Organizational restructuring and social network changes implications on work performance, work satisfaction and satisfaction with changes

x Table of Contents 1.1 A Social Network Analysis of Organizations 4 2.1.2 Network Structural Perspective of Social Capital 16 2.4 Employees’ Satisfaction with Organizational Changes 36

ORGANIZATIONAL RESTRUCTURING AND SOCIAL NETWORK

DEPARTMENT OF MANAGEMENT AND ORGANISATION

SCHOOL OF BUSINESS NATIONAL UNIVERSITY OF SINGAPORE

2004

Acknowledgements

This is dedicated to my beloved grandmother who did not live to see the completion

of this academic endeavor, but whose life and example provided the impetus and motivation for me to prod on and finish the journey This endeavor would not have been possible without the encouragement and cheer of family and friends

To Kelvin, my husband, whose unstinting and unwavering support gave me the confidence to finish this monumental task

To Bryan, Brandon and Beverly, whose winning smiles and shining faces never fail to cheer me up after a long day

To Usa and Yuen Kay, my cheerleaders, intellectual partners and friends The race may not have been completed without you both

To Associate Professor Albert Teo for supervising the thesis amidst his very heavy commitments and Associate Professor Quek Ser Aik for selflessly giving of his time

to guide me in the statistical analysis

To God be the ultimate glory for all the precious lessons that I have learnt about myself, my own limitations and most of all, His bountiful grace and faithfulness in sustaining me in this academic journey

Grace Lee

April 2004

TABLE OF CONTENTS

Acknowledge ments ……… ii

Table of Contents……… iii

Summary ……… vi

List of Tables ……….… viii

List of Figures ……… x

Table of Contents

1.1 A Social Network Analysis of Organizations 4

2.1.2 Network Structural Perspective of Social Capital 16

2.4 Employees’ Satisfaction with Organizational Changes 36

3.1 Trust Networks following Organizational Restructuring 42 3.2 Advice Networks following Organizational Restructuring 45 3.3 Structural Context and Work Satisfaction 47 3.4 Network Turnover and Satisfaction with Changes 51

CHAPTER FOUR: METHODS AND MEASURES 65

4.4.1 Work Satisfaction and Satisfaction with Changes 75

5.3.1 Changes in Trust Networks after Restructuring 95 5.3.2 Analysis of Changes in the Trust Networks after Restructuring 98 5.3.3 Changes in Advice Networks after Restructuring 104 5.3.4 Analysis of Changes in the Advice Networks after Restructuring 107

5.6 Network Determinants of Work Satisfaction 114

5.6.1 Satisfaction with Working in the Organization 114

5.6.3 Satisfaction with Immediate Supervisors 120

5.6.5 Satisfaction with Changes in the Organization 125

5.8 Network Determinants of Work Performance 129

5.8.1 Advice Network Centrality and Work Performance 129 5.8.2 Structural Holes and Work Performance 132

6.1 Changes in Social Networks after Restructuring 138 6.2 Network Variables, Work Satisfaction and Satisfaction with Changes 141 6.3 Minor Hypotheses: Network Variables and Work Performance 143

Summary

While organizational scholars have acknowledged the importance of understanding how employee attitude, reactions and morale are impacted following organizational restructuring (Mishra and Spreitzer, 1998), there has been little attention paid to the mediating effects of social network structure in explaining employee outcomes This study seeks to fill this gap in the literature by examining how changes in employees’ network centrality and structural holes induced by organizational restructuring impacted employees’ work satisfaction, satisfaction with changes and work performance

Network centrality and structural holes of employees’ advice and trust networks were tracked at three points in time: before, three months after, and nine months after organizational restructuring Results indicated that survivors’ trust network centrality was significantly lower nine months after organizational restructuring when compared to pre-restructuring levels In contrast, advice network centrality and structural holes in survivors’ advice networks were significantly higher after restructuring compared to pre-restructuring levels

Work satisfaction comprising four dimensions of employee satisfaction with respect to: working in organization, job, immediate supervisor and colleagues, were tracked over three separate points in time: before restructuring, three months and nine months after Advice betweenness centrality and structural holes in survivors’ advice networks were found to be positively associated with satisfaction with working in the organization three months after restructuring Results indicated that advice network centrality and effective size of advice networks had no strong associations with satisfaction with immediate supervisor and colleagues

Additionally, employee satisfaction with changes in the organizational restructuring was tracked at two points in time: three months and nine months after restructuring Individuals with higher advice network centrality and whose networks were richer in structural holes were more satisfied with changes in the organization three months post-restructuring However, the relationship between the network variables and satisfaction with changes were not apparent nine months after restructuring

Finally, the effects of trust and advice network turnover on satisfaction with changes relating to the organizational restructuring were examined The findings showed that advice network turnover had a negative impact on satisfaction with organizational changes The findings also provided empirical support for the contribution of network variables to work performance Specifically, advice network centrality and structural holes were associated with higher work performance ratings

by supervisors in the post-restructured context respectively

Keywords: Organizational Change, Organizational Restructuring, Social Networks, Turnover, Work Performance, Work Satisfaction

List of Tables

Table 2.1: Examples of types of networks in previous studies 25 Table 4.1: Response rates for all Phases 70

Table 5.1: Zero-order Correlations for Pre-restructuring data (baseline,

Phase 1)

89 Table 5.2: Zero-order Correlations for Post-restructuring data, three months

after restructuring (Phase 2)

91

Table 5.3: Zero-order Correlations for Post-restructuring data, nine months

after restructuring (Phase 3)

93

Table 5.4: Paired Samples T-Tests (Trust Network Measures) 111 Table 5.5: Paired Samples T-Tests (Advice Network Measures) 112 Table 5.6: Regression Analyses of Advice Network Measures on

Satisfaction with working in the organization before restructuring (Phase 1)

