The Good, the Bad and the Ugly - Network Messages and M&A Activity -

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1 Morten H. Finslo 08XXXXX Rune O. Steihaug 08XXXXX MASTER THESIS The Good, the Bad and the Ugly - Network Messages and M&A Activity - Supervisor: Amir Sasson Submission date: Campus: BI Norwegian Business School Examination code and name: GRA Master Thesis Programme: Master of Science in Business and Economics This thesis is a part of the MSc programme at BI Norwegian Business School. The school takes no responsibility for the methods used, results found and conclusions drawn.

2 Acknowledgements First, we would like to thank Professor Øyvind Bøhren and the CCGR center for granting us access to the CCGR database. Without their help this project would never have been possible. We wish to thank our supervisor Associate Professor Amir Sasson for his support and guidance throughout the work with this thesis. He has inspired and challenged us to be creative by giving us great responsibility from the start of the project. This has allowed us to learn and do more than we thought possible. Also, we are highly appreciative for his teaching in prior courses, always having an open door to his office and for the funny remarks and comments making it always a pleasure to meet. We would also like to express our gratitude to the professors at the Department of Strategy and Logistics and Department of Financial Economics we have had the pleasure to meet at BI Norwegian Business School. Their teachings have been an inspiration throughout our Master of Science program and for this they deserve our acknowledgements. Lastly, our warm thanks go out to our respective families and girlfriends who have supported us not just during the period of working with this thesis, but for the entire five years of study. Oslo, August 2 nd 2012, Morten H. Finslo Rune O. Steihaug Page i

3 Executive Summary In this thesis we focus on the conditions under which firms past and current board and CEO networks influence their merger and acquisition (M&A) behavior and performance. Whereas previous research on behavioral effects have shown how mere exposure to an activity through network ties promote imitative behavior, we explore the possibility that this relationship is moderated by the positive or negative performance feedback the focal firm receives from their tiedto firms. We also investigate how the distinction between positive and negative M&A performance experiences in the network work as a contingent factor for the form taken by social capital. Hypotheses are developed and tested on Norwegian M&A data. Results show that the board and CEO network is a source of strategic behavior to be imitated, and that messages about the performance of network partners prior M&A activity do not moderate the effects of exposure alone. Furthermore, we find that both open and closed network structures enhance M&A performance. However, including networks performance experiences in the analysis alter this relationship: In high performing networks closed structures yield the best performance, while open structures is the preferred form when embedded in poor performing networks. Our findings corroborate on the existent literature on network-behavior and network-performance links, in addition to provide fresh insights by testing and distinguishing between the influence of positive and negative performance signals from tied-to firms. Theoretical and practical implications, as well as limitations and suggestions for future research are considered. Page ii

4 Table of contents ACKNOWLEDGEMENTS... I EXECUTIVE SUMMARY... II TABLE OF CONTENTS... III TABLE OF FIGURES... IV INTRODUCTION... 1 THE CURRENT FIELD OF M&AS: EXPLANATIONS FOR BEHAVIOR AND PERFORMANCE... 1 INTRODUCING THE SOCIAL NETWORK PERSPECTIVE... 3 INTRODUCING SOCIAL NETWORKS TO THE M&A CONTEXT... 5 THEORETICAL FOUNDATION... 7 SOCIAL CONTAGION AND IMITATION... 8 STRENGTH OF WEAK TIES SOCIAL CAPITAL AND STRUCTURAL HOLES SOCIAL CAPITAL AND NETWORK CLOSURE DISTINGUISHING STRUCTURE FROM RELATIONS CONTINGENCIES OF SOCIAL CAPITAL AND IMITATIVE BEHAVIOR HYPOTHESES METHODOLOGY SAMPLE AND DATA COLLECTION DEPENDENT VARIABLES INDEPENDENT VARIABLES CONTROL VARIABLES RESULTS AND ANALYSIS MODEL PERFORMANCE AND ECONOMETRIC ISSUES M&A BEHAVIOR: IMITATION AND PERFORMANCE SIGNALS M&A PERFORMANCE: SOCIAL CAPITAL AND PERFORMANCE SIGNALS SENSITIVITY ANALYSES DISCUSSION IMPLICATIONS LIMITATIONS AND FUTURE RESEARCH CONCLUDING REMARKS APPENDICES REFERENCES Page iii

5 Table of Figures FIGURE 1 ARTICLES WITH KEYWORD SOCIAL NETWORK... 4 FIGURE 2 RESEARCH MODEL TABLE 1 CORRELATION MATRIX PAST NETWORK LOGIC TABLE 2 CORRELATION MATRIX CURRENT NETWORK LOGIC TABLE 3 CORRELATION MATRIX OLS REGRESSIONS TABLE 4 REGRESSIONS FOR M&A BEHAVIOR TABLE 5 REGRESSIONS FOR M&A PERFORMANCE Page iv

6 Introduction With increasing globalization, less restrictions on cross-border capital flows, and the world economy growing steadily and fast, mergers and acquisitions (M&As) has year-by-year hit new record highs peaking at close to four trillion USD in 2006 and 2007 (Barkema and Schijven 2008a). M&A activity tend to move in waves and is very sensitive to global cycles (Andrade, Mitchell, and Stafford 2001); a point that was effectively illustrated by the sharp drop observed following the financial crisis in Two years later global M&As were totaling at 2.4 trillion USD (Thomson Reuters 2011). The comparable numbers for Norway in 2010 were approximately 12 billion USD (KPMG 2011). Regardless of the movements and relative sizes, the activity has significant practical importance both in strategic and monetary terms. The increased importance has resulted in more academic studies focusing on both antecedents to and outcomes of M&A activity (Haleblian et al. 2009). Despite the broad attention given, new explanations and understandings rapidly emerge as scholars from multiple fields show interest in its causes and consequences. Haleblian, Kim, and Rajagopalan (2006, 368) encourage future research to incorporate characteristics of board of directors and management team to explain variance in organizations M&A decisions. Following this, we will in our thesis use board and CEO networks as explanatory variable for M&A activity and performance. The network perspective could provide fresh insights into the decision-making processes underlying this important strategic activity. Our study will consist of two parts: One explaining the propensity to engage in M&A activity, i.e. looking at the antecedents explaining this behavior; the other part will be concerned with explaining the performance or outcome effects of the activity. The current field of M&As: Explanations for behavior and performance Antecedents of M&As: Most commonly used independent variables In their review of the M&A literature, Haleblian and his colleagues categorized variables used by researchers to explain M&A activity into four generic categories: (i) value creation; (ii) managerial self-interest; (iii) firm characteristics; and (iv) environmental factors (Haleblian et al. 2009). Page 1

