Assessing the Relationships Between Person …Assessing the Relationships Between...

Assessing the Relationships Between Person-Organization Fit,

Moral Philosophy, and the Motivation to Lead

Dissertation

Submitted to Northcentral University

Graduate Faculty of the School of Psychology

in Partial Fulfillment of the

Requirements for the Degree of

DOCTOR OF PHILOSOPHY

by

ELENA MARIE PAPAVERO

Prescott Valley, Arizona January 2009

Copyright Notice

© Copyright 2009

Elena Marie Papavero

Approval



by


Approved by: Chair: William G. Shriner, PhD Date Member: Robert Haussmann, PhD Member: Nadira Tidwell Pardo, PhD Certified by: School Chair: Heather Frederick, PhD Date

iv

Abstract



by


Northcentral University, January 2009

When individuals who perceive their values as different from those of their

organization (low PO fit) are less motivated to lead, values homogeneity in leadership

may occur, resulting in ethical dysfunction. Likewise, if idealists are less attracted to

leading, this may influence homogeneity towards pragmatism. The primary goal of this

research was to explore the prediction of three dimensions of motivation to lead (MTL)

from PO fit and idealism. The interaction of PO fit and relativism was also examined. An

online survey, including Cable and DeRue’s fit measure, Forsyth’s EPQ, and Chan’s

MTL scale, was completed by 1,024 working adults. Lower fit predicted lower MTL on

all dimensions, and higher idealism predicted lower MTL on all dimensions (with social-

normative MTL receiving limited support). No support was found for relativism as a

moderator of the fit to MTL relationship. These results suggest that low fit individuals are

self-selecting away from leadership positions. Practical recommendations include

considering fit in advancement processes and using fit as a gap-analysis diagnostic for

organizational values misalignment. Future research on a situational model of MTL

should consider situations that promote involvement or identification with organizations

v

and objectives, and those that create a lack of alternatives or a sense of obligation due to a

psychological contract.

vi

Acknowledgments

I would like to express great appreciation to my chairperson, Dr. William Shriner,

for his steady guidance and enthusiastic support of my ideas, and to my committee

members, Dr. Robert Haussmann and Dr. Nadira Pardo, for their patience and wisdom. I

would also like to thank my external reviewer, Dr. Jon Billsberry, for providing

inspiration, and for freely sharing his knowledge and insights. The support and

camaraderie of my school colleagues, especially Judy Kelly and Brian Cesario, made a

world of difference, not only instrumentally, but also in the inspiration provided by their

demonstrations of intellectual curiosity, will, and spirit. Finally, I would like to

acknowledge all family, friends, and work colleagues who supported this effort, with

special thanks to Marc Saxton for his interest and faith in my work, and for his special

talent for listening.

vii

Table of Contents

Copyright Notice ................................................................................................................. ii

Approval ............................................................................................................................ iii

Abstract .............................................................................................................................. iv

Acknowledgments.............................................................................................................. vi

List of Tables ...................................................................................................................... x

List of Figures ................................................................................................................... xii

Chapter 1: Introduction ....................................................................................................... 1

Background ..................................................................................................................... 3

Problem Statement .......................................................................................................... 4

Purpose of the Study ....................................................................................................... 5

Conceptual Framework ................................................................................................... 5

Research Questions ......................................................................................................... 8

Hypotheses ...................................................................................................................... 9 Hypotheses for PO fit and motivation to lead. ........................................................ 9 Hypotheses for PO fit, relativism, and motivation to lead. ................................... 12 Hypotheses for idealism and motivation to lead. .................................................. 14

Definition of Terms....................................................................................................... 16

Limitations .................................................................................................................... 18

Summary and Conclusions ........................................................................................... 19

Chapter 2: Review of the Literature .................................................................................. 21

Introduction ................................................................................................................... 21

Conceptualizing Person-Organization Fit ..................................................................... 21 The person-organization fit focus. ........................................................................ 21 Choosing a PO fit interaction type. ....................................................................... 22 Operationalizing PO fit with values. ..................................................................... 27 Choosing a view of PO fit. .................................................................................... 28 PO misfit. .............................................................................................................. 32 Conceptualizing PO fit in the present study. ........................................................ 35

PO Fit and the Motivation to Lead ............................................................................... 37

viii

Individual outcomes of PO fit. .............................................................................. 37 Organizational outcomes of PO fit. ...................................................................... 39 How PO fit changes. ............................................................................................. 42 PO fit, individual characteristics, and situation. ................................................... 44 Ethical fit. .............................................................................................................. 45

Moral Philosophy and the Motivation to Lead ............................................................. 48 PO fit and moral philosophy. ................................................................................ 48 Moral philosophy overview. ................................................................................. 48 PO fit, ethical conflict, and relativism. ................................................................. 52 Ethical conflict, relativism, and the motivation to lead. ....................................... 54 Idealism and the motivation to lead. ..................................................................... 61

Conceptualizing and Studying Motivation to Lead ...................................................... 63 Theoretical model of the motivation to lead. ........................................................ 64 The motivation to lead construct........................................................................... 65 Relevant studies using Chan’s motivation to lead construct. ............................... 68 Studies on motivation to lead and situation. ......................................................... 70

Motivation to Lead Antecedents ................................................................................... 73 Personality trait antecedents and situation. ........................................................... 73 Values antecedents and situation. ......................................................................... 76 Leadership antecedents and situation. ................................................................... 78 Summary of motivation to lead antecedents and situation. .................................. 78

Summary of Literature Review ..................................................................................... 78

Chapter 3: Methodology ................................................................................................... 80

Overview ....................................................................................................................... 80

Restatement of Hypotheses ........................................................................................... 80

Research Design............................................................................................................ 82

Operational Definition of Variables .............................................................................. 82

Instrumentation ............................................................................................................. 83

Sampling ....................................................................................................................... 85 A priori power calculations. .................................................................................. 85 Selection of participants. ....................................................................................... 89

Procedures ..................................................................................................................... 90

Data Analysis ................................................................................................................ 91

Methodological Assumptions, Limitations, and Delimitations .................................... 92

Ethical Assurances ........................................................................................................ 93

Summary ....................................................................................................................... 94

Chapter 4: Findings ........................................................................................................... 95

ix

Overview ....................................................................................................................... 95

Data Preparation............................................................................................................ 95

Sample Description ....................................................................................................... 96

Common Method Variance ........................................................................................... 97

Nonresponse Bias.......................................................................................................... 97

Descriptive Statistics ................................................................................................... 100

Tests of Statistical Assumptions ................................................................................. 101

Hypothesis Testing Procedure .................................................................................... 103

Hypothesis Testing...................................................................................................... 105 Hypothesis testing for PO fit and motivation to lead. ......................................... 105 Hypothesis testing for PO fit, relativism, and motivation to lead. ...................... 108 Hypothesis testing for idealism and motivation to lead. ..................................... 110

Summary of Findings .................................................................................................. 112

Supplemental Analysis................................................................................................ 114

Chapter 5: Discussion ..................................................................................................... 117

Conclusions for PO Fit and Motivation to Lead ......................................................... 118

Conclusions for PO Fit, Relativism, and Motivation to Lead..................................... 120

Conclusions for Idealism and Motivation to Lead ...................................................... 121

Practical Implications.................................................................................................. 123

Study Limitations ........................................................................................................ 126

Recommendations for Future Motivation to Lead Research ...................................... 127

Recommendations for Future PO Fit Research .......................................................... 128

Recommendations for Future Moral Philosophy Research ........................................ 131

Recommendations for Future Group Differences Research ....................................... 133

Epilogue ...................................................................................................................... 134

References ....................................................................................................................... 138

Appendix A: Scale Items ................................................................................................ 158

Appendix B: Request for Participation ........................................................................... 161

Appendix C: Informed Consent, Survey, and Debriefing............................................... 162

Appendix D: Additional Statistical Tables and Figures ................................................. 171

x

List of Tables

Table 1. Hierarchical Multiple Regression: A priori Power Calculation ........................ 86

Table 2. Moderated Multiple Regression: A priori Power Calculation Not Considering Coefficient Differences .............................................................................................. 87

Table 3. Moderated Multiple Regression: A priori Power Calculation Considering Coefficient Differences .............................................................................................. 88

Table 4. Personal Characteristics .................................................................................... 98

Table 5. Job and Organization Characteristics ................................................................ 99

Table 6. Coefficient Alphas, Correlations, Means, and Standard Deviations for Study Variables ................................................................................................................. 100

Table 7. Correlations of Characteristics and Study Variables ....................................... 115

Table 8. One-Way Analyses of Variance for Ethnicity on Study Variables .................... 116

Table 9. Means and Standard Deviations for Study Variables and Age ........................ 171

Table 10. Means and Standard Deviations for Study Variables and Gender ................. 171

Table 11. Means and Standard Deviations for Study Variables and Educational Level 172

Table 12. Means and Standard Deviations for Study Variables and Work Experience . 172

Table 13. Means and Standard Deviations for Study Variables and Leadership Experience ............................................................................................................... 173

Table 14. Means and Standard Deviations for Study Variables and Ethnicity .............. 173

Table 15. Means and Standard Deviations for Study Variables and Job Tenure........... 174

Table 16. Means and Standard Deviations for Study Variables and Job Level ............. 174

Table 17. Means and Standard Deviations for Study Variables and Employment Status ................................................................................................................................. 175

Table 18. Means and Standard Deviations for Study Variables and Organization Size 175

Table 19. Means and Standard Deviations for Study Variables and Organization Tenure ................................................................................................................................. 176

Table 20. Summary of Hierarchical Regression Analysis for PO Fit Predicting General Motivation to Lead .................................................................................................. 184

Table 21. Summary of Hierarchical Regression Analysis for PO Fit Predicting Affective-Identity Motivation to Lead ..................................................................................... 185

Table 22. Summary of Hierarchical Regression Analysis for PO Fit Predicting Non-Calculative Motivation to Lead .............................................................................. 186

Table 23. Summary of Hierarchical Regression Analysis for PO Fit Predicting Social-Normative Motivation to Lead ................................................................................ 188

xi

Table 24. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict General Motivation to Lead ................................................ 189

Table 25. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Affective-Identity Motivation to Lead .................................. 190

Table 26. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Non-Calculative Motivation to Lead ................................... 191

Table 27. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Social-Normative Motivation to Lead ................................. 192

Table 28. Summary of Hierarchical Regression Analysis for Idealism Predicting General Motivation to Lead .................................................................................................. 193

Table 29. Summary of Moderated Regression Analysis for Idealism Predicting Affective-Identity Motivation to Lead ..................................................................................... 194

Table 30. Summary of Hierarchical Regression Analysis for Idealism Predicting Non-Calculative Motivation to Lead .............................................................................. 195

Table 31. Summary of Hierarchical Regression Analysis for Idealism Predicting Social-Normative Motivation to Lead ................................................................................ 195

xii

List of Figures

Figure 1. Initial model: Person-organization fit predicting motivation to lead, and idealism predicting motivation to lead. .................................................................... 10

Figure 2. Initial Model: Person-organization fit, as moderated by relativism, predicting motivation to lead. .................................................................................................... 10

Figure 3. Revised model: Person-organization fit predicting motivation to lead, and idealism predicting motivation to lead. .................................................................. 113

Figure 4. Histogram of participants' reported person-organization fit scores with normality curve superimposed. ............................................................................... 177

Figure 5. Normal probability of participants’ reported person-organization fit scores. 177

Figure 6. Histogram of participants' reported idealism scores with normality curve superimposed. ......................................................................................................... 178

Figure 7. Normal probability of participants’ reported idealism scores. ...................... 178

Figure 8. Histogram of participants' reported relativism scores with normality curve superimposed. ......................................................................................................... 179

Figure 9. Normal probability of participants’ reported relativism scores. .................... 179

Figure 10. Histogram of participants' reported general motivation to lead scores with normality curve superimposed. ............................................................................... 180

Figure 11. Normal probability of participants’ reported general motivation to lead scores. ..................................................................................................................... 180

Figure 12. Histogram of participants' reported affective-identity motivation to lead scores with normality curve superimposed. ............................................................ 181

Figure 13. Normal probability of participants’ reported affective-identity motivation to lead scores. ............................................................................................................. 181

Figure 14. Histogram of participants' reported non-calculative motivation to lead scores with normality curve superimposed. ....................................................................... 182

Figure 15. Normal probability of participants’ reported non-calculative motivation to lead scores. ............................................................................................................. 182

Figure 16. Histogram of participants' reported social-normative motivation to lead scores with normality curve superimposed. ............................................................ 183

Figure 17. Normal probability of participants’ reported social-normative motivation to lead scores. ............................................................................................................. 183

1

Chapter 1: Introduction

Organizations are thought to become more homogenous over time through

attraction, selection, attrition, and individual socialization (Schaubroeck, Ganster, &

Jones, 1998; Schneider, 1987; Schneider, Smith, Taylor, & Fleenor, 1998). Individuals

who fit the organization are more likely to be attracted to it, and more likely to be

selected. Those who do not fit tend to leave, although some who do not fit experience a

socialization process that increases fit. In this way, the organization is a function of the

persons behaving in it, rather than the person and environment producing behavior

(Schneider). The definition of fit in this context initially focused on the similarity of

values between person and organization, also known as values congruence (Chatman,

1989, 1991; O’Reilly, Chatman, & Caldwell, 1991), but has since been extended to

encompass types of fit that consider how the person and organization complement one

another on a variety of characteristics. The idea of fit has also been expanded to include

interactions between persons and their jobs, supervisors, peers, and groups, in addition to

the original concept of fit between the person and organization.

Person-organization fit (PO fit) at the individual level is seen as positive,

producing higher commitment, job satisfaction, and lower intention to leave (Davis,

2006; Westerman & Cyr, 2004). However, the desirability of organizational homogeneity

has been questioned (Atwater & Dionne, 2007; Boone, Olffen, Witteloostuijn, &

Brabander, 2004; Giberson, Resick, & Dickson, 2005). In general, it is thought that

homogenous organizations have more difficulty changing in response to increasingly

dynamic external environments. Further, Judge (2008) recently questioned the ethicality

2

of homogenizing around fit, as selecting and socializing for attitudes could be considered

an invasion of individual privacy and an abuse of power.

One area where homogeneity may not be desirable is organizational values. Deep

implicit socialization can lead to values homogeneity in an organization’s leadership

through the promotion process, the opportunity structure, and implicit leader emergence

schemas (Hackman & Wageman, 2007; Rayburn & Rayburn, 1996; Snell, 2000). Snell

proposed that this in turn leads to ethical dysfunction. Snell further suggested that ethical

dysfunction might be necessary for organizational survival. However this has not been

proven and may not always be the case.

Ethics is becoming an increasingly important business issue as business problems,

and the moral dilemmas they produce, become more complex (Bennis, 2007; Nicholson,

1994). Although it is not yet known, it is possible that an organization that is

heterogeneous on values might be better equipped to address complex moral dilemmas

and shape the organization’s ethical standards to reduce ethical dysfunction. Recent

scandals at large corporations give evidence that this question is worthy of exploration

(Ghoshal, 2005).

It is possible that low PO fit at the individual level increases values homogeneity

at the organizational level by diminishing motivation to lead. Therefore, the present study

explored the prediction of motivation to lead from PO fit. The motivation to lead

construct used in the present study is based on commitment (Chan, 1999). Further, an

individual difference, known as moral philosophy, predicts commitment (Peterson, 2003;

Shaub, Finn, & Munter, 1993). An individual’s moral philosophy provides guidelines

used to solve ethical dilemmas. Paralleling previous findings for commitment, moral

3

philosophy was explored as an individual difference that could predict motivation to lead,

and also as a moderator of the relationship between PO fit and motivation to lead.

Background

As mentioned previously, several theories propose that, over time, employees

with low PO fit leave the organization (for example, Schneider’s [1987] attraction-

selection-attrition or ASA theory, and Ponemon’s [1992] studies of the effect of

selection-socialization on the ethics of auditors). However, it is possible that employees

with low PO fit join organizations despite their lack of fit (Chatman, Wong, & Joyce,

2008) and remain with organizations for a variety of reasons related to embeddedness

(Harman, Lee, Mitchell, Felps, & Owens, 2007) or a perceived, or actual, tight

marketplace (Stern, 2003). Further, they may remain with the organization and function

in informal and possibly less influential leadership roles, such as internal networkers

(Senge, 1996) or tempered radicals (Meyerson & Scully, 1995). In practice, identifying

these employees and encouraging their participation makes a contribution to the

organization that includes increased diversity of values. For theory extension, identifying

situational factors that predict motivation to lead is a first step in building a situational

model.

This study also makes other contributions to leadership theory. Another

researcher has proposed an evolutionary psychology theory that those with poor PO fit

might self-select away from leading (Nicholson, 2005). This self-selection away from

leading may be explained, in part, by low motivation to lead. In addition, Ashforth and

Anand (2003) proposed that those with low PO fit might be systematically excluded from

leadership positions. If this proposition were to be tested, the present study suggests a

4

way to determine if self-selection away from leading is occurring rather than, or in

addition to, exclusion.

The study of individuals who avoid leadership roles contributes to a neglected

area in organizational theory. In general, low PO fit on values means the organizational

system is not aligned. Vital information about an organization’s operating values versus

espoused values could be tapped in a positive way by identifying and studying

individuals who self-select away from leading (Papavero, 1999). This could result in

better integration of diverse values within the organization.

Problem Statement

Powell (1998) suggests that diverse values at higher levels of the organization are

more important to extending existing organizational values versus reinforcing them.

Further, Bretz, Ash, and Dreher (1989) suggest that values homogeneity increases with

organizational level. Therefore, one way to increase the values heterogeneity of an

organization would be to diversify the values of those in leadership roles, allowing the

ethics of the current culture to be tested (Thorne & Saunders, 2002). This could be done

by attracting, developing, supporting, and rewarding leaders whose values differ from the

existing organizational culture. However, it is possible that those whose values do not fit

the existing culture are less motivated to move into leadership roles (Papavero, 1999).

To determine if PO fit predicts motivation to lead, a motivation to lead theory and

construct are necessary. Chan’s (1999) motivation to lead framework offers both. Chan’s

motivation to lead theory seeks to explain why individuals choose to lead. His model uses

individual differences to predict motivation to lead. However, the model does not account

for situational aspects, such as PO fit, which may influence motivation to lead. Chan has

5

called for an exploration of situational variables that may influence motivation to lead to

give direction in creating a situational model.

Other individual attributes may contribute to motivation to lead. Past research has

found that moral philosophy predicts commitment (Peterson, 2003; Shaub et al., 1993),

which is an attitude on which Chan’s (1999) motivation to lead construct is based. In

addition, Papavero (1999) found that individuals who rejected promotions exhibited

qualities associated with idealism. These include commitment to profession,

conscientiousness, and intrinsic motivation (Bierly, Kolodinsky, & Charette, in press;

Forsyth, 1992; Shafer, Park, & Liao, 2002b). As the motivation to lead construct is

relatively new, the present research considered whether these findings also apply to

motivation to lead.

Purpose of the Study

In a previous qualitative study of six software engineers, Papavero (1999)

uncovered various factors that contributed to the rejection of advancement offers, most of

which were value laden. The present quantitative study was designed to corroborate and

generalize these findings by examining the relationships between measured perceived

values similarity (also known as perceived supplementary person-organization fit) and

motivation to lead with a larger and more diverse sample.

Conceptual Framework

Chan’s (1999) motivation to lead construct, which is based on Meyer and Allen’s

(1991) model of organizational commitment, has three dimensions: (a) affective-identity

motivation to lead (liking to lead), (b) non-calculative motivation to lead (making a

rational decision to lead), and (c) social-normative motivation to lead (feeling a duty to

6

lead). A person low in non-calculative motivation to lead would lead only if they see a

net benefit. They consider all types of costs, including non-economic ones. Someone

higher in the non-calculative dimension would lead even if there were no net benefit, and

they disregard the costs (although it should be noted that they may not be aware of the

costs).

Chan (1999) identified four major factors that predict motivation to lead: (a)

personality traits, (b) values, (c) leadership self-efficacy, and (d) previous leadership

experiences, all of which interact with the environment (Amit, Lisak, Popper, & Gal,

2007). Chan’s premise is that even though the potential to lead is present, it will not

manifest without motivation to lead. In other words, motivation to lead is essential for

leadership behavior emergence (Popper & Mayseless, 2002).

A first-person perception of how one’s values fit with an organization may be at

least as important as actual fit, especially when the organization does a poor job of

advertising and promoting its values. As Schein (2004) put it so aptly, “if the founders or

leaders are trying to ensure that their values and assumptions will be learned, they must

create a reward, promotion, and status system that is consistent with those assumptions”

(p. 260). Intuitively, it seems that an individual’s motivation to lead could vary depending

on how similar they perceive their values to be to those of the organization. PO fit has

been shown to predict organizational commitment in a number of studies (Cable & Judge,

1996; Chatman, 1991; McConnell, 2003; O’Reilly et al., 1991; Silverthorne, 2004; van

Vianen, 2000; Westerman & Cyr, 2004). As Chan’s (1999) motivation to lead construct

is modeled after a theory of commitment, one might expect to also find that PO fit

predicts motivation to lead. Therefore, PO fit was assessed as a predictor of general

7

motivation to lead, and each of the three correlated dimensions that make up general

motivation to lead: (a) affective-identify motivation to lead, (b) non-calculative

motivation to lead, and (c) social-normative motivation to lead.

Individual differences could change the relationship between PO fit and

motivation to lead. Moral philosophy as defined by Forsyth (1980) is conceptualized

using two orthogonal continuous dimensions: (a) relativism (rejecting universal moral

rules) and (b) idealism (preferring solutions to ethical problems that cause no harm to

others). It is possible that if conflict arises due to poor PO fit, an individual with a higher

relative moral philosophy will handle this conflict differently than someone with a lower

relative moral philosophy, creating a moderating effect on the relationship. This idea is

based on Peterson’s (2003) findings that individuals who did not believe ethics were

relative were less committed to their organization when pressured to engage in unethical

behavior. Accordingly, this study assessed individual relativism as a possible moderator

of the relationship between PO fit and each of general, affective-identity, non-calculative,

and social-normative motivation to lead.

Although not a situational variable, idealism has also been considered in relation

to organizational commitment. Shaub et al. (1993) found that idealism was not related to

organizational commitment. However, they did find that idealists were committed to their

professions. Given that taking a leadership position may change an employee’s ability to

participate in their profession, idealism may predict general motivation to lead, and each

of the three dimensions of general motivation to lead.

8

Research Questions

Because PO fit has previously been found to predict commitment, and motivation

to lead is based on a model of commitment, studying the prediction of motivation to lead

from PO fit is a reasonable choice. Relativism has been studied as a moderator of the

relationship between ethical conflict and commitment. Similarly, this research considered

relativism as a moderator of any relationship found between PO fit and motivation to

lead. Another dimension of moral philosophy, idealism, could predict motivation to lead.

Previous research found that idealists were committed to their professions, rather than to

their organizations. Therefore, idealism was studied as a predictor of motivation to lead.

The three dimensions of motivation to lead were also looked at separately as predicted by

PO fit, PO fit with relativism as a moderator, and idealism.

Studies have shown that a number of personal, job, and organization factors

influence PO fit, moral philosophy, commitment, and motivation to lead. For example,

age, organization tenure, work experience, previous leadership experience, and current

job level were all found to affect motivation to lead (Chan & Drasgow, 2001). Gender

and job tenure are known to influence PO fit outcomes (Ostroff & Rothausen, 1997;

Young & Hurlic, 2007). Regarding organizational commitment, Sommer, Bae, and

Luthens (1996) showed that employees at larger organizations are less committed, and

employees with a part-time employment status have been found to exhibit lower levels of

job involvement and inclusion (Clinebell & Clinebell, 2007). Furthermore, ethnicity and

education were found to influence idealism and relativism (Singhapakdi, Vitell, &

Franke, 1999; Swaidan, Rawwas, & Vitell, 2008). As such, these factors were controlled,

and all predictions of motivation to lead were made over and above personal (age,

9

gender, educational level, work experience, leadership experience, ethnicity), job (tenure,

level, employment status), and organization (size, tenure) characteristics. Specifically,

these questions were asked.

1. To what extent does PO fit predict general, affective-identity, non-calculative,

and social-normative motivation to lead among employed individuals, over

and above personal, job, and organization characteristics?

2. To what extent does relativism moderate PO fit’s prediction of general,

affective-identity, non-calculative, and social-normative motivation to lead

among employed individuals, over and above personal, job, and organization

characteristics?

3. To what extent does idealism predict general, affective-identity, non-

calculative, and social-normative motivation to lead among employed

individuals, over and above personal, job, and organization characteristics?

Hypotheses

Hypotheses for PO fit and motivation to lead.

The initial model guiding the questions regarding PO fit and motivation to lead,

and idealism and motivation to lead is shown in Figure 1. The initial model guiding the

questions regarding PO fit, as moderated by relativism, predicting motivation to lead is

shown in Figure 2.

10

-

- - 0 /-

+ 0/+

+ +

General Motivation to Lead

Affective - Identity Motivation to Lead

Non-Calculative Motivation to Lead

Social - Normative Motivation to Lead

Person - Organization Fit

Idealism

Figure 1. Initial model: Person-organization fit predicting motivation to lead, and idealism predicting motivation to lead.

0

0

0

+

+

General Motivation to Lead +

Non-Calculative

Motivation to Lead

Social- Normative

Motivation to Lead


Low Relativism

High Relativism

Affective -Identity Motivation to Lead

0

+

Figure 2. Initial Model: Person-organization fit, as moderated by relativism, predicting motivation to lead.

11

Previous studies have shown that PO fit predicts organizational commitment

(Cable & Judge, 1996; Chatman, 1991; McConnell, 2003; O’Reilly et al., 1991;

Silverthorne, 2004; van Vianen, 2000; Westerman & Cyr, 2004). Therefore, it is possible

that PO fit also predicts general motivation to lead. The hypothesis is that, as in the

prediction of commitment from PO fit, lower PO fit will predict lower general motivation

to lead.

H1: Lower levels of PO fit will predict lower levels of general motivation to lead,

over and above personal, job, and organization characteristics.

Because the antecedents of affective-identity motivation to lead are a unique

pattern of personality traits that are relatively stable (Chan & Drasgow, 2001), it is not

expected that a relationship will be found between PO fit and affective-identity

motivation to lead. However, PO fit may affect two antecedents of affective-identity

motivation to lead (openness to experience and leadership self-efficacy). Therefore it is

also possible that PO fit will predict affective-identity motivation to lead. Because the

relationship between PO fit and affective-identity motivation to lead is not clear, the

following competing hypotheses are proposed.

H2a: PO fit will not be associated with affective-identity motivation to lead.

H2b: Lower levels of PO fit will predict lower levels of affective-identity

motivation to lead, over and above personal, job, and organization

characteristics.

12

Because the compromises that come as a result of low PO fit can be seen as a

serious detriment and cost, it is expected that lower PO fit will predict lower non-

calculative motivation to lead. Further, because the major antecedent of non-calculative

motivation to lead is a collectivist value system, and lower PO fit may decrease a feeling

of membership in the collective, those lower in PO fit may be more likely to be aware of

and account for this cost when deciding to lead. Further, Chan (2001) found that

participants in his original 1999 study had an increased level of non-calculative

motivation to lead after they took leadership positions. Lower non-calculative motivation

to lead due to PO fit could limit leadership experience. This could reduce the feedback

effect from leadership experience to higher non-calculative motivation to lead.

H3: Lower levels of PO fit will predict lower levels of non-calculative motivation

to lead, over and above personal, job, and organization characteristics.

Because PO fit predicts prosocial behaviors such as teamwork (Posner, 1992) and

organizational citizenship behaviors (O’Reilly & Chatman, 1986), it is possible that

lower PO fit will predict lower social-normative motivation to lead, as it may be less

likely that a feeling of connection and duty toward the organization is present.

H4: Lower levels of PO fit will predict lower levels of social-normative


characteristics.

Hypotheses for PO fit, relativism, and motivation to lead.

When PO fit is low, individuals who believe ethics are based on a universal moral

code may be less likely to be motivated to lead, compared to those who believe ethics are

13

relative and based on situation. This parallels a previous study where, when ethical

conflict was present, a low relativistic moral philosophy, or belief in a universal moral

code, was found to predict lower organizational commitment (Peterson, 2003). However,

when ethical conflict was present, there was no effect on organizational commitment for

those with highly relative moral philosophies. A similar result is predicted for this study.

H5: Lower levels of PO fit will predict lower levels of general motivation to lead

when relativism is low, over and above personal, job, and organization

characteristics. However, lower levels of PO fit will not predict lower

levels of general motivation to lead when relativism is high.