115

Table 5.7: Regression Analyses of Advice Network Measures on

Satisfaction with working in the organization 3 months after restructuring (Phase 2)

116

Table 5.8: Regression Analyses of Advice Network Measures on

Satisfaction with working in the organization 9 months after restructuring (Phase 3)

118

Table 5.9: Regression Analyses of Advice Network Measures on

Satisfaction with Job in the organization before restructuring (Phase 1)

119

Table 5.10: Regression Analyses of Advice Network Measures on

Satisfaction with Job 3 months after restructuring (Phase 2)

119 Table 5.11: Regression Analyses of Advice Network Measures on

Satisfaction with Job 9 months after restructuring (Phase 3)

120

Table 5.12: Regression Analyses of Advice Network Measures on

Satisfaction with Immediate Supervisors in the organization before restructuring (Phase 1)

121

Table 5.13: Regression Analyses of Advice Network Measures on

Satisfaction with Immediate Supervisors 3 months after restructuring (Phase 2)

122

Table 5.14: Regression Analyses of Advice Network Measures on

Satisfaction with Immediate Supervisors 9 months after restructuring (Phase 3)

122

Table 5.15: Regression Analyses of Advice Network Measures on

Satisfaction with Colleagues before restructuring (Phase 1)

123 Table 5.16: Regression Analyses of Advice Network Measures on

Satisfaction with Colleagues 3 months after restructuring (Phase 2)

124

Table 5.17: Regression Analyses of Advice Network Measures on

Satisfaction with Colleagues 9 months after restructuring (Phase 3)

124

Table 5.18: Regression Analyses of Advice Network Measures on

Satisfaction with Changes 3 months after restructuring (Phase 2)

126

Table 5.19: Regression Analyses of Advice Network Measures on

Satisfaction with Changes 9 months after restructuring (Phase 3)

127 Table 5.20: Regression Models for Network Turnover Rate on Satisfaction

with Changes

128 Table 5.21: Regression Analyses of Advice Centrality Measures on Work

Performance Ratings by Supervisors

130 Table 5.22: Regression Analyses of Advice Centrality Measures on Peer

Performance Ratings

132

Table 5.23: Regression Analyses of Effective Size of Advice Networks on

Work Performance Ratings by Supervisors

133

Table 5.24: Regression Analyses of Effective Size of Advice Network on

Peer Performance Ratings

135

List of Figures

Figure 1: Concepts of centrality (adapted from Krackhardt, 1990) 15 Figure 2: Optimizing structural holes (adapted from Burt, 1992) 20 Figure 3: Possible effects of turnover of friend on stayer (adapted from Krackhardt

and Porter, 1985)

53 Figure 4: Turnover in networks (adapted from Krackhardt and Porter, 1985) 54

Figure 5: Four scenarios depicting degrees of impact from leavers (extracted from

Krackhardt and Porter, 1984, p 247)

55

Figure 7: Trust networks before organizational restructuring (baseline, Phase 1) 96 Figure 8: Trust networks three months after organizational restructuring (Phase 2) 97 Figure 9: Trust networks nine months after organizational restructuring (Phase 3) 98

Figure 10: Percentage of ties in the trust networks of all respondents within Work

Groups across All Phases

99 Figure 11: Advice networks before organizational restructuring (baseline, Phase 1) 104 Figure 12: Advice networks three months after organizational restructuring (Phase 2) 105 Figure 13: Advice networks nine months after organizational restructuring (Phase 3) 106

Figure 14: Percentage of ties in the advice networks of all respondents within Work

Groups across All Phases

107

CHAPTER ONE INTRODUCTION

Organizations today are reeling from discontinuities created by a growing level of globalization, heightened volatility, intense competition and demographic changes (Prange, 1999) In these times of rapid change, organizations routinely displace and hire large segments of their workforces in a continuous restructuring process (Fisher and White, 2000)

Organizations restructure even in the best of economic conditions (McKinley and Scherer, 2000; McKinley et al., 2000) Organizational scholars suggested that management frequently uses restructuring to improve productivity and to gain the favor of Wall Street (Worrell et al., 1991; Ellis, 1998) This generates cognitive order for executives in turbulent environments but contributes to long-term turbulence at the environmental level (McKinley and Scherer, 2000) Cognitive order is created when there is a perceived congruence or “fit” (Drazin and Van de Ven, 1985) between the organization’s internal structure and the state of the environment The cognitive order experienced by top executives and the disruption of environmental conditions provide the stimulus for further restructuring Restructuring thus becomes a learned and self-perpetuating phenomenon (McKinley and Scherer, 2000)

In turbulent environments, top management is driven by pressures to take some action as opposed to clinging to the existing structure Farjoun (2001) suggested that when top management takes no action, it may be interpreted as a sign

of passivity by external and internal stakeholders, and by the executives themselves,

as a relinquishing of control Therefore, organizations restructure because

complacency is penalized and compliance with social expectations is rewarded (Farjoun, 2001)

Given the widespread practice of organizational restructuring, it is not surprising that research on restructuring has surged in the past ten years (Bowman et al., 1999; Mishra and Spreitzer, 1998) Previous empirical work on organizational restructuring has had a few major focuses The first is primarily descriptive, presenting reasons why organizations reorganized, the problems they encountered, and the forms of reorganized structures (Cascio, 1993; Bruten et al., 1996) The second focus assesses outcomes of restructuring Within this stream of research, an approach commonly used by empirical researchers is to assess whether the financial and economic objectives of organizational restructuring are achieved These usually include expectations of productivity improvement, lower expense ratios, higher profits, increased return-on- investment, and boosted stock prices (Bowman and Singh, 1993; Bowman et al., 1999) The beneficial effects of restructuring on financial outcomes are however not always clear Although some companies have reported that restructuring spurs organizational performance, others have reported no or even negative effects (Cascio et al., 1997; Healy, Palepu, and Ruback, 1992; Kaplan, 1989; Ofek, 1994)