7 Value creation encompasses efficiency concerns and generation of economies of scope (e.g. Kaplan and Weisbach 1992; King, Slotegraaf, and Kesner 2008), as well as explanations from agency theory and the market for corporate control. The latter following the classic argument from Jensen (1986) arguing that takeovers are triggered by agency costs. A bidder can solve this problem and create value if it has better governance than the target firm. The second category, managerial self-interest, is used as an explanation in many corporate governance papers. Generous, equity-based compensation plans (Harford and Li 2007), overconfidence and hubris (Hayward and Hambrick 1997), and a variety of takeover-protections (for examples see Becht, Bolton, and Röell 2002) are all examples belonging to this category. Third, characteristics of the individual firm have also been used to explain acquisition behavior. Experience and learning as a motivator are common across many studies (for a review see Barkema and Schijven 2008a). For example focal firm s performance and previous acquisitions (Haleblian, Kim, and Rajagopalan 2006), and target similarity (Yang and Hyland 2006) have been found as powerful explanatory variables. Lastly, there are effects from environmental factors. Theories emphasizing the influence of other organizations upon the focal firm (DiMaggio and Powell 1983; Pfeffer and Salancik 1978) have been popular for some time. Mutual dependence and power imbalance (Casciaro and Piskorski 2005), and exposure to M&A activity from tied-to firms (Haunschild 1993; Haunschild and Beckman 1998) are examples of independent variables from this category used in empirical papers. Outcomes of M&As: Moderating variables Most, if not all, of the above mentioned variables could be used to explain performance effects in addition to the propensity to engage in M&As. Nevertheless, several variables moderating the relationships are identified in the M&A literature. Bruner (2005) uncovered in his meta-analysis of over 130 academic papers that M&A performance are most significantly influenced by several deal characteristics: Degree of relatedness between bidder and target; whether markets are hot or cold; the target s listing status, i.e. public or private; and payment type. In a similar vein, Agrawal, Jaffe, and Mandelker (1992) found the merger/acquisition distinction to affect post-m&a success. Others, for example Wright et al. (2002), looked at managerial effects and showed the effect of insider Page 2

8 ownership and CEO-compensation packages on stock market returns. Adding to the managerial effects discussed above, outside director expertise in acquisitions are found to exert significant influence on M&A success (McDonald, Westphal, and Graebner 2008). Firm characteristics such as size of target and bidder, their performance, and M&A experience are also much used variables impairing or enhancing performance. Servaes (1991) tested the first two variables finding that high bidder performance (as measured by Tobin s Q) and large size relative to target both lead to better post-acquisition performance. The experience variable, on the other hand, shows mixed results. Zollo and Singh (2004) found experience alone to have no effect on operating performance, while Haleblian and Finkelstein (1999) found a U-shaped relationship between experience and performance. Despite the wide variety of moderating variables used to explain performance, few studies connect M&A performance to the social network of the board and CEO (for exceptions see Beckman and Haunschild 2002; Haunschild 1994). We believe further investigations of a network-performance link will enrich and further develop current understandings of M&As. Introducing the social network perspective Explaining differences in firms behavior and performance, the main concern of management research, have by researchers typically been done by considering firms to be autonomous entities gaining competitive advantage either from sources external to the firm (e.g. industry structure) or from internal characteristics (Gulati, Nohria, and Zaheer 2000, 203). However, in the later part of the 20 th century huge growth (see figure 1) has been seen in the incorporation and use of social network analysis to explain economic action (Borgatti and Halgin 2011). The development can be seen in parallel with other shifts in social sciences in the second half of the century away from the structuralist movement (e.g. Lèvi-Strauss 1971) towards the more relational-oriented post-structuralism (e.g. Barthes 1972). More formally, the phrase social network refers to the set of actors and the ties among them (Wasserman and Faust 1994, 9). The network perspective sees actors as embedded within complex networks of relationships that shape their behavior by offering opportunities for and imposing constraints on action. This differs from the more traditional accounts in management studies using atomized-actor explanations, i.e. focus on attributes, but rather adopt a more Page 3

9 GRA Master Thesis sophisticated account of economic action focusing on structured patterns of interaction (Granovetter 1985) Number of articles with keyword "social network" Figure 1 Articles with keyword social network Source: ISI Web of Science The increasing popularity of social network analysis has resulted in the application of network theories to a wide range of topics in management research. Given its great versatility, network analysis has been conducted in combination with a variety of theoretical perspectives such as organizational learning, resource dependency, institutional and agency theory, and the resource-based view. In general, studies of network effects could be classified as choice or success studies (Borgatti and Halgin 2011, 8). The first category has mainly been interested in using networks for explaining similarity in choices, for instance adoption of practices, and is referred to as social homogeneity-studies by Borgatti and Foster (2003, 1002). The second category success, on the contrary, is closely related to social capital and focuses more on the benefits that can be accrued from holding a certain position in a network. Most existing choice studies seems to take for granted that simply observing repeated actions of some kind in an actor s network will result in an increased likelihood of the focal actor quickly conforming to the observed trend and engage in the same activity (for notable exceptions see Davis and Greve 1997; Galaskiewicz and Wasserman 1989). The danger by such an assumption is that it relies too heavily on social structural mechanisms for behavior and risks ignoring important and deeper aspects of the networks relational nature. While influential on behavior (e.g. Burt 1987; Davis 1991), exposure or observation of a practice from partners in a network alone does not (necessarily) imply strong relational ties to exist. Strength or quality of relations cannot be disconnected from structural explanations of behavior and performance (Rowley, Behrens, and Krackhardt Page 4

10 2000). By putting more emphasis on the influences from the content of messages obtainable through network ties, i.e. characteristics of the relationships, we will get better indications of relational mechanisms effect on behavior. Thus, we believe strong gains could be achieved by incorporating more elements of dyadic properties into explanations of choice processes. Stated otherwise, the quality of information you obtain from your network, which amongst others comes from previous experiences, success and social capital of the focal actor s connections, may very well moderate the likelihood that the focal actor will conform to activities observed in his/her environment. The argument is transferable to success studies as well; information received interacts with structural properties to yield outcomes. Hence, information signals transmitted through the network s ties may significantly alter the level of social capital given by the actor s network position. For reasons discussed more in-depth below, M&As are an apt setting for testing these predictions. Social networks can be studied at several levels of analysis. We will be applying it at the organizational level, and more specifically formalize social networks in the form of board and CEO ties. Much work has been done in this field explaining imitation of practices, innovation processes, performance consequences, and formation of other interorganizational relationships such as joint ventures (for reviews see Borgatti and Foster 2003; Brass et al. 2004). Still, there are many areas that remain underexplored by researchers, for instance processes underlying M&A activities and outcomes. Introducing social networks to the M&A context Novelty of a practice or environment has been found to increase the rate of imitation for individuals (e.g. Miller and Thelen 1986). In strategic management literature similar mechanisms are seen at the firm level of analysis, with studies having found declining propensity of imitative behavior as a practice becomes well-established within its field (e.g. Guillén 2002). As noted earlier, networks speed up diffusion and are influential in the ultimate distribution of ideas (Borgatti and Foster 2003, 1005). Thus, when applied in a novel setting imitation effects will likely be particularly strong. For example, the much-cited article by Davis (1991) on the diffusion of poison pills in American companies could be severely affected by the novelty of the takeover defense at the time from which the sample was drawn. The novelty argument can also be applied to the study of medical Page 5