As relativism may cause the employee to see low PO fit as less salient because

they are more willing to rationalize and adjust their values (thus reducing the notice, cost,

and impact of low PO fit), it is suspected that relativism will moderate the relationship

between PO fit and all three dimensions of motivation to lead.

H6: Lower levels of PO fit will predict lower levels of affective-identity

motivation to lead when relativism is low, over and above personal, job,

and organization characteristics. However, lower levels of PO fit will not

predict lower levels of affective-identity motivation to lead when

relativism is high.


to lead when relativism is low, over and above personal, job, and

organization characteristics. However, lower levels of PO fit will not

predict lower levels of non-calculative motivation to lead when relativism

is high.

14




predict lower levels of social-normative motivation to lead when

relativism is high.

Hypotheses for idealism and motivation to lead.

Idealism indicates the extent to which an individual feels that “harming others is

always avoidable, and they would rather not choose between the lesser of two evils which

will lead to negative consequences for other people” (Forsyth, 1992, p. 462). Idealists

believe that a moral solution is always possible where no harm comes to another. In

contrast, those low in idealism believe that negative consequences are acceptable for

some in order to attain positive consequences for others.

It seems plausible that a highly idealistic employee will foresee situations where,

as a leader with formal influence and power, they would have to make uncomfortable

decisions that could lead to negative consequences for others. Therefore, their desire to

lead may be lower. This indicates that higher idealism may predict lower general

motivation to lead. Others studies (Shaub et al., 1993) found that higher idealism

predicted higher professional commitment, but idealism was not related to organizational

commitment. Taking a leadership position may affect an employee’s ability to continue

in their profession. Changing occupation within an organization is a difficult decision;

this decision has been found to be more difficult than leaving the organization and

remaining in the same occupation (Blau, 2000). As idealists are committed to their

professions, they may find the decision to change to a leadership role especially difficult.

Therefore, although no relationship was found previously between idealism and

15

organizational commitment, it is possible that higher idealism will predict lower general

motivation to lead.

H9: Higher levels of idealism will predict lower levels general motivation to lead,


Because the antecedents of affective-identity motivation to lead are a unique

pattern of personality traits that are relatively stable (Chan & Drasgow, 2001), it is not

expected that a relationship will be found between idealism and affective-identity

motivation to lead. However, idealism may be related to one antecedent of affective-

identity motivation to lead (conscientiousness). Further, higher levels of dedication to

professional ideals may produce conflict for professionals and lower organizational

commitment (Shafer et al., 2002b). Therefore it is also possible that idealism will predict

affective-identity motivation to lead. Because the relationship between idealism and

affective-identify motivation to lead is not clear, the following competing hypotheses are

proposed.

H10a: Idealism will not be associated with affective-identity motivation to lead.

H10b: Higher levels of idealism will predict lower levels of affective-identity


characteristics.

Similar to PO fit, because an idealist might see potential conflicts as a

nonnegotiable cost of leadership, it is expected that higher idealism will predict lower

16

non-calculative motivation to lead. In summary, the inordinate costs to the idealist of

leading may bring an individual to give these costs more consideration.

H11: Higher levels of idealism will predict lower levels of non-calculative


characteristics.

Idealism, with its preference for avoiding decisions that may affect another

individual negatively, may exert a force greater than a feeling of duty to the group. In

addition, Shafer, Lowe, and Fogarty (2002a) found that idealists become desensitized and

defensive, also indicating a lower feeling of obligation towards the group. Therefore, it is

suspected that higher idealism will predict lower social-normative motivation to lead.

H12: Higher levels of idealism will predict lower levels of social-normative


characteristics.

Definition of Terms

Affective-identity motivation to lead is a first-order factor representing motivation

to lead based on liking to lead and seeing oneself as having leadership qualities based on

past leadership experience.

Ethics is a theory or system of moral values.

General motivation to lead is a second-order construct of motivation to lead that

accounts for the common variance among the three first-order factors of affective-

identify motivation to lead, non-calculative motivation to lead, and social-normative

motivation to lead (Chan & Drasgow, 2001).

17

Idealism is a personal belief that ideal consequences that cause harm to no one

can always be attained when making a moral judgment.

Morals provide motivation based on ideas of right and wrong.

Moral philosophy is a personal theory of right and wrong. An individual’s moral

philosophy gives guidelines for moral judgments and suggests actions in ethical

dilemmas. Moral philosophy is also known as ethical ideology. Idealism and relativism

are two types of individual moral philosophy that were identified by Schlenker and

Forsyth (1977).

Motivation to lead affects the decision to assume leadership training, roles, and

responsibilities, and the amount of effort given to leading and persistence as a leader

(Chan & Drasgow, 2001).

Non-calculative motivation to lead is a first-order factor representing motivation

to lead based on not requiring rewards for leading and being generally agreeable to

leading, even without prior leadership experience or feelings of leadership self-efficacy


Perceived supplementary person-organization fit is the extent to which the values

of an individual are similar to those of their organization as reported directly by that

person.

Relativism is a personal moral philosophy, where the correctness of a moral

judgment is not considered absolute. Rather, moral judgment is correct relative to the

convictions and practices of a culture. Further, universal moral rules are not considered

possible. Relativists consider situation and personal values over ethical principles when

making a decision.

18

Social-normative motivation to lead is a first-order factor representing the

motivation to lead based on a sense of social duty, being accepting of social hierarchies,

and rejecting of social equality (Chan & Drasgow, 2001).

Universalism is a personal moral philosophy, where the correctness of a moral

judgment is based on absolute and universal principles.

Values are enduring beliefs that a type of conduct or end-state mode of existence

is preferable, on a personal or social level, to opposing types of conduct or end-states of

existence (Rokeach, 1973). Values are considered when making ethical decisions.

Limitations

The present study required participants with a variety of attributes and

experiences, across several different organizations, and at various job levels. As it was

not feasible to meet these sample requirements by partnering with multiple organizations,

a convenience sampling method was used. Although non-random sampling limits the

external validity of the study results, this method enabled the sample to represent a

diversity of participants and organizational contexts, giving an increase in external

validity over most organizational research, which usually involves participants from a

single organization (Eaton & Struthers, 2002).

The sample consisted of 1,024 adults employed by organizations in the United

States. Because a U.S. sample was used, the study results cannot be generalized to

employees in other countries. Also, as the majority of participants were adult learners at

an online university, and the other participants were friends and work colleagues who

were mainly professionals, the high educational and job levels of the sample may have

affected generalizability.

19

The study was conducted using an online survey. The participants remained

anonymous and the survey was hosted by a third party to ensure the confidentiality,

reliability, and safety of the data. However, online surveys can suffer from sampling

biases due to data introduced when an uninvited respondent completes the survey. Even

though an uninvited respondent could complete a mailed survey, online surveys may be

more susceptible to fraudulent data, as the survey is universally available to anyone who

happens upon it. Therefore, to increase data validity, the survey was completed by

invitation only and a password was required to enter the survey.

As self-report measures were used, and predictor and criterion variables were

reported by the same individual at the same time, common method bias may have

occurred (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).

Summary and Conclusions

We need to motivate the types of individuals who will create healthy, resilient,

and productive workplaces, which may not necessarily be the type of person already

leading in the organization. If those with a values mismatch (and especially those who are

not willing to compromise their values) are not motivated to lead, the leadership pool

may become homogenous enough to create a negative effect. For example, it has been

proposed that leadership homogeneity can decrease the organization’s ability to react and

change with its external environment (Bowen, Ledford, & Nathan, 1991; Giberson et al.,

2005; Powell, 1998).

A first step to determining if a “fit” filter is creating values homogeneity is to

determine if PO fit predicts the will to pursue (or avoid) leading. Chan (1999) has

developed a measure of motivation to lead. However, situational variables, such as PO

20

fit, are not included. This dissertation explored the predictive strength of one situational

variable, PO fit, for Chan’s motivation to lead construct, directly and as moderated by a

relative moral philosophy. In addition, idealism may predict motivation to lead,

especially for professionals. Therefore, the predictive strength of idealism for motivation

to lead was also assessed.

21

Chapter 2: Review of the Literature

Introduction

This literature review gives analyses of PO fit, moral philosophy, and motivation

to lead. An understanding of previous research on PO fit and its various forms helps to

identify and justify the conceptualization, operationalization, and measurement of PO fit

used to predict motivation to lead. Special attention is given to how PO fit predicts

commitment, an attitude on which motivation to lead is based. Further, links among

moral philosophy dimensions (relativism and idealism), commitment, and motivation to

lead are explored. A treatment of the current literature on motivation to lead, especially

the area of motivation to lead and situation, follows. The review ends with a short

summary of the literature and gives a description of how the present study was

conceptualized from it.

Conceptualizing Person-Organization Fit

The person-organization fit focus.

Person-environment fit (PE fit) represents a broad array of interactions that can

occur between a person and environment. PE fit can occur between a person and another

individual (e.g., a supervisor, as in PS fit), a job (PJ fit), a group (PG fit), a vocation (PV

fit), or an organization. These fit types are currently being explored to create a

multidimensional theory of PE fit (Jansen & Kristof-Brown, 2006). In addition, the

attribute used to determine the content of the interaction can vary, as can the outcome of

the interaction, which can be attitudinal or behavioral. PE fit has been conceptualized and

operationalized in a variety of ways. In fact, in a recent meta-analysis of 172 studies,

Kristof-Brown, Zimmerman, and Johnson (2005) found that there is no agreed upon way

22

to define, measure, or account for the impact of PE fit. There is also some disagreement

on how best to proceed in utilizing and extending research in the area. For example,

Judge (2007) calls for an ideational consolidation of terms and continuing research in

current directions, whereas Harrison (2007) suggested that the actual scope and

boundaries of PE fit should be revisited and possibly revised.

Papavero (1999) conducted a qualitative study of six software engineers that

found that perceived values dissimilarity between the individual and the organization

diminished the desire to advance. Based on that finding, the present study is concerned

with measuring the relationship between an individual’s perception of the similarity of

their values and those of their organization, and how that perception relates to their

decision to take a leadership role. This goal identifies the environment of interest to be

the organization, and the type of fit to be studied as PO fit. The individual may exercise

several options when understanding and processing the term “organization.” It has been

found that individuals consider both the organization and other employees in their

conceptualization of PO fit (Billsberry, Marsh, & Moss-Jones, 2004). Further, individuals

do see the organization as a different entity than the employees that comprise it

(Piasentin, 2007). Although not often mentioned, another area of concern is whether it is

best to assess fit in a single organization, or across organizations. Ostroff (2007a)

suggested that it is preferable to measure fit across organizations, as is done in the present

study.

Choosing a PO fit interaction type.

An interaction between person and organization can occur when these two entities

are similar (supplementary PO fit), or when they differ but also mesh and interlock

23

(complementary PO fit). Further distinctions on the nature of complementary fit

interactions between person and organization have been made (Kristof-Brown et al.,

2005). Needs-supplies PO fit occurs when individual needs are met by environmental

supplies. Demands-abilities PO fit occurs when individual abilities meet environmental

demands. There is still some question as to whether complementary PO fit reflects needs-

supplies PO fit or demands-abilities PO fit (or both), or whether complementary fit is a

type of PO fit independent of these. Edwards and Shipp (2007) treat needs-supplies PO

fit and demands-abilities PO fit as types of complementary PO fit, as do Cable and

DeRue (2002). However, Piasentin (2007) found support for complementary PO fit as a

construct distinct from each of needs-supplies fit and demands-abilities fit that represents

“perceptions of being different in the organization combined with the belief that these

differences are valued by the organization” (p. 121).

Harrison (2007) pointed out that it is not tenable to study all possible person and

environment interactions. To bound its definition, he classified fit as the intersection of

both entities on a shared commensurate attribute. Supplementary fit represents affinity,

where there is similarity in the magnitudes of compatibility (or intersection), which

comes from person and environment sameness. By commensurate, Harrison was clear

that attributes must be defined by the same or similar content. As complementary fit

represents joining rather than intersection, it is nonviable under Harrison’s definition of

fit. However, Judge (2007) found Harrison’s definition of fit as intersection, and his

requirement for strictly commensurate attributes, too restrictive. Judge gives the study of

high achievers seeking organizations that pay well as an obvious example of fit that

would fail Harrison’s characterization.

24

There is some debate as to whether supplementary or needs-supplies fit is better

suited to predicting attitudinal outcomes. Kristof-Brown et al. (2005) suggested that

needs-supplies fit has a stronger and more direct link to outcomes than supplementary fit.

However, this has not been proven. Cable and Edwards (2004) found that both

complementary and supplementary fit affected attitudes. However, although these were

interrelated, they also contributed independently to outcomes. So, as proposed by Kristof

(1996), supplementary fit may represent the similarity between individual values (the

needs side of complementary fit) and the cultural values of the system of the organization

(the supplies side of complementary fit), making supplementary fit one possible

instantiation of needs-supplies fit. Further supporting Cable and Edwards’ model,

Greguras and Diefendorff (in press) found that supplementary PO fit had indirect effects

on employee outcomes through psychological need satisfaction, as the need for autonomy

mediated the relationship between PO fit and affective organizational commitment.

Edwards and Shipp (2007) further explored the relationship between

supplementary and needs-supplies fit. Their results showed that supplementary fit

influenced affective (affiliation needed), continuance (benefits needed), and normative

(shared values needed) commitment through needs-supplies fit (which they view as a

type of complementary fit). Edwards and Shipp found that supplementary fit predicted

attitudes indirectly by affecting the needs of people and the organization’s ability to meet

these needs. However, Karakurum (2005) saw a more direct relationship between

perceived supplementary PO fit and affective commitment. Karakurum used multiple

hierarchical regression analysis to study the relative abilities of PO fit measurement types

(perceived supplementary PO fit and four indirect measures) to predict organizational

25

commitment. Surveying 180 employees from various departments of a Turkish public

company, Karakurum found that directly measured PO fit was the best predictor of

commitment. Karakurum suggested that perceived supplementary PO fit predicts

affective commitment because “employees perceive an emotional attachment to the

organization or identify with the organization. Congruence between personal and

organizational values can be cited as one of the most important factors underlying such

an emotional attachment or identification” (p. 86).

Considering motivation may give direction for exploring the relationship between

supplementary fit on values, and complementary fit as needs fulfillment in the context of

values. Latham and Pinder (2005) discussed needs-based theories in terms of motivation,

noting that these theories explain why a person must act, but they do not explain why

specific actions are selected in specific situations. They propose that situational

knowledge, assessments, and intentions are driven by an individual’s values. Values may

be rooted in needs, but they provide the principled basis for goals, and guide the behavior

of an organization’s members (Chatman, 1989). Values are similar to needs, as they

arouse, direct, and sustain behavior, i.e., motivate. However, Latham and Pinder view

needs as inborn, whereas values can be acquired through cognitions and experience (i.e.,

needs are more stable than values). In their view, values are closer to action than needs.

Needs are common among most individuals, but values differentiate the actions

taken to satisfy them (Pinder, 2008). For example, gaining the esteem of others is a

common need. However, a person who values material acquisition might wear expensive

jewelry to gain esteem, while someone who values service might volunteer in the

community (Pinder). An example more applicable to a work setting also considers

26

environmental supplies of the need for esteem. If individual values of material attainment

are met with public recognition for mentoring, fit may not be present. If met with a

bonus, fit might be realized. Conversely, an individual who values service would be more

likely to fit an organization offering recognition, rather than one offering bonuses. The

nature of the environmental supply must match the individual’s values, in addition to

meeting the more universal need. That is, the need for esteem must be met with a supply

that satisfies the values of the individual. Therefore, it appears that supplementary PO fit

on values could be considered a context of motivation where, as individual and

organizational values similarity changes when situations arise, motivation increases and

diminishes. This view seems related to Edwards and Shipp’s (2007) assertion that fit on

values predicts attitudes through needs; however, it describes the converse situation

where needs predict attitudes through fit on values. It seems clear that further work is

required to determine possible interactions and precedence of needs and values when

determining behavioral and attitudinal outcomes of PO fit.

The issue of the relationship between needs-supplies fit and supplementary fit,

and the underlying meaning (and appropriate uses) of supplementary and complementary

fit remains unresolved, and research is in preliminary stages. However, in their meta-

analysis, Kristof-Brown et al. (2005) found supplementary fit had a larger effect for

commitment than needs-supplies fit. More recently, Piasentin and Chapman’s (2007)

results showed that both supplementary and complementary fit contributed to

commitment, with supplementary fit being a much stronger predictor. Their results also

showed that, although similarity is central to subjective fit, complementary fit also plays

a role when similarity is low.

27

Operationalizing PO fit with values.

The content used to compare PO fit is usually determined by the fit interaction

type. Abilities-demands fit research has focused on knowledge, skills, and abilities

(KSAs), and organizational demands, while needs-supplies fit research measured general

individual need preferences (Kristof-Brown et al., 2005). However, personality traits and

values have been used with needs-supplies fit studies, and values have been included in

abilities-demands fit studies (Kristof-Brown et al.). More recently, Piasentin (2007)

included values and goals in her assessment of complementary fit as a unique construct.

For supplementary PO fit, the same content must be measured for both the person

and organization. Values, goals, personality traits, and attitudes are the most common

content types. There is disagreement as to which content dimension is best at predicting

particular outcomes of supplementary PO fit (Kristof-Brown et al., 2005). In early

research, the meaning of PO fit was interwoven with values content. Chatman defined PO

fit as "the congruence between the norms and values of organizations and the values of

individuals” (1989, p. 339). More stable content types are thought to have a larger effect

on attitudes and behavior (Kristof-Brown et al.). For example, if personality were

considered more stable than values, then personality should offer a better result than

values (Kristof-Brown et al.). However, as Kristof-Brown et al. noted, if similarity on all

personality traits is not related to the outcome, then content consisting of all personality

traits would have a smaller effect on the outcome than values. Further, measuring values

alone produced only slightly weaker relationships than a combination of values,

personality, needs, and KSAs (Kristof-Brown et al.). This supports Chatman’s emphasis

28

on values as fit content, and gives further support for operationalizing fit using values in

the present study.

Choosing a view of PO fit.

Subjective PO fit considers PO fit from the viewpoint of the individual. Subjective

PO fit can be measured indirectly, where individuals evaluate themselves and the

environment, with these evaluations compared afterwards. Alternatively, PO fit can be

measured directly, where individuals report their perception of the compatibility of

themselves and the environment. Subjective PO fit that is measured directly is often

termed perceived PO fit. PO fit can also be viewed objectively, by assessing fit indirectly

using different sources. The content to be compared is assessed for the individual, by the

individual. The same content is then assessed separately for the environment, by another

source. The two assessments are then compared to measure objective PO fit, which is also

known as actual PO fit.

There is some disagreement as to the value of subjective PO fit. Objective and

subjective PO fit are not equivalent (Ravlin & Ritchie, 2006; van Vuuren, Veldkamp, de

Jong, & Seydel, 2007). Subjectively measured PO fit has been found to have the

strongest relationship with outcomes, especially attitudes. However, subjective measures

can suffer from common method bias (Kristof-Brown & Jansen, 2007).

There is also some debate specific to the value of directly assessed (i.e.,

perceived) PO fit. Perceived PO fit does not give the direction of variance (Edwards &

Shipp, 2007). Therefore, perceived PO fit operates at a global level and represents

similarity in a general sense with no dimensions of comparison. This limits analysis of

the functional form of the relationship between PO fit and the outcome (Ostroff, 2007a).

29

For example, finding higher subjective PO fit on values reveals nothing about how the

values of the person and organization differ, only that they do differ. If the values of the

organization were highly ethical and the employee’s were not, or vice versa, the

difference in outcome variance would be identical.

Perceived PO fit has been categorized as a viable construct that captures the

overall affective reaction to the contextual environment. It has been suggested that

perceived fit should be used only in certain restricted cases (Harrison, 2007; Ostroff,

2007b). In fact, Harrison called for perceived PO fit to be reclassified out of the area of

fit. Perceived PO fit may be an affective measure of the extent to which a person

perceives or feels they fit, but it is still a construct that can be studied in its own right as

an implicit theory of fit (Cable & DeRue, 2002; Cable & Edwards, 2004; Finegan; 2000;

Kristof-Brown & Jansen, 2007; Ostroff, 2007a). Perceived PO fit is especially suited to

examining feelings of fit at an individual level of analysis, where fit is unique to each

individual (Autry & Wheeler, 2005; Kristof-Brown & Jansen; Ostroff, 2007b).

Efforts are being made to define and differentiate subjective PO fit approaches so

they can be examined in more detail. Edwards et al. (2006) studied the cognitive process

of comparison used to determine subjective needs-supplies PE fit (note that these results

may not generalize to others types of fit, such as supplementary fit). Three approaches to

studying subjective PE fit were defined. Molar fit signifies affect and gives a holistic

assessment of similarity, rather than a judged match of perceived personal needs and

environmental supplies. Molar fit appears to be equivalent to perceived fit. Subjective fit

can also be molecular, where the individual compares themselves to others, but not with a

focus on similarity. Finally, subjective fit can be atomistic, a reductionist approach,

30

where the individual describes their own values and those of the organization, which are

then compared. These three approaches were found to be distinct, but issues were found

with each. With the molar approach, fit varied with the direction of the relationship

between the person and environment. When environmental supplies exceeded the

person’s needs, fit increased on dimensions such as pay and vacation time, but when the

person exceeded the environment, fit decreased on dimensions such as span of control

and supervision. The molecular approach produced different results depending on

whether the person was the target (my needs exceed the organization’s supply) or the

environment was the target (the organization’s supply does not meet my needs),

suggesting that an unequally weighted comparison was taking place. Edwards et al.

explored these results further in an unplanned post hoc analysis and found that both the

molar and molecular approaches had high correlations with satisfaction, and may actually

represent satisfaction rather than fit. They also found that molar and molecular judgments

were not made by combining atomistic impressions of the environment. Further, they

observed that atomistic perceptions are probably subjective because individuals could use

some other standard of comparison, such as other experiences or referent others, when

making judgments. Edwards et al. concluded that it is not clear as to exactly what

subjective PE fit represents, and that more research is needed to find its true meaning.

Others continue to support perceived PO fit as a viable construct for which

objective measurement is not appropriate (Autry & Wheeler, 2005; Caldwell, 2003).

According to Kristof-Brown et al. (2005), perceived PO fit allows the greatest level of

cognitive manipulation, as the individual applies their own weighting, and it continues to

be the best predictor of attitudes because it gives a holistic assessment of fit. Supporting

31

this view, Cable (personal communication, as cited in Caldwell) gave a description of

perceived PO fit as molar and representing “idiosyncratic processing of demands, needs,

and attributes of the environment relative to themselves in ways that cannot be

constructed objectively by researcher's formulae” (p. 47). Giving some clarification as to

which values are considered by individuals when reporting perceived PO fit, human

relations values predicted perceived fit best (van Vuuren et al., 2007). van Vuuren et al.

suggested that, when reporting perceived PO fit, respondents are thinking of “typically

human values, ethics, or morale, and neglect values like stability and innovation, for

which ‘values’ is a less obvious connotation” (p. 1743).

Although the status of subjective PO fit is still being considered, Judge (2007)

calls for consensus, and cautions that free intellectual thought should continue to be

exercised to explore the issues further. In an example of continuing efforts to elicit the

meaning of subjective fit, Billsberry, Ambrosini, Marsh, Moss-Jones, and van Meurs

(2005) have used causal mapping and storytelling as methods of uncovering and

organizing individual experiences of fit.

A direct measure of subjective PO fit is the most widely used because it has

consistently been found to obtain results for attitudes (Kristof-Brown & Jansen, 2007).

Recently, Piasentin and Chapman (2007) identified perceived PO fit as a unique construct

that predicts attitudes. Although perceived PO fit has been criticized as increasing

common method bias, it continues to reflect reality, as interactional psychology theory

suggests that people can only be influenced by fit with their environment as they perceive

it (Kristof-Brown et al., 2005). Perceived PO fit gives no information regarding the

direction of fit variance. However, as the goal of the present study is to determine if any

32

outcome variance occurs, it is not concerned with the direction of the variance (nor will it

make judgment on whether one direction of variance is qualitatively different from the

other, i.e., better or worse).

PO misfit.

The topic of misfit continues to receive increased attention. In Harrison’s (2007)

view, examining fit produces too much information, and may not be as productive as

examining misfit, which is more focused and manageable. Employees may not start as

misfits; they either fit or are neutral (Billsberry et al., 2005). Billsberry et al. proposed

that a misfit is something one becomes, alluding to a process of moving from fit to misfit.

Fit cannot be assumed to be positive, as those with higher fit can become

complacent (Harrison, 2007). However misfit can also be detrimental. Individuals may

not be able to choose where they work, which may increase the level of detrimental misfit

in an organization (Schneider, 2007). When misfits think there are no viable alternatives

to their current position, they stay. With a sample of 205 employees from two regions in

the U.S., Wheeler, Gallagher, Brouer, and Sablynski (2007) used an online survey, and

hierarchical mediated and moderated regressions, and found that low PO fit was more

likely to result in intent to turnover when perceived job mobility was high. Wheeler et al.

did note a limitation, in that actual turnover was not measured. Staying in a job when PO

fit is low may result in cynicism, which may have a negative impact on the individual and

organization (Naus, 2004). Billsberry (2007) has proposed four fit meta-categories (that

appear to fold in the impact of consequences of misfit) that may be useful in determining

when misfit is damaging. When fit is advantageous for both the individual and the

33

organization, misfit is detrimental for both. While self-serving misfit is detrimental for

the organization, organization-serving misfit is negative for the individual.

Detrimental misfit can stem from a variety sources. For example, Billsberry et al.

(2005) found that while senior employees did not value work-life balance, lower-level

employees did. It should be noted that higher-level employees might have better access to

resources that can help them cope with work-life conflicts, which may reduce the salience

of misfit. Regardless of the reasons for differences in employee levels, Billsberry et al.

note that the importance of work-life balance may have been underplayed in the past,

given that most studies of fit involve managers. If management requires increased

commitment and a devaluing of work-life balance, then valuing work-life balance may

contribute to lower motivation to lead (Papavero, 1999; Stern, 2003). However,

addressing this type of misfit may not be straightforward. With a stratified random

sample of 460 employees at a large university in the U.S., Rothbard, Phillips, and Dumas

(2005) used hierarchical multiple regression and found that individuals who preferred

work-life segmentation and had access to integration policies (e.g., onsite childcare) were

less committed than those with less access. Further, individuals who wanted work-life

segmentation and had access to segmentation policies (e.g., flextime) were more

committed. These results were found over and above age, gender, domestic partnership

status, income, number of children, and age of children. However, Rothbard et al. did

note that their study might have been limited by common method bias (although

Harman’s one-factor test found common method variance was not present), and the fact

that the sample was sourced with one university.

34

Billsberry et al. (2005) found that a sense of misfit most often resulted from poor

fit with direct management and organizational values. Talbot, Billsberry, and Marsh

(2007) later found different root causes for fit (e.g., job, environment, and colleagues),

suggesting misfit as a unique construct. Further, the same root cause resulted in fit or

misfit depending on subsequent managerial actions. The line between fit and misfit,

which is perhaps the point at which low fit becomes detrimental, is not clearly defined.

However, fit seems to be emerging as a categorical construct. Those employees who fit

well may also have elements of misfit, which may not be entirely detrimental. As Talbot

et al. state, “it is possible that this is desirable in employees; perhaps the people who are

able to look critically at organisational behaviours, policies, procedures and others’

behavior are the best fit” (p. 12).

Much like heterogeneity at the organizational level, a state of misfit for the

individual could be a useful state that brings necessary change and increased resilience at

the individual and, perhaps, organizational levels. Of course, that change may entail

leaving the organization. Arthur, Bell, Villado, and Doverspike (2006) pointed out that

subgroup differences in PO fit are “understudied or not reported in the extant literature”

(p. 797). Those who see themselves as misfits, which may include a disproportionate

number of women and minority group members, may leave (Hoobler, 2005). However,

this might not produce the best outcome for the organization, especially if diversity is a

priority.

Welsh and Dehler (2001) described conditions that may lead to misfit, and

different reactions to misfit in the form of resistance versus leaving the organization.

Even with efforts to change and modernize organizations, control processes have not

35

inherently changed. A colonization process is used to obscure the contradictions between

demands of a high level of commitment from the employee, and the low level of

commitment actually received by the employee (Welsh & Dehler). Colonization works

best when employees have higher PO fit, but as commitment to employees wanes, lower

PO fit may result, and resistance may increase. Resistance can create heretics, who are

low in PO fit, but apply critical reason to identify values incongruity and invite debate.

Membership in the organization is essential for heretics in maintaining separateness and

context for resistance. Eventually, heretics may surrender their separate selves, or they

may become tempered radicals who seek to maintain both personal and organizational

identities simultaneously in order to advance in the organization. However, tempered

radicals spend more energy balancing opposing forces than transforming the

organization. It is likely that when heretics or tempered radicals express dissent, their

advancement is prevented. Constructive deviants, whose personal identity is separate

from the organization, occur at all organizational levels. Constructive deviants take action

on discrepancies identified by the heretics and tolerated by the tempered radicals (Welsh

& Dehler). They identify organizational limits and use action to break through for their

own personal transformation and emancipating change (Welsh & Dehler).

