total EIa - .52** .90** .41* .37 .65** .81** .07 -.35 .37 .23 .22 .38 .00 .42* .16 -.28 -.07 .08

2. Strategic EIa - .10 .72** .71** .24 .04 -.19 -.47* .36 .03 .27 .23 .12 .12 .06 -.38 -.14 -.20

3. Experiential EIa - .12 .08 .63** .93** .18 -.18 .26 .25 .12 .33 -.12 .43* .15 -.11 -.02 .14

4. Managing emotionsa - .05 .37 .02 .05 -.60** .54** .24 .48* -.17 .15 .52** .26 -.43* -.40* -.28

5. Understanding emotionsa - .01 .08 -.33 -.03 -.01 -.18 -.13 .48* -.02 -.34 -.13 -.13 .21 -.01

6. Using emotionsa - .33 .38 -.31 .32 .14 .33 .05 -.23 .39 .26 -.23 -.27 -.19

7. Perceiving emotionsa - .05 -.13 .17 .27 .02 .34 -.06 .40* .09 -.03 .05 .20

8. Opennessa - .04 -.19 .03 .16 -.19 .22 .15 .38 .33 .12 .17

9. Neuroticisma - -.58** -.29 -.78** .11 .01 -.54** .15 .53** .20 .47*

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Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

10. Extraversiona - .33 .47* .01 -.27 .31 -.22 -.52** -.10 -.47*

11. Conscientiousnessa - .38 -.07 .30 .22 .05 .08 -.17 -.13

12. Agreeablenessa - -.24 .10 .35 .05 -.43* -.08 -.32

13. GMAa - .07 -.16 -.11 .03 -.01 .39

14. Integritya - -.04 .17 .27 .15 .33

15. Transformational

leadershipb

- .37 -.32 -.44** -.19

16. Contingent rewardb - .07 -.05 .16

17. Management-by-exception

active self-ratings

- .14 .34


active supervisor ratings

- .03


active peer ratings

-

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Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19


active follower ratings

21. Passive/avoidant

leadershipb

22. Satisfaction (of followers)b

23. Effectiveness (of

individual/group)b

24. Extra effort (of followers)b

25. Idealised attributesb

26. Idealised behavioursb

27. Inspirational motivationb

28. Intellectual stimulationb

29. Individualised

considerationb

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Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19


passiveb

31. Laissez-faireb

aN = 25. bN = 100.

* < .05 level, two-tailed. ** < .01 level, two-tailed.

120

Variable 20 21 22 23 24 25 26 27 28 29 30 31

1. Total EIa -.15 -.34 .28 .12 .11 .38 .22 .39 .22 .37 .00 -.47*

2. Strategic EIa -.09 -.15 -.06 -.12 -.02 .04 -.07 .25 .02 .11 -.02 -.19

3. Experiential EIa -.17 -.28 .29 .17 .16 .42* .31 .35 .24 .36 .06 -.45*

4. Managing emotionsa .20 -.25 .17 .17 .30 .33 .43* .68** .13 .36 -.08 -.26

5. Understanding emotionsa -.34 -.03 -.25 -.30 -.27 -.25 -.52** -.31 -.12 -.19 -.01 -.03

6. Using emotionsa -.08 -.15 .24 .06 .21 .35 .54* .39 .15 .19 .19 -.42*

7. Perceiving emotionsa -.15 -.30 .26 .19 .14 .40* .22 .33 .24 .35 -.05 -.36

8. Opennessa .09 .03 .06 .13 .25 -.11 .29 .13 .27 -.03 .09 -.05

9. Neuroticisma .01 .06 -.32 -.23 -.06 -.41* -.36 -.68** -.14 -.39 -.04 .13

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Variable 20 21 22 23 24 25 26 27 28 29 30 31

10. Extraversiona .09 -.03 .12 .37 .17 .26 .28 .52** -.08 .15 -.07 .04

11. Conscientiousnessa .25 -.37 .23 .55** .32 .24 .12 .48* -.16 .13 -.07 -.44*

12. Agreeablenessa -.15 -.01 .30 .21 .03 .13 .33 .50* .01 .33 .18 -.22

13. GMAa .12 .02 -.08 .02 -.25 .01 -.29 -.16 .04 -.24 .14 -.12

14. Integritya .57** -.10 -.15 .12 .03 -.26 -.18 -.03 .12 .14 -.05 -.08

15. Transformational leadershipb .17 -.58** .71** .55** .42* .80** .77** .79** .71** .73** -.34 -.43*

16. Contingent rewardb .07 -.51** .38 .30 .50* .16 .36 .29 .37 .22 -.20 -.49*


active self-ratings

.24 .18 -.26 -.05 .23 -.25 -.24 -.31 -.11 -.27 .30 -.08


active supervisor ratings

-.23 .37 -.29 -.21 -.30 -.58** -.28 -.41* -.19 -.28 .12 .37


active peer ratings

.14 .01 -.29 -.17 .00 -.10 -.21 -.41* .00 .06 .02 -.01

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Variable 20 21 22 23 24 25 26 27 28 29 30 31


active follower ratings

- -.02 -.14 .42* .31 .06 .16 .25 .14 .01 -.18 .17

21. Passive/avoidant leadershipb - -.61** -.59** -.38 -.54** -.17 -.39 -.53** -.49* .70** .61**

22. Satisfaction (of followers)b - .52** .21 .74** .44* .50* .60** .41* -.18 -.64**


individual/group)b

- .39 .44* .37 .60** .34 .28 -.51** -.25

24. Extra effort (of followers)b - .33 .29 .37 .27 .32 -.18 -.33

25. Idealised attributesb - .54** .62** .45* .46* -.22 -.52**

26. Idealised behaviours - .69** .38 .39 -.44 -.19

27. Inspirational motivationb - .26 .41* -.18 -.35

28. Intellectual stimulationb - .59** -.44* -.25

29. Individualised considerationb - -.32 -.33

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Variable 20 21 22 23 24 25 26 27 28 29 30 31


passiveb

- -.13

31. Laissez-faireb -

124

The results of the research questions and hypotheses tested in the Pilot Study

are presented below:

Hypothesis 1. EI will have discriminant validity from GMA.

GMA only had one significant correlation with any of the EI variables in the

Pilot Study and that was with the understanding emotions branch of EI (.48, p = <

.05). As this was the only relationship, and it was only moderate in size, EI was

considered to have discriminant validity from GMA.

Hypothesis 2. EI will have discriminant validity from personality factors

(neuroticism, extraversion, openness, conscientiousness and agreeableness).

Total EI was not significantly correlated with any of the five personality

factors. The managing emotion branch of EI was significantly correlated with three of

the five personality factors, specifically: agreeableness (.48, p = < .05), extraversion

(.54, p = < .01) and inversely with neuroticism (-.60, p = < .01). Neuroticism was also

negatively correlated with the strategic area of EI (-.47, p = < .05). As the strongest

correlation was only .60 (p = < .01), EI was considered to have adequate discriminant

validity from personality factors in the Pilot Study.


males.

An independent samples t-test was undertaken to test the hypothesis that

women (M = 103.32, SD = 10.30, n = 15) would have higher scores of total EI than

men (M = 100.75, SD = 11.01, n = 10). Gender was the independent variable (with

two levels: male and female) and total EI score was the dependent variable. Equal

variances assumed statistics are reported as Levene‟s test for equality of variances

was larger than .05. The test was not significant t(23) = .60, p = .56. Therefore, scores

for Total EI were not significantly different for males and females in the Pilot Study.

125

The mean difference was 2.58 with a 95% confidence interval ranging from -6.36 to

11.52. The magnitude of the differences in the means was small (Eta squared = .02).


for females than for males.

In order to examine the mean differences between males (M = 3.28, SD = .17,

n = 10) and females (M = 3.29, SD = .26, n = 15) on scores of transformational

leadership, an independent samples t-test was conducted to test the hypothesis that

women are more transformational as leaders than men. Gender was the independent

variable (with two levels: male and female) and transformational leadership scores

(all raters combined) was the dependent variable. As Levene‟s test for equality of

variances was larger than .05 the assumption of equal variances was not violated.

Therefore, equal variances assumed statistics are reported. The test was not significant

t(23) = .15, p = .88 (two-tailed). Therefore, scores of transformational leadership were

not significantly different for males and females in the Pilot Study. The mean

difference was .01 with a 95% confidence interval ranging from -.18 to .21. The

magnitude of the differences in the means was very small (Eta squared = .00).


between EI and transformational leadership.

Transformational leadership was strongly related to the managing emotions

(.52, p = < .01) branch of EI. Moderate correlations were found between

transformational leadership and several of the EI variables, notably; total EI (.42, p =

< .05), the experiential area (.43, p = < .05) and the perceiving emotions branch (.40,

p = < .05). Therefore, total EI, the experiential area, and the managing emotions and

perceiving emotions branches of EI were found to be positively related to

transformational leadership. No significant correlations were found between

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transformational leadership and the strategic area, or the understanding emotions and

facilitating thought branches of EI.


between EI and perceived leadership outcomes (satisfaction, extra effort and

effectiveness).

None of the EI variables were significantly correlated with any of the

perceived leadership outcomes variables (satisfaction, effectiveness and extra effort).

Hence, EI was not found to be positively related to perceived leadership outcomes in

the Pilot Study.

Research question 3. Investigate whether there is a relationship between EI

and transactional leadership (contingent reward and management-by-exception

active).

The contingent reward scale of transactional leadership was not significantly

correlated with any of the EI variables. As the rwg(j) value for combined ratings of the

management-by-exception active scale was only .50 (below the .70 cut-off) results are

reported for ratings of the scale at each of the four rating levels. Self-ratings (-.43, p =

< .05) and supervisor ratings (-.40, p = < .05) of management-by-exception active

shared moderate inverse correlations with the managing emotions branch of EI. Peer

and subordinate ratings of management-by-exception active were not significantly

correlated with any of the EI variables.

Research question 4. Investigate whether there is a negative relationship

between EI and passive/avoidant leadership.

Passive/avoidant leadership was not significantly correlated with any of the EI

variables. Hence, EI was not found to be negatively related to passive/avoidant

leadership.

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Integrity was not significantly correlated with any of the five personality

factors. Therefore, integrity demonstrated discriminant validity from personality

factors.

Discussion

The Pilot Study was undertaken to commence the investigation of the

question: to what extent is the Mayer and Salovey (1997) model of EI a useful

predictor of leadership style and leadership outcomes? The Pilot Study presented an

opportunity to: examine the relationship between EI and leadership style and EI and

perceived leadership outcomes, assess the methodology selected for the project and

ascertain whether further investigation was warranted. The impact of gender was also

examined. The nine per cent response rate from the leaders invited to participate in

the Pilot Study was low. Follow up enquiries revealed that some of the university

leaders were concerned that if their anonymity was ever compromised their responses

to some of the controversial items in the integrity questionnaire and their scores from

the GMA questionnaire could have a negative impact on their employment prospects

at the university. Some of those invited to participate found the idea of undertaking a

test of GMA to be too confronting. Several of the leaders contacted also indicated that

they were invited to participate in too many research projects and could not

participate in them all. Hence, the reluctance of some unit coordinators and course

coordinators to participate in the study. Therefore, participants for the Main Study in

the project would be recruited from outside this university.

Several technical problems were encountered by participants whilst accessing

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the online questionnaires. As a result of copyright restrictions, the WPT-Q

(Wonderlic, 2003), MLQ5X (Avolio et al., 1995), MSCEIT (Mayer et al., 2002) and

Integrity Express (Vangent, 2002a) could only be completed by accessing secure

websites administered by the publisher of each instrument. The BFI (John et al., 1991)

was loaded onto an online platform created by technical support staff at QUT.

Consequently, participants were required to access and log into five different websites

to complete the participation process. Whilst efforts were made to keep the process as

simple as possible, difficulties were experienced by several participants. Some leaders

encountered problems when attempting to access the various publishers‟ websites.

Most of the issues related to these problems were resolved during the Pilot Study and

no participants withdrew as a result of experiencing technical difficulties. The

individual codes used by participants to maintain their confidentiality worked well

and no problems were reported regarding their use.

Generally, participants were able to complete all of the questionnaires in less

than one hour and thirty minutes although many elected to complete the

questionnaires in more than one session. Raters were able to complete their ratings of

the leader in 15 to 30 minutes depending on how much time they spent answering the

optional qualitative questions. No participants withdrew as a result of the demands on

their time. This alleviated prior concerns that participants may find that the time

required to complete the questionnaires was too long.

Further concerns regarding the intrusive nature of some of the items included

in the integrity questionnaire were alleviated as all participants completed the

questionnaire and no negative feedback was received regarding its content. Therefore,

the same questionnaires were considered suitable for use in a further study. Although

participants were requested to complete the questionnaires within a two-week time-

129

frame, several participants did not complete the task within this period and were sent

reminder notices by email. These participants were provided with additional time to

complete the questionnaires.

On completion of the questionnaires, all participants requested feedback.

Hence, feedback was considered to be an effective incentive to obtain participants for

the study. As it was noted that some individual scores from the GMA and integrity

questionnaires were extremely low, scores from these two questionnaires were only

provided to each leader following specific requests. Hence, leaders who had obtained

exceptionally low scores on these measures would not be disappointed by knowing

their results and their experience of participating in the study would not be tarnished.

Regarding the results of the Pilot Study, several of the EI variables were

positively related to transformational leadership. This was an encouraging finding and

was in-line with the findings of Leban (2003). However, taking into account the

strong relationship between transformational leadership and the perceived leadership

outcomes variables (satisfaction, effectiveness and extra effort) it was surprising to

find that none of the EI variables were significantly correlated with any of these

variables. These relationships warranted further examination.

The contingent reward scale of transactional leadership was not related to EI.

Self-ratings and supervisor ratings of the management-by-exception active scale of

transactional leadership were inversely related to the managing emotions branch of

EI, but peer and subordinate ratings were not related to any of the EI variables.

Differences based on the ratings levels for the management-by-exception active scale

were to be expected taking into account the moderate level of interrater agreement for

the scale (rwg[j] = .50).

Integrity demonstrated discriminant validity from the five factors of

130

personality. Hence, Integrity Express (Vangent, 2002a) would be suitable for use in a

further study. Taking into account the findings of Van Rooy and Viswesvaran (2004),

it was expected that GMA would be related to EI. However, GMA was not related to

EI or personality factors in the Pilot Study.

No differences were found between scores of transformational leadership for

males and females. This differed from the findings of Bass and Avolio (1994), Bass et

al. (1996) and Eagly et al. (2003). Also, no differences were found for scores of EI

between males and females. This differed from the findings of Mandell (2003), Mayer

and Geher (1996), Mayer, Caruso and Salovey, (1999) and Mayer et al. (2004). It is

possible that the number of participants in the Pilot Study was too small to accurately

test the hypotheses related to gender and that these hypotheses needed to be tested

again in a further study using a larger sample.

As the sample size was only 25 it was not possible to undertake multivariate

analysis. Even the results of the bivariate analysis undertaken in the Pilot Study must

be interpreted with caution in view of the limitations imposed by the small sample

size. However, the results of the Pilot Study indicated that a further study was

warranted to examine the relationship between EI, leadership style and perceived

leadership outcomes in Australian schools.