11 innovation by Burt (1987) (using data from Coleman, Katz, and Menzel 1966); the large and unfamiliar market of non-profit organizations studied by Galaskiewicz and Wasserman (1989); and the first-wave effects from board reforms in Canada by Shiplov, Greve, and Rowley (2010). By contrast, we argue that M&As are well-established activities familiar to most firms either through first or second-hand experience which implies the context to a large extent precludes some perverse effects possibly present in earlier studies on imitation and diffusion through board and CEO networks. However, the existing studies using networks to explain behavior in this context are heavily tilted towards more structural explanations (Haunschild 1993) arguing that the mere effect of being exposed to a certain activity result in the desire to achieve peer isomorphism. The few contributions made linking networks to M&A performance are slightly more sophisticated in their analyses compared to the behavioral studies. Haunschild (1994) and Beckman and Haunschild (2002) look at the premium paid by the focal firm, and find it to be significantly related to premiums paid by interlocking partners. The latter paper even incorporates an organizational learning perspective arguing that the content of information received from interlocking partners affects behavior and performance. However, the use of premium paid as performance measure for studies in general is debated (Zollo and Meier 2008). As such, Beckman and Haunschild s (2002) measure could be criticized for not testing post-m&a success. In addition, there is no discussion of whether different network structures promote or restrain learning to yield different outcomes either. This would have been an interesting perspective to take given the substantial debate over different forms of social capital reviewed later in this thesis. We argue there to be value derived from closing these discrepancies and investigate further if there can be found moderating effects of M&A activities from the content and properties of a firm s network relationships. Like our empirical study, our research question has the form of two sub questions. First, we want to test if information content is a behavioral moderator for structural position and network experience of organizations in the M&A context. Thus, we will attempt to answer the following question: Does past merger and acquisition performance in the focal firm s network influence their current merger and acquisition activities? Secondly, we aim at investigating at a more general level Page 6

12 how performance feedback from network partners influences an actor s choices and performance. Therefore, we will try to answer in our paper: To what extent do structurally similar actors exhibit differences in their agency and strategies when they receive dissimilar information on the outcomes of previous behavior in the network, and will the information received significantly influence subsequent performance? That is examine if the choices, operationalized as propensity to imitate, and/or success, i.e. social capital, of an actor vary based on the dyadic properties on which it is based. In an attempt to answer the outlined questions, we develop a set of hypotheses related to network position and experiences held by partners to a focal firm. Our data consists of all domestic M&As undertaken by Norwegian firms in the time period of , while network and performance data are obtained from the CCGR-database available at BI Norwegian Business School. By distinguishing between positive and negative contents communicated through network ties, our research is able to enrich theoretical discussions regarding effects of social structures and agency in general, and processes underlying M&A behavior and strategies in special. Also, by bringing forth the content of the message transmitted and connect it with network structures we aim at both identifying an important contingency of social capital, and see how certain structural arrangements facilitates for or disable learning and strategies affecting M&A performance. The rest of the paper is structured in the following way: First, we provide a comprehensive overview of theoretical and empirical accounts of imitation processes, social capital, and various contingencies of both behavior and performance in a social network perspective. We then move onto our methodology chapter presenting our data and formulations of the variables used. The last chapters include results, discussions on theoretical and practical implications, limitations, and concluding remarks. Theoretical foundation Crucial to our understanding of how board and CEO networks may significantly influence M&A behavior and success, is a review of the most prominent theoretical and empirical contributions in the field of social networks. The theories and concepts discussed form the fundament for the overall discussion of Page 7

13 the thesis, namely the inherent tension between social structures and agency, and how this in turn affects outcomes here in the specific context of M&As. Our review is organized in the following manner: First, we present imitation models and discuss how these relate to networks to promote certain behaviors. Second, we discuss theoretical and empirical papers explaining success primarily as a function of network structure. This part goes under the label social capital, and a deep understanding of the theories here are essential to answer the outlined research questions. Lastly, we review a recent stream of literature on contingent factors for both success and behavior in a social network perspective. The reader may find it helpful to keep in mind that we will use different network characteristics as independent variables on Norwegian M&A data. Our hypotheses later presented are derived from the reasoning around explicit and implicit assumptions from the theories reviewed next. Social contagion and imitation A well-studied segment in the network-literature is on social homogeneity and contagion. Theoretical explanations for this are rooted in the isomorphic processes described by DiMaggio and Powell (1983): (i) Coercive isomorphism resulting from formal and informal external pressures and problems of legitimacy; (ii) mimetic isomorphism which is the active adoption of an external practice as a response to environmental uncertainty; and (iii) normative isomorphism stemming from increasing professionalization of fields. It is the second category that is being most applied to the studies of networks. Given the inherent uncertainty and desire for change behind M&A activities, this category will be appropriate for our discussion as well. Instead of explaining variation in behavior, DiMaggio and Powell ask the question of why organizations are so similar and point to a paradox observed from structured fields of organizations: Rational actors make their organizations increasingly similar as they try to change them (DiMaggio and Powell 1983, 147). When facing uncertainty, organizations model themselves on other organizations within the same field who they perceive to be more successful or legitimate. What is often observed is that the first adopters of a certain practice are driven by a genuine desire to improve internal efficiency and performance. But as more and more organizations conform to the same given way of doing things there is no longer a strategic choice behind adopting the practice amongst the followers; Page 8

14 it is merely conceived to be the only way of obtaining legitimacy. Thus it can be argued that the ubiquity of certain kinds of structural arrangements can more likely be credited to the universality of mimetic processes than to any concrete evidence that the adopted model enhance efficiency (DiMaggio and Powell 1983, 152). Important to note here is that imitation is expected to happen even in the absence of proof that it will increase internal efficiency 1. Including social networks to the mimetic process, DiMaggio and Powell (1983, ) hypothesize that boundary-spanning personnel in an organization enhance the likelihood that the above processes will take place. Discussions regarding the latter hypothesis of DiMaggio and Powell, and among network scholars in general, have centered around two contagion mechanisms: Structural equivalence and cohesion. Burt (1976, 96) defines structural equivalence as two actors that have identical relational ties to all other actors. A less strict definition is that actors/nodes with similar structural environment will exhibit similarities in behavior (Borgatti and Halgin 2011, 8). This implies that sameness in centrality leads to more similar attitudes and behavior. Contagion by structural equivalence focuses on symbolic communication: An ego and alter close in social distance are in competition, and thus provide the most vivid models for imitation (Burt 1987). Implicit here is the expectations that adhere with a network position; to affirm in-group membership and distance themselves from the out-group, individuals in structurally similar positions are expected to express similar perceptions and attitudes (Galaskiewicz and Burt 1991, 89). That is, the central actor wants to act similarly to other central actors. Hence, when observing increased M&A activity amongst his/hers alters, ego s propensity to engage in the same activity is increased. Cohesion on the other hand, focuses on behavioral communication rather than symbolic. Models for imitation are not directly related to your position, but rather on the frequency of communication between ego and alters; more frequent interaction increases likelihood of adoption. Through discussions the network members come to a normative understanding on the costs and benefits of conducting an activity; an understanding highly influential for subsequent choices made by all actors. While the structural equivalence model 1 Externally efficiency may increase however, although not necessarily intended, as a result of an easier transactional environment being more similar to peers. Page 9