Conceptualizing PO fit in the present study.

No matter what terminology is used Harrison (2007) suggests that any study

concerning fit make all assumptions clear. For the present study, a molar, or direct,

comparison is made on content consisting of values. Fit here is a subjective perceived

construction, not a cognitive representation. Maximum and minimum fit have no

meaning in this study, as no strict correlation of the person and environment is being

36

measured independently. However, if necessary, minimum and maximum fit could be

defined as the lowest and highest values on the perceived fit scale. No attempt is made in

the present study to categorize fit or misfit. It should be noted that although it remains an

open question as to whether misfit is a continuum moving from fit to misfit, recent

research suggested that misfit is a distinct construct (Talbot et al., 2007). In any case, the

need to characterize participants as misfits is not anticipated.

The present study considers PO fit as fit to the organization itself as an entity,

rather than to other members. Ostroff and Schulte (2007) described this mode as person-

situation fit that characterizes features of a situational context (values), which is

differentiated from person-person fit. Strictly speaking, the present study is concerned

with the social person-situation subtype of PO fit in terms of values congruence. As the

present study examines the similarity of the entities being compared for purposes of

exploring individual outcomes, the relationship can also be characterized as

supplementary, rather than complementary. Further, as the latest findings on

supplementary, needs-supplies, and complementary fit have shown that supplementary fit

continues to be a good predictor of an attitude with similarities to motivation to lead (i.e.,

commitment), supplementary fit will be used in the present study.

Finally, the present study is mainly concerned with how an individual’s

perception of fit motivates them to lead or not lead. The goal is not to assess how other

environmental factors contribute to fit, but to determine if fit perception contributes to

motivation to lead. In summary, the present study is concerned with the relationship

between an individual’s perception of fit and their decision to take a leadership role (or

not), not all causes for this attitudinal outcome. Further, directly perceived PO fit gives

37

the strongest correlation with commitment (Verquer, Beehr, & Wagner, 2003), and may

do the same with motivation to lead. Therefore, perceived supplementary PO fit on

values is appropriate and is used in the present study. For brevity, the term PO fit will be

used to identify perceived supplemental PO fit on values in subsequent references.

PO Fit and the Motivation to Lead

Individual outcomes of PO fit.

Billsberry (2004) noted that a good number of studies have shown that low PO fit

can predict attrition. However, there is a scarcity of studies on the role that low PO fit

plays in incumbent attitudes and job performance. In their meta-analysis of 25 studies,

Kristof-Brown et al. (2005) confirmed the relevance of PO fit for post-entry attitudes,

with commitment being the most strongly predicted. Several studies found links between

PO fit and outcomes related to motivation to lead, including commitment, and some

researchers have made proposals in the same area. In a meta-analysis of over 100 studies

regarding PO fit, job performance, and attitudes, Arthur et al. (2006) found the

relationship between PO fit and organizational commitment to be strong and

generalizable. Further, PO fit may impact motivation to lead indirectly through

commitment. In a study of 103 white-collar employees, Fowke (1998) found that layoffs

lowered affective commitment, which in turned decreased career motivation. Because

Arthur et al. found a much weaker relationship for PO fit and job performance they

suggest that, compared to using PO fit in entry-level selection, PO fit is more useful in

“employment related decision making, including promotions, appointments to leadership

positions, transfers, terminations, and even the formation of work teams” (p. 797).

38

Billsberry et al. (2004) used causal mapping and storytelling with 63 individuals

and found that fit on opportunities for growth and development was important enough

that employees with poor fit in this area would leave the organization. However, no

mention was made of the likely outcome when poor fit occurs because growth and

development at work is not preferred. This situation could occur when the organization

demands growth and development that benefits its goals, while the individual prefers

growth and development outside of work that benefits individual goals. In other words,

the result of low fit on growth and development opportunities could vary depending on

whether strong work-life segmentation is desired by the individual.

Finegan (2000) surveyed employees at a large petroleum company and obtained a

sample of 121 mostly male (83%) employees. Using hierarchical multiple regression,

Finegan found that PO fit predicted affective commitment, but not normative or

continuance commitment. However, he notes that the results are limited as all participants

were from the same organization, and most had long tenure with the organization.

In a study of 783 graduates from two industrial relations programs, Bretz and

Judge (1992) used regression analysis and LISREL, and found that individuals with

higher PO fit achieved higher levels of intrinsic and extrinsic success. They did note that

this was not a longitudinal study and, therefore, fit could not be measured before

assessing success to determine a causal relationship. Bretz and Judge suggest that once a

promotion decision is made based on fit, false-positive selection errors will not be undone

by subsequent decisions because the selected individual competes in a smaller and more

homogeneous group at each level. If an individual is passed over at lower levels because

of perceived low fit, it is unlikely that they will be given the opportunity to compete at

39

higher levels. These false-negative selection errors are particularly damaging since those

who might have been highly successful at higher levels are less likely to be considered.

These inaccurate decisions all occur under conditions of sponsored mobility. This implies

that low PO fit could reduce sponsored mobility (Bretz & Judge), which could in turn

affect an individual’s motivation to lead.

Haley and Sidanius (2005) proposed that PO fit and promotion may be linked

based on socio-political attitudes. Socio-political attitudes reflect a preference for

hierarchy attenuating or hierarchy enhancing institutions as defined by social dominance

theory. Previous studies have found that egalitarian individuals are attracted to hierarchy

attenuating organizations, whereas those who endorse social hierarchies are attracted to

hierarchy enhancing organizations (Haley & Sidanius). Socio-political homogenization

could result due to self-selection, organizational selection, organizational socialization,

differential rewards, and differential attrition rates (Haley & Sidanius). As Chan (1996)

stated, “over time, individuals in cognitive misfit are likely to be less motivated, less

committed, and experience more work-related stress and job dissatisfaction than those in

fit” (p. 199). Haley and Sidanius see this as “a process that should affect not just an

individual’s turnover intentions, but also the likelihood that an individual will suffer

when it comes to salary, promotion, and layoff decisions” (p. 196). In essence, those who

do not fit may have less opportunity to gain the leadership experiences that contribute to

leadership self-efficacy, which in turn decreases motivation to lead.

Organizational outcomes of PO fit.

Argyris (1954) studied the organization of a bank through observations and

interviews and found a caste-like system between employees and officers that had

40

adaptive value in that it helped maintain peace by minimizing interactions. People

became increasingly agreeable to avoid confrontations. However, 89% of the employees

said inflexibility and rigidity were detrimental because everyone continued doing things

in the same way, simply because it was the way it was done before. It appeared that the

bank perpetuated the personality that came to the organization through feedback and

fusion (Argyris). This observation, although offered over fifty years ago, seems to reflect

the same process of homogenization in organizations, and the accompanying

complacency, that is prompting researchers to turn their attention to the positive aspects

of fit diversity for organizations today.

The dynamic processes underlying PE fit are described by Schneider’s (1987)

attraction-selection-attrition theory (ASA). ASA focuses on both individual and

organizational outcomes. Because this theory argues that individual fit may lead to

organizational homogeneity over time, the consequences of individual fit could transcend

individual outcomes. Although not the focus of this study, the consequences of lowered

motivation to lead as a result of poor PO fit may very well create long-lasting effects for

the organization as a whole. For example, Scott (2000) found that individuals were more

likely to interview with organizations that fit their moral values, and suggested that as a

result the range of values represented in the organization would become smaller.

Current thought continues to focus on the causes of homogeneity and its

consequences. Schneider (2007) noted that organizational development change practices

would not work because people in the organization are similar and comfortable. He

suggested that it is impractical to change the homogeneity of personalities of

organizational incumbents, as homogeneity is a cause for resistance. Boone et al. (2004)

41

offer a concrete example of this, where top management teams experienced homosocial

reproduction and closed ranks during crisis. Boone et al. suggested it would be better to

diversify the team to help their membership cope.

van Vianen and Stoelhorst (2007) proposed that bottom-up fit produces

homogeneity in the organization through the behavioral homogeneity of conformity.

Individuals prefer to copy similar others and those whose behavior has brought the

highest payoff. People may especially imitate prestigious models in the organizational

hierarchy, staying as long as the benefits outweigh the costs of adaptation to the

organizational culture. Those with low fit might try to create a niche to adapt and fit in,

and leave if they cannot. This may explain why homogeneity develops more readily in

stronger cultures, where niches are discouraged. The power of imitation may relate to low

non-calculative motivation to lead, where a leadership role is not taken if the perceived

cost is too high. It is possible that the cost of leadership figures highly in the decision to

identify with and imitate current leaders, and that what is considered acceptable cost and

payoff varies widely. For example, the definition of success and prestige may not be

equivalent for someone who values home, family, and community first, versus someone

who values material wealth first. Favorable models of behavior, worthy of imitation,

probably vary by individual. Imitation of current leadership would produce leaders who

share values with incumbent leaders. Low propensity to imitate current leaders by those

who do not share their definition of success would also feed reproduction of current

leadership values. This could also work in a top-down fashion, as Giberson et al. (2005)

found that organizational values are congruent with the values of top leadership because

leaders surround themselves with similar others.

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Zhang, Dolan, Straub, and Kusyk (2007) observed that both life and work values

are important to fit and wondered if female values in executive boards would decrease

scandals and fraud. Diversity of values in teams can test the ethics of the existing

organizational culture. Dukerich, Nichols, Elm, and Vollrath (1990) found that the moral

reasoning of the group was at a higher level after discussion, but some individuals moved

higher than their original level and some moved lower. Moon and Woolliams (2000) later

found that ethical debate changed the individual values and norms of groups.

Finally, Nelson and Billsberry (2007) point out that it is not clear that

organizational homogeneity is advantageous or detrimental, no matter what the situation.

No study to date has proven this either way because the effect of fit on organization-level

performance has not been shown successfully. The positive and negative effects of

organizational homogeneity continue to be considered in the literature. However, it is still

unknown as to whether the values homogeneity that may result from PO fit is a

detriment. This question warrants consideration. In fact, fit with an environment is

probably not beneficial when the environment is unethical.

How PO fit changes.

PO fit can change over time as the individual and organization interact. A central

proposal in the present study is that motivation to lead is not only associated with PO fit,

but that changes in PO fit, whether sourced with the individual or organization, may

increase or diminish the motivation to lead. The study of the idea of temporal fit, where

estimates of the environment change over time, is in its early stages (Kristof-Brown &

Jansen, 2007). PO fit can change with time, as individuals may change, or the individual

may change the organization. For example, goals and values can change in importance as

43

groups evolve, which may impact the needs of the group. PO fit can change when the

organization changes (Caldwell, Herold, & Fedor, 2004) and when career stage changes

(Powell & Meyer, 2004; Shafer et al., 2002b).

One example of an individual changing the organization would be when a

cooperative organization hires a competitive person, who changes the organization over

time (Chatman, 1989). An example of an organization changing an individual would be

that of a professional, whose values shift from those of their profession to those of the

organization as they advance. Age and other individual attributes may be related to the

interplay of values and needs, and how these impact on PO fit change. For example, PO

fit was found to be unaffected for older workers, but changed for younger workers, at an

organization experiencing turmoil (Shafer et al., 2002b).

PO fit can be consciously extended or reinforced by the organization (Powell,

1998). Which is preferable depends on personal and job attributes, and situational

characteristics. In general, reinforcement is needed for values central to the organization,

especially for lower levels of the organization, and at early stages of the organization.

However, according to Powell, values should be extended for those at higher levels of the

organization who have decision-making responsibilities. This seems to imply that, as

organizational needs change due to context, values can be extended or reinforced to meet

these needs. Extending values at higher levels of the organization may be difficult to

accomplish. West (2007) found that conflict within top management teams (TMTs) was

detrimental, especially when values diverged. This led to task and relationship conflict,

and lower organizational commitment. On the other hand, Yokota and Mitsuhashi (2008)

found that long-term reproduction of demographically similar executive teams caused

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inertia and an inability to meet changing external environments. Like Powell, West

suggested that optimal diversity (or optimal homogeneity) is needed. Although the riddle

of exactly how changes in needs and values occur, there is probably a difference in the

result of these changes based on other factors, such as the consciousness and transparency

with which the changes are approached. One might wonder, for example, how

consciously and explicitly introducing conflict, as suggested by Powell, and Yokota and

Mitsuhashi, might produce different results than allowing mismatch to occur by chance,

as described by West. Although not addressed directly by the present study, conscious

change of the values mix of leadership teams could be accomplished by encouraging the

full participation of qualified individuals who avoid leadership roles due to low PO fit.

PO fit, individual characteristics, and situation.

PO fit outcomes have been shown to be affected by gender (Young & Hurlic,

2007). Women with low PO fit sought promotions more often when the organization

accepted gender differences in behavior (a tolerant macro culture) than if gender

differences were not accepted. Both women and men viewed CEO, vice presidential, and

mid-level management roles within organizations as positive and possible when the

organization had a feminine image, such as clothing manufacturing (Killeen, López-

Zafra, & Eagly, 2006). However, for organizations with a more masculine image (e.g.,

auto manufacturing), women saw these roles as positive, but not possible; whereas men

saw the roles as both positive and possible, regardless of the organizational image. A

contextualization of the aspirations of women appears to be occurring. This indicates that

differences may be found for gender when predicting attitudes, such as motivation to

lead, from PO fit.

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Nwadei (2003) found relationships between values congruence and organizational

commitment based on different values for socio-cultural groups. Bottom-line values

congruence, on values such as health and safety, predicted commitment for Africans,

whereas change values congruence, on values such as openness, growth, innovation, and

flexibility, predicted commitment for Americans. For Europeans, people-based values

congruence made a difference, whereas in the Middle East, ethical congruence predicted

commitment. This indicates that differences may be found for socio-cultural groups when

predicting attitudes from PO fit, such as motivation to lead.

Numerous other situational and individual characteristics that affect PO fit have

been explored. These include self-efficacy, personal control, past work experience,

openness to influence, ethnicity (e.g., PO fit had a smaller effect for African Americans

and fit was lower), organizational culture strength (i.e., tightness-looseness),

organizational support, leader-member exchange quality, and burnout (Erdogan, Kraimer,

& Liden, 2004; Gelfand, Nishii, & Raver, 2006; Kristof-Brown et al., 2005; Siegall &

McDonald, 2004). It appears that individual characteristics, such as gender and socio-

cultural group, serve to increase or decrease the salience of PO fit to magnify or diminish

its effect. Others factors, such as organizational support and tightness-looseness, change

PO fit based on the situation. It is possible that the relationship between needs and values

is circular, or at least multi-directional. Situation may reprioritize needs, which then

necessitates a change in individual values priorities.

Ethical fit.

Pierce and Snyder (in press) term ethical fit as compatibility in ethical values and

behavior. Ethical fit can be based on organizational norms that are ethical or unethical.

46

Pierce and Snyder point out that when ethical fit is defined by organizational norms that

include illegal behavior, the outcome can be very serious. Using behavioral data from

vehicle inspection stations to determine ethical fit, they found that ethical diversity

mitigated attrition due to ethical misfit. By measuring directional misfit they found that

unethical employees left ethical organizations, and ethical employees left unethical

organizations. Pierce and Snyder sensed that this effect would be stronger for ethical

employees, but they did not predict or test this. Their evidence suggests that vehicle

emissions testing is a market where ethics is unprofitable, meaning that some

organizations may suffer financially by hiring ethical employees when competitors do

not. This situation may be analogous to an arms race. Organizations may race to the

bottom to match the unethical behavior of their competition as a matter of survival.

Pierce and Snyder suggest monitoring and fining for unethical behavior in the

marketplace to counterbalance this impulse.

Ethical fit has been found to predict affective and continuance commitment (Sims

& Kroeck, 1994). Another more recent study (Ambrose, Arnaud, & Schminke, 2008) also

found that ethical fit (how well ethical climate matched individual moral development)

predicted higher levels of organizational commitment. In a study of 314 employees at 128

organizations, Sims and Keon (1997) used multiple regression analysis and found that fit

on individual business ethics and the organization’s ethical climate predicted lower intent

to leave. However, they did note that commitment or satisfaction could have also

contributed to lower intent to leave. Later, Valentine, Godkin, and Lucero (2002) found

that corporate ethical climate itself predicted fit on values, as well as predicting

commitment. Coldwell, Billsberry, van Meurs, and Marsh (2008) give an explanation for

47

these results. Corporate social responsibility (CSR) has become increasingly important to

the public and to employees. CSR and corporate reputation are linked, so ethically

oriented employees may be attracted and retained due to CSR. In fact, they note that it

has been shown that people would rather work for an ethical company for less pay, and

when employees observe ethical behavior by management, they are more satisfied.

Coldwell et al. also suggest that ethical fit could be an issue for retention when the public

face of the corporation does not match internal reality.

Coldwell et al. (2008) proposed that when misfit occurs between the

organization’s moral stage and the individual’s, negative attitudes and behavior can

result. This refers to Kohlberg’s stages of moral development: (a) post-conventional - a

level never attained by most adults, with social mutuality and genuine interest in welfare

of others, respect for universal principles, and the demands of individual conscience; (b)

conventional - where approval of others is paramount; and (c) pre-conventional - a level

reached by most at primary school, where obedience and punishment guide morality

centered on law and order. Ambivalence may also occur instead if the degree of misfit is

minor.

The actual impact of ethical fit on organizational performance is still unknown.

Peterson (2004) posited that corporate social performance could influence stakeholder

groups, in addition to financial performance. Based on social identity theory, he found

that, when employees believed social responsibility to be important, economic, legal, and

ethical corporate citizenship predicted commitment, with ethical corporate citizenship

being the best predictor. It is possible that lower ethical fit relates to lower motivation to

48

lead, which in itself is not a negative attitude, but may be an attitude that negatively

impacts the organization by limiting leadership resources.

Moral Philosophy and the Motivation to Lead

PO fit and moral philosophy.

PO fit is known to predict commitment, an attitude on which the motivation to

lead construct is based. In the present study PO fit is treated as an affective construct that

reflects perceptions of fit on values, or how what is important to the individual is

perceived as similar to what is important to the organization. However, as discussed

previously, PO fit can change for an individual. This could occur due to changes in the

organization. Additionally, the individual values on which PO fit is based can change

(Kristof-Brown & Jansen, 2007; Puente, 2004). It is possible that some individuals are

more willing to adjust their values or value priorities to meet the conditions of the

organization in which they are embedded. An individual’s ethical processing system, also

known as a moral philosophy, could be an individual difference that influences values

change. Further, openness to values adjustment may influence the relationship between

level of PO fit and an attitude such as motivation to lead, even if the need for values

change is anticipatory rather than immediate.

Moral philosophy overview.

While morality is a set of beliefs about what is right or wrong, ethics is a

conscious reflection on the adequacy of these beliefs (Dodig-Crnkovic, 2007). A moral

philosophy describes the process of how ethicality is decided, rather than morals

themselves (Dodig-Crnkovic). Schlenker and Forsyth (1977) developed a widely used

49

model of moral philosophy that is explored in the present study in relation to motivation

to lead.

There are a variety of ethical bases for moral philosophies. Schlenker and Forsyth

(1977) chose questions around teleology (also known as utilitarianism), deontology, and

skepticism to explore factors that could be used to measure moral philosophy. Teleology

minimizes self-interest to maximize utility using a cost to risk ratio. In teleology, intrinsic

values (pleasure, happiness, ideals, preferences, self-realization, and fulfillment) are

considered most important (Schlenker & Forsyth). Teleology has been criticized because

a person cannot be responsible for all consequences, as they cannot be foreseen. Further,

putting aside self-interest could include putting aside personal integrity. It is also unclear

as to who should be in the domain of concern (Dodig-Crnkovic, 2007). Finally, luck

contributes to consequences, making it even more difficult to predict outcomes.

Deontology rejects the consequences of rules or actions as a basis for moral

evaluation (Schlenker & Forsyth, 1977). Deontology grounds decisions on rules and

universal laws of humanity (Dodig-Crnkovic, 2007). This philosophy appeals to natural

law and rationality to determine ethical judgments. Acts are judged as moral by

comparing them with universal moral rules, and there are no exceptions, regardless of

consequences. For example, it would be immoral to lie, even for benign motives. Like

teleology, deontology has difficulties with calculating and balancing rewards and risks

because future consequences are unknown (Schlenker & Forsyth).

Contrary to deontology, ethical skepticism, with many moral points of view (e.g.,

emotivism, cultural relativism, and ethical egoism), holds that inviolate moral codes

cannot be formulated (Schlenker & Forsyth, 1977). For example, emotivism says that a

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person cannot decide what is moral unless they can see, touch, hear, or otherwise sense

its meaning. Cultural relativism ties morality to society. Egoism holds that there are no

moral standards, except in reference to what one feels is right, and further, everyone acts

to promote their own self-interest. Egoism, like teleology, considers consequences, but

only for the self.

The initial version of Schlenker and Forsyth’s (1977) Ethics Position

Questionnaire (EPQ) used 50 questions that tapped the common major dimensions of

ethical concern for teleology, deontology, and skepticism: (a) importance of

consequences, (b) consideration of consequences, and (c) feasibility of universal moral

codes. Two major distinctions were found among the moral philosophies: (a) relativism,

which is the extent to which one is willing to accept the existence of a universal moral

code, and (b) idealism, which is an endorsement of idealistic versus pragmatic beliefs and

actions. These two orthogonal dimensions represent individual differences that influence

actions, judgments, and emotions when dealing with moral issues (Forsyth, O’Boyle, &

McDaniel, 2008; Park, 2005).

Orienting the two dimensions around the original ethical bases helps to explain

their meaning. On the high end of the continuum of relativism, skeptics deny the

existence of universal ethical rules. On the low end, a deontologist would condemn an act

that fails to meet a rule, regardless of the amount of harm or benefit. Somewhere between

skeptics and deontologists on the relativism continuum, teleologists tolerate negative

consequences to the degree that positive consequences outweigh them, so they are more

pragmatic than idealistic. Skeptics are guided by consequences, but some may judge

consequences as idealists, where others would be more pragmatic. However, Schlenker

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and Forsyth (1977) found that most skeptics are pragmatic. In either case, relativists

differ from both teleologists and deontologists by denying the applicability of universal

moral rules under any circumstances. Along the continuum of idealism, an underlying

calculation process is used to weigh decisions. However, at highest end, the idealist is far

more concerned with costs than benefits, whereas the pragmatist considers both. Finally,

deontology is most closely related to universalism (i.e., low relativism) and idealism in

Schlenker and Forsyth’s model.

Schlenker and Forsyth (1977) noted that science can provide answers to questions

concerned with the means used to obtain or implement particular values and goals, and

the consequences and affect of their implementation. The question of whether a value or

goal is moral is not a scientific question, but rather, morality is determined by moral

philosophy. Although Schlenker and Forsyth’s initial work grew out of an effort to

analyze ethics codes used in social science research, the resulting theory has been used

extensively in business research, especially in the area of business ethics (Forsyth et al.,

2008).

The EPQ can be viewed as a four-way classification of relativism and idealism, or

as two orthogonal dimensions. Davis, Andersen, and Curtis (2001) found discriminant

validity for idealism and relativism. They also found that idealism is stable for age and

gender, whereas relativism is not. In the present study, the role that universalism might

play in moderating the relationship between PO fit and motivation to lead is explored. It

is possible that individuals who make decisions based on strict moral rules might find low

PO fit to be more salient in this situation, whether they are pragmatic or idealistic. It

seems plausible that an intrapersonal conflict concerning immutable rules would override

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any influence of pragmatism. In addition, universalists have been shown to experience

lower self-esteem when they succeed, whether the goal is selfish or selfless (Forsyth,

1992). This may depress the motivation to lead. As idealism is more stable than

relativism, it is considered a direct predictor of motivation to lead in the present study.

Whether based on universal rules or not, the tendency for some idealists to almost

exclusively calculate costs, with less consideration for benefits, drives the view in the

present study that idealism is a potential negative correlate of motivation to lead.

PO fit, ethical conflict, and relativism.

In the present study, PO fit describes the extent to which individual and

organizational values are perceived by the individual to be similar. An individual’s

decision-making process involves value judgments (Liedtka, 1989). These judgments are

produced by assessing the fit between the course of action proposed by the organization

(organizational values) and the individual’s self-image (personal values). Liedtka

observed that conflict occurred when individuals were unsure as to whether

organizational expectations were consistent with their personal values. Conflict between

personal values and the values held by the organization produces ethical conflict (Toffler,

1986).

Perceptions of ethical conflict have been shown to be based on comparisons

between personal values and the perceived values of direct management (Schwepker,

Ferrell, & Ingram, 1997; Soutar, McNeil, & Molster, 1994). However, the behavior of top

management is also considered by individuals (Soutar et al.). The influence of direct

management is especially strong when the ethical code of the organization is unclear.

Values are not always explicitly stated to employees. In fact, Kristof-Brown et al. (2005)

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proposed that actual and perceived fit on ethical values might be distally related for this

reason. It appears that when the beliefs of top management are unclear, the values of

direct management have the greatest influence on the individual, and individual

perceptions of differences produce ethical conflict. As values influence the process of

determining what is ethical, PO fit could also be said to describe how well the individual

perceives that, when making ethical decisions, consulting their values will produce a

result similar to relying on the organization’s values. When personal and organizational

values are incongruent due to low PO fit, conflict may occur. However, relativism may

determine how this conflict is handled, or whether conflict is experienced at all.

Ethical conflict can occur for employees at any hierarchical level (Peterson,

2003). Further, employees who do not agree with the organization’s values, and who feel

pressured to compromise their own, may experience cognitive dissonance. This scenario

may be common, as employees almost always see themselves as more ethical than their

co-workers, supervisors, and top management (Brenner & Molander, 1977). Ethical

conflict occurs when employees feel pressured by their peers and management to

compromise their personal values in order to achieve organizational goals (Leicht &

Fennell, 1997). Employees have also been found to experience pressure to go against

formal organizational standards that they see as ethical (Goodell, 1994). This probably

reflects the influence of the informal organizational standards described by Quinn, Reed,

Browne, and Wesley (1997). In addition, a large majority (70%) of managers at all levels

were found to feel pressured to conform to ethical norms of their organizations with

which they disagreed (Posner & Schmidt, 1984). Upper managers and entrepreneurs were

also found to feel pressure to make business decisions that conflicted with their personal

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moral values (Longenecker, McKinney, & Moore, 1988). Values compromise is not

limited to the private sector, as it was found to occur in the public sector by Bowman

(1976).

Treviño, Weaver, and Reynolds (2006) proposed that professionals might become

morally compromised gradually over time. Individuals carve out private “identity spaces”

(or niches) and situationally defined organizational identifies (Weaver, 2006). As their

organizational identities become incorporated with the organization, the moral content of

this niche may become different from their individual identity. Differences in these

identities would probably vary given the norms of the organization. In addition, the

organization could be normless. Anomie (defined as a lack of purpose, identity, or values

in a person or society) can lead to a breakdown of the norms that rule the conduct of

people and assure the social order (Kuczmarski & Kuczmarski, 1995). This results in a

loss of meaning and a sense of injustice, and can affect moral thinking. Tsahuridu’s

(2006) findings showed that individuals view the work context as more normless than the

world outside of work. The process of values incorporation may be more apparent to low

relativists, as the content of the organizational niche becomes more different from the

inviolate rules that are part of their personal identity, and this may increase the salience of

low PO fit. For example, Tsai and Shih (2005) suggested that relativists are more likely

to excuse an unethical decision, and therefore experience less role conflict.

Ethical conflict, relativism, and the motivation to lead.

A review of the literature did not reveal any theories or empirical research directly

relating relativism and motivation to lead. However, it was found that when

organizational values were considered ethical, higher organizational commitment resulted

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(Herndon, Fraedrich, & Yeh, 2001). Further, Schwepker (1999) found that when a

personal and organizational values mismatch was experienced by an individual, personal

ethical conflict resulted. This ethical conflict produced lower organizational commitment.

It has been shown that managers believe their jobs require them to compromise

their ethics (Moser, 1988). Moser points out that if this were not so, a code of ethical

conduct would be unnecessary. The tension created by the incongruence of what an

individual acting alone would do, versus actions as an agent of the organization, is the

source of ethical conflict (Fasching, 1981). As a coping mechanism, complete

detachment from ethical concerns and personal responsibility may result (Moser). To

eliminate or reduce ethical conflict, individuals may withdraw or resign. More subtle

effects of ethical conflict include whistle-blowing, poor morale, disloyalty, strained

personal relationships, uncooperativeness, reduced quality, and absenteeism, all of which

lead to lower productivity (Moser).