Recently, there have also been a significant number of studies examining financial outcomes of organizational restructuring, specifically its impact on employee perceptions and reactions (Mishra and Spreitzer, 1998; Amabile and Conti, 1999; Burkhardt, 1994) Cascio (1993) observed that survivors in a restructured organization experience increased job stress and symptoms of burnout Fisher (1991) similarly noted that trust and morale are negatively affected as remaining employees

non-experience workload increases and job insecurity Directly contrasting these findings are other studies that showed that employees are energized and consider restructuring

to be an opportunity for personal growth (Emshoff, 1994; Henkoff, 1994; Isabella, 1989) The different and varying results from organizational studies done on restructuring show that the effects of organizational restructuring on employees are far from straightforward It does suggest that more research needs to be done to further understand what mediates the effects of organizational restructuring on employees What is interesting is the lack of attention paid to the mediating effects of social network structure in explaining employee outcomes

When an organization restructures by reorganizing current divisional structures and reporting relationships, the restructuring has a direct influence not only

on the task-related and job-related aspects of employees, but also on where employees are located within the organization, as well as on the social interactions of individuals (Reilly, Brett and Stroh, 1993) Changes to the social and relational dimensions of the organizational context will ultimately have an effect on employee outcomes such as commitment, work satisfaction and morale (Shah, 2000) In a recent study, Shah (2000) examined the impact of social structure on survivors’ reactions to layoffs in a downsizing organization He suggested that a longitudinal study is necessary to investigate network effects over different time frames In addition, he suggested that more attention should be paid to the impact of structural changes on survivors’ work performance given that “positional ramifications of a layoff may also have performance implications” (p.111) Where Shah’s study (2000) examined structural implications of a downsizing initiative, no study has focused on the implications of a restructuring initiative that involves changes in administrative and accountability structures, rather than downsizing per se Since longitudinal research examining the

social structural implications of restructuring is sparse, this study seeks to fill this gap

in restructuring literature by exploring changes in the trust and advice network structures following organizational restructuring in a longitudinal study The changes

in employees’ network centrality and structural holes induced by organizational restructuring were then examined to determine their effects on employees’ work satisfaction, satisfaction with changes and work performance

1.1 A SOCIAL NETWORK ANALYSIS OF ORGANIZATIONS

An organization is made up of social groupings with relatively stable patterns

of interaction over time (Weick, 1969) Networks are constructed when individuals interact (Tolbert et al., 1995) Social networks are defined as “specific sets of linkages among a defined set of persons, with the additional property that the characteristics of the linkages as a whole may be used to interpret the social behavior

of the persons involved” (Mitchell, 1962, p.2) Not all pairs of individuals are directly joined, and some are joined by a variety of relationships When many individuals are involved, the resulting structure can be analyzed to derive information about the individuals or the organizational groupings The network structure can reflect much about the functioning of organizations and individuals (McPherson, Popielarz and Drobnic, 1992)

Network scholars are interested in the patterning of relationship ties within a social network structure and seek to establish both their causes and consequences It

is important to understand why relationships exist in some context and are absent in another (Tichy, Tushman and Fombrun, 1979) There could be two reasons why relationships are absent If either party to a relationship does not participate, the relationship simply does not exist The second reason why some interactions do not

take place is because all interactions occur in a context of institutions which include rules and roles (Tolbert et al., 1995) Organizational policies impose some of these rules and roles For example, organizational units can be explicitly directed to interact with one unit but not others, or are instructed to report to one level rather than another Others might arise from prejudices or rules that are set in place for other purposes Therefore, individuals at different levels of the social structure sometimes

do not mix with each other In some organizations, for example, high- level managers may not mix with lower- level employees

Network scholars are particularly interested in mapping informal relationships and ties As Tolbert et al (1995, p 343) described the realities in organizations:

“The structural designers of organizations, those who mandate reporting

relationships or memo distribution lists or access to databases, are much like

architects who try to predict where the pedestrian traffic will be or should flow

on a university campus They lay their cement, install fences and other

obstacles, but inevitably the flows of people and classes carve bare spots in the

grass where the sidewalks need to be.”

More often than not, interactions and relationships in organizations consist of informal ties that link people across formal lines of control These social interactions emerge over time, become relatively stable, and may shadow formally prescribed work- flow and authority relationships These interactions and relationships form the social networks within the organization

Examining organizational dynamics from a network structural perspective has the advantage of providing understanding and insights into important relationships or

ties other than those specified on the organization charts (Krackhardt and Hanson, 1993) Because interactions are often not formally specified, it is important to map out the presence of informal social networks and trace how they carry information or ideas from place to place

A network analysis of organizations not only advances our knowledge of organizations by the modeling of formal and informal interactions, it provides additional insights on access to resources within the context of analysis (Brass, 1992) Coleman (1988) argued that the structural context provides access to and control of valued resources at any given time

Over the last decade, network scholars have been keen to understand how network ties and structural positions that are embedded in both formal and informal interaction patterns are associated with instrumental outcomes like innovation opportunities and brokerage opportunities (Burt, 1997; Hargadon, 1997) Given the merits of utilizing a structural approach to understanding both organizational and individual phenomena, a study of organization restructuring from a social network perspective is likely to yield important insights on its impact on the organization and the consequences on employee- level outcomes

1.2 RESEARCH QUESTIONS

Social networks are the patterned, repeated interactions among individuals in the organization (Mintzberg, 1979; Weick, 1969) A major restructuring is likely to disrupt the existing interaction patterns and relationship ties within the organization as people leave and newcomers join the orga nization Krackhardt and Hanson (1993) suggested that organizational restructuring creates changes to the informal

organization, which they defined as the networks of relationships that employees form across functions Social interaction patterns within the organization are likely to be more fluid than stable in a context such as in an organizational restructuring Changes

to interaction patterns following organizational restructuring will alter the structures

of social networks within the organization, affecting employees’ centrality within these social networks and their effective size of networks