15 does not make any specific predictions to network tie types, the cohesion model is closely related to closure ties (Coleman 1988, 1990). There exist several empirical accounts testing the theoretical predictions just described. Galaskiewicz and Wasserman (1989) tested and found support for DiMaggio and Powell s hypothesis on the likelihood of organizations mimicking other organizations they shared boundary-spanning personnel with. Burt (1987) found structural equivalence to dominate cohesion amongst a set of Midwestern physicians in the 1950s. Similarly, Galaskiewicz and Burt (1991) found overwhelmingly support for structural equivalence as the main source of contagion in their study of corporate philanthropy: The majority of contributions to nonprofit organizations were determined and evaluated on the basis of opinions held by peers in the social structure rather than personal and direct communication. On the contrary, Davis (1991) found direct contacts and the cohesion model to best explain the diffusion of poison pills - a takeover defense initiated by U.S. companies in the 1980s. Other cases of imitation can be found in Palmer, Jennings, and Zhou (1993) showing how the multidivisional form diffused through interorganizational networks. Haunschild (1993) is the only one who has studied imitative behavior in the M&A context. She finds strong evidence for focal firms imitating tied-to firms in M&A activities. The results are robust and hold after controlling for many traditional managerial and financial explanations. What is missing from her study however, is the control for information content (i.e. tied-to firms M&A performance) that will likely influence both where in the network adopters are placed and the practice s speed of diffusion (Davis and Greve 1997, 16). While it remains clear that networks are influential in ensuring rapid diffusion of models for behavior, the current literature has held focus on the relation between structures and communication disregarding the message transmitted. Distinguishing between positive and negative contents of a message will give rise to different interpretations by actors in the network influencing their feelings of uncertainty, and in turn potentially trigger change in behaviors away from the observed practice. This important contingency of the network-behavior relationship is to date largely ignored. Page 10

16 Strength of weak ties One key contribution to social network theory comes from the strength of weak ties-argument made by Granovetter (1973). Granovetter argues that analysis of social networks is a tool linking micro-interaction with macro implications. More specifically, he uses the strength of interpersonal ties to explain several macro phenomena such as diffusion and social cohesion (Granovetter 1973, 1361). The strength of weak ties-argument is organized from explicit premises and conclusions. Firstly, Granovetter hypothesizes that the stronger the tie between two individuals, the more likely they will have overlapping friendship circles. That is, they will both be connected to the same people through a strong or weak tie. This is a transitivity argument of a relation, capturing the notion a friend of a friend is a friend (Wasserman and Faust 1994, 150). The reason for this, he further argues, is that strong ties most often imply similarities between two individuals. Thus, if person A has a strong connection to B and C, B and C are more likely to be similar and form a friendship tie (strong or weak) once they meet. The implication being that similarity causes ties to be formed gradually altering the overall network structure of individuals. Secondly, Granovetter emphasizes the importance of bridges in transmitting information and ideas. A bridge between the two individuals A and B provides the only route along which information or influence can flow from any contact of A to any contact of B, and, consequently, from anyone connected indirectly to A to anyone indirectly connected to B (Granovetter 1973, 1364). Combining the two arguments stated above, Granovetter concludes that bridges are highly unlikely to consist of strong ties. The reason is that transitivity argument of a relation, suggesting that the only condition under which a bridge is a strong tie is when neither party of a dyad has any other strong ties. Granovetter never states that all weak ties are bridges, however all bridges are weak ties (Granovetter 1973, 1364). With bridges being the source of more novel information, and all bridges being weak ties, individuals or organizations with the most weak ties will be the top performers and best placed to transmit unique and nonredundant information across large, disconnected networks. At first it may seem odd that an actor with more weak, rather than strong, ties will be most successful. However, actors in closely knitted networks are likely to have equal Page 11

17 access to information. Thus, the informational advantages from having many bridges (and in turn weak ties) and the stronger global cohesion this entail at a group level, result in a situation where social structure can dominate the motivation your close acquaintances have in helping you (Granovetter 2005). That is, social structure influences both likelihood of making specific choices and their subsequent success. Granovetter s arguments would imply that the board and CEO network structure influence focal firms M&A performance. Since structure may dominate dyadic properties, firms should proceed in two steps: First design their network, and second exploit potential benefits of their partners knowledge. This gives access to novel information first, while there is only the potential of there being positive second-order effects from the properties of the relations (e.g. knowledge on how to proceed with the information transmitted). Also implicit in the argument is that firms should sit on boards outside their own industry. Since equality is a source of strong ties, and none strong ties are bridges, then diversity is key to competitive advantages. Taken together, the strength of weak ties-argument is a structural argument of value derived from information access through network ties. Social capital and structural holes Although Granovetter (1973) never explicitly mentions social capital, his theory discusses the concept per se. One that more directly deals with this concept, and further builds upon many of the ideas put forth by Granovetter, is Burt (1992) with his structural holes theory of social capital. Burt sees social capital as a metaphor about advantage (Burt 2000, 2002a). He further argues that a player brings at least three kinds of capital to the competitive arena: Financial, human, and social capital. The latter is the contextual complement of the first two: Through relations with colleagues, friends, and clients come the opportunities to transform financial and human capital into profit (Burt 1992, 9). Social capital then concerns both whom you reach and how you reach them (Burt 1992, 12). Still, the question of who is largely ignored by Burt instead focusing on how a player is connected. Behaviors by players in a network can vary greatly depending on the setting, but it is always the overall structure that provides rewarding opportunities. As such, networks do not act; they are a context for action (Burt 2004). Page 12

18 Social structure, or more precisely structural holes, can create benefits for a player or individual advantageously positioned in the network. A structural hole indicates that there is a relationship of nonredundancy between two contacts. Because there is a hole between the two, the network benefits that can be drawn from them are additive rather than overlapping (Burt 1992, 18). Since people with access to the same contacts or groups are likely to focus on similar activities and hold equal information, structural holes are created. Given there are greater similarity within than between groups, people whose networks span or bridge structural holes will have early access to rich sources of information that in turn gives them competitive advantage (Burt 2004). Following this logic, the position a player inhabits in a social structure could be seen as a valuable asset; that asset is social capital, in essence, a story about location effects in differentiated markets (Burt 1997, 340). Stated otherwise, social capital is a function of the brokerage opportunity in a network (Burt 1997, 2001, 2004). Brokering opportunities give rise to benefits of two kinds: Information and control. More precisely, participation in, and control of, information diffusion underlies the social capital of structural holes (Burt 2001, 34). Information benefits occur in three forms: Access, timing, and referrals (Burt 1992). Since some contacts may lead to the same information, the player needs to optimize his network structure creating an efficient-effective network. Efficiency concerns maximizing the number of nonredundant contacts so as to maximize the yield in structural holes per contact (Burt 1992, 20). Effectiveness, on the other hand, is about the total number of people you reach through your primary contacts. For control benefits, the ideal position is being the tertius gaudens, i.e. a person who benefits from brokering between others (Burt 1992, 30-34). Structural holes provide a setting for control to be exercised, while information is the substance in this structure. Hence, information and control benefits work mutually reinforcing strengthening the position and power of a player that in turn increases this player s social capital and rates of return. The concept of structural holes is very similar to that of Granovetter s (1973) bridges. Nevertheless, there are some distinctions. First, Burt holds a more instrumental and strategic view on social capital. While the two are equally deterministic when it comes to the consequences of network structure, Burt gives an agent or player more autonomy in designing his/her own network. This agency Page 13

