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CEO selection performance: does board experience matter?

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CEO selection performance: does board experience matter?

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CEO SELECTION PERFORMANCE:
DOES BOARD EXPERIENCE MATTER?

by
Jie Tian

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BUSINESS ADMINISTRATION)

May 2008

Copyright 2008 Jie Tian
ii
ACKNOWLEDGEMENTS
This dissertation would not have been finished without all the insightful advice,
thoughtful encouragement, and kind support from my adviser, Professor Nandini
Rajagopalan. I want to thank her from the bottom of my heart for being the most
inspiring mentor I have ever had and for showing me what it means to be a good scholar
and a good person. I am also grateful to Professor Tom Cummings for his kindness and
superb sense of humor, to Professor Kyle Mayer for his constructive comments, and to
Professor Cheng Hsiao for his patience. Professor John Haleblian gave me valuable
suggestions and tremendous help while I was working on this dissertation and I want to
thank him for that. My thanks go to Professor Chung Ming Lau who provided very
helpful advice on my previous work along this line of research. This dissertation is
dedicated to my mother who knows probably less than two percent about my work and to
my little sister who disagrees with about eighty percent of whatever I say but whom I
know I can count on anytime. And my best friend, Sophia Wang. I cannot thank her
enough for all the moral and emotional support she has given me over years (and for all
the money she has spent on our numerous long distance phone calls). Without her I
wouldn’t be able to see the “big picture” and turn to a new page of my life. These
wonderful people have made this work possible and I thank all of you so very much.

iii
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii

LIST OF TABLES v

LIST OF FIGURES vi

ABSTRACT vii

Chapter 1. INTRODUCTION 1

Chapter 2. LITERATURE REVIEW 10
2.1 Value-in-Specificity Hypothesis: RBV Perspective 14
2.2 Value-in-Specificity Hypothesis: Learning Perspective 20
2.3 Value-in-Diversity Hypothesis: Upper Echelon Perspective 30
2.4 Board Experience in Existing Literature 38
2.5 Summary 43

Chapter 3. THEORY AND HYPOTHESES 44
3.1 Types of Board Experience 44
3.2 Board Experience and CEO Selection Performance 51
3.3 Experience Effects and Industry Instability 68
3.4 Experience Effect and Past Performance 74

Chapter 4. RESEARCH METHODS 79
4.1 Sample and Data Sources 79
4.2 Variable Measurement 81
4.3 Data Analysis 93

Chapter 5. RESULTS 95
5.1 Event Study Results 95
5.2 Regression Results 100

iv
Chapter 6. DISCUSSION AND CONCLUSION 124
6.1 Summary of Key Findings 124
6.2 Contributions 131
6.3 Limitations 141
6.4 Future Research 142
6.5 Conclusion 145

REFERENCES 146

v
LIST OF TABLES
Table 1. Comparison of Three Theories on Managerial Experience 11
Table 2. Sample Distributions 97
Table 3. Stock Market Reactions to New CEO Appointment Announcements 98
Table 4. Mean, Standard Deviation, and Correlation 101
Table 5. Board Experience and CARs, Industry Instability as Moderator 105
Table 6. Board Experience and Post-Succession Performance, Industry Instability as
Moderator 107

Table 7. Board Experience and CARs, Prior Performance as Moderator 117
Table 8. Board Experience and Post-Succession Performance, Prior Performance as
Moderator 119

Table 9. Summary of Hypothesis Testing Results 123

vi
LIST OF FIGURES
Figure 1. Effects of Board Experience on CEO Selection Performance 50
Figure 2. Interaction between CEO Experience and Industry Instability 113
Figure 3. Interaction between CEO Experience and Prior Performance 121
Figure 4. Interaction between Industry Experience and Prior Performance 122
Figure 5. Interaction between Task Experience and Prior Performance 122
vii
ABSTRACT
Previous studies have emphasized that independent boards of directors with formal power
and financial incentives should be an effective monitoring mechanism. Research on board
independence, however, has largely overlooked the possibility that independent directors
may differ from one another in terms of work experience that they have acquired from
their primary occupations and from serving on the focal firm’s board of directors. This
dissertation research aims to examine the effects of board experience at multiple levels
(task, job, team, firm, and industry) on firm performance in the context of CEO
selection – one of the most important decisions that a board of directors makes. Drawing
upon the resource-based view of the firm, learning theory, and the upper echelon
perspective, I argue that boards of directors are likely to make better CEO selection
decisions when independent directors have worked as CEOs themselves and have
experience of working together on the focal firm’s board. Experience of working in the
firm’s primary industry and experience with the task of hiring a CEO also help improve
board effectiveness in CEO selection. Effects of board experience were examined in a
sample of 242 new CEO appointments that occurred in 226 large, publicly traded U.S.
manufacturing firms from 1999 to 2003. I examined both stock price reactions to the
announcements of new CEO selection and post-succession accounting performance of the
firm. Results show that, after controlling for the effects of board independence,
succession event characteristics, and other organizational / environmental factors, board
experience explained a substantial proportion of variances in stock and accounting
performance. Moreover, industry instability and firm performance prior to CEO
succession were found to moderate the effects of various types of board experience.
viii
Overall, board experience had a positive impact not only on stock market investors’
expectations for future firm value but also on realized post-succession firm performance.
In response to the increasing attention to board accountability for significant
organizational decisions, this study shows that context-specific, history-dependent work
experience of directors is the key to understanding board effectiveness in CEO selection.
The findings also have important implications for director selection practices.
1
CHAPTER 1
INTRODUCTION
The board of directors plays important roles in a public corporation through its
interactions with the CEO and the top management team (TMT). Previous researchers
have identified three key roles of the board -- monitoring, providing resources, and
strategic advice (see Daily, Johnson, & Dalton, 1999; Dalton, Daily, Ellstrand, & Johnson,
1998; Johnson, Daily, & Ellstrand, 1996; Zahra & Pearce, 1989 for reviews of the boards
of directors research). Monitoring role refers to the board’s responsibility for ensuring
that managers make decisions in the interests of shareholders. Resource role suggests that
the board is a source of critical resources and a linkage mechanism between the company
and its external environment. Strategy role suggests that board members provide strategic
advice and counsel to firm management based on their information, experience and
expertise (Hillman & Dalziel, 2003).

Boards of directors and their influence over organizational decisions have been an
important topic in the academic literature as well as in popular business press. The factors
determining board effectiveness in the above-mentioned roles have been examined in
different tasks that the board is supposed to perform, e.g., hiring a CEO, setting a
compensation package for the CEO, evaluating CEO performance, planning for CEO
succession, or firing a poorly-performing CEO where necessary. Over years various
theories have been developed and tested; however, researchers have not yet been able to
identify a set of factors that consistently predict board effectiveness. Intuitively, as
suggested in many practitioner-oriented, qualitative studies, the board is more likely to
2
make better decisions if it has greater power, better knowledge and information about the
firm and is more motivated to perform its roles (Conger, Finegold, & Lawler, 1998).
Power, motivation, knowledge and information should all be “critical success factors” for
a top decision-making group such as the board of directors. But these factors have
received different degrees of attention in the academic literature. Motivation and power
issues have been discussed much more often than knowledge and information that is
gained through individual and group learning experiences. Agency theory, one of the
most influential perspectives in the board research, places a special emphasis on the
means of improving board power and motivation. This theory suggests that independent
directors are more powerful and motivated than inside and affiliated directors. The
former tend to be more objective in evaluating CEO performance and less susceptible to
CEO influence, which makes them better monitors than the latter (Eisenhardt, 1989a).
Moreover, board independence can be established by carefully “designing” board
structure. The desired structural attributes include a separate leadership structure under
which the board chairperson and the CEO are different individuals, high ratios of
independent outside directors, and high levels of directors’ stock ownership, to name just
a few. The argument for board independence is based on the assumption that the board is
at an inevitable informational disadvantage relative to the CEO and it can do not much
more than controlling the “outcomes” of managerial actions by setting performance-
based CEO compensation (ex ante control) or dismissing the CEO when organizational
performance declines (ex post control) (Walsh & Seward, 1990). What has largely been
ignored is that, given the same level of power / motivation, some directors may have
3
more relevant experience, knowledge, and information and may be better able to perform
their roles.

The independence criterion has greatly influenced board practices in large public
corporations in the United States (Pound, 2000). Over the past three decades, corporate
boards have become more and more similar to one another in terms of outsider ratio,
leadership structure, board incentive plans and other “design” attributes. Yet, the links
between increased board independence and board effectiveness are not as clear or as
compelling as agency theorists predict. The fact that some large corporations involved in
recent financial scandals had substantially independent boards of directors only adds to
the confusion (Lavelle, 2002). Many corporate governance observers have noted that
some independent directors are not as effective as expected because they do not have the
needed experience and expertise to carry out their duties (e.g., the duty of hiring a
competent CEO) (Bianco & Bryrne, 1997; Lorsch, 1995). Given the complex nature of
typical board decisions, it should be reasonable to require directors to understand the
focal firm’s businesses. As Conger and Lawler (2003) noted, the key question about an
effective director is as follows: “Does the director have an adequate understanding of the
company’s strategies, industries, markets, competitors, financials, operating issues,
regulatory concerns, technology, and general trends?” Considering this question and the
fact that board power and incentive arrangements have failed to guarantee board
effectiveness in many situations, it is time for us to look beyond power and motivation
and search for the experience factors that underline performance differences across
corporate boards of directors.
4
In addition to the lack of attention to experience-based determinants of board
effectiveness, another limitation of the prior research is that board effectiveness has been
measured as bottom-line organizational performance in many studies. In the “real world”,
however, the board is likely to influence firm performance only indirectly through the
decisions it makes and through its interactions with the CEO. To better understand what
make some corporate boards more effective than others, we first need to define and
measure the concept of board effectiveness within the context of specific board tasks /
decisions (Forbes & Milliken, 1999). Finally, although theories differ in their predictions
about desired board attributes (e.g., size, leadership structure, membership composition,
and directors’ characteristics), the same attributes have been associated with different
roles in many studies. For example, the proportion of outside directors has been used as
an indicator of both the board’s monitoring ability (Singh & Harianto, 1989) and its
resource-providing ability (Pearce & Zahra, 1992). The proportion of insiders has been
used as a measure of the board’s lack of independence (Cochran, Wood, & Jones, 1985)
and the board’s possession of firm-specific knowledge (Baysinger, Kosnik, & Turk,
1991). These kinds of mismatches between operationalizations and theoretical concepts
make it difficult to isolate the underlying reasons for observed empirical associations
(Daily et al., 1999).

To address these problems and limitations, we need a theoretical model that
systematically examines the factors determining board effectiveness within a specific task
context and based on valid operationalizations of theoretical constructs. This dissertation
develops a model that meets these requirements. My primary purpose is to investigate the
5
associations between directors’ career experience, measured at different levels, and
organizational performance within the context of CEO selection. I argue that, controlling
for the effects of board power and motivation, board experience should have a significant
impact on board effectiveness. With a focus on CEO selection, this study aims to answer
two questions: (1) How do different types of board experience influence firm
performance in the context of CEO selection? and (2) Are the effects of board experience
contingent on critical internal and external contextual factors? Board effectiveness should
be a function of individual directors’ learning experiences obtained both from their work
inside the focal firm (on the board) and from their work outside the focal firm (in their
primary jobs). In this study, I further argue that an analysis of director experience is
particularly needed for the subgroup of independent directors because it would help us
isolate the effects of experience on performance over and above those of board
independence.

This study also develops a classification scheme of board experience relevant to the task
of hiring a CEO. Drawing upon several theoretical perspectives that address the role of
experience in improving individual / group task performance and firm performance [the
resource-based view of the firm (RBV), the learning perspective, and the upper echelon
perspective (UEP)], I propose that board experience can be classified into four types that
form a hierarchy along the dimension of situational specificity: task experience
(directors’ previous experience with the task of hiring a CEO), job experience or CEO
experience as labeled hereafter (directors’ work experience as CEOs of other companies),
group co-working experience (experience of working together on the focal board), and
6
industry experience of working in the focal firm’s primary industry. This categorization
leads to three general arguments. First, consistent with the RBV and learning theory, I
argue that the level of these four types of context-specific experience should be positively
associated with CEO selection performance, defined both as cumulative abnormal stock
returns(CARs) surrounding the announcement of new CEO appointment and as the firm’s
post-succession financial performance. Second, directors bring to the focal firm diverse
experiences that they have acquired while serving as CEOs of other companies or while
working in different industries. In line with the UEP, I argue that diversity of CEO
experience and industry experience affects the degree to which the board can develop a
holistic understanding of the job requirements for the new CEO. Third, the effects of
board experience are likely to be contingent on the firm’s internal and external strategic
context. In particular, pre-succession organizational performance and industry instability
may moderate the relationships between board experience and CEO selection
performance.

This dissertation extends the research on boards of directors in several ways. A major
contribution of this study is that board effectiveness is examined in the context of a
crucial board task. Hiring a CEO is arguably the most important decision that a board
makes. Researchers have been debating over how much the boards are or should be
involved in other strategic decisions and how much the boards can directly affect firm
performance, but there should be little disagreement on the board’s primary responsibility
when it comes to hiring the CEO. Other things being equal, corporate boards are perhaps
involved in the process of CEO selection more actively and more deeply than they are
7
involved in any other strategic decision. In their study on CEO turnover, Huson and
colleagues (2004) argued that focusing on performance changes around turnover
decisions helps to isolate a specific corporate event in which a board decision potentially
has a significant impact on future firm value. For my purpose, CEO selection provides an
ideal empirical setting for studying the performance effect of board experience. Prior
research on CEOs and TMTs has also shown that the CEO does have a significant impact
on organizational strategy and performance. This logically leads to the argument that if
the CEO matters, then who hired him/her in the first place should also matter. The board
may influence organizational outcomes through its CEO selection decision – the present
study offers an empirical test of this possibility.

This study also provides a multifaceted, theory-based, and context-specific typology of
board experience. Based on a comprehensive literature review, this study identifies the
types of board experience that are crucial for effectively performing the task of CEO
selection. The classification scheme developed here is consistent with previous efforts to
classify general work experience (Quinones, Ford, & Teachout, 1995; Tesluk & Jacobs,
1998) and executive career experience (Castanias & Helfat, 1991). The focus is on direct
experience with the task of hiring a CEO, experience with the problem domain (i.e., the
CEO’s job), experience accumulated within the organizational and industrial contexts,
and experience of working with the same group members (i.e., co-working experience).
To the best of my knowledge, this is the first study that systematically operationalizes
these theoretical domains of board experience.

8
In this study, the extensive previous work on the experience-performance relationship is
integrated into two distinct views. One is labeled the “value-in-specificity” hypothesis.
Mainly grounded in the RBV and learning literatures, this hypothesis suggests that
learning-by-doing task experience and group co-working experience help to improve
individual and group information processing capacities. Moreover, path-dependent and
situation-specific experience can be a value-creating resource for the firm. The other
view, labeled the “value-in-diversity hypothesis,” is generally consistent with the UEP
and suggests that complex decisions require the board to have diverse experiences and
perspectives. I argue that the two general hypotheses are not necessarily exclusive from
each other. They emphasize different aspects of experience and can be combined to
provide a more complete understanding of the performance effect of board experience.

I provide a systematic analysis about how different types of board experience affect CEO
selection performance. Taking a step further from most previous studies, this study
defines CEO selection performance in two ways: Board experience is linked to both stock
market reactions to new CEO appointments (stock performance) and post-succession
accounting performance. I argue that board experience has an impact on investors’
expectations for future firm value at the time when a new CEO is hired. It is also likely to
influence the long-term outcomes of CEO succession. By comparing the experience
effects on both performance measures, we will have a clearer understanding of whether
or not the stock market “makes the correct predictions” when new CEOs are hired.

9
Independent directors’ lack of firm- and industry-specific knowledge has attracted
increasing attention from policy makers, academic scholars, and business practitioners.
The popular belief that board structural independence guarantees effective corporate
governance needs to be reexamined with an effort to incorporate differences among
independent directors in terms of experience and knowledge. Research has shown that
career experiences of independent directors do affect investor expectations when the
directors are appointed to a corporate board (Brickley, Linck, & Coles, 1999; Fich, 2005).
But we know little about how these directors make decisions after they join the board and
how their experience affects organizational performance. The present study fills this gap
and helps up better understand the value-creating effect of board experience.

The rest of this dissertation is organized as follows. Chapter 2 reviews the three
theoretical perspectives that lay the foundation for this study – the RBV, learning theory,
and the UEP. This chapter also reviews some studies that address the impact of executive
and director experience on organizational strategy and performance. Chapter 3 presents
the theoretical model about how board experience affects CEO selection performance.
Research methods and results are presented in Chapter 4 and 5 respectively. Chapter 6
summarizes key findings and discusses the contributions, limitations, and implications of
this study.

10
CHAPTER 2
LITERATURE REVIEW
To date there has been little theoretical and empirical work systematically examining how
experience influences effectiveness of the board of directors as a decision-making group.
Fortunately, the strategy literature has offered several theoretical approaches to
investigating the general performance implications of group experience, knowledge, and
skills. This study is particularly informed by three theoretical approaches – the resource-
based view of the firm (RBV) (Barney, 1986, 1991; Conner, 1991; Dierickx & Cool,
1989; Penrose, 1959; Peteraf, 1993; Rumelt, 1983), the learning perspective (Fiol &
Lyles, 1985; Huber, 1991; Reagans, Argote, & Brooks, 2005), and the upper echelon
perspective (UEP) (Finkelstein & Hambrick, 1996; Hambrick & Mason, 1984).

Table 1 compares the three perspectives along several dimensions. At the outset, note that
all three theories share the same behavioral assumption. That is, individuals are
boundedly rational and have limited cognitive capacities to notice, collect, code, store,
recall, and interpret information. Consequently, they tend to make suboptimal decisions
(Cyert & March, 1963). However, after this starting point, these theories seem to diverge
and follow distinct paths in reaching different solutions to the bounded rationality
problem. The RBV / learning solution can be seen as resting with a “value-in-specificity”
hypothesis. It suggests that managerial experience and knowledge developed within
specific contexts over time can be a strategic resource that leads to persistent
performance heterogeneity. Thus, making the best use of your own context-specific

11
Table 1. Comparison of Three Theories on Managerial Experience
Resource-Based View Learning Theory Upper Echelon Perspective
Behavioral assumption • Bounded rationality • Bounded rationality • Bounded rationality
Level of analysis • Firm • Individual
• Group
• (Firm)
• Group
• Firm
Type of experience • Firm-specific
• Industry-specific
• Generic
• Task-specific
• Group-specific
• (Firm-specific)
• Functional
• Educational
• Firm
• Industry
Temporal vs. spatial
pattern
• Historical accumulation • Historical accumulation
• Spatial distribution – level (central
tendency)
• Spatial distribution -- diversity
Desired characteristics
of experience
• Valuable
• Rare
• Inimitable (history-dependent,
causally ambiguous, socially
complex)
• No substitutes
Æ value-in-specificity
• Routine-based
• History-dependent
• Causally ambiguous
Æ value-in-specificity
• Heterogeneous
• Comprehensive
Æ value-in-diversity
Key learning process • Learning by doing • Learning by doing
• Information sharing
• Information sharing

Key argument • Previous experience determines
future directions
• Direct experience and related
experience are associated with good
performance
• Expertise and information
processing capacity increase as
experience increases
• Group co-working experience leads
to TMS, which in turn, improves
performance
• Experience diversity is associated
with high decision quality and
hence better firm performance

12
experience, making it difficult for outsiders to understand the cause-effect logic
underlying your decisions and thereby creating “cognitive barriers” to your rivals would
be the best strategy for maintaining sustained competitive advantage. This argument finds
support in Wernerfelt’s (1984) early paper on the RBV: “What a firm wants is to create a
situation where its own resource position directly or indirectly makes it more difficult for
others to catch up” (pp. 173). By contrast, the UEP proposes a “value-in-diversity”
hypothesis, which suggests that a team makes more comprehensive, better informed
decisions if team members have diverse functional, educational, organizational, and/or
industrial experiences (Hambrick et al., 1984). Therefore, the UEP focuses on the
mechanisms that help decision makers overcome their own “cognitive limitations” and
that help them approach the “optimal” decision.

As shown in Table 1, the differences among the three theories can be seen in several
aspects. First, while the RBV generally involves a firm-level analysis of resource
endowments and the UEP has mostly been used to explain group-level diversity and its
effect on organizational outcomes, the learning perspective explains the experience-
performance relation at both individual and group levels. The learning perspective and
the UEP involve cross-level analysis by linking individual / group experience to higher-
level performance outcomes. Second, the three theories define experience in different
ways. For the RBV, the key is where experience has been learned and applied. Thus,
“spatial boundaries” become a critical dimension and the distinction is made among firm-
specific, industry-specific, and generic experience. While the RBV treats the firm as the
13
unit of analysis, the learning perspective adds another level to the hierarchy of context-
specific experience, i.e., group experience. Both the RBV and the learning perspective
concern the degree to which experience gained from one social context can be useful in
another social context. In addition to the where issue, the UEP literature also emphasizes
what the experience is about. It then defines experience in terms of functional domains
(e.g., finance, accounting, law, operations, production, marketing, and so on) and focuses
on whether or not group members have all kinds of specific experience needed for
making a good decision.

Third, one may argue that the value-in-specificity hypothesis emphasizes the temporal /
historical patterns of experience accumulation, whereas the value-in-diversity hypothesis
highlights the structure and composition of the decision-making team, which in turn,
reflect spatial distribution of experience among team members. Fourth, as will be
discussed in greater detail next, the RBV and the learning perspective share some
common descriptions about the desired characteristics of experience. Both recognize the
path-dependent nature of experience, and the RBV further explains what conditions a
resource must meet in order to become a rent-creating resource. By contrast, the UEP
places more emphasis on the distribution of experience rather than on the characteristics
of each type of experience.

Finally, the three theories emphasize different learning processes. The RBV attaches
particular value to the notion of learning by doing. Learning from others is assumed to be
very difficult, if not impossible, due to causal ambiguity and inimitability of experience
14
(Barney, 1991). But in the learning literature we have seen more discussion about sharing
information, knowledge, and expertise among organizational members. Group task
performance depends not only on the types of individual experience but also on the
abilities of group members to share their experiences with one another. This sharing
element is also a major concern in the UEP literature for many UEP-based studies are
intended to ascertain to what degree diversity facilitates group sharing. This is not to say
that the RBV never addresses the sharing issue or the UEP never touches on the
importance of individual experience, but the theories do emphasize different aspects of
experience.

2.1 Value-in-Specificity Hypothesis: RBV Perspective
2.1.1 Value of Firm-Specific Resources: Overview
The RBV is arguably one of the dominant theoretical views in strategic management
today (Stieglitz & Heine, 2007). This theory focuses on a crucial question: Why do some
firms consistently perform better than others? It is argued that performance heterogeneity
arises from resource heterogeneity. Penrose, who has been regarded as a pioneer in the
resource-based thinking, argued that: “It is the heterogeneity … of the productive
services available or potentially available from its resources that gives each firm its
unique character” (Penrose, 1959: 75). The RBV assumes that firms are “bundles of
resources” and resources are defined as “all assets, capabilities, organizational processes,
firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to
conceive of and implement strategies that improve its efficiency and effectiveness”
(Barney, 1991: 101). Barney (1986) argued that firms are likely to achieve superior
15
performance if they own physical capital, human capital, and organizational capital
resources that have four features: (1) they must be valuable in the sense that they
facilitate the exploitation of environmental opportunities and help reduce environmental
uncertainty; (2) they must be rare among a firm’s current and potential competitors; (3)
they must imperfectly imitable, and (4) there cannot be strategically equivalent substitutes
for these resources.

Specifically, a resource is valuable when it helps the firm achieve the fit among various
organizational conditions (strategy, structure, and processes) and the fit between the
firm’s internal conditions and external environments. Moreover, valuable resources must
have some additional attributes if they are to generate sustained competitive advantage.
The first such attribute is rareness. Although the ideal scenario of rareness is that the firm
owns an absolutely unique resource among a group of current and potential competitors,
the rareness condition is met as long as the number of resource owners is less than the
number of firms needed to generate perfect competition dynamics in an industry.

Moreover, rent-generating resources must be inimitable. Valuable and rare resources may
give a firm first-mover advantage, but it is imperfectly imitable resources that are the
source of sustained competitive advantage. These resources are developed under specific
historical and situational conditions, which have been widely discussed in the RBV
literature (Barney, 1991; Dierickx et al., 1989; Lippman & Rumelt, 1982; Mahoney &
Prandian, 1992). The first condition that characterizes inimitable resources is historical
dependency or path dependency. The RBV suggests that firms are intrinsically historical
16
and social entities and their ability to acquire and exploit some resources depends on their
place in time and space. Other firms that do not have the focal firm’s unique historical
conditions will not be able to reproduce the resources owned by the focal firm. The
second condition is causal ambiguity, which can be directly linked to the bounded
rationality assumption. Resources are causally ambiguous if the relations between these
resources and a firm’s performance are not perfectly understood by outsiders. Causal
ambiguity prevents competitors from imitating the firm’s actions. But this is only one
side of the story. The RBV suggests that for a resource to be a source of sustained
competitive advantage, neither its owner nor the competing firms have perfect
understanding of the link between the resource and performance. In other words, it is
causal ambiguity on both sides (the owner of the resource and the potential competitors)
that guarantees sustained competitive advantage. This notion has also been captured in
the knowledge-based view of the firm that emphasizes the strategic importance of tacit,
situation-specific knowledge (Grant, 1996; Kogut & Zander, 1992). The third reason why
some resources cannot be perfectly imitated is that resource development and deployment
are very complex social phenomena. Social complexity can be found in many types of
resources, e.g., interactions among top management team members (Hambrick et al.,
1984), R&D capacity (Cohen & Levinthal, 1990), organizational culture (Frank &
Fahrbach, 1999), and so on. Again, socially complex resources are context-specific. The
competitors are unlikely to copy the entire social system that supports the creation and
maintenance of the resources. A related notion is interconnectedness of resources.
According to Dierickx and Cool (1989), accumulating increments in an existing resource
oftentimes depends not only on the level of that resource, but also on the level of other
17
resources. This interconnectedness makes it very costly, if not impossible, for other firms
to recreate the focal firm’s resource base. Taken together, hard-to-imitate resources must
be history-dependent, causally ambiguous, and/or socially complex – conditions that vary
among firms. Therefore, firm specificity of resources is a key determinant of high
performance.