Prior research concerning the relationship between ethical conflict and outcomes

has produced mixed results (Peterson, 2003). Peterson sought to uncover the cause of

these inconclusive findings by examining possible moderators. Using regression analysis

with 161 responses, Peterson found that lower commitment and higher intention to leave

were each predicted from ethical conflict, over and above age, gender, and educational

level. Peterson then used moderated regression analysis to examine relativism as a

moderator of the relationship between ethical conflict and commitment, and as a

moderator of the relationship between ethical conflict and intention to leave. He chose

relativism because it influences the ethical decision-making process, specifically when

formulating an intention to act. As relativists would be more likely to consider the

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situation when faced with an ethical dilemma, Peterson hypothesized that they would be

better able to cope with the pressure to engage in unethical behavior in an organization.

Peterson found a strong negative relationship between ethical conflict and organizational

commitment. However, when relativism was high, this relationship was no longer

present. When relativism was low and ethical conflict was high, organizational

commitment decreased. The effect on intention to leave was small, and Peterson

proposed any number of reasons for this. For example, even if someone is conflicted,

they may not have the option to leave their job due to monetary concerns. As the

relationship with commitment was especially strong for moral universalists, Peterson

suggested that they might experience much more stress when ethical conflict arises. No

interaction was found between ethical conflict and relativism for intention to leave.

Peterson notes that interaction detection in the field is known to be difficult, and that this

limitation might explain the absence of this interaction in his findings.

Relativists have been shown to be less ethically sensitive (Chan & Leung, 2006;

Sparks & Hunt, 1998). For example, in a study of 151 buying professionals at 52

companies, Park (2005) used hierarchical multiple regression and found that relativists

were less likely to consider socially responsible behavior, which could affect their

intentions when making an ethical decision. Park suggested that although the study was

limited due to a low response rate of 18.4%, this rate is comparable to other surveys on

business ethics and social responsibility.

Jackall (1988) studied the nature of moral behavior in organizations. He found

that the rules for success in an organization form a bureaucratic ethic that necessitates

separating personal morality from that of the organization. He further argued that

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personal ethics might be sublimated to get ahead in the organization. As Senge (1990)

pointed out, “Only [when the organization fosters values in alignment with peoples' own

core] will it be possible for managers to stop living by two codes of behavior, and start

being one person" (p. 312). The sublimation of personal values seems related to

Goodpaster’s (2004) description of how teleopathy, or the unbalanced pursuit of

organizational purpose, is characterized by fixation, rationalization, and detachment. And

as commitment to those higher in the organization increases, the need to sublimate

personal moral codes increases. Ashforth and Vaidyanath (2002) likened this process to

experiencing faith in the organization as a secular religion, with normative controls

instilling a shared moral code. Jackall further describes how managers' moral

compromises preserve the organizational culture:

As it happens, given their pivotal institutional role in our epoch, they help create and re-create, as one unintended consequence of their personal striving, a society where morality becomes indistinguishable from the quest for one's own survival and advantage. (p. 204)

To advance in an organization, an individual must assimilate its rules (Quinn et

al., 1997). As Jackall (1988) observed, as well as Ford and Richardson (1994), when one

shifts into the management structure of a large organization more is involved than a

simple change in job description. The management context is a social and cultural

environment, with rules of behavior that differ from society at large (Quinn et al.). These

rules of behavior are generally unwritten and sometimes communicated using oral

tradition, and the new manager must be able to determine and assimilate these using

observation and discussion (Quinn et al.). This assimilation is required for advancement

in the bureaucratic hierarchy (O’Neil & Pienta, 1994). The ethical rules for advancement

are external to the manager. Those who hold moral concerns that conflict with what the

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group collectively agrees to may be considered troublemakers, creating more pressure to

conform to move up (Quinn et al.). The assimilation process required for advancement

may be more difficult for low relativists who refuse to bend ethical rules. In contrast, the

moral anchor of the relativist is more likely to be attached to the anchor of the

organization’s culture (Quinn et al.). For this reason, the low relativist’s strict adherence

to a moral code could impact motivation to lead negatively. For example, describing a

foray into a management position, one individual said:

I do think it’s important to have some principles and that kind of thing. I actually feel good that I’ve been able to hang on to those. When you go through all this, especially if you try management. I’ll tell you the things… remarkable… people don’t realize. (Papavero, 1999, p. 57)

It is possible that, in addition to lower commitment to the organization, a universalist may

be less likely to imitate successful others who do not share their moral code. This could

also impact their motivation to lead.

Moore (2008) proposed that moral disengagement fosters organizational

corruption by rewarding decisions that advance organizational goals, whether or not these

decisions are ethical, and thereby dampening individual moral awareness. A talent in

prioritizing organizational goals above all else has been shown to be a top leadership

skill, especially valued in times of crisis or uncertainty (Bligh, Kohles, & Meindl, 2004).

It seems reasonable to expect that possession of this skill would affect advancement. For

example, Scott Sullivan advanced quickly at WorldCom in part because of his

willingness to misrepresent financial statements (Jeter, 2003). Andrew Fastow was

advanced by the leadership at Enron in part because it was understood that he would do

“whatever it took” to make Enron’s numbers (Mclean & Elkind, 2003). It is possible that

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some organizations reward those most willing to collude in corrupt practices

(Eichenwald, 1995).

Ethics and advancement are rarely studied (Moore, 2008). The structures and

processes that support organizational survival and growth could influence unethical

behavior without direct intention on the part of the organization. Dominant groups align

their interests with the corporation (Cyert & March, 2002; Thompson, 1967).

Organizational norms will reflect the norms of these groups, even when they sanction

corrupt behavior (Moore). It is possible that strong performers who are less sensitive to

ethical issues advance more quickly into leadership positions (Moore). These same

individuals will then create a climate which models, rewards, or further embeds corrupt

practices into the social structure (Moore). This could create strong situation pressures

that cause perpetuation of corrupt actions throughout the organization (Sims & Brinkman,

2002). Moore proposes that individuals higher in moral disengagement will advance

more quickly through the organizational hierarchy than those low in moral

disengagement.

It is possible that relativism makes it easier to sublimate personal ethics, which

could lead unintentionally to moral disengagement. For example, Cynthia Cooper, a

whistle-blower at WorldCom stated in retrospect that she was different than her

colleagues because she “refused to overlook actions that were contrary to her principles.

When evaluating her priorities, she would not succumb to the pressures placed by

superior figures” (Kumar, 2007, p. 5).

Ms. Cooper appears to have been able to maintain her moral congruence in this

case by whistle blowing. Moral congruence is defined as the condition and process of

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achieving consistency between self-selected moral values and the manifest behaviors of

the individual. In a qualitative study, Rodriquez (2005) found that morally congruent

managers felt loyal to their internal convictions and had an internal locus of control.

These managers viewed being morally congruent as a life-long process of discovery,

sense making, alignment, critical self-reflection, and self-correction. They saw

incongruence as the door to congruence, such that a loss of inner peace was a wakeup call

to change, and they believed that leaders must be morally congruent to generate

congruence in others.

The cognitive dissonance produced by ethical conflict may be interpreted in a far

different way than as a call for personal growth and development. To eliminate the cause

of cognitive dissonance, the individual may leave the organization as a way to reduce

associated stress. Further, avoiding leadership roles could be considered as a parallel to

leaving the organization, insofar as this avoidance could be seen as a coping mechanism.

The ethical reasoning process could be influenced by moral philosophy. Ethical reasoning

is thought to occur in steps that include: (a) identifying the dilemma, (b) developing an

ideal solution, (c) formulating an intention to act, and (d) ethical action (Peterson, 2003).

Relativism may influence the formulation of intention to act based on potential outcomes.

The relativist may rationalize intentions to act in a way that is ethically acceptable based

on the situation: Organizational goals must be achieved at any cost. This rationalization

could also result in an increase of their perception of PO fit, removing any influence that

low PO fit may have had on motivation to lead. This adaptation process may take place

on a regular basis in many daily scenarios of potential ethical conflict in order to decrease

the discomfort caused by cognitive dissonance. Further, the instances of adaptation

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increase with hierarchical level, and those cognizant of this may experience lower

motivation to lead. Again, the low motivation to lead that may result from poor PO fit

could be likened to the intention to leave, where the hierarchical level is abandoned rather

than the organization. In an exploration of the individual decision to refuse an

advancement offer, it was found that anticipation of compromising values was a major

factor in the decision to turn down a promotion (Papavero, 1999). Relativists may

rationalize that ethics at work do not have to match ethics in personal life, as what is

ethical changes with the situation.

Idealism and the motivation to lead.

Aggressiveness, materialism, high achievement motivation, and traditional sex

role divisions are antiethical to the “person-centered, humble, nurturing, and

interpersonally sensitive orientation of high idealism” (Cui, Mitchell, Schlegelmilch, &

Cornwell, 2005, p. 26). This seems to indicate that idealism is negatively related to

motivation to lead.

Idealists have been found to be more ethically sensitive than those low in idealism

(Bass, Barnett, & Brown, 1999; Chan & Leung, 2006). Idealism has been found to be

positively related to ethical perceptions, judgments, intent, and behavior (Shaub et al.,

1993). Idealists are less likely to engage in organizational and interpersonal deviance

(Henle, Giacalone, & Jurkiewicz, 2005), and, in China, they were more likely to report

the unethical behavior of peers (Chiu & Erdener, 2003). The high ethical sensitivity of

idealists may occur because they place a greater importance on ethics and social

responsibility than those low in idealism (Tansey, Brown, Hyman, & Dawson, 1994).

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The ethical sensitivity of idealists may be attributable in part to their almost

singular focus on costs for none when considering consequences (Forsyth, 1992).

Idealists have been found to be low in Machiavellianism, where manipulative, persuasive,

and deceitful behavior is used to achieve goals (Bass et al., 1999; Leary, Knight, &

Barnes, 1986). However, idealists are willing to be disloyal and they are more likely to lie

or engage in an immoral act if they perceive that human welfare will benefit (Byers &

Powers, 1997; Forsyth). On the other hand, Forsyth and Schlenker (1977) found that

idealists see obedience as positive behavior. This gives one explanation as to why

Chonko, Wotruba, and Loe (2003) discovered that idealists find ethics codes more useful

than pragmatists. This could also explain why idealists have been found to experience

higher levels of intrapersonal role conflict. It could be difficult to be simultaneously

obedient and cause no harm to others. Idealists are more likely to experience

incompatible expectations, especially when organizational values are not clear (Sims &

Keon, 2000; Tsai & Shih, 2005). In addition, due to low pragmatism, idealists can

become divorced from practice.

Organization-professional conflict can occur when professionals are forced to

focus on profit rather than professional goals, or when organizational demands diverge

from accepted professional behavior, especially when these demands are unethical. In a

cross-sectional study of 319 accountants at various organizations, Shafer et al. (2002b)

used structural equation modeling to examine the relationships among professionalism,

organization-professional conflict, and organizational commitment. Organization-

professional conflict was found to have a negative relationship with organizational

commitment. As the idealist is more committed to their profession, they may be more

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likely to experience organization-professional conflict. They may therefore be less

committed to the organization.

The association of idealism with organization-professional conflict, and further,

the relationship of this conflict with lower organizational commitment, suggests that

highly idealistic individuals may be reticent to take a leadership role. Further, idealists

may be harder on themselves in regards to failure (Forsyth, 1992), which may lessen their

attraction to leadership situations that they may view as more risky. With their concern

for costs and protecting the general welfare, they may avoid leadership roles that require

decisions that harm other employees. This may be especially true if, given the idealist’s

higher ethical sensitivity, they are more likely to perceive unfair or unethical behavior

and sense that they would be required to impose the consequences of this behavior on

their subordinates. For example, when discussing the decision to leave a leadership

position, an individual stated:

You’re affecting people’s lives and their families with these things. That’s what I found offensive. You don’t really have the power to make things better for them but you have the responsibility for being the one that hits them with it, whether it’s a bad salary or whether it’s a layoff. (Papavero, 1999, p. 58)

Conceptualizing and Studying Motivation to Lead

Where leadership emergence describes the “what” of people who lead (that is,

their individual characteristics), motivation to lead answers the question of why they

want to lead. Before Chan’s (1999) proposal of the motivation to lead construct, some

work was done in this area, most notably that of House and Singh (1987). They proposed

three psychodynamic attributes of people who are motivated to lead: (a) high power

motive, (b) high activity inhibition, and (c) low affiliation need. Although power and

control may be important motivators for some, this cannot be assumed to be true for all

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leaders. The individual differences of leaders seem a logical avenue to explore to

discover more about the diverse and complex motives that drive their attraction to

leading.

Theoretical model of the motivation to lead.

Chan (1999) recognized that a theoretical framework was needed to link

individual differences and various leadership behaviors. He noted that prior research

discredited the role of individual differences. Later, individual differences came back to

the fore, but much of the work used bivariate correlations rather than multivariate

models. Chan also agreed with Lord and Hall (1992) by identifying a criteria problem

affecting research in this area, in that leader perception, leader emergence, and leader

effectiveness were often treated as equivalent.

Chan’s (1999) intent was to differentiate leader emergence and performance. He

also suggested that the research focus should move in a different direction regarding

individual differences. Rather than measuring direct relationships between individual

differences and performance, we should consider that “non-cognitive constructs such as

personality and values may be linked to leadership performance through the process of

leadership development” (Chan, p. 86). It is important to recognize that Chan did not

suggest that motivation to lead predicts leader effectiveness. However, he did conjecture

that motivation to lead might relate to leader effectiveness indirectly by predicting morale

and job satisfaction.

Chan (1999) defines motivation to lead in terms of a definition of motivation

where internal processes determine direction (the decision to lead), intensity (effort given

to leading), and persistence (leading during adversity). The motivation to lead construct

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represents individual differences that can affect these leadership behaviors. Individual

differences included in motivation to lead are considered relatively stable. However,

motivation to lead could interact with external factors such as domain and task. For

example, motivation to lead may change if one takes part in leadership training. Further,

motivation to lead integrates leader development and leader performance by including

past leadership experience in the framework. Learned knowledge and skills from

leadership experiences are also antecedents of motivation to lead. Leadership experiences

cause one to seek out more training and further development occurs. A feedback loop is

created where each experience interacts with motivation to lead to create different

performance outcomes.

The motivation to lead construct.

Chan (1999) based the dimensions of motivation to lead on Meyer and Allen’s

(1991) model of organizational commitment. Meyer and Allen identified a

multidimensional construct of commitment with affective, normative, and calculative

types. The sources of each type of commitment are different: affective commitment is

sourced in a need for achievement, calculative commitment in job investment, and social-

normative commitment in socialization in the organization. Affective commitment is

thought to be related to intrinsic motivation and relational psychological contracts,

whereas social-normative commitment is thought to be related to extrinsic motivation,

and both calculative and social-normative commitment are thought to be related to

transactional psychological contracts (Meyer, Stanley, Herscovitch, & Topolnytsky,

2002).

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Chan (1999) also identified conceptual similarities between the commitment

model and two major social behavior theories: Fishbein and Ajzen’s (1975) theory of

reasoned action (TRA) and Triandis’ (1980) theory of interpersonal behavior (TIB). TRA

sees intent to act as based on individual attitude regarding outcome valence and perceived

social norms. Similarly, TIB explains behavior through four constructs: cognition, affect,

social norms, and personal norms. The common components of these models

(attitude/affect, cognition, norms) were then mapped to three possible dimensions of

motivation to lead: people like to lead (affective-identity motivation to lead), people

make a rational decision to lead (calculative or instrumental motivation to lead), and

people feel it is their duty to lead (social-normative motivation to lead). Chan reasoned

that it made more sense to predict a strong non-calculative dimension in those with a

motivation to lead because there is often a cost associated with leading.

It is important to clarify the meaning of non-calculative motivation to lead.

Although Chan’s (1999) description could lead one to believe that this dimension

indicates the level to which someone disregards the cost of leadership, Hiller (2005)

pointed out that the antecedents to non-calculative motivation to lead actually heavily

emphasize the choice to lead as a selfish one based on rewards and benefits. For example,

a person high in non-calculative motivation to lead would give a low rating to this item:

“I would only agree to be a group leader if I know I can benefit from that role.” A person

low in non-calculative motivation to lead would weigh individual costs and benefits, and

lead only if there were a net benefit. They would consider all types of costs, including

non-economic ones. However, there may be individual differences in awareness of costs

and the weights assigned to them.

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Someone higher in non-calculative motivation to lead would lead even if there

were no net benefit. However, this does not mean that those higher in non-calculative

motivation to lead do not consider the costs. To paraphrase Hiller (2005), a person higher

in non-calculative motivation to lead is not necessarily someone who simply is not aware

of the costs of leadership. Rather, an individual higher in non-calculative motivation to

lead would disregard the costs, even if they were aware of them. Non-calculative

motivation to lead will be looked at closely in the dissertation study, as Chan, Ong, and

Chah (1999) suggested that the choice to lead is a social dilemma, where an individual

must choose between their own interests and those of the collective. As such, if costs or

benefits are inordinately high, an imbalance could be created in the leadership pool to the

detriment of the collective.

Previous research was used to identify possible antecedents to motivation to lead:

general cognitive ability, personality traits, values, self-efficacy beliefs, and past

leadership experience. Focus groups were then used to develop items that measured each

of the three motivation to lead dimensions. The instrument resulting from Chan’s (1999)

work incorporated measurements of the Big Five personality factors developed by

Goldberg (1999), the Individualism-Collectivism values measure developed by Singelis,

Triandis, Bhawuk, and Gelfand (1995), and the Leadership Self-Efficacy scale developed

by Feasel (1999). Leadership experience was measured using biographical data and self-

reports, and cognitive ability was measured using results from previously administered

standardized tests. Using three samples (1,594 Singapore military recruits, 274 Singapore

students, and 293 U.S. students) and hierarchical regression analysis, Chan found patterns

and paths between antecedents and the motivation to lead dimensions. He cited

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limitations in that the age range was narrow (17 to 21) and situation was not included in

the model. However, the model was developed with situation in mind, and the present

study seeks to extend Chan’s work by exploring a situational variable, PO fit, in relation

to motivation to lead.

Chan’s (1999) results showed that personality, values, and leadership experience

were all related to motivation to lead, both directly and through leadership self-efficacy.

Both leadership self-efficacy and past leadership experience were related to motivation to

lead, suggesting that motivation to lead “is a dynamic construct that is partially

changeable through social-learning processes and experience” (Chan & Drasgow, 2001,

p. 496). Chan did not find that cognitive ability predicted motivation to lead.

Relevant studies using Chan’s motivation to lead construct.

Chan, Rounds, and Drasgow (2000) studied the relationship between vocational

interests and the motivation to lead construct. Using Holland’s (1973) RIASEC model of

occupational interests, motivation to lead was found to be orthogonal to occupational

types. Chan et al. concluded that motivation to lead is independent of vocational interests.

It is therefore not expected that participants in the present study with different

occupations would vary in level of motivation to lead.

Chan (2001) later conducted a two-year long longitudinal stability study (at one-

year and two-year intervals) of the motivation to lead scale and several antecedents of

motivation to lead (personality, individualism/collectivism, leadership self-efficacy). This

study used a subset of the Singapore military sample from his original study (Chan,

1999). The results showed that motivation to lead was stable; more stable than

individualism/collectivism values, but less so than the personality measures. Motivation

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to lead did change with increased work experience. Affective-identity motivation to lead

and social-normative motivation to lead increased over time. Also, the non-calculative

motivation to lead of those who became officers during the study increased. Limited

support was also found for a developmental feedback loop between motivation to lead

and leadership experience. Given these results, the present study will include control

variables for age, organization tenure, work experience, previous leadership experience,

and current job level.

Chan’s (1999) motivation to lead construct has been used in several other studies.

Cintrón (2004) studied the motivation to lead of Hispanic women using Chan’s

motivation to lead scale, along with an acculturation scale and an emotional intelligence

scale. She found that emotional intelligence and biculturalism predicted motivation to

lead, which may support Chan’s finding that emotional stability is related to motivation

to lead. However, no significant results were found regarding acculturation and the

motivation to lead. Cerff (2006) used regression analysis with a sample of 200 university

students in South Africa and found that hope and self-efficacy predicted motivation to

lead. However, her study did have some limitations in that the sample was sourced in one

region in Cape Town.

Erickson (2005) explored the antecedents of motivation to lead across the lifespan

and in relation to vocational interests using a sample of 63 leaders at a Pentagon office.

Using hierarchal multiple regression, he also looked at a possible situational factor

(collective efficacy, or a shared belief of a workgroup in the team’s capabilities) and its

relationship to both motivation to lead and the motivation to lead antecedent of self-

efficacy. His sample was older (28 to 62), more educated, and more experienced than

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Chan’s (1999). Erickson’s results supported the internal reliability of the motivation to

lead scales. His results also indicated that antecedents to motivation to lead may change

over the lifespan and when occupations change. Erickson’s results also supported Chan

and Drasgow’s (2001) findings that motivation to lead changes with work experience, but

they contradicted Chan et al.’s (2000) findings that motivation to lead is independent of

vocational interests. Finally, Erickson found that the situational factor, collective

efficacy, had no effect on motivation to lead. However, he cites the limitations of his

single context sample as one explanation for this result. Erickson did suggest PO fit as a

possible situational factor worthy of future research, which lends further support for the

present study.

Studies on motivation to lead and situation.

Others have studied motivation to lead and situation, but have not used Chan’s

(1999) construct. Kabacoff (2002) studied the relationship between emotional drivers and

leadership behaviors with a large (N = 1,300) sample of U.S. and Canadian managers. He

used the Individual Directions Inventory (IDI) to measure motivational factors and the

Leadership Effectiveness Analysis (LEA) to measure leadership behaviors. Citing

limitations in current research, including that of Chan and Drasgow (2001), he studied a

“wide range of personal motivators and leadership behavior within a broad array of

organizational settings“ (p. 1). He suggests that leadership requirements are driven by

context, and that emotional drivers must be matched to these requirements. For example,

someone who thrives on affiliative experiences would not be a good match for a position

requiring dominant, controlling behaviors. This work gives some support for the idea that

situation may be related to motivation to lead.

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Richter (2001) developed a survey measuring the correlation between

encouragement, opportunity, and the success of past leadership with the motivation to

move up from teaching to school administrator positions. She also used qualitative data to

triangulate the quantitative survey results. Richter found that educators were motivated to

move into leadership positions when they were encouraged to do so. She found a very

strong relationship between familiarity with the leadership role and the motivation to

lead. Richter also found strong links between both financial interests and positively

affecting children’s lives, and the motivation to lead. She did not find any relationship

between mentoring or past leadership success, and motivation to lead. She cited many

contextual elements of the educational system structure that could be responsible for

these results. The sole path to an increased salary was through an advanced degree and an

administrative role. However, she questioned the financial motive, and the structure that

compels it, by positing that it may not attract people who are motivated for reasons that

will make them effective leaders.

In an article from a newsletter of the Chronicle of Higher Education, Jacobson

(2002) interviewed academics that rejected promotions. The academics reported that they

believed their quality of life would be impacted adversely, and that higher pay was not

worth this sacrifice. Many said they were happy with research and teaching, and were not

interested in the administrative aspects of higher-level jobs. They preferred to move up in

their fields, rather than climb an administrative career ladder.

Whetstone (2001) contrasted police officers that sought promotions and those

who did not. Officers that did not pursue promotion often cited a discrepancy between the

effort required and the pay. They felt officers had more flexibility with assignments and

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schedules, which indicates that work-life balance was also a concern. Some officers were

not attracted to the duties of a sergeant. They did not want to “lose touch with the streets”

(p. 155). Organizational complaints were also found. Officers not interested in promotion

distrusted their managers and the selection process itself.

Howard and Wilson (1982) studied the motivation to lead by contrasting studies

from the 1950s and 1970s. They found that in the 1970s sample, the motivation to move

up the corporate ladder was significantly reduced and expectations regarding work life

were much lower. The 1970s sample was also found to be much less interested in

dominating others. Howard and Wilson did find, through qualitative means, that this did

not necessarily indicate a desire to follow, but rather a rejection of the leadership role and

the organizational hierarchy. They attributed these differences to a problem with fit

between organizational and personal values.

A qualitative study of six software engineers who rejected promotions to

management positions was conducted by Papavero (1999). The results indicated that the

engineers were not motivated to lead for a number of reasons. They considered the costs

associated with leading to be too high. These included increased emotional and time

demands, and pressure to violate their principles (e.g., laying subordinates off, lying to

their subordinates, and making unreasonable and unfair demands on their subordinates).

This may indicate that the engineers had a low level of non-calculative motivation to

lead. It may also indicate that idealism caused them to avoid affecting individuals

negatively. The engineers also stated that they valued people first, whereas the

organization’s values could be summed up as “success at all cost,” indicating a possible

low level of PO fit and a less relative moral philosophy.

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Several of the parallels between software engineers, educators, academics, and

police officers are striking. It is notable that all of these professionals were given a choice

to lead that entailed forfeiting their chosen profession. Idealism might have contributed to

their reluctance to leave their profession and potentially cause harm to others. Also,

because they would lose a large investment in their profession, this cost may have also

been a factor in their decision, indicating lower non-calculative motivation to lead.

Motivation to Lead Antecedents

The literature discussed to this point argues that PO fit may affect motivation to

lead. However, a more detailed analysis of how situation may affect the antecedents

motivation to lead, and therefore the motivation to lead dimensions themselves, gives a

more detailed view of the role of PO fit as a situational factor.

Personality trait antecedents and situation.

Chan (1999) found four of five personality traits (extraversion, agreeableness,

conscientiousness, and emotional stability) to be direct antecedents of motivation to lead.

The fifth trait, openness to experience, was related to motivation to lead though past

leadership experience and leadership self-efficacy. Shin and Holland (2004) found that

PO fit moderated the prediction of job performance from these traits. Although the

present study concerns motivation to lead attitudes, Shin and Holland’s results suggest

that this analysis has value.

Extraversion was positively related to both affective-identify motivation to lead

and social-normative motivation to lead through leadership self-efficacy. However, it is

possible that extraversion could be affected by situation. Some confirmation of this

comes from a study of extraversion, situational factors, and evolutionary principles by

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Campbell, Simpson, Stewart, and Manning (2003). They used small work groups

consisting of men who were evaluated by an attractive man or woman, or not evaluated at

all. In this intrasexually competitive situation, Campbell et al. found that “more

extraverted men were significantly more likely to emerge as leaders, but only in the

female-evaluator condition” (p. 1556). This result indicates that extraversion is a

personality trait that is used selectively. A person may choose to behave in an extraverted

way and take a leadership role only when there is a perceived benefit, or norms require it.

This may explain the absence of a relationship between extraversion and non-calculative

motivation to lead in Chan’s (1999) study, where situation was not taken into account.

Extraverts may be more likely to calculate leader costs and benefits based on the

situation. Although the female evaluator situation may not be related to PO fit, these

results show that situation can change the extravert’s decision to lead; that is, situation

can change the demonstration of a behavior expected from a relatively stable individual

difference that is an antecedent of motivation to lead.

Agreeableness was positively related to non-calculative motivation to lead and

social-normative motivation to lead in Chan’s (1999) study. However, situation might

change an agreeable person’s calculation of costs and benefits and sense of duty. For

example, agreeable individuals have been found to be more committed to their

organizations (Cohen-Charash & Spector, 2001). However, if an individual perceives a

low level of organizational justice, they are less committed to the organization, even if

they are agreeable (Cohen-Charash & Spector). Software engineers (Papavero, 1999) and

police officers (Whetstone, 2001) perceived unjust environments and exhibited low

motivation to lead. An unjust environment does not necessarily indicate low PO fit;

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however it may be related to a person’s perception of values mismatch. Therefore, PO fit

could have an effect similar to low justice, and change the relationship between

agreeableness and motivation to lead, giving a less positive relationship than if PO fit

were not considered.

Conscientiousness was positively related to social-normative motivation to lead

and affective-identify motivation to lead through leadership self-efficacy. Similar to

agreeableness, when in a specific situation, a conscientious person might decide that it is

best not to take a leadership position if they are convinced it is impossible to do a good

job. For example, one of the reasons that software engineers (Papavero, 1999) gave for

declining promotions was that they believed they would have to make unreasonable

demands on their people due to a lack of resources. Therefore, PO fit could change the

relationship between conscientiousness and affective-identity motivation to lead.

Idealism may also change this relationship, given the idealist’s strong desire to cause no

harm to others.