19 component has received far less attention than the structure component (Buskens and van de Rijt 2008, 373). Second, Burt sees tie weakness as a correlate, and not cause. In addition he argues that information benefits will transmit over any bridge regardless of its strength, and the strength of weak ties-argument does not take into consideration the control benefits of structural holes (Burt 1992, 27-30). Empirically Burt s arguments of social capital as a function of the brokering opportunities in a network have been tested and given support in a variety of studies across different contexts and levels of analysis. To mention only a few, the presence of structural holes has been found to explain profit inequalities between industries (Burt 1988); accumulation of power amongst individuals (Cook et al. 1983); increase in salary, positive job evaluations, and likelihood of promotion for individuals and teams (Burt 2004; Gabbay and Zuckerman 1998; Reagans and Zuckerman 2001); access to more information and opportunities resulting in innovative outputs (Hargadon and Sutton 1997; Lee 2010; McEvily and Zaheer 1999); and changes in market shares for mutual funds (Zaheer and Bell 2005). The broad empirical support given to the structural holes-argument strongly suggests it to be one form taken by social capital. Focus among scholars using Burt s conceptualization is on individuals leveraging upon opportunities residing in their structural environments. The ideas and arguments are often applied in combination with theoretical perspectives emphasizing the actions of individual actors such as resource dependency, organizational innovation, and the resourcebased view of the firm. However, many of the studies are static, one-shot pictures or find the advantages gained to be short-lived in character (e.g. Soda, Usai, and Zaheer 2004). Thus, not all accounts see benefits as coming from informational transmission across structural holes or bridges; many argue that network closure is the social structure yielding best advantages. Social capital and network closure Whereas Burt emphasizes the value enhancing effects of brokerage and cooperation, Coleman (1988, 1990) argues that a closed network structure has some distinct advantages that are the source of social capital. Coleman defines social capital by its function: It is not a single entity, but a variety of different entities having two characteristics in common: They all consist of some aspect of a social structure, and they facilitate certain actions of individuals who are within Page 14

20 the structure (Coleman 1990, 302). Three forms are identified in Coleman s (1988, 1990) concept of social capital: (i) Obligations and expectations, (ii) information-flow capability of the social structure, and (iii) norms and effective sanctions. Coleman argues that social capital comes through closed networks that engender agency, either individual or collective. Taking into consideration the three forms identified above, closure of a network does two things for the behavior and outcomes of the people in it. First and foremost, it facilitates for effective sanctions against players acting opportunistically. This implies that people may forgo their own primary interest to act in the interest of the collective (Coleman 1990, 311) because the second-order effects from violating the established norms may prove too harmful. In an open structure, like Granovetter (1973) and Burt (1992) describes, reputation cannot arise, and thus collective sanctioning will be impossible. Closure then emerges as the only alternative to create systems of trust (Coleman 1988, ; for counterarguments see Burt 1999). The effect is a reduction in the risk of trusting others, and in turn the cost of economic exchanges. Any actor in the network will benefit from this as he/she is better positioned to cooperate and draw upon resources from others. As this process reiterates network structures will be reproduced, continuously adding more value to the underlying capital. This effectively illustrates another property of Coleman s notion of social capital, namely the public-good aspect of it (Coleman 1990, ). Secondly, the information flow of a closed structure is highlighted. One of the forms of social capital is the potential for information in relationships, as this serves as a basis for action. However, information search is costly (Coleman 1988, 104). Closeness to other knowledgeable actors can provide information needed on subjects the focal actor otherwise does not have the capacity to focus on. Several examples of the information-flow capability of closed networks can be found in Coleman (1988, ; 1990). The effects of network closure have received significant attention among scholars, and been found as a strong predictor of choices and outcomes for individuals, groups, and organizations. In most papers the above mentioned characteristics of closure triads have lead focus towards collective agency mechanisms when discussing Coleman s arguments. They are commonly applied together with a learning perspective, processes underlying structurations of fields, or transactional Page 15

21 efficiency. Some of the most cited contributions on behavior are on adoption of medical innovations (Coleman, Katz, and Menzel 1966); reproduction of existing network structures in biotechnology (Walker, Kogut, and Shan 1997; see also Burt 2000, 365 for a comprehensive list of studies in the biotech setting); enforcement of social norms (Piskorski and Gorbatai 2010); organizational governance (Rowley 1997); knowledge transfer (Hansen 1999; Uzzi 1997); and involvement in innovation tasks (Obstfeld 2005). Some of the above include performance effects, other examples are found in the board interlocks literature using the cohesion model (for a review see Mizruchi 1996, ), and for investment bankers information acquisition (Gargiulo, Ertug, and Galunic 2009). The insights of Coleman can be applied in making predictions about M&A activity. Equal to Granovetter (1973) and Burt (1992), it is the structural properties of the network that are powerful in explaining patterns of behavior and success. First, given the expected sanctioning if violating norms of behavior, all actors will contribute with the information they hold. Second, the closed structure allow for fast information spread so that all actors quickly possess the same information. This reduce searching costs for firms, but limit their opportunities to exploit novel information: If the value of potential M&A targets is known to all, then increased competition for undervalued targets will drive up the premium paid. Hence, closure seems to be more beneficial when learning about the properties of an action, in contrast to opportunities for it. Stated otherwise, closure may lower risks but also precludes abnormal rewards from strategic actions. If this is the case, network closure gives advantages compared to open network structures in post-m&a activities, but not in pre-m&a processes. Distinguishing structure from relations Building on his seminal work on the social embeddedness of economic exchanges (Granovetter 1985), Granovetter (1992) makes more explicit how actors are embedded in the social structure by separating structural from relational embeddedness. What he argues (Granovetter 1992, 33) is that any explanation of behavior and performance in the economy needs to take both dimensions into account, i.e. characteristics of the overall network and the content of these relations. The structural dimension is concerning the properties of the network as a whole, and is similar to what has been reviewed earlier. Relational embeddedness, on the other hand, is more concerned with how interaction Page 16

22 between actors shape and influence their behavior over time. Emphasis is put on features such as depth of information exchange and trust (Uzzi 1996). This type of embeddedness moderates the structural conditions; similar network configurations need not yield similar outcomes. As such, relations could both enhance and constrain the opportunities offered by the overall network structure. Scholars have later tried to refine this conceptualization by linking it directly to different forms of social capital, arguing dense networks to facilitate for more relational and subsequently intellectual capital that can be transformed into competitive advantage (Nahapiet and Ghoshal 1998). Empirical accounts of relational embeddedness remain comparably few (but see for example Moran 2005; Uzzi 1997). As a result, research on structural embeddedness and relational embeddedness remain disconnected (Baum, McEvily, and Rowley 2012, 529). This disconnection has sparked new debates among scholars on the dynamics and contingencies of network structures in an attempt to give more accurate descriptions of the interactions between social structures, agency, and outcomes. Contingencies of social capital and imitative behavior Until now we have reviewed both performance, i.e. social capital, and imitation solely as a function of a network s structural properties. This reflects the general pattern in the literature, even if some authors acknowledge that they do not believe this is entirely true (Burt 2004, 355). The recent stream of literature discussing various contingencies between network structure, behavior, and performance can help resolve much of the mixed evidence seen across studies (Burt 2000, 383). We group the contingencies into three generic categories: (i) focal firm characteristics; (ii) context and uncertainty; and (iii) information content and feedback. Excluded from the discussion are factors not applicable to our context, e.g. cultural embeddedness (Burt, Hogarth, and Michaud 2000; Lin et al. 2009; Xiao and Tsui 2007) and some of those referred to by Burt (2000, 2002a, 1997). Focal firm characteristics The processes underlying agency in networks are not homogeneous as implicitly assumed by many, but depend on inputs provided by individuals rather than on anthropomorphized firms that imitate one another (Shropshire 2010, 247). While previously ignored, scholars now increasingly include motivation and ability, primarily characteristics of the individuals involved in board and CEO networks, Page 17