From a social capital perspective, an individual’s centrality in a social network structure will affect the individual’s ability to draw on that standing to achieve individual goals (Friedman and Krackhardt, 1997) Social capital theory predicts that returns to intelligence, education, and seniority depend on a person's location in the social structure of a market or hierarchy (Granovetter, 1973; Burt, 1997; Lin and Dumin, 1986; Lin, 1998) Individuals with more social capital get higher returns to their human capital because they are positioned to identify and develop more rewarding opportunities (Burt, 1992) What is critical to success is not just individual attributes like intelligence and charisma, but the way one is embedded in an organization - that is, one's position in a web of social relations that provide information and political support (Brass, 1994) Information represents capital that exists in the very presence of relationships The more people one knows and the more informed are that person's contacts, the more information that person has available to him or her (Burt, 1997)

Based on social capital theory, an individual employee’s centrality in the social network structure will have implications on individual- level outcomes (Brass,

1984 Ibarra, 1993, Granovetter, 1995; Podolny and Baron, 1997) Despite the widespread consensus among scholars that informal organizational networks are

powerful mechanisms for the control and distribution of a wide array of resources (Brass, 1992; Krackhardt, 1990), empirical evidence linking resources and outcomes derived from an individual’s network centrality and structural holes following organizational restructuring is practically non-existent

The discussion so far raises interesting questions from both restructuring and network perspectives The following summarizes the research questions for this study:

1 What are the changes within the trust and advice network structures following organizational restructuring in a longitudinal study?

2 How are employees’ network centrality and structural holes impacted as a result of changes in the trust and advice network structures?

3 How does organizational restructuring affect employees’ work satisfaction and satisfaction with changes through the network effects of centrality and structural holes respectively?

4 How does network turnover affect employees’ satisfaction with organizational changes?

5 How does organizational restructuring affect employees’ work performance through the network effects of centrality and structural holes respectively?

1.3 AIMS AND CONTRIBUTIONS

This study aims to focus on an organizational restructuring context that encompasses work reorga nization and changes to administrative structures and work processes Through this study, I seek to contribute to the network literature by examining how social networks within the organization are altered following organizational restructuring in a longitudinal study A good network theory of organization should include a longitudinal perspective of how relationships and interactions change over time (Tolbert et al., 1995) A network analysis taken in a snapshot of time might miss the organizing that is going on and the stable system that eventually evolves A longitudinal study following organizational restructuring will provide us with a better understanding of changes in social relations within the work context

Restructuring provides a context in which to examine how social networks are affected by formal structural changes Given that social network studies have traditionally focused on intact and stable networks (Shah, 2000), an investigation of how social networks evolve and are changed after organizational restructuring should enrich the existing network literature that is primarily focused on intact networks Previous studies in organizational restructuring have focused on the social-psychological implications on employees by directly examining changes in employee outcomes (Brockner et al., 1986, 1987, 1993, 1994; Mishra and Spreitzer, 1998) This study aims to add to the existing literature by examining the impact of organizational restructuring on employees through the mediating effects of social network changes

1.4 OUTLINE OF DISSERTATION

I begin Chapter Two with the literature review In Chapter Three, I will present the arguments for the hypotheses that will be tested in this study The measures and methodology will be presented in Chapter Four In Chapter Five, results of the data analyses for each of the proposed hypotheses will be presented In Chapter Six, the results and implications, limitations, and suggestions for future research will be discussed

CHAPTER TWO

LITERATURE REVIEW

This chapter begins with an introduction on features of social networks that are foundational concepts in the network literature The concepts of network centrality and structural holes are given further elaboration because these network variables are the focal points of interest in this study Next, the characteristics of the two types of networks to be examined in this study — trust and advice networks, are described The later sections pertain to the review of literature on research that has been done on organizational restructuring, work performance, work satisfaction and employees’ satisfaction with organizational changes

2.1 THE SOCIAL NETWORK STRUCTURE

The social network structure comprises patterned, repeated social interactions among individuals (Ibarra and Andrews, 1993) In social network theory, the pattern

of relations among a set of actors in a network can explain outcomes related to either the individuals or the set (Wasserman and Faust, 1994) The fundamental assumption

in social network methods is the idea that individual- level outcomes and perceptions may be determined by the social network structure

Network theorists posit that individuals are embedded in social structures that influence their perceptions of organizational reality and regulate their access to or control over valued resources (Granovetter, 1973, Burt, 1992) Social influences on perceptions can stem either from the larger structural context in which individuals are embedded or from their more immediate socia l environment (Salancik and Pfeffer, 1978; Contractor and Eisenberg, 1990)

Three particular structural features of social networks — structural cohesion, similarity and centrality are foundational concepts in the network literature (Friedkin, 1991) Formal properties of networks like connectivity and density indicate network structures that foster social cohesion For dyads, the structural cohesion of actors A and B is a function of their joint membership in a structurally cohesive group, not of their feelings about each other For example, in a structurally cohesive group where the members are mutually reachable via communication paths, then actors A and B in the group are structurally cohesive if they are joint members of such a group Members of a cohesive group are likely to be more aware of each other’s views than are actors who are not members of a cohesive group Opinion is likely to be more visible and salient in a cohesive group because the actors are embedded in a context that values recip rocity and compromise (Friedkin, 1991) The greater the structural cohesion of A and B, the more likely they will be in frequent communication on a particular issue The pressure toward uniformity of opinions that arises from a comparison of opinions (Festinger, 1954) is likely to occur in a structurally cohesive group