Conclusion

A Pilot Study was undertaken to make a preliminary examination of the

relationship between EI and leadership style, and EI and perceived leadership

outcomes. Additionally, the impact of gender on the variables of interest was

examined. The results of correlation analysis indicated that total EI, the experiential

area, and the managing emotions and perceiving emotions branches were found to be

positively related to transformational leadership. None of the EI variables were related

131

to any of the perceived leadership outcomes variables. Self-ratings and supervisor

ratings of the management-by-exception active scale of transactional leadership scale

were inversely related to the managing emotions branch of EI. It was noted that as the

sample for the Pilot Study only consisted of 25 leaders, the results must be interpreted

with much caution in view of the limitations imposed by the small sample size.

Following an assessment of the methodology used in the Pilot Study the procedure

and instruments used were considered suitable for use in a further study. Minor

modifications would be made to the online testing platforms to simplify the test taking

process for participants.

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Chapter 5: Main Study - Descriptive and Measurement Component

Introduction

This chapter presents the descriptive and measurement component of the Main

Study in this project (the inferential component of the Main Study is presented in

Chapter 6). Initially, the independent and dependent variables examined in the Main

Study are presented, followed by the specific research questions and hypotheses used

to test the relationships between the variables of interest. The discriminant validity of

the instruments selected is tested, and the impact of role and gender on leadership

style and EI are examined. The methodology for the Main Study is outlined with

regard to the procedure, participants and instruments selected to operationalise the

conceptual variables. The final sample consisted of 144 educational leaders (52 male

and 92 female) and 432 nominated peers, followers and supervisors. Methods for data

entry using SPSS version 15.0 (SPSS, 2007) and the data screening process are

described. Then, descriptive statistics are presented followed by the results of

correlation and difference between the means procedures undertaken. Finally, the

results from the descriptive and measurement component of the Main Study are

discussed and the methodology is assessed.


In the Main Study, the following independent variables were measured and

their effect on the dependent variables was measured: total EI, strategic EI,

experiential EI, perceiving emotions, using emotions, understanding emotions,

managing emotions, general mental ability, neuroticism, extraversion, openness,

conscientiousness, agreeableness and integrity.



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Research Questions and Hypotheses

Taking into account the findings from previous studies it is predicted that

support will be found for the following hypotheses which will be tested in the Main

Study:

Hypothesis 1. Total EI will have discriminant validity from GMA (Refer to

Van Rooy & Viswesvaran, 2004).

Hypothesis 2. Total EI will have discriminant validity from personality factors

(neuroticism, extraversion, openness, conscientiousness and agreeableness)

(Refer to Van Rooy & Viswesvaran, 2004).


males (Refer to Mayer & Geher, 1996; Mayer, Caruso, & Salovey, 1999;

Mayer et al., 2004).


for females than for males (Refer to Bass & Avolio, 1994; Bass et al., 1996;


Hypothesis 5. Scores for the contingent reward scale of transactional

leadership will be significantly higher for females than for males (Refer to


Hypothesis 6. Scores for the management-by-exception active scale of

transactional leadership will be significantly higher for males than for females

(Refer to Eagly et al., 2003).

Hypothesis 7. Passive/avoidant leadership scores will be significantly higher

134

for males than for females (Refer to Eagly et al., 2003).

As there is insufficient literature in some areas of interest to develop specific

hypotheses the following research questions have been formulated for the descriptive

and measurement component of the Main Study:

Research question 1. Investigate whether scores of transformational leadership

vary according to the role of the leader (principal, vice-principal, head of

department, tertiary coordinator and administrator).

Research question 2. Investigate whether scores of total EI vary according to

the role of the leader (principal, vice-principal, head of department, tertiary

coordinator and administrator).




Methodology


In order to obtain participants for the Main Study, project information was

emailed to the Australian Council of Educational Leaders (ACEL) with a request to

forward it to all members. Subsequently, 260 expressions of interest were received

from members of ACEL regarding participation in the study. The majority of those

interested in participating were principals or vice-principals currently working in

Australian schools. Therefore, in order to maximise the validity of the sample, a

decision was made to only select principals and vice-principals located in Australia as

participants for the study. Details of how to participate in the study were sent to the

selected leaders by email (Refer to Appendix B).

One leader withdrew from the study as his computer did not have the software

135

required to complete the questionnaires. Another leader withdrew from the study as

he did not support the face validity of the MSCEIT (Mayer et al., 2002) items. Three

other leaders withdrew without explanation. Consequently, 43 men and 77 women (N

= 120) completed the participation task as leaders.

Participants were requested to complete the questionnaires online within a

two-week period. Those who had not completed the task by the end of this period

were sent a reminder by email and offered more time to complete the questionnaires.

The BFI (John et al., 1991) and MLQ5X (Avolio et al., 1995) were accessed via a

website set up by QUT, whilst the WPT-Q (Wonderlic, 2003), the MSCEIT (Mayer et

al., 2002) and Integrity Express (Vangent, 2002a) were accessed via the test

publishers‟ websites. Additionally, online leadership ratings were provided by one

supervisor, one peer and one follower nominated by each leader (Refer to Appendix

C). Each participant was provided with an individual code which was used as a form

of identity during the study. Each code consisted of three letters and two numbers

(e.g., bkm41). The first two letters represented the initials of the participant whilst the

third letter represented gender; „m‟ for male or „f „for female. The two numbers were

the age in years of the participant.

In return for participating in the study, leaders were offered feedback related

to their test scores from The BFI (John et al., 1991), the MLQ (Avolio et al., 1995)

and the MSCEIT (Mayer et al., 2002). Raters‟ responses to the qualitative items from

the MLQ (Avolio et al., 1995) were also provided.

Instruments

The instruments used in the Main Study were the same as those used in the

Pilot Study. The conceptual variables were operationalised using online tests. The

instrument selected to test leadership styles and perceived leadership outcomes was

136

the MLQ5X (Avolio et al., 1995). EI was assessed using the MSCEIT (Mayer et al.,

2002). Personality factors were operationalised using The BFI (John et al., 1991).

GMA was tested using the WPT-Q (Wonderlic, 2003) and integrity was assessed by

Integrity Express (Vangent, 2002a).

Results

Data entry and analysis was conducted using SPSS version 15.0 (SPSS, 2007).

Initially, an independent samples t-test was undertaken to examine the mean

differences for scores of transformational leadership between the Pilot Study sample

(M = 3.23, SD = .30, N = 27) and the sample obtained for the Main Study (M = 3.25,

SD = .30, N = 120). Participants was the independent variable (with two levels: Pilot

Study and Main Study) and transformational leadership was the dependent variable.

As the Levene‟s test for equality of variances was above .05 the equal variance

assumes statistics are reported. The test was not significant t(147) = .45, p = .66 (two-

tailed). The mean difference was .03 with a 95% confidence interval for the difference

in means ranging from -.10 to .16. The magnitude of the differences in the means was

very small (Eta squared = .00). As the scores were not significantly different for the

two samples, a decision was made to combine both samples to form one larger sample

(N = 147) in order to increase the power and validity of the Main Study.

As a relatively large number of variables would have been produced if the data

for each MLQ scale (Avolio et al., 1995) had been analysed at each of the four rating

levels, using aggregated ratings for each scale was considered to be preferable as it

would result in a more parsimonious outcome. In order to assess whether or not levels

of interrater agreement for each of the MLQ (Avolio et al., 1995) scales were

sufficient to justify the aggregation of ratings rwg(j) (James et al., 1984) estimates were

calculated. Aggregate scores from each of the four raters were calculated for each

137

item from each MLQ (Avolio et al., 1995) scale. In accordance with the

recommendations of James et al. (1984), negative values and values exceeding 1.00

were considered to be the result of sampling error and were reset to .00 to indicate a

complete lack of agreement. The mean rwg(j) estimate for each scale was used to assess

whether or not ratings should be aggregated. Using the standards for interpreting

interrater agreement estimates suggested by LeBreton and Senter (2008), the mean

rwg(j) estimates for each of the MLQ (Avolio et al., 1995) scales, except management-

by-exception active, demonstrated strong (.71 to .90) or very strong (.91 to 1.00)

levels of interrater agreement. The mean rwg(j) estimate for management-by-exception

active was .56 which is lower than the .70 cut-off often used to justify the aggregation

of ratings (LeBreton & Senter, 2008). Therefore, data for the management-by-

exception active scale was not aggregated in the Main Study. Rather, data was

reported for each of the four rating levels (self-ratings, supervisor ratings, peer ratings

and follower ratings) for this scale. The data for all of the other MLQ (Avolio et al.,

1995) scales was reported as the aggregate of ratings across the four rating levels.

Factor analysis was not undertaken on the tests used in the Main Study for

several reasons. Firstly, the data required to undertake factor analysis on the WPT-Q

(Wonderlic, 2003) and Integrity Express (Vangent, 2002) was not available. In both

cases, the items and the responses made by participants were retained by the test

publishers and were not made available for analysis.

Secondly, taking into account the number of items in the MSCEIT (Mayer et

al., 2002) (144 items), the BFI (John et al., 1991) (44 items) and the MLQ (Avolio et

al., 1995) (45 items), the sample size of 144 in the Main Study was considered to be

too small to undertake factor analysis. There are several rules of thumb regarding the

138

sample size required for factor analysis which refer to either the minimum number of

respondents or the ratio of the sample size to the number of items (MacCallum,

Widaman, Zhang, & Hong, 1999). Gorsuch (1983) recommended a minimum of five

respondents per item, whereas Cattell (1978) recommended 3 to 6 respondents per

item with a sample size of at least 250. Guilford (1954) proposed that the sample size

for factor analysis should be at least 200. Alternatively, Comrey and Lee (1992)

described a sample size of 100 as poor, 200 as fair, 300 as good, 500 as very good and

more than 1,000 as excellent. Everitt (1975) recommended a minimum of 10

respondents per item, whereas Cureton and D‟Agostino (1983), and Tabachnick and

Fidell (2007) suggest that a sample for factor analysis should consist of several

hundred respondents. Costello and Osborne (2005) tested the effect of sample size on

the results of factor analysis and reported that larger samples produced more accurate

results. Taking into account these recommendations, the sample size in the Main

Study of this project was not large enough to undertake factor analysis. There are

several problems which may be encountered as a result of using small samples for

factor analysis. Various forms of sampling error can result in the emergence of factors

that are specific to the individual data set. Factors which may not be replicated can

occur as a result of unique patterns of responding to a single item. Hence, the extent to

which the data is representative of a larger population may be limited and factor

structures which may not be replicated can be generated. Additionally, small samples

may result in the breaking-up of factors into smaller groupings of items that are really

representative of a larger factor (MacCallum et al., 1999).

A third reason for not undertaking factor analysis is related to the envisaged

contribution of the project to human resource practitioners. One of the aims of the

project is to examine the relationships between the variables of interest using readily

139

available tests in their standard „off-the-shelf form‟ as would be used by human

resource practitioners in the workplace. Hence, if the outcome of factor analysis

suggested that alterations to the tests should be made, such as changes to the factor

structure or the removal of items, the tests would no longer be in their standard form

and this would not be congruent with the aims of the project as it is unlikely that

human resource practitioners would conduct factor analysis prior to using these tests.

Finally, the factor structure of each of these tests is reasonably well

established. This is one explanation why factor analysis has not always been

conducted on these tests in previous research. For example, in a study which used the

MLQ (Avolio et al., 1995), Parry and Proctor-Thomson (2003) asserted that “factor

analysis was not conducted on the MLQ because its factor structure has been

confirmed many times since its inception in 1985.” Consequently, factor analysis was

not undertaken in this project.

Aggregate scores were calculated for the five transformational scales of the

MLQ (Avolio et al., 1995) and the two passive/avoidant scales. The two transactional

scales, contingent reward and management-by-exception active, were analysed

separately. The structure selected to represent the MLQ (Avolio et al., 1995) in the

Main Study of this project is in-line with the recommendations made in a personal

email from the co-author of the test B. J. Avolio (personal communication, April 11,

2010).

Data Screening

Data from the completed questionnaires was entered into SPSS (2007) and

checked for entry errors and omissions. Scatterplots were generated in SPSS (2007) to

check the linearity of each independent variable with each of the dependent variables,

and to assess levels of homoscedasticity. Tabachnick and Fidel (2007) argue that tests

140

used to evaluate skewness and kurtosis are too sensitive with large samples and

recommend that the shape of the distribution is inspected instead. Therefore, the shape

of the distribution of each variable was assessed for normality using histograms

generated in SPSS (2007) instead of formal inference tests.

Initially, several variables were transformed in an attempt to improve

normality. Transformational leadership, passive/avoidant leadership, extra effort (of

followers) and agreeableness all underwent natural square root transformations.

Conscientiousness underwent a reverse square root transformation. However, the

negatively skewed distribution of conscientiousness was considered to be

representative of the fact that the sample consisted of educators and as such they were

likely to be a highly conscientious group. Neuroticism underwent a logarithmic

transformation. As all of the transformations only achieved minor improvements in

the normality and linearity of the variables, a decision was made to proceed using the

untransformed variables. Normality was also assessed using boxplots generated by

SPSS (2007). Each boxplot was screened for the presence of outliers. A score was

considered to be an outlier if it extended three box-lengths or more from the edge of

the box. A total of five univariate outliers were detected. Three cases had extremely

low scores for transformational leadership. One of these three cases also had an

extremely high score for passive/avoidant leadership. These three outliers were

deleted as they were contributing to the non-normality of the distribution of

transformational leadership and passive/avoidant leadership. One hundred and forty

four cases remained in the Main Study. One outlier for integrity was retained as its

deletion did not considerably improve the distribution of the variable and increased

the level of kurtosis. Although several of the variables were still slightly skewed, the

normality of distribution was considered to be adequate to undertake bivariate

141

analysis as Tabachnik and Fidel (2007) suggest that skewness does not make a

substantive difference to the analysis when a reasonably large sample is used. No

problems were found with the independence of residuals.

There were several cases with missing data. Several participants missed items

on the scales of the MLQ (Avolio et al., 1995). Due to the small amount of missing

data it was not considered necessary to remove these cases from the analysis. In

calculating the scale scores for each measure, missing data was handled in accordance

with the instructions of the test publisher. One participant missed more items on the

MSCEIT (Mayer et al., 2002) than the test publisher permits. Therefore, this

participant re-took the whole test in order to continue to be involved.

The final sample for the Main Study consisted of 144 leaders and 432 raters.

More specifically, the sample consisted of 66 principals, 51 vice-principals and 10

heads of departments employed in Australian schools. Twelve course and unit

coordinators employed at an Australian university and five Department of Education

and Training administrators from Queensland were also included in the sample.


The descriptive statistics for the Main Study variables are presented in Table

12.