23 as critical factors in explaining diffusion of practices and performance in networks. Behavior can be considered as a stepwise process over two levels of analysis where the motivation and ability of the individuals involved precede organizational receptivity (Shropshire 2010). Accordingly, to exploit the informational and control advantages firms can obtain from their network position they must inhabit certain characteristics. First, decision-makers need to be motivated (Anderson 2008; Reinholt, Pedersen, and Foss 2011) and organizational strategies enabling them to act upon their motivation must be in place. Second, individual ability and network-enabling organizational capabilities (Lee 2010; Shipilov 2009; Tsai 2001; Zaheer and Bell 2005) will influence the relationship between network structures and behavior and/or outcomes. Incorporating focal firm characteristics into the network context gain strengths from the inclusion of a causal agent. The problematic part however, is that the lack of ability or motivation in many cases will increase the propensity to imitate (Shropshire 2010, 257). That is, since directors are not able to evaluate a proposal with the necessary quality they instead reduce uncertainty by modeling others (DiMaggio and Powell 1983). The effect being that without solid operationalization of ability-variables in empirical studies, lack of ability and exposure to an activity may yield similar results. Context and uncertainty Central to network research is the argument that the actor s social relationships offer a context for action (e.g. Brass et al. 2004). However, one should not disconnect the set of relationships from the context in which they are embedded. It is not merely the set of relationships that provide opportunities and constraints for action; decision-makers are also influenced by the strategic context where they operate (Carpenter and Westphal 2001). This notion has enriched the discussion on social capital and behavior. Gargiulo and Benassi (2000) discuss the difficulties in finding the optimal structure balancing the flexibility obtained from open networks with the safety from closed structures. The choice may be contingent on the conditions under which cooperation must take place (Gargiulo and Benassi 2000, 193). Hence for the M&A context, the network structure giving the best accumulation of social capital is contingent on where in the process the firm currently is. Similarly, Ahuja (2000) argues the effectiveness of structural holes versus closure to be a function of the context under study. M&As are Page 18

24 situations where speedy access to information is essential (Yang et al. 2011, 243); a context favoring structural holes. On the contrary, at later stages such as during post-merger integration phases the distinct attributes of closed structures may be preferred. In total, situations vary widely so the form taken by social capital is likely to be contingent on what actors seek to enable through it (Ahuja 2000, 452). The most central contextual component affecting outcomes and behavior is degree of uncertainty. Uncertainty exists in various forms, but most classifications separate between internal and external sources (Beckman, Haunschild, and Phillips 2004). Whenever present actors aim at reducing its level (Bourgeois 1984). Still, the strategies for doing so differ depending on type of uncertainty. Conducting a merger or acquisition gives rise to firm-specific or internal uncertainty (Haunschild 1994). From a network perspective the common response in this context is to broaden the search for information by initiating more ties (Beckman and Haunschild 2002; Mizruchi and Stearns 1988) or seek into brokering positions to exploit better access to more novel information (Baum and Ingram 2002; Podolny 2001). Regardless, a central position in an open network seems preferable and the type of uncertainty facing a firm will be highly influential for the strategy followed. Podolny (2001) shows that when a firm is uncertain about the quality of their future decisions, i.e. egocentric uncertainty being high, a network rich in structural holes will be of great value. The basic claim is that this network structure gives the focal firm superior information on new market opportunities, as well as on how to fill those opportunities, effectively reducing the level of uncertainty facing them. In our context this implies that firms with networks rich in structural holes should both have a higher propensity to engage in M&As, and perform better when they do so. Uncertainty external to the focal actor is usually responded to by reinforcing existing relationships (Hansen 1999; Podolny 1994) or exploit own status to extract resources from others (Castellucci and Ertug 2010). Status however, is not expected to yield any advantages to help reduce egocentric uncertainty (Podolny 2001, 42), i.e. leading to increased M&A activity and higher performance. What Podolny misses in his analysis though, is the potential second-order effects of status. Alters of a high-status focal firm may want to aspire and thus seek to connect with the focal firm (Shipilov, Li, and Greve 2011). The implication being Page 19

25 that an actor s status helps attracts valuable partners to the network that are both cooperative and possess information sought by the focal firm, in turn reducing uncertainty. Shipilov and Li (2008) argue that structural holes facilitate for status accumulation, but dampen performance. The two are correlated, however, so that the net effect and overall benefits from network structure are contingent on the information sought and uncertainty surrounding the firm. Applying these arguments to the M&A context, open networks will hold distinct advantages when seeking out targets, but be less preferred at later stages as information requirements changes to for example knowledge of post-m&a integration strategies. Overall, both behavior and the form taken by social capital are clearly contingent on context and uncertainty. Still, as the last paragraph indicates their bases change as relationships progress and new needs emerge. Hence, the inclusion of more dynamism to the network perspective could greatly enhance its explanatory power. Information content and feedback If one take the perspective of networks as pipes transmitting information between actors (Podolny 2001), then it should be reasonable to expect the performance or social capital of alters to influence both ego s choices and outcomes. Actors can borrow the social capital of others (Burt 2000), for example to increase own legitimacy through the relation (Dacin, Oliver, and Roy 2007) or exploit alters status and resources to enhance firm growth (Stuart, Hoang, and Hybels 1999). Still, empirical accounts are not all supportive of this relation (e.g. Zaheer and Bell 2005); indicating that what matters is not just who the connections are but also the content of the individual relations. Podolny and Baron (1997) developed a typology where information content was decisive for performance. When strategic information about new opportunities are desired, open networks yield the best performance. Nonetheless, if the ego-alter relationship implies performance feedback and more continuous interaction, the exchanges get increasingly socially embedded (Granovetter 1985). As partners get increasingly similar, they exert more influence on each other s behavioral patterns (Haunschild and Beckman 1998; Vissa, Greve, and Chen 2010). Also quality of the content conveyed will likely be higher if the parties trust and support one another; characteristics best promoted by a closed network structure (Podolny and Baron 1997, 676). With the typology Podolny and Baron suggest what has already been indicated several Page 20