In addition to value, rareness, and imitability, the fourth feature of rent-creating resources
is the lack of substitutes. For a resource to become the source of sustained competitive
advantage, it must not have strategically equivalent substitutes. This means that the
success of the strategy can only be achieved with this set of resources. No similar
resources can be found to replace them. No different resources can be used to replace
them, either. The lack of substitutes means that the resources must be idiosyncratic to the
firm, as suggested in the value-in-specificity hypothesis. Overall, the RBV suggests that
firms can achieve persistent better performance than their peers if they possess bundles of
valuable, rare, inimitable resources (tangible and intangible) that have no substitutes.

Given the characteristics of rent-generating resources, the RBV suggests that the firm’s
future strategic actions are determined by its current resource base (Barney, 1991). The
relations between path-dependent resources / learning experiences and organizational
strategic actions have been examined in such areas as diversification (Lemelin, 1982;
MacDonald, 1985), merger and acquisition (Karim & Mitchell, 2000), strategic alliances
(Eisenhardt & Schoonhoven, 1996), and innovation and R&D activities (Geroski, Machin,
& Reenen, 1993). Evidence generally shows that a firm’s path of expansion is influenced
18
by its previous strategic experience and existing resource base. Other things being equal,
an expansion strategy characterized by relatedness and situational specificity would lead
to better performance.

In recent years, some researchers have suggested that the RBV’s focus on internal
resources should be complemented by an external environmental focus because the value
of a resource is likely to be influenced by the environmental context within which it is
deployed (Miller & Shamsie, 1996). For example, Hult, Ketchen, and Arrfelt (2007)
examined the relations between two types of intangible resources (a culture of
competitiveness in the knowledge creation process and knowledge development ability)
and supply chain management success. They found a stronger positive relation between
culture of competitiveness and supply chain management success under conditions of
higher market turbulence, indicating that knowledge creation was more important in a
turbulent environment. Environmental uncertainty is also a key contingency factor in
Miller and Shamsie’s study (1996). These authors drew distinctions between two types of
resources: property-based resources that are controlled by a firm by virtue of property
rights and knowledge-based resources that cannot be imitated by virtue of the conditions
described in the RBV. While property-based resources are likely to contribute most to
firm performance in stable environments, knowledge-based resources will be of the
greatest utility in unstable environments. The contingency logic has also been used to
examine if the “match” between firm strategy and certain types of resources will lead to
better organizational performance (e.g., Christmann, 2000; Hitt, Bierman, Shimizu, &
Kochhar, 2001; Mishina, Pollock, & Porac, 2004). Overall, the contingency-based RBV
19
aims to identify the critical environmental and organizational conditions under which
certain types of resources contribute most to firm performance than others.

2.1.2 Managerial Experience as Specific Resource
Based on the general argument that firm-specific resources create sustained competitive
advantage, researchers have also examined the role of top decision makers’ experience
and knowledge in integrating various types of organizational resources into a coherent
system (Amit & Schoemaker, 1993). As a rent-generating resource, experience and
knowledge has a special feature. That is, it is possessed by individuals who can move
from employer to employer on the labor market. Experience learned in one organization
may not be useful in another organization. This “context specificity” is a key dimension
of the typology of managerial resources developed by Castanias and Helfat (1991).
According to these authors, context specificity influences the value of an individual’s
human capital (skills, experience, and knowledge) as perceived by his or her current
employer and potential employers on the labor market. There are three types of
managerial human capital: (1) generic human capital that is valuable in different firms
and industries, (2) industry-specific human capital that has value only in a certain
industry, and (3) firm-specific human capital that has value only within a firm. All the
three types of managerial human capital are rent-generating resources because their
supply is limited. Firm- and industry-specific managerial skills also generate quasi-rents,
defined as the difference between the value of a resource in its first best use and its value
in its next best use, because these skills matter more for the focal firm / industry than for
other firms / industries. More important, these rents will tend to be inimitable and
20
persistent over time because the accumulation of managerial skills follows no clear
blueprint and involves a good deal of learning by doing. Managerial experience is
obtained within a specific context and more useful in guiding future behaviors within the
same context. Even if a competitor could “raid” experienced managers from the focal
firm, the managers might not be able to do as good a job in the new firm where they have
to use their skills “out of context.”

In brief, the RBV proposes an economic explanation for why top managers’ work
experience can be a resource for the firm. The learning approach reviewed below, in
comparison, offers a cognitive explanation why direct experience with a job improves
information processing capacity and decision quality. And this learning benefit can be
analyzed at both individual and group levels.

2.2 Value-in-Specificity Hypothesis: Learning Perspective
Consistent with the RBV, learning theory explains how situation-specific, history-
dependent experience improves individual and group task performance. In their review
article, Fiol and Lyles (1985) defined learning as “the process of improving actions
through better knowledge and understanding” (pp. 803), indicating a direct link between
learning outcomes and previous experience (as source of knowledge and expertise). This
link is more obvious in Levitt and March’s conceptualization of learning (1988). These
authors suggested that organizations learn by encoding inferences from history into
routines that guide behavior. By linking individual learning experience to organizational
21
routines and processes, the learning approach offers a micro-level explanation why these
routines / processes become inimitable, causally ambiguous resources.

Experience is an important source of work expertise and knowledge, which in turn,
contributes to work performance (Tesluk et al., 1998). Although secondary sources such
as books can impart knowledge relevant to managerial tasks, managers probably learn
even more in their day-to-day work. An effective manager needs to know how to
communicate with organizational members and relevant external stakeholders, and how
to encourage subordinates to work for the organizational objectives. He or she must also
be a good “coordinator” who knows how to integrate expertise and views of other
organizational members. All these roles require of the manager a tacit understanding of
the organization and its members. Therefore, direct participation in managerial tasks and
learning-by-doing experience has a significant impact on a manager’s job ability.

Several streams of research have been devoted to reveal how direct experience affects job
ability and performance. One is the experience curve research that has mostly been
conducted in manufacturing settings. Studies have documented a positive relation
between accumulated task experience and productivity (Levitt & March, 1988). Parallel
with this work is the expert / novice research that compares job performance of experts
and novices in more complex decision tasks. Typically an expert refers to an individual
who has specific skills or knowledge derived from training or work experience (Bedard,
1989). Experts and novices tend to display different information processing and decision
making styles. This is because experience enhances knowledge by improving the way
22
events are recorded into memory and the way linkages between the events and pre-
existing knowledge are established. It has been reported that experts are able to
categorize decision problems and task information with respect to abstract underlying
principles. By contrast, novices often organize facts based on their surface features
(Rentsch, Heffner, & Duffy, 1994). Moreover, experience accumulation and knowledge
acquisition is a dynamic process. An individual’s ability to acquire new knowledge
depends on the breadth of conceptual categories into which prior knowledge is organized,
the differentiation of those categories, and the linkages across them (Bower & Hilgard,
1981), implying that individuals who already have rich experience are in a better position
to acquire and understand new knowledge. Compared with novices, experts are also more
likely to notice atypical patterns in task information which are critical for making correct
judgments (Choo & Trotman, 1991). Overall, experience contributes to both efficiency
and effectiveness of information processing by enabling individuals to quickly “see
through” the surface facts and find the underlying cause-effect relations.

Context-specific experience also contributes to task performance. High knowledge
individuals were found to take less effort to search for information when tasks were well-
structured and, regardless of task structure, high knowledge individuals were able to
acquire considerably more contextual information than were low knowledge individuals
(Devine & Kozlowski, 1995). In relation to the board of directors, some studies on board
audit committees have reported a positive relationship between experience with auditing
tasks and the quality of committee members’ decisions (DeZoort, Hermanson,
Archambeault, & Reed, 2002). DeZoort (1998) compared performance on an internal
23
control oversight task between 87 audit committee members and a group of external
auditors. The results show that directors with general domain (auditing) and task specific
(internal control evaluation) experience made internal control judgments more like
external auditors than directors without such experience. Experienced audit committee
members also made more consistent judgments, had higher self-insight, higher consensus,
and higher technical content levels for additional items offered. In another study, DeZoort
and Salterio (2001) examined how board audit committee members made judgments
when there were disputes between external auditors and firm management. A sample of
68 audit committee members completed an accounting policy dispute case and several
knowledge and ability tests. The results show that independent directors who had
financial- and audit-reporting knowledge were less likely to “side with the management”
but more likely to support an auditor’s decision, indicating that these experienced
independent directors were more effective monitors.

The third stream of research on the experience-performance link involves many studies
on group learning and information processing. It is believed that when a group of
individuals is brought together, each with his/her own work experience and expertise,
some kind of emergent collective knowledge is likely to exist (Walsh, 1995). An
important purpose of the group learning literature is to examine the types of group-level
experience, their antecedents and their performance implications. Essentially, group
performance depends on both the resources available to the group and the processes
utilized by the group (Hackman, 1987). The resource input refers to individual members’
experience, knowledge, and expertise brought to the decision task. This type of input has
24
much to do with how to perform a task and hence is labeled “task experience” (Littlepage,
Robison, & Reddington, 1997). But there is another type of experience that can only be
studied at the supra-individual level and can significantly influence a group’s task
performance. Littlepage and colleagues (1997) named this type of experience “group
experience.” It refers to experience of working with other group members. Both types
contribute to group performance but they affect performance in different ways. While
task experience is expected to increase the level of task ability of individual members,
group experience is expected to allow group members to more accurately judge the
expertise of other members. In a similar vein, Reagans, Argote, and Brooks (2005)
argued that the rate of organizational learning depends on the level of both individual task
experience and experience working together. The former influences the level of worker
proficiency and the latter is associated with group members’ abilities to use knowledge
accumulated by their colleagues. Experience of working together also improves group
members’ abilities to trust one another and coordinate their activities (Faraj & Sproull,
2000) and allows them to develop a clear understanding of the group’s rules, routines,
and norms – the so-called teamwork knowledge (Rentsch et al., 1994). All these authors
suggest that any examination of the experience-performance link should explore the
effects of both individual task experience and group co-working experience.

As more and more companies rely on teams to accomplish complex tasks, it is worth
taking a closer look at how various types of previous experience influence group
information processing (Hinsz, Tindale, & Vollrath, 1997). A big difference between
individual and group information processing is that the latter has a “share” element,
25
which may be analyzed both as “shared information” and a “sharing process” (Hinsz et
al., 1997). Shared information can relate to tasks at hand, characteristics of the group,
aspects of group members, the pattern of group interaction, or the context within which
the task, group, and its members exist. The sharing process describes how group
members notice, encode, store, retrieve, and use information. The two dimensions are
interdependent and group effectiveness varies as a function of both.

Hinsz et al. (1997) developed a generic information processing model to describe the
sharing process. This model starts from the attention phase in which group members
notice external information based on some processing objectives. The next phase is
encoding, which involves the structure and interpretation of information in groups. The
key issues here involve how individual representations of the information are combined
into a meaningful group representation and how this group “mental model” differs from
individual mental model in terms of complexity. Followed is the storage phase that plays
a central role in most information processing models. Groups tend to differ from
individuals in terms of information processing efficiency (how much information is
stored and how much time it takes to absorb the information) and information storage
“strategy.” Stored information must be retrieved before being used in the decision
process. Again, groups may memorize and recall information more accurately than
individuals because a group can draw on a number of different individual memories.
Moreover, group interactions may stimulate information recall and hence creating
synergistic productivity (Hackman, 1987). Finally, groups must combine and integrate
information in the processing phase during which various biases and heuristics may also
26
affect groups as they affect individuals. However, it has been generally found that groups
use information processing rules or strategies more reliably and consistently than
individuals do (Hinsz et al., 1997).

Note that in each of the above-mentioned information processing phase, the present state
of a group’s “shared information” affects the outcomes of that phase. Group-level shared
information has been studied under many concepts such as, among others, transactive
memory system (TMS) (Moreland & Myaskovsky, 2000; Wegner, 1987), mutual
knowledge (Cramton, 2001), team mental model (Klimoski & Mohammed, 1994),
collective cognition (Langfield-Smith, 1992), and dominant logic (Prahalad & Bettis,
1986). Research on such shared group knowledge is particularly important in two
situations: 1) when groups members’ special expertise or unique experiences provide
some members with access to information that others do not have, and 2) when not all the
information needed is available within the group and members have to work together to
find a solution based on their shared knowledge and past experiences (Rulke & Rau,
2000). Typically, corporate boards of directors are faced with such situations. On the one
hand, most individual directors are highly capable experts in certain areas, but not all of
them understand every aspect of the firm and its environments. On the other hand,
directors have to share information and coordinate their expertise in the decision-making
process. Therefore, the research on shared knowledge may shed light on our
understanding of board performance.

27
The concept of TMS is worth special attention here because it directly links group-level
knowledge to group members’ shared co-working experience and helps us understand
how task experience and group experience influence group performance simultaneously.
A TMS can be briefly described as knowledge about “who knows what” in the group.
Specifically, it is a shared system that people in close relationships develop for encoding,
storing, and retrieving information from different domains (Wegner, 1987), a form of
knowledge that is embedded in group members and in a group’s structure and processes
(Lewis, 2004). A TMS is a way of dividing “cognitive labor” among group members.
The basic idea is that individuals develop “an implicit structure for assigning
responsibility for information based on their shared conception of one another’s
expertise” (Brandon & Hollingshead, 2004: 633).

A TMS, once developed, allows group members to share two types of information: the
experience and expertise possessed by team members and an awareness of the location of
such expertise / experience within the team. Effective TMSs facilitate the allocation of
responsibility for obtaining, retaining, and communicating information when needed. The
influence of a TMS on group information processing has been documented in some
studies. In the encoding phase, it has been found that groups with established TMSs are
more likely to uncover individual members’ domains of expertise and “file” this
information with all members. Group members are more likely to assign each piece of
information to ensure that the expert(s) in a domain will receive the relevant information,
that every piece of information is filed under an agreed code, and that no information has
been missed. The influence of a TMS on encoding is also reflected in group members’
28
improved abilities to evaluate one another’s expertise and competence, which is
particularly important for groups that may not be able to meet face-to-face very often
(e.g., boards of directors). Similarly, in the recall phase, it has been found that groups
with an established TMS are more likely to recall unique information known to some but
not all group members (Stasser, Stewart, & Wittenbaum, 1995).

TMS can help mitigate the problem of information sharing bias in the group discussion
process. One often-studied bias is called a “hidden profile” problem, which occurs when
the total profile of information available to a group favors one decision alternative, but
the pattern of information seen by individual members prior to discussion favors another
(suboptimal) alternative (Stangor, Lynch, Duan, & Glass, 1992). In other words, group
members may have different information items and all items are needed to make an
accurate decision, but they tend to share common information and ignore the unique
information owned by only some members. This can be a serious problem when unshared
information plays a key role in improving decision accuracy. TMSs have been found to
reduce the negative effect of such information sharing biases by “cuing” group members
to seek information from those who are most likely to have it. Groups with established
TMSs tend to have lower cognitive load and higher abilities to see the connections among
all information items (Fraidin, 2004). Stasser (1985) found that group members were less
likely to be biased toward common information and more likely to recall unshared,
unique information when they were assigned to different expert roles (i.e., exposed to an
established TMS), which also supports the performance-enhancing effect of the
knowledge about who knows what.
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Researchers have also examined various conditions that facilitate the establishment of a
TMS. For example, Brandon and Hollingshead (2004) argued that cognitive
interdependence among group members, i.e., the degree to which group members rely on
one another to take responsibility for storing information, is a key prerequisite condition
for TMS development. Moreover, experience of working or training together has been
found to be an important initial condition for TMS development. Generally speaking, the
longer group members have been working or training together, the more they become
familiar with one another, the more likely a TMS is to emerge in this group. It has been
reported that TMSs may emerge as a result of training together (Liang, Moreland, &
Argote, 1995) or working together (Rentsch et al., 1994). Interestingly, in addition to
group experience, another factor that has been found to facilitate the establishment of a
TMS was found to be initial expertise distribution on the team. Lewis (2004) found that a
TMS was more likely to come into being when group members possessed diverse
expertise and when group members had been familiar with one another for a long time.
This finding is interesting because it points to one possible way how diverse experience
facilitates the creation of specific group experience in an initial stage. It was also found
that experience of working together was a significant driving force behind the TMS.
Team members who were familiar with one another were more likely to develop a TMS.
These findings are thought-provoking because they help us understand how specificity
and diversity actually work together to create a common knowledge within the group.

The performance consequences of group experience and TMS have also been widely
studied (e.g., Hollingshead, 1998; Liang et al., 1995; Moreland et al., 2000). Evidence
30
shows that group experience increases the likelihood that team members will accept the
correct solution proposed by a member (Laughlin & Hollingshead, 1995). In addition,
group experience on a related task increased group performance by facilitating
recognition and utilization of member expertise (Littlepage et al., 1997). Lewis (2004)
found a positive relation between a mature TMS (a TMS that focuses on implementation
or information retrieval) and performance of a knowledge-worker team. Recent studies
also show that a TMS not only improves performance in the task for which it first
developed but also helps members learn about similar tasks (Lewis, Lange, & Gillis,
2005).

Overall, at the individual level of analysis, the expert/novice research explains how
learning-by-doing task experience increases an expert’s information processing efficiency.
At the group level of analysis, research on TMSs shows how the distribution of specific
task experience among group members and the level of group co-working experience
(also a situation-specific experience) combine to create a group-level TMS that
“channels” group members’ diverse expertise into an coordinated decision process (Faraj
et al., 2000). In this sense, the learning approach emphasizes two types of learning:
learning by doing and information sharing (through a TMS).

2.3 Value-in-Diversity Hypothesis: Upper Echelon Perspective
Compared to the RBV and learning perspectives, the UEP is more in line with the value-
in-diversity hypothesis. This theory also assumes that individuals are boundedly rational
and complex decisions are largely the outcome of behavioral factors rather than a quest
31
for economic optimization. In their seminal paper on upper echelons (defined as the top
decision-making teams in an organization, including the TMT and the board), Hambrick
and Mason (1984) argued that strategic choices made by top executives and board
directors have a large behavioral component. The more complex the decision, the more
applicable the behavioral view of decision making is thought to be. It is in this sense that
these authors conceptualized organizational strategies and effectiveness as “reflections of
the values and cognitive bases of powerful actors in the organization” (pp. 193). Each
decision maker brings to a decision task his or her own set of “givens,” which reflects the
decision maker’s assumptions about future events, knowledge of alternatives, and
knowledge of consequences attached to alternatives. It is interesting to note how the
depiction of the decision market’s cognitive base in the UEP is different from that in the
RBV/learning literature. While the RBV and learning theorists view idiosyncratic
cognition as a potential source of competitive advantage, the UEP proponents compare
the decision makers’ “givens” against the rational model of decision making (thus the
terms assumptions, alternative options, and consequences attached to alternatives). With
a different “reference point”, the UEP generally sees an individual’s cognitive base as a
limitation rather than a potential resource. The sequential view of perceptual process
proposed by Hambrick and Mason (1984) further demonstrates the UEP assumption
about managerial cognition. In this view, cognitive base is described as a filtering lens
that distorts the decision maker’s perception of what is going on in the organization and
in the environment and what should be done about it:
The perceptual process can be conceptualized by taking a sequential view
(Hambrick & Snow, 1977). First, a manager, or event an entire team of managers,
cannot scan every aspect of the organization and its environment. The manager’s
32
field of vision – those areas to which attention is directed – is restricted, posing a
sharp limitation on eventual perceptions. Second, the manager’s perceptions are
further limited because one selectively perceives only some of the phenomena
included in the field of vision. Finally, the bits of information selected for
processing are interpreted through a filer woven by one’s cognitive base and
values. (Hambrick et al., 1984: 195, emphasis in original text)

Since limited cognitive base is posited as a “threat” to optimal decision making, it is not
surprising that many UEP-based studies have proposed that group diversity should have a
positive effect on the quality of group decisions. To understand the value-in-diversity
hypothesis, several issues need to be explained: (1) conceptualizations of diversity, (2)
types of diversity that matter for group decision performance, and (3) situational factors
that may moderate the diversity-performance relationship.

Hambrick and Mason’s initial analysis emphasizes the “amount of dispersion, or
heterogeneity, within a managerial group” (Hambrick et al., 1984: 202) and the effect of
group heterogeneity on decision quality without elaborating on what diversity means
exactly. The more general literature on work groups, from which the UEP has drawn
many important concepts and theoretical arguments, provides some guidelines about
theorizing and measuring group diversity. Most researchers define group diversity in
terms of demographic characteristics (age, sex, race, etc.) or career backgrounds
(functional background, educational background, job / firm / industry experience, etc.)
Tsui and Gutek (1999) identified three approaches to analyzing group diversity. An early
approach assumes that individuals in certain categories of demographic characteristics
(e.g., males) will have experiences at work that are different from others in a different
category (e.g., females). Since this approach typically compares attitudes and behaviors
33
of individuals in different demographic groups, it is labeled “categorical approach.” In
comparison, the “compositional approach” defines diversity as a structural property of a
group. Rather than focusing on a specific category or level, this approach focuses on
collective demographic profiles of groups and measures that reflect the entire spectrum of
the distribution of a demographic attribute. This approach has often been used to answer
such questions as “What is the relationship between different distributions of a
demographic attribute and group performance?” or “Do groups perform better or worse
with a different mix of functional backgrounds among members?” This approach defines
diversity as a group-level property and treats the effect of the group’s demographic
distribution to be the same for all individuals in the group. But it does not recognize that
two individuals with different demographic profiles but in the same group may have
different experiences in that group. This intra-group diversity is captured in the
“relational approach” that emphasizes an individual’s relationship to others in the group.
The basic premise of this approach is that the relationship of an individual’s own
demographic attributes to that of all the other members in a group will have an impact on
the individual’s experience in that group. It combines the emphases of both the
categorical approach and the compositional approach by capturing the diversity of
demographic attributes or backgrounds within a group (or between individual group
members). I argue the third conceptualization of diversity best corresponds to the
“expertise dispersion” notion in the TMS literature. One can argue that it is the relational
diversity among group members in terms of experience and expertise that creates various
information sharing situations.

34
The UEP has inspired numerous studies on the associations between the demographic
composition of TMTs / boards and organizational outcomes. Researchers have been
particularly interested in TMT diversity; however, the relation between diversity and firm
performance has turned out to be a complicated one. One the one hand, TMT diversity
has been linked with creativity, innovation, change, broad perspective, improved
cognitive resource, comprehensive decision making and good performance. For example,
it has been argued that the presence of people with different points of view ensures
consideration of a larger set of problems and a larger set of alternative solutions.
Therefore, diversity may have a positive impact on a firm’s innovative capacity.
Consistent with this view, Bantel and Jackson (1989) found a positive relation between
TMT functional background diversity and technical and administrative innovations in a
sample of banks. Ancona and Caldwell (1992) found that the higher functional
background diversity, the more communications with outsiders (e.g., marketing,
manufacturing, and management teams), the better performance of new product teams.
Eisenhardt and Schoonhoven (1990) reported a positive relation between TMT industry
tenure diversity and the growth rates of semi-conductor companies. TMT heterogeneity
was also found to have a positive relation with the firm’s stock market performance
(Murray, 1989).

On the other hand, diversity is said to cause interpersonal conflicts, a lack of cohesion,
slow decision speed, communication problems, misunderstanding between group
members, negative political activity and poor performance. For example, Smith et al.
(1994) argued that diverse teams will be less predictable in their attitudes and behaviors
35
because of goal and informational uncertainties among team members. They found a
negative relation between a composite measure of TMT heterogeneity (educational years,
team tenure, and functional background) and return on investments in a sample of 53
high-tech firms. O'Reilly, Snyder, and Boothe (1993) found that firm tenure
heterogeneity was negatively related to adaptive change in a sample of electronics firms.
Knight et al. (1999) looked at how TMT diversity affects team members’ strategic
consensus in 76 high-tech firms and found that both functional diversity and educational
diversity had a negative direct effect on consensus.

These contradictory findings suggest that group diversity is a “double-edged sword.”
However, given the unique features of the TMT and the board as strategic decision
making groups (e.g., highly capable individual members, complex decision tasks, and
time pressure), the benefits of group diversity cannot be underestimated. It is perhaps one
reason why the UEP suggests that group diversity may have a direct positive impact on
performance regardless of what happens in the group process.