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Table 12

Descriptive Statistics for Main Study Variables

Variable Mean Standard

deviation

Minimum Maximum Range Cronbach‟s

alpha

rwg(j) Sample

size

Age 46.93 7.14 26.00 62.00 36.00 144

Total EI 101.61 11.16 69.03 130.04 61.01 144

Experiential EI 101.55 14.43 65.54 130.32 64.78 144

Strategic EI 100.49 7.79 78.81 116.40 37.59 144

Perceiving emotions 101.86 15.62 61.44 135.43 73.99 144

Understanding emotions 99.43 9.77 74.25 118.35 44.10 144

Managing emotions 100.30 7.81 72.96 115.44 42.48 144

Using emotions 101.25 12.61 69.49 128.49 59.00 144

Openness 4.08 .53 2.70 5.00 2.30 .76 144

Neuroticism 2.35 .80 1.00 4.63 3.63 .85 144

Extraversion 3.85 .74 2.25 5.00 2.75 .84 144

Conscientiousness 4.47 .52 2.56 5.00 2.44 .83 144

Agreeableness 4.26 .58 2.56 5.00 2.44 .79 144

GMA 25.81 3.76 13.00 33.00 20.00 144

Integrity 12.57 2.16 6.00 17.00 11.00 144

Transformational leadershipa 3.27 .27 2.34 3.80 1.46 .90 .98 576

Idealised attributesb 3.28 .30 2.44 3.88 1.44 .61 .87 576

Idealised behavioursb 3.39 .30 2.40 3.94 1.54 .68 .91 576

Inspirational motivationb 3.39 .36 2.31 4.00 1.69 .83 .92 576

Intellectual stimulationb 3.07 .36 1.81 2.06 3.88 .81 .88 576

Individualised considerationb 3.21 .32 1.88 2.00 3.88 .53 .82 576

Contingent rewardb 3.13 .36 1.96 3.88 1.92 .67 .82 576

Management-by-exception active self-

ratings

1.44 .76 .00 3.25 3.25 .71 144


supervisor ratings 1.86 .93 .00 4.00 4.00 .68 144

Management-by-exception active peer

ratings

1.79 .96 .00 4.00 4.00 .75 144


follower ratings

1.56 .91 .00 3.75 3.75 .63 144

Passive/avoidant leadershipc .53 .24 .09 1.34 1.25 .63 .92 576

Management-by-exception passiveb .67 .32 .06 1.69 1.63 .55 .81 576

Laissez-faireb .38 .25 .00 1.31 1.31 .55 .87 576

Satisfaction (of followers) b 3.50 .32 2.38 4.00 1.63 .79 .89 576

Effectiveness (of individual/group) b 3.43 .28 2.69 3.92 1.23 .64 .91 576

Extra effort (of followers) b 2.85 .39 1.83 3.92 2.08 .59 .73 576

aAll four rating levels and the five transformational scales combined. bAll four rating levels combined. cAll four rating levels and the two passive/avoidant scales combined.

143

Bivariate Analysis

To test for relationships between the variables, Pearson product moment

correlation coefficients were computed using SPSS (2007). For reasons of

consistency, descriptions of correlations were based on the guidelines outlined by

Cohen and Cohen (1983). Therefore, effect sizes for correlations are classified as

follows: r = .10 (classified as weak), r = .30 (classified as moderate), and r = > .50

(classified as strong). The inter-correlations for all of the variables in the Main Study

are presented in Table 13.

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Table 13

Inter-correlations between Main Study Variables

Variable

1 2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

1. Transformational leadershipb

- .68** -.09 -.02 -.08 -.03 -.41** .72** .72** .53** .06 .08 .05 .02 .07 .10 .03 .34** -.29**

2. Contingent rewardb - -.03 -.03 .01 .05 -.32** .56** .61** .49** .05 .11 .00 .02 .11 .10 -.03 .30** -.04

3. Management-by-exception active self-

ratings

- .25** -.01 -.02 .04 -.09 .00 -.03 -.11 -.18* -.06 -.20* -.04 -.12 -.01 -.02 .22**

4. Management-by-

exception active

supervisor ratings

- -.04 .10 -.01 -.10 -.11 -.06 -.01 -.04 .01 -.14 .09 -.05 .03 .01 .08

5. Management-by-exception active peer

ratings

- .14 -.05 -.12 -.05 .06 .02 -.05 .03 .04 -.09 -.11 .10 .08 .07

6. Management-by-exception active follower

ratings

- .09 -.04 -.05 .09 -.01 -.04 -.01 .06 -.11 -.10 .04 .11 .09

7. Passive/avoidant

leadershipb

- -.43** -.46** -.06 -.01 -.15 .06 -.05 -.13 -.03 .09 -.10 .11

8. Satisfaction (of followers)b

- .70** .38** .00 .09 -.04 .01 .10 .00 -.04 .18* -.22**

9. Effectiveness (of individual/group)b

- .55** -.05 -.02 -.06 -.08 .05 .03 -.09 .24** -.19*

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Variable

1 2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

10. Extra effort (of followers)b

- .04 -.02 .06 -.04 .04 .03 .09 .27** -.15

11. Total EIa - .68** .91** .48** .51** .72** .82** .13 -.07

12. Strategic EIa - .33** .67** .75** .33** .27** .09 -.05

13. Experiential EIa - .24** .26** .75** .91** .12 -.10

14. Managing emotionsa - .03 .30** .17* .11 -.06

15. Understanding emotionsa

- .21* .23** .04 .00

16. Using Emotionsa - .44** .19* -.06

17. Perceiving Emotionsa - .03 -.11

18. Opennessa - .01

19. Neuroticisma -

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Variable

1 2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

20. Extraversiona

21. Conscientiousnessa

22. Agreeablenessa

23. GMAa

24. Integritya


26. Idealised

Behavioursb

27. Inspirational

motivationb

28. Intellectual stimulationb

29. Individualised

considerationb

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Variable

1 2

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

30. Management-by-exception passiveb

31. Laissez-faireb

aN = 144. bN = 576.

* < .05 level, two-tailed. ** < .01 level, two-tailed.

148

Variable 20 21 22 23 24 25 26 27 28 29 30 31

1. Transformational leadershipb .14 .09 .30** -.26** .16 .83** .83** .83** .83** .78** -.27** -.41**

2. Contingent rewardb -.01 .09 .05 -.15 .12 .55** .54** .54** .57** .57** -.17* -.37**

3. Management-by-exception active

self-ratings

-.13 .06 -.18* -.01 .04 -.05 -.05 -.15 -.02 -.09 .09 -.04


supervisor ratings

.01 .08 .04 .00 .16 -.10 .12 -.07 .05 -.06 .00 .04


peer ratings

-.10 .03 -.15 -.06 -.23 .03 -.13 -.11 -.03 -.06 -.03 -.06


follower ratings

.09 .09 -.06 -.02 .04 -.09 .03 -.03 -.01 -.04 .07 .07

7. Passive/avoidant leadershipb -.05 -.25** -.10 .15 -.07 -.43** -.21* -.34** -.37** -.31** .86** .77**

8. Satisfaction (of followers)b .00 .05 .30** -.11 .02 .69** .52** .52** .59** .65** -.24** -.48**


individual/group)b

.05 .20* .16 -.16 .15 .65** .48** .59** .61** .60** -.29** -.47**

149

Variable 20 21 22 23 24 25 26 27 28 29 30 31

10. Extra effort (of followers)b .04 .14 .12 -.18* .15 .45** .44** .39** .49** .40** .03 -.15

11. Total EIa .06 .05 .07 .26** .13 .02 .05 .07 .05 .07 -.06 .05

12. Strategic EIa .07 .01 .11 .26** .14 .04 .01 .06 .07 .15 -.17* -.07

13. Experiential EIa .05 .05 .03 .19* .09 .02 .07 .08 .03 .01 .00 .09

14. Managing emotionsa .17* .09 .13 .11 .19* -.05 -.03 .06 -.00 .09 -.09 .02

15. Understanding emotionsa -.07 -.07 .00 .25** .03 .07 .03 .00 .09 .11 -.12 -.10

16. Using emotionsa .04 .07 .09 .07 .11 .05 .11 .14 .04 .05 -.08 .04

17. Perceiving emotionsa .02 .04 .00 .22** .05 .01 .05 .04 .03 .00 .05 .09

18. Opennessa .17* .17* .23** -.22** .18* .20* .34** .33** .28** .24** -.12 -.06

19. Neuroticisma -.27** -.17* -.46** .07 .06 -.30** -.21* -.40** -.17* -.09 .06 .11

150

Variable 20 21 22 23 24 25 26 27 28 29 30 31

20. Extraversiona - .22** .32** -.15 .01 .11 .15 .29** .01 .02 -.06 -.03

21. Conscientiousnessa - .27** -.05 .22** .12 .08 .18* -.07 .08 -.19* -.25**

22. Agreeablenessa - -.14 .12

.19* .25** .35** .18* .26** -.05 -.12

23. GMAa - .00 -.18* -.21* -.21* -.27** -.17* .16 .09

24. Integritya - .06 .17* .17* .15 .08 -.04 -.09


- .60** .65** .58** .61** -.23** -.49**

26. Idealised behavioursb - .72** .59** .51** -.11 -.24**

27. Inspirational motivationb

- .56** .46** -.24** -.32**

28. Intellectual stimulationb - .62** -.30** -.30**

29. Individualised considerationb - -.19* -.32**

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Variable 20 21 22 23 24 25 26 27 28 29 30 31


passiveb

- .33**

31. Laissez-faireb

-

152

The results of the research questions and hypotheses tested in the descriptive

and measurement component of the Main Study are presented below. Regarding

difference between the means procedures, the effect size, or proportion of variance in

the dependent variable explained by the independent variable, was determined by Eta

squared using the guidelines proposed by Cohen (1988): .01 = small effect, .06 =

moderate effect, .14 = large effect:

Hypothesis 1. Total EI will have discriminant validity from personality factors

(neuroticism, extraversion, openness, conscientiousness and agreeableness).

A small significant correlation was found between the using emotions branch

of EI and openness (.19 p = < .05). A small significant correlations was also found

between the managing emotions branch of EI and extraversion (.17, p = < .05). No

other relationships were found between the EI variables and personality factors.

Therefore, total EI was considered to have discriminant validity from all five

personality factors.

Hypothesis 2. Total EI will have discriminant validity from GMA.

The relationship between GMA and total EI was small (.26 p = < .01).

Therefore, Total EI demonstrated discriminant validity from GMA.


males.

To examine the mean differences between males (M = 99.47, SD = 10.76, n =

52) and females (M = 102.82, SD = 11.25, n = 92) for total EI scores, an independent

samples t-test was undertaken to evaluate the hypothesis that women score more

highly on EI than men. Gender was the independent variable (with two levels: male

and female) and EI total score was the dependent variable. The test was not

significant t(142) = 1.75, p = .08. Therefore, scores for total EI were not significantly

153

different for males and females in the Main Study. The mean difference was 3.36 with

a 95% confidence interval ranging from -.44 to 7.15. The size of the difference

between the means was small (Eta squared = .02).


for females than for males.

In order to examine the mean differences between males (M = 3.20, SD = .28,

n = 52) and females (M = 3.31, SD = .25, n = 92) for scores of transformational

leadership, an independent samples t-test was undertaken to test the hypothesis that

women are more transformational than men as leaders. Gender was the independent

variable (with two levels: male and female) and transformational leadership scores

(all raters combined) was the dependent variable. Levene‟s test for equality of

variances was larger than .05 hence the assumption of equal variances was not

violated. Therefore, equal variances assumed statistics are reported. The test was

significant t(142) = 2.47, p = .02 (two-tailed). Scores for transformational leadership

were significantly different for males and females. The mean difference was .11 with

a 95% confidence interval ranging from .23 to .20. The magnitude of the difference

between the means was small (Eta squared = .04). Females were found to be more

transformational in their leadership style than males in the Main Study.

Hypothesis 5. Scores for the contingent reward scale of transactional

leadership will be significantly higher for females than for males.

To examine the mean differences between males (M = 3.00, SD = .33, n = 52)

and females (M = 3.20, SD = .35, n = 92) for contingent reward, an independent

samples t-test was undertaken with gender as the independent variable (with two

levels: male and female) and contingent reward scores as the dependent variable.

Levene‟s test for equality of variances was larger than .05 hence the assumption of

154

equal variances was not violated. Therefore equal variances assumed statistics are

reported. The test was significant t(142) = 3.41, p = .001 (two-tailed). Scores for

transactional leadership were significantly different for males and females. The mean

difference was .20 with a 95% confidence interval ranging from .09 to .32. The size of

the differences in the means was moderate (Eta squared = .08). Females were found to

engage in more contingent reward behaviours than males in the Main Study.

Hypothesis 6. Scores for the management-by-exception active scale of

transactional leadership will be significantly higher for males than for females.

To examine the mean differences between males and females for scores of the

management-by-exception active scale of transactional leadership four independent

samples t-tests were undertaken. Gender was the independent variable (with two

levels: male and female) in each of the four t-tests and self-ratings, supervisor ratings,

peer ratings, and follower ratings were the dependent variables. Levene‟s tests for

equality of variances were larger than .05 in each of the t-tests that assessed: self-

ratings, supervisor ratings and peer ratings. Therefore, equal variances assumed

statistics are reported for these three tests. As Levene‟s test for equality of variances

was less than .05 in the t-test that assessed follower ratings equal variances not

assumed statistics are reported for this test.

For self-ratings of management-by-exception active, the t-test was not

significant t(142) = -1.08, p = .28 (two-tailed). Therefore, males (M = 1.53, SD = .77,

n = 52) were not found to engage in more self-rated management-by-exception active

behaviours than females (M = 1.39, SD = .76, n = 92) in the Main Study. The mean

difference was -.14 with a 95% confidence interval ranging from -.40 to .12. The size

of the differences in the means was small (Eta squared = .01).

For supervisor ratings of management-by-exception active, the t-test test was

155

not significant t(142) = 1.40, p = .16 (two-tailed). Therefore, males (M = 1.71, SD =

.98, n = 52) were not found to engage in more management-by-exception active


difference was .23 with a 95% confidence interval ranging from -.09 to .54. The size

of the differences in the means was small (Eta squared = .01).

For peer ratings of management-by-exception active, the t-test was not

significant t(141) = -.50, p = .62 (two-tailed). Therefore, males (M = 1.84, SD = .92, n

= 52) were not found to engage in more management-by-exception active behaviours

than females (M = 1.75, SD = .99, n = 91) in the Main Study. The mean difference

was -.08 with a 95% confidence interval ranging from -.42 to .25. The size of the

differences in the means was very small (Eta squared = .00).

Finally, for follower ratings of management-by-exception active, the t-test was

not significant t(127) = 1.48, p = .14 (two-tailed). Therefore, males (M = 1.42, SD

=.77, n =52) were not found to engage in more management-by-exception active


difference was .22 with a 95% confidence interval ranging from -.07 to .51. The size

of the differences in the means was small (Eta squared = .02). Overall, the scores for

males were not significantly higher than for females at each of the four rating levels

for the management-by-exception active scale of transactional leadership.

Hypothesis 7. Passive/avoidant leadership scores will be significantly higher

for males than for females.

To examine the mean differences between males (M = .59, SD = .26, n = 52)

and females (M = .49, SD = .21, n = 92) for passive/avoidant leadership, an

independent samples t-test was undertaken with gender as the independent variable

(with two levels: male and female) and passive/avoidant leadership scores (all raters

156

combined) as the dependent variable. As Levene‟s test for equality of variances was

larger than .05 the assumption of equal variances was not violated. Therefore, equal

variances assumed statistics are reported. The test was significant t(142) = -2.55, p =

.01 (two-tailed). Scores for passive/avoidant leadership were significantly different

for males and females. The mean difference was -.10 with a 95% confidence interval

ranging from -.18 to -.23. The magnitude of the difference between the means was

small (Eta squared = .04). Males were found to be more passive/avoidant in their

leadership style than females in the Main Study.

Research question 1. Investigate whether scores of transformational leadership

vary according to the role of the leader (principal, vice-principal, head of

department, tertiary coordinator and administrator).