26 times in this review, namely that the basis for social capital changes with time in our context: Structural holes gives the best initial information, but to turn this information into a longer-term advantage the focal actor must initiate more ties and aim at (locally) cohesive structures. Whether the content transmitted is positive or negative, either as signals initially or in the form of feedback at a later stage, seems an obvious distinction yet it has not entered research on social capital (Burt 2000, 387). Only a few have investigated the consequences of negative contents (see for example Labianca and Brass 2006). Another approach is to study behavioral responses to the kind of content a focal firm receives from tied-to firms using performance feedback theory (Baum et al. 2005; Greve 2003). Shipilov, Li, and Greve (2011) show how the propensity to make strategic moves depend on the interaction between structural position in the network and feedback on performance. Opportunities and constraints offered by initial network position influence aspiration levels (Greve 2002), with central firms in open networks being best positioned to pursue status enhancing relationships (Shipilov, Li, and Greve 2011, 1421). This is likely to happen through search behavior; the equivalent in our context being more aggressive growth strategies using M&As. By contrast, if embedded in a closed network firms tend to display more rigidity in their strategies and hold lower aspirations. Shipilov, Li, and Greve illustrate how firms that experience discrepancy between their strategic goals and feedback received completely reverse the previously observed relationships: Firms in closed networks initiate search behavior for new strategies, while central firms in open networks lower aspirations and start focusing on building stronger ties with similar partners. Ultimately what this study shows is that the distinction positive/negative content significantly influences firms strategic behavior in a network, and that firms serve as active agents responding to the substance, i.e. information content, of the network, not only its structural properties. No one is able to maintain a structural advantage in the long run, because if, or when, they exist others will quickly recognize the benefits from that position and employ similar network strategies; the effect being evenly distributions of profits so that no actor has excess returns (Buskens and van de Rijt 2008). Still, this is not the relationship observed across studies where systematic inequalities are found. Instead, as we have seen in the above review, the contingencies identified will Page 21

27 likely interact to form complex causal mechanisms explaining differences in behavior and outcomes between firms. By incorporating an active agency component, and various contingent factors to the analysis, a more nuanced and dynamic picture emerges possibly holding greater explanatory power. Given that the focal actor inhabits the necessary ability and motivation, they can design strategies appropriate to their context and meet the inherent uncertainty of the business world. These strategies change with informational requirements, time, and performance feedback in the network. One plausible hypothesis put forth is that spanning structural holes, i.e. having an open network, is more valuable in the short-term due to its access to novel information. However, to turn an opportunity into competitive advantage the focal actor needs reliable information from cooperative partners and effective routines to exploit available knowledge; these are characteristics often found in closed networks. Hence, the value of network closure increases as a function of time (Baum, McEvily, and Rowley 2012; Soda, Usai, and Zaheer 2004). Still, the hypothesis, while in many ways uniting structural and relational characteristics, run the risk of ignoring the effect of positive or negative information. A sole focus on the opportunities and constraints offered by the respective structures at different points in time do not fully take into account the complexities of informational needs surrounding organizations in the process of strategic change, in our case the choice to perform or not perform a merger or acquisition. In fact, the information signals transmitted through the network may catalyze individual or collective interpretation and agency that is not overly dominated by structural properties and in turn be decisive of the form taken by social capital. This leads us to our specific hypotheses following next. Hypotheses Our hypotheses are a mix between the more structurally dominated explanations (hypothesis 1, 2, and 4) from the review, and the incorporation of relational mechanisms through the contingent factors of information content and feedback (hypothesis 3 and 5). We argue that traditional explanations only hold under certain conditions, and that the relationships will be moderated by the last two hypotheses. M&As are arguably a well-established growth strategy for firms (Barkema and Schijven 2008b). Given this and holding everything else equal, firms in central network positions are more likely to enact this strategy as they hold distinct Page 22

28 advantages enabling them to absorb external constraints (Pfeffer and Salancik 1978), exercise control (Burt 1992), and exploit informational advantages accruing from structural properties of the network to make better causal inferences (Beckman and Haunschild 2002, 94). Furthermore, centrality and brokering opportunities significantly influence propensity to pursue status accumulation and growth (Shipilov, Li, and Greve 2011), and search into segments high in egocentric uncertainty (Podolny 2001); characteristics achievable from M&As. Thus, strategies pursued are partly determined by structural embeddedness. In total, managers and firms with more social capital will have a continuous competitive advantage vis-à-vis firms with less social capital (Burt 1992). We believe open network structures embody certain characteristics, such as better access to more novel information and incentive for more active search and explorative behavior, so that firms inhabiting this structure hold advantages over others helping them overcome the inherent uncertainties of M&As. In turn, this should lead to higher observed activity level than for firms with more closed network structures. We therefore propose the following hypothesis: Hypothesis 1: Ceteris paribus, the more open the network structure of a firm in terms of direct and indirect board and CEO ties, the more likely it is to engage in merger and acquisition-activity compared to firms with relatively more closed network structure. In a rapidly changing and uncertain business world, firms constantly try to maneuver into new and more beneficial positions. Uncertainty however, is a powerful force that encourages imitation (DiMaggio and Powell 1983, 151). When uncertainty is prevalent turning to sources of trusted information reduce perceived risk and searching costs. Ties through board of directors are one form of boundary-spanning contacts, and a familiar source of information which is also powerful. Activity observed by this group of people is likely to affect focal firm behavior. Hence, organizations tend to mimic behavior of firms to which they have ties via boundary-spanning personnel (Galaskiewicz and Wasserman 1989). Whether the underlying mechanism through which this process takes place is interpersonal contact (Davis 1991) or observation of structurally equivalent others (Burt 1987) are difficult to predict. Regardless, networks speed up diffusion, even of practices that are widely known (Brass et al. 2004, 805). Page 23

29 In the short run (from t-1 to t), we argue, firms are especially likely to mimic the behavior of their tied-to firms. Uncertainty about the success of your partners strategies have yet to be fully understood, so the focal firm model themselves on their contacts. This way they conform to what is believed to be current industry norms and legitimate behavior. Close contact increases levels of trust (Coleman 1990) and the network gives informational benefits (Burt 1992), so when your partners acquire you acquire as a result of the trust held in either the relationships or the structure of the network. This arguing leads us to believe that recent exposure to M&A activity through the focal firm s network will function as a model for imitation, and the following hypothesis is suggested: Hypothesis 2: Recent merger and acquisition-activity amongst firms tied-to the focal firm will increase the propensity of the focal firm to engage in merger and acquisition-activity. The previous hypothesis tests the propensity to use network partners as models for imitation simply by observing them conducting an activity. This sort of testing is in line with much previous research; the firm either imitates their partners or they do not. In that tradition, explanations for behavioral choices do not take into account the possible moderating influence of the experience held by the tied-to firms (Beckman and Haunschild 2002). Networks are effective in facilitating for discussion and transmit information. Partners, and especially trusted ones, can inform about the costs and benefits of adopting a practice. Like Granovetter (1985) argues, interorganizational contacts can prove extremely useful in overcoming uncertainties surrounding economic transactions. Related experiences held by actors are brought into new decisionmaking processes. In the context of M&As this could be general knowledge and information on how to manage post-integration processes or other kinds of information not publicly available. This is in line with DiMaggio and Powell s (1983) hypothesis predicting organizations to model themselves after organizations they perceive to be successful when facing uncertain decisions. The argument also bears similarities to the system delay described by Becker (1970): Central actors in a network use their position to reduce uncertainty by observing which innovations alters adopt and how successful they presumably are. Influence are likely to be particularly strong from high status actors upon the behavior of Page 24