Certainly the mixed findings with respect to the diversity-performance relation have not
gone unnoticed in the academic literature. Researchers have attempted to clarify this
issue mainly along two lines of thinking. One approach involves drawing distinctions
between different types of group diversity and then identifying the types that are relevant
to the research questions at hand. Diversity is always about some underlying individual
attribute. Studies on work groups in general and TMTs in particular have discussed
different types of diversity (e.g., Jackson, May, & Whitney, 1992; Milliken & Martins,
36
1996; Tsui, Egan, & O'Reilly, 1992). In response to the mixed findings about the
diversity-performance link, Jackson (1992) suggested that distinction should be drawn
between diversity of personal attributes such as race, gender, and personality and task-
related attributes (e.g., team tenure, firm tenure, industry tenure, functional background,
etc.). A similar argument was made by Milliken and Martins (1996), who used the terms
salient or readily detectable attributes versus job-related attributes. The distinction is
important because salient diversity is presumed to be more likely to lead to
sociopsychological reactions among group members such as social categorization
processes, social comparison, out-group/in-group judgments, and/or emotional conflicts
(Jehn, 1995; Pelled, 1996; Turner, 1985; Wagner, Pfeffer, & O'Reilly, 1984). When
differences among people are visible, they are especially likely to evoke responses that
are directly due to biases, prejudices, or stereotypes (Milliken et al., 1996). By contrast,
job-related diversity has often been associated with cognitive processes such as cognitive
diversity, debate, and task conflicts that eventually lead to high-quality decisions (Jehn,
1995; Kilduff, Angelmar, & Mehra, 2000; Simons, Pelled, & Smith, 1999). These
arguments imply that when the dependent variable has an attitudinal / psychological
component (e.g., job satisfaction, organizational commitment, or job turnover), group
diversity in terms of visible demographic characteristics may be a significant predictor.
However, job-related diversity may be more important than visible diversity when the
dependent variable has a cognitive component (e.g., information processing or decision
quality).

37
The other line of thinking can be described as a contingency-based approach that focuses
on identifying the contextual conditions under which certain types of diversity are more
closely associated with job performance than others. The main-effects model proposed in
Hambrick and Mason’s original paper has been contextualized by taking environmental,
organizational, and team-level contingencies into account. For example, Keck (1997)
studied TMTs in 56 cement and 18 minicomputer firms and found that TMT functional
heterogeneity was positively related to firm performance in the minicomputer firms,
whereas average TMT tenure was negatively related to firm performance. These findings
suggest that heterogeneity may be needed more in turbulent contexts (the minicomputer
industry) than in stable contexts (the cement industry). West and Schwenk (1996)
presented a contingency-based framework in which TMT homogeneity was assumed to
have a positive effect on firm performance in stable industry environments, but they did
not find any supportive evidence. Carpenter and Fredrickson (2001) argued that
environmental uncertainty should positively moderate the relation between TMT
diversity and a company’s global strategic posture. In support of this argument, they
found that environmental uncertainty positively moderated the curvilinear, U-shaped
relation between TMT educational diversity and global strategic posture. Organizational
strategy is also an important contextual factor. Evidence shows that the link between
TMT diversity and firm performance tends to be stronger in firms with higher levels of
internationalization (Carpenter, 2002). Some researchers focus on team-level moderators
rather than environmental- or organizational-level moderators. For example, Simons,
Pelled, and Smith (1999) reported that the effect of TMT diversity on firm performance
38
was moderated by debate – an interaction process among team member that helps
leverage the advantages of diversity.

In brief, the value-in-diversity hypothesis maintains that high levels of diversity in job-
related attributes will have a positive effect on team performance, and this effect tends to
be stronger when the task context is unstable and when the team has appropriate process
mechanisms that help enhance the benefits of diversity while reducing the costs of
diversity. Studies on TMTs largely support these arguments.

2.4 Board Experience in Existing Literature
Except for a few articles, there has been little systematic theoretical discussion, let alone
empirical studies, about board experience and its performance implications. Forbes and
Milliken (1999) drew upon group learning and information processing literature and
presented a conceptual model of board processes and their impacts on board effectiveness.
In their model, boards of directors are viewed as “large, elite, and episodic decision-
making groups that face complex tasks pertaining to strategic-issue processing” (pp. 492).
These authors suggested that boards require a high degree of specialized knowledge and
skills to function effectively. Moreover, distinction must be made between the presence
of knowledge and the use of knowledge and board effectiveness in control and service
roles depends on both. In terms of knowledge input, board members must have functional
area knowledge and skills that span the traditional domains of business as well as firm-
specific knowledge. Boards of directors will also be benefited from establishing some
39
“collective learning” and “cross-training” mechanisms that coordinate the use of
members’ expertise.

Similarly, human capital possessed by directors (including experience, expertise, and
reputation) is a key factor in Hillman and Dalziel’s theoretical model of board functions
(2003). These authors commented that agency theory does not pay enough attention to
the heterogeneity of monitoring ability among corporate boards:
The focus on incentives, however, overlooks the board’s ability to monitor.
Agency theorists have often employed measures of a board’s independence
without considering the heterogeneity of monitoring ability. If we compare the
monitoring ability of two boards, one dominated by outside independent directors
who are CEOs of Fortune 500 firms and the other dominated by outside,
independent, small local business representatives, we see the CEOs’ experience,
skills, and expertise are likely to make the former board more effective at
monitoring than the latter. (Hillman & Dalziel, 2003: 389)

They argued that boards with relevant experience and expertise may be better at both
providing resources and monitoring. In fact, board capital is positioned as a primary
determinant of monitoring and resource role effectiveness, which then leads to good firm
performance.

With the exception of these conceptual discussions, no empirical study has systematically
examined the performance effects of strategic decision makers’ career experiences. Some
studies in the finance and strategy literatures, however, do address the impact of
managerial ability / director experience in different ways. There have been two types of
studies. One group of studies examines stock price reactions to executive or director
turnover. The key question is whether or not individuals with certain types of career
40
experience are evaluated more favorably than those without experience. For example,
there has been some evidence that the market evaluates top executives according to their
abilities. Fee and Hadlock (2003) argued that there should be a positive relation between
firm performance and the likelihood that a manager moves to a superior position at
another firm. They identified every outside CEO hired by a sample of 2,196 large
publicly traded firms from 1990 to 1998. Consistent with their prediction, they found that
executives who jumped to CEO positions at new employers came from firms that
exhibited above-average stock price performance. This finding appeared to be stronger
for managers who jumped immediately from their old employer to the new employer, and
also for executives who were relatively more senior at their prior employer. Also
consistent with the managerial ability hypothesis, Hayes and Schaefer (1999) reported
that when executives left their employers to accept high-level positions elsewhere, the
average market reaction to the job change was negative for the firms the executives left
and positive for the firmed they joined.

The hypothesis that job ability matters has also been tested in the context of director
selection. Brickley, Linck, and Coles (1999) examined the factors determining CEOs’
chances of being invited to sit on the board of their own firms and/or other firms after
their retirement, and found a strong positive relation between the likelihood of post-
retirement board service and the CEO’s performance while on the job. Stock market
performance and accounting performance during the CEO’s career had substantial power
to explain the likelihood of a CEO serving on his own board after retirement. They
concluded that firms considered ability in selecting outside directors. Other studies on
41
outside director selection report similar results. Kaplan and Reishus (1990) found that top
executives of firms that reduced dividends were 50 percent less likely to obtain additional
directorships. Gilson (1990) found that outside directors who left the boards of
financially distressed firms held approximately one-third fewer directorships three years
after their departure. One study is of particular interest here. Fich (2005) examined 1,493
first-time (outside) director appointments to Fortune 1000 boards during 1997-1999.
Three major findings emerged from his study: (1) Investors reacted more favorably when
outside directors recruited by a firm were CEOs of other companies; (2) CEOs of well-
performing firms were more likely to be invited to sit on other companies’ boards; and (3)
Well-performing CEOs were also more likely to gain directorships in firms with growth
opportunities. While most studies focus on stock market reactions to outsider director
selection, Rosenstein and Wyatt (1997) examined appointments of inside directors.
Results show that the stock reactions to insider appointments were significantly negative.
But if the inside directors also owned firm stock between 5% and 25%, the stock market
reactions to their appointments became positive. These results indicate that the stock
market reacts to both ability and motivation of directors. Inside directors have often been
questioned about their willingness to monitor the CEO. Stock ownership may be
interpreted as a sign that these inside directors would align their interests with interests of
shareholders rather than the CEO.

All studies reviewed above focused on director selection. A consistent finding is that the
stock market welcomes highly capable directors with relevant career experience (e.g.,
CEO experience). However, these studies do not consider how the stock market reacts to
42
the decisions actually made by such directors (e.g., the decision of hiring a new CEO).
The present study fills this gap and thereby complements prior studies on board
experience.

Another line of research examines the effect of board experience on organizational
strategy / performance. In the boards of directors literature, studies on board monitoring
effectiveness and studies relying on insider/outsider dichotomy as a measure of board
independence appear to outnumber studies that examine the relationship between board
experience variables and board resource/strategy roles. Some researchers have used the
proportion of inside directors as a proxy for directors’ firm-specific knowledge, but have
reported mixed findings. For example, Judge and Zeithaml (1992) did not find any
significant impact of insider ratio on board involvement in strategy process. Research on
board demography has also generated mixed findings. For example, Golden and Zajac
(2001) examined the effect of board diversity on strategic change. Using a sample from
the U.S. hospital industry, they found that occupational diversity of the board had an
inverse U-shaped relation with strategic change, whereas the proportion of directors from
business occupations (including other hospital CEOs, nonhospital corporate executives,
independent business people, banker/financiers, and lawyers) was positively related to
strategic change. On the contrary, Goodstein, Gautam, and Boeker (1994) found a
negative relation between board occupational background diversity and strategic change
during periods of environmental turbulence. Finally, board average tenure and tenure
heterogeneity were found to have no significant impact on corporate strategic
restructuring (Johnson, Hoskisson, & Hitt, 1993). When it comes to the board’s influence
43
over CEO selection / succession, as mentioned above, most studies emphasize the board’s
monitoring role and the effect of board independence. Very few studies have investigated
how experience influences the board’s decision.

2.5 Summary
This section reviewed the three theoretical perspectives that lay the foundation for the
present study – the RBV, the learning perspective, and the UEP. Recent theoretical and
empirical work that examined the effects of board experience on board performance was
also reviewed. The RBV and learning perspective suggest that history-dependent,
context-specific experience should have a positive impact on individual / group /
organizational performance, whereas the UEP suggests that diversity of experience on a
team is generally positively related to performance. In next section, I will discuss how the
value-in-specificity and value-in-diversity hypotheses can be combined to provide a set
of robust theoretical predictions of the relations between various indicators of board
experience and CEO selection performance.

44
CHAPTER 3
THEORY AND HYPOTHESES
3.1 Types of Board Experience
As discussed in Chapter 2, work experience that contributes to task/decision performance
has been classified in different ways. Some researchers focus on the criterion of
situational specificity (Castanias et al., 1991; Kor, 2003). Thus, distinctions are drawn
between group-, firm-, and industry-specific experience. Context-specific experience is a
source of sustained competitive advantage while generic experience is not. Others focus
on the criterion of functional specialization, so distinction is made between various
domain-specific experience (e.g., experience in the area of finance, accounting,
marketing, law, and so on) and task-specific experience (e.g., direct involvement in
performing certain typical tasks in a functional domain) (Devine et al., 1995). Experience
is routine-based and history-dependent, implying that any attempt to explore the relation
between experience and task performance should focus on both the functional expertise
needed to perform that task and the situational context within which the task is to be
performed. To identify the types of performance-improving experience, it may be helpful
to think of an “experience matrix” that has two dimensions: situational specificity and
functional specificity, and map this matrix onto the task of question. This approach has
been used by previous researchers in classifying CEO’s career experience specialization
(Smith & White, 1987) or board knowledge (Forbes et al., 1999).

45
In addition to these conceptual considerations, it is also important to examine what
exactly the board of directors is expected to do when hiring a CEO. Vancil’s (1987)
description offers insights in this regard. In an informative and in-depth study on
corporate boards, Vancil suggested that the boards selects a new CEO based on the firm’s
“strategic mandate,” defined as “a forecast of the future environment facing the
corporation, an assessment of the degree and rate of change that will be required to cope
with that environment, and an identification of the skills, experience, and foresight
required of the next CEO if he is to create and execute a successful strategy for the next
era” (Vancil, 1987: 27).

Based on previous in-depth qualitative research on board experience (e.g., Conger &
Fulmer, 2003; Lorsch & Khurana, 1999; Vancil, 1987), I propose a classification scheme
of board experience relevant to the task of CEO selection. The first type is CEO
experience, defined as a director’s experience of working as the CEO of another company.
For a director to identify “the skills, experience, and foresight required of the next CEO”,
he or she must understand the complex nature of the CEO’s job. Directors who have CEO
experience (labeled “CEO directors” hereafter) are more likely to develop job knowledge
specific to the CEO position. I argue that when assessing if a director is good at picking a
CEO for the firm, it may be more meaningful to focus on the director’s CEO experience
than on his or her experience in certain functional areas such as finance, accounting,
marketing, law, and so on. This is not to say that functional knowledge is not important –
it is important when the board must evaluate strategic proposals provided by firm

46
management. But in the case of CEO selection, what is required of the board is tacit
knowledge about the CEO’s job. Since the CEO is supposed to be an integrator and
coordinator of TMT members’ diverse functional knowledge (Calori, Johnson, & Sarnin,
1994), the board members who are responsible for choosing the CEO must also be able to
understand the technical / functional aspects of the CEO’s job and its non-technical
aspects such as communication skills and leadership styles.

Board co-working experience refers to the time directors have spent together serving on
the focal firm’s board. The important role of group co-working experience in facilitating
the establishment of TMS has been discussed earlier. It should be noted here that co-
working experience gives rise not only to board-specific knowledge (about who knows
what and how the board as a group works) but also to firm-specific knowledge. For
independent directors, the time they have spent on serving their board duties perhaps
provides them with the only chance to learn about the firm.

Consistent with human capital theory and the resource-based view (RBV), I argue that
directors’ industry-specific experience is also important for board effectiveness in CEO
selection. Industry conditions constitute an important context within which firms
formulate and implement their strategies (Rajagopalan & Datta, 1996). Vancil’s (1987)
description of the CEO selection task highlights the need for the board of directors to
develop “a forecast of the future environment facing the corporation, an assessment of the
degree and rate of change that will be required to cope with that environment.” Directors’

47
industry-specific experience is particularly important for non-diversified firms that
operate in relatively stable industries because, for these firms, the best candidate for the
CEO position is very likely to be found in the same industry, if not from within the firm
(Parrino, 1997).

Finally, I argue that task experience, defined as previous experience with the task of CEO
selection, should be considered as a determinant of board effectiveness. Directors might
have high levels of firm and industry knowledge and are familiar with the CEO’s job, but
if they had never got involved in the process of hiring a CEO before, they might lack
unique “procedural knowledge” that is needed for performing a complex task such as
CEO selection.

Several years ago, in the wake of Enron and other corporate scandals, Business Week
published a special report on corporate governance practices. In this report, several
principles of “good governance” were proposed (Lavelle, 2002). In this report, “director
quality” was regarded as important as such familiar notions as increasing board
independence and awarding stock-based incentives to directors. It was suggested that the
board should include at least one independent director with experience in the company’s
core business and one who was the CEO of an equivalent-size company. These principles
for director quality are captured by the classification scheme developed in this study.

48
I focus on the experience of independent directors in this study for two reasons. First,
independent directors’ experience may have a greater impact on the board’s CEO
selection decision than inside directors’ experience. Insiders may be less motivated to
contribute their information and experience to the process of selecting a new CEO
because of their dependence on the outgoing CEO. Moreover, some insiders themselves
may be contenders for the CEO position, which leads to the concern about conflict of
interest. In addition, as subordinates to the outgoing CEO, inside directors may be
reluctant to take a hard look at the firm’s problems and its implications for the selection
of a new CEO. All these “confounding” motivational factors make it difficult to predict
the performance effect of insider directors’ experience, and explain why prior studies
have concentrated on the influence of independent directors (Sundaramurthy, Mahoney,
& Mahoney, 1997; Westphal & Zajac, 1995). Second, by focusing on independent
directors’ work experience, it is possible to examine if experience heterogeneity within
the subgroups of independent directors has an effect on board effectiveness over and
above the effects of board power and financial incentives.

The purpose of this study is to examine the relationships between various types of board
experience and CEO selection performance. CEO selection performance is defined in two
ways. First, CEO selection is an important organizational event that may influence the
future value of the firm perceived by investors. Assuming that the stock market is
efficient, stock price reaction to the announcement of new CEO appointment should
reflect investors’ expectation. Other things being equal, a firm’s stock gains abnormal or

49
excess return if investors expect that the benefits gained from the new CEO's
appointment will exceed the costs caused by the old CEO’s departure (Johnson & MaGee,
1985). Many studies have examined the wealth effects of CEO succession events (e.g.,
Borokhovich, Parrino, & Trapani, 1996; Furtado & Rozeff, 1987; Reinganum, 1985), but
few studies have discussed whether or not the market responds to the “experience
profiles” of the boards that make the hiring decisions. This dissertation examines whether
or not new CEO appointments are associated with abnormal stock returns calculated over
different intervals following the appointment announcements. Based on the patterns of
cumulative abnormal returns (CARs), a cross-sectional analysis is then conducted to
examine how much variance of CARs is explained by board experience variables.
Second, stock price reactions to CEO appointments reflect investors’ expectations but do
not reveal the actual outcomes of those appointments (Huson et al., 2004). The
performance outcome of CEO succession has often been defined as the firm’s post-
succession accounting performance (e.g., Denis & Denis, 1995; Hotchkiss, 1995; Shen &
Cannella, 2002). It has been argued that accounting performance numbers represent the
realized outcomes of managerial decisions; they are less susceptible to the influence of
exogenous factors unrelated to managerial actions (Johnson, Young, & Welker, 1993).
One key question this study is intended to answer is whether or not experienced boards
are able to hire new CEOs who help improve firm performance in the long run. Therefore,
post-succession accounting performance is incorporated as another quality measure of the
board’s CEO selection decision.

50
Figure 1. Effects of Board Experience on CEO Selection Performance

H2a, 2b, 6a, 6b
H1a, 1b, 5a, 5b
CEO Experience
• Level
• Diversity
Industry Experience
• Level
• Diversity
Co-working
Experience
Task Experience
Industry Instability
Prior Firm
Performance
Stock Market
Reaction to CEO
Appointment
Post-Succession
Performance
H3a, 3b
H4a, 4b
H7, H8
Board Experience
CEO Selection Performance
H9, H10

51
A theoretical model about board experience and CEO selection performance is illustrated
in Figure 1. The hypotheses derived from this model are discussed next.

3.2 Board Experience and CEO Selection Performance
3.2.1 CEO Experience
Directors with CEO experience are likely to be more effective at specifying the skills and
abilities required for a new CEO than directors without CEO experience. CEO directors
have most likely accumulated decision-making and leadership experience unique for the
CEO position, such as developing a strategic vision, representing the firm to outside
constituents and dealing with environmental uncertainty (Lorsch et al., 1999). Based on
their first-hand, job-specific experiences, CEO directors are able to provide advice
regarding the leadership expertise and style needed for running a firm. A sociopolitical
approach to board functioning suggests that CEO directors tend to support the incumbent
CEO of the focal firm because corporate CEOs are a cohesive elite group regardless of
their organizational affiliations (Lorsch & MacIver, 1989). But as pressures from
regulators and investors for board accountability increase, it is reasonable to expect that
CEO directors now may have stronger incentives to protect their reputation on the
directorial labor market as “decision control experts.”

The learning and information processing literature offers further theoretical support for
the argument that directors with high levels of CEO experience are more effective in
performing the task of CEO selection. It has been found that individuals who have high

52
levels of relevant job experience (experts) and those who have low experience (novices)
process information differently, which is reflected in the manner they collect, code, recall,
and interpret information (Devine et al., 1995). Experienced decision makers are more
selective in information searching. They are able to categorize information and identify
patterns among phenomena with respect to abstract underlying principles whereas
inexperienced decision makers are more likely to be misled by superficial data. Experts
can also recall information, particularly atypical information, more accurately than
novices (Choo et al., 1991; Shane, 2000). Moreover, prior work has shown that as
individuals develop task-specific skills from relevant experience, they not only improve
their performance on such tasks but are also able to judge the efficacy of others on similar
tasks (Bandura, 1997). By logical extension, we would expect CEO directors to have
developed the expertise to judge the efficacy of other potential CEOs from the skills they
build from their own CEO experience.

Viewed from the resource-based perspective, CEO experience meets the conditions for a
strategic resource. This type of experience is valuable because CEO directors are likely to
be better than other independent directors at analyzing business-related problems and
helping the firm achieve the environment-strategy “fit.” Moreover, the limited supply of
and increasing demand for managerial talent make directors’ CEO experience a rare
resource. On the supply side, current CEOs may be unwilling to accept board seats in
other companies because they are too busy with managing their own companies and/or
too concerned about the costs of outside directorships (e.g., exposure to shareholder

53
lawsuits or discipline on their own boards for non-value-maximizing behavior) (Booth &
Deli, 1996). On the demand side, however, there has been an increasing demand for CEO
directors. In the past decade, companies have been not only adding more outsiders but
also vastly upgrading their requirements. Figureheads, celebrities, and yes-men are no
longer sought for. The new prototype is a forceful, knowledgeable executive – preferably
a CEO (Bianco et al., 1997). Boards are trying to find directors that better reflect the
dynamics of the business. Directors themselves have also been reported to cite
broadening their business perspective as the job’s most important requirement (and
benefit) (Conger, Lawler, & Finegold, 2001). Given the complexity of a CEO’s day-to-
day work, CEO experience is also a hard-to-copy resource that does not have readily
available substitutes.

Some empirical evidence shows that companies and investors value directors’ CEO
experience. For example, retired CEOs were more likely to be invited to sit on the boards
of their own companies or other companies (Brickley et al., 1999), indicating companies
consider CEO experience a criterion for choosing board members. Appointments of CEO
Directors are also welcomed by the stock market. Fich (2005) found that the market
reacted positively to the appointments of outside directors who were CEOs of other
companies. Moreover, well-performing CEOs were more likely to gain directorships in
firms with growth opportunities. These results imply that CEOs are sought as outside
directors to enhance firm value. In sum, both theoretical work and empirical findings
support the argument that a board with higher levels of CEO experience is more likely to

54
make superior CEO selection decisions than a board with limited CEO experience. Hence,
I hypothesize the following:

Hypothesis 1a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with the level of independent directors’
CEO experience.
Hypothesis 1b: The level of independent directors’ CEO experience will be positively
associated with post-succession accounting performance.

3.2.2 Industry Experience
Some independent directors have work experience in the firm’s primary industry (labeled
“intra-industry directors” hereafter). There are several reasons why these directors may
be a valuable human resource for the firm and why they may perform a better job of
hiring a CEO. The significant effect of external environments, particularly industry
conditions, on organizational strategy formation, CEO succession, and organizational
performance has been recognized in many theories. Some theories treat industry context
as a factor that determines the firm’s strategic decisions (e.g., the decision of selecting a
CEO or a director.) For example, the industrial organization economics literature
suggests that industry structure (e.g., number of sellers and buyers, product
differentiation, barriers to entry) determines firm conduct (e.g., pricing or advertising
strategy), which in turn determines economic performance (Conner, 1991). Resource
dependence theory (Pfeffer & Salancik, 1978) suggests that organizations depend on the

55
external environments for resources. The importance of a resource to the organization,
the number of sources from which the resource is available, and the number, variety, and
power of organizations competing for the resource determine the degree of
“environmental dependence.” Organizations may use various strategies to reduce
environmental dependence and the board of directors is one of the significant
environmental linkage mechanisms that connect the firm to external resource providers.
Previous studies have examined the board’s role in securing financial resources for the
organization (Pfeffer, 1973), reducing environment uncertainty (Boyd, 1990), and
handling changes caused by deregulation (Hillman, Cannella, & Paetzold, 2000; Lang &
Lockhart, 1990), but little research has been done to explore the board’s role as a source
of industry knowledge in CEO selection.

I argue that directors with high levels of industry-specific experience tend to have a better
understanding of the competitive conditions in the firm’s task environment and can do a
better job at “translating” environmental information into skill requirements for the new
CEO. This argument is supported by both contingency theory and information processing
theory. Contingency theory predicts that decision makers strive to match internal resource
deployment to environmental conditions and firms that achieve higher degrees of
“environmental fit” will have better performance (Lawrence & Lorsch, 1967). Consistent
with this view, Datta and Rajagopalan (1998) found in a sample of CEO succession
events that firms attempted to match new CEOs’ demographic characteristics to industry
conditions. New CEOs tended to have shorter firm tenures, higher education, and output-

56
oriented functional backgrounds in industries characterized by high levels of product
differentiation. It was also found that the match between CEO characteristics and
industry conditions led to performance improvement following CEO succession. The
present study shifts attention to the board that makes the decision of matching CEO
characteristics to industry conditions. Following the contingency logic, I argue that
directors with more industry experience may understand better what characteristics the
new CEO should have in order to meet the environmental challenges. The link between
directors’ industry-specific experience and CEO selection performance can also be
explained from the information processing perspective. At the heart of this perspective is
the concept of knowledge structure, defined as a mental template that individuals impose
on an information environment to give it form and meaning (Walsh, 1995). This mental
template is built on past experience in an information environment and consists of
organized knowledge about an information domain. As mentioned in the preceding
chapter, both the expert/novice research and the research on TMSs show that past
experience improves information processing efficiency and hence decision quality. In
addition, intra-industry directors are likely to have more information about potential CEO
candidates within the industry. In this sense, they also have a better understanding of the
supply condition of managerial talent in the industry. Taken together, I propose the
following hypotheses:

57
Hypothesis 2a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with the level of independent directors’
industry-specific experience.

Hypothesis 2b: The level of independent directors’ industry-specific experience will be
positively associated with post-succession accounting performance.