A one-way between groups analysis of variance was conducted to assess the

impact of role on transformational leadership scores. Participants were divided into

five groups according to their role: Group 1 = principal (M = 3.30, SD = .25, n = 66),

Group 2 = vice-principal (M = 3.25, SD = .27, n = 51), Group 3 = tertiary coordinator

(M = 3.15, SD = .35, n = 12), Group 4 = head of department (M = 3.26, SD = .30, n =

10) and Group 5 = administrator (M = 3.34, SD = .18, n = 5). There was no statistical

difference in transformational leadership scores for the five groups: F(4, 139) = .98, p

= < .05. Therefore, there was no significant difference for scores of transformational

leadership between the groups of principal, vice-principal, tertiary coordinator, head

of department and administrator in the Main Study.

Research question 2. Investigate whether scores of total EI vary according to

the role of the leader (principal, vice-principal, head of department, tertiary

coordinator and administrator).

A one-way between groups analysis of variance was conducted to assess the

157

impact of role on total EI scores. Participants were divided into five groups according

to their role: Group 1 = principal (M = 100.67, SD = 11.59, n = 66), Group 2 = vice-

principal (M = 102.71, SD = 11.19, n = 51), Group 3 =tertiary coordinator (M = 98.05,

SD = 8.58, n = 12), Group 4 = head of department (M = 103.55, SD = 7.89, n = 10)

and Group 5 = administrator (M = 107.62, SD = 15.37, n = 5). There was no

statistical difference in total EI scores for the five groups: F(4, 139) = .99, p = < .05.

Therefore there was no significant difference for scores of Total EI between the

groups of principal, vice-principal, tertiary coordinator, head of department and

administrator in the Main Study.




A small significant correlation was found between integrity and

conscientiousness (.20, p = < .05). No other relationships were found between

integrity and the other four personality factors. Therefore, integrity demonstrated

adequate discriminant validity from all five personality factors in the Main Study.

Discussion

The preceding section of this chapter reported on the descriptive and

measurement component of the Main Study in this project. The discriminant validity

of the instruments selected for the study was tested and the impact of gender and role

on leadership style and EI was examined. Taking into account the extreme difficulty

experienced in obtaining participants for the Pilot Study, the number of expressions of

interest from potential participants for the Main Study far exceeded expectations. This

was probably the result of targeting members of the most suitable and cooperative

professional body (ACEL). One leader who expressed an interest in participating in

158

the study did not have access to a computer with the hardware required to complete

the questionnaires online. Otherwise, all of those selected were able to access the

questionnaires online, from any location, at a time that suited them. Several

participants commented on the convenience of the arrangement. Some technical

problems were experienced by participants when accessing the online questionnaires.

Some of these problems were the result of issues with hyperlinks, whilst others were

related to levels of computer literacy amongst participants. These technical problems

were resolved during the study. The number of websites that each participant was

required to access to complete the questionnaires was reduced from five in the Pilot

Study to four in the Main Study. This reduction was possible as permission was

obtained from Mind Garden Inc., the publisher of the MLQ5X (Avolio et al., 1995),

to load the questionnaire onto an external website. Therefore, the MLQ5X (Avolio et

al., 1995) was loaded onto the same website as The BFI (John et al., 1991). This

simplified the process a little for participants. The use of individual codes rather than

names to identify respondents assured the participants that their test scores would

remain confidential. This may have been one of the reasons for the very high rate of

completion of the questionnaires by the participants who commenced the study.

Although participants were requested to complete the questionnaires within

two weeks, many did not complete the task within this timeframe. Those that had not

completed the questionnaires within the designated timeframe were sent email

reminders and provided with additional time to complete the task. Some participants

received up to five reminders over a period of four months. As some raters were slow

in responding to their invitations several leaders decided to nominate alternative raters

during the data collection process in order to ensure that multiple ratings of their

leadership behaviours were completed. Eventually, all remaining participants and

159

their raters completed the questionnaires. Hence, the final response rate for raters

(supervisors, peers and followers) nominated by the leaders was 100%.

All participants requested and received feedback related to their test scores

from The BFI (John et al., 1991), the MLQ (Avolio et al., 1995) and the MSCEIT

(Mayer et al., 2002). This was a successful incentive to obtain participants in this

study and may partly explain why the response rate was high. Only one participant

requested debriefing. The participant had been disturbed by some of the comments

written by her nominated supervisor in response to the qualitative items of the MLQ

(Avolio et al., 1995). Debriefing was conducted via the telephone.

Regarding the results, no significant differences were found between

transformational leadership scores for the five groups (principal, vice-principal, head

of department, tertiary coordinator and administrator) that participated in the study.

Therefore, levels of transformational leadership did not vary according to role. Hence,

those whose dominant leadership style is transformational are not necessarily

fulfilling higher level leadership roles (e.g., administrator or principal) in Australian

educational institutions. As there was no significant difference between the EI scores

of principals, vice principals and heads of departments, it is possible that EI may not

be an important factor in determining the position of a leader within the leadership

hierarchy in Australian schools. Alternatively, the abilities of those who scored more

highly on EI may not be recognised by the current frameworks for career progression.

Another possible explanation for the lack of difference in EI scores between the

various roles is that the abilities measured by the MSCEIT (Mayer et al., 2002) may

not be particularly relevant for leaders in Australian educational institutions.

The discriminant validity of several of the measures included in the project

was also assessed in the Main Study. Ones et al. (1993) had found that there was

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considerable overlap between integrity and conscientiousness. However, Integrity

Express (Vangent, 2002a) was found to have discriminant validity from all five

personality factors including conscientiousness in the Main Study. Therefore,

Integrity Express (Vangent, 2002a) was not measuring the same factors as The BFI

(John et al., 1991).

Van Rooy and Viswesvaran (2004) had found that there was a small

relationship between EI and GMA. This finding was replicated in the Main Study. As

the relationship was small, total EI demonstrated adequate divergent validity from

GMA. The findings of the Main Study provide further evidence that EI is a different

construct to GMA. Furthermore, EI was considered to have discriminant validity from

all five personality factors in The BFI (John et al., 1991). This is in-line with the

findings of Van Rooy and Viswesvaran (2004) who found that the relationship

between EI and personality factors was small. This finding provides further evidence

that the MSCEIT (Mayer et al., 2002) is measuring a different construct to the five

factors of personality.

Regarding gender, in the Main Study females were perceived to demonstrate

more transformational leadership behaviours than males. This replicates the findings

of Bass and Avolio (1994), Bass et al. (1996) and Eagly et al. (2003), who reported

that females were more transformational than males. Although the size of the

difference in scores was small it represents further evidence that females are more

transformational as leaders than males. Furthermore, females were perceived to

demonstrate more behaviours measured by the contingent reward scale of

transactional leadership than males which replicates the findings of Eagly et al. (2003)

and provides further support for the selection of females for leadership roles. Males

were not perceived to demonstrate more behaviours measured by the management-by-

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exception active scale of transactional leadership which differs from the findings of

Eagly et al. (2003). However, males were perceived to engage in more

passive/avoidant leadership behaviours than females in the Main Study which

replicates the findings of Eagly et al. (2003). The importance of predicting

passive/avoidant leadership behaviours is often overlooked by researchers. However,

it is important to identify those whose dominant leadership style is passive/avoidant in

order to be aware of their likely limitations in leadership positions. More research is

required to confirm the impact of gender on leadership style.

Scores for total EI were not significantly different for males and females in the

Main Study. This is contrary to the findings of Mandell (2003), Mayer and Geher

(1996), Mayer, Caruso and Salovey, (1999) and Mayer et al. (2004), all of whom

found that females scored significantly higher than males on tests of EI. As the mean

score for males (M = 99.47) in this study was lower than the mean score for females

(M = 102.82), and lower than the mean score for males and females in the normative

sample (M = 100), this finding cannot be explained by the males in this study having a

particularly high level of EI. Rather, the fact that differences between the scores for

males and females on EI in the Main Study simply failed to reach significance may be

a likely explanation.

Conclusion

This chapter reported on the descriptive and measurement component of the

Main Study. Research questions and hypotheses were formulated to test the

discriminant validity of the instruments selected for the project. Additionally, the

impact of role and gender on leadership style and EI were examined. In summary,

results indicated that levels of transformational leadership and EI did not vary

according to role. EI was considered to have discriminant validity from personality

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factors and GMA. Hence, the same instruments could be retained for use in the

upcoming inferential component of the Main Study as they were deemed to be

measuring different constructs. In the Main Study, females were perceived to

demonstrate more transformational leadership behaviours and more contingent reward

behaviours (transactional leadership) than males, whilst males were perceived to

engage in more passive/avoidant leadership behaviours than females. The following

chapter reports on the inferential component of the Main Study in which the

usefulness of EI as a predictor of leadership style and perceived leadership outcomes

is examined by comparing its predictive validity with the other predictors included in

the project.

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Chapter 6: Main Study - Inferential Component

Introduction

This chapter reports on the inferential component of the Main Study (the

descriptive and measurement component is reported in Chapter 5). Initially, the

independent and dependent variables examined in the Main Study are presented.

Then, the specific research questions formulated to examine the usefulness of EI as a

predictor of leadership style and perceived leadership outcomes are presented. The

predictive validity of EI is assessed to determine whether or not it is a better predictor

of transformational leadership and perceived leadership outcomes than the other

predictors included in the study.

A brief reminder of the methodology undertaken in the Main Study is made

with reference to the procedure, participants and instruments selected to

operationalise the conceptual variables. The participants were 144 educational

leaders, and 432 nominated raters (the same sample as in the descriptive and

measurement component of the Main Study). Methods for data entry, data screening

and the results of multivariate statistical analysis conducted using SPSS version 15.0

(SPSS, 2007) are reported. Finally, the methodology and results of the inferential

component of the study are discussed.


In the Main Study, the following independent variables were measured and

their effect on the dependent variables was measured: total EI, strategic EI,

experiential EI, perceiving emotions, using emotions, understanding emotions,

managing emotions, general mental ability, neuroticism, extraversion, openness,

conscientiousness, agreeableness and integrity.


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Research Questions

As there is insufficient literature to develop specific hypotheses the following

research questions have been formulated for the inferential component of the Main

Study (Refer to pp. 134 for research questions 1 - 3 which are related to the

descriptive and measurement component of the Main Study):

Research question 4. Investigate whether EI predicts transformational

leadership.

Research question 5. Investigate whether EI has incremental validity above

GMA in predicting transformational leadership.


personality factors (neuroticism, extraversion, openness, conscientiousness

and agreeableness) in predicting transformational leadership.


integrity in predicting transformational leadership.

Research question 8. Investigate whether EI predicts satisfaction (of

followers).

Research question 9. Investigate whether EI predicts effectiveness (of

leader/group).

Research question 10. Investigate whether EI predicts extra effort (by

followers).

Research question 11. Investigate whether EI predicts the contingent reward

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scale of transactional leadership.

Research question 12. Investigate whether EI predicts the management-by-

exception active scale of transactional leadership.

Research question 13. Investigate whether EI predicts passive/avoidant

leadership.

Methodology


The sample of leaders for the inferential component of the Main Study was the

same as the sample for the descriptive and measurement component reported in

Chapter 5 (144 educational leaders, and 432 nominated raters). Refer to page 134 for

details of the procedure.

Instruments

The instruments used in the inferential component of the Main Study were the

same as those used the descriptive and measurement component. The conceptual

variables were operationalised using online tests. The instrument selected to test

leadership styles and perceived leadership outcomes was the MLQ5X (Avolio et al.,

1995). EI was assessed using the MSCEIT (Mayer et al., 2002). Personality factors

were operationalised using The BFI (John et al., 1991). GMA was tested using the

WPT-Q (Wonderlic, 2003) and integrity was assessed using Integrity Express

(Vangent, 2002a).

Results

The results of an independent samples t-test had confirmed that there was no

difference in the mean scores of transformational leadership between the Pilot Study

sample (N = 27) and the sample obtained for the Main Study 1 (N = 120). Therefore,

in order to maximise the power and validity of the Main Study, the combined data

sample was retained. In order to ensure that the research design was sensitive enough

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to detect an effect, the sample size was determined using a power calculation. Kirk

(1982) proposes that power should be at least .80. In order to achieve this level of

power for multiple regression analysis the required number of participants is 122,

given an alpha level of .05, an anticipated effect size of .015 and 11 predictors.

Therefore the number of participants in the Main Study exceeded this requirement (N

= 144).

Data Screening

The bivariate data screening process for the Main Study is described on page

154. In order to check for multivariate outliers, scatterplots were generated in SPSS

(2007). Tabachnik and Fidel (2007) define outliers as cases that have a standardised

residual of more than 3.30, or less than -3.30. No outliers were found using

scatterplots. Casewise diagnostics were generated in SPSS (2007) for each of the 10

regression models in Study 2 to highlight cases with residual values above 3.00 and

below -3.00. One case in Model 2 slightly exceeded this range. However, as one per

cent of the sample size is permitted to be outside this range in a normally distributed

sample this case was retained (Tabachnik & Fidel, 2007). Mahalanobis distances were

also checked using the critical chi square value of 31.30 and the 11 independent

variables as degrees of freedom. No cases exceeded the maximum value for

Mahalanobis distances. Additionally, values for Cook‟s Distance were checked to

determine whether or not any cases existed with a value larger than one. As all cases

had a value of less than one in the regression models all cases were retained.


Refer to Table 12 for descriptive statistics of the Main Study variables.

Bivariate Analysis

The inter-correlations for all of the variables in the Main Study are presented

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in Table 13. Significant correlations between each of the leadership variables and the

predictor variables are highlighted below. The results of the correlation analysis

indicated that four correlations between transformational leadership and the predictor

variables were statistically significant. Moderately sized significant correlations were

found between transformational leadership and openness (.34, p = < .001), and

transformational leadership and agreeableness (.30, p = < .001). Small negative

correlations were also found between transformational leadership and neuroticism (-

.29, p = < .001), and transformational leadership and GMA (-.26, p = < .01).

The contingent reward scale of transactional leadership shared a moderately

sized correlation with openness (.30, p = < .001). Self-ratings of the management-by-

exception active scale of transactional leadership shared small correlations with

neuroticism (.22, p = < .01) and agreeableness (.18, p = < .05), and small negative

correlations with the strategic area of EI (-.18, p = < .05) and the managing emotions

branch of EI (-.20, p = < .05). The correlations of EI with the other leadership style

and perceived leadership outcomes variables were not significant. Passive-avoidant

leadership shared a small negative correlation with conscientiousness (-.25, p = <

.01).

Regarding the perceived leadership outcomes variables, satisfaction (of

followers) shared a small correlation with openness (.18, p = < .05), a moderate

correlation with agreeableness (.30, p = < .001) and a small negative correlation with

neuroticism (-.22, p = < .01). Effectiveness (of individual/group) shared small

correlations with openness (.24, p = < .01) and conscientiousness (.20, p = < .05), and

a small negative correlation with neuroticism (-.19, p = < .05). Finally, extra effort (of

followers) shared a small correlation with openness (.27, p = < .01) and a small

negative correlation with GMA (-.18, p = < .05).