30 their network contacts (Podolny 1993); a status that could come from prior success (Davis and Greve 1997, 7). This tendency is further enhanced by participation in social arenas where they meet perceived successful people frequently and discuss issues at hand; boards of directors are one such place. Taken together, this will augment the probability of the focal firm undertaking a merger or acquisition itself (Shipilov, Greve, and Rowley 2010). On the contrary, if the information received from network contacts is negative, i.e. M&A activity has been unsuccessful, the opposite effect should take place; information on poor performance from the focal firm s contacts reduce the propensity to imitate their actions. Another possible explanation for why good M&A performance in the focal firm s network should increase the propensity to merge or acquire can be found in literature on performance feedback and organizational learning. Firms are believed to respond differently to good or bad performance (Haleblian, Kim, and Rajagopalan 2006), and will most likely respond to external information in a similar matter. As such only examining the effect of exposure to M&A outcomes without considering its success could be misleading. While strong performance may lead firms to conform to strategies exploiting capabilities and knowledge at hand (Greve 2003), in this case related to the continuing engagement in M&A activity, poor performance are more likely to lead to shifts in strategy (Haleblian, Kim, and Rajagopalan 2006), here equivalent to reducing M&A activity. This, we believe, will hold despite differences in structural properties of the network. Firms with many structural holes respond strongly to performance signals and starts exploring new paths for action if deviations are experienced (Shipilov, Li, and Greve 2011). Within closed networks, individual firms display less variance in strategies as a function of performance feedback, but rather conform to existing norms of behavior. Norms however, may be altered or reproduced (Coleman 1988, 1990) if several firms experience the same signals. Hence, the effects are the same as for an open network structure but the underlying agency mechanism differ being more collective as opposed to individual. We use the same logic as Zollo and Singh (2004) arguing that the true performance of the acquisition is known three years after deal closure, and that it is this performance signal the focal firm observes and is informed of by its partners. Thus, we propose: Page 25

31 Hypothesis 3: Performance of tied-to firms merger and acquisition activities in t- 3 will influence propensity to engage in merger and acquisition activity at time t. In order to survive and perform well organizations are critically dependent upon a variety of resources. When they cannot generate these resources internally they are forced to obtain them from external sources (Mizruchi and Stearns 1988, 194). From a resource dependency perspective organizational survival hinges on the ability to procure critical resources from the external environment (Casciaro and Piskorski 2005, 167). Organizations facing constraints in resource supply therefore need to position themselves in a way such that they can obtain these resources from their external environment. Interlocking directorates are one mean of doing so (Burt, Christman, and Kilburn Jr. 1980). The decline in network centrality of banks found by Davis and Mizruchi (1999) effectively illustrates how organizations may function as active agents altering their environmental constraint or create new opportunities for action. This indicates that board interlocks more generally can function as a strategic instrument in dealing with external resource constraints. Social capital gives higher rates of return, and is a function of social structures and an actor s position within that structure (Burt 1992; Coleman 1988). Being beneficially positioned will give an actor superior access to information about an industry, on optimal implementation procedures of M&As, and general knowledge which can be exploited to perform better compared to firms with less profitable structures. In the context of M&As it is our belief that social capital could take either forms discussed in this thesis, i.e. networks rich in structural holes or closure. Stated otherwise, more benefits will accrue to both strong individuals (Burt 1992) and collectives (Coleman 1988) comparable to those with mixed network structures. Hence, we want to test the following hypothesis: Hypothesis 4: There is a U-shaped relationship between the presence of structural holes in firms board and CEO networks and M&A performance. According to organizational learning theory, organizations can learn by encoding inferences from history into routines that guide behavior (Levitt and March 1988, 319). Learning can happen both through first-hand experience and experience spillovers from other organizations. Regardless, focal firm performance is affected as organizations continuously change or reinforce behaviors (Zollo and Reuer Page 26

32 2010). In the case of spillovers, the board and CEO network may facilitate for the transfer of knowledge and capabilities that can be exploited in the focal firm s pre- and post-m&a work. However, the structure of the network and the content of messages transmitted through it are likely to interact with the effect being differences in performance when changing one or both of the variables; equivalent structural conditions or partner experiences do not necessarily imply similar degree of outcome success. When exposed to strong performance in the network, this may function as a best practice -benchmark for the focal firm. Hence, they are more likely to adopt these practices. However, it is when this is combined with the internal experience and capabilities they generate the best performance (Nahapiet and Ghoshal 1998). The argument made that success of a partner fosters success for the focal firm is similar to what has been found in studies of alliance networks in biotech, where there is significant correlation between the success of a startup company and its connection to strong performing incumbents (Baum, Calabrese, and Silverman 2000). Positive performance messages transmitted through open networks, i.e. having many structural holes, are likely to reinforce current behavior and performance. This implies that detection of a positive trend is combined with access to novel information. In this situation, the network position enables firms to select among or synthesize alternatives (Baum, McEvily, and Rowley 2012, 530), resulting in high performance (McEvily and Zaheer 1999). Similar results are believed to be seen with closed networks when receiving signals of high performance from partners. Dense, persistent interaction fosters high levels of cooperation and information-sharing (Coleman 1988). The focal firm learns about the properties of the actions previously undertaken by their partners, and can use this knowledge in their subsequent M&A work; they exploit certain advantages derived from the network s structural properties. Therefore, we predict the following: Hypothesis 5a: When receiving positive performance signal from the M&A activity of tied-to firms there will be a U-shaped relationship between the presence of structural holes and M&A performance for the focal firm M&As are complex events that fail for plenty of reasons and equivalent to the success-argument above, messages of poor performing M&A activities in a Page 27

33 network are likely to affect the focal firm s subsequent M&A performance. As previously discussed, advantages of structural holes are mostly immediate (Baum, McEvily, and Rowley 2012) because firms attempt to realize potential in novel opportunities before others do. Still, implicit in this logic is that firms know what to do with the information they hold. However, structural holes work poorly with friendship (Burt 1992), so firms rich in brokering opportunities seldom learn about the properties of an action; they simply learn that it is taking place. Hence, when the signal received is negative, it is difficult to know how to break out of the negative trend. Faced with a given opportunity set the focal firm is highly uncertain of where on that set the best opportunities reside, in turn effectively reducing the value of structural holes (Podolny 2001); the efficient network structure is dominated by the dyadic properties on which it is based. By contrast, the closed network structure promotes learning about the properties of an action, not just that it has taken place. Inherent in the closed structure resides selfenforcing governance mechanisms, limiting opportunism and fostering cooperation and trust (Piskorski and Gorbatai 2010). The effect is high degrees of information-sharing (Coleman 1988, 1990), and existence of semipublic goods (Baum, McEvily, and Rowley 2012, 530) enhancing performance for all members of the network. Thus, when negative performance signals are transmitted through the network, actors coordinate their efforts and collectively learn from what went wrong. In addition, the quality of the performance feedback will likely be higher in dense networks (Podolny and Baron 1997). As opposed to what are to be expected from a network rich in structural holes, the focal firm embedded in a closed network will know what to do with the opportunities presented to them. They may not be the first or only ones to know of an opportunity, but they are the ones with the ability to achieve high performance over time. In total, when the content transmitted through the network is negative performance feedback of M&As by tied-to firms, closed network structures offer some distinct advantages relative to open structures. We therefore propose the following: Hypothesis 5b: When receiving negative performance signals from the M&A activity of tied-to firms there will be a negative relationship between the presence of structural holes and M&A performance for the focal firm Page 28

34 Figure 2 Research model Page 29