3.2.3 Co-working Experience
The RBV and the group information processing literatures both suggest that co-working
experience among directors is likely to have a positive effect on the quality of CEO
selection decision. Experience of working with the same team members is a valuable
resource developed over time. Penrose’s insights regarding the importance of top
managers’ co-working experience also applies to independent directors who have been
working together for a long time:
An administrative group (management team) is something more than a collection
of individuals; it is a collection of individuals who have had experience in
working together, for only in this way can ‘teamwork’ be developed. Existing
managerial personnel provide services that cannot be provided by personnel
newly hired from outside the firm, not only because they make up the
administrative organization which cannot be expanded except by their own
actions, but also because the experience they gain from working within the firm
and with each other enables them to provide services that are uniquely valuable
for the operations of the particular group with which they are associated …
Extensive planning requires the cooperation of many individuals and this requires
knowledge of each other. (Penrose, 1959: 46-47)

According to information processing theory, long co-working experience increases
opportunities for direct interactions among group members and hence facilitates the

58
creation and sharing of group knowledge (Cramton, 2001). Researchers have argued that
co-working experience allows group members to develop a transactive memory system
(Wegner, 1987), a “shared mental model” (Cannon-Bowers, Salas, & Converse, 1993), or
“mutual knowledge” (Cramton, 2001) about who knows what on the team and what are
appropriate ways to seek from and share with other team members important decision
information. When members have been working together for a long time, they tend to
develop an increasingly accurate view on the content, credibility, and depth of other
members’ expertise (Moreland, 1999). Mutual familiarity also increases members’
likelihood of offering, discussing, and considering unique information (Gruenfeld,
Mannix, Williams, & Neale, 1996).

The group-level knowledge creation and sharing as described above is difficult to achieve
in boards of directors that are typically composed of many outsiders who perform their
duty on an intermittent basis and meet infrequently. But it does not mean there is no way
for board members to develop solid group knowledge. In fact, the likelihood of knowing
each other personally and finding a comfortable communication pattern increases as
board members’ co-working experience increases. For independent outside directors,
working together on the board allows them to develop in-depth knowledge not only about
other members’ expertise but also about the firm’s internal and external strategic situation.
With this mutual knowledge, directors can skip the lengthy “tell me what you know about
this” part at board meetings and focus on solving problems. As noted by Lorsch (1995),
directors’ real problems are not lack of concrete information or data but knowledge about

59
the “content and context” of the information. Working together on the same board helps
independent directors develop specific knowledge about the firm’s resources and
constraints (Conger et al., 1998).

Studies in other group settings provide some empirical evidence about the positive
performance impact of co-working experience among team members. In her study on top
management team (TMT) experience, Kor (2003) argued that shared team-specific
management experience, defined as the amount of time managers have spent with the
same members, should result in positive team dynamics. Shared team-specific
experiences include decision making, decision implementation, risk taking, commitment
to certain strategic actions, and jointly winning or losing as a team. These experiences are
unique to each team, and cannot be imitated and transferred across teams. Overall, high
levels of co-working experience are likely to be associated with high mutual knowledge
about expertise location, effective knowledge sharing, smooth communication, and in-
depth firm-specific knowledge, which in turn, will lead to high-quality decisions. The
decision of hiring a new CEO requires a great deal of information and opinion sharing
among directors when directors review the firm’s strategic situation, specify the
requirements for the new CEO, identify potential candidates, and compare their
qualification profiles. Co-working experience, as a source of group/firm knowledge and a
process-facilitating mechanism, becomes a critical factor affecting the quality of the
selection decision. Co-working experience can be seen as a history-dependent and
context-specific resource that adds special value to the board’s decision. Investors are

60
likely to be more confident in hiring decisions made by boards with high levels of co-
working experience. By the same logic, such decisions are likely to lead to better post-
succession performance. Thus, the following hypotheses are proposed:

Hypothesis 3a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with the level of independent directors’
co-working experience.

Hypothesis 3b: The level of independent directors’ co-working experience will be
positively associated with post-succession accounting performance.

3.2.4 Task Experience
I have argued that better CEO selection decisions are likely to be made by directors who
know what are required of a CEO, how the firm is operated, how industry conditions may
change, what expertise the other directors have, and how board members can work
together effectively as a group. Besides all this context- and domain-specific knowledge,
task-specific knowledge also contributes to board effectiveness. Task experience is
defined as a director’s personal involvement in the task of hiring a CEO. CEO selection is
not a linear process with clear-cut decision rules. Its complexity and secrecy have been so
unusual that some observers liken CEO selection to the election of a pope (Lorsch et al.,
1999). The process is time-consuming: More and more boards are beginning to initiate
succession planning several years before the incumbent CEO’s expected retirement. In

61
the process board members are expected to keep in touch with multiple “players” in
different ways. For example, the board needs to maintain good communication with the
incumbent CEO and make sure that the latter clearly maps out his or her plan for
choosing a successor. The board needs to evaluate that plan and challenge it if necessary.
The board also needs to have regular and direct contact with all the promising internal
candidates. Some of the contact should be formal. For example, candidates can make
presentations at board meetings. Sometimes board members must observe the candidates
in “real world” in order to get an idea how they solve problems, how they interact with
superiors, peers, and subordinates, and so on. Finally, the board needs to seek outside
input when designing a succession plan, including outside advice and industry talent
benchmarking. Although some boards may turn to executive search firms for help, it has
been noted by senior corporate directors and corporate governance observers that head-
hunting service can never replace the board’s own involvement in the process of CEO
selection (Ward, 1997). In the past, corporate boards were known to leave the task of
hiring the next CEO to the incumbent CEO. This situation has been changing in
fundamental ways recently as corporate boards are faced with increasing pressure for
taking responsibilities for their decisions (Lorsch, 1995). Therefore, whether or not board
members are familiar with the various steps of the selection task becomes a critical
indicator of board effectiveness in the CEO selection process.

CEO selections are relatively rare events in an organization’s history. In this sense,
directors who have participated in the previous selection decision can be seen as

62
possessing unique experience that helps them better understand the problems and identify
the solutions. Previous research has identified task experience along with job and
organizational experience as an important qualitative component of work experience
(Tesluk et al., 1998). As mentioned in Chapter 2, these types of experience differ along
the dimension of situational specificity with “task” at the lowest level of analysis. Some
researchers have found that the number of times a person performs a particular task is
more relevant than job tenure for predicting task performance (Quinones et al., 1995). In
a meta-analysis of work experience, Quinones and colleagues (1995) found that task-
level measure of work experience had a higher correlation with job performance than job-
or organization-level experience measures. The importance of task experience is also
documented in a review of the research on expertise in auditing (Bedard, 1989). An
auditor may have years of experience in the domain of auditing, but if he or she has been
involved only a few times in the task of evaluating internal control, he or she can hardly
be seen as an expert in evaluating internal control systems. In a similar vein, a complete
understanding of the effect of board experience on CEO selection should incorporate the
component of task experience. In particular, I focus on directors’ experience with the
CEO selection task in the focal firm rather than their task experience in other firms. This
measure should accurately reflect a major feature of the hierarchy of context-specific
experience as suggested by Castanias and Helfat (1991). That is, experience of lower-
level specificity is “nested” within experience of higher-level specificity. Hence, the
following hypothesis is proposed:

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Hypothesis 4a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with the level of independent directors’
experience with the task of CEO selection.

Hypothesis 4b: The level of independent directors’ experience with the task of CEO
selection will be positively associated with post-succession accounting performance.

3.2.5 Experience Diversity and CEO Selection Performance
Hypotheses 1a to 4b predict that experience specificity (measured as the level of various
types of context-specific board experience) will be positively associated with CEO
selection performance. In this section, I argue that experience diversity may also have a
positive effect on CEO selection performance. At the group level of analysis, specificity
and diversity are not necessarily in conflict with each other. The former concerns the
depth of a certain type of experience owned by directors, whereas the latter concerns the
breadth or range of board experience. Both dimensions are crucial for the board’s job
performance as a group. I have mentioned that the RBV and learning literature pays
relatively more attention to the benefits of specific experience. Even in this stream of
research, the importance of experience diversity has been addressed with relation to such
notions as resource complementarity (Krishnan, Miller, & Judge, 1997) and absorptive
capacity (Cohen et al., 1990). Cohen and Levinthal’s (1990) argument that absorptive
capacity derives from history-dependent, firm-specific experience with R&D activities is
essentially consistent with the value-in-specificity hypothesis. However, these authors

64
also address the value-in-diversity hypothesis by calling attention to the balance between
knowledge sharing and knowledge diversity in the development of organizational
absorptive capacity. Sharing means that organizational members must achieve some
common knowledge about critical technologies and knowledge about who knows what in
the organization. Diversity means that an organization will be benefited from “only
partially overlapping knowledge complemented by nonoverlapping diverse knowledge”
(Cohen & Levinthal, 1990: 134). In other words, learning effectiveness is determined by
both the level of common knowledge, which can only be accumulated in specific
organizational contexts, and the availability of nonoverlapping knowledge, which gives
rise to innovative capabilities. Some RBV-inspired studies posit that diverse resources
that complement one another can be a source of sustained competitive advantage. These
studies shift the focus from identifying single resources to examining the configuration of
different resources. For example, Krishnan, Miller, and Judge (1997) examined the effect
of complementary TMTs (defined as differences in functional backgrounds between the
acquiring and acquired firm managers) on post-acquisition performance in 147
acquisitions completed during 1986-88. They found that post-acquisition performance
was better when the TMT of the acquiring firm and its counterpart in the acquired firm
had different functional backgrounds, an indicator of diverse functional experiences.

Experience diversity may make a positive contribution to team information processing.
This occurs because the more diverse experience team members bring to the decision
process, the more likely they will be aware of the differences among themselves. This

65
“belief in expertise differences” then motivates team members to take responsibility for
contributing their own information and expertise (Lewis, 2004). In addition, if members
believe that others have different rather than similar expertise / experience and when task
outcomes depend on members recalling different, but complementary, information, then
individuals will tend to learn more information in their own areas of expertise
(Hollingshead, 2001). In one word, the presence of diverse experience tends to change
members’ expectations and motivate them to review their own information more
thoroughly and to share with other members more willingly. In this sense, experience
diversity can actually help reduce the information sharing bias associated with the
“hidden profile” situation. It has been mentioned that groups tend to underemphasize
members’ unique knowledge during discussions and overemphasize common knowledge
that team members have prior to discussion. But if the initial experience / expertise
distribution among team members is diverse, teams are less likely to experience such a
information sharing bias (Lewis, 2004).

In this study, I argue that diversity of directors’ CEO experience and industry experience
may positively affect CEO selection performance. I focus on these two types of
experience based on the premise that diversity may not be a major concern in the analysis
of task and co-working experience as defined in this study. The main reason is that all
independent directors have gained task and co-working experience within the same
context – the focal firm. But they have gained CEO and industry experiences from
different other firms. Task and co-working experience helps directors develop a common

66
understanding of the CEO selection task and of the board’s inner workings within the
firm’s historical context. Therefore, the key issue is commonality rather than diversity. In
contrast, CEO and industry experiences are brought to the board from outside the firm.
Diversity thus becomes more important than commonality.
In the case of CEO experience, diversity is closely related to the different kinds of
information processing preferences and decision styles that CEO directors bring to the
focal firm, which in turn, are likely a function of the directors’ tenures as CEOs in other
companies. According to Hambrick and Fukutomi (1991), there are discernible phases (or
“seasons”) within a CEO’s tenure and these seasons give rise to distinct patterns of
executive attention and behavior. A new CEO who just takes the job may devote
attention and energy to responding to the strategic mandate that the board or the
predecessor CEO sets for him / her. In this early phase, the CEO typically has low task
knowledge and low power but is eager to gather information from multiple sources,
establish legitimacy, and undertake immediate changes in the functional areas he or she is
familiar with. After the first phase, the CEO may enter into a stage of experimentation
and then move into a phase of selecting an enduring theme. The paradigm he or she has
chosen for running the firm is likely to be reinforced in a following convergence phase.
Hence, Hambrick and Fukutomi argued that a CEO tends to involve in more focused and
narrower information search as his/her tenure increases. This view about the seasons of a
CEO’s tenure implies that, since CEO directors are in different seasons of their careers,
they tend to bring to the focal board different job knowledge and cognitive maps. I argue

67
that, other things being equal, higher CEO experience diversity may be associated with
lower likelihood of information sharing limitations and biases.

Similarly, one can argue that diversity of directors’ industry experience may also have a
positive effect on board effectiveness. Industry experience diversity can be
conceptualized in two ways. First, it can be diversity in terms of job tenure in the focal
firm’s primary industry. This is similar to the concept of CEO experience diversity
defined above. The assumption is that directors may have developed different
understandings of the industry conditions facing the focal firm, depending on how long
they have been working in the industry. Newcomers and veterans may have different
perceptions of and expectations for the industry’s competitive dynamics and growth
opportunities. They may have different methods to collect information about the industry.
Newcomers may rely more on formal channels such as reports and forecasts provided by
analysts and consultants, whereas veterans may have more informal sources to get
information. When directors who have diverse industry tenures apply their industry-
specific knowledge to the decision process, there will be a larger pool of information and
expertise, which will generate a positive performance effect. Second, industry experience
diversity can also be defined as intra-personal industry experience diversity, that is, the
extent to which the independent directors have narrow experience in a limited number of
industries or have broad experience in a large number of industries (Bunderson &
Sutcliffe, 2002). This measure concerns the breadth of directors’ industry experience.
Given the importance of the environmental analysis in CEO selection, directors with

68
broad industry experience may be better at examining the focal firm’s strengths and
weaknesses in a broader context and have more access to potential CEO candidates.
These arguments lead to the following hypotheses:

Hypothesis 5a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with CEO experience diversity among
independent directors.

Hypothesis 5b: CEO experience diversity among independent directors will be positively
associated with post-succession accounting performance.

Hypothesis 6a: Cumulative abnormal returns (CARs) following announcements of new
CEO appointments will be positively associated with industry experience diversity
among independent directors.

Hypothesis 6b: Industry experience diversity among independent directors will be
positively associated with post-succession accounting performance.

3.3 Experience Effects and Industry Instability
Environmental change is an important contextual factor that influences organizational
strategy and performance. Researchers have used different terms to describe rapid and
unpredictable environmental change, e.g., instability (Guthrie & Olian, 1991; Miller et al.,
1996), uncertainty (Aragon-Correa & Sharma, 2003), dynamism (Dess & Beard, 1984),

69
turbulence (Virany, Tushman, & Romanelli, 1992), high-velocity (Eisenhardt, 1989b),
and so on. Dealing with such change is seen as the “essence of the administrative
process” (Thompson, 1967: 159). Instability of the firm’s primary industry is a
particularly important environmental force that sometimes changes not only the strength
but also the direction of the effect of an organizational strategy on performance. Rapidly
changing product demand, customer needs, production technologies and/or other factors
pertinent to strategic decision making increase risks to the firm and require organizational
decision makers to constantly adapt their perceptions of the environment to fit the current
reality. How managers can achieve the fit between organizational strategy / structure and
environmental conditions dynamically thus becomes a central issue in the strategy
literature.

I argue that the strength of the effects of board experience on CEO selection performance
may vary with the degree of industry instability. But industry conditions may influence
the effects of experience specificity and diversity in different ways. Specifically, history-
dependent, context-specific experience may become less valuable in unstable industries
than in stable industries. However, experience diversity is likely to add more value in
unstable industries than in stable industries.

History-dependent, learning-by-doing experience is viewed as a source of sustained
competitive advantage in the RBV literature. Firm-specific knowledge and skills
embedded in employees, technical systems, managerial services, and values and norms

70
associated with the process of knowledge creation constitute a firm’s “core capabilities.”
However, this internally-oriented thinking of resource strength has been challenged for its
lack of attention to external environmental change. When change is unpredictable and
discontinuous, core capabilities may become “core rigidities” that prevent the firm from
responding to change timely and effectively (Leonard-Barton, 1992). Situational
embeddedness emphasized in the RBV has a down side. That is, when managers have
become too familiar with established organizational routines and processes, they may
develop an “incumbent inertia” (Lieberman & Montgomery, 1988) in the face of
environmental changes. They may fall into a “competency trap” by sticking to routines
and procedures that used to be effective but no longer suit the current environmental
conditions (Levitt et al., 1988). Experience does help improve problem solving skills and
information processing efficiency, but experience may also reduce information search,
which may result in the overlooking of new opportunities (Cyert et al., 1963). Incumbent
inertia is particularly problematic in unstable industries where active environmental
scanning and innovativeness are crucial for organizational survival and growth. The
positive relation between experience accumulation (measured as the level of experience
at a point in time) and organizational performance may become weaker in unstable
industries. The relation may even change in direction from positive to negative. This is
not only because long experience leads to reduced scanning and searching activities in
the future but also because in unstable industries “history” does not add that much value
as it does in stable industries. In a rapidly changing environment, few strategic choices
and organizational routines can be proven useful for a long time. It is the ability to initiate

71
changes that is rewarded in unstable industries. Consistent with this view, Guthrie and
Olian (1991) found that firms in unstable environments tended to hire general managers
with fewer years of organizational experience. Grimm and Smith (1991) found that
railroad company managers with fewer years of industry experience were more likely to
initiate strategic changes in the deregulation period.

In the case of board experience, I expect that task experience that directors have learned
from previous CEO selection events may be less valuable for firms facing unstable
industry conditions because the strategic and skill requirements associated with the
previous CEO selection decision are very likely to have changed when the next CEO is
hired. Similarly, although arguably the positive effect of co-working experience on
interpersonal communication does not easily change, previously learned knowledge about
the firm’s business does depreciate in value more quickly in unstable industries. The
same can be said about directors’ industry-specific experience: In an unstable industry,
historical experience helps improve current performance only to a limited extent. And the
possibility that past experience may become a burden and even hurt current performance
cannot be ruled out. Finally, although directors’ CEO experience may have a positive
effect on CEO selection performance in general, one may argue that unstable industry
conditions would impose such tremendous information-processing demands on directors
that even experienced CEO directors might find their previous experience limited in use.
Based on these arguments, I propose the following moderating effect of industry
instability:

72
Hypothesis 7: The positive relationships between the level of board experience and CEO
selection performance as predicted in Hypothesis 1a through Hypothesis 4b will be
weaker in unstable industries than in stable industries.

Different from the level of specific experience, experience diversity has been found in
many studies to have a stronger positive effect on innovation and firm performance in
more unstable environments. Recall my earlier discussion about how experience diversity
affects team information processing by enlarging the pool of information, increasing the
number of strategic alternatives, and improving the quality of their evaluation. In unstable
industries, firms are faced with rapidly changing competitive conditions, technological
shifts, high information-processing requirements, more opportunities and threats – all
necessitate the adaptive capabilities ensured by experience diversity (Finkelstein et al.,
1996). Group members with diverse experiences tend to become more aware of their
own expertise and pay more attention to what others can offer (Lewis, 2004). This
awareness of expertise location increases the likelihood that members will share their
unique knowledge. The result is a larger pool of information and alternative options. The
options are likely to be evaluated under more comprehensive decision rules. Overall,
experience diversity ensures open-mindedness to new ideas and perspectives, which is
very important for firms in unstable industries.

The positive performance effect of experience diversity in relatively unstable
environments has been reported in many studies. For example, Haleblian and Finkelstein

73
(1993) found that firms with large TMTs and less dominant CEOs performed better in
turbulent environments, ostensibly because such TMTs had superior information-
processing capabilities. Arguing that diverse TMTs engaged in more constructive conflict,
Eisenhardt and Schoonhoven (1990) found a positive relation between various measures
of TMT diversity and firm performance in high-velocity industries. In a sample of 32 US
airlines over eight years, Hambrick, Cho, and Chen (1996) found that TMTs with diverse
functional backgrounds, education, and company tenures exhibited a relatively great
propensity for taking competitive moves, and both their actions and responses were of
substantial magnitude.

In this study, I argue that corporate boards that have diverse CEO experience and
industry experience make better CEO selection decisions in unstable industries. Diverse
CEO experience ensures that every aspect of the CEO’ job will be analyzed and a more
comprehensive knowledge profile for the new CEO will be proposed. Diverse industry
experience, in addition, allows the board to conduct a broader environmental analysis
about the potential business opportunities and promising CEO candidates from outside
the industry. In one word, the hiring board will be benefited from directors’ diverse
experience, rich information and comprehensive decision-making. There is a concern that
experience diversity may be associated with slow decision speed (Hambrick et al., 1996).
But decision speed, which is crucial for competitive moves in daily business, may not be
as important as decision comprehensiveness if the decision is to hire a CEO. It is
reasonable to believe that in most cases the board has time to prepare for the CEO

74
selection decision. In an unstable industry, boards with diverse experience are likely to
make better strategic choices. Therefore, I propose the following hypothesis:

Hypothesis 8: The positive relationships between CEO and industry experience diversity
and CEO selection performance as proposed in Hypothesis 5a through Hypothesis 6b will
be stronger in unstable industries than in stable industries.

3.4 Experience Effect and Past Performance
Firm performance prior to CEO change is another critical contingency factor that may
moderate the relationship between board experience and CEO selection performance.
Past performance serves two functions: It provides outside observers with information
about the effectiveness of the strategic choices that the firm has made over a certain
period of time. It also serves as a feedback mechanism that modifies the patterns of
subsequent organizational learning (Cyert et al., 1963). For stakeholders of the firm,
particularly those outside the firm who do not have chance to observe how managers
make decisions and how the decisions are implemented, bottom-line performance
measures give an overall assessment of organizational effectiveness. The increasing
complexity of business operations in these days perhaps only increases stakeholders’
reliance on straightforward outcome measures. Firm performance has been treated as an
indicator of managerial performance in the research on executive compensation and
succession. It is not surprising that many studies have attempted to examine the degree to
which executive compensation or executive turnover is “sensitive” to firm performance.

75
In principle, top executives should be rewarded and punished based on a range of criteria,
including managers’ efforts, abilities, behaviors, and outcomes of their decisions. But in
reality, performance as a behavioral outcome seems to have received much more
attention than other “soft” criteria. The same logic has also been applied to evaluate
board effectiveness. Past firm performance may affect perceived value of board
experience. Poor performance immediately prior to CEO change may become an
overwhelming contextual factor that casts a shadow on investors’ perceptions of the
hiring board’s ability. Board experience is likely to be devalued in the face of
performance decline.

Performance also provides feedback for directors. Learning theory suggests that good
performance and poor performance affect subsequent learning behavior differently.
Numerous studies have shown that poor performance may be a catalyst for strategic
change (Gordon, Stewart, Sweo, & Luker, 2000; Tushman & Romanelli, 1985). When
performance is unsatisfactory, managers will engage in external information search in
order to correct the deficiency (Cyert et al., 1963). For example, Hayward (2002) found
that small acquisition losses experienced in the past intensified the search for richer
inferences about what to acquire subsequently. Poorly performing firms have been found
to be more likely than well-performing firms to invoke various forms of change,
including managerial change (Warner, Watts, & Wruck, 1988), strategic change (Boeker,
1989), and divestitures (Kaplan & Wiesbach, 1992). Poor performance gives decision
makers motivation and opportunity to initiate change, but whether or not change actually

76
occurs and how change affects organizational performance depends on the decision
makers’ capabilities to learn from failures. In a comprehensive review of the strategic
change literature, Rajagopalan and Spreitzer (1997) contended that poor performance
first influences managerial cognition (e.g,. attention, information collection and
interpretation), which in turn, affects the degree of strategic change. Barr, Stimpert, and
Huff (1992) proposed a model of organizational renewal in which changes in top
managers’ mental models must occur before changes in organizational strategy and
practices. Largely consistent with the UEP, their framework suggests that managers’
mental models play a central role in making organizational renewal possible.

These studies suggest that decision makers’ ability to notice performance problems and to
initiate necessary corrective actions determines how the firm responds to poor
performance. When examining the possible moderating effect of pre-succession firm
performance on the relationship between board experience and CEO selection
performance, a key step is to identify the type(s) of experience positively associated with
the board’s ability to initiate change. Research shows that as learning-by-doing
experience increases, the tendency to follow established routines also increases (Cyert et
al., 1963). It has been generally recognized that high levels of learning-by-doing
experience result in tendencies towards maintaining the status quo, focused (but also
limited) information search, less time and effort devoted to exploring new opportunities,
and resistance to change (e.g., Haleblian & Finkelstein, 1999; Miller & Chen, 1994).
When firms are having performance problems, strategic decision makers with high levels

77
of learning-by-doing experience may not be able to initiate necessary changes in a timely
manner. In relation to board experience, an implication is that the more learning-by-doing
experience director have gained from the focal firm and from their primary jobs, the more
difficult for them to shift to new views and practices when the situation requires strategic
change (e.g., when the focal firm is faced with performance problems), and this tendency
to stick to old routines and solutions will in turn hurt future performance. These
arguments lead to the following hypotheses:

Hypothesis 9: The positive relationships between the level of board experience and CEO
selection performance as predicted in Hypothesis 1a through Hypothesis 4b will be
weaker in firms with lower pre-succession performance.

I have argued that boards with diverse CEO and industry experiences are better able to
handle changing industry conditions than are boards without diverse experiences. Based
on a similar logic, poor pre-succession performance provides stimulus for more
information search and behavioral change, but it is the boards with diverse experiences
that are likely to meet those challenges and successfully launch change activities. In the
TMT research, various diversity measures, particularly functional background diversity,
have been found to facilitate cognitive diversity (Mohammed & Ringseis, 2001), task
conflict (Pelled, Eisenhardt, & Xin, 1999; Simons & Peterson, 2000), and debate (Simons
et al., 1999) among team members, which in turn increase decision comprehensiveness

78
(Simons et al., 1999) and likelihood of strategic change (Boeker, 1997). These arguments
lead to the final hypothesis tested in this dissertation:

Hypothesis 10: The positive relationships between CEO and industry experience
diversity and CEO selection performance as proposed in Hypothesis 5a through
Hypothesis 6b will be stronger in firms with lower pre-succession performance than in
firms with higher pre-succession performance.