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Multivariate Analysis

Multiple regression analysis was undertaken to investigate the

interrelationship of the variables in the study and assess the predictive validity of the

independent variables. Multiple regression shares all the assumptions of correlation

(Tabachnick & Fidell, 2007). As a result of the exploratory nature of the study,

standard multiple regression was conducted to assess the predictive validity of the

predictor variables with respect to the leadership variables. As a rule of thumb, the

minimum number of cases required per independent variable is often considered to be

ten. Therefore, the number of cases (N = 144) in the Main Study exceeded the

minimum requirements for up to 14 independent variables to be tested as predictors.

However, the regression models undertaken in the Main Study used only 11

independent variables. Tabachnik and Fidel (2007) state that the sample size should

be at least N>50+8m (where m is the number of independent variables). Therefore, a

sample size of 138 (50+8[11] = 138) was required to test 11 predictors. The sample

size in the Main Study exceeded this requirement.

Results

Research question 4. Investigate whether EI predicts transformational

leadership.

In Model 1, a standard multiple regression was performed between

transformational leadership as the dependent variable and total EI, the two areas of EI

(experiential EI and strategic EI), the four branches of EI (perceiving emotions,

understanding emotions, managing emotions and using emotions), personality factors

(agreeableness, neuroticism, openness, extraversion and conscientiousness), integrity

and GMA as the independent variables. Analysis was performed using SPSS

REGRESSION. No multivariate outliers were found.

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Unsurprisingly, problems of singularity were found among the EI variables.

The values of variance inflation factors (VIF) for the EI variables ranged from 16.53

to 141.96. These values were much higher than the recommended maximum value of

10. Therefore, the two EI areas (experiential EI and strategic EI) and total EI were

deleted from the analysis to solve the problem of singularity as they had very high

correlations with the branches of EI. The multiple regression analysis was then rerun

without the deleted variables. All VIF values were now below 10, indicating that the

problem with multicollinearity had been resolved by deleting the variables. The linear

combination of predictor measures was significantly related to transformational

leadership, F(11, 132) = 4.32, p < .001. The sample multiple correlation coefficient

was .51, indicating that 26.5% of the variance in transformational leadership was

accounted for by the linear combination of predictor measures. Openness (Beta = .26)

contributed to the variance of transformational leadership. Neuroticism (Beta = -.25)

and GMA (Beta = -.20) were also significant negative predictors of transformational

leadership. The part correlations indicated that the most important predictors were

openness, which contributed 5.57% to the variance of transformational leadership,

and emotional stability (the inverse of neuroticism) which contributed 4.45%. GMA

contributed 3.17%. Although the bivariate correlation between agreeableness and

transformational leadership was statistically significant, agreeableness did not

contribute significantly to the regression. The relationship between agreeableness and

transformational leadership may be mediated by the relationship between

transformational leadership and the other independent variables. None of the EI

branches predicted transformational leadership in Model 1. Notably, the pattern of

results was the same when the regression model was re-run with total EI as an

independent variable replacing the four branches of EI, and then with the two areas of

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EI as independent variables replacing the four branches of EI. A summary of

regression Model 1 for variables predicting transformational leadership is presented in

Table 14.

Table 14

Summary of Regression Model 1 for Variables Predicting Transformational

Leadership (N = 144)

Variable B SE B β

Perceiving emotions .00 .00 .02

Understanding emotions .00 .00 .10

Managing emotions .00 .00 -.04

Using emotions .00 .00 .01

Agreeableness .05 .04 .11

Neuroticism -.08 .03 -.25**

Openness .13 .04 .26**

Extraversion .00 .03 -.01

Conscientiousness -.03 .04 -.05

Integrity .02 .01 .13

GMA -.01 .01 -.20*

Note. R2 = .27.

*p < .05. **p < .01.


GMA in predicting transformational leadership.

In multiple regression Model 1, none of the EI branches had incremental

validity above GMA in predicting transformational leadership as none of the EI

branches were significant predictors of transformational leadership, whereas GMA

was a significant negative predictor.

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personality factors (neuroticism, extraversion, openness, conscientiousness

and agreeableness) in predicting transformational leadership.


validity above personality factors in predicting transformational leadership as none of

the EI branches were significant predictors of transformational leadership, whereas

neuroticism (inversely) and openness were significant predictors.


integrity in predicting transformational leadership.


validity above integrity in predicting transformational leadership as neither the EI

branches or integrity were significant predictors of transformational leadership.

Research question 8. Investigate whether EI predicts satisfaction (of

followers).

In Model 2, a standard multiple regression was performed between satisfaction

(of followers) as the dependent variable and the four branches of EI (perceiving

emotions, understanding emotions, managing emotions and using emotions),

personality factors (agreeableness, neuroticism, openness, extraversion and

conscientiousness), integrity and GMA as the independent variables. Analysis was

performed using SPSS REGRESSION. Casewise Diagnostics generated in SPSS

(2007) highlighted a potential outlier with a residual value of -3.10. However, as 1%

of the sample size is permitted to be outside the range of -3 to 3 in a normally

distributed sample this case was retained. Therefore, no multivariate outliers were

found. As all VIF values were below 10 no problems with multicollinearity were

encountered. The linear combination of predictor measures was significantly related

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to satisfaction (of followers), F(11, 132) = 2.20, p < .05. The sample multiple

correlation coefficient was .39, indicating that 15.50% of the variance in satisfaction

(of followers) was accounted for by the linear combination of predictor measures.

Agreeableness (Beta = .25) was a significant predictor of satisfaction (of followers).

The part correlation indicated that agreeableness contributed 4.24% to the variance of

satisfaction (of followers). None of the branches of EI predicted satisfaction (of

followers). A summary of regression Model 2 for variables predicting satisfaction (of

followers) is presented in Table 15.

Table 15

Summary of Regression Model 2 for Variables Predicting Satisfaction (of Followers)

(N = 144)

Variable B SE B β

Perceiving emotions .00 .00 -.05


Managing emotions .00 .00 .01

Using emotions .00 .00 -.05

Agreeableness .14 .05 .25*

Neuroticism -.06 .04 -.14

Openness .09 .05 .15

Extraversion -.06 .04 -.14

Conscientiousness -.01 .05 -.20

Integrity .00 .01 -.02

GMA -.01 .01 -.07

Note. R2 = .16.

*p < .05. **p < .01.

Research question 9. Investigate whether EI predicts effectiveness (of

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individual/group).


effectiveness (of individual/group) as the dependent variable and the four branches of

EI (perceiving emotions, understanding emotions, managing emotions and using

emotions), personality factors (agreeableness, neuroticism, openness, extraversion and


performed using SPSS REGRESSION. No multivariate outliers were found. As all

VIF values were below 10 no problems with multicollinearity were encountered. The

linear combination of predictor measures was significantly related to effectiveness (of

individual/group), F(11, 132) = 2.41, p < .01. The sample multiple correlation

coefficient was .41, indicating that 16.70% of the variance in effectiveness (of

individual/group) could be accounted for by the linear combination of predictor

measures. Openness (Beta =.20) was a significant predictor of effectiveness (of

individual/group) whilst neuroticism (Beta = -.21) was a significant negative predictor

of effectiveness (of individual/group). The part correlations indicated that openness

contributed 3.31% to the variance of effectiveness (of individual/group) and

neuroticism contributed 3.24%. None of the branches of EI predicted effectiveness (of

individual/group). A summary of regression Model 3 for variables predicting

effectiveness (of individual/group) is presented in Table 16.

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Table 16

Summary of Regression Model 3 for Variables Predicting Effectiveness (of

Individual/Group) (N = 144)

Variable B SE B β



Managing emotions -.01 .00 -.13


Agreeableness -.01 .05 -.20

Neuroticism -.07 .03 -.21*

Openness .11 .05 .20*


Conscientiousness .07 .05 .13


GMA -.01 .01 -.09

Note. R2 = .17.

*p < .05. **p < .01.

Research question 10. Investigate whether EI predicts extra effort (of

followers).

In Model 4, a standard multiple regression was performed between extra effort

(of followers) as the dependent variable and the four branches of EI (perceiving

emotions, understanding emotions, managing emotions and using emotions),

personality factors (agreeableness, neuroticism, openness, extraversion and




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linear combination of predictor measures was significantly related to extra effort (of

followers), F(11, 132) = 2.11, p < .05. The sample multiple correlation coefficient

was .39, indicating that 15% of the variance in extra effort (of followers) could be

accounted for by the linear combination of predictor measures. Openness (Beta = .24)

was a significant predictor of extra effort (of followers). The part correlation indicated

that openness contributed 4.71% to the variance of extra effort (of followers). None of

the branches of EI predicted extra effort (of followers). A summary of regression

Model 4 for variables predicting extra effort (of followers) is presented in Table 17.

Table 17

Summary of Regression Model 4 for Variables Predicting Extra Effort (of Followers)

(N = 144)

Variable B SE B β






Neuroticism -.08 .05 -.17

Openness .18 .07 .24**




GMA -.02 .01 -.15

Note. R2 = .15.

*p < .05. **p < .01.

Research question 11. Investigate whether EI predicts the contingent reward

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scale of transactional leadership.

In Model 5, a standard multiple regression was performed between contingent

reward as the dependent variable and the four branches of EI (perceiving emotions,

understanding emotions, managing emotions and using emotions), personality factors

(agreeableness, neuroticism, openness, extraversion and conscientiousness), integrity

and GMA as the independent variables. Analysis was performed using SPSS

REGRESSION. No multivariate outliers were found. As all VIF values were below

10 no problems with multicollinearity were encountered. The linear combination of

predictor measures was significantly related to contingent reward, F(11, 132) = 1.92,

p < .05. The sample multiple correlation coefficient was .37, indicating that 13.80%

of the variance in contingent reward was accounted for by the linear combination of

predictor measures. Openness (Beta = .28) was a significant predictor of contingent

reward. The part correlation indicated that openness contributed 6.20% to the variance

of contingent reward. None of the branches of EI predicted contingent reward. A

summary of regression Model 5 for variables predicting the contingent reward scale

of transactional leadership is presented in Table 18.

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Table 18

Summary of Regression Model 5 for Variables Predicting the Contingent Reward

Scale of Transactional Leadership

(N =144)

Variable B SE B β






Neuroticism -.04 .04 .08

Openness .19 .06 .28**




GMA -.01 .01 -.13

Note. R2 = .14.

*p < .05. **p < .01.

Research question 12. Investigate whether EI predicts the management-by-

exception active scale of transactional leadership.

In Models 6 - 9, standard multiple regressions were performed between self-

ratings (Model 6), supervisor ratings (Model 7), peer ratings (Model 8) and follower

ratings (Model 9) of management-by-exception active as the dependent variables and

the four branches of EI (perceiving emotions, understanding emotions, managing

emotions and using emotions), personality factors (agreeableness, neuroticism,

openness, extraversion and conscientiousness), integrity and GMA as the independent

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variables. Analysis was performed using SPSS REGRESSION. No multivariate

outliers were found in Models 6 - 9. As all VIF values were below 10 no problems

with multicollinearity were encountered.

In Model 6, the linear combination of predictor measures was not significantly

related to self-ratings of management-by-exception active, F(11, 132) = 1.59, p > .05.

In Model 7, the linear combination of predictor measures was not significantly related

to supervisor ratings of management-by-exception active, F(11, 132) = 1.11, p > .05.

In Model 8, the linear combination of predictor measures was not significantly related

to peer ratings of management-by-exception active, F(11, 132) = 1.54, p > .05.

Finally, in Model 9 the linear combination of predictor measures was not significantly

related to follower ratings of management-by-exception active, F(11, 132) = 1.07, p

> .05. Therefore, in Models 6 – 9 EI did not predict the management-by-exception

active scale of transactional leadership for any of the rating levels.

Research question 13. Investigate whether EI predicts passive/avoidant

leadership.


passive/avoidant leadership as the dependent variable and the four branches of EI

(perceiving emotions, understanding emotions, managing emotions and using

emotions), personality factors (agreeableness, neuroticism, openness, extraversion and




linear combination of predictor measures was significantly related to passive/avoidant

leadership, F(11, 132) = 1.94, p < .05. The sample multiple correlation coefficient

was .37, indicating that 13.90% of the variance in passive/avoidant leadership was

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accounted for by the linear combination of predictor measures. Conscientiousness

(Beta = -.26) and the understanding emotions branch of EI (Beta = -.22) were

significant negative predictors of passive/avoidant leadership. The part correlations

indicated that conscientiousness contributed 5.62% to the variance of passive/avoidant

leadership and the understanding emotions branch of EI contributed 4.04%. Apart

from the understanding emotions branch of EI, the other EI branches did not

contribute to the variance in passive/avoidant leadership. A summary of regression

Model 10 for variables predicting passive/avoidant leadership is presented in Table

19.

Table 19

Summary of Regression Model 10 for Variables Predicting Passive/Avoidant

Leadership (N =144)

Variable B SE B β


Understanding emotions -.01 .00 -.22*



Agreeableness .01 .04 .03

Neuroticism .02 .03 .08

Openness -.01 .04 -.02

Extraversion .01 .03 .04

Conscientiousness -.12 .04 -.26*


GMA .01 .01 .17

Note. R2 = .14.

*p < .05. **p < .01.

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Discussion

In the inferential component of the Main Study, multiple regression

procedures were undertaken to investigate the interrelationship of the variables in the

study and assess the predictive validity of the independent variables. EI was assessed

to determine whether or not it was a useful predictor of transformational leadership

and perceived leadership outcomes.

In regression Model 1, the predictors accounted for a surprisingly small

amount of variance in transformational leadership. Openness and emotional stability

(the inverse of neuroticism) were the most important predictors, followed by GMA

(inversely). None of the EI branches predicted transformational leadership in the Main

Study, yet in the Pilot Study several of the EI variables were positively related to

transformational leadership. This discrepancy highlights the problem of making

inferences from a sample which is too small (N = 25) to provide reliable findings. The

findings from regression Model 1 are also contrary to the findings of previous studies

by Silvanathan and Fekken (2002), Leban (2003), Coetzee and Schaap (2004) and

Srivsastava and Bharamanaikar (2004), all of whom found that EI predicted

transformational leadership. However, it is important to note that apart from the study

by Leban (2003) these studies used different EI instruments from the one used in this

project. The findings from regression Model 1 are in-line with the findings of Schulte

(2003), who also used the MLQ5X (Avolio et al., 1995) and the MSCEIT (Mayer et

al., 2002), and found that EI did not account for additional variance in

transformational leadership when GMA and personality were included in the

regression. The meta-analysis by Harms and Crede (2010) also reported that when

multiple ratings of leadership behaviours were obtained the MSCEIT (Mayer et al.,

2002) did not predict transformational leadership style. As multiple ratings are

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considered to be the most valid form of assessing leadership behaviours (Landy &

Conte, 2006) this finding highlights the limitations of the MSCEIT (Mayer et al.,

2002) in predicting transformational leadership.

Although total EI and the two area scores (strategic EI and experiential EI)

were deleted from regression Model 1 in order to solve the problem of singularity, it

is worth noting that the pattern of results remained the same when the regression was

run with total EI as the only independent variable representing EI. Similarly, when the

regression was run again with the two area scores as the only independent variables

representing EI, the EI variables were not significant predictors of transformational

leadership. Therefore, it is reasonable to conclude that EI is not a useful predictor of

transformational leadership in this context. Furthermore, the findings from Model 1

rekindle the discussion regarding whether or not the Mayer and Savoley (1997) model

of EI is useful a predictor of transformational leadership in any setting.