Emotional stability was positively related to non-calculative motivation to lead. It

is entirely possible that situational aspects, such as high conflict or limited resources,

could affect emotional stability negatively. Siegall and McDonald (2004) found that low

PO fit had a strong association with burnout (emotional exhaustion; depersonalization of

co-workers, customers, and administrators; and feelings of diminished personal

accomplishment). In a high-stress context, an emotionally stable person might exceed

some level of tolerance that causes them to become more calculative in their decision to

lead, or more cognizant of costs (actual or perceived). We know that stress can affect

leader performance. For example, Sissem (2004) found that positive leadership in the

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context of adult education was reduced when leaders were placed under stress. PO fit has

been shown to be negatively related to stress levels (Choi, 1998). Therefore, PO fit could

contribute to stress, and alter the relationship between emotional stability and non-

calculative motivation to lead, giving a less positive relationship than if PO fit were not

considered.

Openness to experience was positively related to affective-identify motivation to

lead and social-normative motivation to lead through previous leadership experience and

leadership self-efficacy. One possible situational variable that might change this is an

exclusionary promotion process. If someone is open to experience, but they are low in PO

fit, they may not be given the opportunity to gain leadership experience and,

consequently, leadership self-efficacy. Therefore, the relationship between openness to

experience and affective-identify motivation to lead and social-normative motivation to

lead may diminish when low PO fit is present.

Values antecedents and situation.

Collectivist values, both horizontal (collective harmony and equality) and vertical

(accept social hierarchies and subordinate goals to majority or authority), were positively

related to non-calculative motivation to lead and social-normative motivation to lead

(Chan, 1999). However, some organizational cultures may foster collectivist values by

inspiring trust and feelings of membership, while others do not. PO fit has been positively

related to level of trust (Tikanmaki, 2001). Therefore, PO fit may affect the relationship

between collectivist values and non-calculative motivation to lead and social-normative

motivation to lead.

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Horizontal individualism (individuality and uniqueness) was negatively related to

non-calculative motivation to lead and social-normative motivation to lead (Chan, 1999).

Organizational culture might affect this value. A very bureaucratic organizational culture

that demands consistency and unquestioning loyalty might not fit a person with these

values. However, an organization that values individual contributions and is less

concerned with creating a homogenous workforce might attract this type of individual to

a leadership role. Therefore, PO fit on horizontal individualism may change the

relationship between horizontal individualism itself and each of non-calculative and

social-normative motivation to lead.

Vertical individualism (achievement oriented and competitive) was positively

related to all three motivation to lead dimensions (Chan, 1999). However, if achievement

is not appreciated and rewarded (e.g., in an organization high in nepotism) this might not

be the case. Additionally, vertical individualists working in organizational cultures with a

high level of affiliation may not be attracted to leadership positions because they would

have to care for their subordinates’ social needs. In other words, PO fit on vertical

individualism may be a factor, as the value of vertical individualism may not be

supported by the organizational culture.

Finally, a related point concerning the individualism and collectivism constructs

themselves is given by Ryckman and Houston (2003). They note that it may be more

accurate to “conceptualize individualism and collectivism as two separate dimensions in

which cultures and individuals can be classified as high or low on both dimensions”

(p.135). Workers, and organizational cultures, could be collectivist and individualist to

different degrees at the same time. These combinations (i.e., additional dimensions of

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individualism/collectivism) may need to be considered in future research on motivation

to lead.

Leadership antecedents and situation.

Leadership self-efficacy and past leadership experience were positively related to

affective-identify motivation to lead and social-normative motivation to lead. The

promotion process may be key to this result. If individuals are generally promoted

because they share the values of existing leadership, or because they are less idealistic,

others may not be given the opportunity to gain leadership experience and leadership

self-efficacy. Similar to openness to experience, PO fit could affect leadership self-

efficacy, and therefore affective-identify motivation to lead and social-normative

motivation to lead.

Summary of motivation to lead antecedents and situation.

The majority of the personality and values antecedents of the motivation to lead

dimensions have the potential to be impacted by PO fit and idealism. In general, lower

PO fit and higher idealism are each expected to predict lower levels for each motivation

to lead dimension. However, the antecedents of the affective-identity dimension are

mainly personality differences that are more stable and may be less likely to change.

Summary of Literature Review

This review reveals that employees are self-selecting away from leadership

positions. This may be occurring for a variety of reasons, but a central theme appears to

be values incongruence and idealism. Exploring this phenomenon is important because it

may be contributing to a situation where the values of leaders may be less diverse than is

desirable. For example, in a study of women and leadership, Billing and Alvesson (1989)

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point out that “organizational selection and socialization processes seem to lead to a

mainstreaming of candidates where proposed beneficial women-specific attributes are

lost” (p. 16). We may have converged on this state because those with values that match

the organization (or those whose values do not match, but are willing to change) may be

more likely to be motivated to lead.

The identification of those who are avoiding leadership in their current

organization, but who possess leadership ability, could bring rich information, generating

positive changes in the organization. This information may identify other situations that

could be affecting their decisions. Also, those outside the dominant culture may be better

able to question and extend the organization’s values to make positive change. It may be

beneficial to find ways to encourage their contributions. With a diversity of values in

leadership, we would be better able to work together to balance moral strengths and

weaknesses in each other and create more ethically resilient organizations. This study

takes a first step by identifying additional factors that may be related to motivation to

lead.

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Chapter 3: Methodology

Overview

The two main objectives of this research were to determine if PO fit predicts an

individual’s motivation to lead, and to determine if idealism predicts motivation to lead.

A secondary purpose was to determine if PO fit predicts motivation to lead when

moderated by moral relativism. The answers to these questions are significant because

they may indicate that certain individuals are not assuming leadership roles and

contributing fully to their organizations. This may result in less diversity in leadership

values than is desirable.

Restatement of Hypotheses

H1: Lower levels of PO fit will predict lower levels of general motivation to lead,


H2a: PO fit will not be associated with affective-identity motivation to lead.

H2b: Lower levels of PO fit will predict lower levels of affective-identity


characteristics.


to lead, over and above personal, job, and organization characteristics.



characteristics.

H5: Lower levels of PO fit will predict lower levels of general motivation to lead

when relativism is low, over and above personal, job, and organization

characteristics. However, lower levels of PO fit will not predict lower

levels of general motivation to lead when relativism is high.

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H6: Lower levels of PO fit will predict lower levels of affective-identity



predict lower levels of affective-identity motivation to lead when

relativism is high.


to lead when relativism is low, over and above personal, job, and

organization characteristics. However, lower levels of PO fit will not

predict lower levels of non-calculative motivation to lead when relativism

is high.




predict lower levels of social-normative motivation to lead when

relativism is high.

H9: Higher levels of idealism will predict lower levels general motivation to lead,


H10a: Idealism will not be associated with affective-identity motivation to lead.

H10b: Higher levels of idealism will predict lower levels of affective-identity


characteristics.

H11: Higher levels of idealism will predict lower levels of non-calculative


characteristics.

H12: Higher levels of idealism will predict lower levels of social-normative


characteristics.

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Research Design

The present study used a quantitative non-experimental predictive design. The

design allowed the prediction of motivation to lead from PO fit, idealism, and relativism

over and above control variables. Using a predictive design is also consistent with

previous research that assessed the prediction of commitment from PO fit (Cable &

Judge, 1996; Chatman, 1991; O’Reilly et al., 1991). An earlier study also predicted

motivation to lead from personality, values, leadership, self-efficacy, and past experience


One survey was used to collect all data. In addition to the predictor and criterion

variables, the data collected included several descriptive variables concerning personal,

job-related, and organization-related characteristics, which were used as control

variables: (a) age, (b) gender, (c) ethnicity, (d) educational background, (e) number of

years of work experience, (f) number of years of leadership experience, (g) job level, (h)

number of years in position, (i) employment status (full-time or part-time), (j) number of

employees in organization, and (k) number of years at organization. These variables were

used as controls to predict motivation to lead over and above personal, job, and

organization characteristics.

Operational Definition of Variables

The variables in this study were all measured at the individual level of analysis.

Three predictor variables (PO fit, relativism, and idealism) and three criterion variables

(affective-identity motivation to lead, non-calculative motivation to lead, and social-

normative motivation to lead) were measured.

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PO fit is defined as the values similarity between individuals and their

organizations, measured by asking for the individual’s subjective assessment.

Relativism is a moral philosophy where ethics change given the situation.

Idealism is a moral philosophy that strongly prefers to find solutions that do not harm

others. Both relativism and idealism were measured using Forsyth’s (1980) Ethics

Position Questionnaire.

Affective-identity motivation to lead is seeing one’s self as a leader, non-

calculative motivation to lead is not including the cost of leadership in the decision to

lead, and social-normative motivation to lead is leading to benefit the group. All

motivation to lead variables were measured directly using Chan’s (1999) motivation to

lead instrument. General motivation to lead was not measured directly as it was derived

from the three first-order motivation to lead dimensions.

Instrumentation

PO fit was measured with three questions created by Cable and DeRue (2002).

The three PO fit items are shown in Appendix A. The response scale ranged from 1

(strongly disagree) to 7 (strongly agree). Scores for the three items were summed (giving

a range of 3 to 21) to obtain the degree to which participants perceived that their values

matched that of the organization and the organization’s employees. Cable and DeRue

found predictive validity by comparing results from these questions to those from a

measure of congruence of reported individual and organizational values. Cable and

DeRue found a coefficient alpha reliability of .92 in their multi-organization sample, as

compared to alpha reliability of .91 in the present study.

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Moral philosophy was measured using Forsyth’s (1980) Ethics Position

Questionnaire (EPQ). The EPQ measures two orthogonal dimensions of moral

philosophy, idealism and relativism, using 10 items per dimension. The 10 relativism

items and 10 idealism items are shown in Appendix A. Each item was rated using a scale

of 1 (strongly disagree) to 5 (strongly agree). Scores for each dimension were summed

individually (giving ranges of 10 to 50) to determine level of idealism and level of

relativism. Forsyth found that the measures were not affected by social desirability, and

he found discriminant validity in that the measures were not related to the Defining Issues

Test (DIT). Forsyth also found predictive validity as the EPQ results mapped to predicted

moral judgment processes. Forsyth found coefficient alpha reliabilities of .80 and .73 for

idealism and relativism respectively, as compared to .89 and .84 in the present study.

Motivation to lead was measured using Chan’s (1999) motivation to lead

instrument. This is a three-dimensional measure, with 9 items for each dimension. The

motivation to lead items are shown in Appendix A. The introductions to the items were

modified to focus the participant on their current organization when considering the

questions. Each item was rated on a scale of 1 (strongly disagree) to 5 (strongly agree).

Scores were summed for individual dimensions (giving ranges of 9 to 45) to obtain levels

for affective-identity, non-calculative, and social-normative motivation to lead. Because

these dimensions were correlated, Chan and Drasgow (2001) found support for a second-

order general motivation to lead measure underlying the three first-order dimensions.

Scores for each dimension were summed, and the result was divided by the number of

dimensions to obtain the level of general motivation to lead. This gave general motivation

to lead the same range as the first-order dimensions (9 to 45).

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Chan (1999) found strong incremental validity for the motivation to lead construct

over its antecedents. He also found strong internal validity, as the construct was not

equivalent to any of the other constructs (personality, values, leadership, self-efficacy,

and past experience) used to measure its antecedents. Although his sample was diverse in

occupation, culture, and gender, it was not diverse on age. However, Erickson (2005)

performed a validation study of Chan’s construct using older participants, and found

internal reliability.

For the general motivation to lead scale, low reliability (α = .54) was reported in

one study of Latinas (Cintrón, 2004), and for all motivation to lead scales, low reliability

was reported in another study of South Africans (Cerff, 2006). However, low reliability

did not occur in the present study. The coefficient alpha reliabilities for affective-identity,

non-calculative, and social-normative motivation to lead found by Chan and Drasgow

(2001) in their study using three samples were .84-.91, .80-.94, and .65-.75 respectively,

as compared to those of the present study, which were .85, .85, and .81.

Sampling

A priori power calculations.

In order to achieve adequate power for this study, a priori sample size calculations

for small, medium, and large effect sizes were performed for the first type of inferential

test, which was hierarchical multiple regression. A priori sample size calculations for

small, medium, and large effect sizes were also performed for the second type of

inferential test, which was moderated multiple regression. Every effort was made to

obtain a sample size that met the requirements of the largest required sample size

(assuming a medium effect) resulting from these calculations.

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A free sample size calculator for hierarchical regression (Soper, 2007a) was used

to find minimum sample sizes for small, medium, and large effects. The results are

shown in Table 1. The result for a medium effect showed that a sample size of 75 would

be required for the hierarchal multiple regression tests to achieve adequate power.

Tabachnick and Fidell (2001) give another way to calculate sample size for multiple

regression that tests the ratio of the number of participants to predictors (N ≥ 104 +

number of predictors). With 21 control variables and two predictors (PO fit and idealism)

the required sample size was 127.

Table 1. Hierarchical Multiple Regression: A priori Power Calculation

Final Block Effect Size Calculation Parameters Sample Size

Small (.02)

Alpha level: .05 Predictors in previous blocks: 21 Predictors in final block: 1 Desired statistical power level: .80

406

Medium (.15)


75

Large (.35)


46

Four analyses were performed to determine the required sample size for the

moderated multiple regression tests. First, the same calculator used for the hierarchical

multiple regressions was used to calculate sample size for the moderated multiple

regression tests (Soper, 2007a). The results are shown in Table 2. The required sample

size for a medium effect was 77.

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Table 2. Moderated Multiple Regression: A priori Power Calculation Not Considering Coefficient Differences

PO fit X Relativism Effect Size Calculation Parameters Sample Size

Small (.02)


408

Medium (0.15)


77

Large (0.35)


48

The second analysis for moderated multiple regression used a table offered by

Aguinis (2004, p. 114) that shows required sample sizes for varying power levels and

moderator group correlations, assuming equal sample sizes for the groups. The table

considers the differences between the regression coefficients for the two moderator

groups to determine the power that a sample size will give. The power becomes lower as

the differences between the regression coefficients become smaller. The results gathered

by looking up entries for one group with a zero coefficient (expected effect for high

relativism) and each of small (.1), medium (.3) and large coefficients (.5) for the second

group (low relativism) gave a required sample size of 400 for a medium difference and

120 for a large difference.

The third analysis used Aguinis, Boik, and Pierce’s (2001) MMRPOWER tool to

calculate power considering the differences in the sizes of the two moderator groups (low

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and high relativism), in addition to differences in the regression coefficients. The results

are shown in Table 3. The result for a medium coefficient difference showed that a

sample size of 1,500 was required for the moderated multiple regression tests to achieve

adequate power for a medium interaction effect size for low relativism.

Table 3. Moderated Multiple Regression: A priori Power Calculation Considering Coefficient Differences

PO fit X Low Relativism Coefficient Calculation Parameters Sample Size

Small (.10)

Alpha level: .05 PO fit X high relativism coefficient: .01 Statistical power level: .85

90,000

Medium (.30)


1,500

Large (.50)


300

For the fourth analysis, Tabachnick and Fidell’s (2001) calculation (N ≥ 104 +

number of predictors) was used with PO fit and idealism, 21 control variables, and

relativism as an additional predictor, giving a required sample size of 128. The results of

all analyses for moderated multiple regression produced four sample sizes ranging from

77 for a hierarchical multiple regression analysis not accounting for differences in

moderator group sizes (i.e., when the moderated regression was treated as a more simple

hierarchical multiple regression, with the interaction term included as an additional

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predictor) to 128 using a participants to predictors ratio calculation, and from 400 using a

table source assuming equal moderator group sizes to 1,500 for differing group sizes.

Because one sample was used for both the hierarchical multiple regression and the

moderated multiple regression tests, an attempt was made to satisfy the largest of all

requirements, which is that of moderated multiple regression. As it was not known if it

would be feasible to obtain a sample of 1,500 in this study, a sample size of 400 was

considered adequate, and it was assumed that moderator group sizes would be balanced.

The balanced group assumption seemed reasonable, as the groups would be created by

gathering scores one standard deviation above mean relativism and one standard

deviation below mean relativism, rather than by splitting using a dichotomous moderator

value, such as gender. In fact, it was found in the present study that the groups were

sufficiently balanced, as 45% of the participants were highly relative.

Selection of participants.

A non-random sampling design and a convenience sampling method were used in

the present study. Participants with a variety of attributes were required, as levels of

motivation to lead, PO fit, and moral philosophy are each present for any individual who

works in an organization. The goal of recruitment was to include participants with diverse

educational backgrounds, job levels, and experience who work in organizations of

varying sizes.

Participants were adults, age 18 and over, who were employed in organizations of

various sizes. Self-employed participants were not sought. The survey included questions

on employment status that were used to qualify participants.

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Each person from a list of 279 personal and professional contacts received a

recruitment e-mail containing a request for participation (see Appendix B). The list was

compiled by gathering 98 contacts from a personal e-mail address book, which consisted

mainly of friends (most of whom were previous work colleagues) and several family

members. Internal e-mail lists of current coworkers at various hierarchical levels from

engineering, marketing, and support groups totaling 181 individuals were then added to

the list. The same recruitment text was sent to 6,141 Northcentral University students and

faculty using the internal messaging system. Note that some text in the e-mail recruitment

content can be attributed to MacPhee (2006).

Procedures

Participants completed an online survey (shown in Appendix C, along with the

informed consent and debriefing pages) hosted on a third-party survey site

(www.surveymonkey.com). Written permission was obtained to use the motivation to

lead and EPQ instruments included in the survey. The questions regarding PO fit are

published in numerous forms in various studies. Therefore, because they are not part of a

named instrument, no permission was sought to reuse them. Secure transmission of

survey results was ensured by using https encryption, and it was not possible to open the

survey using http rather than https. User identifiers were not collected and IP addresses

were not included in collected data. Survey reliability was enhanced by requiring a

password to enter the survey. In addition, internal reliability was tested for all scales.

The informed consent page stated explicitly that participation was being requested

for a research project. An indication of consent was recorded in the form of an answer to

a question on the consent page. This record of consent was logged with a timestamp. The

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informed consent page contained contact information that participants used to ask

questions about the study. The debriefing page also contained contact information that

participants were free to use to ask questions about the study.

The results database was accessible to the researcher only through the use of a

username and password. The survey site publishes a privacy policy stating that they will

not access or disclose research data. Data was backed up once an hour, and then backed

up at a central site once a day. The servers containing the data were located in a locked

cage at a staffed data center with environmental controls. Deleted data was restorable for

up to 14 days.

Data Analysis

The SPSS (Version 15) statistical software package was used for all statistical

calculations. Descriptive statistics were conducted to obtain a demographic profile of the

sample. Means, standard deviations, and reliability estimates were then calculated for the

study variables. Cronbach coefficient alphas were calculated using the raw scores of each

predictor and criterion variable. The resulting reliability estimates gave the internal

consistency for each scale used to measure the study variables.

Before regressions were performed, Pearson correlation was used to verify

relationships for PO fit and each of general, affective-identity, non-calculative, and

social-normative motivation to lead. Correlations were also verified for idealism and each

of general, affective-identity, non-calculative, and social-normative motivation to lead.

Before regression testing, PO fit, relativism, and idealism were mean centered to

reduce multicollinearity. Hierarchical multiple regression was used to identify control

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variables and then to test the prediction of each motivation to lead type from each of PO

fit and idealism.

Hierarchical moderated regression (Aquinis, 2004) was used to test the

moderating role of relativism for the relationship between PO fit and general motivation

to lead, PO fit and affective-identity motivation to lead, PO fit and non-calculative

motivation to lead, and PO fit and social-normative motivation to lead.

Methodological Assumptions, Limitations, and Delimitations

As all measures appeared in one instrument, it was anticipated that common

method bias could be introduced. An individual rating both predictor and criterion

variables may attempt to maintain consistency in similar questions (Podsakoff et al.,

2003). However, the scales used for the predictor and criterion variables had explicitly

different items, and the scales for the predictor and criterion variables differed in size.

The survey guaranteed the participants' anonymity (reducing evaluation apprehension and

social desirability threats) and the criterion constructs were presented before the predictor

constructs, all of which are good remedies for common method bias (Podsakoff et al.).

Online research can incur some limitations, including coverage error (sample does

not reflect target population), sampling error due to self-selection, measurement error due

to misinterpretation or fraudulent responses, and nonresponse error (Bartlett, 2005).

However, a meta-analysis found the quality of data collected online to be equivalent to

data collected via traditional methods, suggesting that online survey research does not

carry as much risk as first thought (Gosling, Vazire, Srivastava, & John, 2004).

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Ethical Assurances

Institutional Review Board (IRB) approval was obtained before data was

collected. Participants were not deceived or misled, and their responses remained

anonymous. Participants were volunteers who were recruited as individuals, and they did

not receive compensation or payment. No institutional sponsorship was pursued.

Social science studies can present risk in the form of social, legal, economic, or

psychological outcomes (Kraut et al., 2004). Ethics principles and federal regulation

prescribe that the chance of harm be no greater than that presented in ordinary life (Kraut

et al.). Online participation in research may be less risky in that there is less social

pressure to complete the survey. However, online experiments can cause unpleasant

feelings or distress. This occurs without the benefit of a researcher present to mitigate

harm. To address this risk, the survey included researcher contact information and

participants were encouraged to contact the researcher.

For online research, debriefing documents can be presented on the research web

site. However, because the researcher is not present, it is difficult to determine if the

debriefing material has met the needs of the participants. Therefore, the debriefing page

contained contact information and participants were encouraged to contact the researcher.

Walther (2002) notes that academic research enjoys a privileged position in

regards to telephone surveys (they are not blocked by “do not call” lists), suggesting

more latitude for academics conducting online research. However, online research may

pose special risks that must be managed. Research data is vulnerable to theft during

transit and when stored on public servers (Smith, 2003). Data collected during this study

did not contain identifying information (with the exception of the IP address, which was

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available in transit and stored by the survey hosting service, but was not included in the

study results) to minimize risk of a breach of confidentiality. Because participants could

have taken the survey while at work, a high level of security was needed to guarantee that

their responses were not viewable by their employer. SSL encryption of responses was

used to accomplish this.

Federal regulation requires written consent by human participants. However,

IRBs can waive this requirement and allow participants to give consent by clicking a

button. Kraut et al. (2004) suggest breaking informed consent into multiple pages or

testing for understanding when the subject is at a greater than normal risk. Mueller,

Jacobsen, and Schwarzer (2000) suggest that informed consent for online experiments

should be as short as possible, as Internet users are not pressured to participate, and they

are, to a very high degree, volunteering to participate. To address this issue, the informed

consent form was placed on a separate page for this survey and kept as short as possible.

The level of data security should match the risk. In this study, sensitive data was

handled by a third party to relieve the researcher of this responsibility.

Summary

This chapter reiterated the hypotheses, and gave descriptions of the research

method and design used for the present study. The sampling method, participant

characteristics, and study procedures were described. The methods used to collect,

process, and analyze the data were then discussed. Finally, assumptions, limitations, and

ethical assurances were given.

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Chapter 4: Findings

Overview

This chapter describes the data collected for this study and the results of analyses

of the data. Demographics, descriptive statistics, reliability test results, and correlations

for all scales and control variables are presented. A confirmatory factor analysis for the

general motivation to lead scale is also included to verify the presence of this second-

order measure.

Results of hierarchical multiple regression analyses used to determine the effect

of the PO fit predictor on each motivation to lead criterion are presented. Results of tests

of the interaction of PO fit and relativism for each motivation to lead criterion are then

given. Finally, test results showing the effect of the idealism predictor on each motivation

to lead criterion are provided.

Data Preparation

All survey responses (including incomplete surveys) were downloaded from the

host website. A separate data collector was used for friends and family versus co-workers

and Northcentral University students and faculty. The resulting data was analyzed using

SPSS (Version 15.0) statistical software. The possibility for out-of-range errors was

minimized through the online data collection method, and an inspection of minimum and

maximum values revealed no out-of-range values. A total of 1,141 responses were

received, 46 of which were friends and family. Of these, 5 did not give consent, 31 were

essentially empty responses (no demographic or scale responses), and 21 gave

demographic responses only. These cases were excluded from the subsequent analyses.

SPSS missing value analysis (MVA) was performed on the remaining 60 incomplete

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responses to determine if the omitted predictor variables were missing at random (MAR)

for criterion variables. If missing cases can be classified as MAR, then listwise deletion is

advised (Allison, 2001). Separate variance t-tests showed PO fit and idealism to be MAR

for all types of motivation to lead. Relativism was MAR for non-calculative and social

normative motivation to lead, and borderline MAR (p = .045) for affective-identity

motivation to lead. Due to these findings, and because Allison also considers listwise

deletion to be robust to regression, these cases were removed from the analysis, giving a

total of 1,024 complete responses. A custom Java program and SPSS were used to

calculate reverse codes, compute scale totals, and create dummy-coded control variables.

Sample Description

Participation was requested from 6,141 students and faculty at a distance-learning

university, 98 friends and family, and 181 work colleagues, giving a total of 6,440

potential research participants. The total number of complete responses collected was

1,024, yielding a response rate of 16%. Of these, 40 were friends and family, and 984

were work colleagues, university students, or faculty.

The participants were mainly older workers, with a median age of 41 to 50 years

old. However, 37% were 40 years of age and younger, and 14% were 32 and under. The

sample was fairly balanced in terms of gender at 47% male and 53% female. The

majority of participants were White (79%), but the sample was also made up of 10%

Black, 4% Hispanic, and 3% Asian participants. The educational level was very high,

with 77% of participants possessing a graduate degree. Not surprisingly given the age of

the participants, the majority (70%) had 16 or more years of work experience. Leadership

experience, job tenure, and organization tenure were more balanced, all with medians of

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6 to 10 years. Organization size was also balanced, with a median of 101 to 500

employees. The job level was high, as a majority of the participants (59%) characterized

themselves as professionals. Of the rest, 34% were first line, middle, or executive

managers, and only 7% were technical or clerical. Most participants worked full time

(92%).

Personal characteristics are shown in Table 4, and job and organization

characteristics are shown in Table 5. Selected characteristics were included in regression

analyses in order to control for their effect. Predictor and criterion means and standard

deviations for all characteristics are shown in Table 9 through Table 19 in Appendix D.

Common Method Variance

As all measures were taken using one survey, Harman’s one-factor test

(Podsakoff et al., 2003) was used to estimate the extent of common method variance. If a

single factor emerges or if one factor accounts for the majority of the covariance in the

predictor and criterion variables, then common method bias may be present. The second-

order general motivation to lead score, relativism, idealism, and PO fit were entered into

an unrotated factor analysis. The analysis gave two factors, with the largest accounting

for less than a majority of covariance at 32%. This suggests that common method bias is

not a concern in this sample.

Nonresponse Bias

Armstrong and Overton (1977) showed that late responders are similar to

nonrespondents. They suggested that comparing early and late responders could give

information as to whether nonrespondents would provide different replies than

respondents. Using their extrapolation technique, the means of early and late responders

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Table 4. Personal Characteristics

Characteristic n %

Age 18 to 23 years 9 .9

24 to 32 years 136 13.3

33 to 40 years 239 23.3

41 to 50 years 359 35.1

51 years and over 281 27.4

Gender Male 485 47.4

Female 539 52.6

Educational level Some high school 0 0

Completed high school 2 .2

Some college 37 3.6

Completed college 42 4.1

Some graduate school 154 15.0

Graduate degree 789 77.1

Work experience Less than 1 year 2 .2

1 to 5 years 55 5.4

6 to 10 years 95 9.3

11 to 15 years 157 15.3

16 years or more 715 69.8

Leadership experience Less than 1 year 88 8.6

1 to 5 years 247 24.1

6 to 10 years 218 21.3

11 to 15 years 164 16.0


Ethnicity White non-Hispanic 811 79.2

Asian or Pacific Islander 26 2.5

Hispanic 37 3.6

Black non-Hispanic 103 10.1

Other 47 4.6

Note. N = 1024.

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were compared using one-way ANOVA on gender, ethnicity, educational level, work

experience, leadership experience, job level, general motivation to lead, idealism,

relativism, and PO fit. No significant differences (p > .05) were found between the two

groups.

Table 5. Job and Organization Characteristics

Characteristic n %

Job tenure Less than 1 year 50 4.9

1 to 5 years 343 33.5

6 to 10 years 274 26.8

11 to 15 years 144 14.1


Job level Clerical 22 2.1

Technical 52 5.1

Professional 599 58.5

First line manager 53 5.2

Middle manager 160 15.6

Executive 138 13.5

Employment status Part-time 81 7.9

Full-time 943 92.1

Organization size 1 to 50 employees 205 20.1

51 to 100 employees 122 11.9

101 to 500 employees 253 24.7

501 to 1000 employees 110 10.7

1001 employees or more 334 32.6

Organization tenure Less than 1 year 112 10.9

1 to 5 years 342 33.4

6 to 10 years 236 23.0

11 to 15 years 105 10.3


Note. N = 1024.