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CHAPTER 4
RESEARCH METHODS
4.1 Sample and Data Sources
The focus of this study is the board’s role in CEO selection, so a sample of CEO selection
events was used to test the hypotheses. Following previous studies on stock market
reactions to CEO succession events (e.g.,Bonnier & Bruner, 1989; Friedman & Singh,
1989; Furtado et al., 1987; Huson et al., 2004; Worrell, Davidson, Chandy, & Garrison,
1986), I first examined the “Who’s News” and “What’s News” columns of every issue of
the Wall Street Journal (WSJ) from January 1, 1999 to December 31, 2003 for
announcements of new CEO appointments. For an appointment to be included in the
sample, the following criteria were employed:
(1) Appointments had to be permanent. Temporary, interim, or acting appointments
were excluded. This criterion serves to filter out events that have potentially little
importance and do not represent the board’s “final decision” about who should be
the next CEO.
(2) If the company announced more than once the same CEO change news during the
sample period, only the first announcement entered the sample. This typically
happened when the company first announced a CEO succession plan and then
confirmed the CEO change when the successor officially assumed the CEO
position some time later. This criterion was used to capture the stock market’s
earliest possible reaction to the board’s CEO selection decision.

80
(3) The company had to announce the departure of the predecessor (the old CEO) and
the appointment of the successor (the new CEO) simultaneously (i.e., in the same
news story). This was to rule out the cases in which information about the new
CEO might have been “leaked” to the market between the time of the old CEO’s
departure and that of the new CEO’s official appointment. If the departure and the
arrival occurred at different points in time, information (or rumors) about
potential CEO candidates might be spread on the market before the board makes
the final choice. To avoid the potential information leakage effect of separate
announcements, I only included simultaneous announcements [or “paired
changes” in Reinganum’s (1985) term] in the sample.
(4) The company had to be a publicly traded, relatively large (average sales revenues
greater than $50 million dollars in the three years prior to CEO change), non-
diversified US manufacturing firm. This criterion was used to control for some
environmental and organizational factors other than those related to CEO
succession that may also influence stock prices and long-term performance. A
manufacturing firm had a 6-digit North American Industry Classification System
(NAICS) code between 311111 and 339999 for its primary industry. A non-
diversified firm was defined as one having on average more than 70 percent of
total sales from its primary industry during the three years prior to CEO
succession (Zhang & Rajagopalan, 2004). The data on the firm’s primary NAICS
code and sales were collected from COMPUSTAT.

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The final sample consisted of 242 announcements made by 226 firms (212 firms with one
announcement, 12 with two announcements, and 2 with three announcements) for testing
the effect of board experience on stock market reactions and 214 announcements for
testing experience effect on post-succession performance.
1

Archival data from multiple sources were used to construct all the variables. Specifically,
the information needed for determining the “event date” when new CEO appointments
were announced was obtained from the WSJ and the Press Release Wires in Dow Jones’
Factiva news database. Financial data of the sample firms and other firms in their
industries were obtained from COMPUSTAT. Stock returns data were collected from the
Center for Research in Security Prices (CRSP). Data about characteristics of the new
CEO and the old CEO, nature of the succession event, and board experience were mainly
coded from the WSJ, company press releases, company proxy statements and annual
reports.

4.2 Variable Measurement
4.2.1 Dependent Variables
Cumulative abnormal stock returns (CARs). The importance of an event like CEO
selection may be assessed by the stock’s price change during a period surrounding the
event date. This price change, known as abnormal return and, was calculated as the

1
Post-succession performance data were not available in COMPUSTAT for 28 firms. I checked Hoover’s
and SEC’s EDGAR database and found that the 28 firms were acquired within one year after CEO
succession. However, dropping these 28 cases did not alter the effects of board experience on abnormal
stock returns. So, the full sample of 242 events was used for testing the experience effects on abnormal
stock returns.

82
difference between the observed return for a stock and the predicted or normal return for
the same stock (Brown & Warner, 1980, 1985). Thus, the impact of an event was
measured by the portion of the return that was unanticipated by an economic model of
anticipated, normal returns. This may be expressed mathematically as follows:
) (
mt i i it
R R E β α + − =
where R
it
= return on stock i for day t; R
mt
= return on the market portfolio for day t; α
i
=
constant; and β
i
= beta of stock i.
2

The event study method assumes that an event is announced in the press and investors
gain information from the announcement (McWilliams & Siegel, 1997). Considering the
possibility of information leakage, it is very important to accurately determine the date of
the announcement or the earliest day when the news of CEO succession is known to the
public. Many early studies treated the day when the WSJ reported the news as the event
date. This practice, however, encountered some problems in my sample. I noticed that
since 2001 the WSJ’s “Who’s News” column had been published every week instead of
every day. The column covers the board and executive change news in the past week.
Although the WSJ is still very useful for identifying important, high-profile succession
events, the change in its report format did create a problem in determining the event date.
To address the problem, I compared the WSJ publication date to the date when the same
event was reported in Factiva’s Press Release Wires. I found that, in all cases, the WSJ
date was the same as or later than the date of company press release. The two sources
reported the event on the same day in 16 out of 242 events. There were 112 events in

2
It is assumed that α and β are stable and are calculated during an arbitrary estimation period. The arbitrary
estimation period used in this study is 255 days, from 300 days to 46 days before the event.

83
which the WSJ date was a day later than the press release date. The time lag between the
two press dates ranged from 2 days to 26 days for the other events. Since the company
press release date was earlier than the WSJ date, I used the former as the event date (day
0) and constructed various event windows surround that day.

Stock price reactions around the time of new CEO appointments reflect investors’
expectations regarding the outcomes of these appointments but do not reveal the
outcomes themselves (Huson et al., 2004). Therefore, a second performance measure was
created. Post-succession accounting performance was measured using two dimensions:
return on assets (ROA) and return on equity (ROE). Following prior research (Finkelstein
& Hambrick, 1990; Zhang et al., 2004), I created a composite performance index by first
standardizing ROA and ROE for the year following CEO succession within the sample
(mean = 0, s.d. =1) and then summating the two standardized values. Data for ROA and
ROE were obtained from COMPUSTAT.

4.2.2 Independent Variables
As mentioned above, this study focuses on independent directors’ work experience.
Therefore, the first step of data coding was to identify independent directors in each firm.
Consistent with previous board research, directors were classified into three types:
insiders, affiliated directors, and independent directors. Insiders were defined as current
employees of the firm. Securities and Exchange Commission regulation 14A, item 6b sets
forth the conditions under which directors’ affiliation must be disclosed in proxy

84
statements. According to Investor Responsibility Research Center (IRRC) (Investor
Responsibility Research Center), a key monitor of corporate governance activity, a non-
employee director is considered “affiliated” rather than “independent” if he or she is:
• a former employee of the company or of a majority-owned subsidiary;
• a provider of professional services—such as legal, consulting or financial—to the
company. The services may be provided either personally by the director or by the
director’s employer;
• a customer of or supplier to the company, unless the transaction occurred in the
normal course of business and was explicitly deemed "not material" by the
company in proxy materials;
• an employee of an affiliate of which the company owns less than 50 percent. (An
employee of a subsidiary that is 50 percent or more owned by the company, is
considered an employee director);
• a designee under a documented agreement by a group (such as a union) or
significant shareholder. Majority holders (or employees of majority holders) are
assumed to be designated;
• a family member of an executive officer;
• a part of an interlocking directorship whereby a director and executive of the
company sits on a board of another company that has an executive and director
who also sit on the original company’s board;
• a recipient of the company’s charitable giving, if this is disclosed in the proxy
statement; and

85
• any other type of affiliation that may compromise the ability or incentive of a
director to perform oversight duties in the best interests of shareholders.

Following these descriptions, I coded each director’s type based on the affiliation
information provided in company proxy statements. Board members who were neither
insiders nor affiliated directors were defined as independent directors. The following
board experience measures were then constructed for the subgroup of independent
directors. All board experience variables were measured for the year just preceding the
year when CEO succession took place.

CEO experience of independent directors was measured in two ways. The level of CEO
experience was measured as the number of CEO directors on the board. A CEO director
was defined as an independent director who currently served or had served as the CEO of
another firm. Data on each independent director’s primary or most recent employer were
mainly collected from proxy statements. The second measure, CEO experience diversity
was computed using the following formula (Tsui et al., 1992):
2
1
2
1
] ) (
1
[
j
n
j
i
s s
n
−
∑
=

Where si, sj are CEO tenures of any two CEO directors, and n is the total number of CEO
directors. This is a Euclidean distance measure that equals the square root of the summed
squared differences between a director’s CEO tenure and every other director’s CEO
tenure, divided by the total number of CEO directors. A higher score represents a higher
level of diversity.

86
Industry experience was also measured in two ways. The first variable – presence of
intra-industry directors was a dichotomous variable indicating if there was any
independent director whose primary or most recent employer was in the same 4-digit
NAICS industry as the focal firm. The value of “1” means there were one or more such
intra-industry directors on the board whereas the value of “0” means no independent
director was from the same industry. The dichotomous variable was used because very
few firms in my sample had more than one independent director from the same industry. I
also measured the diversity of independent directors’ industry experience. This variable
was created to capture each director’s intrapersonal industry experience. As suggested by
Bunderson and Sutcliffe (2002), at the individual level, intrapersonal diverse experience
in multiple industries reflects the extent to which an individual has accumulated “narrow”
experience in a limited number of industries or has “broad” experience in a wide range of
industries. Bunderson and Sutcliffe (2002) used the following formula to measure the
group-level intrapersonal experience diversity:
n p
n
i
m
j
ij
/ )] 1 ( [
11
2
∑∑
==
−
Where p
ij
equals the percentage of individual i’s total years of experience spent in the jth
industry and n equals group size (here the number of independent directors). This
measure is the average intrapersonal experience diversity of a group. Since the data on
the number of years a director had spent in a certain industry were incomplete for most
directors in the sample, I used an alternative method to measure industry experience
diversity. Specifically, I checked each independent director’s primary or most recent
employer and recorded the number of industries in which that company had operations.

87
The information was obtained from the business segment data of COMPUSTAT. The
idea is that a director who had been working in a more diversified, multiple-industry
company might have broader industry experience and hence a higher degree of
intrapersonal industry experience diversity. This way, industry experience diversity can
be seen as a “cross-sectional” measure rather than a “longitudinal” measure. I then
defined p
ij
in the above formula as the reciprocal of the number of industries (i.e., 1
divided by the number of industries in which a director’s primary or most recent
employer was operated), m as the number of industries, and n as the number of
independent directors. A higher score represents a higher level of industry experience
diversity.

Independent directors’ co-working experience was measured as the overlap in
independent directors’ board tenure times using a variation of the measure developed by
Carroll and Harrison (1998). The formula I used is as follows:
Tenure overlap = ) min(
1
j
j i
i
u u
n
∑
≠

where u
i
is board tenure of the ith director and n is the number of pair-wise comparisons.
This measure captures the average amount of time each pair of individuals has spent
together serving as directors for the same firm.

Task experience was measured as the percentage of independent directors who had been
on the board since one year prior to the year when the previous CEO was appointed. This
variable was computed by comparing the year when a director began his/her board

88
service at the focal firm and the year when the old CEO was hired. The number of
directors who joined the firm earlier than the old CEO was then divided by the total
number of independent directors. In other words, this variable measures the percentage of
independent directors who had been involved in hiring the previous CEO and hence
serves as an indicator of the board’s experience with the task of CEO selection in the
focal firm.

In addition to board experience variables, two contingency factors were added to test the
moderating-effects hypotheses. To measure the external contingency factor -- industry
instability, I first regressed time against industry sales. The following regression equation
was estimated for each 6-digit NAICS industry in the sample:
Y
t
= b
0
+ b
1
*t +ε
t

where Y
t
is the total sales of all firms in an industry in year t, and ε is the residual.
Estimate for any year was based on the 5 preceding years, i.e., the estimate for 1999 was
based on data from 1994 to 1998. Industry instability was then computed as the standard
error of the estimated beta coefficient (b
1
) divided by sales averaged over the 5-year
period prior to the year of CEO succession (from year t-5 to t-1). This measure has been
used in previous studies (e.g., Boyd, 1990; Dess et al., 1984; Keats & Hitt, 1988). Sales
data for all firms in an industry were obtained from COMPUSTAT.

The internal contingency factor -- the firm’s pre-succession performance was
hypothesized as another moderator of the relation between board experience and CEO

89
selection performance. Prior firm performance was measured in the same way as post-
succession performance. That is, it was the sum of the standardized values of ROA and
ROE for year t-1. I chose year t-1 because it has been found that investors tend to
associate significant organizational events such as managerial turnover (Warner et al.,
1988) or director appointments (Brickley et al., 1999) with firm performance over a
relatively short period of time immediately prior to an event.

4.2.3 Control Variables
I included a set of control variables to represent key organizational conditions, corporate
governance mechanisms, succession context and CEO characteristics. These variables
have been associated with CEO succession performance in prior empirical work.

Research has shown that investors respond differentially to CEO successions in large and
small firms (Furtado et al., 1987; Reinganum, 1985), so I controlled for firm size,
measured as the logarithm of the firm’s total assets averaged over the three years prior to
CEO selection, and the logarithm of firm age. Since the sample firms were from multiple
manufacturing industries, I also controlled for prior industry performance, measured as
the median performance of all firms except for the focal firm in an industry in year t-1
(Huson et al., 2004). Industry performance and firm performance were computed in the
same way.

90
Prior research shows that the consequences of CEO selection also depend on the supply
conditions within the hiring firm and in the external managerial labor market (Zhang et
al., 2004). I added two control variables measuring the managerial talent supply
conditions to address the question “Who are available for the CEO position?”: The first
was TMT size in year t-1. It is not uncommon that many industrial corporations first
consider inside senior executives when selecting the new CEO. Vancil (1987) described
different modes of CEO succession in large companies. Whether the succession takes the
form of a smooth relay succession (in which an heir apparent is expected to assume the
CEO position when the old CEO retires and becomes Board Chair) or the form of a
“horse race” (in which several internal candidates compete for the top job), the number of
internal candidates (typically the TMT members) is an important factor that sets the
boundaries for the firm’s internal choices. In this study, TMT size was measured as the
number of top executives whose names were listed in the proxy statement filed in the
year prior to CEO succession.

Prior research has also shown that when internal CEO candidates are not available (from
a supply point of view) or not desirable (from a demand point of view), boards of
directors tend to select the CEO from the firm’s primary industry (Parrino, 1997; Zhang
et al., 2004). Moreover, firms are more inclined to hiring new CEOs from larger firms in
the same industry (Zhang et al., 2004). Hence, the number of non-smaller firms in the
industry was used as a control variable to capture the supply condition on the external
labor market. A non-smaller firm was defined as a firm in the focal firm’s primary 6-digit

91
NAICS industry whose sales was equal to or larger than the focal firm’s sales in the three
years prior to CEO succession.

Characteristics of the departing CEO (the “old CEO”) are also likely to affect CEO
selection and stock market reactions. Thus, two variables related to the old CEO were
added to the analysis. First, age can be seen as a proxy for a CEO’s experience and
influence (Cannella & Shen, 2001), so the old CEO’s age was included as a control
variable. Second, it is important to examine why the old CEO left his or her position.
Consistent with prior succession research (Cannella & Lubatkin, 1993; Friedman et al.,
1989; Huson et al., 2004), I classified succession events into two types: routine
departures (coded “1”) and non-routine departures (coded “0”). Specifically, routine
departures include (a) relay succession in which an heir apparent (an individual who held
the title(s) of president and/or COO and who had been with the firm for at least two years)
became CEO and the outgoing CEO became board chairperson; and (b) retirement in
which the outgoing CEO retired from the top position but remained as Chairman or a
director. Non-routine departures include (1) voluntary resignation in which the outgoing
CEO resigned and accepted a position in another company or it was explicitly stated that
the CEO resigned for personal reasons not related to company performance; (2) forced
resignation and dismissal. Non-routine departures included cases in which all officer and
directorship connections between the firm and the outgoing CEO were severed at
succession as well as cases in which the outgoing CEO resigned due to conflict with the

92
board; and (3) deaths / health reasons. Data to identify succession type were coded from
the WSJ, company press releases, and corporate proxy statements.

Two control variables describe the characteristics of the new CEO: new CEO age and
new CEO origin. The latter is a dichotomous variable indicating if the new CEO is an
insider or an outsider. Researchers have reported different findings on stock market
perceptions of insider successions versus outsider successions. Some have found positive
reactions to outsider succession (Borokhovich et al., 1996; Davidson, Worrell, & Dutia,
1993), while others have found either positive reactions to insider succession (Shen &
Cannella, 2003), or no relation between CEO origin and stock performance (Beatty &
Zajac, 1987). The variable “new CEO origin” was coded “1” if the new CEO was an
insider and “0” if s/he was an outsider. New CEOs who had been with their firms for two
years or less at the time of their appointments were classified as outsiders (Zhang et al.,
2004). All other CEOs were classified as insiders. Data were collected from the WSJ,
company press releases, and corporate proxy statements.

The stock market may react to CEO appointment decisions in different ways depending
on the power of the boards that make those decisions. To control for board power, I
included three commonly -used measures. Outsider ratio refers to the proportion of
independent outside directors on the board. Separate leadership structure equals one if the
CEO and the Board Chair positions are held by two individuals. Agency theory suggests
that boards with such a separate leadership structure are more powerful than boards with

93
a unitary leadership structure under which the CEO and the board chair positions are
assumed by the same person. Independent directors who have a financial stake in the firm
may be more motivated to monitor firm management (Hambrick & Jackson, 2000), so I
also included independent directors’ stock ownership as a control variable (measured as
the percentage of shares outstanding owned by all independent directors).

Inside directors’ role in corporate governance has been a topic of debate in previous
studies. Some researchers argue that insiders contribute to board effectiveness by virtue
of their firm-specific knowledge (Baysinger & Hoskisson, 1990), whereas others argue
that insiders may use their knowledge for their own personal interests rather than for the
benefits of shareholders (Weisbach, 1988). I included average board tenure of inside
directors as a control for inside directors’ experience.

4.3 Data Analysis
Standard event study methodology was employed to analyze stock market reaction to the
announcement of new CEO appointment (Dodd & Warner, 1983). The market model was
estimated using 255 days of daily returns, ending 46 days before the announcement date
based on the equally weighted CRSP index (Shen et al., 2003). The estimation was then
used to generate stock return prediction errors for the various event windows. The daily
prediction errors were summed to obtain the cumulative abnormal returns (CARs) for
individual firms, which were then averaged across sample firms to obtain mean CARs.

94
Hierarchical multiple regression analysis was performed to test all the research
hypotheses. There were two dependent variables. The first was the CARs for the two-day
window (0, 1). McWilliams and Siegel (1997) suggested that an event window should be
as short as possible because it is much more difficult to control for confounding effects
when long windows are used. Therefore, I chose the (0,1) window but the empirical
findings reported below were also robust for the (0, 2) and (0, 3) windows. The second
dependent variable -- post-succession performance, was the sum of standardized ROA
and ROE for the year following CEO succession.

For each dependent variable, I estimated three models as follows. Model 1 included the
control variables only. Model 2 added the six board experience (level and diversity)
variables to Model 1. The interaction terms between the contingency factor (industry
instability or prior firm performance) and the board experience variables were added in
Model 3a to Model 3f. Board experience variables and the moderator variable were
mean-centered prior to the creation of the interaction term to address the issue of
potential multicollinearity between the main effect and interaction terms (Aiken & West,
1991).

95
CHAPTER 5
RESULTS
5.1 Event Study Results
Table 2 provides some descriptions of the sample. It can be seen that the sample events
were distributed across years more or less evenly. The sample firms came from multiple
industries. The largest subgroup was from computer and electronic product
manufacturing industries (73 firms, accounting for approximately 30 percent of the
sample).
3

Table 3 shows mean CARs for different panels. For each panel the results for three event
windows [(0,1), (0,2), and (0,3), treating the announcement day as day 0] were reported.
Consistent with previous studies (Bonnier et al., 1989; Davidson et al., 1993; Furtado et
al., 1987; Huson et al., 2004; Weisbach, 1988), panel A shows that for the full sample,
the mean CARs were positive and the t-statistic values were significantly different from
zero for the 2-day and the 3-day windows, and the difference was marginally significant
for the 4-day window. Panel B reports the mean CARs for routine successions (N=184).
Eighty out of the 184 routine events were relay successions in which an heir apparent
who held the title President or COO (or both) and who had been with the focal firm for at
least 2 years was promoted to the CEO position and the old CEO remained on the board.
In the other 104 events, the old CEO also remained on the board but the new CEO was

3
A dummy variable was created with 1 equal to “computer and electronic product manufacturing firms”
and 0 otherwise. When it was added to regression analysis as a control variable, the results were very
similar to those obtained from the analysis without it. I also added four dummy variables to capture year
effect (with year 1999 as reference) and the results were largely similar. To save space, the computer-firm
and year variables are excluded from the results presented here.

96
either a non-heir insider or an outsider. It can be seen that firms experiencing routine
successions gained substantial positive abnormal returns for all the three event windows
[1.63% over the (0,1) window, 1.91% over the (0,2) window, and 1.81% over the (0,3)
window]. Moreover, for the (0,1) window, 102 events reported positive CARs and 82
events reported negative CARs. The generalized sign test was significant. The same was
found for the other two event windows. Positive stock price reactions to routine CEO
successions have been documented in other studies. For example, Shen and Cannella
(2003) examined 130 heir promotion events (relay succession) that occurred in a sample
of large, publicly traded U.S. corporations between 1988 and 1997 and found that CARs
over the (-1, +1) window were positive (0.92%) and significant (p<.001). The results of
Panel B were consistent with their findings.

Panel C shows that the mean CARs were negative for the subsample of 58 non-routine
successions, but the differences were not significant. This result was similar to that
reported by Warner and colleagues (1988). They studied 351 succession events involving
changes in the titles of CEO, president, and board chairperson in 269 firms listed on the
NYSE and AMEX from 1962 to 1978. There was a subsample of 56 events in which the
CEO was forced to resign (one type of non-routine departure defined in this study). The
stock reactions to these events were negative but not significant. Note that some studies
have reported positive and significant market reactions to CEO dismissals (Furtado et al.,
1987) or positive but not significant reactions to CEO resignations (Weisbach, 1988).

97
Table 2. Sample Distributions
(by Year, Succession Type, New CEO Origin, and Industry)
Description N Percent of
sample
Succession year
1999 58 23.97
2000 50 20.66
2001 54 22.31
2002 44 18.18
2003 36 14.88
Total 242 100
Succession type
Non-routine departure 58 23.97
Routine departure 184 76.03
Total 242 100
New CEO origin
Outsider 103 42.56
Insider 139 57.44
Total 242 100
Industry (NAICS)
311 Food Manufacturing 5 2.07
312 Beverage and Tobacco Product Manufacturing 5 2.07
313 Textile Mills 1 0.41
314 Textile Product Mills 1 0.41
315 Apparel Manufacturing 10 4.13
316 Leather and Allied Product Manufacturing 2 0.83
322 Paper Manufacturing 5 2.07
323 Printing and Related Support Activities 6 2.48
324 Petroleum and Coal Products Manufacturing 2 0.83
325 Chemical Manufacturing 29 11.98
326 Plastics and Rubber Products Manufacturing 6 2.48
327 Nonmetallic Mineral Product Manufacturing 2 0.83
331 Primary Metal Manufacturing 10 4.13
332 Fabricated Metal Product Manufacturing 6 2.48
333 Machinery Manufacturing 25 10.33
334 Computer and Electronic Product Manufacturing 73 30.17
335 Electrical Equipment, Appliance, and Component Manufacturing 12 4.96
336 Transportation Equipment Manufacturing 17 7.02
337 Furniture and Related Product Manufacturing 3 1.24
339 Miscellaneous Manufacturing 22 9.09
Total 242 100

98
Table 3. Stock Market Reactions to New CEO Appointment Announcements
Days N Mean CAR (%) Positive :
Negative
t-statistic
Panel A: All events
(0,1) 242 0.95
127:115
†

2.01*
(0,2) 242 0.97 133:109* 1.78*
(0,3) 242 0.91
128:114
†
1.52
†

Panel B: Routine Successions
(0,1) 184 1.63
102:82*
3.45***
(0,2) 184 1.91 108:76** 3.58***
(0,3) 184 1.81 100:84* 3.18***
Panel C: Non-routine Successions
(0,1) 58 -1.23 25:33 -0.99
(0,2) 58 -2.03 25:33
-1.39
†

(0,3) 58 -1.93 28:30 -1.15
Panel D: Outsider Successions
(0,1) 103 1.67
58:45
†

2.03*
(0,2) 103 1.34 54:49
1.39
†

(0,3) 103 0.88 51:52 0.85
Panel E: Insider Successions
(0,1) 139 0.41 69:70 0.75
(0,2) 139 0.69 79:60* 1.11
(0,3) 139 0.94 77:62*
1.32
†

Panel F: Routine Departure & Outsider Succession
(0,1) 72 2.64 44:28* 3.06**
(0,2) 72 2.66
41:31
†

2.57**
(0,3) 72 2.24 38:34 2.12*
Panel G: Routine Departure & Insider Succession
(0,1) 112 0.98 58:54 1.83*
(0,2) 112 1.44 67:45** 2.50**
(0,3) 112 1.53
62:50
†

2.38**
Panel H: Non-routine Departure & Outsider Succession
(0,1) 31 -0.58 14:17 -0.32
(0,2) 31 -1.71 13:18 -0.84
(0,3) 31 -2.29 13:18 -0.99
Panel H: Non-routine Departure & Insider Succession
(0,1) 27 -1.97 11:16 -1.17
(0,2) 27 -2.40 12:15 -1.14
(0,3) 27 -1.52 15:12 -0.61

† p < .10; * p < .05; ** p < .01; *** p < .001. All two-tailed t tests.