In regression Model 1, GMA was found to be a negative predictor of

transformational leadership. As scores of GMA increased, scores of transformational

leadership decreased. However, the meta-analysis by Judge et al. (2004) had indicated

that GMA was positively related to leadership behaviours, whilst Schmidt and Hunter

(1998) had reported that GMA was the most useful predictor of job performance.

Whilst it was not surprising to find that a relationship existed between

transformational leadership and GMA in regression Model 1, the negative direction of

the relationship was surprising. One possible explanation for the inverse direction of

the relationship is that there was a restriction of range in the sample. It is reasonable

to assume that any sample consisting solely of educational leaders would score highly

on a measure of GMA. The mean score of the leaders on the WPT-Q (Wonderlic,

2003) was 25.81 whilst the mean score for the normative sample is 21.90

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(Anonymous, 2004). Another possibility is that the measure used to operationalise

GMA, the WPT-Q (Wonderlic, 2003), is unable to adequately differentiate amongst

test takers at the higher end of the scale. The WPT-Q (Wonderlic, 2003) caters for a

broad spectrum of abilities but as it only has a total of 30 items there are not many

items available to differentiate between test takers in a sample that has a relatively

high mean score. The standard deviation of the leaders‟ WPT-Q (Wonderlic, 2003)

scores was only 3.76 which is less than the 5.03 reported in the normative sample

(Anonymous, 2004). Another possible explanation is that GMA could be an

antecedent of transformational leadership up to a certain level, but once above that

threshold the usefulness of GMA as a predictor may diminish. It is also worth

recalling that although Schmidt and Hunter (1998) had reported the usefulness of

GMA as a predictor of job performance, leadership and job performance are different

constructs and as such they may require different levels of abilities, or different

abilities altogether. An alternative view is offered by Bono and Judge (2004) who

proposed scores on objective instruments may be less important than the perceptions

of leaders by others in attaining leadership roles.

Therefore, the findings from regression Model 1 support the position of

Goldstein et al. (2002) who argued that personnel selection processes overemphasise

the importance of GMA. This may well be the case when selecting leaders in

Australian educational institutions and elsewhere.

Regarding personality factors, openness and emotional stability (the inverse of

neuroticism) were found to be the best predictors of transformational leadership in

regression Model 1. These findings differ from the findings of Judge and Bono (2000)

who reported that agreeableness and extraversion were the most useful predictors of

transformational leadership. Judge and Bono (2000) found that openness to

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experience was positively related to transformational leadership but it was not

influential when other traits were controlled. In a further meta-analysis, Bono and

Judge (2004) had reported that all five personality factors were modestly related to

transformational leadership. In the Main Study, although the bivariate correlation

between agreeableness and transformational leadership was statistically significant,

agreeableness did not contribute significantly to the regression in Model 1. Hence, the

relationship between transformational leadership and agreeableness may be mediated

by the relationship between transformational leadership and the other predictor

variables. Judge et al. (2002) suggested that different personality factors may be

important in different vocational settings. Hence, openness and emotional stability

(the inverse of neuroticism) may be especially important for educational leaders.

Further research is required into the relationship between personality factors and

educational leadership.

The findings from regression Model 1 suggest that integrity is not a useful

predictor of transformational leadership. This finding differs from the findings of

Parry and Proctor-Thomson (2002) who reported that integrity predicted

transformational leadership. However, it should be noted that the measure used to

operationalise integrity by Parry and Proctor-Thomson (2002) was conceptually

different from the measure of integrity used in the Main Study of this project. This

finding is also out-of-line with the findings of Schmidt and Hunter (1998), and Ones

et al. (1993) who found that integrity was a useful predictor of job performance. One

possible explanation for this is that the constructs of transformational leadership and

job performance are too dissimilar. However, the failure of integrity to predict

transformational leadership in regression Model 1 must be interpreted with caution as

it was noted that following the removal of a single outlier from the integrity data in

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the Main Study integrity became a modest predictor of transformational leadership.

As this outlier was not considered extreme enough to be removed from the data a

decision was made to retain the case, and in doing so integrity became a non-predictor

of transformational leadership. Taking into account the small size of the margin which

influenced this outcome the relationship between overt integrity tests and

transformational leadership warrants further investigation. The extremely short length

(16 items) of the Integrity Express (Vangent, 2002a) instrument used to operationalise

integrity in this project may also have influenced the outcome. Therefore, is it

suggested that future research related to integrity and leadership behaviours should

use a longer instrument such as The Reid Report (Vangent, 2002b).

In regression Models 2 - 4, none of the EI variables were able to predict any of

the perceived leadership outcomes variables (satisfaction, effectiveness and extra

effort). This underlines the limitations of using the Mayer and Salovey (1997) model

of EI in this context when multiple ratings of leadership have been obtained. The

findings of regression Model 3 were contrary to the findings of the studies by Bardoch

(2008), Kerr et al. (2006), Rosete and Ciarrochi (2005), and the meta-analysis by

Mills (2009), all of which indicated that higher EI scores were associated with higher

levels of leader effectiveness. Notably, the measures of leader effectiveness used in

these studies varied from the perceived outcomes measured by the MLQ (Avolio et

al., 1995) in the Main Study of this project which may go some way to explaining the

difference in the findings. However, taking into account that transformational

leadership shared significant positive correlations with each of the perceived

leadership outcomes variables in the Main Study and that EI was unable to predict

transformational leadership, it is most likely that this outcome simply reflects the

inability of EI to predict any of the perceived leadership outcomes variables.

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Regarding transactional leadership, none of the EI variables predicted the

contingent reward scale of transactional leadership in regression Model 5. This

finding differed somewhat from the findings of Harms and Crede (2010) who reported

that EI had a positive relationship with the contingent reward scale. Openness

predicted a small amount of variance in the contingent reward scale. In regression

Models 6 - 9, none of the EI variables predicted the management-by-exception scale

of transactional leadership at any of the four levels at which is was examined.

In regression Model 10, the understanding emotions branch of EI was found to

predict passive/avoidant leadership. This was an interesting finding as it is useful to

be able to identify leaders who are likely to consistently engage in passive/avoidant

leadership behaviours if only to be aware of their limitations in a leadership role.

However, as the amount of variance predicted in passive/avoidant leadership was

small it is unlikely that human resource practitioners would use the MSCEIT (Mayer

et al., 2002) for the sole purpose of identifying those who would consistently engage

in this style of leadership. However, as Harms and Crede (2010) reported that EI was

negatively related to passive/avoidant leadership in their meta-analysis, this

relationship does require further investigation.

Although several researchers have proposed that there is a relationship

between EI and leadership (George, 2000; Prati et al., 2003), taking into account the

findings of the Main Study this relationship seems minimal in Australian educational

institutions. EI was only able to predict a small amount of variance in one of the

leadership style and perceived leadership outcomes variables, specifically;

passive/avoidant leadership.

Conclusion

The inferential component of the Main Study examined the usefulness of EI as

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a predictor of leadership style and perceived leadership outcomes. EI was assessed to

determine whether or not it was a better predictor of transformational leadership and

perceived leadership outcomes than the other predictors in the study. The results of

multivariate analysis revealed that only a small amount of variance in

transformational leadership could be accounted for by the predictors in regression

Model 1. Openness and emotional stability (the inverse of neuroticism) were the most

important predictors, followed by GMA (inversely). None of the EI variables were

found to predict transformational leadership or the two transactional leadership scales

(contingent reward and management-by-exception active). Furthermore, none of the

EI variables were able to predict any of the perceived leadership outcomes variables.

The understanding emotions branch of EI was found to predict passive/avoidant

leadership but the amount of variance predicted was small. Overall, EI was not found

to be a useful predictor of leadership style and perceived leadership outcomes in the

Main Study.

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Chapter 7: Discussion, Limitations and Recommendations

Introduction

This project has examined the relationship between EI, leadership style and

perceived leadership outcomes in Australian educational institutions. A cross-

disciplinary approach has been taken in response to the new discourse of

effectiveness, efficiency and accountability which has emerged in the field of

educational leadership in recent years (Christie &Lingard, 2001). The project is set in

the context of a period in which educational researchers are attempting to meet the

mandates of reform-seeking policy makers (Leithwood & Sleegers, 2006). Hence,

researchers have become more interested in leadership theories such as

transformational leadership (Bass, 1985) which originated in the management

literature, and human resource practitioners in educational settings have become more

interested in the assessment and selection methods used in corporate domains.

The benefits of transformational leadership style in organisational settings

(Judge & Piccolo, 2004; Lowe et al., 1996) and educational settings (Chin, 2007;

Leithwoood & Jantzi, 2005) were highlighted in Chapter 2. It was noted that

established predictors of leadership style and leader effectiveness have been unable to

account for much of the variance in transformational leadership, hence the need to

continue to explore constructs such as EI that may be useful predictors. A Pilot Study

and a Main Study were undertaken to answer the main research question: to what

extent is the Mayer and Salovey (1997) model of EI a useful predictor of leadership

style and leadership outcomes? This overarching question was divided into a series of

questions, specifically: Is the Mayer and Salovey (1997) model of EI related to

leadership style and leadership outcomes? Does the Mayer and Salovey (1997) model

of EI have divergent validity from general mental ability (GMA) and personality

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factors? Is the Mayer and Salovey (1997) model of EI able to predict leadership style

and leadership outcomes when multiple ratings of leadership behaviours are obtained?

Does the Mayer and Salovey (1997) model of EI have incremental validity above

other predictors of leadership style and leadership outcomes? These questions were

further sub-divided and became the research questions and hypotheses that were

examined in the project. The impact of role and gender on leadership style and EI

were also examined.

In this chapter, the findings of the project are discussed and the contribution of

the project to the field of leadership studies is outlined with particular reference to

educational leadership. Then, limitations of the project are identified. Finally,

recommendations and implications for researchers and human resource practitioners

in Australian educational institutions are indicated.

Discussion

Leadership research related to EI is littered with projects which have used

different conceptualisations of EI, self-report leadership instruments, various

leadership outcomes as dependent variables, students in the role of leaders and

inadequately sized samples. Hence, some researchers, such as Antonakis et al. (2009)

and Landy (2005), have criticised previous research in the field and called for projects

to incorporate more methodological rigor. The methodology of this project was

designed to move research in the field forward by: using valid and reliable

instruments, controlling for other predictors, obtaining an adequately sized sample of

real leaders as participants and obtaining multiple ratings of leadership behaviours.

The project replicated previous research in the field by using a quantitative

methodology to examine the relationship between EI, leadership style and perceived

leadership outcomes. EI was assessed to establish whether or not it has discriminant

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validity from established predictors of job performance and incremental validity

above these constructs. Predictors were selected from individual difference variables

commonly used to predict leadership behaviours and leader effectiveness (GMA and

personality factors). The project has advanced research in the field by obtaining

multiple ratings of leadership behaviours and by including integrity as an additional

potential predictor. The impact of gender was also examined. The following valid and

reliable psychological tests were used to operationalise the conceptual variables:

leadership styles and perceived leadership outcomes (MLQ, Avolio et al., 1995), EI

(MSCEIT, Mayer et al., 2002), personality factors (BFI, John et al., 1991), GMA

(WPT-Q, Wonderlic, 2003) and integrity (Integrity Express, Vangent, 2002a). A

summary of the research questions, hypotheses, findings and statistical analyses

undertaken in the Pilot Study and Main Study is presented in Table 20.

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Table 20

Summary of Research Questions, Hypotheses and Findings of Each Study

Study Research questions and hypotheses Findings Statistical analysis

undertaken

Pilot studya Hypothesis 1. EI will have discriminant validity from GMA. EI demonstrated discriminant validity from GMA. Correlation

Hypothesis 2. EI will have discriminant validity from personality factors. EI demonstrated discriminant validity from personality factors. Correlation

Hypothesis 3. Total EI scores will be significantly higher for females than for males. Total EI scores were not significantly different for males and females. Independent samples t-test

Hypothesis 4. Transformational leadership scores will be significantly higher for females

than for males.

Transformational leadership scores were not significantly different for males and

females.

Independent samples

t-test Research question 1. Investigate whether there is a positive relationship between EI and

transformational leadership.

Total EI, the experiential area, and the managing emotions and perceiving emotions

branches were positively related to transformational leadership. The strategic area and

the perceiving emotions and using emotions branches were not related to transformational leadership.

Correlation

Research question 2. Investigate whether there is a positive relationship between EI and

perceived leadership outcomes.

EI was not related to perceived leadership outcomes. Correlation

Research question 3. Investigate whether there is a relationship between EI and

transactional leadership (contingent reward and management-by-exception active).

EI was not related to contingent reward. Self-ratings and supervisor ratings of the

managing emotions branch of EI were inversely related to management-by-exception

active.

Correlation

Research question 4. Investigate whether there is a negative relationship between EI and

passive/avoidant leadership.

EI was not related to passive/avoidant leadership. Correlation


Integrity demonstrated discriminant validity from personality factors. Correlation

Main study –

descriptive and measurement

componentb

Hypothesis 1. Total EI will have discriminant validity from personality factors. Total EI demonstrated discriminant validity from personality factors. Correlation

Hypothesis 2. Total EI will have discriminant validity from GMA. Total EI demonstrated discriminant validity from GMA. Correlation Hypothesis 3. Total EI scores will be significantly higher for females than for males. Total EI scores were not significantly different for males and females. Independent samples

t-test


Transformational leadership scores were significantly higher for females than for males. Independent samples t-test

Hypothesis 5. Scores for the contingent reward scale of transactional leadership will be

significantly higher for females than for males.

Contingent reward scores were significantly higher for females than for males.

Independent samples

t-test Hypothesis 6. Scores for the management-by-exception active scale of transactional

leadership will be significantly higher for males than for females.

Management-by-exception active scores were not significantly higher for males than for

females.

Independent samples

t-test Hypothesis 7. Passive/avoidant leadership scores will be significantly higher for males

than for females.

Passive/avoidant leadership scores were significantly higher for males than for females. Independent samples

t-test

Research question 1. Investigate whether scores of transformational leadership vary according to the role of the leader.

No significant difference for scores of transformational leadership according to the role of the leader.

One-way between groups ANOVA

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Study Research questions and hypotheses Findings Statistical analysis undertaken

Research question 2. Investigate whether scores of total EI vary according to the role of

the leader.

No significant difference for scores of Total EI according to the role of the leader. One-way between

groups ANOVA Research question 3. Investigate whether integrity has discriminant validity from

personality factors.

Integrity demonstrated discriminant validity from personality factors. Correlation

Main study –

inferential

componentb

Research question 4. Investigate whether EI predicts transformational leadership. None of the EI branches predicted transformational leadership. Openness, neuroticism

(inversely) and GMA (inversely) were significant predictors.

Multiple regression

Research question 5. Investigate whether EI has incremental validity above GMA in predicting transformational leadership.

EI did not have incremental validity above GMA. None of the EI branches predicted transformational leadership whereas GMA was an inverse predictor.

Multiple regression

Research question 6. Investigate whether EI has incremental validity above personality

factors in predicting transformational leadership.

EI did not have incremental validity above personality factors. None of the EI branches

predicted transformational leadership whereas neuroticism and openness did.

Multiple regression

Research question 7. Investigate whether EI has incremental validity above integrity in

predicting transformational leadership.

None of the EI branches or integrity predicted transformational leadership.