Another property of network structure is structural similarity Actors who share similar patterns of relationships with others in the network can be grouped together A critical assumption in this approach is that roles and positions are determined by the patterns of relationships actors share with other actors in the network An actor A may not be cohesively joined to B in a network but actor B’s opinions will be salient to actor A if the latter recognizes that they share similar social positions Structural similarity may be defined by similar normative circumstances in the social structure Actor A will be attentive to structurally similar B’s opinion or behavior that will have a bearing on A’s status and interests (Burt, 1987) Friedkin

(1991) observed that the greater the similarity between two actors’ structural positions, the more similar their initial opinions on issues are likely to be Conversely, opinion differences will take on additional social distance corresponding

to structural dissimilarity in actors’ normative circumstances Hence, actors will attach more weight to opinions of actors who are in similar circumstances The central argument is that position similarity will lead to homogeneity of attitudes and behavior appropriate for that social position

A third property of network structure concerns the center-periphery pattern of

a social network An actor's embeddedness in a social network has important implications for a number of outcomes An actor who has high centrality in a network

is likely to have many direct contacts With the multiple links he or she has with others in the network, he or she has ready access to many others in the network Employees with high network centrality are likely to be regarded as more powerful and prestigious than more marginal actors (Scott, 1991), and are more likely to have disproportionate access to important tangible and intangible resources (Brass, 1992) Cent ral actors tend to be resourceful and cohesively linked to other actors (Friedkin, 1991)

A structural source of control arises from holding a central position within a network of relationships (Astley and Sachdeva, 1984; Pfeffer and Salancik, 1978), as opposed to formally prescribed Like formal authority, network centrality implies a high position in a status hierarchy and is expected to enjoy different degrees of access

to and control over valued resources (Burt, 1982) The key difference between formally and informally derived control is that the latter comes from actors' positions

in the actual patterns of interaction that define a social network, rather than from their

positions in the formally defined vertical and horizontal division of labor (Monge and Eisenberg, 1987)

Network research has examined the influence of two types of actors on individual behavior: cohesive and structurally equivalent referents Cohesion researchers state that individuals are influenced by their direct ties because of the frequency, intensity, and proximity of interaction (Burt, 1987) Structural equivalence researchers state that individuals are influenced by others occupying the same position

in their social structure that the individuals themselves occupy (structurally equivalent referents) However, the focal interest in this study is not behavior mimicry Neither

is it concern with how similarity between structural equivalents provide each other with information regarding appropriate role behavior Based on social capital theory, the two network measures that have been found to be related to instrumental outcomes are network centrality (Freeman, 1979) and structural holes (Burt, 1992) These measures are therefore chosen and discussed in the following sections

2.1.1 NETWORK CENTRALITY

A multitude of measures of centrality, each slightly different from the others, has evolved in the social network literature (Freeman, 1979; Bonacich, 1987; Friedkin, 1991; Knoke and Burt, 1983) Much of the thinking concerning network centrality has been defined by the work of Freeman (1979), whose measures of network centrality have been widely used by network researchers On the basis of their theoretical relevance and previous use, two centrality measures will be discussed here: degree and betweenness

Degree centrality is measured as the number of direct links connected to a given position The degree measure of centrality may represent the number of alternatives available to an actor (Friedkin, 1991) In-degree measure of centrality is defined as the number of others in the network who chooses a focal person An individual with high centrality will have more available alternatives than another who

is peripheral Other measures of centrality include out-degree centrality, which is defined as the number of people chosen by a focal individual Although out-degree centralities have been used, it is widely acknowledged that a more reliable indicator is in-degree centrality which measures the number of people who choose the focal individual (Freeman, 1979) For example, an employee may choose many others, but these others may not reciprocate the choice In-degree centrality is used as a measure

of prestige on the assumption that relations are often asymmetric Asymmetric measures of centrality and in particular, in-degree centrality have been shown to be related to power in diffusion of innovation (Burkhardt and Brass, 1990; Knoke and Burt, 1983) Figure 1 portrays the concepts of centrality diagrammatically In both networks X and Y, position D has the highest degree centrality because it has the most number of links connected to a given position

The second measure of centrality, betweenness, refers to the extent to which a focal person falls between pairs of other persons on the shortest path connecting the pairs Centrality measures based on betweenness reflect the intermediary location of

a position along indirect relationships linking other positions (Mardens, 2002) It is conceptualized as the extent to which the focal person has potential control over others (Freeman, 1979) Thus, if persons A and C are connected only through person

B, B would fall between A and C and would control any resources, such as information, that flow between A and C A position with high betweenness has a capacity to facilitate or limit interaction between the positions it links The betweenness measure represents potential control, or the possibility of increasing the dependence of others on the actor Freeman (1979) suggested that betweenness centrality is particularly appropriate for measuring the control of information In Figure 1, position H is the most central when calculating the betweenness measure

2.1.2 NETWORK STRUCTURAL PERSPECTIVE OF SOCIAL CAPITAL

There are at least three kinds of capital that an individual brings to the competitive arena The first is financial capital, and this includes cash, financ ial reserves and investments The second is human capital, like qualities of charm, health, intelligence, skills, formal education and job experience, that enables the individual to excel at certain tasks The third kind of capital is social capital, a term that has been coined by sociologists to designate the assets tied to the individual’s network (Coleman, 1988) This includes friends, colleagues and more general contacts through which an individual receives opportunities to use his or her financial and human capital Burt (1992) argued that social capital is the final arbiter of competitive success Through relations with contacts come the opportunities to

transform financial and human capital into profit Relationships within and beyond the organization are social capital