This table shows cumulative abnormal returns associated with announcements of new CEO appointments by sample
firms during 1999-2003. Announcement period abnormal returns associated with a sample of 242 new CEO
appointments at large, non-diversified manufacturing firms between 1999 and 2003. The abnormal returns were
calculated over three event windows (0,1) (0,2) and (0,3). Abnormal returns were calculated with the market model
parameters estimated over the 255-day period ending 46 days before the appointment announcement.

99
Panel D and E focus on the origins of new CEOs. When new CEOs were hired from
outside the firm (n=103), the mean CARs for the (0,1) window was positive (1.67%) and
significantly different from zero. The wealth effect for the (0,2) window was also positive
(1.34%) and marginally significant. In the literature CEO origin has been a widely
studied factor. The findings reported here are consistent with some previous studies. For
example, Warner and colleagues (1988) reported positive stock price responses to the 46
outsider succession events in their sample for the (-1,0) window. Lubatkin and colleagues
(1989) examined 477 CEO succession events at 357 firms during the 1971-85 period and
found that firms had gained substantial positive abnormal returns when the new CEOs
were hired from outside the firm. In particular, financially distressed firms that relied on
external recruitments have been found to receive strong positive responses from the
market (Bonnier et al., 1989; Davidson et al., 1993).

By contrast, the market reactions to insider successions in my sample were not very
impressive. As shown in Panel E, the mean CARs were positive but not significantly
different from zero. Although some studies reported positive and significant market
reactions to insider successions (Worrell, Davidson, & Glascock, 1993), it has also been
documented that inside successions were associated with positive but not significant
stock price reactions (similar to this study) (Chung, Lubatkin, Rogers, & Owers, 1987).

Some researchers have argued that the origin of the new CEO and the disposition of the
old CEO should be considered together in order to depict the nature of a succession event

100
more accurately (Borokhovich et al., 1996; Worrell et al., 1993). Following this
suggestion, I examined the sampled selection events in more details. The results are
shown in Panel F through Panel H. The most impressive pattern was that routine
successions seemed to be the driving force behind the positive market reactions. As
shown in panel F and panel G, regardless of the origin of the new CEO, investors showed
confidence in a firm if the succession was a smooth arrangement in which the old CEO
was not fired, resigned or left for other unexpected reasons. Also, more routine departures
were followed by insider promotions (N=112) than by outsider recruitments (N=72). By
contrast, non-routine successions in which the old CEO was fired or resigned recorded
negative mean CARs whether the successor was an outsider or an insider. Overall, the
univariate analysis in Table 3 shows that the stock market reactions to the new CEO
announcements were significant and these results supported the need for further cross-
sectional regression analysis of the determinants of the abnormal returns.

5.2 Regression Results
5.2.1 Descriptive Statistics
Table 4 shows descriptive statistics and correlations for the variables used in the study.
On average, each pair of independent directors had been working together on the focal
firm’s board for 4.24 years (s. d. = 2.88 years). Fifty-one percent of independent directors
also participated in the selection of the old CEO. Only 58 firms, about 24 percent of the
entire sample, had intra-industry independent directors serving on their boards of
directors. The number of these directors ranges from 1 to 3. The average number of CEO

101
Table 4. Mean, Standard Deviation, and Correlation
Mean s.d. 1 2 3 4 5 6 7 8 9 10
1 CAR (0,1) .01 .08
2 Post-succession performance .01 1.71-.09
3 Firm size 6.68 1.85.03 .16*
4 Firm age 3.50 .96-.12 .11 .33***
5 Industry instability .04 .03.08 -.09 -.03 .04
6 Prior firm performance .00 1.46.03 .17* .07 .16* .01
7 Prior industry performance .00 1.58 -.03 .14* .16* .27***-.04 .27***
8 TMT size 8.87 3.79 .01 .10 .52*** .18** -.15* .05 .12
9 # of non-smaller firms 42.23 66.57 .02 -.07 -.39*** -.33*** -.23*** -.17** -.35*** -.31***
10 Old CEO age 58.51 7.57 -.10 .15* .12 .25*** .19** .14* .12 .11 -.29***
11 Succession type .76 .43 .17** .09 .04 .04 -.03 -.04 -.04 .12 -.03 .25***
12 New CEO age 50.07 6.90 -.15* -.14* .10 .17* .13* -.06 .09 .03 -.26*** .10
13 New CEO origin .57 .50 -.07 .08 .13* .14* -.11 .08 .04 .20*** -.14* .13*
14 Outsider ratio .61 .18 -.10 -.08 .17** .29*** .07 .00 .02 .00 .02 .06
15 Director stock ownership .22 1.01 -.03 -.15* -.27*** -.12 -.09 -.22*** -.12 -.13* .11 -.06
16 Separate leadership .36 .48 .01 -.08 -.10 -.14* -.02 .04 -.12 -.09 .05 -.23***
17 Insiders' average board tenure 8.68 5.97 -.07 .17* -.08 .14* -.01 .05 -.03 -.04 .01 .24***
18 # of CEO directors 1.97 1.80 .04 -.06 .43*** .20*** .05 .05 .22*** .18** -.23*** .04
19 Intra-industry directors .24 .43 .05 -.07 -.02 .01 -.07 -.13* -.17** .01 .22*** -.17**
20 Co-working experience 4.24 2.88 .14 .01 .04 .14* .01 .02 .13* -.01 -.06 .22***
21 Task experience .51 .39 -.09 -.12 .13 -.01 -.06 -.07 .13* .09 -.06 -.14*
22 CEO experience diversity 9.29 6.60 .02 .16* .08 .04 .04 .01 .12 .00 -.10 .07
23 industry experience diversity .16 .28 .05 .03 .10 -.03 .13* .01 -.09 .06 .02 -.06

102
Table 4. Mean, Standard Deviation, and Correlation (Continued)
11 12 13 14 15 16 17 18 19 20 21 22
11 Succession type
12 New CEO age -.22***
13 New CEO origin .12 -.01
14 Outsider ratio .02 .14* .03
15 Director stock ownership -.01 .04 -.10 .01
16 Separate leadership -.31*** -.04 -.11 -.25*** .06
17 Insiders' average board tenure .18** -.09 .13* -.06 -.02 -.11
18 # of CEO directors -.05 .19** .09 .46*** .02 -.19** -.20***
19 Intra-industry directors .04 -.02 -.03 .20*** .07 -.03 -.14* -.02
20 Co-working experience .12 .01 .11 -.02 -.01 .02 .25*** -.05 -.07
21 Task experience -.28*** .10 .02 -.13* -.01 .30*** -.27*** .10 -.04 .10
22 CEO experience diversity -.09 .10 .05 .08 .08 -.03 .07 .21*** -.06 .00 -.04
23 industry experience diversity .09 -.07 .00 .22*** -.02 .01 -.11 -.01 .12 -.07 -.12 -.13*
N=242.
* p < .05
** p < .01
*** p < .001

103
directors is 1.97 (s.d.=1.80), with a range from 0 to 10. Some individual-level statistics
with respect to CEO directors not shown in Table 4 are also worth mentioning. There
were 813 CEO directors in the sample (accounting for approximately 59.4 percent of the
1,368 independent directors), who were further classified into two groups: directors who
were current CEOs of other companies (n=605) and directors who were retired CEOs of
other companies (n=208). Among the 208 retired CEO directors, about 79 percent (n=164)
had been retired for less than six years -- a relatively short period of time implying that
these directors’ CEO experience might still be relevant and useful.

With respect to board structural power and independence, the average outsider ratio was
0.61 (s.d. = .18), indicating a high degree of board independence in the sample. But
independent directors held only a small proportion of the firm’s shares (mean = 0.22%,
s.d. = 1.01%). In addition, CEO non-duality was not common – only about 36 percent of
the sample firms adopted a separate leadership structure. The departing CEOs in my
sample were 58.51 years old on average (s.d. = 7.57 years). The new CEOs were 50.57
years old on average (s.d, = 6.90 years).

Several significant correlations shown in Table 4 were interesting. For example, there
was a positive correlation between routine successions and CARs (r = .17, p <.01), but
the correlations between new CEO origin and firm performance were not significant.
Large firms tended to have more independent directors (r = .17, p < .01), larger TMTs (r
= .52, p < .001), but lower stock ownership by independent directors (r = -.27, p < .001).

104
Moreover, outsider-dominated boards were less likely to have a separate leadership
structure (r = -.25, p < .001), indicating that the two independence-increasing governance
mechanisms – outsider domination and separate leadership structure did not always co-
exist in the sample firms. Further, outsider ratio was positively related to industry
experience diversity (r = .22, p < .001) whereas separate leadership structure was
positively related to task experience (r = .30, p < .001). These numbers show that board
experience and board independence variables are related to one another in a complicated
way.

5.2.2 Hypothesis Testing
The regression results are presented in Table 5 through Table 8. The tables are arranged
in this way: Table 5 presents the results for the first dependent variable (DV) – CARs (0,
1) including the direct effects of board experience variables and the moderating effects of
industry instability. Table 6 includes the same independent variables as in Table 5, but
the dependent variable is post-succession accounting performance. The interaction effects
of board experience and prior firm performance on CARs (0,1) and post-succession
performance are shown in Table 7 and Table 8 respectively. Table 9 summarizes the
results of hypothesis testing.

105
Table 5. Board Experience and CARs, Industry Instability as Moderator
Model 1 Model 2 Model 3a Model 3b Model 3c
(Constant) 14.25*
a
(6.54) 17.77** (6.51) 21.54*** (6.63) 19.01** (6.53) 21.64*** (6.65)
Firm size 0.39 (0.36) 0.15 (0.38) 0.18 (0.38) 0.15 (0.38) 0.17 (0.38)
Firm age -0.67 (0.63) -0.67 (0.63) -0.76 (0.63) -0.68 (0.63) -0.68 (0.63)
Industry instability (A) 0.29* (0.17) 0.27
†
(0.17) 0.31* (0.17) 0.27
†
(0.17) 0.29
†
(0.17)
Prior firm performance 0.35 (0.38) 0.32 (0.38) 0.34 (0.37) 0.32 (0.38) 0.31 (0.38)
Prior industry performance 0.01 (0.37) -0.16 (0.37) -0.18 (0.37) -0.17 (0.37) -0.16 (0.37)
TMT size 0.00 (0.16) 0.05 (0.16) 0.02 (0.16) 0.05 (0.16) 0.04 (0.16)
# of non-smaller firms 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01)
Old CEO age -0.14* (0.08) -0.17* (0.08) -0.19** (0.08) -0.17* (0.08) -0.18* (0.08)
Succession type 3.74** (1.35) 3.06* (1.36) 3.01* (1.35) 3.03* (1.37) 3.03* (1.36)
New CEO age -0.11
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08)
New CEO origin -0.98 (1.08) -1.28 (1.07) -1.13 (1.06) -1.28 (1.07) -1.19 (1.08)
Outsider ratio -3.70 (3.09) -7.14* (3.52) -7.88* (3.51) -7.19* (3.53) -7.15* (3.52)
Director stock ownership 0.03 (0.54) -0.21 (0.54) -0.24 (0.54) -0.20 (0.55) -0.22 (0.54)
Separate leadership -0.14 (1.19) 0.09 (1.22) -0.03 (1.21) 0.08 (1.22) 0.16 (1.23)
Insiders' average board tenure -0.08 (0.09) -0.16
†
(0.10) -0.13
†
(0.10) -0.15
†
(0.10) -0.15
†
(0.10)
# of CEO directors (B) 0.63* (0.37) 0.77* (0.38) 0.64* (0.38) 0.63* (0.38)
Intra-industry directors (C) 0.97 (1.27) 0.87 (1.26) 1.01 (1.28) 0.96 (1.27)
Co-working experience (D) 0.65***(0.19) 0.65***(0.19) 0.65*** (0.19) 0.65*** (0.19)
Task experience (E) -2.72* (1.52) -2.38
†
(1.52) -2.74* (1.53) -2.76* (1.52)
CEO experience diversity (F) 0.06 (0.08) 0.06 (0.08) 0.06 (0.08) 0.07 (0.08)
Industry experience diversity (G) 0.45 (1.96) 0.33 (1.94) 0.43 (1.96) 0.44 (1.96)
AXB -0.17* (0.09)
AXC 0.09 (0.39)
AXD -0.04 (0.05)
R squared 0.10 0.17 0.18 0.17 0.17
Adjusted R squared 0.04 0.09 0.10 0.08 0.08
R squared change 0.07*
b
0.02*
c
0.00
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=242. All one-tailed t tests.

106
Table 5. Board Experience and CARs, Industry Instability as Moderator (Continued)
Model 1 Model 2 Model 3d Model 3e Model 3f
(Constant) 14.25*
a
(6.54) 17.77** (6.51) 17.14** (6.48) 19.52** (6.44) 18.87** (6.52)
Firm size 0.39 (0.36) 0.15 (0.38) 0.14 (0.38) 0.14 (0.38) 0.14 (0.38)
Firm age -0.67 (0.63) -0.67 (0.63) -0.65 (0.63) -0.76 (0.62) -0.70 (0.63)
Industry instability (A) 0.29* (0.17) 0.27
†
(0.17) 0.26
†
(0.17) 0.35* (0.17) 0.27
†
(0.17)
Prior firm performance 0.35 (0.38) 0.32 (0.38) 0.33 (0.38) 0.32 (0.37) 0.34 (0.38)
Prior industry performance 0.01 (0.37) -0.16 (0.37) -0.16 (0.37) -0.19 (0.37) -0.16 (0.37)
TMT size 0.00 (0.16) 0.05 (0.16) 0.04 (0.16) 0.04 (0.16) 0.04 (0.16)
# of non-smaller firms 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01)
Old CEO age -0.14* (0.08) -0.17* (0.08) -0.18* (0.08) -0.18** (0.08) -0.18* (0.08)
Succession type 3.74** (1.35) 3.06* (1.36) 3.12* (1.36) 3.01* (1.34) 2.96* (1.37)
New CEO age -0.11
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08)
New CEO origin -0.98 (1.08) -1.28 (1.07) -1.22 (1.07) -0.97 (1.07) -1.12 (1.09)
Outsider ratio -3.70 (3.09) -7.14* (3.52) -7.12* (3.52) -7.02* (3.48) -6.96* (3.53)
Director stock ownership 0.03 (0.54) -0.21 (0.54) -0.23 (0.54) -0.21 (0.54) -0.18 (0.54)
Separate leadership -0.14 (1.19) 0.09 (1.22) 0.17 (1.23) 0.02 (1.21) 0.07 (1.22)
Insiders' average board tenure -0.08 (0.09) -0.16
†
(0.10) -0.16
†
(0.10) -0.12 (0.10) -0.15
†
(0.10)
# of CEO directors (B) 0.63* (0.37) 0.65* (0.38) 0.67* (0.37) 0.64* (0.38)
Intra-industry directors (C) 0.97 (1.27) 1.03 (1.27) 1.14 (1.25) 0.98 (1.27)
Co-working experience (D) 0.65***(0.19) 0.65***(0.19) 0.66*** (0.19) 0.64*** (0.19)
Task experience (E) -2.72* (1.52) -2.71* (1.52) -2.29
†
(1.51) -2.65* (1.52)
CEO experience diversity (F) 0.06 (0.08) 0.07 (0.08) 0.04 (0.08) 0.06 (0.08)
Industry experience diversity (G) 0.45 (1.96) 0.36 (1.96) 0.17 (1.94) -0.21 (2.12)
AXE -0.27 (0.39)
AXF -0.06** (0.02)
AXG 0.54 (0.67)
R squared 0.10 0.17 0.17 0.19 0.17
Adjusted R squared 0.04 0.09 0.08 0.11 0.08
R squared change 0.07*
b
0.00
c
0.02*
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=242. All one-tailed t tests.

107
Table 6. Board Experience and Post-Succession Performance, Industry Instability as Moderator
Model 1 Model 2 Model 3a Model 3b Model 3c
(Constant) -85.1
a
(148.8) -114.0 (149.8) -196.0 (155.1) -131.2 (151.8) -151.8 (153.7)
Firm size 14.14* (7.74) 18.22* (8.33) 17.89* (8.31) 18.67* (8.36) 17.50* (8.37)
Firm age 6.70 (14.85) 6.72 (14.91) 7.07 (14.86) 7.21 (14.93) 6.98 (14.91)
Industry instability (A) -4.59 (4.01) -5.48
†
(4.05) -6.21
†
(4.07) -5.96
†
(4.10) -5.68
†
(4.06)
Prior firm performance 12.38
†
(9.28) 13.13
†
(9.33) 13.18
†
(9.29) 12.54
†
(9.36) 13.64
†
(9.34)
Prior industry performance 8.69 (7.82) 10.82
†
(8.03) 10.90
†
(8.00) 11.09
†
(8.04) 10.64
†
(8.03)
TMT size -0.82 (3.55) -0.40 (3.53) -0.07 (3.53) -0.69 (3.55) -0.28 (3.53)
# of non-smaller firms 0.08 (0.22) 0.10 (0.23) 0.08 (0.23) 0.09 (0.23) 0.09 (0.23)
Old CEO age 2.61
†
(1.78) 2.47
†
(1.82) 2.70
†
(1.82) 2.38
†
(1.82) 2.64
†
(1.82)
Succession type 10.08 (30.81) 9.92 (31.65) 9.21 (31.55) 9.50 (31.68) 10.19 (31.66)
New CEO age -3.10
†
(1.90) -2.79
†
(1.90) -2.52
†
(1.90) -2.93
†
(1.91) -2.88
†
(1.90)
New CEO origin 4.50 (24.04) 3.65 (23.96) 2.27 (23.90) 3.97 (23.98) 0.90 (24.12)
Outsider ratio -72.13 (70.85) -49.85 (83.42) -32.28 (83.97) -43.11 (83.86) -50.69 (83.43)
Director stock ownership -11.35 (13.59) -8.37 (13.63) -8.07 (13.58) -9.04 (13.66) -7.48 (13.66)
Separate leadership -11.57 (26.10) -7.22 (27.03) -5.32 (26.97) -7.21 (27.05) -9.50 (27.13)
Insiders' average board tenure 3.30
†
(2.04) 2.22 (2.17) 1.81 (2.18) 2.04 (2.18) 2.23 (2.17)
# of CEO directors (B) -12.67
†
(8.66) -15.35* (8.82) -13.61
†
(8.74) -12.53
†
(8.66)
Intra-industry directors (C) -8.83 (28.86) -9.32 (28.77) -11.67 (29.08) -9.64 (28.87)
Co-working experience (D) -3.48 (4.49) -3.22 (4.48) -3.30 (4.50) -4.06 (4.53)
Task experience (E) -33.90 (35.02) -39.99 (35.15) -33.00 (35.07) -29.08 (35.37)
CEO experience diversity (F) 4.28** (1.78) 4.46** (1.78) 4.45** (1.80) 4.24** (1.79)
Industry experience diversity (G) 40.01 (42.58) 43.28 (42.50) 42.57 (42.72) 40.78 (42.59)
AXB 3.01 (2.01)
AXC -8.07 (9.58)
AXD 1.26 (1.28)
R squared 0.14 0.18 0.19 0.19 0.19
Adjusted R squared 0.07 0.09 0.10 0.09 0.09
R squared change 0.04
†b
0.01
c
0.01
c
0.01
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=214. All one-tailed t tests.

108
Table 6. Board Experience and Post-Succession Performance, Industry Instability as Moderator (Continued)
Model 1 Model 2 Model 3d Model 3e Model 3f
(Constant) -85.1
a
(148.8) -114.0 (149.8) -183.2 (149.4) -98.4 (151.1) -128.9 (151.3)
Firm size 14.14* (7.74) 18.22* (8.33) 18.51* (8.27) 17.94* (8.35) 18.22* (8.36)
Firm age 6.70 (14.85) 6.72 (14.91) 9.49 (14.87) 6.97 (14.93) 6.72 (14.95)
Industry instability (A) -4.59 (4.01) -5.48
†
(4.05) -6.88* (4.09) -5.74
†
(4.07) -5.48
†
(4.07)
Prior firm performance 12.38
†
(9.28) 13.13
†
(9.33) 13.84
†
(9.26) 12.89
†
(9.34) 13.14
†
(9.36)
Prior industry performance 8.69 (7.82) 10.82
†
(8.03) 11.05
†
(7.97) 10.85
†
(8.04) 10.82
†
(8.05)
TMT size -0.82 (3.55) -0.40 (3.53) -0.74 (3.51) -0.42 (3.54) -0.40 (3.54)
# of non-smaller firms 0.08 (0.22) 0.10 (0.23) 0.12 (0.23) 0.10 (0.23) 0.10 (0.23)
Old CEO age 2.61
†
(1.78) 2.47
†
(1.82) 2.31 (1.80) 2.54
†
(1.82) 2.47
†
(1.82)
Succession type 10.08 (30.81) 9.92 (31.65) 17.42 (31.65) 9.70 (31.68) 9.92 (31.76)
New CEO age -3.10
†
(1.90) -2.79
†
(1.90) -2.43 (1.89) -2.69
†
(1.90) -2.79
†
(1.90)
New CEO origin 4.50 (24.04) 3.65 (23.96) 6.68 (23.83) 2.56 (24.02) 3.67 (24.53)
Outsider ratio -72.13 (70.85) -49.85 (83.42) -43.07 (82.88) -53.24 (83.61) -49.83 (83.69)
Director stock ownership -11.35 (13.59) -8.37 (13.63) -9.19 (13.53) -9.54 (13.72) -8.37 (13.67)
Separate leadership -11.57 (26.10) -7.22 (27.03) -3.49 (26.90) -5.23 (27.17) -7.22 (27.11)
Insiders' average board tenure 3.30
†
(2.04) 2.22 (2.17) 2.02 (2.15) 1.99 (2.19) 2.22 (2.19)
# of CEO directors (B) -12.67
†
(8.66) -12.07
†
(8.60) -12.50
†
(8.67) -12.67
†
(8.71)
Intra-industry directors (C) -8.83 (28.86) -7.89 (28.65) -10.69 (28.98) -8.83 (28.95)
Co-working experience (D) -3.48 (4.49) -4.21 (4.47) -3.46 (4.49) -3.48 (4.52)
Task experience (E) -33.90 (35.02) -33.06 (34.77) -36.88 (35.26) -33.89 (35.15)
CEO experience diversity (F) 4.28** (1.78) 4.32** (1.77) 4.53** (1.81) 4.28** (1.80)
Industry experience diversity (G) 40.01 (42.58) 34.87 (42.35) 41.85 (42.68) 39.92 (47.34)
AXE -19.16* (9.78)
AXF 0.51 (0.65)
AXG 0.07 (15.19)
R squared 0.14 0.18 0.20 0.19 0.18
Adjusted R squared 0.07 0.09 0.11 0.09 0.09
R squared change 0.04
†b
0.02
†c
0.01
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=214. All one-tailed t tests.

109
Direct Effects of Board Experience
Hypothesis 1a predicts a positive relationship between the number of CEO directors on
the board and stock market reactions to new CEO appointments. This hypothesis was
supported. As shown in Model 2 (Table 5 & 7), the coefficient for this CEO experience
measure was 0.63 (p < .05). This direct effect held in the two sets of moderating-effect
models (Model 3a – Model 3f in Table 5 & 7). Hypothesis 1b predicts a positive
relationship between the number of CEO directors and post-succession accounting
performance. This hypothesis, however, was not supported. Model 2 in Table 6 and Table
8 shows that the number of CEO directors had a marginally significant and negative
effect on post-succession performance (b = -12.67, p < .10).

Hypothesis 2a and Hypothesis 2b predict a positive effect of the level of directors’
industry-specific experience on CARs and post-succession performance respectively.
These hypotheses, however, were not supported. Whether or not the board had intra-
industry director(s) appeared to have little impact on CEO selection performance.
Hypothesis 3a and 3b focus on the positive effects of co-working experience on CARs
and post-succession performance. Consistent with Hypothesis 3a, co-working experience
showed a strong positive effect on CARs (b=0.65, p < .001, Model 2 in Table 5 & 7),
indicating that investors responded favorably to CEO selections made by boards with
high levels of co-working experience. But Hypothesis 3b was not supported – Model 2 in
Table 6 and Table 8 showed that the coefficient of co-working experience was negative
(although not statistically significant) when the dependent variable was post-succession

110
performance. Similarly, task experience was found to have a negative and significant
effect on CARs, contrary to Hypothesis 4a. Hypothesis 4b was not supported, either.
These results will be further discussed in the next chapter.

Hypothesis 5a-5b and Hypothesis 6a-6b concern performance effects of CEO experience
diversity and industry experience diversity. Although Hypothesis 5a was not supported,
Hypothesis 5b received strong support, indicating a positive relationship between CEO
experience diversity and post-succession performance (b=4.28, p < .01, Model 2 in Table
6 & 8). Unfortunately, the results did not support Hypothesis 6a and 6b that propose
positive effects of industry experience diversity on CEO selection performance.

Overall, Model 2 in Table 5 reported a R-squared value of 0.17, representing an increase
of 0.07 (p < .05) compared to the R-squared value of 0.10 for Model 1 that included
control variables only. This result showed that the variables measuring board experience,
as a group, had a significant impact on CARs, even after controlling for effects of key
environmental / organizational factors, board power and incentive, CEO characteristics,
and succession event characteristics. When post-succession performance was used as the
dependent variable, Model 2 reported a R-squared value of 0.18, representing an increase
of 0.04 from Model 1.

111
Moderating Effects of Industry Instability
Model 3a through Model 3f in Table 5 (for CARs) and Table 6 (for post-succession
performance) tested the interaction effects between industry instability and various board
experience variables.