Multiple regression

Research question 8. Investigate whether EI predicts satisfaction (of followers). None of the EI branches predicted satisfaction (of followers). Agreeableness was a significant predictor.

Multiple regression

Research question 9. Investigate whether EI predicts effectiveness (of leader/group). None of the EI branches predicted effectiveness (of individual/group). Openness and

neuroticism (inversely) were significant predictors.

Multiple regression

Research question 10. Investigate whether EI predicts extra effort (by followers). None of the EI branches predicted extra effort (of followers). Openness was a significant

predictor.

Multiple regression

Research question 11. Investigate whether EI predicts the contingent reward scale of transactional leadership.

None of the branches of EI predicted the contingent reward scale of transactional leadership. Openness was a significant predictor.

Multiple regression

Research question 12. Investigate whether EI predicts the management-by-exception

active scale of transactional leadership.

None of the branches of EI predicted the management-by-exception active scale of

transactional leadership.

Multiple regression

Research question 13. Investigate whether EI predicts passive/avoidant leadership. The understanding emotions branch of EI predicted passive/avoidant leadership whereas

the other EI branches did not.

Multiple regression

aN = 25 leaders and 75 other raters of leadership behaviours. bN = 144 leaders and 432 other raters of leadership behaviours.

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Initially, a Pilot Study (N = 25 leaders and 75 raters) made an examination of

the relationship between the variables included in the project. Total EI, the

experiential area, and the managing emotions and perceiving emotions branches of EI,

were found to be positively related to transformational leadership which indicated that

further research was warranted.

In the Main Study, 144 leaders and 432 raters were recruited as participants to

assess the discriminant validity of the instruments and examine the usefulness of EI as

a predictor of leadership style and perceived leadership outcomes. In the descriptive

and measurement component of the Main Study the discriminant validity of the

instruments was assessed. Notably, the MSCEIT (Mayer et al., 2002) demonstrated

discriminant validity from GMA and personality factors. This finding contributes to a

body of work which upon which the boundaries of the EI construct will ultimately be

firmly established. Notably, integrity also demonstrated discriminant validity from the

five factors of personality. The impact of role and gender on leadership style and EI

were also examined, and females were found to be more transformational as leaders

than males. In conjunction with the findings of Bass and Avolio (1994), Bass et al.

(1996) and Eagly et al. (2003) this finding goes some way to confirming that women

are more transformational than men as leaders. The project did not replicate the

findings of previous studies which reported that females scored significantly higher

on tests of EI than males (Mayer & Geher, 1996; Mayer, Caruso, & Salovey, 1999;

Mayer et al., 2004). However, as this is a fairly well established claim, it seems likely

that this finding is specific to this project and may simply have been the result of the

difference in gender scores failing to reach statistical significance.

In the inferential component of the Main Study, multiple regression

procedures were used to examine the usefulness of EI as a predictor of leadership

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style and perceived leadership outcomes. None of the EI branches were found to be

related to transformational leadership. Although most of the variance in

transformational leadership scores remained unexplained, openness, emotional

stability (the inverse of neuroticism) and general mental ability (inversely) each

predicted a small amount of variance in transformational leadership. None of the EI

branches predicted the contingent reward scale of transactional leadership. Openness

was found to be a significant predictor of contingent reward. Furthermore, none of the

EI branches predicted the management-by-exception active scale of transactional

leadership at any of the four rating levels at which it was assessed (self-ratings,

supervisor ratings, peer ratings and follower ratings). Passive/avoidant leadership was

inversely predicted by the understanding emotions branch of EI.

One of the most surprising findings in the Main Study was the negative

relationship between GMA and transformational leadership. This may have been the

result of a restriction of range in the sample. Alternatively, GMA scores above a

certain threshold may not be useful for predicting transformational leadership.

Another possible explanation is that leaders with higher scores on GMA may focus on

behaviours which are outside the boundaries of transformational leadership, such as

the behaviours representative of instructional leadership.

No significant relationships were found between the EI variables and any of

the perceived leadership outcomes variables (satisfaction, effectiveness and extra

effort) in the Main Study. Although several previous studies have found that EI is a

useful predictor of leader effectiveness (Mills, 2009) the outcome measures used to

assess leader effectiveness have varied in previous research. Hence, it is difficult to

compare the findings of the Main Study in this project with the findings from previous

research related to EI and leader effectiveness. Overall, EI was not found to be a

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useful predictor of leadership style and leadership outcomes in the Main Study of this

project.

With reference to current EI tests in general Antonakis et al. (2009, p. 248)

assert that “given the sparse empirical evidence, it is unethical and unconscionable to

use these measures in applied settings”. Hence, EI measures clearly require further

development (Antonakis et al., 2009) before it is possible to ascertain if the EI

construct is a useful predictor of leadership behaviours.

Regarding the potential to develop EI, it is worth noting that the two

participants with the highest scores on the MSCEIT (Mayer et al., 2002) in this

project had previously attended an EI development course. Although it is not possible

to state that the course had increased their emotional knowledge without knowing

how they rated prior to taking the course, it is an interesting point nonetheless which

may have implications for the development of EI. Perhaps the EI course did increase

their emotional knowledge, or perhaps the course simply enabled them to score more

highly on whatever it is that the MSCEIT (Mayer et al., 2002) is measuring. More

research which firmly establishes the construct validity of EI is required before efforts

to develop EI can be validated.

The project has made several important contributions to theory and

professional practice in the field. Firstly, the findings have resulted in an increase in

the theoretical understanding of the relationship between EI, leadership style and

perceived leadership outcomes. Secondly, the findings have contributed to a body of

knowledge assessing the usefulness of EI as a predictor of leadership style and

leadership outcomes. Thirdly, further knowledge related to the antecedents of

transformational leadership has been be gained by the assessment of the other

predictors included in the project (GMA, personality factors and integrity). Finally,

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the application of the findings by human resource practitioners may contribute to

improved methods of leadership assessment and selection in Australian educational

institutions.

Limitations

The project was subject to the usual limitations associated with quantitative

methods, cross-sectional designs and psychological testing methods. The use of a

quantitative methodology, rather than a qualitative or mixed-methodology, may have

resulted in some contextual details, motivating actions and subjective meanings being

overlooked.

A cross-sectional design was selected for the project but it should be noted

that unlike longitudinal designs, cross-sectional designs only provide a snapshot of the

phenomena of interest and do not take into account changes over time (Hussey &

Hussey, 1998). Furthermore, although cross-sectional designs enable correlations to

be identified they do not facilitate an explanation regarding why a correlation exists.

Regarding sample size, the sample for the Pilot Study (N = 25 leaders and 75 raters)

was too small to undertake multivariate statistical analysis and the results of the

bivariate analysis must be interpreted with much caution. Also, the sample for the

Main Study (N = 144 leaders and 432 raters) may not have been large enough to

effectively identify small effects in accordance with the guidelines for sample size

outlined by Cohen (1998).

Although valid and reliable psychological tests were employed in the project it

is important to recognise that these tests are only tools to be used as part of any

assessment and selection process in the workplace. As psychological tests often

attempt to measure hypothetical constructs that are not expressed directly by

behaviour, differences highlighted by the findings of a test do not necessarily reflect

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actual individual differences (Urbina, 2004).

Several limitations can be identified in relation to the tests selected to

operationalise the conceptual variables in the project. Factor analysis was not

undertaken on the tests due to the inadequate size of the sample in the case of The BFI

(John et al., 1991), MSCEIT (Mayer et al., 2002), and MLQ (Avolio et al., 1995).

Although the sample size was large enough to undertake factor analysis on the WPT-

Q (Wonderlic, 2003) and Integrity Express (Vangent, 2002a), the relevant data was

withheld by the publishers and was not made available for analysis. Hence, it was not

possible to confirm the factor structure of these tests.

The validity of the MLQ (Avolio et al., 1995) data collected could have been

increased by engaging more raters per focal leader. However, it was not practical to

do this as all participants were volunteers and it was difficult enough to ensure that

the number of raters invited to participate in the project completed their tasks.

The EI construct is still evolving and the fact that different models of EI exist,

raises concerns about the construct validity of the EI model selected for this or any

other project. It would have been beneficial to include a mixed measure of EI, such as

the EQ-i (Bar-On, 1995), in the project in order to compare its impact on the

leadership variables with the MSCEIT (Mayer et al., 2002) and assess its relationship

with other the predictors. However, taking into account the additional time that would

have been required for each participant to complete another measure this was

considered to be impractical. In this project, the MSCEIT (Mayer et al., 2002)

demonstrated discriminant validity from GMA and personality factors. Therefore, the

MSCEIT (Mayer et al., 2002) is measuring something substantially different to GMA

and personality factors but exactly what it is measuring remains debatable.

The test selected to operationalise GMA, the WTP-Q (Wonderlic, 2003), is a

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very short 30-item measure which contains only a few items which make it possible to

differentiate between respondents with high scores. This limitation may have

facilitated a restriction of range in GMA scores in the sample.

Finally, the antecedents of leadership behaviours and leader effectiveness

included in this project were not exhaustive as the project took a leader-focused,

individual differences approach. Therefore, the characteristics of followers and the

situation were not assessed.

Recommendations

The findings of this project have implications for researchers in the field and

human resource practitioners in Australian educational institutions. Several

recommendations can be made regarding the direction of future research and the

implementation of these findings in the workplace. Further research which takes a

cross-disciplinary approach to educational leadership would be useful taking into

account the discourse of effectiveness, efficiency and accountability which has

emerged in the field (Christie & Lingard, 2001).

As so much of the variance in transformational leadership scores remained

unexplained in this project more research into its antecedents is clearly required.

Although Bass introduced the concept of transformational leadership in 1985 many of

its antecedents remain unknown. Further research which continues to explore

transformational leadership is required as human resource practitioners and

researchers in the field aiming to meet the requirements of reform-seeking policy

makers require answers to questions about the value of this approach to educational

leadership (Leithwood & Sleegers, 2006).

Although a significant positive relationship was found between EI and

transformational leadership in the Pilot Study, this finding was not replicated in the

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Main Study. It is likely that the significant relationship found in the Pilot Study

occurred as a result of the sample size being too small for robust statistical analyses to

be undertaken. Hence, future researchers in the field must ensure that an adequately

sized sample is obtained before making inferences about the relationships between EI

and other variables.

If it is practical to do so, future researchers in the field who administer the

MLQ (Avolio et al., 1995) could engage more raters per focal leader in order to

increase the validity of the leadership data collected. An increase in the number of

raters would also help to protect the identity of each rater if feedback is provided to

the leader in the form of qualitative comments. However, it should be noted that even

ensuring that the number of raters engaged in this project completed their task

required considerable persistence. If there are no restrictions on the amount of time

participants are able to invest in the research a mixed measure of EI, such as the EQ-i

(Bar-On, 1997), could also be administered in order to compare its impact on the

leadership variables with the MSCEIT (Mayer et al., 2002) and assess its relationship

with other predictors such as personality factors, GMA and integrity.

As a result of the findings of this project human resource practitioners in

Australian educational institutions who are already using EI instruments as a form of

leadership assessment and selection need to reassess the suitability of these

instruments. Practitioners may choose to suspend the use of EI measures in their

leadership assessment and selection processes, or delay their introduction until the

construct validity of EI is more firmly established and until such time that empirical

research is able to confirm their predictive validity. Overall, it seems that the MSCEIT

(Mayer et al., 2002) would not be a useful instrument to add to the toolkit of human

resource practitioners seeking to identify potential transformational leaders in

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Australian schools. Clearly, further research is required to assess whether or not the

MSCEIT (Mayer et al., 2002) is a useful predictor of transformational leadership in

other settings when multiple ratings of leadership are obtained. Further research

which examines the construct validity of the MSCEIT (Mayer et al., 2002) is also

required to determine exactly what it is measuring.

Of the five personality factors examined in the project, openness and

emotional stability (the inverse of neuroticism) were found to be useful predictors of

transformational leadership in the Main Study. However, Judge et al. (2002)

suggested that certain personality factors are more useful in some workplace contexts

than in others. Therefore, more research is required to confirm which personality

factors are useful predictors of transformational leadership style in educational and

other vocational settings. Bono and Judge (2004) also proposed that whilst a broad

model of personality, such as the five-factor model, is a useful framework for

cumulating research results, using narrower traits may be more suitable for predicting

leadership behaviours. Furthermore, Bono and Judge (2004) suggested that the focus

on ratings of specific leadership behaviors in the workplace, rather than broad

leadership constructs in laboratory settings, may reduce the extent to which

personality theories are able to account for aspects of leadership. Therefore, further

research aimed at uncovering the dispositional bases of leadership behaviours could

focus on the specific traits relevant for each type of leadership behavior.

Taking into account the negative relationship found between GMA and

transformational leadership in the Main Study, more research is required to clarify

whether or not GMA scores above a certain threshold are actually useful for

predicting transformational leadership. If the finding of the Main Study is replicated,

human resource practitioners in educational institutions should place less emphasis on

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GMA scores in leadership assessment and selection procedures. The longer WPT

(Wonderlic, 1992) would be more suitable than the WPT-Q (Wonderlic, 2003) for

operationalising GMA in future studies in order to minimise the possibility of a

restriction of range in the sample.

Although a significant relationship was not found between transformational

leadership and integrity in this project further research which examines this

relationship is warranted taking into account that the removal of a single outlier from

the integrity data was able to change this outcome. However, it is recommended that a

longer measure of integrity than the 16-item Integrity Express (Vangent, 2002a)

should be employed. Future research related to integrity and leadership behaviours

may require the development of a suitable measure of integrity.

Regarding the impact of role on transformational leadership style, there is

scope for some Australian schools to introduce a leadership style assessment tool such

as the MLQ5X (Avolio et al., 1995) in their methods to identify potential

transformational leaders, as those identified as the most transformational were not

consistently found in the highest leadership position (e.g., principal). It also seems

that there is scope to develop transformational leadership behaviours in existing

leaders in Australian educational institutions.

Scores for EI did not vary according to role in this project. In light of this

finding it cannot be recommended that human resource practitioners attempt to seek

out those with higher EI scores for higher level leadership positions in schools simply

because they score highly on the MSCEIT (Mayer et al., 2002). Further research

would need to establish that the MSCEIT (Mayer et al., 2002) is measuring something

useful before such a recommendation could be made.

As females were found to be more transformational than males in the Main

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Study, human resource practitioners need to take into account the impact of gender

when assessing potential or existing leaders in Australian educational institutions. The

case for females to be considered for leadership roles is strengthened by the other

gender related findings in the project as females demonstrated more contingent reward

behaviours than males, and males demonstrated more passive/avoidant leadership

behaviours than females. Further research is required to determine whether certain

traits may enable females to be more transformational than males as leaders, or

whether females work harder to be transformational leaders in order to overcome the

potential for gender-bias in the workplace.

The use of various measures to operationalise theoretical constructs makes it

difficult to compare the findings from previous research and reach solid conclusions

about the predictive validity of EI in this context. Hence, future researchers in the

field should use established measures to compare their findings with the findings of

others. More research is also required which compares the impact of transformational

leadership with objective measures of student outcomes rather than the outcomes

perceived by stakeholders. Additionally, research related to the effects on students of

alternative approaches to leadership is required. Finally, further comparative research

which examines the relationship between EI and leaderships styles and leadership

outcomes in other vocational settings would be useful.

Conclusion

This project began by reviewing the literature related to the most important

leadership theories, including full range leadership (Avolio, 1999; Bass, 1999) and

transformational leadership (Bass, 1985). As transformational leadership is known to

have many benefits in organisational settings (Judge & Piccolo, 2004; Lowe et al.,

1996), including in educational settings (Chin, 2007; Leithwoood & Jantzi, 2005), the

202

importance of identifying transformational leaders was highlighted. As established

predictors of leadership style and leader effectiveness have been unable to account for

all of the variance in transformational leadership style the need to continue to explore

constructs which may be useful predictors was noted, and EI was identified as a

promising construct in this respect. Subsequently, the three main conceptualisations of

EI were described, compared and assessed, and a case for the superiority of the

Salovey and Mayer (1997) 'abilities' model was presented. Then, the literature which

has used psychological testing methods to examine the relationship between EI,

leadership style and leadership outcomes was reviewed. Subsequently, a design

framework for a project set in Australian educational institutions was presented to

address the main research question: to what extent is the Mayer and Salovey (1997)

model of EI a useful predictor of leadership style and leadership outcomes?

Initially, a Pilot Study (N = 25 leader and 75 raters) was undertaken to make a

preliminary examination of the relationship between the variables of interest and

investigate whether further research was warranted. The results of correlation analysis

indicated that total EI, the experiential area, and the managing emotions and

perceiving emotions branches were found to be positively related to transformational

leadership. It was noted that as the sample size for the Pilot Study was small, the

results needed to be interpreted with caution, but further studies were warranted.

Then, in the descriptive and measurement component of the Main Study (N =

144 leaders and 432 raters) the discriminant validity of the instruments selected for

the project was tested. EI was considered to have discriminant validity from

personality factors and GMA. Additionally, the impact of role and gender on

leadership style and EI were examined. Results indicated that levels of

transformational leadership and EI did not vary according to role. Females were

203

perceived to demonstrate more transformational leadership behaviours and more

contingent reward (transactional leadership) behaviours than males, whilst males were

perceived to engage in more passive/avoidant leadership behaviours than females.

There was no significant difference between males and females for scores of EI.

In the inferential component of the Main Study, the usefulness of EI as a

predictor of leadership style and perceived leadership outcomes was examined. EI

was also assessed to determine whether or not it was a better predictor of

transformational leadership and perceived leadership outcomes than other predictors

included in the study. The results of multivariate analysis revealed that only a small

amount of variance in transformational leadership could be accounted for by the

predictors. Openness and emotional stability (the inverse of neuroticism) were the

most important predictors, followed by GMA (inversely). None of the EI variables

were found to predict transformational leadership or the transactional leadership

scales (contingent reward and management-by-exception active). Openness was found

to predict the contingent reward scale of transactional leadership. The understanding

emotions branch of EI was found to predict passive/avoidant leadership but the

amount of variance predicted was small. Furthermore, none of the EI variables were

able to predict any of the perceived leadership outcomes variables. Overall, EI was

not found to be a useful predictor of leadership style and perceived leadership

outcomes in this study. Hence, EI is not recommended for use by human resource

practitioners as a means of predicting transformational leadership style in Australian

educational institutions.

The project was subject to the usual limitations associated with quantitative

methods, cross-sectional designs and psychological testing methods. The findings of

the project increase the theoretical understanding of the relationship between EI,

204

leadership style and leadership outcomes, and contribute to a body of literary work

assessing the usefulness of EI as a predictor of leadership style and leadership

outcomes. Ultimately, the application of the findings may contribute to improved

methods of leadership assessment and selection in Australian educational institutions.

Further research which takes a cross-disciplinary approach to educational

leadership would be useful taking into account the discourse of effectiveness,

efficiency and accountability which has emerged in the field (Christie & Lingard,

2001). As so much of the variance in transformational leadership style remained

unexplained in this project more research into the antecedents of transformational

leadership style is clearly required. Personality factors are known to predict

transformational leadership style but more research is required to confirm which

personality factors are useful predictors in educational and other vocational settings.

More research is also required to clarify whether GMA scores above a certain

threshold are useful for predicting transformational leadership style or whether there

is a ceiling beyond which their usefulness diminishes. Additionally, the relationship

between overt integrity tests and leadership behaviours warrants further investigation

to determine if integrity is a useful predictor of transformational leadership. There is

also a need for more research which examines the relationship between leadership

style and objective performance outcomes rather than perceived outcomes. Finally,

further comparative research which examines the usefulness of EI as a predictor of

leadership style and leadership effectiveness in other vocational settings would be

useful.

In summary, this research project has examined the relationship between EI,

leadership style and perceived leadership outcomes in Australian educational

institutions. Overall, EI was not found to be a useful predictor of leadership style and

205

leadership outcomes in this project. Consequently, EI is not recommended for use by

human resource practitioners as a means of predicting transformational leadership

style in Australian educational institutions. The findings of this project go some way

to confirming the limitations of using this conceptualisation of EI to predict leadership

style and leader effectiveness and answer the main research question: to what extent is


leadership outcomes?

206

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Appendix A

Hello, Thank you for your response and for your interest in my educational leadership PhD project. Please read the information below in order to learn more about the project.

Background This research is in the area of educational leadership and is being undertaken by Paul Grunes as a PhD project supervised by Dr Amanda Gudmundsson and Dr Bernd Irmer at Queensland University of Technology (QUT). The project will examine the usefulness of the Mayer and Salovey (1997) model of emotional intelligence as a tool for assessing and selecting transformational leaders (Avolio, 1999; Bass, 1999) and predicting positive leadership outcomes in educational settings.

Transformational leadership is characterised by; idealised attributes, idealised behaviours, inspirational motivation, intellectual stimulation and individualised consideration (Bass, 1990). Many studies have found that transformational leadership is related to positive outcomes for employees and students in educational settings (Leithwood, 1994). Therefore it is important to explore constructs which may predict transformational leadership style. Research interest in emotional intelligence stems from the possibility that it may account for aspects of workplace performance, including leadership style, which cannot be accounted for by other constructs. Mayer and Salovey (1997, p. 10) define emotional intelligence as “the ability to perceive, appraise, and express emotion; to access and/or generate feelings when they facilitate thought; to understand emotion and emotional knowledge; and to regulate emotions to promote emotional and intellectual growth”.

Many practitioners believe that much more is known about emotional intelligence than has actually been found by empirical research. Although several studies in non-educational settings claim to have found that emotional intelligence is a useful predictor of transformational leadership style there is a paucity of studies which have examined the Mayer and Salovey (1997) model of emotional intelligence in educational settings. Hence, many questions about the relationship between emotional intelligence and leadership remain unanswered. Therefore, the introduction of emotional intelligence questionnaires in leadership assessment processes in some educational settings may have been premature.

This project will assess whether emotional intelligence has discriminant validity from, and incremental validity above, individual differences-based variables used to predict leader emergence and leader effectiveness in the field of personnel psychology (general mental ability, personality factors, integrity). The effect of gender will also be examined. Ultimately, the project aims to provide human resources personnel in educational settings with an empirical platform on which to base decisions to introduce, or relinquish, the use of emotional intelligence questionnaires in their leadership assessment and selection processes.

Participation You must fulfill an educational leadership role to be eligible to participate in this project. Your participation is voluntary and will not impact upon your current or future relationship with QUT. You will be allocated a personal project code which will enable you to keep your identity confidential. Only Paul Grunes (Chief Investigator) will be able to match your identity to your responses. You will be able to withdraw from the project at any time without penalty.

You will be asked to complete a battery of online questionnaires at a location of your choice (e.g., home or office). Each questionnaire is considered to be the benchmark, or a derivative of the benchmark, in the specific area of individual differences that it represents. It is

PARTICIPATION IN QUT LEADERSHIP RESEARCH PROJECT

An examination of the relationship between emotional intelligence, leadership style and perceived leadership outcomes in an educational context

227

estimated that it will take a total of 50-60 minutes to complete the five questionnaires representing:

Emotional intelligence

General mental ability

Personality factors Integrity

Leadership style and outcomes You will also be asked to nominate a workplace supervisor, a peer and a subordinate to complete the leadership style and outcomes questionnaire in order to compile a 360-degree, or „multi-rater‟ profile, of your leadership behaviours. Your nominees for this task will receive an email informing them of the procedure. The questionnaire will take your nominees approximately five minutes to complete online and their responses will remain confidential. Expected benefits If you choose to participate you will be eligible to receive feedback based on your responses to the emotional intelligence, leadership and personality questionnaires. Additionally, you may request information about the findings of the completed project.

It is anticipated that other researchers in this field may benefit from an increased understanding of the constructs under investigation as a result of the findings of the project. Ultimately, the application of these findings may lead to improved methods of leadership assessment and selection in educational settings in Australia.

Ethical Clearance The project has been reviewed as Human Ethics Level 1 by the QUT Research Ethics Unit and confirmed as meeting the requirements of the National Statement on Ethical Conduct of Research Involving Humans. If you have any concerns about the ethical conduct of the project you may contact the QUT Research Ethics Officer. Confidentiality You will be allocated a personal project code to use which will enable you to keep your identity confidential. Only the Chief Investigator, Paul Grunes, will be able to match your identity to your responses. The data from the questionnaires will be securely stored during and after the study.

Consent to participate The return of the completed questionnaires will be accepted as an indication of your consent to participate in the project.

Confirming your interest in participating Please reply by email to Paul Grunes to confirm your interest in participating in the project. Once you have been confirmed as a participant you will be sent an email containing the information you will require to complete the questionnaires.

When your reply, if you would like to participate please: A. Provide you age (in years) in order to be allocated your project code.

B. Provide the names, email addresses and positions of your nominated raters (a supervisor, a peer and a subordinate) for the leadership style and outcomes questionnaire. Thank you for your consideration. I look forward to hearing from you soon.

Paul Grunes BBus(BusPsych), GradDipPsych with Distinction, MBA with Distinction, PhD Candidate

228

References Avolio, B. (1999). Full leadership development: Building the vital forces in organizations.

Thousand Oaks, CA: Sage. Bass, B. M. (1990). Bass & Stogill's handbook of leadership: Theory, research & managerial

applications (3rd ed). New York, NY: The Free Press. Bass, B. M. (1999). Two decades of research and development in transformational

leadership. European Journal of Work and Organizational Psychology, 8(1), 9-32. Leithwood, K. (1994). Leadership for school restructuring. Educational Administration

Quarterly, 30(4), 498-518. Mayer, J. D., & Salovey, P. (1997). What is emotional intelligence? In P. Salovey, & D. Sluyter

(Eds.), Emotional development and emotional intelligence: Implications for educators (pp. 3-31). New York, NY: Basic Books.

School of Management | Faculty of Business | Queensland University of Technology

www.bus.qut.com | CRICOS No. 00213J

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Appendix B

An examination of the relationship between emotional intelligence, leadership style and

perceived leadership outcomes in an educational context

Paul Grunes (Chief Investigator) Phone: Deleted Email: Deleted

Dr Amanda Gudmundsson (Principal Supervisor) Dr Bernd Irmer (Associate Supervisor)

Phone: Deleted Phone: Deleted

Email: Deleted Email: Deleted

Dear Example, Please save this document to your hard-drive. Then, follow the instructions provided to complete the questionnaires. It is estimated that it will take approximately one hour to complete the five questionnaires. Your project code is: xym43

General instructions for completing the questionnaires

You will access the five questionnaires by visiting four different websites (copyright restrictions prevent us from loading the items onto a single website).

Report any technical problems to Paul Grunes

To save time it is recommended that you do not answer the publishers‟ optional demographic questions at the beginning of each questionnaire.

In order to keep your identity confidential use your project code instead of your name.

When you have answered all of the items in a questionnaire and submitted your responses, close the window, return to these instructions and move on to the next questionnaire.

You may choose to complete the five questionnaires in more than one sitting if necessary. However, you will not be able to partially complete a questionnaire and return to finish the same questionnaire later.

Specific instructions for completing the questionnaires

Website 1: QUT Questionnaire

Copy and paste the URL below into your address bar (or press CTRL and click the URL) to access the website:

http:// Deleted Signing-in and required fields:

Enter your project code: xym43 You will be asked to complete two questionnaires on this website: Multifactor Leadership Questionnaire

A measure of leadership style and outcomes

Approximate duration: 7 mins. The Big Five Inventory

A measure of personality factors.

Approximate duration: 4 mins.

INSTRUCTIONS FOR LEADERSHIP RESEARCH PROJECT

230

Website 2: Mayer-Salovey-Caruso Emotional Intelligence Test

A measure of emotional intelligence.

Approximate duration: 20–35 mins.

Press CTRL and click the URL below to access the questionnaire website: http:// Deleted Signing-in and required fields:

Select Language: English-United States Code: Deleted Password: Deleted Enter your project code as follows: First Name: xym43 Last Name: Deleted

Website 3: Integrity Express

A measure of integrity.

Approximate duration: 2 mins.

Press CTRL and click the URL below to access the questionnaire website: http:// Deleted Signing-in and required fields:

Enter your project code: xym43

Website 4: Wonderlic Personnel Test – Quicktest

A measure of general mental ability.

Duration: 8 mins (Note: This questionnaire will time out after 8 minutes).

To access the questionnaire website open the email forwarded to you by Paul Grunes

with the title “Assessment Invitation from Queensland University of Tech - Wonderlic

Personnel Test – QuickTest”. Then, press the „click here‟ button on the email. Signing-in and required fields:

Enter your project code as follows: First Name: xym43 Last Name: Deleted Phone: click “international” box

Thank you for completing the questionnaires. Your nominees for the 360-degree appraisal of your leadership behaviours will receive an email with the title “Leadership Rating Request”. The email will include a link to the Multifactor Leadership Questionnaire. Information about the findings of the completed project will be available on request. You are welcome to provide feedback related to your experience as a participant. Thank you for very much for participating in this project. Paul Grunes BBus(BusPsych), GradDipPsych with Distinction, MBA with Distinction, PhD Candidate

School of Management | Faculty of Business | Queensland University of Technology

www.bus.qut.com

231

Appendix C

An examination of the relationship between emotional intelligence, leadership style and perceived leadership outcomes in an educational context

Paul Grunes (Chief Investigator) Phone: Deleted Email: Deleted

Dr Amanda Gudmundsson (Principal Supervisor) Dr Bernd Irmer (Associate Supervisor)

Phone: Deleted Phone: Deleted

Email: Deleted Email: Deleted

Hello,

Example has nominated you as a peer who can provide leadership ratings of him as part of a leadership research project he is participating in.

Your participation will take approximately fifteen minutes. There are other raters also completing this questionnaire. Your ratings will be aggregated with the other ratings to provide feedback. This aggregation is to assist you in providing direct and honest feedback as you will not be identified by your ratings.

You will also have the opportunity to provide written feedback to three questions at the end of the questionnaire. Your responses to these three questions will be provided as feedback.

To complete your rating please access the following website by copying and pasting the URL below into your address bar:

http:// Deleted Use the project access code: xym43/1 Your organisational level: same

Report any technical problems to Paul Grunes by email.

All data collection will cease on Friday 30th May. Thank you very much for your assistance.

Kind regards,

Paul Grunes BBus(BusPsych), GradDipPsych with Distinction, MBA with Distinction, PhD Candidate

INSTRUCTIONS FOR LEADERSHIP RESEARCH PROJECT

an examination of the relationship between emotional intelligence

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