The competitive arena has a social structure: actors trusting certain others, obligated to support certain others, dependent on exchange with certain others In an arena where competition is imperfect and where either financia l or human capital is abundant, social capital then becomes an even more important competitive advantage Opportunity is determined less by what one knows than by whom one knows An actor’s position in the structure of social exchanges can be an asset in terms of yielding social capital Each actor has a network of contacts The structure of the actor’s network and the location of the actor’s contacts in the social structure can provide a competitive advantage Social capital is both the resource contacts held (i.e., whom you reach) and the structure of contacts in a network (i.e., how you reach)

There are two main tracks of scholarly interest within social capital theory The first line of work focuses on the magnitude of association between contact resources and the actor’s own resources Social capital developed from this perspective has extended to studies on how resources available to any one individual

in a population are contingent on the resources available to individuals socially proximate to the person (Lin, 1982) Network analysts in social contagion studies have also used network structure to predict the similarity of attitudes and behaviors of actors in a network instead of predicting attitudes and behaviors directly (Contractor and Eisenberg, 1990)

Instead of viewing social structure as a conduit to gaining social capital, a second line of work describes social structure as a form of social capital Network range or size is the primary measure of social capital Boxman et al (1991) showed

that people with larger contact networks obtain higher paying positions than people with smaller networks

The traditional view of social capital stresses the positive effects of network closure A network is closed to the extent that people in it are connected by strong relationships Typical forms of closure are dense networks, in which everyone is connected to everyone else, and hierarchical networks, where people are connected indirectly through mutual relations with a few actors at the center of the network This view argues for the presence of cohesive ties in promoting a normative environment that facilitates trust and cooperation between actors (Coleman, 1988, Lin and Dumin, 1986) From the perspective of network closure theory, social capital is viewed as the accumulation of ties or contacts with others in the social structure or the strength of ties within networks It is generally assumed that the closer and stronger the ties in the social networks, the greater the opportunity for cooperation and productivity Other benefits include greater mobility outcomes and status (Flap and

De Graaf, 1989; Coleman, 1988)

On the other hand, Burt (1992) argued that network size is a mixed blessing Increasing network size without considering diversity can be a disadvantage What is beneficial is the number of non-redundant contacts Contacts are redundant to the extent that they lead to the same people and so provide the same information benefits

A sparse network may provide more information benefits if it contains more redundant contacts than strong relations in a dense network with redundant contacts The sparse network reaches contacts in separate areas of social activity In comparison, each person in a dense network with strong ties knows what the other person knows and will discover the same opportunities at the same time The dense

non-network is inefficient in that it returns less diverse information for the same costs as that of the sparse network The term “structural hole” was developed by Burt (1992)

to denote the separation between non-redundant contacts “A structural hole is a relationship of non-redundancy between two contacts As a result of the hole between them, the two contacts provide network benefits that are in some degree additive rather than overlapping” (Burt, 1992: p.18)

2.1.3 STRUCTURAL HOLES

Burt (1992) suggested that balancing network size and diversity is a question

of optimizing structural holes The number of structural holes can be expected to increase with network size, but the holes are the key to information benefits An optimized network has two basic features: efficiency and effectiveness

An efficient network is one that maximizes the number of non-redundant contacts to maximize the yield in structural holes per contact (Burt, 1992) Given two networks of equal size, the one with more non-redundant contacts provides more benefits In Figure 2, network A provides four non-redundant contacts and network B provides the same number The information benefits provided by the additional four relationships in network A are redundant Network B is more efficient than network

A because it is maintained at a cost of four primary relations, instead of investing time and effort to keep up with eight relations

Network A Network B Network C

Figure 2: Optimizing structural holes (adapted from Burt, 1992)

A second feature of an optimized network involves the concept of effectiveness, which concerns the total number of people reached with all primary contacts Like networks A and B, network C also has four non-redundant contacts in the network even though there are sixteen contacts The effectiveness of a network is improved when one contact in each cluster can be a primary link to the cluster Network C is more effective than network B in that it has access to clusters of many secondary contacts The time and effort saved by withdrawing from redundant contacts can be reallocated to the pursuit of new non-redundant contacts in new clusters An effective network with ties to diverse non-redundant clusters is rich in structural holes and network benefits

The arguments behind structural holes are similar to the strength of weak ties argument proposed by Granovetter (1973) People with strong relations with others in

a similar cluster will have access to the same set of information and opportunities The flow of information will come through weak ties that connect people from

Node

separate clusters Weak ties are essential to the flow of information that integrates otherwise disconnected social clusters (Granovetter, 1973) Although weak ties and structural holes seem to describe the same phenomenon, there are important distinctions between the two concepts Although both concepts are associated with network benefits, structural hole theory argues that the causal agent is the structural hole between disconnected social clusters rather than tie weakness They are also conceptually different in that a structural hole spans unconnected others in the social structure and is associated with control benefits, whereas strength of tie relates to the measure of closeness and frequency of association between two parties The weak tie argument is about the strength of a relationship that spans the gap between two social clusters, while the structural hole theory is about the chasm spanned Granovetter (1973) suggested that non-redundant ties, the bridges that provide information benefits, are more likely weak than strong This implies that tie weakness is likely to

be a correlate of structural holes Although all bridges are likely to be weak ties, weak ties are not automatically bridges between two otherwise separate clusters Burt (1992) therefore argued that structural hole theory provides a more concrete foundation for empirical research on the information and control benefits related to network positions

2.1.4 TYPES OF NETWORK

Social networks are constructed from particular kinds of relationships, and researchers have increasingly come to rely on defined subsets of relationship types in the study of organizations Two such subsets have proven to be especially important

in predicting many important organizational outcomes — instrumental networks and expressive networks (e.g., Brass, 1992; Ibarra and Andrews, 1993)

Social network theory distinguishes between the instrumental network relations that arise in the course of work-role performance and expressive network relations that primarily provide friendship and social support (Tichy, Tushman, and Fombrun, 1974; Lincoln and Miller, 1979; Fombrun, 1982) Instrumental networks include advice relations and other instrumental kinds of relations in organizations like formal communication ties Expressive networks include friendship networks, social support networks and trust networks (Ibarra, 1995; Krackhardt and Stern, 1988)

Expressive network relations generally characterized by stronger, more intimate links, tend to connect people who are similar on a variety of personal characteristics (Marsden, 1988), and involve more frequent interactions (Krackhardt and Porter, 1985; Krackhardt and Stern, 1988; Krackhardt, 1990) Expressive networks generally connect individuals who share friendship and are associated with high degrees of intimacy

Instrumental relations, in contrast, tend to be weaker ties linking people who differ in personal characteristics and in their positions in the vertical and horizontal hierarchies (Laumann, Galaskiewicz, and Marsden, 1978; Lincoln, 1982; Lin, 1982) Instrumental relations are likely to be asymmetrical ties that serve as connections to disparate parts of the social system and that are critical for instrumental action Instrumental networks are also likely to contain ties linking more diverse individuals (Ibarra, 1993; Laumann, Galaskiewicz, and Marsden, 1978; Lincoln, 1982; Lin, 1982) Asymmetries in network ties reflect discrepancies in social power Thus, while dissimilar people may not be very useful for making comparisons, chains of asymmetric relationships may be useful for access to information and resources (Lin, 1982)

Instrumental and expressive networks have important differences Firstly, ties such as those that are found in an instrumental network are likely to develop between people in a similar work or task context whereas expressive relations tend to develop between people who are similar on a variety of personal characteristics, including gender, race, age, and religion (Marsden, 1988; Ibarra, 1992) Conversely, ties in expressive networks are more likely than instrumental ties to link people who are similar with respect to both personal characteristics and organizational affiliations, and who are thus more likely to have consistent interests Instrumental networks are more likely than expressive networks to link people who are dissimilar and disconnected except for a common work or task context Instrumental networks, being more asymmetrical in nature, are expected to be associated with control benefits

Secondly, it is expected that expressive relations will be characterized by more frequent interactions than instrumental relations (Granovetter, 1973; Krackhardt and Porter, 1985) By this argument, expressive relations in general are expected to be stronger than instrumental relations It is expected that expressive networks will be characterized by closer and more affectionate relationships than instrumental networks

Thirdly, given the homophilous nature of expressive relations, expressive networks carry great potential for persuasion and influence (Rogers and Kincaid, 1981; Granovetter, 1982; Krackhardt, 1992) Information obtained from expressive networks is expected to be perceived as more credible or relevant, more easily or frequently available, and more persuasive or influential (Brass, 1992)

In this study, advice (instrumental) and trust (expressive) networks are examined Advice network is widely acknowledged by network scholars to be an important instrumental network to facilitate tasks and work performance (please see Table 2.1) Therefore, it was chosen as one of the social networks to be examined in this study In selecting an appropriate expressive network to examine in the restructuring context, it was thought that the development or severance of trust ties in

an organization undergoing change will have implications for social support, particularly in the context of change and uncertainty Additionally, there has been a growing acknowledgement by organizational scholars that trust is important to the functioning of organizations (Dirks and Ferrin, 2001; Mishra, 1996) Although organizational scholars have devoted attention to examining the numerous potential benefits of trust, few have focused on examining trust ties in organizations undergoing change Trust relations are likely to be affected in a context of change, uncertainty and turnover Given that no network study has examined trust networks within organizations undergoing change, this study should offer a unique contribution

to both trust and network literature

An examination of the social network literature revealed that advice and trust networks have thus far been unexplored in studies of restructuring that involves a structural change in the organization Investigating the implications of a strategic decision like organizational restructuring from a social structural perspective should provide a valued contribution to both strategic management literature and organizational studies

Table 2.1: Examples of types of networks in previous studies

Ibarra (1993) Advice communication, support,

influence, and friendship networks

Cross-sectional Brass and Burkhardt (1993) Communication network Cross-sectional Ibarra and Andrews (1993) Advice and friendship networks Cross-sectional

Baldwin, Bedell and Johnson,

(1997)

Advice, friendship and adversarial networks

Cross-sectional Shah (2000) Advice and friendship networks Cross-sectional Sparrowe, Liden and Kraimer

el al, 1995; Golembiewski and McConkie, 1975)

Scholars have offered different explanations of the processes through which trust forms, the processes through which trust affects workplace outcomes, and the nature of the construct itself From a dispositional perspective, Rotter (1967) and others argued that individuals vary in the extent to which they trust others in general The trait is often referred to as propensity to trust, and is hypothesized to influence individuals’ trust in specific individuals with whom they have personal relationships For instance, this propensity might affect how individuals initially perceive and

interact with others, which might then impact the ultimate level of trust in the relationships

Although most definitions of trust seem to have a common conceptual core (Rousseau et al., 1998), individual researchers have utilized different operational definitions of trust This has resulted in potentially different "definitions" of trust Scholars themselves have suggested that trust comprises multiple dimensions (Clark and Payne, 1997; Cook and Wall, 1980; McAllister, 1995)

McAllister (1995) suggested that interpersonal trust can be categorized into two different types: cognitive and affective Cognitive forms of trust reflect issues such as the reliability, integrity, honesty, and/or fairness of a referent Affective forms of trust reflect a special relationship with the referent that may cause the referent to demonstrate concern about one's welfare Other definitions have implicitly combined these two types into an overall measure of trust Although the concept of trust has been defined in a number of ways, a good definition is offered by Rousseau

et al (1998, p.395), who proposed that trust is: "a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intent ions or behavior of another."

There are two main perspectives on trust: relationship-based and based (Dirks and Ferrin, 2001) The relationship-based perspective of trust in the literature focuses on the nature of the relationship Trust researchers from this perspective describe trust as operating according to a social exchange process, such that the parties operate on the basis of goodwill, and the perception of mutual obligations (Blau, 1964) The exchange denotes a high-quality relationship, and issues

character-of care and consideration in the relationship are central This relationship-based

perspective is based on principles of social exchange and deals with an individual’s willingness to reciprocate care and consideration that another may express in a relationship (Konovsky & Pugh, 1994) A second perspective is the character-based perspective which focuses on the perception of the character of the parties in the relationship (Mayer et al., 1995) This perspective implies that parties attempt to draw inferences about the other’s characteristics such as integrity, dependability, fairness, and ability From this perspective, perceptions of the trustworthiness of the parties in the relationship become important

Trust is a dynamic construct reflecting an individual's perceptions of environment relationships Granovetter (1985) and Lewis and Weigert (1985) defined trust as a willingness to be vulnerable to others, based on the prior perception that those others are trustworthy (Mayer, Davis, and Schoorman, 1995; Mishra, 1996; Sitkin and Roth, 1993) Being vulnerable means that a significant potential for loss exists for an individual (Deutsch, 1973; Luhmann, 1979; Zand, 1972) Scholars have documented several key dimensions of trustworthiness, including a concern for others' interests, competence, openness, and reliability (Hart and Saunders, 1997; Mayer et al., 1995; Mishra, 1996) Each dimension additively contributes to a party's trustworthiness The fact that trust may be violated in instances when colleagues may be self- interested, or uncooperative, or may withhold important information reflect the vulnerability of trust

person-From the relationship-based perspective which functions primarily on expectations of social exchange, individuals’ willingness to reciprocate care and consideration is key (Konovsky & Pugh, 1994) Individuals who feel that the other party has, or will, demonstrate care and consideration will reciprocate this sentiment

in the form of a mutual exchange From the character-based perspective of trust, perceptions of the other party in a trust relation are important (Mayer et al, 1995) If, for example, a party perceives that the other does not have integrity, trust is violated Because social exchange is associated with expectations and perceptions of reciprocity, it is likely to be vulnerable to differing inferences on the nature of the relationship

2.1.4.2 ADVICE NETWORK

Research in the social network tradition has demonstrated the importance of personal connections in the construction and acquisition of information (Burt, 1992, Granovetter, 1995) To determine what people get from other people when they turn

to them for information or advice, Cross (2000) conducted in-depth interviews with forty managers in a global consulting organization The findings indicated that solutions and meta-knowledge are exchanged in advisory interactions A distinction

is made between declarative knowledge (know-what) and procedural knowledge (know-how) Cross (2000) in his study, found that out of the 68 interactions in which solutions are shared, only 9 are valued for know-what and 59 are valued for know-how The findings suggested that more of procedural knowledge is shared than declarative knowledge

Other than solutions, he also found that meta-knowledge is exchanged within advisory interactions The social interactions help to uncover information about where to find answers that are needed (meta-knowledge) The parties may learn of the location of important information (if in a database) or expertise (if in a person)

The advice network has been widely used in network studies to facilitate instrumental outcomes like innovation involvement, work performance and promotion (Ibarra, 1993; Burt, 1992; Baldwin, 1997; Sparrow et al., 2001) The knowledge that

is shared in an advisory relationship will not only benefit the advisee, but the advisor will also gain from knowing firsthand the technical problems that are faced in the advisees’ work situation This two-way exchange of information will have direct bearings on instrumental outcomes Based on its previous use and relevance to the research focus, the advice network is selected as a focus of examination in the study

2.2 ORGANIZATIONAL RESTRUCTURING

McKinley and Scherer (2000) defined organizational restructuring as any major reconfiguration of the internal administrative structure that is associated with an intentional change management program It is important to delineate the difference between various types of restructuring that take place in organizations According to Bowman and Singh (1993), there are three types of restructuring: organizational, portfolio, and financial Organizational restructuring excludes portfolio restructuring and financial restructuring such as increasing the debt level or reducing free cash flow (Bowman et al., 1999; Donaldson, 1994) The distinction is made because as Bowman and Singh (1993) pointed out, portfolio or financial restructuring may be correlated with organizational restructuring, but they are not the same phenomenon

Organizational restructuring initiatives can include downsizing and reorganization of the formal organizational structure Organizations may reorganize without downsizing Downsizing may also take place without significant changes to the formal structures Although conceptually different, downsizing and reorganization often contribute to the other Organizations in the process of aligning

their internal organizations with the external market conditions may adopt new structural changes, which produce redundancies of jobs and employees Even when downsizing is implemented without the intention of major reorganization, fewer employees are often left to do the same amount of work As a result, downsizing can itself be an impetus for reorganization to address overload and burnout (Brockner, 1988)

Organizational restructuring and reorganization efforts are and will continue to

be common organizational responses to a variety of challenges The prevailing belief

is that organizational restructuring will provide a better alignment with the external competitive environment, improve financial indicators, and ultimately improve stock price performance (McKinley and Scherer, 2000)

Organizations in decline often attribute their performance to inefficient processes and excessive bureaucracy (Cascio, 1993) To remedy these inefficiencies, organizations attempt to restructure to improve productivity and reduce costs Better earnings and improved competitiveness should logically lead to better financial performance and drive the stock price upward Unfortunately, the evidence shows that the outcomes of organizational restructuring in economic and financial terms are mixed at best Cascio et al (1997) examined 537 companies from the Standard and Poor's (S & P) 500 over a 12-year period Using a firm's return on assets (ROA) and stock returns as measures of financial performance, Cascio and his colleagues questioned the effectiveness of organizational restructuring in its ability to deliver the intended objectives of improved financial performance (Cascio et al., 1997) Contrary

to conventional beliefs about the benefits of restructuring on the bottom line, they found that organizations with the largest employment declines also experienced the