Hypothesis 7 focuses on the levels of the four types of experience and how their effects
on CARs and post-succession performance are moderated by industry instability. In
support of this hypothesis, the number of CEO directors showed a stronger positive effect
on CARs in stable industries than in unstable industries (Model 3a in Table 5). The
regression coefficient for the interaction term between industry instability and the number
of CEO directors is -0.17 (p < .05). To facilitate interpretation of this result, I plotted the
interaction effect in Figures 2(A). All interaction plots were created following the
approach proposed by Aiken and West (1991). Take Figure 2 (A) as an example. All
control and independent variables in Model 3a, Table 5 except for industry instability (A)
and the number of CEO directors (B) were constrained to their sample mean values. Both
A and B took the values of one standard deviation above and below their means. As
shown in the figure, in low-instability (or relatively stable) industries, the number of CEO
directors was positively associated with CARs. But in high-instability industries, the
effect was not obvious. This pattern is consistent with the argument that investors may
attach different values to directors’ past work experience for firms operating in different
industries. Historical experience is seen as more valuable in a stable environment than in
a rapidly changing environment. Following Aiken and West’s suggestion, a simple

112
regression slope analysis was also conducted to further reveal the effects of CEO
experience on CARs under different industry conditions. The simple slope of the number
of CEO directors was 1.33 (standard error or s.e. = .51) in stable industries, which was
significantly different from zero ( p <.01). In contrast, the simple slope was 0.20 (s.e. =
0.43) in unstable industries, which is not significantly different from zero. These results
showed that the number of CEO directors was positively associated with CARs when
firms were operated in stable industries, but it had little impact on CARs when firms were
operated in unstable industries.

According to Hypothesis 8, CEO experience diversity and industry experience diversity
will have a greater positive effect on CEO selection performance in unstable industries
because directors with diverse job and industry experience are better able to handle
environmental changes. However, Model 3e and Model 3f in Table 5 did not support this
hypothesis. Contrary to the hypothesis, the interaction effect between CEO experience
diversity and industry instability appeared to be negative and significant. As shown in
Figure 2(B), CEO experience diversity was positively related to CARs in stable industries
(simple slope = 0.23, s.e. = 0.10) but negatively related to CARs in unstable industries
(simple slope = -0.15, s.e. = 0.12). Thus, evidence did not support the interaction effects
between industry instability and other board experience variables.

113
Figure 2. Interaction between CEO Experience and Industry Instability

(A)

0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
Low High
# of CEO Directors
CARs (0,1)
Low industry instability
High industry instability

(B)

-0.03
-0.02
-0.01
0
0.01
0.02
0.03
Low High
CEO Experience Diversity
CARs (0,1)
Low industry instability
High industry instability

114
Moderating Effects of Prior Firm Performance
Prior firm performance (or pre-succession performance) may also moderate the
relationships between board experience variables and CEO selection performance. Model
3a through Model 3f in Table 7 (for CARs) and Table 8 (for post-succession performance)
tested the moderating effects of pre-succession performance. Hypothesis 9 predicts that
the positive relationships between the levels of the four board experience variables and
CEO selection performance will be weaker for firms with lower pre-succession
performance. This hypothesis received partial support. Specifically, Model 3a in Table 7
reported a significant interaction effect between prior firm performance and the number
of CEO directors (b=0.38, p < .05). The effect was plotted in Figure 3(A). The simple
slope analysis showed that in well-performing firms the number of CEO directors was
positively related to CARs (simple slope = 1.18, s.e. = 0.49, p < .05). By contrast,
although the number of CEO directors was still positively related to CARs in poorly-
performing firms, the simple slope was not statistically significant (simple slope = 0.12,
s.e. = 0.49, n.s.). Also shown in Figure 5, task experience was found to have a marginally
significant and negative effect on post-succession performance in low-performance firms
(simple slope = 96.89, s.e. = 54.67, p < .10). But in high-performance firms, the effect of
task experience was positive although not significant (simple slope = 12.03, s.e. = 48.60).
These results suggest that experience with the previous CEO selection task might be
valuable when the firm had been performing well under the old CEO’s leadership, but
task experience became devalued when the firm had been performing poorly.

115
Hypothesis 10 suggests that CEO experience diversity and industry experience diversity
should be positively related to CEO selection performance and the effects should be
stronger in firms with lower pre-succession performance. Results generally supported this
hypothesis. First, Model 3e in Table 7 reported a marginally significant interaction effect
of CEO experience diversity and pre-succession performance on CARs (b = -0.22, p
< .10). As illustrated in Figure 3(B), CEO experience diversity was positively related to
CARs in low-performance firms (simple slope = 0.37, s.e. = 0.22, p < .10) but negatively
related to CARs in high-performance firms (simple slope = -0.26, s.e. = 0.23, n.s.).

Second, Model 3e in Table 8 showed a significant interaction effect between CEO
experience diversity and pre-succession firm performance (b = -11.27, p < .01). Figure
3(C) shows that CEO experience diversity had a strong positive effect on post-succession
performance when pre-succession performance was low (simple slope of CEO experience
diversity = 20.72, s.e. = 6.16, p < .01). By contrast, the effect was significant but negative
in firms with high pre-succession performance (simple slope = -12.18, s.e. = 6.13, p
< .05). Third, also consistent with Hypothesis 10, Model 3f in Table 7 reported a negative
and significant interaction effect of pre-succession performance and industry experience
diversity on CARs (b = -6.27, p < .01). As illustrated in Figure 4, industry experience
diversity was positively related to CARs in low-performance firms (simple slope = 10.17,
s.e., = 4.16, p < .05). But this effect was reversed in direction in high-performance firms
(simple slope = -8.07, s.e. = 3.84, p < .05). Taken together, these results supported
Hypothesis 10 by showing that experience diversity was valuable in firms that had been

116
having performance problems just prior to CEO succession. However, in well-performing
firms too much diversity might cause unnecessary instability and hence hurt future firm
performance.

117
Table 7. Board Experience and CARs, Prior Performance as Moderator
Model 1 Model 2 Model 3a Model 3b Model 3c
(Constant) 14.25*
a
(6.54) 17.77** (6.51) 19.28** (6.60) 18.64** (6.48) 20.73** (6.64)
Firm size 0.39 (0.36) 0.15 (0.38) 0.12 (0.38) 0.31 (0.37) 0.10 (0.38)
Firm age -0.67 (0.63) -0.67 (0.63) -0.70 (0.63) -0.78 (0.61) -0.68 (0.63)
Industry instability 0.29* (0.17) 0.27
†
(0.17) 0.26
†
(0.17) 0.25
†
(0.17) 0.26
†
(0.17)
Prior firm performance (A) 0.35 (0.38) 0.32 (0.38) 0.55
†
(0.40) 0.03 (0.50) 0.45 (0.40)
Prior industry performance 0.01 (0.37) -0.16 (0.37) -0.43 (0.40) -0.08 (0.37) -0.25 (0.39)
TMT size 0.00 (0.16) 0.05 (0.16) 0.05 (0.16) 0.01 (0.16) 0.05 (0.16)
# of non-smaller firms 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01)
Old CEO age -0.14* (0.08) -0.17* (0.08) -0.17* (0.08) -0.17* (0.08) -0.18* (0.08)
Succession type 3.74** (1.35) 3.06* (1.36) 3.07* (1.35) 3.31** (1.35) 2.99* (1.36)
New CEO age -0.11
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.15* (0.08) -0.12
†
(0.08)
New CEO origin -0.98 (1.08) -1.28 (1.07) -1.18 (1.07) -1.21 (1.06) -1.22 (1.07)
Outsider ratio -3.70 (3.09) -7.14* (3.52) -7.47* (3.51) -6.43* (3.41) -7.14* (3.52)
Director stock ownership 0.03 (0.54) -0.21 (0.54) -0.02 (0.55) -0.37 (0.53) -0.27 (0.55)
Separate leadership -0.14 (1.19) 0.09 (1.22) 0.10 (1.22) 0.14 (1.18) 0.11 (1.22)
Insiders' average board tenure -0.08 (0.09) -0.16
†
(0.10) -0.15
†
(0.10) -0.14
†
(0.10) -0.15
†
(0.10)
# of CEO directors (B) 0.63* (0.37) 0.63* (0.37) 0.38 (0.37) 0.65* (0.38)
Intra-industry directors (C) 0.97 (1.27) 1.13 (1.26) 1.32 (1.23) 0.90 (1.27)
Co-working experience (D) 0.65*** (0.19) 0.65*** (0.19) 0.66*** (0.19) 0.67*** (0.19)
Task experience (E) -2.72* (1.52) -2.78* (1.51) -2.35
†
(1.48) -2.80* (1.52)
CEO experience diversity (F) 0.06 (0.08) 0.06 (0.08) 0.12
†
(0.08) 0.07 (0.08)
Industry experience diversity (G) 0.45 (1.96) 0.32 (1.95) 0.25 (1.90) 0.59 (1.96)
AXB 0.38* (0.23)
AXC 0.62 (0.77)
AXD 0.19 (0.22)
R squared 0.10 0.17 0.18 0.17 0.17
Adjusted R squared 0.04 0.09 0.09 0.09 0.08
R squared change 0.07*
b
0.01
†c
0.00
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=242. All one-tailed t tests.

118
Table 7. Board Experience and CARs, Prior Performance as Moderator (Continued)
Model 1 Model 2 Model 3d Model 3e Model 3f
(Constant) 14.25*
a
(6.54) 17.77** (6.51) 16.47** (6.46) 19.05** (6.50) 19.26** (6.44)
Firm size 0.39 (0.36) 0.15 (0.38) 0.15 (0.38) 0.18 (0.38) 0.08 (0.38)
Firm age -0.67 (0.63) -0.67 (0.63) -0.69 (0.63) -0.63 (0.63) -0.84
†
(0.63)
Industry instability 0.29* (0.17) 0.27
†
(0.17) 0.26
†
(0.17) 0.26
†
(0.17) 0.20 (0.17)
Prior firm performance (A) 0.35 (0.38) 0.32 (0.38) 0.24 (0.40) 0.21 (0.38) 0.04 (0.39)
Prior industry performance 0.01 (0.37) -0.16 (0.37) -0.21 (0.38) -0.12 (0.37) -0.09 (0.37)
TMT size 0.00 (0.16) 0.05 (0.16) 0.04 (0.16) 0.04 (0.16) 0.03 (0.16)
# of non-smaller firms 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01) 0.00 (0.01)
Old CEO age -0.14* (0.08) -0.17* (0.08) -0.18* (0.08) -0.18* (0.08) -0.17* (0.08)
Succession type 3.74** (1.35) 3.06* (1.36) 2.98* (1.37) 2.81* (1.37) 2.60* (1.35)
New CEO age -0.11
†
(0.08) -0.12
†
(0.08) -0.12
†
(0.08) -0.13
†
(0.08) -0.11
†
(0.08)
New CEO origin -0.98 (1.08) -1.28 (1.07) -1.23 (1.07) -1.33 (1.07) -1.19 (1.06)
Outsider ratio -3.70 (3.09) -7.14* (3.52) -7.06* (3.52) -7.04* (3.51) -6.78* (3.48)
Director stock ownership 0.03 (0.54) -0.21 (0.54) -0.28 (0.55) -0.22 (0.54) -0.45 (0.54)
Separate leadership -0.14 (1.19) 0.09 (1.22) 0.03 (1.23) 0.08 (1.22) -0.15 (1.21)
Insiders' average board tenure -0.08 (0.09) -0.16
†
(0.10) -0.15
†
(0.10) -0.16
†
(0.10) -0.15
†
(0.10)
# of CEO directors (B) 0.63* (0.37) 0.62
†
(0.38) 0.70* (0.38) 0.66* (0.37)
Intra-industry directors (C) 0.97 (1.27) 1.01 (1.27) 1.22 (1.27) 0.71 (1.25)
Co-working experience (D) 0.65***(0.19) 0.64***(0.19) 0.66*** (0.19) 0.63*** (0.19)
Task experience (E) -2.72* (1.52) -2.75* (1.52) -2.85* (1.52) -2.74* (1.50)
CEO experience diversity (F) 0.06 (0.08) 0.07 (0.08) 0.05 (0.08) 0.07 (0.08)
Industry experience diversity (G) 0.45 (1.96) 0.43 (1.96) 0.41 (1.95) 1.05 (1.95)
AXE 0.68 (1.13)
AXF -0.22
†
(0.15)
AXG -6.27** (2.45)
R squared 0.10 0.17 0.17 0.17 0.19
Adjusted R squared 0.04 0.09 0.08 0.09 0.11
R squared change 0.07*
b
0.00
c
0.00 0.02*
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=242. All one-tailed t tests.

119
Table 8. Board Experience and Post-Succession Performance, Prior Performance as Moderator
Model 1 Model 2 Model 3a Model 3b Model 3c
(Constant) -85.1
a
(148.8) -114.0 (149.8) -135.8 (153.2) -124.6 (140.3) -126.9 (152.8)
Firm size 14.14* (7.74) 18.22* (8.33) 18.45* (8.38) 10.41
†
(7.69) 17.61* (8.46)
Firm age 6.70 (14.85) 6.72 (14.91) 6.90 (14.95) 4.89 (13.60) 6.29 (14.97)
Industry instability -4.59 (4.01) -5.48
†
(4.05) -5.42
†
(4.07) -8.90* (3.82) -5.50
†
(4.06)
Prior firm performance (A) 12.38
†
(9.28) 13.13
†
(9.33) 11.27 (10.93) 26.44* (11.76) 14.65
†
(9.95)
Prior industry performance 8.69 (7.82) 10.82
†
(8.03) 12.26
†
(9.17) 1.64 (7.74) 9.74 (8.40)
TMT size -0.82 (3.55) -0.40 (3.53) -0.43 (3.54) -0.26 (3.22) -0.35 (3.54)
# of non-smaller firms 0.08 (0.22) 0.10 (0.23) 0.11 (0.23) -0.04 (0.21) 0.09 (0.23)
Old CEO age 2.61
†
(1.78) 2.47
†
(1.82) 2.45
†
(1.82) 2.31
†
(1.74) 2.45
†
(1.82)
Succession type 10.08 (30.81) 9.92 (31.65) 8.57 (31.99) -5.67 (29.70) 9.53 (31.73)
New CEO age -3.10
†
(1.90) -2.79
†
(1.90) -2.86
†
(1.92) -0.85 (1.78) -2.69
†
(1.91)
New CEO origin 4.50 (24.04) 3.65 (23.96) 3.24 (24.05) -3.90 (22.61) 4.46 (24.08)
Outsider ratio -72.13 (70.85) -49.85 (83.42) -46.73 (84.14) -56.14 (75.80) -49.88 (83.59)
Director stock ownership -11.35 (13.59) -8.37 (13.63) -10.36 (14.93) -5.62 (12.91) -9.23 (13.79)
Separate leadership -11.57 (26.10) -7.22 (27.03) -7.50 (27.10) 0.10 (24.59) -6.40 (27.15)
Insiders' average board tenure 3.30
†
(2.04) 2.22 (2.17) 2.16 (2.18) 1.53 (2.00) 2.26 (2.17)
# of CEO directors (B) -12.67
†
(8.66) -12.64
†
(8.68) -6.41 (7.99) -12.42
†
(8.70)
Intra-industry directors (C) -8.83 (28.86) -9.17 (28.94) -17.97 (26.47) -9.57 (28.97)
Co-working experience (D) -3.48 (4.49) -3.38 (4.51) 2.08 (4.38) -3.05 (4.60)
Task experience (E) -33.90 (35.02) -34.59 (35.17) -42.90
†
(32.13) -35.86 (35.37)
CEO experience diversity (F) 4.28** (1.78) 4.25** (1.79) 3.62* (1.67) 4.30** (1.79)
Industry experience diversity (G) 40.01 (42.58) 39.93 (42.68) 39.77 (38.78) 40.77 (42.70)
AXB -2.00 (6.06)
AXC -29.38
†
(18.70)
AXD 2.20 (4.94)
R squared 0.14 0.18 0.18 0.18 0.18
Adjusted R squared 0.07 0.09 0.09 0.08 0.09
R squared change 0.05
†b
0.00
c
0.00
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=214. All one-tailed t tests.

120
Table 8. Board Experience and Post-Succession Performance, Prior Performance as Moderator (Continued)
Model 1 Model 2 Model 3d Model 3e Model 3f
(Constant) -85.1
a
(148.8) -114.0 (149.8) -130.6 (147.9) -60.0 (147.2) -107.1 (149.9)
Firm size 14.14* (7.74) 18.22* (8.33) 18.40* (8.32) 19.06* (8.20) 18.38* (8.42)
Firm age 6.70 (14.85) 6.72 (14.91) 4.53 (14.96) 4.81 (14.67) 6.73 (14.95)
Industry instability -4.59 (4.01) -5.48
†
(4.05) -5.99
†
(4.06) -5.49
†
(3.98) -5.38
†
(4.12)
Prior firm performance (A) 12.38
†
(9.28) 13.13
†
(9.33) 10.15 (9.56) 13.40
†
(9.17) 13.44
†
(9.58)
Prior industry performance 8.69 (7.82) 10.82
†
(8.03) 8.23 (8.23) 12.55
†
(7.92) 10.63
†
(8.15)
TMT size -0.82 (3.55) -0.40 (3.53) -0.58 (3.53) -0.52 (3.47) -0.38 (3.55)
# of non-smaller firms 0.08 (0.22) 0.10 (0.23) 0.05 (0.23) 0.14 (0.22) 0.10 (0.23)
Old CEO age 2.61
†
(1.78) 2.47
†
(1.82) 2.48
†
(1.81) 2.37
†
(1.79) 2.46
†
(1.82)
Succession type 10.08 (30.81) 9.92 (31.65) 5.71 (31.73) 5.24 (31.16) 9.80 (31.74)
New CEO age -3.10
†
(1.90) -2.79
†
(1.90) -2.68
†
(1.90) -2.98
†
(1.87) -2.82
†
(1.91)
New CEO origin 4.50 (24.04) 3.65 (23.96) 8.30 (24.15) 0.64 (23.57) 3.25 (24.17)
Outsider ratio -72.13 (70.85) -49.85 (83.42) -38.57 (83.64) -46.08 (82.00) -49.91 (83.63)
Director stock ownership -11.35 (13.59) -8.37 (13.63) -13.35 (14.08) -3.73 (13.50) -7.94 (13.96)
Separate leadership -11.57 (26.10) -7.22 (27.03) -7.74 (26.97) -1.26 (26.65) -7.20 (27.10)
Insiders' average board tenure 3.30
†
(2.04) 2.22 (2.17) 2.50 (2.17) 2.18 (2.13) 2.20 (2.18)
# of CEO directors (B) -12.67
†
(8.66) -13.55
†
(8.67) -9.75 (8.58) -12.72
†
(8.69)
Intra-industry directors (C) -8.83 (28.86) -5.31 (28.91) 1.56 (28.61) -8.45 (29.05)
Co-working experience (D) -3.48 (4.49) -3.66 (4.48) -3.44 (4.41) -3.43 (4.51)
Task experience (E) -33.90 (35.02) -39.50 (35.19) -44.93
†
(34.65) -34.05 (35.13)
CEO experience diversity (F) 4.28** (1.78) 4.33** (1.78) 4.31** (1.75) 4.29** (1.79)
Industry experience diversity (G) 40.01 (42.58) 35.83 (42.59) 37.94 (41.86) 39.68 (42.75)
AXE 36.05
†
(26.42)
AXF -11.27**(4.05)
AXG 10.55 (72.07)
R squared 0.14 0.18 0.19 0.21 0.18
Adjusted R squared 0.07 0.09 0.10 0.12 0.09
R squared change 0.05
†b
0.01
c
0.03**
c
0.00
c

a. Values are unstandardized regression coefficients, with standard errors in parentheses. Coefficients and standard errors are multiplied by 100 to facilitate interpretation.
b. Relative to Model 1.
c. Relative to Model 2.
† p < .10; * p < .05; ** p < .01; *** p < .001. N=214. All one-tailed t tests.

121
Figure 3. Interaction between CEO Experience and Prior Performance

(A)
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
Low High
# of CEO Directors
CARs (0,1)
Low prior performance
High prior performance

(B)
0
0.005
0.01
0.015
0.02
0.025
Low High
CEO Experience Diversity
CARs (0,1)
Low prior performance
High prior performance

(C)
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Low High
CEO Experience Diversity
Post-Succession Performance
Low prior performance
High prior performance

122
Figure 4. Interaction between Industry Experience and Prior Performance

-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
0.06
Low High
Industry Experience Diversity
CARs (0,1)
Low prior performance
High prior performance

Figure 5. Interaction between Task Experience and Prior Performance

-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
Low High
Task Experience
Post-Succession Performance
Low prior performance
High prior performance

123
Table 9. Summary of Hypothesis Testing Results
Hypothesis Result
Direct Effects
H1a. # of CEO directors Æ (+) CARs Supported
H1b. # of CEO directors Æ (+) post-succession
performance
Not supported
H2a. Presence of intra-industry directors Æ (+)
CARs
Not supported
H2b. Presence of intra-industry directors Æ (+) post-
succession performance
Not supported
H3a. Co-working experience Æ (+) CARs Supported
H3b. Co-working experience Æ (+) post-succession
performance
Not supported
H4a. Task experience Æ (+) CARs Not supported
• Found negative effect
H4b. Task experience Æ (+) post-succession
performance
Not supported
H5a. CEO experience diversity Æ (+) CARs Not supported
H5b. CEO experience diversity Æ (+) post-
succession performance
Supported
H6a. Industry experience diversity Æ (+) CARs Not supported
H6b. Industry experience diversity Æ (+) post-
succession performance
Not supported
Moderating Effects of Industry Instability
H7. (Level) Effects predicted in H1a – H4b will be
weaker in unstable industries
Partially supported
• Supported for # of CEO directors when
DV=CARs

H8. (Diversity) Effects predicted in H5a – H6b will
be stronger in unstable industries
Not supported
• Found negative interaction between CEO
experience diversity and industry instability
Moderating Effects of Pre-succession
Performance

H9. (Level) Effects predicted in H1a – H4b will be
weaker in poorly-performing firms
Partially supported
• Supported for # of CEO directors when
DV=CARs
• Supported for task experience when
DV=post-succession performance
H10. (Diversity) Effects predicted in H5a – H6b will
be stronger in poorly-performing firms
Generally supported
• Supported for CEO experience diversity
(both DVs)
• Supported for industry experience diversity
for CARs

124
CHAPTER 6
DISCUSSION AND CONCLUSION
6.1 Summary of Key Findings
This dissertation elaborates on two views about the value of board experience to a firm
based on the RBV, learning theory, and the upper echelon perspective. The value-in-
specificity hypothesis emphasizes the positive effects of history-dependent and context-
specific experience on group task performance. It concerns the level or depth of
experience. By contrast, the value-in-diversity hypothesis suggests that group
performance depends on the diversity or breadth of different types of experience that
group members bring to the decision making process. Both experience specificity and
diversity should positively affect group task performance, but the effects are likely to be
moderated by contextual factors. In particular, in contexts that require strategic change,
diverse experience will have a greater positive effect on performance. In contexts where
continuity is preferred, in-depth historical experience will contribute more to
performance.

Based on these theoretical arguments, this study examined the effects of board experience
on firm performance in the context of CEO selection. Four types of board experience
crucial for the task of CEO selection were defined: CEO experience, industry experience,
co-working experience, and task experience. Each benefits the selection decision in its
unique way. Directors who are current or retired CEOs of other companies have deeper
knowledge about the nature of the CEO’s job and corresponding skill requirements.

125
Directors who have industry have a better understanding of the firm’s immediate task
environment, e.g., knowledge about customer needs, supplier relationships, potential
rivals, and technological trends. Directors who have been serving on the board together
for a relatively long time tend to develop accurate knowledge about other directors’
expertise, about the norms / rules / routines of the board, and about the firm’s business
operations. This knowledge enables the board to specify a more accurate and relevant
“strategic mandate” for the new CEO. Finally, the task of hiring a CEO is very
complicated and challenging. Thus, directors who have participated in hiring the previous
CEO for the firm have more task experience, which turn, improves the quality of their
next CEO selection decision. The positive effects of these experiences on board
performance are consistent with the RBV and learning argument that history-dependent,
context-specific experience is a value-creating resource and improves the board’s
information processing capabilities. In addition, diversity of CEO and industry
experience should also positively influence board effectiveness. I examined how specific
experience and experience diversity affect (1) stock market reactions to new CEO
appointments, and (2) post-succession accounting performance. The analysis was focused
on independent directors’ experience. Therefore, the results reported here help us
understand if, after controlling for board power and incentives, board experience still has
incremental effect on board effectiveness in the context of CEO selection. The
experience-performance link was examined in a sample of 242 CEO selection events that
occurred between 1999 and 2003.

126
6.1.1 Comparison of Key Findings to Prior Research
Several findings concerning the hypotheses are worth discussing. First, it was found that
the stock market responded favorably to the hiring decisions made by boards with more
CEO directors. This result complements Fich’s (2005) study of 1,493 director
appointments to Fortune 1000 boards during 1997-99 (a time period just prior to the
sample period of the present study). Fich found positive stock market reactions to the
appointments of CEO directors to corporate boards, while the present study offers further
evidence about investors’ confidence in the decisions made by the CEO directors after
they had been appointed. Second, the effect of the number of CEO directors on abnormal
stock returns appeared to be stronger in stable industries than in unstable industries, a
result consistent with the argument that history-dependent experience tends to be more
valuable in stable environments. These findings along with the anecdotal notes about
firms’ efforts to recruit CEO directors (Bianco et al., 1997) offer evidence that the stock
market does respond to directors’ executive experience.