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Descriptive Statistics

Scale means, standard deviations, correlations, and reliabilities for study variables

are shown in Table 6. Means for the predictor variables PO fit, idealism, and relativism

were consistent with previous studies. The participants reported high levels of PO fit, i.e.,

they perceived that their values were aligned with their organization and coworkers. They

were more relative than idealistic, indicating that they take situation into account and are

pragmatic when making ethical decisions. The motivation to lead criteria means were

slightly higher than those found for Chan and Drasgow’s (2001) U.S. sample of students

(N = 290), which may reflect the relatively high job level and amount of leadership

experience for the sample used in the present study. The means found by Chan and

Drasgow for general, affective-identity, non-calculative, and social-normative motivation

to lead respectively were M = 32.08, SD = 5.99; M = 31.24, SD = 7.39; M = 34.22, SD =

5.59; and M = 30.79, SD = 4.99.

Table 6. Coefficient Alphas, Correlations, Means, and Standard Deviations for Study Variables

Study Variable 1 2 3 4 5 6 7 M SD

1. PO Fit .91 .03 -.07* .13** .15** .15** .19** 14.79 4.81

2. Idealism .89 .01 -.12** -.14** -.07* -.15** 26.16 7.04

3. Relativism .84 -.07* .06* .10** .08 34.99 7.40

4. Affective-identity MTL .85 .26** .37** .76** 32.89 6.05

5. Non-calculative MTL .85 .31** .71** 35.01 5.72

6. Social-normative MTL .81 .73** 32.05 4.99

7. General MTL .88 33.32 4.11

Note. N = 1024. MTL = motivation to lead; Coefficient alphas are presented in boldface along the diagonal. *p < .05 (two-tailed). **p < .01 (two-tailed).

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Tests of Statistical Assumptions

All predictor and criterion correlations required for linear regression analysis were

present. As expected, lower levels of PO fit were statistically significantly related to

lower levels of each motivation to lead type. Also, as expected, higher levels of idealism

were statistically significantly related to lower levels of each motivation to lead type.

Idealism and relativism were found to be orthogonal, as expected given previous

findings (Davis et al., 2001; Forsyth, 1980). Although Forsyth et al. (2008) suggest that

predictions from either of these dimensions should consider the other, this study is

concerned with contributions of distinct aspects of each to motivation to lead, and

therefore, their discriminant validity was relevant. However, given Forsyth’s suggestion,

and although not formally hypothesized, each dimension was tested as a moderator of the

other for each hypothesized relationship to motivation to lead (tests of a three-way

interaction for PO fit, relativism, and idealism; and a two-way interaction for idealism

and relativism). These tests did not change the statistical significance level of any results

for tests not including the additional moderator.

The hierarchical multiple regression and moderated multiple regression tests used

to evaluate study hypotheses, and the t-tests used to compare residuals, require that

certain statistical assumptions be met. Univariate linear relationships between each

predictor and criterion are assumed (Cohen & Cohen, 1983). These relationships were

tested by examining scatter plots and correlations. All relationships appeared to be linear.

PO fit had a significant positive relationship with each motivation to lead criterion, and

idealism had a significant negative relationship with each motivation to lead criterion.

Therefore, the linearity assumption appeared to have been met.

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The relativism moderator had a significant positive relationship with the non-

calculative and social-normative motivation to lead criteria, and a significant negative

relationship with the PO fit predictor and the affective-identity motivation to lead

criterion. Although it had been thought that a moderator and predictor should not be

related (Baron & Kenny, 1986), it was later found that this concern was unfounded

(Aguinis, 2004). Kenny (2004) also later stated that correlation between predictor and

moderator has no special interpretation.

Univariate normality for all predictor and criterion variables was examined using

histograms and normal probability plots (see Figure 4 through Figure 17 of Appendix D).

All skewness and kurtosis values were between -1 and 1. Because skewness for PO fit

approached -1 at -.95, a square root transformation was performed. However, although

there was some improvement in skewness, using the transformed variable did not change

the overall significance or direction of the effects for regression. Therefore, the

transformed variable was not used.

Examination of plots for residual versus predicted values, and histograms and

normal probability plots of the regression standardized residuals indicated that the

homoscedasticity (homogeneity of residual variance) assumption was not violated and

that the residuals were normally distributed.

Examination of the Durbin-Watson statistic for each regression performed

showed that the independence of residuals assumption was not violated. All statistics

were within the acceptable range of 1.50 to 2.50.

The homogeneity of error variance assumption, which requires that the

distribution of residuals remain constant across moderator groups, must be met for

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moderated multiple regression using categorical moderators. Although the regressions in

the present study use continuous moderators, subgroups were created using a median split

to test this assumption with Aguinis’ (2008) ALTMMR tool. No violations of this

assumption were detected.

Multicollinearity between predictors and controls was checked by examining the

variance tolerance statistics for each regression coefficient. All predictors and controls,

with the exception of the professional job level (with a variance tolerance of .07), had a

variance tolerance larger then .10, indicating most predictors and controls were not highly

correlated (de Vaus, 2002).

Hypothesis Testing Procedure

All hypotheses were tested using hierarchical multiple regression or moderated

multiple regression. Predictors were mean centered before being entered. Backward

elimination was used to exclude redundant control variables for each regression equation.

The set of dummy-coded variables for each control variable was entered in a separate

step. When the R2 change value was significant (p < .05) for a step and the set had at least

one statistically significant regression coefficient (also at p < .05) in the final step, the set

of dummy-coded control variables was used in the next version of the regression (Hardy,

1993). This procedure was repeated until only dummy-coded control variable sets that

contributed significantly to the model were retained. Note that for each regression, the

backward elimination procedure was performed exactly twice. Also note that the some

high school educational level group was empty and was not included in this analysis.

After control variables were selected for each regression, new baseline

regressions were performed. Control variables were entered first to observe the predictor

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or interaction effect after accounting for differences attributable to the control variables.

Each set of selected dummy-coded control variables was entered in a separate step. For

each hierarchical multiple regression the predictor variable was then entered in the final

step. For each moderated multiple regression the predictor variables were entered in the

next step, and the interaction term was entered in the final step.

The baseline regressions included all outliers. Outliers were then removed by

deleting cases with standardized residuals with absolute values greater than three.

Revised regressions were then performed. None of the revised regressions differed in

direction or significance level from the baseline, and the R2 values did not vary from the

baseline by more than 2%. Therefore, the results of the baseline models were used to

evaluate all hypotheses.

Effect size was calculated for each regression, and confidence intervals are given

in all regression tables (Soper, 2007b; Soper, 2008). Reported effect size magnitude is

characterized here as small at .01, medium at .09, and large at .25 (Cohen, 1988, pp. 75-

107). A posteriori power analysis was not performed, as power analysis is considered

appropriate for study design rather than data analysis (Hoenig & Heisey, 2001; Lenth,

2001; Zumbo & Hubley, 1998).

This study had a finite number of a priori inferences, which reduces concerns for

Type I errors (Hochberg & Tamhane, 1987). However, given that multiple comparisons

may have inflated Type I error, two methods were used as controls during hypothesis

testing. First, the experimentwise Type I error rate was controlled for multiple

comparisons by using a Bonferroni adjusted statistical significance level. Families were

defined by grouping hypotheses which were similar in content and use (Hochberg &

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Tarhane). Each question (the relationship of PO fit and motivation to lead; the

relationship of PO fit, relativism, and motivation to lead; and the relationship of idealism

and motivation to lead) was considered an experimental family using this guideline,

giving a Bonferroni adjusted alpha level of .0167 (.05/3).

Second, Benjamini and Hochberg’s (1995) false discovery rate (FDR) method,

which is considered liberal but suitable for a priori inference testing (Anderson,

Burnham, & Thompson, 2000), was used. This method controls the proportion of errors

among rejected null hypotheses. This preserves power by controlling the most relevant

errors. The significance level cutpoint found using this method was p <= .012, meaning

any null hypothesis with a statistical significance greater than .012 was accepted. The

experimentwise Bonferroni method and the FDR method produced the same set of

accepted null hypotheses. For familywise Type I error, all significance tests used this

same level by way of the Fisher method. Each test of significance for the R2 change of

each step is considered an omnibus test for significance that protects the tests for

coeffiecients within it. This is the suggested method for control of Type I error rates for

multiple regression due to multiple comparison given by Cohen and Cohen (1983, pp.

172-176) and is offered as a way to control Type I error rate without losing a great deal of

power by inflating the Type II error rate.

Hypothesis Testing

Hypothesis testing for PO fit and motivation to lead.

The present study questioned the extent to which lower PO fit predicts lower

general, affective-identity, non-calculative, and social-normative motivation to lead. It

was hypothesized that lower PO fit would predict lower levels of each motivation to lead

106

type, over and above personal, job, and organization characteristics. A competing

hypothesis that PO fit would not relate to affective-identity motivation to lead was also

included. Details of the regression analyses used to test these hypotheses can be found in

Table 20 through Table 23 in Appendix D.

Hierarchical multiple regression analysis was conducted to predict general

motivation to lead from PO fit, over and above the control variables leadership

experience and job level. PO fit demonstrated a significant effect on general motivation

to lead, β = .15, t[1013] = 4.96, p < .001, ƒ2 = .02. The results of the analysis indicated

that PO fit accounted for a small but significant proportion of general motivation to lead

variance after controlling for characteristics, R2 change = .02, F(1, 1013) = 24.60, p <

.001. In other words, employees with similar characteristics who are lower in PO fit are

more likely to be lower in general motivation to lead, making individuals with low PO fit

less likely to assume leadership roles. Hypothesis 1 was supported.

As PO fit was found to be related to affective-identity motivation to lead,

hypothesis 2a was not supported. A hierarchical multiple regression analysis was

conducted to predict affective-identity motivation to lead from PO fit, over and above the

control variables leadership experience and job level. PO fit demonstrated a significant

effect on affective-identity motivation to lead, β = .08, t[1013] = 2.52, p = .007, ƒ2 = .01.

The results of the analysis indicated that PO fit accounted for a small but significant

proportion of affective-identity motivation to lead variance after controlling for

characteristics, R2 change = .01, F(1, 1013) = 7.34, p = .007. In other words, employees

with similar characteristics who are lower in PO fit are more likely to be lower in

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affective-identity motivation to lead, making individuals with low PO fit less likely to

view themselves as having leadership ability. Hypothesis 2b was supported.

A hierarchical multiple regression analysis was conducted to predict non-

calculative motivation to lead from PO fit, over and above the control variables gender,

leadership experience, ethnicity, and job level. PO fit demonstrated a significant effect on

non-calculative motivation to lead, β = .12, t[1008] = 3.93, p < .001, ƒ2 = .02. The results

of the analysis indicated that PO fit accounted for a small but significant proportion of

non-calculative motivation to lead variance after controlling for characteristics, R2 change

= .01, F(1, 1008) = 15.41, p < .001. In other words, employees with similar

characteristics who are lower in PO fit are more likely to be lower in non-calculative

motivation to lead, making individuals with low PO fit more likely to calculate the costs

of leadership when deciding to take a leadership role. Hypothesis 3 was supported.

A hierarchical multiple regression analysis was conducted to predict social-

normative motivation to lead from PO fit, over and above the control variable gender. PO

fit demonstrated a significant effect on social-normative motivation to lead, β = .15,

t[1021] = 4.81, p < .001, ƒ2 = .02. The results of the analysis indicated that PO fit

accounted for a small but significant proportion of social-normative motivation to lead

variance after controlling for characteristics, R2 change = .02, F(1, 1021) = 23.14, p <

.001. In other words, employees with similar characteristics who are lower in PO fit are

more likely to be lower in social-normative motivation to lead, making individuals with

low PO fit less likely to lead due to a sense of obligation to the group. Hypothesis 4 was

supported.

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Hypothesis testing for PO fit, relativism, and motivation to lead.

The present study questioned the extent to which lower PO fit predicts lower

general, affective-identity, non-calculative, and social-normative motivation to lead when

PO fit is moderated by relativism. It was hypothesized that lower PO fit would predict

lower levels of each motivation to lead type, over and above personal, job, and

organization characteristics, but only when relativism was low. That is, individuals who

believe in universal moral rules would be more likely to be influenced by lower PO fit.

Further, it was hypothesized that relativists would not be influenced by lower PO fit at

all. Details of the regression analyses used to test these hypotheses can be found in Table

24 through Table 27 in Appendix D.

A moderated multiple regression analysis was conducted to predict general

motivation to lead from the interaction of PO fit and relativism, over and above the

control variables leadership experience and job level. The interaction of PO fit and

relativism did not demonstrate a significant effect on general motivation to lead, β = .04,

t[1011] = 1.37, p = .17, ƒ2 = .14. The results of the analysis indicated that the interaction

of PO fit and relativism did not account for a significant proportion of general motivation

to lead variance after controlling for characteristics, R2 change = .002, F(1, 1011) = 1.81,

p = .17. The slopes for both high (+1 SD, β = .15, p < .001) and low (-1 SD, β = .09, p =

.005) relativism groups were significant and positive, but the interaction was not

statistically significant. In other words, employees with similar characteristics who are

lower in PO fit are more likely to be lower in general motivation to lead, whether or not

they believe in a universal moral code. Hypothesis 5 was not supported.

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A moderated multiple regression analysis was conducted to predict affective-

identity motivation to lead from the interaction of PO fit and relativism, over and above

the control variables leadership experience and job level. The interaction of PO fit and

relativism did not demonstrate a significant effect on affective-identity motivation to

lead, β = .06, t[1011] = 1.95, p = .05, ƒ2 = .12. The results of the analysis indicated that

the interaction of PO fit and relativism did not account for a significant proportion of

affective-identity motivation to lead variance after controlling for characteristics, R2

change = .003, F(1, 1011) = 3.80, p = .05. The slope for the high relativism group was

significant and positive (+1 SD, β = .17, p < .001), the slope for the low relativism group

was not significant (-1 SD, β = .03, p = .259), and the interaction was not statistically

significant. In other words, employees with similar characteristics who are lower in PO

fit are more likely to be lower in affective-identity motivation to lead, whether or not they

believe in a universal moral code. Hypothesis 6 was not supported.

A moderated multiple regression analysis was conducted to predict non-

calculative motivation to lead from the interaction of PO fit and relativism, over and

above the control variables gender, leadership experience, ethnicity, and job level. The

interaction of PO fit and relativism did not demonstrate a significant effect on non-

calculative motivation to lead, β = .002, t[1006] = .539, p = .59, ƒ2 = .09. The results of

the analysis indicated that the interaction of PO fit and relativism did not account for a

significant proportion of non-calculative motivation to lead variance after controlling for

characteristics, R2 change < .001, F(1, 1006) = .29, p = .59. The slopes for both high (+1

SD, β = .16, p < .001) and low (-1 SD, β = .12, p = .015) relativism groups were

significant and positive, but the interaction was not statistically significant. In other

110

words, employees with similar characteristics who are lower in PO fit are more likely to

be lower in non-calculative motivation to lead, whether or not they believe in a universal

moral code. Hypothesis 7 was not supported.

A moderated multiple regression analysis was conducted to predict social-

normative motivation to lead from the interaction of PO fit and relativism, over and

above the control variable gender. The interaction of PO fit and relativism did not

demonstrate a significant effect on social-normative motivation to lead, β = .01, t[1019] =

.436, p = .66, ƒ2 = .06. The results of the analysis indicated that the interaction of PO fit

and relativism did not account for a significant proportion of social-normative motivation

to lead variance after controlling for characteristics, R2 change < .001, F(1, 1019) = .19, p

= .66. The slopes for both high (+1 SD, β = .16, p < .001) and low (-1 SD, β =.13, p =

.002) relativism groups were significant and positive, but the interaction was not

statistically significant. In other words, employees with similar characteristics who are

lower in PO fit are more likely to be lower in social-normative motivation to lead,

whether or not they believe in a universal moral code. Hypothesis 8 was not supported.

Hypothesis testing for idealism and motivation to lead.

The present study questioned the extent to which higher idealism predicts lower

general, affective-identity, non-calculative, and social-normative motivation to lead. It

was hypothesized that higher idealism would predict lower levels of each motivation to

lead type, over and above personal, job, and organization characteristics. A competing

hypothesis that idealism would not relate to affective-identity motivation to lead was also

included. Details of the regression analyses used to test these hypotheses can be found in

Table 28 through Table 31 in Appendix D.

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A hierarchical multiple regression analysis was conducted to predict general

motivation to lead from idealism, over and above the control variables leadership

experience and job level. Idealism demonstrated a significant effect on general

motivation to lead, β = -.13, t[1013] = - 4.26, p < .001, ƒ2 = .02. The results of the

analysis indicated that idealism accounted for a small but significant proportion of

general motivation to lead variance after controlling for characteristics, R2 change = .02,

F(1, 1013) = 18.12, p < .001. In other words, employees with similar characteristics who

are idealistic are more likely to be lower in general motivation to lead, making idealists

less likely to assume leadership roles. Hypothesis 9 was supported.

As idealism was found to be related to affective-identity motivation to lead,

hypothesis 10a was not supported. A hierarchical multiple regression analysis was

conducted to predict affective-identity motivation to lead from idealism, over and above

the control variables leadership experience and job level. Idealism demonstrated a

significant effect on affective-identity motivation to lead, β = -.09, t[1013] = -2.86, p =

.004, ƒ2 = .01. The results of the analysis indicated that idealism accounted for a small but

significant proportion of affective-identity motivation to lead variance after controlling

for characteristics, R2 change = .01, F(1, 1013) = 8.16, p = .004. In other words,

employees with similar characteristics who are idealistic are more likely to be lower in

affective-identity motivation to lead, making idealists less likely to view themselves as

having leadership ability. Hypothesis 10b was supported.

A hierarchical multiple regression analysis was conducted to predict non-

calculative motivation to lead from idealism, over and above the control variables gender,

leadership experience, ethnicity, and job level. Idealism demonstrated a significant effect

112

on non-calculative motivation to lead, β = -12, t[1008] = -3.93, p < .001, ƒ2 = .02. The

results of the analysis indicated that idealism accounted for a small but significant

proportion of non-calculative motivation to lead variance after controlling for

characteristics, R2 change = .01, F(1, 1008) = 15.45, p < .001. In other words, employees

with similar characteristics who are idealistic are more likely to be lower in non-

calculative motivation to lead, making idealists more likely to calculate the costs of

leadership when deciding to take a leadership role. Hypothesis 11 was supported.

A hierarchical multiple regression analysis was conducted to predict social-

normative motivation to lead from idealism, over and above the control variable gender.

Idealism did not demonstrate a significant effect on social-normative motivation to lead,

β = -.07, t[1021] = -2.21, p = .027, ƒ2 = .01. The results indicated that idealism did not

account for a significant proportion of social-normative motivation to lead variance after

controlling for characteristics, R2 change = .01, F(1, 1021) = 4.89, p = .027. In other

words, employees with similar characteristics who are idealistic are not more likely to be

lower in social-normative motivation to lead. Although hypothesis 12 was not supported,

it should be noted that if a non-adjusted significance level (p = .05) were used, hypothesis

12 would be supported. This suggests that weak or tentative support for this hypothesis

could be considered.

Summary of Findings

The study results are depicted in Figure 3. Support was found for all hypothesized

predictions of lower motivation to lead from lower PO fit, over and above personal, job,

and organization characteristics. No support was found for any of the hypotheses

proposing that the interaction of PO fit and relativism would predict motivation to lead.

113

-

- - -

+ +

+ +

General Motivation to Lead

Affective - Identity Motivation to Lead

Non-Calculative Motivation to Lead

Social - Normative Motivation to Lead


Idealism

Figure 3. Revised model: Person-organization fit predicting motivation to lead, and idealism predicting motivation to lead.

Support was found for hypothesized predictions of lower general, affective-

identity, and non-calculative motivation to lead from higher idealism. Although not

statistically significant under the Bonferroni adjusted alpha level (.0167), prediction of

social-normative motivation to lead from idealism was significant, at p = .027, under the

non-adjusted alpha level (p = .05). Given this borderline statistical significance,

hypothesis 12 concerning the relationship between higher idealism and lower social-

normative motivation to lead will be considered to have received limited support, and this

support will be interpreted with caution when discussed.

114

Supplemental Analysis

Although examining relationships between characteristics and study variables was

not a goal for this study, it has been suggested that PO fit research has neglected group

differences (Arthur et al., 2006), and that moral philosophy research could also benefit

from a better understanding of group differences (Forsyth et al., 2008). Further,

motivation to lead is a new construct that would benefit from additional findings

regarding group differences. Therefore, supplemental analysis was preformed to explore

differences based on personal, job, and organization characteristics.

Spearman rank order correlation tests found several relationships of note (see

Table 7 for details). Older workers with more education, work experience, and

organization tenure were less idealistic, and therefore more pragmatic. Individuals at

higher job levels, and with more leadership experience at larger organizations, were

found to have a stronger belief in universal moral codes, and would therefore be less

likely to consider context when making ethical decisions.

Individuals with more education and leadership experience, and a higher position

in the organization, were more likely to perceive that the values of the organization fit

their own. However, the perception of PO fit decreased for employees of larger

organizations.

More educated individuals viewed themselves as leaders and were more likely to

enjoy leading. Further, older participants, with more experience and time with the

organization, were less likely to calculate the costs of leadership when deciding to take a

leadership role.

115

Point biserial correlation tests found several significant relationships with study

variables for gender and employment status (details appear in Table 7). In general,

women were less motivated to lead, but they were also less likely to calculate the costs of

leading. Women did not see themselves as leaders, and they were less likely to lead due

to a sense of duty. Women were also more likely to consider situation when making

ethical decisions. Part timers were significantly more idealistic, and less motivated to

lead.

Relationships were explored among study variables and ethnicity using one-way

ANOVA (details are shown in Table 8). Significant differences were revealed across

ethnic groups on idealism, relativism, and non-calculative motivation to lead. Post-hoc

Table 7. Correlations of Characteristics and Study Variables

Characteristic PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Age .02 -.18** -.01 .06 .14** .06 .08*

Educational level .09** -.08** -.01 .08** .03 .03 .06

Work experience .04 -.15** -.06 .05 .11** .03 .11**

Leadership experience .14** -.13** -.15** .25** .15** .15** .26**

Job tenure .05 -.06 .03 .01 .04 .05 .05

Job level .13** -.04 - .11** .23** .10** .17** .23**

Organization tenure .07* .09** -.02 .01 .07* .04 .08**

Organization size -.09** -.01 -.09** .03 .01 .02 .04

Gender (0 = female) .01 -.02 -.23** .11** -.10** .14** .07*

Employment status (0 = part-time)

< .001 -.08** -.01 .08* .04 .06 .08*

Note. N = 1024. AIMTL = affective-identity motivation to lead; NCMTL = non-calculative motivation to lead; SNMTL = social-normative motivation to lead; GMTL = general motivation to lead. *p < .05 (two-tailed). **p < .01 (two-tailed).

116

Tukey’s HSD tests were used to compare the five ethnic groups on each of these

variables at a significance level of .05. The Asian group was more likely to calculate the

costs of leading than the White group, the Black group, and the Other group. The Asian

group was also more idealistic and less pragmatic than the White group and the Other

group. However, the White group was more likely to believe in universal moral codes

than the Hispanic group and the Black group. Further, the Other group was more likely to

depend on universal moral codes than the Hispanic group.

Table 8. One-Way Analyses of Variance for Ethnicity on Study Variables

Study Variable SS MS F (4, 1019)

PO fit Between groups 31.17 7.79 .34

Within groups 23,615.57 23.18

Idealism Between groups 669.89 167.47 3.41**


Relativism Between groups 2052.48 513.12 9.70***


AIMTL Between groups 53.08 13.27 .36


NCMTL Between groups 552.50 138.13 4.28**


SNMTL Between groups 145.72 36.43 1.47


GMTL Between groups 68.30 17.07 1.01


Note. N = 1024. AIMTL = affective-identity motivation to lead; NCMTL = non-calculative motivation to lead; SNMTL = social-normative motivation to lead; GM = general motivation to lead. ** p < .01. ***p < .001.

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Chapter 5: Discussion

The primary goal of the present study was to explore the relationships between

person-organization fit, moral philosophy, and motivation to lead by focusing on these

questions.

1. To what extent does PO fit predict general, affective-identity, non-calculative,

and social-normative motivation to lead among employed individuals, over

and above personal, job, and organization characteristics?

2. To what extent does relativism moderate PO fit’s prediction of general,

affective-identity, non-calculative, and social-normative motivation to lead

among employed individuals, over and above personal, job, and organization

characteristics?

3. To what extent does idealism predict general, affective-identity, non-

calculative, and social-normative motivation to lead among employed

individuals, over and above personal, job, and organization characteristics?

The study results showed that lower PO fit consistently predicted lower general

motivation to lead, and lower levels for all three dimensions of motivation to lead.

However, contrary to hypotheses, none of these relationships was moderated by

relativism. Higher idealism was found to predict lower general, affective-identity, and

non-calculative motivation to lead. However, the results for social-normative motivation

to lead were not definitive. Although idealism was significantly negatively correlated

with social-normative motivation to lead, the regression model was not significant under

the Bonferroni adjusted alpha level of .0167. However, the regression model was

significant using a non-adjusted alpha level of .05. This chapter presents conclusions

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drawn from these results, practical implications, study limitations, and recommendations

for future research.

Conclusions for PO Fit and Motivation to Lead

This study showed that individuals who do not share the values of their

organization are less attracted to leading and less likely to see themselves as having

leadership qualities. van Vianen and Stoelhorst (2007) suggest that, based on behavioral

ecology theory, individuals prefer to emulate similar successful others. As employees

with low PO fit do not share the values of their leadership, they are less likely to emulate

them, and would therefore have less interest in leading. The findings of the present study

support this scenario and demonstrate that the self-selection away from promotions

suggested by Nicholson (2005) is occurring. Further, as leaders are known to promote

individuals to whom they are similar (Giberson et al., 2005), employees with low PO fit

may also be excluded from leadership opportunities. In essence, those with low PO fit do

not have the opportunity to gain the leadership experience and leadership self-efficacy

that promotes motivation to lead.

The results indicated that low PO fit individuals calculate and consider the costs

of leadership. This is most likely due to the high salience of costs for those who differ in

values, as reported by Whetstone (2001) and Papavero (1999). In particular, Billsberry et

al.’s (2005) finding that work-life balance was important to lower-level employees, but

not to those at higher levels, is telling given the results of the present study. Valuing

work-life balance when the organization does not may indicate a serious cost of leading

that decreases non-calculative motivation to lead, populating management with those

who are less likely to value it. The present study also showed that those who do not share

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values are less motivated to lead due to feelings of obligation and duty to the group. This

supports previous findings that PO fit encourages prosocial behaviors (Posner, 1992) and

organizational citizenship behaviors (O’Reilly & Chatman, 1986). In addition,

individuals who do not feel a duty to lead are less accepting of social hierarchies,

preferring social equality (Chan, 1999). This may explain their reluctance to advance in

the organizational hierarchy when low PO fit is due to a mismatch in values regarding

social dominance type. An individual who prefers social hierarchy might be hesitant to

lead in a hierarchy attenuating organization, and someone who believes in social

egalitarianism may avoid leadership in an organization that is hierarchy enhancing (Haley

& Sidanius, 2005).

Most importantly, this study introduced an outcome for PO fit that has never been

considered before, with the potential to impact both the individual and the organization.

In addition, these findings support results from a past qualitative study that indicated

values incongruence as a cause for promotion rejection (Papavero, 1999). This study also

adds to the literature on PO fit and incumbents, which is limited (Billsberry, 2004). For

example, the fact that lower PO fit predicts lower motivation to lead provides an

explanation for Bretz and Judge’s (1992) findings that lower PO fit leads to lower levels

of success.

The findings of this study indicated that, for incumbents, low PO fit leads to

outcomes other than attrition, which, by extension, gives a new dimension to attraction-

selection-attrition theory. That is, a new mechanism of homogenization was identified by

which homogenization at higher levels becomes concentrated. This mechanism may have

an inordinate impact on the organization, as it mostly affects higher levels by limiting the

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leadership pool. This also provides an explanation for Bretz et al.’s (1989) contention that

values are more homogenous at higher levels.

This study provided early evidence that situation influences motivation to lead.

The finding that PO fit predicts motivation to lead also provides evidence of a

phenomenon that fits the integrated model of motivation and commitment proposed by

Meyer, Becker, and Vandenberghe (2007). When PO fit is low, low commitment results,

leading to a prevention focus (the fulfillment of obligations rather than working to

advance ideals), and a reliance on external goal regulation. A less difficult goal is then

chosen (i.e., a non-leadership role) and less effort and persistence are exerted towards that

goal. Non-discretionary behavior, rather than discretionary behavior, is then exhibited in

the non-leadership role. Finally, non-discretionary behavior leads to lowered outcome

expectancy and satisfaction, which then leads to lowered self-efficacy. This further

reinforces a prevention focus and external goal regulation. This reveals the process by

which situation influences the outcomes that preclude leadership experiences, resulting in

lower motivation to lead. This model also provides direction for temporal PO fit research,

as goal regulation is expected to change in response to external and internal conditions.

Conclusions for PO Fit, Relativism, and Motivation to Lead

This study predicted an interaction form where those low in relativism, who

believe in universal moral rules, would experience lower motivation to lead when PO fit

is lower, and the motivation to lead of those high in relativism would not be affected by

lower PO fit. However, no interactions were found and none of these hypotheses were

supported. Although ethical conflict could result from a mismatch in values, either

conflict was not present, or relativism did not impact the reaction to this conflict in such a

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way that motivation to lead was affected. It is possible that low PO fit is not equivalent,

or even similar to, ethical conflict, or that low PO fit does not necessarily imply ethical

conflict.

Even for the low relativist (i.e., universalist), external forces, such as the need for

job security, may create a coping mechanism that allows moral rules to be overridden.

Strength of conviction regarding moral codes may vary with economic opportunity or

individual characteristics such as self-efficacy and self-confidence. That is, the severity

of consequences may affect the salience of personal moral values (Forsyth, 1992). Just as

commitment can be forced due to fear or obligation (Ashman & Winstanley, 2006),

motivation to advance to increased rewards while in a state of low PO fit may be subject

to forces more salient than moral philosophy.

Forsyth (1992) points out that moral philosophies influence action only when they

are accessible. Certain personal values may be unclear to the individual and have varying

priorities. Social pressures may also cause organizational values to be internalized by the

individual, and this may make low PO fit less salient (Edwards & Shipp, 2007) and cause

low relativism to become irrelevant. It is also possible that organizational moral codes are

generally unclear, in which case belief in the possibility (or impossibility) of universal

moral codes is irrelevant, as the moral codes of the context are subject to individual

interpretation and rationalization.

Conclusions for Idealism and Motivation to Lead

This may be the first empirical study to consider idealism in relation to motivation

to lead. The finding that idealists are less motivated to lead adds a new individual

difference to the current motivation to lead model. It also introduces a new outcome for

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idealism. Although uncovering explanations for this finding was not a goal of this study,

several clues are suggested by the literature. The idealist focuses on costs and negative

consequences for others (Forsyth, 1992), and this is probably key to their low motivation

to lead. To limit their exposure to decision making that might bring negative

consequences for others, idealists may avoid leadership roles. Idealists are also more

committed to their professions (Shafer et al., 2002a) and they may see abandonment of

profession as a cost and loss of investment. If an idealist is dedicated to the principles of

their profession, this may also reduce attraction to a new leadership role where

professional ethics and goals could be challenged. Idealists are conscientious, and

conscientiousness is an antecedent of affective-identity and social-normative motivation

to lead (Chan, 1999). However, Forsyth (1992) suggests that idealists may be very hard

on themselves regarding failure, which may affect their estimation of their own

leadership self-efficacy, thus lowering motivation to lead.

Idealists are intrinsically motivated (Bierly et al., in press). As such, they would

prefer self-regulation and self-management, described by Pinder (2008) as monitoring

and evaluation of a person’s own behavior, and self-administration of rewards and

sanctions. This conclusion is in line with Greguras and Diefendorff’s (in press) finding

that autonomy mediated the relationship between PO fit and affective organizational

commitment, i.e., autonomy need satisfaction directly predicted commitment. Individuals

who rejected promotions have been found to consider themselves to be intrinsically

motivated (Papavero, 1999). Further, these individuals found the requirement to manage

others who are externally motivated to be a barrier to advancement. This excerpt

describes their strong feelings on the subject.

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Another engineer explained that, when managing a group of talented and motivated people, a manager does not have to rely on wielding power in the form of salary reviews in order to produce good work. The engineers prefer working with people who do good work because they want to, not because they are being forced to. This was a common theme for all of the engineers. They are not interested in persuading or manipulating people: "I tend to prefer to have people do what they want to do because they want to do it rather than because you're telling them." (Papavero, p. 57)

The idealist’s preference for self-regulation and self-management gives an additional

explanation for their low motivation to lead.

Given the weak support for lower idealism predicting lower social-normative

motivation to lead, it appears that idealists do feel an obligation to lead. As

conscientiousness is both an antecedent of social-normative motivation to lead (Chan,

1999) and an attribute of the idealist (Forsyth, 1992), there may be a greater sense of duty

regarding leading. Further, this finding could be due to the idealist’s concern for

obedience (Forsyth), which might dull the need for negative consequence avoidance and

create higher salience for organizational norms. Idealists face a choice between being

obedient and conforming to organizational norms by taking a leadership role (and

perhaps hoping that these norms can be changed), or rejecting leadership roles due to

conflicts with personal ideals. The less conclusive results for social-normative motivation

to lead may reflect the tension produced by these choices.

Practical Implications

Meyer et al. (2004) proposed that goal choice, self-efficacy, and goal mechanisms

from motivation theory, and forms, foci, and bases of commitment from commitment

theory could be integrated to better account for situation. One suggestion by Meyer et al.

is that in times of economic uncertainty, the motivation provided by commitment can still

be harnessed by changing the foci of commitment to targets with goals compatible with

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the organization (e.g., a focus on profession rather than organization). Likewise,

motivation to lead might be increased during times of low PO fit by changing the foci to

informal leadership roles that decrease the need for identification with management and

the organization, but continue to support goals compatible with the organization.

The advancement processes and reward structures of organizations should be

examined to determine if they are properly aligned in support of organizational goals

(Schein, 2004). If the organization desires diversity, the advancement process and reward

structure should support this goal (Nicholson, 2005). Individuals who do not value

dominance may experience low motivation to lead when placed in situations where only

dominance is valued and rewarded (Nicholson). Further, the organizational design itself

could reflect values of competition and political game playing that may not be attractive

to individuals who possess valuable knowledge and leadership ability (Nicholson;

Papavero, 1999). These individuals may be women, individuals in ethnic groups

underrepresented in current leadership, or members of any group with conflicting values.

Regarding the impact of organizational designs on advancement decisions, Nicholson

states that these:

discriminate both directly and indirectly against the accession of women to leadership positions, not least because of the self-selection of women away from them, on the grounds that such positions are unattractive and their demands are felt to be a poor fit with their style. (p. 406)

The exclusion of idealists from leadership could also have a detrimental effect.

Although not known for their pragmatism, they are known for their creativity (Bierly et

al., in press), and their strategic input would balance and inform decisions. Idealists,

perhaps with roles as thought leaders, have the potential to inspire their colleagues to

broaden their horizons. The inclusion of idealists could help leadership seek alternatives

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that produce more benefit for employees, the community, and the environment, while still

meeting organizational goals. Intrinsically motivated idealists might receive special

benefit from programs that offer more autonomy, such as opportunities for self-

management.

Complementary fit is already exploited by organizations that recruit executives

externally to instigate change. Another demonstration of this principle is the terminology

used in the media regarding the cabinet of president-elect Obama, which is being called a

team of rivals (borrowing from Lincoln’s theory of team formation [Goodwin, 2005])

that will promote robust debates. The same process could be exercised with internal

applicants by assessing the complementary PO fit of incumbents during promotion

planning.

Low PO fit can be used as a gap-analysis tool at the organizational level to

diagnose misalignments between espoused and operational values. Just as individual

moral incongruence can spur self-development (Rodriguez, 2005) misalignment at the

organizational level can be used to integrate diverse values to transform the organization.

Specifically, points of low PO fit can be identified at the group or individual level, and

information gathered about the nature of this phenomenon could be used to increase the

moral congruence of the organization. A promotion rejection interview could be used,

much like an exit interview, to determine if low PO fit is affecting motivation to lead.

These would be initial steps in an exploration that could lead to the discovery of points of

resistance to the status quo. The purpose of identifying these points is not necessarily to

change or reduce resistance. Rather, resistance can identify areas for improvement in the

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current organizational design and may indicate organizational values that should be

questioned.

Study Limitations

External validity for this study was limited by a non-random sample. However,

very little organizational research uses random sampling, making generalizability

commonly problematic. Sample selection bias and range restriction were likely present as

the sample included mostly highly educated and high job level individuals, and a

relatively smaller number of friends and work colleagues. In addition, common method

bias may have been present, as all predictors and criteria were presented in a single

instrument. Although the survey was administered online and offered complete

anonymity to participants, social desirability may have affected the results, especially

with more sensitive questions, such as those regarding moral philosophy.

All questions posed by participants were answered immediately. However, this

may not have been as effective as having the researcher physically present when the

survey was administered. The present study was not designed to examine the meaning

inferred by participants for the term “organization” when perceived PO fit was measured.

However, one participant questioned the connotation of this term. Inquiries on the

meaning of several moral philosophy questions were also answered. This underlines the

importance of clarity on context and meaning of terms in future research in these areas.

Members of the military participated in this study, as the Northcentral University

community included service men and women. The impact of this group was not

anticipated. No category for public, private, or military sector was included in the survey.

A previous meta-analysis found that organizational commitment measures did not differ

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by private and public sector (Steinhaus & Perry, 1996). So this limitation may be minimal

for these groups. However, although it may have been better to do so, the military group

was not differentiated, so military organizations could not be treated as a separate group

in the analysis. As the decisions made by members of the military are certainly more

serious and pressing, and governed by more strict guidelines and a duty to defend one’s

country, the results for this group are likely to be more complex and would likely differ

from private and public organizations.

Recommendations for Future Motivation to Lead Research

The situational factors suggested by the bases of commitment, as identified by

Meyer and Herscovitch (2001), give direction for other situations that may influence

motivation to lead. As the bases of affective commitment include the shared values

reflective of PO fit, the other bases for this form of commitment are the most strongly

suggested by the current findings. These include any situation that influences

involvement, or promotes identification with an organization or objective. Other

situational factors suggested by normative and continuance commitment that may

influence motivation to lead include a lack of alternatives and a sense of obligation due to

a psychological contract. Situational factors in these areas are recommended as

candidates for future research to further develop a situational model of motivation to lead.

More research is needed to compare commitment and motivation to lead. As these

concepts are differentiated, the relationship between PO fit and motivation to lead may be

partially explained by commitment. Motivation to lead may be sourced in commitment,

or commitment may motivate an individual to take a leadership role. Westerman (1997)

proposes that values congruence feeds organizational commitment, which then

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contributes to the intention to remain with the organization. Likewise, PO fit could

increase organizational commitment, which could, in turn, increase motivation to lead.

Conversely, Edwards and Shipp (2007) suggest that, as commitment is identification with

and involvement with the organization, it could be assumed that leaders are higher in

organizational commitment. More research comparing commitment and motivation to

lead would be useful. As Chan and Drasgow’s (2001) motivation to lead construct is

relatively new, research based on the premise that motivation to lead and organizational

commitment are related could utilize the relatively rich body of knowledge already

existing for organizational commitment.

This study found that both idealists and individuals experiencing low PO fit are

self-selecting away from leadership positions. However, it is still not known if these

individuals are also systematically excluded from leadership positions. Organizational

barriers to advancement due to low PO fit or idealism, such as withholding of

opportunity, could lead to internalized suppression of the motivation to lead, and these

forces could accumulate and compound over time (Fassinger, 2008). Future research

could explore these outcomes by differentiating the relative contribution of the

organization via exclusion versus self-exclusion by the low PO fit individual or idealist.

Detailed case studies might be best suited to this investigation.

Recommendations for Future PO Fit Research

van Vianen, de Pater, and van Dijk (2007) identified work values categories that

could be used to determine how PO fit on specific values relate to the motivation to lead

dimensions. They describe affective work values as being related to feelings and

emotions, and referring to happiness, good human relationships, and friendships at work.

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Cognitive work values relate to belief systems about appropriate behaviors, and refer to

broadening one's horizons, contributing to society, and having meaningful work.

Instrumental work values are based on obtaining desired ends like work benefits,

security, and success. van Vianen et al. found cognitive and instrumental values to be

related to turnover intention, but affective values were not. Although value dimensions

are not included in the present study, the differences found by van Vianen et al. indicate

that each motivation to lead dimension may have a different relationship with PO fit

based on each of these values categories.

The present study did not measure differential content or directional differences

for PO fit. Although it was shown that those lower in PO fit were lower in motivation to

lead, it is unknown as to exactly which values were perceived to be different and the

direction of the differences. For example, lower fit on work-life segmentation preferences

could indicate that the individual desires more segmentation while the organization offers

less, or vice versa. One application of measuring directional content would be exploring

the differences in effect for low ethical fit when the ethical level of the individual is

higher than that of the organization. Individuals low in ethical fit in this situation may

experience exclusionary punishment, which could induce low motivation to lead. For

example, “senior executives at Prudential-Bache systematically marginalized, demoted,

and fired individuals who objected to the company’s questionable practices and rewarded

those who went along” (Ashforth & Anand, 2003, p. 33). Ethical individuals within

corrupt environments might self-select away from leadership, as well as being

systematically excluded (Bradley, Brief, & Smith-Crowe, 2008). This exclusion

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phenomenon, which appears to be occurring in the field, merits further investigation, and

directional ethical fit measurement could be one component used to detect its presence.

Although supplementary fit was the focus of the present study, needs-supplies fit

and its relationship with motivation to lead offers another avenue of research that would

be particularly valuable in a single organization context. This exploration could be

informed by the notion of affordances, which are the relationships between “abilities and

aspects of a situation that enable those abilities” (Jayawickreme & Chemero, 2008, p.

121). Much like assessing the climbability of stairs based on one’s own abilities, the

desire to advance on the corporate ladder and the opportunity supplied by the

organization, could produce varying affordances based on any number of individual and

organizational factors. Hodges and Baron (1992) propose that values themselves could

constrain the perception of affordances. Therefore, even if motivation to lead is initially

high, if values lower the perception of affordance, diverse leaders will not emerge. In

other words, if an individual wishes to lead, but the individual perceives that the

organization does not supply the opportunity and context that would enable them to lead,

the individual may simply conclude that they are unable to lead, decide that leadership is

too costly, or disengage and become unwilling to lead.

Another topic suggested by the present study is the interplay of PO fit and ethical

conflict. Results from the present study suggest that low PO fit does not automatically

imply ethical conflict. Relativism was proposed as a moderator of PO fit and motivation

to lead, in large part because relativism is known to effect reactions to ethical conflict.

However, no interaction was found. This implies that low PO fit is not an antecedent of

ethical conflict. It is possible that, rather than resulting from low PO fit, ethical conflict

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moderates the relationship between PO fit and motivation to lead. An exploration of this

topic could show whether ethical conflict increases the salience of low PO fit.

On a system level, the introduction of diverse values by promoting those with low

PO fit could change the norms of the organization (Dickson, Resick, & Goldstein, 2008)

and diversify the leader pool, but it is unclear if and when this is desirable. For example,

Lankau et al. (2007) found that perceived values differences in top management teams

increased conflict and reduced commitment. Others have proposed that diversity of

experience, values, and opinions, and the resulting conflict, may assure ethical decisions,

and increase firm performance (Daboub, Rasheed, Priem, & Gray, 1995; Jehn &

Bendersky, 2003). Future studies may show concretely what is only proposed in the

present study concerning the importance of complementary fit on values at the systems

level. Using another categorization introduced by Ostroff and Schulte (2007), leadership

diversity could offer a compilational perspective, where a group of people, each with

differing values, offers a view that transcends that of a more homogenous group.

Recommendations for Future Moral Philosophy Research

In commitment research, attention has centered on affective commitment and PO

fit because affective commitment is thought to reflect shared values (Meyer &

Herscovitch, 2001). The results of the present study saw one difference between

affective-identity motivation to lead and the other motivation to lead dimensions, in that

affective-identity motivation to lead was related negatively to relativism, whereas the

other dimensions were related positively to relativism. That is, individuals with a belief in

universal rules were less likely to feel that they were leadership material. Also, although

only approaching significance (p = .052), an interaction may have been present for PO fit,

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relativism, and affective-identity motivation to lead, where relativists were less likely to

lead when PO fit was low, and low PO fit had no effect for universalists. Further

investigation of affective-identity motivation to lead may be warranted to determine if,

how, and why it differs from the other dimensions in relation to relativism.

The present study cannot answer the question of exactly why idealists exhibited

consistently low motivation to lead. It seems likely that idealists avoid leadership because

they view this role as requiring them to make decisions that would result in harm to

others. In addition, idealists value obedience (Forsyth, 1992). In a hierarchical

organization that uses command and control that requires acquiescence to authority, the

idealist may anticipate being torn between complying and honoring their principles.

Qualitative research exploring the experiences of idealists in organizations could clarify

the reasons for their low motivation to lead.

Those who are low in motivation to lead because of idealism may still feel some

pull to lead. For example, Ostroff and Schulte (2007) note that an individual response to

low PO fit may be an attempt to remake an environment to be more congruent. A similar

phenomenon may occur for the idealist. An idealist who believes they can provide

benefits for the group without causing harm may attempt to change the system, and then

later retreat from leadership when system resistance is strong enough that it breaks their

resolve (Papavero, 1999). A study of the experiences of idealists (and others) who have

left leadership positions could shed light on this phenomenon.

Idealists are more committed to their professions than their organizations (Shaub

et al., 1993). This suggests a possible negative relationship between person-vocation fit

(PV fit) and motivation to lead. A person with higher PV fit may be more reluctant to

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move into a leadership position (Papavero, 2007). This topic could be explored by

comparing the relationship between PV fit and motivation to lead, using idealism as a

moderator.

Recommendations for Future Group Differences Research

PO fit did not differ for ethnicity or gender in the present study. This is possibly

due to attributes of the sample, such as the relatively high job level, which could impact

the importance of fit to the individual and the presence of fit itself. Gender and ethnicity

were related to relativism and motivation to lead, especially the non-calculative and

social-normative dimensions. This finding suggests a need for further research exploring

these differences, and organizational recognition of the reality of diverse values and

motivational bases for potential leaders. Top management is known to more closely

match the organization’s culture than lower management and non-management

employees, which is not surprising given that promotions are often based on fit with the

culture (Berthon, 1993). However, little research has explored how membership in groups

with values generally different from dominant organizational cultures relates to

advancement. Qualitative study of the experiences of group members that may be

marginalized and excluded would also be valuable in zeroing in on how values

differences are experienced in the general population of the organization. The study of

socio-cultural group differences for the prediction of motivation to lead from PO fit and

idealism is also warranted, similar to the work of Nwadei (2003) for PO fit and

commitment in the U.S., the Middle East, Africa, and Europe.

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Epilogue

Motivation to lead decreases due to lower PO fit and higher idealism, which could

lead to increased turnover and lower commitment. These outcomes are especially costly

at higher levels of the organization. Clashes in organizational priorities and personal

values such as work-life balance can be addressed by offering honest portrayals of

expectations, and policies that balance and support both agendas. Shifting the

advancement process from exclusion to inclusion is key. Recognition that definitions of

success vary, and that these definitions may include values such as flexibility and

creativity that seem contrary to existing organizational values, may bring advantage to

the organization willing to recruit and accommodate talented and diverse employees and

management trainees.

Changes could be made to the advancement process to allow advancement

decisions and recommendations to be made by diverse teams that include peers and

subordinates, and top management could provide guidance. Decision makers could be

educated in self-reflection, and individual growth and development. Rather than focusing

on the possible detriments of conflict created by values differences in top teams, leaders

could be educated in viewpoints and team skills that enable constructive use of conflict,

and skills that enable movement to moral congruence.

However, change takes time, and other factors may adjust the color of these

concerns. If organizations become more decentralized and the relationship between

individuals and the organization become more loosely coupled, individuals may be able

to make choices that fit their values, but do not meet other basic needs, such as security

and fair compensation. The role of management may decrease dramatically if

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technological controls are substituted for management controls. For example, if

employees are guided and monitored electronically, then managers may become obsolete.

If (or rather when) this occurs, the advancement process will be impacted dramatically, as

the corporate ladder will be far shorter and far further removed from the average worker.

Evidence of this transition can be seen in ever increasing income disparity. Strategic

leadership and high-level organizational element manipulation will remain as necessary

skills. However, relationships and linkages between employees and leadership could

become no more than up line reporting of results and productivity monitoring.

Allowances for creative expression at lower levels of the organization would have to be

made, but it is unclear how this would be accomplished.

We may be experiencing a crisis of confidence in organizations that have not

evolved beyond materialist values. Organizations are not democracies and they are not

subject to democratic accountability (Quinn et al., 1997). Anecdotally, a worker who had

recently arrived in the U.S. from China in the late 1990s expressed surprise that she did

not feel free to express her true self in the undemocratic context of the large corporation

in which she worked (personal communication, 1997). She likened the lack of freedom to

that of her homeland. Quinn et al. suggest that we need a democratic conversation among

equals. Otherwise, we will be left with pure instrumentalism, meaning that the least cost

route to advancement will always be taken. Quinn et al. see citizenship as a prerequisite

of virtue and differentiate between pragmatic ethics and vulgar pragmatism. The

unwritten rules of ethical conduct in organizations offer no protection to those who

espouse a foreign ethic (Quinn et al.). Under constant pressure, employees simply give in

and conform, as out of sync attributes must be hidden from those who make promotion

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decisions (Quinn et al.). It is possible that some individuals who are not motivated to

lead, or are excluded from leadership roles due to low PO fit, are the very individuals

who could introduce us to a more democratic organization. We can welcome this change

by thoughtfully integrating leaders with values known to conflict with the current ethic

through upgraded reward structures and advancement policies.

The present study is value laden, and was conceived from observations in the field

regarding rejections of advancement. As Bennis (2007) points out, leadership is always a

matter of values, which are difficult, to say the least, to research objectively. Bennis calls

for new scholarly forms that are both expansive and rigorous. It is necessary to start a

conversation on how our organizations are designed and controlled, and whether

admittance to leadership levels requires a price that some do not notice or choose to

ignore, some understand and tolerate, and some are not willing to pay. This situation

presents a paradox, where diverse values orientations enable pluralistic leadership, but

individuals select away (or are excluded) from leadership when values differ. However,

these are the people who might be the least resistant to change and who might have the

best chance of moving organizations forward.This subject is sensitive as it involves

questioning existing leadership and the advancement process itself. Individuals who

differ in basic values, especially values of social dominance and control, are unlikely to

be taken into the fold without resistance from the existing culture that may view these

individuals as a threat. But this could change.

It is hoped that this study will generate further research into the role that low PO

fit and idealism play in the advancement process, and how organizations can be

transformed to allow more pluralistic leadership that welcomes the full participation and

137

contributions of all individuals. In Argyris’ (2004) words, “one criterion of a better world

is a better fit between self-actualizing needs of individuals and the requirements of

organizational effectiveness” (p. 379).

138

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Appendix A:

Scale Items

Affective-Identify Motivation to Lead Items

1. Most of the time, I prefer being a leader rather than a follower when working in a group.

2. I am the type of person who is not interested in leading others. (reverse scored)

3. I am definitely not a leader by nature. (reverse scored)

4. I am the type of person who likes to be in charge of others.

5. I believe I can contribute more to a group if I am a follower rather than a leader. (reverse scored)

6. I usually want to be the leader in the groups that I work in.

7. I am the type who would actively support a leader but prefers not to be appointed as leader. (reverse scored)

8. I have a tendency to take charge in most groups or teams that I work in.

9. I am seldom reluctant to be the leader of a group.

Non-Calculative Motivation to Lead Items

1. I am only interested to lead a group if there are clear advantages for me. (reverse scored)

2. I will never agree to lead if I cannot see any benefits from accepting that role. (reverse scored)

3. I would only agree to be a group leader if I know I can benefit from that role. (reverse scored)

4. I would agree to lead others even if there are no special rewards or benefits with that role.

5. I would want to know “what’s in it for me” if I am going to agree to lead a group. (reverse scored)

6. I never expect to get more privileges if agree to lead a group.

7. If I agree to lead a group, I would never expect any advantages or special benefits.

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8. I have more of my own problems to worry about than to be concerned about the rest of the group. (reverse scored)

9. Leading others is reality more of a dirty job rather than an honorable one. (reverse scored)

Social-Normative Motivation to Lead Items

1. I feel that I have a duty to lead others if I am asked.

2. I agree to lead whenever I am asked or nominated by the other members.

3. I was taught to believe in the value of leading others.

4. It is appropriate for people to accept leadership roles or positions when they are asked.

5. I have been taught that I should always volunteer to lead others if I can.

6. It is not right to decline leadership roles.

7. It is an honor and a privilege to be asked to lead.

8. People should volunteer to lead rather than wait for others to ask or vote for them.

9. I would never agree to lead just because others voted for me. (reverse scored)

Person-Organization Fit Items

1. The things that I value in life are very close to the things that my organization values.

2. My personal values match my organization’s values and culture.

3. My organization’s values and culture provide a good fit with the things that I value in life.

Relativism Items

1. There are no ethical principles that are so important that they should be a part of any code of ethics.

2. What is ethical varies from one situation and society to another.

3. Moral standards should be seen as being individualistic; what one person considers to be moral may be judged to be immoral by another person.

4. Different types of morality cannot be compared as to "rightness."

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5. Questions of what is ethical for everyone can never be resolved since what is moral or immoral is up to the individual.

6. Moral standards are simply personal rules that indicate how a person should behave, and are not to be applied in making judgments of others.

7. Ethical considerations in interpersonal relations are so complex that individuals should be allowed to formulate their own individual codes.

8. Rigidly codifying an ethical position that prevents certain types of actions could stand in the way of better human relations and adjustment.

9. No rule concerning lying can be formulated; whether a lie is permissible or not permissible totally depends upon the situation.

10. Whether a lie is judged to be moral or immoral depends upon the circumstances surrounding the action.

Idealism Items

1. People should make certain that their actions never intentionally harm another even to a small degree.

2. Risks to another should never be tolerated, irrespective of how small the risks might be.

3. The existence of potential harm to others is always wrong, irrespective of the benefits to be gained.

4. One should never psychologically or physically harm another person.

5. One should not perform an action which might in any way threaten the dignity and welfare of another individual.

6. If an action could harm an innocent other, then it should not be done.

7. Deciding whether or not to perform an act by balancing the positive consequences of the act against the negative consequences of the act is immoral.

8. The dignity and welfare of the people should be the most important concern in any society.

9. It is never necessary to sacrifice the welfare of others.

10. Moral behaviors are actions that closely match ideals of the most "perfect" action.

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Appendix B:

Request for Participation

Subject: Request for Research Participation

Dear (contact),

I am a PhD student at Northcentral University, Department of Psychology and I am currently collecting data for my dissertation. I am hoping that this study will increase our understanding of leadership and values.

Your input is necessary to ensure the success of this project. You can help further research that seeks to improve our workplaces and our experiences at work.

You will complete a simple and interesting online survey (you will not be asked to identify yourself, so your answers will be completely anonymous).

Here is a link to the survey. The password is: leadership.

[surveylink]

Participation is completely voluntary. If you have any questions about the study, please email me at [email protected].

Your participation is valuable and your time is greatly appreciated. Thank you in advance for your input.

Sincerely,

Elena Papavero [email protected]

https://www.surveymonkey.com/optout.aspx

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Appendix C:

Informed Consent, Survey, and Debriefing

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Appendix D:

Additional Statistical Tables and Figures

Table 9. Means and Standard Deviations for Study Variables and Age

Age PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

18 to 23 years M 12.11 29.00 34.00 32.56 35.56 33.67 33.93

SD 5.69 8.31 7.75 7.02 4.83 3.97 4.10

24 to 32 years M 14.66 28.21 35.33 32.20 33.99 31.94 32.71

SD 4.22 6.82 7.04 6.03 5.43 4.90 3.84

33 to 40 years M 15.18 27.22 34.80 32.50 33.80 32.46 32.92

SD 4.38 6.67 7.49 5.87 5.91 4.90 4.08

41 to 50 years M 14.73 25.38 35.20 33.01 35.57 32.26 33.61

SD 5.12 7.28 7.42 6.38 5.80 4.94 4.34

51 years and over M 14.67 25.07 34.87 33.40 35.79 31.45 33.54

SD 4.98 6.70 7.42 5.74 5.41 5.16 3.91

Note. N = 1024. AIMTL = affective-identity motivation to lead; NCMTL = non-calculative motivation to lead; SNMTL = social-normative motivation to lead; GMTL = general motivation to lead.

Table 10. Means and Standard Deviations for Study Variables and Gender

Gender PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Male M 14.83 26.00 33.24 33.59 34.44 32.80 33.61

SD 4.81 7.09 7.68 5.63 5.96 5.04 4.24

Female M 14.74 26.25 36.32 32.26 35.52 31.38 33.05

SD 4.81 6.95 6.71 6.34 5.45 4.84 3.97


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Table 11. Means and Standard Deviations for Study Variables and Educational Level

Educational Level PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Some high school -- -- -- -- -- -- --

Completed high school M 13.50 30.50 33.50 24.50 32.00 31.50 29.33

SD 2.12 2.12 4.95 7.78 1.41 .71 3.30

Some college M 13.35 27.36 34.83 31.32 36.03 31.19 32.85

SD 5.27 6.94 7.15 6.49 5.22 5.53 4.44

Completed college M 12.14 27.73 35.59 30.31 32.81 32.14 31.75

SD 4.98 6.95 6.91 5.40 5.97 5.27 4.37

Some graduate school M 14.94 27.03 34.88 32.67 35.08 31.96 33.27

SD 4.73 6.53 7.93 6.82 5.92 5.29 4.49

Graduate degree M 14.97 25.81 35.03 33.16 35.07 32.11 33.45

SD 4.76 7.10 7.32 5.85 5.68 4.90 3.99


Table 12. Means and Standard Deviations for Study Variables and Work Experience

Work Experience PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Less than 1 year M 11.00 28.00 39.00 28.50 36.50 29.50 31.50

SD 7.07 8.49 2.83 7.78 4.95 2.12 .24

1 to 5 years M 13.49 29.06 36.04 31.66 33.76 32.07 32.50

SD 4.65 7.69 6.45 7.01 5.42 5.22 3.89

6 to 10 years M 14.85 27.05 36.40 32.33 33.63 31.62 32.53

SD 4.55 6.29 7.31 5.80 5.63 4.37 3.88

11 to 15 years M 15.17 27.23 35.05 32.66 34.35 31.98 33.00

SD 4.54 7.29 7.19 6.10 6.53 4.99 4.25

16 years or more M 14.80 25.54 34.74 33.12 35.43 32.13 33.56

SD 4.90 6.91 7.48 5.98 5.52 5.06 4.11


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Table 13. Means and Standard Deviations for Study Variables and Leadership Experience

Leadership Experience PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Less than 1 year M 13.73 27.74 37.22 29.15 33.19 30.78 31.04

SD 4.87 6.67 6.20 6.83 6.75 5.18 4.42

1 to 5 years M 14.28 27.54 36.47 31.60 34.32 31.63 32.52

SD 4.91 6.94 7.34 6.15 5.45 4.37 3.76

6 to 10 years M 14.59 25.24 34.52 32.89 34.53 31.30 32.91

SD 4.68 7.21 7.11 5.73 5.55 4.81 3.80

11 to 15 years M 25.68 35.07 33.33 35.77 32.46 33.85 15.18

SD 6.96 7.01 5.62 5.59 4.93 4.17 4.76

16 years or more M 15.42 25.41 33.56 34.75 36.01 33.07 34.61

SD 4.74 6.86 7.75 5.44 5.59 5.36 4.00


Table 14. Means and Standard Deviations for Study Variables and Ethnicity

Ethnicity PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

White non-Hispanic M 14.73 25.98 34.39 32.97 34.94 31.92 33.28

SD 4.86 7.10 7.25 6.17 5.72 4.97 4.14

Asian or Pacific Islander M 15.15 30.65 36.85 32.50 31.31 32.50 32.10

SD 4.02 6.22 6.73 5.67 4.72 4.60 3.40

Hispanic M 14.70 26.65 39.89 32.97 34.89 32.57 33.48

SD 4.85 6.34 6.90 6.37 5.47 5.75 4.03

Black non-Hispanic M 15.26 26.59 37.72 32.24 36.36 32.11 33.57

SD 4.70 6.79 6.81 5.49 5.70 4.80 4.03

Other M 14.64 24.85 35.06 33.02 35.32 33.62 33.99

SD 4.63 6.13 8.77 5.23 5.75 5.15 4.11


174

Table 15. Means and Standard Deviations for Study Variables and Job Tenure

Job Tenure PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Less than 1 year M 14.40 27.36 34.60 32.08 35.20 30.94 32.74

SD 4.82 7.10 8.15 5.88 4.90 4.12 3.22

1 to 5 years M 14.79 26.47 34.73 32.88 34.60 32.12 33.20

SD 4.74 7.38 7.46 6.16 6.00 5.10 4.29

6 to 10 years M 14.33 26.02 35.32 32.85 35.04 31.77 33.22

SD 4.85 6.63 7.34 6.26 5.75 5.19 4.31

11 to 15 years M 15.41 26.04 34.45 32.88 34.98 31.98 33.28

SD 4.42 7.26 7.19 5.77 5.54 4.79 3.83

16 years or more M 15.02 25.53 35.59 33.13 35.61 32.61 33.78

SD 5.08 6.72 7.73 5.85 5.51 4.81 3.90


Table 16. Means and Standard Deviations for Study Variables and Job Level

Job Level PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Clerical M 13.36 27.38 35.57 28.91 34.14 31.23 31.42

SD 5.38 8.54 7.36 7.34 5.70 5.71 4.61

Technical M 13.36 27.38 35.57 28.91 34.14 31.23 31.42

SD 5.38 8.54 7.36 7.34 5.70 5.71 4.61

Professional M 14.63 26.08 35.80 32.24 34.78 31.61 32.88

SD 4.86 6.99 7.17 6.16 5.76 4.84 3.98

First line manager M 14.81 27.09 37.02 32.89 34.51 31.81 33.07

SD 5.04 6.90 7.06 4.69 5.15 4.70 2.96

Middle manager M 14.93 26.72 33.58 33.55 35.00 33.01 33.85

SD 4.41 6.87 7.63 5.65 5.64 5.05 4.29

Executive M 16.11 25.48 32.93 36.18 36.72 33.56 35.49

SD 4.50 7.18 7.54 4.93 5.82 5.14 4.00


175

Table 17. Means and Standard Deviations for Study Variables and Employment Status

Employment Status PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Part-time M 14.17 26.06 37.10 31.34 34.30 31.04 32.23

SD 5.16 8.62 6.35 6.20 5.55 3.82 3.50

Full-time M 14.84 26.14 34.84 33.02 35.07 32.14 33.41

SD 4.78 6.87 7.43 6.02 5.73 5.07 4.14


Table 18. Means and Standard Deviations for Study Variables and Organization Size

Organization Size PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

1 to 50 employees M 15.46 25.67 35.52 32.42 35.02 31.77 33.07

SD 4.81 7.38 7.08 6.44 5.47 5.05 4.08

51 to 100 employees M 14.70 24.43 37.34 32.57 34.71 32.39 33.22

SD 4.83 7.02 6.50 6.32 5.74 4.44 3.92

101 to 500 employees M 26.51 34.81 33.14 35.03 32.27 33.48 14.82

SD 7.44 7.06 5.67 5.75 5.15 4.05 4.68

501 to 1000 employees M 14.98 26.33 34.77 33.43 35.01 31.77 33.40

SD 4.75 6.79 7.05 5.88 6.50 4.98 4.43

1001 or more M 14.31 25.95 34.10 32.92 35.09 32.02 33.34

SD 4.90 6.54 8.01 6.04 5.60 5.03 4.14


176

Table 19. Means and Standard Deviations for Study Variables and Organization Tenure

Organization Tenure PO Fit Idealism Relativism AIMTL NCMTL SNMTL GMTL

Less than 1 year M 14.27 27.65 34.84 31.99 34.69 32.56 33.08

SD 4.77 6.65 7.32 6.57 5.45 4.70 3.87

1 to 5 years M 14.80 26.56 34.95 33.15 34.51 31.80 33.15

SD 4.86 7.48 7.23 5.93 6.13 5.08 4.27

6 to 10 years M 14.27 25.71 35.31 32.50 34.77 31.36 32.88

SD 4.83 6.61 7.22 5.98 5.38 5.01 3.92

11 to 15 years M 15.51 24.84 34.48 33.44 35.71 32.57 33.91

SD 4.58 6.68 7.65 6.16 5.98 4.63 4.18

16 years or more M 15.21 25.77 35.16 33.07 35.84 32.64 33.85

SD 4.79 6.93 7.70 5.97 5.35 5.05 4.08


177

Person-Organization Fit Score25.020.015.010.05.00.0

Fre

qu

en

cy

400

300

200

100

0

Figure 4. Histogram of participants' reported person-organization fit scores with normality curve superimposed.

Observed Cum Prob1.00.80.60.40.20.0

Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 5. Normal probability of participants’ reported person-organization fit scores.

178

Idealism Score50.040.030.020.010.00.0

Freq

uenc

y

60

50

40

30

20

10

0

Figure 6. Histogram of participants' reported idealism scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 7. Normal probability of participants’ reported idealism scores.

179

Relativism Score60.050.040.030.020.010.0

Freq

uenc

y

60

40

20

0

Figure 8. Histogram of participants' reported relativism scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 9. Normal probability of participants’ reported relativism scores.

180

General Motivation to Lead Score45.040.035.030.025.020.015.0

Freq

uenc

y

120

100

80

60

40

20

0

Figure 10. Histogram of participants' reported general motivation to lead scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 11. Normal probability of participants’ reported general motivation to lead scores.

181

Affective-identity Motivation to Lead Score50.040.030.020.010.0

Freq

uenc

y

100

80

60

40

20

0

Figure 12. Histogram of participants' reported affective-identity motivation to lead scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 13. Normal probability of participants’ reported affective-identity motivation to lead scores.

182

Noncalculative Motivation to Lead Score50.040.030.020.010.0

Freq

uenc

y

120

100

80

60

40

20

0

Figure 14. Histogram of participants' reported non-calculative motivation to lead scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 15. Normal probability of participants’ reported non-calculative motivation to lead scores.

183

Social-normative Motivation to Lead Score50.040.030.020.010.0

Freq

uenc

y

120

100

80

60

40

20

0

Figure 16. Histogram of participants' reported social-normative motivation to lead scores with normality curve superimposed.


Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Figure 17. Normal probability of participants’ reported social-normative motivation to lead scores.

184

Table 20. Summary of Hierarchical Regression Analysis for PO Fit Predicting General Motivation to Lead

Step Variable B SE B β CIL.95 CIU.95

1 (Intercept) 31.66*** .43 30.81 32.51

Lead exp 1 - 5 yearsa .83† .50 .09 -.15 1.80

Lead exp 6 - 10 yearsa 1.20* .51 .12 .21 2.19

Lead exp 11 - 15 yearsa 2.19*** .53 .20 1.14 3.24

Lead exp >= 16 yearsa 2.70*** .48 .31 1.76 3.64

2 (Intercept) 28.52*** 1.05 26.46 30.58

Lead exp 1 - 5 yearsa .95† .50 .10 -.03 1.92

Lead exp 6 - 10 yearsa 1.18* .51 .12 .18 2.18

Lead exp 11 - 15 yearsa 1.88** .54 .17 .81 2.95

Lead exp >= 16 yearsa 2.56*** .50 .29 1.57 3.55

Technicalb 2.28* 1.05 .12 .23 4.33

Professionalb 2.93** .89 .35 1.18 4.69

First line managerb 3.05** 1.03 .16 1.03 5.07

Middle managerb 3.56*** .92 .31 1.75 5.37

Executiveb 4.90*** .92 .41 3.09 6.71

3 (Intercept) 28.85*** 1.04 26.81 30.89

Lead exp 1 - 5 yearsa .92† .49 .10 -.05 1.88

Lead exp 6 - 10 yearsa 1.12* .50 .11 .13 2.11

Lead exp 11 - 15 yearsa 1.77** .54 .16 .71 2.83

Lead exp >= 16 yearsa 2.42** .50 .27 1.44 3.40

Technicalb 2.20* 1.03 .12 .17 4.23

Professionalb 2.69** .89 .32 .95 4.43

First line managerb 2.79** 1.02 .15 .79 4.79

Middle managerb 3.30*** .91 .29 1.51 5.09

Executiveb 4.51*** .92 .38 2.71 6.31

PO fit (centered) .13*** .03 .15 .08 .18

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .04 for Step 2 (ps < .001); ∆R2 = .02 for Step 3 (ps < .001). avs. < 1 year. bvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

185

Table 21. Summary of Hierarchical Regression Analysis for PO Fit Predicting Affective-Identity Motivation to Lead


1 (Intercept) 30.09*** .64 28.83 31.34

Lead exp 1 - 5 yearsa 1.47* .73 .10 .02 2.91

Lead exp 6 - 10 yearsa 2.72*** .74 .18 1.26 4.18

Lead exp 11 - 15 yearsa 3.24*** .79 .20 1.70 4.79

Lead exp >= 16 yearsa 4.27*** .71 .33 2.89 5.66

2 (Intercept) 23.83*** 1.54 20.81 26.84

Lead exp 1 to 5 yearsa 1.78** .73 .13 .35 3.21

Lead exp 6 - 10 yearsa 2.87*** .75 .19 1.40 4.33

Lead exp 11 - 15 yearsa 2.95*** .80 .18 1.38 4.51

Lead exp >= 16 yearsa 4.32*** .74 .33 2.87 5.76

Technicalb 5.18** 1.53 .19 2.17 8.18

Professionalb 5.80*** 1.31 .47 3.23 8.37

First line managerb 6.27*** 1.51 .23 3.32 9.23

Middle managerb 6.53*** 1.35 .39 3.88 9.18

Executiveb 8.78*** 1.35 .50 6.13 11.44

3 (Intercept) 24.10*** 1.54 21.08 27.11


Lead exp 6 - 10 yearsa 2.82*** .75 .19 1.36 4.28

Lead exp 11 - 15 yearsa 2.86*** .79 .17 1.30 4.42

Lead exp >= 16 yearsa 4.21*** .74 .32 2.76 5.65

Technicalb 5.11** 1.53 .19 2.12 8.11

Professionalb 5.60*** 1.31 .46 3.04 8.17


Middle managerb 6.32*** 1.35 .38 3.68 8.97

Executiveb 8.47*** 1.35 .48 5.82 11.12

PO fit (centered) .10*** .04 .08 .03 .18

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .05 for Step 2 (ps < .001); ∆R2 = .01 for Step 3 (ps = .007). avs. < 1 year. bvs. clerical. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

186

Table 22. Summary of Hierarchical Regression Analysis for PO Fit Predicting Non-Calculative Motivation to Lead


1 (Intercept) 35.52*** .25 35.04 36.00

Gendera -1.09** .36 -.09 -1.79 -.39

2 (Intercept) 34.08*** .62 32.87 35.30

Gendera -1.48*** .36 -.13 -2.19 -.77

Lead exp 1 - 5 yearsb .74 .70 .06 -.63 2.11

Lead exp 6 - 10 yearsb 1.06 .71 .08 -.33 2.46

Lead exp 11 - 15 yearsb 2.42** .75 .16 .94 3.90

Lead exp >= 16 yearsb 2.64*** .68 .21 1.30 3.97

3 (Intercept) 33.88*** .62 32.66 35.11

Gendera -1.40*** .36 -.12 -2.11 -.69

Lead exp 1 - 5 yearsb .90 .70 .07 -.47 2.27

Lead exp 6 - 10 yearsb 1.10 .71 .08 -.29 2.49

Lead exp 11 - 15 yearsb 2.54** .75 .16 1.07 4.01

Lead exp >= 16 yearsb 2.70*** .68 .22 1.36 4.03

Asian or Pacific Islanderc -3.32** 1.12 -.09 -5.52 -1.12

Hispanicc -.18 .94 -.01 -2.03 1.67

Black non-Hispanicc 1.44** .59 .08 .29 2.59

Other ethnicityc .57 .84 .02 -1.09 2.22

4 (Intercept) 30.94*** 1.49 28.00 33.87

Gendera -1.71*** .37 -.15 -2.44 -.99

Lead exp 1 - 5 yearsb 1.11 .71 .08 -.28 2.49

Lead exp 6 - 10 yearsb 1.27† .73 .09 -.16 2.69

Lead exp 11 - 15 yearsb 2.47** .77 .16 .95 3.98

Lead exp >= 16 yearsb 2.81*** .72 .23 1.39 4.23


Hispanicc -.26 .94 -.01 -2.11 1.58


Other ethnicityc .70 .84 .03 -.95 2.35

(table continues)

187


Technicald 3.06* 1.51 .12 .09 6.03

Professionald 2.73* 1.28 .24 .21 5.25

First line managerd 2.68† 1.48 .10 -.22 5.59

Middle managerd 3.07* 1.33 .20 .45 5.69

Executived 4.51** 1.34 .27 1.89 7.13

5 (Intercept) 31.33*** 1.49 28.41 34.25

Gendera -1.67*** .37 -.15 -2.40 -.95

Lead exp 1 - 5 yearsb 1.07 .70 .08 -.31 2.45

Lead exp 6 - 10 yearsb 1.19† .72 .09 -.22 2.61

Lead exp 11 - 15 yearsb 2.33* .77 .15 .82 3.84

Lead exp >= 16 yearsb 2.64*** .72 .21 1.22 4.05

Asian or Pacific Islanderc -3.42* 1.12 -.09 -5.60 -1.23

Hispanicc -.23 .93 -.01 -2.06 1.60



Technicald 2.94† 1.50 .11 .00 5.89

Professionald 2.44† 1.28 .21 -.07 4.94

First line managerd 2.37 1.47 .09 -.52 5.26

Middle managerd 2.76* 1.33 .18 .15 5.36

Executived 4.04* 1.33 .24 1.43 6.65

PO fit (centered) .14*** .04 .12 .07 .21

Note. N = 1024. R2 = .01 for Step 1; ∆R2 = .03 for Step 2 (ps < .001); ∆R2 = .02 for Step 3 (ps = .003); ∆R2 = .02 for Step 4 (ps = .005); ∆R2 = .01 for Step 5 (ps < .001). avs. female. bvs. < 1 year. cvs. White non-Hispanic. dvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

188

Table 23. Summary of Hierarchical Regression Analysis for PO Fit Predicting Social-Normative Motivation to Lead


1 (Intercept) 31.37*** .21 30.96 31.79

Gendera 1.43*** .31 .14 .82 2.03

2 (Intercept) 31.38*** .21 30.97 31.79

Gendera 1.41*** .31 .14 .81 2.01

PO fit (centered) .15*** .03 .15 .09 .22

Note. N = 1024. R2 = .02 for Step 1; ∆R2 = .02 for Step 2 (ps < .001). avs. female. *** p < .001.

189

Table 24. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict General Motivation to Lead


1 - 2 See Table 20.

3 (Intercept) 28.67*** 1.04 26.63 30.71

Lead exp 1 to 5 yearsa .94† .49 .10 -.02 1.90

Lead exp 6 - 10 yearsa 1.23** .50 .12 .24 2.22

Lead exp 11 - 15 yearsa 1.84** .54 .16 .79 2.90

Lead exp >= 16 yearsa 2.56*** .50 .29 1.58 3.53

Technicalb 2.38* 1.03 .13 .35 4.41

Professionalb 2.77* .88 .33 1.03 4.50


Middle managerb 3.46*** .91 .31 1.67 5.25

Executiveb 4.69*** .92 .39 2.89 6.48

PO fit (centered) .12*** .03 .14 .07 .17

Relativism (centered) .04** .02 .08 .01 .08

4 (Intercept) 28.65*** 1.04 26.61 30.69


Lead exp 6 - 10 yearsa 1.25** .50 .12 .26 2.24

Lead exp 11 - 15 yearsa 1.85** .54 .17 .79 2.90

Lead exp >= 16 yearsa 2.56*** .50 .29 1.58 3.53

Technicalb 2.37* 1.03 .13 .34 4.40

Professionalb 2.77** .88 .33 1.04 4.50


Middle managerb 3.48*** .91 .31 1.69 5.27

Executiveb 4.70*** .92 .39 2.90 6.50

PO fit (centered) .12*** .03 .14 .07 .17

Relativism (centered) .05** .02 .08 .01 .08

PO fit X relativism .004 .003 .04 .00 .01

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .04 for Step 2 (ps < .001); ∆R2 = .03 for Step 3 (ps < .001); ∆R2 = .002 for Step 4 (ps = .172). avs. < 1 year. bvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

190

Table 25. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Affective-Identity Motivation to Lead


1 - 2 See Table 21.

3 (Intercept) 24.17*** 1.54 21.15 27.19


Lead exp 6 - 10 yearsa 2.78*** .75 .19 1.31 4.25

Lead exp 11 - 15 yearsa 2.83*** .80 .17 1.26 4.39

Lead exp >= 16 yearsa 4.15*** .74 .32 2.70 5.60

Technicalb 5.04** 1.53 .18 2.04 8.05

Professionalb 5.57*** 1.31 .45 3.00 8.14


Middle managerb 6.26*** 1.35 .38 3.60 8.91

Executiveb 8.40*** 1.36 .47 5.74 11.06

PO fit (centered) .10** .04 .08 .03 .18

Relativism (centered) -.02 .02 -.02 -.07 .03

4 (Intercept) 24.13*** 1.54 21.12 27.15


Lead exp 6 - 10 yearsa 2.82*** .75 .19 1.36 4.29

Lead exp 11 - 15 yearsa 2.84*** .80 .17 1.28 4.40

Lead exp >= 16 yearsa 4.15*** .74 .32 2.70 5.60

Technicalb 5.02** 1.53 .18 2.02 8.02

Professionalb 5.58*** 1.31 .45 3.01 8.14


Middle managerb 6.30*** 1.35 .38 3.65 8.94

Executiveb 8.43*** 1.35 .48 5.77 11.08

PO fit (centered) .10** .04 .08 .03 .18

Relativism (centered) -.02 .02 -.02 -.07 .03

PO fit X relativism .009† .005 .06 .00 .02

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .05 for Step 2 (ps < .001); ∆R2 = .01 for Step 3 (ps = .020); ∆R2 = .003 for Step 4 (ps = .052). avs. < 1 year. bvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

191

Table 26. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Non-Calculative Motivation to Lead


1 - 4 See Table 22.

5 (Intercept) 31.20*** 1.49 28.28 34.11

Gendera -1.54*** .37 -.13 -2.27 -.80

Lead exp 1 - 5 yearsb 1.08 .70 .08 -.30 2.46

Lead exp 6 - 10 yearsb 1.28† .72 .09 -.13 2.70

Lead exp 11 - 15 yearsb 2.38** .77 .15 .87 3.89

Lead exp >= 16 yearsb 2.74*** .72 .22 1.32 4.15


Hispanicc -.51 .94 -.02 -2.37 1.34

Black non-Hispanicc 1.29* .59 .07 .14 2.44


Technicald 3.04* 1.50 .12 .10 5.98

Professionald 2.46† 1.27 .21 -.05 4.96


Middle managerd 2.84* 1.33 .18 .23 5.44

Executived 4.13** 1.33 .25 1.52 6.74

PO fit (centered) .14*** .04 .12 .07 .21

Relativism (centered) .05† .02 .06 .00 .10

6 (Intercept) 31.19*** 1.49 28.27 34.10

Gendera -1.55*** .38 -.14 -2.28 -.81

Lead exp 1 - 5 yearsb 1.09 .70 .08 -.29 2.46

Lead exp 6 - 10 yearsb 1.29† .72 .09 -.12 2.71

Lead exp 11 - 15 yearsb 2.38** .77 .15 .88 3.89

Lead exp >= 16 yearsb 2.74*** .72 .22 1.32 4.15


Hispanicc -.49 .95 -.02 -2.35 1.36

Black non-Hispanicc 1.30* .59 .07 .15 2.45


Technicald 3.04* 1.50 .12 .10 5.99

Professionald 2.46† 1.28 .21 -.04 4.96

(table continues)

192



Middle managerd 2.85* 1.33 .18 .25 5.45

Executived 4.14* 1.33 .25 1.53 6.76

PO fit (centered) .14*** .04 .12 .07 .21

Relativism (centered) .05† .02 .06 .00 .10


Note. N = 1024. R2 = .01 for Step 1; ∆R2 = .03 for Step 2 (ps < .001); ∆R2 = .02 for Step 3 (ps = .003); ∆R2 = .02 for Step 4 (ps = .005); ∆R2 = .02 for Step 5 (ps < .001); ∆R2 < .001 for Step 6 (ps = .590). avs. female. bvs. < 1 year. cvs. White non-Hispanic. dvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

Table 27. Summary of Moderated Regression Analysis for PO Fit and Relativism Interacting to Predict Social-Normative Motivation to Lead


1 See Table 23.

2 (Intercept) 31.23*** .21 31.65 31.23***

Gendera 1.73*** .31 .17 2.34 1.73***

PO fit (centered) .15*** .03 .14 .21 .15***

Relativism (centered) .09*** .02 .14 .13 .09***

3 (Intercept) 31.23*** .21 31.65 31.23***

Gendera 1.72*** .31 .17 2.33 1.72***

PO fit (centered) .15*** .03 .14 .21 .15***

Relativism (centered) .09*** .02 .14 .13 .09***


Note. N = 1024. R2 = .02 for Step 1; ∆R2 = .04 for Step 2 (ps < .001); ∆R2 < .001 for Step 3 (ps = .663). avs. female. *** p < .001.

193

Table 28. Summary of Hierarchical Regression Analysis for Idealism Predicting General Motivation to Lead


1 - 2 See Table 20.

3 (Intercept) 28.85*** 1.04 26.81 30.90


Lead exp 6 - 10 yearsa 1.00* .51 .10 .01 2.00

Lead exp 11 - 15 yearsa 1.73** .54 .15 .67 2.79

Lead exp >= 16 yearsa 2.40*** .50 .27 1.42 3.38

Technicalb 2.05* 1.04 .11 .01 4.09

Professionalb 2.69** .89 .32 .95 4.44


Middle managerb 3.38*** .92 .30 1.58 5.17

Executiveb 4.67*** .92 .39 2.87 6.47

Idealism (centered) -.07*** .02 -.13 -.11 -.04

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .04 for Step 2 (ps < .001); ∆R2 = .02 for Step 3 (ps < .001). avs. < 1 year. bvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

194

Table 29. Summary of Moderated Regression Analysis for Idealism Predicting Affective-Identity Motivation to Lead


1 - 2 See Table 21.

3 (Intercept) 24.16*** 1.54 21.14 27.17


Lead exp 6 - 10 yearsa 2.69*** .75 .18 1.23 4.16

Lead exp 11 - 15 yearsa 2.80*** .80 .17 1.23 4.36

Lead exp >= 16 yearsa 4.16*** .74 .32 2.72 5.60

Technicalb 4.95** 1.53 .18 1.95 7.95

Professionalb 5.56*** 1.31 .45 3.00 8.13


Middle managerb 6.35*** 1.35 .38 3.71 8.99

Executiveb 8.55*** 1.35 .48 5.91 11.20

Idealism (centered) -.07** .03 -.09 -.12 -.02

Note. N = 1024. R2 = .05 for Step 1; ∆R2 = .05 for Step 2 (ps < .001); ∆R2 = .01 for Step 3 (ps = .004). avs. < 1 year. bvs. clerical. ** p < Bonferroni adjusted significance level (.0167). *** p < .001.

195

Table 30. Summary of Hierarchical Regression Analysis for Idealism Predicting Non-Calculative Motivation to Lead


1 - 4 See Table 22.

5 (Intercept) 31.38*** 1.49 28.46 34.30

Gendera -1.71*** .37 -.15 -2.43 -.98

Lead exp 1 - 5 yearsb 1.09 .70 .08 -.29 2.46

Lead exp 6 - 10 yearsb 1.03 .72 .07 -.39 2.45

Lead exp 11 - 15 yearsb 2.26** .77 .14 .75 3.77

Lead exp >= 16 yearsb 2.59*** .72 .21 1.18 4.01

Asian or Pacific Islanderc -2.89** 1.12 -.08 -5.09 -.69

Hispanicc -.18 .93 -.01 -2.01 1.65


Other ethnicityc .57 .84 .02 -1.07 2.21

Technicald 2.71† 1.50 .10 -.24 5.66

Professionald 2.40† 1.28 .21 -.11 4.91

First line managerd 2.45† 1.47 .09 -.44 5.33

Middle managerd 2.80* 1.33 .18 .20 5.40

Executived 4.18** 1.33 .25 1.57 6.79

Idealism (centered) -.10*** .02 -.12 -.15 -.05

Note. N = 1024. R2 = .01 for Step 1; ∆R2 = .03 for Step 2 (ps < .001); ∆R2 = .02 for Step 3 (ps = .003); ∆R2 = .02 for Step 4 (ps = .005); ∆R2 = .01 for Step 5 (ps < .001). avs. female. bvs. < 1 year. cvs. White non-Hispanic. dvs. clerical. †p < .10. *p < .05. **p < Bonferroni adjusted significance level (.0167). *** p < .001.

Table 31. Summary of Hierarchical Regression Analysis for Idealism Predicting Social-Normative Motivation to Lead


1 See Table 23.

2 (Intercept) 31.38*** .21 30.96 31.80

Gendera 1.41*** .31 .14 .81 2.02

Idealism (centered) -.05* .02 -.07 -.09 -.01

Note. N = 1024. R2 = .02 for Step 1; ∆R2 = .01 for Step 2 (ps = .027). avs. female. *p < .05. ***p < .001.

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