Third, I found a strong positive effect of board co-working experience and abnormal
stock returns, indicating that investors perceived directors’ experience of working
together as a valuable resource to the firm. To the best of my knowledge, no previous
study has examined co-working experience among independent directors. This finding
shows the importance of group experience for task performance. In a broader context, the
finding is consistent with many previous studies on other types of groups in which shared

127
working / training experience was reported to have a positive effect on group
performance (e.g., Littlepage et al., 1997; Reagans et al., 2005).

Fourth, it was found that CEO experience diversity and industry experience diversity
were both more positively related to CARs in poorly-performing firms, indicating that
investors expected that directors with diverse business experiences would make more
contribution to future firm performance, especially when the firms had been having
performance problems prior to CEO succession. In addition, CEO experience diversity
also had a significant and positive impact on post-succession firm performance and the
effect, again, was stronger for firms with lower pre-succession performance. These
findings are consistent with the strategic change literature about the relationships between
performance decline, experience diversity of top decision making teams, likelihood of
strategic change, and subsequent firm performance (see Rajagopalan and Spreitzer, 1997
for a review). It is argued that low performance serves as a benchmark that alerts
stakeholders and calls into question the effectiveness of prior strategy (Levitt et al., 1988).
Therefore, low-performance firms are more motivated to initiate strategic changes
(Boeker, 1989; Lant, Milliken, & Batra, 1992) and changes are more likely to be
implemented if the top decision-making teams (the TMT and the board) have a more
flexible, diverse “mental model.” One study is particularly relevant to the current findings.
Arguing that the career experiences of decision makers influence strategic decisions,
Golden and Zajac (2001) found that hospital boards were more likely to initiate strategic
change when they had more members with industry experience and managerial expertise

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(measured as the proportion of directors whose primary occupations were of a business or
legal nature). Researchers on TMT diversity have also found that TMT functional
diversity is negatively related to commitment to the status quo (Geletkanycz & Black,
2001) but positively related to the likelihood of strategic reorientation (Lant et al., 1992)
and strategic innovativeness (Bantel et al., 1989). TMTs with more members from
science and engineering backgrounds and higher levels of educational diversity were
more likely to initiate strategic change (Wiersema & Bantel, 1992). Moreover, groups
that had knowledge broadly distributed across group members (i.e., group consisting of
generalists) are found to outperform groups that had unique knowledge concentrated in
different group members (Rulke & Galaskiewicz, 2000). The present study added to these
findings by showing that diverse CEO and industry experiences among directors were
likely to be seen as change-facilitating factors in poorly-performing firms.

6.1.2 “Surprising” Findings and Possible Explanations
Several “surprising” results that are inconsistent with some of the hypotheses emerged
from the analysis. First, the learning-by-doing perspective suggests that the accumulation
of first-hand experience with a job task leads to performance improvement (Levitt et al.,
1988). Based on this argument, I hypothesized that directors’ experience with the CEO
selection task should be positively associated with CEO selection performance. However,
task experience was found to have a negative direct effect on CARs. There may be two
explanations. One is related to the stock market reaction to directors’ involvement in two
consecutive CEO selection decisions. Investors might be concerned about the fact that

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many independent directors who were responsible for choosing the new CEO had also
been involved in choosing the departing CEO. Although I controlled for succession type
(routine departures vs. non-routine departures), pre-succession firm and industry
performance – potential “quality indicators” of the previous CEO selection decision, the
mere fact that the board had also hired the departing CEO might convey some negative
information because some old CEOs left their companies under non-routine
circumstances. Another possible explanation is that learning from previous CEO
selection decisions may be difficult because these decisions are made infrequently and
there is often a gap between the time of the decision and the time of outcome evaluation
(Kesner & Sebora, 1994). The departing CEOs in my sample had an average tenure of 8.5
years in the CEO position (standard deviation = 7.6 years), implying that, on average,
whatever the directors had learned from the task of hiring the previous CEO was from
more than eight years ago and the firm’s situation might have changed dramatically
during this time period. Unlike other types of board experience that are defined as
ongoing learning experience, task experience, as measured in this sample, might lose
value due to the time gap between the two CEO selection events. However, this does not
mean that task experience should always have a negative effect because experience
gained from more recent tasks may still be relevant and useful. This possibility needs to
be explored in other the context of other strategic decisions (e.g., acquisitions).

Second, CEO experience diversity was hypothesized to have a stronger positive effect on
CARs in more unstable industries. However, it was found that CEO experience diversity

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was positively related to CARs in stable industries but negatively related to CARs in
unstable industries. One explanation for this result is that investors may worry that the
decision situation in the boardroom can become too complicated when a board with
diverse CEO experience is dealing with rapidly changing industry environments. The
idea that too much diversity may be detrimental has been discussed in previous studies.
For example, Virany and colleagues (1992) argued that, in turbulent environments,
diverse perspectives brought to the firm by newly hired top executives helps improve the
firm’s capabilities to renew its routines. However, rapid organizational changes are also
associated with costs. Coordination problems, political activities, and implementation
difficulties all pose challenges to the firm. Hence they argued that change mechanisms
(e.g., executive turnover) should be accompanied by certain stabilization mechanisms
(e.g., promoting an internal executive to the CEO position rather than hiring an outsider
who does not have adequate firm-specific knowledge) in more turbulent environments in
order to maintain a balance between strategic continuity and change. There has been
evidence that heterogeneous teams make decisions slower than homogeneous teams
(Eisenhardt, 1989b). Cost and time pressures are particularly strong in turbulent
environments. In a similar vein, the result reported here may reflect investors’ concerns
about the lack of stabilization mechanisms in boards with diverse CEO experience that
must deal with fast-changing task environments.

Third, it was found that CEO experience diversity and co-working experience affected
CARs and post-succession performance in different ways. In the main-effects models

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(Model 2 in all tables), CEO experience diversity had little impact on CARs but had a
significant and positive effect on post-succession accounting performance. Consistent
with Hypothesis 8, CEO experience diversity had a stronger positive effect on post-
succession performance in unstable industries. However, inconsistent with Hypothesis 8,
CEO experience diversity had a stronger negative effect on CARs in unstable industries.
On the other hand, co-working experience had a significant and positive effect on CARs
but a negative (although not statistically significant) effect on post-succession
performance. The inconsistent effects of CEO and co-working experiences on the two
performance measures may have important implications for understanding the advantages
and disadvantages associated with stock and accounting performance measures. The
implications of these inconsistent results across different performance metrics will be
discussed later in more details in the section about future research.

6.2 Contributions
6.2.1 Theoretical Contributions
To date the dominant theories on board effectiveness (e.g., agency theory) have
emphasized the link between board power / incentives and board effectiveness in
monitoring. This line of thinking emphasizes the importance of board structural
independence and financial incentive plans. However, an important determinant of board
effectiveness -- the board’s decision-making ability is largely missing in the monitoring
framework. Given the increasing public attention to board accountability for their
decisions, research on board experience has become more and more important. Multiple

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theoretical perspectives (the resource-based view, learning theory, and the upper echelon
perspective) suggest that work experience shapes knowledge, skills, and abilities of
decision makers. Moreover, work experience is a multi-level, multi-dimension, and
context-specific construct (Castanias et al., 1991; Quinones et al., 1995), which implies
that assessing board ability requires an examination of the “bundle” of director
experiences relevant to specific board decisions / tasks. Despite the recognition of the
value of board experience in improving board decision quality, little effort has been
devoted to developing a model of multidimensional board experience and board
effectiveness. A major contribution of this study is the development of such a model in
the context of CEO selection, which explains how board experience at the task, job, team,
firm, and industry levels enables the board to hire the right CEO for the firm. Board
experience, after controlling for power and incentive effects, explained a substantial
proportion of variance in CEO selection performance. The findings of this study show
that corporate boards work not just as a reactive, damage-control mechanism but as a
proactive strategic decision-making group that influences firm performance through their
decisions.

Another contribution is that this study developed a contingency-based model of board
experience by examining the moderating effects of two contextual factors – industry
instability and pre-succession firm performance. Both the RBV and learning literatures
suggest that external changes and internal performance problems serve as benchmarks /
feedback mechanisms that urge firms to reevaluate their current resources and initiate

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strategic change when necessary. The contingency logic suggests that the value of board
experience may vary under different environmental and organizational conditions.
Consequently, the stock market will respond positively to CEO selection decisions made
by boards whose “experience profiles” match the requirements of external and internal
contingencies. The match, in turn, will lead to better post-succession performance.
Adding two critical contingency factors to the direct-effects model helps us understand
the boundary conditions for the relationships between board experience and CEO
selection performance.

The third contribution is that the experience effects were identified after controlling for a
set of factors that have been examined in previous studies, including environmental and
organizational factors, board power and incentives, characteristics of the departing CEO
and the arriving CEO, and the nature of the succession event. In this sense, this study was
based on a theoretical model more refined than the models that have been previously
examined. The connections between the key findings with respect to the control variables
in my study and previous studies are briefly discussed as follows.

At the environmental level, this study examined industry instability – a factor that has
received much attention in the literatures on strategic contingency theory, resource
dependent theory, and the resource-based view of the firm. Environmental instability has
been treated as an antecedent of executive succession / CEO characteristics (Datta et al.,
1998; Haveman, Russo, & Meyer, 2001; Wiersema & Bantel, 1993) or a moderator of the

134
succession-performance relationship (Virany et al., 1992). Prior research has suggested
that firms are more likely to encounter performance problems in unstable environments
because it is more difficult to secure necessary external resources (Lawrence et al., 1967),
to renew the firm’s resource base timely (Teece, Pisano, & Shuen, 1997), and to achieve
a “fit” between organizational strategy and environmental requirements (Miller, 1992).
Consistent with these arguments, I found a marginally significant and negative effect of
industry instability on post-succession accounting performance. On the other hand,
industry effects have largely been overlooked in the literature on stock market reactions
to CEO successions. Davidson and colleagues (2002) examined the wealth effect of CEO
successions and found positive stock market reactions to outside CEO succession
announcements when the CEO came from industry related firms (i.e., firms sharing with
the hiring firms the same industry codes). However, no previous study has examined the
joint influence of industry instability and board experience on the wealth effect of CEO
appointments. In this study, I found a positive relationship between industry instability
and CARs. This result may have to do with some specific characteristics of the sample.
As mentioned earlier, a substantial proportion of the sample firms were from computer
and electronic product manufacturing industries. These industries are generally viewed as
fast-changing, unstable but at the same time abundant with growth opportunities (Virany
et al., 1992). The positive relationship between industry instability and CARs can
probably be attributed to investors’ expectations for future growth opportunities present
in unstable industries.

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This study also reported findings about board power and incentives, whose effects were
captured by three variables – outsider ratio, independent directors’ stock ownership, and
separate leadership structure. However, results showed that these variables had little
impact on CEO selection performance. The only exception was a negative relationship
between outsider ratio and CARs, a result contradictory with agency theorists’ prediction
that the stock market would prefer decisions made by outsider-dominated boards. Prior
studies have reported that outsider-dominated boards were more likely to hire outsider
CEOs (Borokhovich et al., 1996; Davidson et al., 2002), but there has been very limited
evidence about stock market reactions to the hiring decisions made by outsider-
dominated boards (Weisbach, 1988). This study documented a negative relationship
between outsider ratio and stock market reactions, which may be indicative of recent
changes in public opinions regarding how outside directors influence organizational
decisions. The stock market may have become more “demanding” when it comes to
evaluating outside directors’ capabilities. Besides the proportion of outside directors, the
market demands more information about who the directors are and what they can do for
the firm.

Several often-researched succession event characteristics were included as control
variables, including the outgoing CEO’s disposition (routine vs. non-routine departure),
the incoming CEO’s origin (insider vs. outsider) and demographic characteristics of the
CEOs. These variables have been the focus of most previous succession studies (Kesner
et al., 1994). In this study, evidence showed that the only significant variable was

136
succession type: Routine, smooth succession events received strong positive reactions
from the market. Conversely, non-routine successions involving CEO dismissals and
forced resignations were associated with negative abnormal returns. In a routine
succession the old CEO remained on the board. In the case of a relay succession, not just
the old CEO remained with the firm the new CEO was also promoted from within the
firm. In these types of succession events, firms are able to maintain top managers’ firm-
specific knowledge and hence avoid the potential disruptive effects of CEO change. This
evidence supports the RBV and human capital argument that managerial firm-specific
knowledge leads to performance improvement but does not necessarily support the
agency theory argument that CEO dismissals will receive positive responses from
investors. Again, the patterns of the empirical findings are more consistent with a
capability or human capital approach to studying stock market reactions to CEO
succession events (Harris & Helfat, 1998; Worrell, Nemec, & Davidson, 1997).

6.2.2 Methodological Contributions
This study developed a context-specific measurement scheme for board experience based
on publicly available archival data. In the organization and strategy literatures there has
been a long tradition of using observable individual characteristics as proxies for inherent
psychological properties and processes. Hambrick and Mason (1984) argued that there is
a better chance that empirical research can be made more cumulative if psychological
properties can be defined in terms of observable individual behaviors. Similarly, Pfeffer
(1983) suggested that demographic variables may prove superior to psychological

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concepts because they are easily measured and produce more parsimonious explanations.
In particular, archival-based, objective measures have been widely used in the research
on TMTs and boards because primary interview or survey data on managerial cognition
and other unobservable psychological processes are very difficult to obtain from TMTs
and boards. Even if researchers were offered opportunities for conducting field
investigation, it would be extremely challenging to collect data on a large sample. Since
archival data on corporate directors tend to be more reliable and comprehensive (after
being audited by external professionals and filed following legal requirements), it is
important to create more refined measurements to capture theoretical concepts such as
experience, power, or incentives.

Many archival-based measures used in previous studies have suffered from a major
problem: They are at best rough proxies for unobservable constructs. The most obvious
example is the insider / outsider dichotomy that has often been used to measure board
independence and CEO origin. Daily and colleagues (1999) noted that board researchers
had often failed to provide conceptual justification for the board composition measures
they adopted. Zajac (1990) made a similar comment on using the insider / outsider
dichotomy to measure CEO successor origin. He argued that insiders and outsiders might
still be different along many other dimensions and yet these differences had not been
specified conceptually as a part of an overall theoretical framework. Since different
theoretical concepts have been measured using the same variables, it is not surprising that
the empirical results have been confusing.

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This study contributes to the literature by developing a theoretically grounded,
multidimensional classification scheme measuring board experience. The types of
experience relevant to the task of CEO selection were identified based on a review of the
major theories (the RBV, learning theory, and the UEP) that address the role of work
experience on task performance. Qualitative studies on corporate boards (e.g., Lorsch et
al., 1989; Vancil, 1987) and practitioner-oriented literature (e.g., Lorsch et al., 1999;
Shultz, 2001) also provide insights into what kinds of experience directors need when it
comes to the hiring a new CEO. The classification scheme was conceptually consistent
with the classification of managerial experience developed in the human capital theory
literature (Castanias et al., 1991) and the multilevel measurement model for TMT
competence (Kor, 2003). Moreover, the empirical measure for each type of board
experience was constructed in a way that the link between the theoretical definition and
the operational meaning was as tight as possible. Therefore, the empirical results are less
susceptible to alternative explanations. Including in the regression models a set of
conventional measures of board independence and CEO succession characteristics also
helped to improve robustness of empirical findings and rule out alternative causal
explanations. And the results did show that the board experience measures explained a
significant portion of the variance in CEO selection performance over and above the
portion explained by the conventional measures. The archival-based experience measures
can be replicated in other samples. In this sense, the measurement scheme developed and
tested in this study represents a meaningful starting point from where evidence for the
effects of board experience can be systematically collected and compared.

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6.2.3 Practical Contributions
The findings also have implications for board practices, particularly for director selection
practices. The debate over the board-CEO relationship has long been centered on power
and control. Years of board reform has focused on shifting power from the CEO to an
independent board (Pound, 2000). The control philosophy would caution against board
attributes that hint any possibility of directors’ being influenced by the CEO. For example,
having CEOs of other companies on the board might not be highly recommended because,
despite their experience, CEO directors might also be seen as collaborators with the CEO
of the focal firm – one of their peers rather than the representatives of shareholders. In
contrast to this conventional belief, the present study reported that firms were likely to
benefit from having independent directors with CEO and industry experiences and with
long co-working experience.

These findings imply that firms should recruit outside directors strategically by choosing
directors with experience and skills that match the firm’s current and future strategic
needs. In this sense, director selection is not much different from CEO selection – both
should be conducted under the criterion of talent-firm match. Firms should adopt a more
focused, more target-driven, and more proactive director selection approach as suggested
by some corporate governance observers. For example, Mizruchi (1983) argued that
outside directors who have knowledge more relevant to the firm’s business have greater
control over firm management than do “public” outsiders from universities and
stakeholder groups. Pound (2000) suggested that board reforms should “seek ways to

140
create and maintain an efficient decision-making process” (Pound, 2000: 81). Desirable
board characteristics thus include “expertise sufficient to allow the board to add value to
the decision-making process” (Pound, 2000: 83). Lorsch (1995) argued that the board
would need information on financial and strategic issues in order to effectively perform
its duty, and the biggest challenge for directors is to turn a broad array of information into
useful knowledge. Ward (1997) provided some “tips” for recruiting knowledgeable
outside directors. For example, he suggested that good CEO skills are important to
investors and firms can start to improve their boards by recruiting current or retired CEOs.
There has been anecdotal evidence that firms did take more effort to search for outside
directors with CEO experience (Bianco et al., 1997). This study offers large-sample
evidence that CEO directors do help firms pick out competent new CEOs.
Co-working experience was found to be associated with positive stock market reactions.
This finding leads to another practical implication. That is, other things being equal, it is
important to maintain board stability. More important, firms should consider developing
“deliberate learning mechanisms” (Zollo & Winter, 2002) for the purpose of improving
the “quality” of directors’ co-working experience. These learning mechanisms include
formal and informal arrangements that help directors collect, share, store, and use
strategic information. For example, at the board meetings director-only, no-executive
discussion sessions can be set up to facilitate open communication among directors.
There should be regular written communication between the firm and directors so that
directors can receive updated information and data about the firm. In addition to
convention board committees such as audit, compensation, and nominating committees, it

141
may be helpful to have a strategy committee where directors with executive and industry
experiences are charged with strategic advice responsibilities.

6.3 Limitations
It must be noted that the study has some limitations. First, the experience variables were
context-specific and archival-based. As discussed earlier, these measures have their
advantages (parsimony, objectivity, replicability, to name a few), but they are still proxies
for unobservable variables such as experience and knowledge. Second, the sample was
selected based on some strict criteria. The purpose was to create a sample of as “clean” as
possible CEO selection events so that the board experience effect could be isolated.
However, this was done at the expense of generalizability. Third, the sampled CEO
succession events occurred between 1999 and 2003, a time period that saw some unusual
fluctuations in the stock market, e.g., the rise and fall of many Internet start-ups.
Moreover, nearly 30 percent of the sample firms were operated in computer and
electronic product manufacturing industries that are typically characterized by rapid
technological changes and abundant growth opportunities. The market efficiency
hypothesis is perhaps faced with the greatest challenges in these industries. That is,
realized post-event performance outcomes are more likely to deviate from stock price
reactions to (or market expectations for) an event as it was announced in the press
because many unexpected changes might occur during the post-event period. This may
explain the small and negative correlation between CARs and post-succession
performance in this sample. This observation leads to the fourth limitation of the present

142
study. Post-succession performance was measured as accounting performance in the year
following CEO succession. Other long-run performance measures may provide more
insights. For example, it may be worth examining how board experience is related to
post-succession long-run abnormal stock returns (Barber & Lyon, 1997; Fama & French,
1993).

6.4 Future Research
The findings reported here have important implications for future research on boards of
directors and CEO succession. First, instead of viewing board independence and board
involvement as two opposing approaches to corporate governance, it will be interesting to
see how the board can strike a balance between the monitoring role and the resource /
strategy roles. There have been some theoretical articles exploring the possibility of
integrating the two approaches (e.g., Hillman et al., 2003; Sundaramurthy & Lewis,
2003), but few studies have systematically examined the attributes that help the board
achieve effectiveness in multiple roles. One way to address this gap is to create a “map”
that link board attributes to role requirements under different theoretical criteria. The
purpose of doing so is to find out which paths have been trodden the most often and
which have been forgotten. It helps identify the mismatches between concepts and
measures and provides insights into how to correct the mistakes.

Second, within the research on board knowledge and experience there remain many
unexplored issues. In this study, I focus on the types of board experience that are valuable

143
inputs in CEO selection decisions. The classification scheme is based on the experience /
skill typologies developed in the human capital and work experience literatures. It is also
informed by the insights of qualitative studies on board decision making processes. The
analysis of board experience in other strategic decision contexts may be improved by
conducting a “job analysis” for corporate directors. That is, for each critical board
decision (e.g., hiring a CEO, making executive compensation plan, evaluating
organizational strategy, and so on) we need to understand what tasks the board is
expected to perform and what kinds of experience and skills are required. Again, this
requires qualitative research on board processes.

Third, the study informs the CEO succession research by emphasizing the board’s active
role in CEO selection. Many previous studies based on agency theory have focused on
the board’s role as a monitoring mechanism. Sometimes the “monitoring” role seems to
be equalized with a “damage control” role in which the board is suggested to fire the
CEO after performance decline has begun (Ward, 1997). However, empirical evidence
shows that firing a CEO is not the end of the story. Ironically, board directors who had
fired the CEO were found to leave their board jobs following the CEO dismissal more
often than their peers in other firms (Ward, Bishop, & Sonnenfeld, 1999). An implication
is that a board that is able to fire a CEO is not necessarily a capable monitor (or at least
not capable of managing the post-dismissal chaos). This, along with other studies
reporting positive stock market reactions to the appointments of CEO directors (Fich,
2005), brings director’s business experience back to attention. The question becomes

144
which boards are better at selecting a CEO and how they do it. Shifting research focus
from “what the board cannot do” to “what the board can do” may help create a “virtuous
circle” in scholarly discussion on board roles.

Fourth, some surprising results reported here open up an interesting question: What is
exactly meant by “stock market efficiency”? I found that some experience factors critical
to actual firm performance were not “noticed” by the stock market (e.g., CEO experience
diversity). Some factors well received by the stock market (e.g., co-working experience)
appeared to have little impact on post-succession performance. These interesting results
indicate at least two avenues of future research. One is to re-examine stock market
reactions from a cognitive perspective. That is, investors’ perceptions have to do with a
“constructed reality” in which investors learn to respond to new information. The market
may be in an early stage where investors have begun to realize the importance of board
experience but are still not sure what kind of experience would be valuable to the firm
eventually. This line of thinking would be interested in how the stock market learns to
react to organizational decisions and how market value is socially constructed (Zajac &
Westphal, 2004). The second avenue of research should shift the lens towards the post-
succession dynamics between the board and the new CEO and between the firm and its
environments with the purpose of identifying new contextual factors that may moderate
the effect of board experience on firm performance. For example, how will the co-
working experience among directors influence the way the board interacts with the new
CEO during the transition period following CEO succession? What factors may help

145
bring out the positive side of that experience while in the same time reducing its negative
effect?

6.5 Conclusion
In conclusion, this study provides empirical evidence on the significant effects of board
experience on both stock market reactions to new CEO appointments and a longer term
measure of firm performance. By demonstrating the importance of board experience in
explaining CEO selection outcomes, this study contributes to the development of a more
completely specified model of CEO succession. It is hoped this research will spur future
efforts that examine how board experience shapes organizational strategic actions in
other contexts.

146
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Abstract (if available)

Abstract Previous studies have emphasized that independent boards of directors with formal power and financial incentives should be an effective monitoring mechanism. Research on board independence, however, has largely overlooked the possibility that independent directors may differ from one another in terms of work experience that they have acquired from their primary occupations and from serving on the focal firm s board of directors. This dissertation research aims to examine the effects of board experience at multiple levels (task, job, team, firm, and industry) on firm performance in the context of CEO selection -- one of the most important decisions that a board of directors makes. Drawing upon the resource-based view of the firm, learning theory, and the upper echelon perspective, I argue that boards of directors are likely to make better CEO selection decisions when independent directors have worked as CEOs themselves and have experience of working together on the focal firm s board. Experience of working in the firm s primary industry and experience with the task of hiring a CEO also help improve board effectiveness in CEO selection. Effects of board experience were examined in a sample of 242 new CEO appointments that occurred in 226 large, publicly traded U.S. manufacturing firms from 1999 to 2003. I examined both stock price reactions to the announcements of new CEO selection and post-succession accounting performance of the firm. Results show that, after controlling for the effects of board independence, succession event characteristics, and other organizational / environmental factors, board experience explained a substantial proportion of variances in stock and accounting performance. Moreover, industry instability and firm performance prior to CEO succession were found to moderate the effects of various types of board experience.

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Asset Metadata

Creator Tian, Jie (author)

Core Title CEO selection performance: does board experience matter?

School Marshall School of Business

Degree Doctor of Philosophy

Degree Program Business Administration

Publication Date 04/16/2008

Defense Date 02/07/2008

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Board of Directors,CEO succession,corporate governance,experience,Learning and Instruction,OAI-PMH Harvest,resource-based view

Language English

Advisor Rajagopalan, Nandini (committee chair), Cummings, Tom G. (committee member), Hsiao, Cheng (committee member), Mayer, Kyle (committee member)

Creator Email jtian@marshall.usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m1130

Unique identifier UC1440454

Identifier etd-Tian-20080416 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-58191 (legacy record id),usctheses-m1130 (legacy record id)

Legacy Identifier etd-Tian-20080416.pdf

Dmrecord 58191

Document Type Dissertation

Rights Tian, Jie

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu