To Bond or to Bridge? Contingent Effects of Managers’ Social Capital on Organizational Performance

Abstract

A top manager’s social capital is considered a critical resource for determining organizational outcomes. However, little is known about the impact of social capital on public organizations’ performance. By dimensionalizing social capital into two subdimensions, this study investigates the impact of a superintendent’s bonding and bridging social capital on the performance of school districts. This study’s findings show that bridging social capital has positive impacts on organizational performance, but in a time of financial difficulty it worsens the negative shocks of the difficulty. Bonding social capital is found to be exactly the opposite. This study argues that choosing between bonding and bridging social capital is not an “either-or” question, and top managers are required to balance the two, depending on the situations that their organizations face.

Keywords

bonding bridging social capital performance financial difficulty contingency

Introduction

Scholars from various fields have actively studied social capital over the last two decades. Their focuses varied, including community social problems (Beyerlein & Hipp, 2005; Messner, Baumer, & Rosenfeld, 2004), education (Leana & Pil, 2006; Menahem, 2011), financial performance of local government (Menahem, Doron, & Haim, 2011), emergency management (Andrew & Carr, 2012), and policy equity (Hawes & Rocha, 2011). Moreover, research on social capital has undertaken various levels of analysis such as individuals (Belliveau, O’Reilly, & Wade, 1996; Portes & Sensenbrenner, 1993), groups or organizations (Baker, 1990), communities (Putnam, 1993), or nations or geographic regions (Fukuyama, 1995). However, there is much about the role of social capital in public management that is still unknown (Andrews, 2012).

What has been commonly believed is that social capital produces positive externalities (Halpern, 2005). However, some studies make a counterargument that social capital does not guarantee positive outcomes (Coffé & Geys, 2007; see also Bourdieu, 1985; Coleman, 1988; DeFilippis, 2001; Foley & Edwards, 1998; Olson, 1982). The acknowledgment that social capital possibly results in negative outcomes has led scholars to identify various types of social capital and contexts in which social capital is exercised. Social capital is a concept with multiple dimensions and, depending on the dimensions of social capital, it may produce positive or negative externalities (Coffé & Geys, 2007; Putnam, 2000). In this sense, this study gives attention to what Putnam (2000) calls bonding social capital and bridging social capital. Also, different types of social capital may produce different outcomes depending on types of problems that actors face (Berardo & Scholz, 2010). Taking types of social capital and contexts into account, this study investigates the impacts of a superintendent’s bonding and bridging social capital on the performance of school districts in both normal and crisis contexts.

The expected and empirically determined causal relationships from this study are that, in a normal context, bridging social capital of a top manager who formally represents his or her organization enhances organizational performance while bonding social capital of the top manager decreases organizational performance. However, in a time of crisis (e.g., unusual financial deficit), bridging social capital may not operate well enough to protect an organization’s core functions as compared with bonding social capital. To analyze the contingent effects of managerial social capital on organizational performance, Granovetter’s (1973) strength of weak ties and Krackhardt’s (1992) strength of strong ties are discussed. This study makes theoretical contributions in that it unravels dimensions of social capital—the bonding and bridging roles—and the different effects of each dimension contingent upon the level of environmental uncertainty. The theoretical implication is that to bond or to bridge is not an “either-or” question; rather, there may exist an equilibrium between the two based on the environments that organizations face, and future research needs to conduct thorough analyses of bonding and bridging social capital as well as of the environments to maximize organizational performance.

Social Capital and Managerial Social Capital: The Concept

The concept of social capital has not been uniformly defined yet, and scholars have defined and operationalized the term differently (Andrews, 2012). Coleman (1988), for instance, defines social capital as “a variety of different entities, with two elements in common: they all consist of some aspect of social structure, and they facilitate certain actions of actors—whether personal or corporate actors—within the structure” (p. 598), whereas Bourdieu (1985) defines social capital as the “aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition” (p. 248). A simple version of Putnam’s (2000) definition of social capital is “connections among individuals—social networks and the norms of reciprocity and trustworthiness that arise from them” (p. 19). Based on various definitions, social capital in this study refers to a set of social networks among people who share values, norms or trust to achieve common goals.

A number of studies of social capital have been conducted, but few scholars have investigated social capital in the context of public management. To fill this gap, this study focuses on managerial social capital meaning a top manager’s network with his or her stakeholders through which the values (contents) are reciprocally transferred to create competitive advantages to accomplish the goals of a top manager (Bourdieu, 1985; Burt, 1992, 2002).

In understanding managerial social capital, however, the level of analysis can be an issue because drawing a sharp line between a top manager as a natural man and a top manager as a representative of a public organization is not easy. Top managers form networks with others who may have some necessary resources that the top managers do not have but are desperate to have, so that they can take advantage of the networks for their own interests (Putnam, 2000). On this point, some contend that well-developed managerial social capital is not guaranteed to support the top managers’ organizational outcomes (Leana & Van Buren, 1999). However, managerial social capital is understood to be transferable to organizational operations and can facilitate organizational outcomes because top managers use their social capital for the benefit of their organizations (Acquaah, 2007; Moran, 2005). Even if a top manager develops strong social capital with reputable people for his or her own sake, the social capital may lead to a better organizational reputation in communities because the top manager is a representative of the organization. Thus, a top manager’s strong social capital may appeal to the stakeholders of the organization.

Furthermore, for measurement purposes, understanding a top manager’s social capital as an organization’s social capital may make sense. Social capital is a relational construct, and by its nature, relationships or social capital of organizations are made and maintained by the top managers who represent the organizations (for this discussion, see Acquaah, 2007; Leana & Pil, 2006; Moran, 2005). Therefore, organizational social capital can be understood through a top manager’s social capital. This point needs to be noted for this study. First, this study is interested in the impacts of a superintendent’s social capital on the performance of the school district for which the superintendent is responsible. Also, a superintendent’s social capital facilitates the sharing of information, which is essential for school district management; thus, a superintendent’s social capital is central to the operation of a school district (Leana & Pil, 2006).

Managerial Social Capital and Organizational Performance

Research on social capital deserves attention in the study of public management because managerial social capital is closely associated with organizational performance. According to resource dependence theory, organizations do not possess all the necessary resources for organizational performance, and they rely on the resources of external organizations (Pfeffer & Salancik, 1978). However, formal resource sharing through contracts is costly, and informal, voluntary resource sharing is not possible without concrete trust between resource lenders and resource borrowers. Social capital between resource lenders and borrowers enables voluntary resource sharing by developing trust between them (Putnam, 2000); thus, top managers can secure scarce but necessary financial and strategic resources, high-quality information, and opportunities for the acquisition and exploitation of knowledge from their social capital (Acquaah, 2007).

Moreover, within a hierarchical relationship, managerial social capital from their subordinates helps top managers build trust with their subordinates, which in turn reduces some economic transactions among organizational members (Acquaah, 2007; Nahapiet & Ghoshal, 1998; Putnam, 1993). For instance, principal–agent relations necessitate costly contracts for the principal to control his or her agent’s behavior, which results from asymmetric information and moral hazards. The basic assumption behind the principal–agent relationship is that an agent has more information than a principal, so the agent can take opportunistic actions. To correct the agent’s opportunism, the principal is willing to pay for precise contract writing or monitoring (Moe, 1984). However, social capital develops a high level of trust between a principal and an agent so that social capital shared by both the principal and the agent decreases the likelihood of the agent’s opportunism as well as the principal’s need to monitor the agent (Acquaah, 2007; Nahapiet & Ghoshal, 1998; Putnam, 1993). Thus, both a principal and an agent can be economically better off when they are in a well-established social capital scheme (Menahem et al., 2011).

In addition, literature on boundary spanning provides a possible logical explanation of why managerial social capital may lead to positive organizational outcomes. Basically, organizations seek information to reduce environmental uncertainties (Kramer, 2014), and it is boundary spanners who obtain, process, and deliver information for their organizations. According to Aldrich and Herker (1977), boundary spanners externally represent their organizations and interact with environmental actors. In so doing, they can obtain information from their environmental actors (Aldrich & Herker, 1977). Once they obtain information, according to Aldrich and Herker, boundary spanners selectively filter relevant information and direct the information to internal organizational members who need it. As a result, organizations’ success in adapting to environmental contingencies relies on boundary spanners’ ability to select, transmit, and interpret information emanating from the environment (Aldrich & Herker, 1977). As a representative of an organization, a top manager plays a boundary spanning role, and the role can be facilitated by a top manager’s social capital. The success of the boundary spanning role relies on the pool of information, and strong, diverse managerial social capital allows managers to expose themselves to diverse information; thus, the level of managerial social capital determines the impacts of boundary spanning roles, which, in turn, result in organizational performance.

In summary, managerial social capital developed by the top managers of an organization through a variety of networking relationships with their external constituents and internal subordinates can be used for better organizational performance. This is one of the appealing arguments for why one expects positive links between managerial social capital and organizational productivity (Acquaah, 2007).

The Dark Side of Managerial Social Capital

Although recent literature as well as empirical research on social capital have focused on the positive outcomes of social capital (Coffé & Geys, 2007), the negative side of social capital should be considered as well. For instance, terrorist organizations clearly hold strong social capital but do not generate positive externalities for the wider community (Coffé & Geys, 2007). O’Toole and Meier (2004) also find a dark side of networking: Superintendents’ social capital developed from networking with local business leaders benefits the academic performance, not of disadvantaged, but only of advantaged students, who may be the sons and daughters of the local business leaders. Furthermore, Hero (2003) argues that social capital is associated with racial and ethnic homogeneity, which does not bridge racial groups resulting in economic and civic inequality.

To identify the positive and negative impacts of social capital, efforts have been made recently to distinguish between bonding and bridging social capital (Putnam, 2000). More discussion on bonding and bridging social capital can be found in the following section.

Bonding Social Capital, Bridging Social Capital, and Organizational Performance

Social capital is a multidimensional concept (Messner et al., 2004), and bonding and bridging social capital are perhaps the most important dimensions (Putnam, 2000). The critical aspect for distinguishing between the two lies in the different types of socializing (Coffé & Geys, 2007), and researchers have investigated the different effects and roles of bonding and bridging social capital (Beyerlein & Hipp, 2005; Menahem, 2011). For instance, Beyerlein and Hipp (2005) investigated crime rates in communities, positing that bonding network structures make it difficult to connect with different groups in communities, which results in communities being more vulnerable to crime. For similar reasons, they argue that bridging network structures bring the opposite outcome. More recently, Menahem (2011) examined the different effects of bonding and bridging social capital on urban educational performance. According to Menahem, groups tied with bonding social capital construct closed, cohesive networks and limit flows of information and diversity of resources; as a result, bonding social capital eventually weakens community-level collective actions and hinders educational achievement. Meanwhile, bridging social capital mobilizes collective resources and promotes educational achievements by allowing a community’s residents to access information and to obtain resources essential for educational performance (Menahem, 2011).

The current knowledge on social capital, however, is limited at the community level, and only a little empirical research has been conducted to separate the effects of bonding and bridging social capital in the field of public management (however, see Andrew & Carr, 2012; Berardo & Scholz, 2010; Menahem et al., 2011). The following section discusses possible causal relationships between bonding and bridging social capital and organizational performance.

Bonding Social Capital and Organizational Performance

Bonding social capital is a network of individuals with homogeneous backgrounds. It tends to be inward looking and clearly distinguishes between inside and outside the boundary of the network (Putnam, 2000). Bonding social capital forms closed networks, and members in the closed networks share high levels of trust and reciprocity (Coffé & Geys, 2007). As a result, a top manager with bonding social capital can expect high commitment and loyalty from the members of his or her closed networks and manage his or her organization by exploiting necessary resources and valuable information from the members of the closed networks.

However, Menahem et al. (2011) find limitations of bonding social capital in improving government performance. They argue that bonding social capital distributes outcomes of public programs to members of closed networks, which limits negotiation with other groups for future policy bargaining and performance. Moreover, individuals with bonding social capital share similar, redundant ideas within the closed networks; as a result, they are limited in the production of new ideas or in acceptance of alternative ways of getting things done from the outside (Janis, 1982; Nahapiet & Ghoshal, 1998; C. B. Perrow, 1984; Turner, 1976). In this regard, Nahapiet and Ghoshal (1998) claim that closed networks produce “collective blindness that sometimes has disastrous consequences” (p. 245).

The problem becomes more serious when top managers, as decision makers, rely on bonding social capital. As top managers depend on information from closed networks to make decisions, the decisions may become narrow and unable to respond effectively to the changing environment. Another downside of bonding social capital may be its economic inefficiency. Granovetter (1973) argues that members of a closed network share similar information, so even if a member of the network has multiple channels, the information the member receives is redundant. Furthermore, a closed network limits a member of the network’s ability to cross-check the reliability of the information because most members in the closed network share similar information. Moreover, because of its exclusiveness and inward-looking social relationships, bonding social capital can lead to out-group hostility (Coffé & Geys, 2007). That is, a top manager with bonding social capital may enjoy high levels of trust and reciprocity with members of a closed network but may also be confined under an “us-versus-them” approach, which results in distrust toward members of other networks (Abrams, Hogg, & Marques, 2005; Coffé & Geys, 2007; Münster, 2007; Portes, 1998). As a result, a top manager’s bonding social capital may lead to ineffective organizational operation and negatively influence organizational outcomes.

Hypothesis 1: A manager’s bonding social capital may negatively influence organizational performance.

Bridging Social Capital and Organizational Performance

The characteristics and the associated effects of bridging social capital are quite opposite to those of bonding social capital. According to Putnam (2000), bridging social capital is a set of networks among individuals with heterogeneous backgrounds that crosscuts diverse external actors/networks. Thus, bridging social capital is outward-looking and covers diverse people and networks, which generate broader identities and reciprocity (Putnam, 2000). As a result, a top manager with bridging social capital can avoid in-group bias and extend social interaction to include out-group members (Marschall & Stolle, 2004).

In contrast to bonding social capital, it is often argued that bridging social capital is more likely to produce beneficial externalities (Coffé & Geys, 2007). For instance, Marschall and Stolle (2004) point out that bonding social capital prohibits members of a closed network from developing and transferring generalized trust to members of other networks, which leads to isolation from the broader community. Thus, a top manager who mostly (or fully) relies on bonding social capital is limited in his or her acceptance of various voices from outside the closed networks. However, a top manager with bridging social capital can open the boundary of the network and develop and share trust with dissimilar individuals outside the closed networks, which extends the pool of resources (Marschall & Stolle, 2004). Its openness and extendibility allow a top manager to be able to share new, different ideas with individuals in different networks so that a top manager can infuse innovation into his or her organization.

Moreover, bridging social capital lets a top manager take a structural hole position that links two or more networks which otherwise would not be linked (Burt, 1992, 2001). The structural hole between two networks does not necessarily mean that the two are not aware of each other; rather, they focus on their own networks without giving attention to the other networks (Burt, 2002). Thus, a top manager situated in the structural hole position plays a gatekeeper role by buffering or brokering his or her networks to other networks and can positively influence his or her organizational performance by taking a competitive advantage with respect to the access to new information from diverse contacts and a control advantage by bridging two other networks (Burt, 2001, 2002). Therefore, it is reasonable to hypothesize the positive link between a top manager’s bridging social capital and organizational performance as follows:

Hypothesis 2: A manager’s bridging social capital will positively influence organizational performance.

Social Capital in a Time of Financial Difficulties

This study hypothesizes about the negative effects of bonding social capital and the positive effects of bridging social capital on organizational performance. However, contingency theory and open-systems theory suggest that organizational strategies may be dependent on the organizational environment. In a stable environment, effective organizations are more formalized, centralized, and routinized, but organizations with the opposite characteristics survive when organizations face uncertainty (Child, 1972; C. Perrow, 1967; Rainey, 2009; Thompson, 1967). Likewise, the effects of bonding and bridging social capital may be conditional on the contexts in which the social capital is exercised. Unlike a normal situation, an emergency situation requires the involvement and sustained commitment of network members (Andrew & Carr, 2012). As a result, when facing environmental uncertainties, a top manager may rely more on bonding relationships with members of closed networks to protect his or her organization. For this reason, this study further investigates the different effects of a top manager’s bonding and bridging social capital in a time of financial difficulties.

Resources are essential for organizational operation, and lack of budget may limit an organization’s functioning (Wenglinsky, 1997). Although some predictable budget cuts may be manageable, more budget cuts are threats to organizational operation (O’Toole & Meier, 2010; Rho, 2013). In some contexts, including Texas school districts from which this study draws its sample, the amount of budget is set heavily but not exclusively by formula, but the budget size is not always predictable because there are many factors that influence the amount of budget such as state legislature decisions, status of the local economy, district bonds issue or even unpredictable major shocks such as a disaster which leads to relocation of resources (O’Toole & Meier, 2010). Previous empirical findings confirm the negative effects of financial difficulties on organizational functioning. For instance, O’Toole and Meier (2010) find that budget shocks negatively influence students’ academic performance, while Rho (2013) finds that budget cuts limit an organization’s capacity to directly deliver services, which results in contracting out. Given the effects of financial difficulties, this study further investigates different moderating effects of bonding and bridging social capital on the negative association between financial difficulties and organizational performance by adopting Granovetter’s (1973) idea of weak ties and Krackhardt’s (1992) idea of strong ties.

Bridging social capital involves social networks with weak ties. According to Granovetter (1973), “except under unlikely conditions, no strong tie is a bridge . . . rather, all bridges are weak ties” (p. 1364). He argues that weak ties form less dense networks, and individuals with weak ties can bridge individuals from different networks; thus, weak ties can expand one’s reach to other networks and access to information and resources that are not otherwise available.

However, social connection is not mere contacts; rather, it is intense involvement with high levels of reciprocity (Putnam, 2000). A social network is composed of nodes and ties, but not all nodes and ties are equal. The quality of a networking relationship between nodes depends on how strongly connected they are. That is, individuals connected with strong ties have a commitment to help one another when any member is in trouble. This is the strength of a strong tie (Krackhardt, 1992).

The discussion of weak ties and strong ties leads to another discussion on the different effects of bridging social capital and bonding social capital in a time of difficulties. Social relationships based on weak ties are shallow and fragile (Krackhardt, 1992). When resources are scarce and positions are insecure, a top manager experiences difficulty in obtaining the necessary resources to overcome environmental uncertainties, because individuals or organizations sharing bridging social capital may hesitate to share their scarce resources with the top manager. Members tied weakly share a relatively low level of trust, and they cannot guarantee the rule of reciprocity when everyone is suffering. In such a situation, it is likely that members with bridging social capital find it difficult to help one another, and a top manager cannot effectively take advantage of members of networks with weak ties.

Meanwhile, a top manager with bonding social capital can obtain benefits from members of the bonding social capital network in a time of difficulty, because bonding social capital reduces uncertainties of resource exchange, and members of closed networks are easily available and greatly motivated to help one another (Granovetter, 1973; Krackhardt, 1992; Moran, 2005). Moreover, members of the bonding social capital network are likely to take collective actions when they experience a turbulent and uncertain situation (Bandura, 1997); as a result, a top manager with bonding social capital can seek assistance from the collective actions to protect his or her organization and relieve the turbulent environment. Larsen and her colleagues (2004) make a similar argument that when people share similar characteristics, they are likely to attempt to protect one another from external turbulence. Their argument is also supported by their empirical study showing that the higher the bonding social capital index, the more people take actions to help one another against their common problems. Their argument and empirical findings suggest that bonding social capital best functions by leading to collective actions to protect members of the bonding social capital network in a time of difficulty. In fact, no one is comfortable with a crisis, but individuals tied strongly share a high level of trust, norms of obligations, and expectations that cause them to help one another to overcome a crisis. A top manager under environmental difficulty can obtain psychological, social, and even financial support from his or her bonding social capital network to overcome the crisis (Coffé & Geys, 2007; Coleman, 1988; Krackhardt, 1992; Putnam, 2000; Putnam & Gross, 2002). Thus, top managers with bonding social capital can effectively buffer their organizations from crises and protect their core missions.

In summary, although bridging (bonding) social capital is more (less) likely to enhance organizational performance, its impact is contingent on the environment that the social structure faces (Andrews, 2012). When the social structure undergoes a time of difficulties, the opposite effects may be plausible. Thus, this study hypothesizes the following:

Hypothesis 3: A manager’s bonding social capital will positively influence organizational performance in a time of difficulties.

Hypothesis 4: A manager’s bridging social capital will negatively influence organizational performance in a time of difficulties.

The Model

Performance management literature suggests that finding key factors central to organizational performance is essential (Ferreira & Otley, 2009; Otley, 1999). In this vein, Lynn, Heinrich, and Hill (2001) identified five key factors influencing organizational outputs and outcomes; they are environmental factors, client characteristics, treatments, structures, and managerial roles and actions. Lynn et al. argue that these five factors interdependently influence organizational outputs and outcomes, but O’Toole and Meier (2011) posit that the performance management frameworks suggested by Lynn et al. are limited because it fails to explain how these five factors are exactly interdependent. To identify key factors for performance management and to understand the theoretical and causal links among key factors and organizational performance, O’Toole and Meier (1999) have developed a contingent model of public management. The model predicts organizational performance with organizational stability, internal management, and external management in addition to organizational environment and the previous performance as follows:

O_{t} = β_{1} (S + M_{1}) \times O_{t - 1} + β_{2} (\frac{X_{t}}{S}) \times M_{2} + e_{t}

where $O_{t}$ and $O_{t - 1}$ are organizational performance at time t and time t − 1, respectively; S denotes organizational stability; $M_{1}$ is a management effort to manage the organization; $X_{t}$ represents environmental shocks at time t; M₂ represents management efforts to exploit environmental resources and to buffer environmental threats; and $e_{t}$ represents some random shocks. $β_{1}$ and $β_{2}$ are estimable parameters.

A superintendent’s social capital corresponds to managerial interactions with environmental actors (M₂) in this model, and it has two forms: bonding and bridging social capital. As this study focuses on managerial social capital, this study modifies the model’s original form in the following two ways:

O_{t} = β_{1} O_{t - 1} + β_{2} {SC}_{bd} + β_{3} {SC}_{br} + β_{4} X_{f} + β_{5} X_{t} + e_{t},

\begin{array}{l} O_{t} = β_{1} O_{t - 1} + β_{2} {SC}_{bd} + β_{3} {SC}_{br} + β_{4} X_{f} + β_{5} (S C_{b d}) \times (X_{f}) \\ + β_{6} (S C_{b r}) \times (X_{f}) + β_{7} X_{t} + e_{t} \end{array}

where, $O_{t}$ and $O_{t - 1}$ are organizational performance at time t and time t − 1, respectively; ${SC}_{bd}$ is bonding social capital at time t; ${SC}_{br}$ is bridging social capital at time t; $X_{f}$ is a measure of environmental difficulty (financial difficulty) at time t; $X_{t}$ represents all other environmental shocks at time t; and $e_{t}$ represents some random shocks. $β_{1}$ through $β_{5}$ are estimable parameters.

Equation 2 tests the direct impacts of bonding and bridging social capital on organizational performance while Equation 3 adds environmental difficulty and its interaction terms with bonding social capital and bridging social capital to Equation 2. In this study, financial difficulty is used to operationalize a measure of environmental difficulty. Further explanation will follow in the next section.

Unit of Analysis, Data, Variables, and Sample

This study sets a school district as a unit of analysis and draws a large sample from the Texas K-12 education system. School districts in Texas provide a unique opportunity to analyze the effects of top managers’ social capital in several ways. An education sector is one of the most representative public sectors in the United States. As a single sample, the Texas school districts are quite large, and “the most common public organization in the United States” (Meier & O’Toole, 2009, p. 7). More than 1% of all government officials of any type in the United States are involved in the Texas school districts (Meier & O’Toole, 2009). As an independent local government, Texas school districts empower superintendents to exercise autonomous discretion. First, superintendents have their own taxing power (O’Toole & Meier, 2010). Moreover, Texas does not have strong unions and uses an employment-at-will policy (O’Toole & Meier, 2010). As a result, superintendents of school districts in Texas are able to make autonomous decisions in taxation and personnel matters. Developing and managing managerial social capital is not mandatory, and the power and magnitude of the effects of managerial social capital may be differently determined by the amount of discretion that top managers can exercise. Thus, Texas school districts provide a unique context to examine the effects of social capital on organizational performance, and any other independent local government similar to Texas school districts can find implications from the findings of the current study. However, it is also noted that school districts have distinctive features as compared with other government agencies (Raffel, 2007). First, school districts are highly professionalized and decentralized, and give more substantial discretion to street-level bureaucrats (teachers) than any other government agencies. Furthermore, not all top managers of government agencies have as much discretion as superintendents of Texas school districts. Thus, government agencies whose characteristics are different from the characteristics of independent local government like Texas school districts need careful generalizations from this study.

Data are drawn from two sources. The first source is two sets of the Superintendent Management Survey conducted in the academic years 2001-2002 and 2004-2005. These surveys are part of an ongoing research project by O’Toole and Meier (for more information about data and instruments, see Meier & O’Toole, 2007).¹ The surveys concern a superintendent’s interaction with external actors in addition to leadership and management styles. There are 1,248 school districts in Texas, and out of 1,248 school districts, 422 districts in 2002 and 586 districts in 2005 were analyzed due to missing data resulting from the failure of superintendents to return surveys. As a result, pooled cross-sectional data of 1,008 observations were finally analyzed. Although individual superintendents were surveyed, the unit of analysis in this study is a school district. It is reasonable to interpret superintendents’ management at a school district level, because the superintendents were surveyed as representatives of their school districts not as natural men. Thus, superintendents’ practices on behalf their school districts can be understood at the school district level.² The second source is the Texas Education Agency, which provided information on a district’s financial and personnel resources as well as student information.

Organizational Performance

This study analyzes students’ average pass rates of the Texas Assessment of Knowledge and Skills (TAKS) as a measure of a school district’s organizational performance.³ The TAKS is a statewide annual exam, and for students to advance to the next grade, they must pass the exam. As a result, the TAKS is one of the most critical performance measures for superintendents, and superintendents as well as communities base their districts’ performance on the TAKS.

Bonding Social Capital and Bridging Social Capital

To construct a social capital index, Putnam (2000) developed five dimensions of social capital: community organizational life, engagement in public affairs, community volunteerism, informal sociability, and social trust. Since then, many studies on social capital have replicated Putnam’s index (e.g., Hawes & Rocha, 2011; Messner et al., 2004). Meanwhile, other researchers measured social capital by relying on civic participation such as membership of religious associations (Beyerlein & Hipp, 2005) or numbers of civic associations per capita per community (Menahem, 2011).

In this study, managerial social capital is measured with special attention to two dimensions of superintendents’ interactions, relying on the concepts of bonding and bridging social capital suggested by Putnam (2000). Accordingly, the measures of managerial social capital in this study are at a superintendent’s egocentric level representing his or her school district.

Bonding social capital

According to Putnam (2000), bonding social capital is a set of networks with people of similar backgrounds. Based upon the definition, some researchers focus on similar socioeconomic characteristics to measure bonding social capital (Coffé & Geys, 2007; Putnam, 2000), but this study pays attention to similar professional interests and operationalizes a superintendent’s bonding social capital as a superintendent’s frequent interaction with external actors whose professional interests are in education: other superintendents, school boards, principals, and the Texas Education Agency. These actors are all in formal positions and either design or implement educational policies. Thus, a superintendent’s networking with these groups represents his or her bonding social capital well.⁴

To measure bonding social capital, superintendents were asked how frequently they interact with other superintendents, school boards, principals, and the Texas Education Agency, and the responses range from never (=1) to daily (=6). The four variables are summed to generate one variable denoting bonding social capital. The mean of this measure is 17.17, and its standard deviation is 2.12.

Bridging social capital

According to Putnam (2000), bridging social capital is an association between members with dissimilar backgrounds. Based on the concept of bridging social capital, this study focuses on frequencies of superintendents’ interaction with external political or interest groups whose main goals are not determining and implementing educational policies but pursuing their own interests: state legislatures, teachers’ associations, parental groups, and local business leaders.⁵

Similar to the bonding social capital variable, the bridging social capital variable is generated by the sum of the superintendents’ interactions with state legislatures, teachers’ associations, parental groups, and local business leaders. The mean of this variable is 11.24, and its standard deviation is 2.40.

Question items used to measure bonding and bridging social capital in this study have been used elsewhere to measure managerial networking (e.g., Meier & O’Toole, 2003). In previous studies, the whole items were factor analyzed to capture managerial efforts to manage organizational environments. However, the managerial networking measure does not capture different characteristics of networking; rather, it combines all efforts to network with different actors, and it limits the understanding of networking. Thus, some try to measure different aspects of managers’ networking (e.g., O’Toole, Meier, & Nicholson-Crotty, 2005). In this study, based on the homogeneous/heterogeneous professional characteristics of external actors, bonding and bridging social capital are operationalized. More discussion on these measures will follow in the “Discussion and Conclusion” section.

Environmental Difficulty

To capture an environmental difficulty, this study focuses on financial difficulties. In Texas, each school district generates revenue and utilizes revenue as its financial resource. According to Budgeted Financial Data by Texas Education Agency,⁶ local tax (51.3%) and state funding (44.7%) are two major sources of school districts’ revenue in the academic year 2001-2002. Financial sources in the academic year 2004-2005 are not much different (54.79% for local tax and 41.88% for state funding). It means that school districts rely heavily on two major sources, and any economic fluctuation in the local and state market can severely influence the revenue of school districts. Of course, minor fluctuations in annual revenue may not cause serious problems, but big leaps, especially large losses of revenues as compared with the previous year, give superintendents difficulties in managing their school districts. A sudden loss of revenue is something that a superintendent should definitely manage, and it is useful in a research context to see how bonding and bridging social capital interact with a financial difficulty.

To measure a financial difficulty, revenue per pupil is regressed on year, and its residual is drawn. Positive values of the residual mean more revenue per pupil than the expected level, while negative values of the residual indicate less revenue per pupil than expected. Because the variable represents financial difficulty, not opportunity, the residual is reversed by multiplying the original residual by −1.

Control Variables

In addition to the main independent variable of interests, this study controls for student composition (percentage of African American students and Hispanic students, and percentage of low-income students), teacher information (average teacher’s experience, average teacher’s salary, and teachers’ turnover rates), and school district information (class size, instructional expenditure per pupil, and lagged TAKS rates).Previous studies analyzing students’ academic achievement found that some students are more difficult to educate than others, and some attribute the reason to students’ poverty and race, which may be related to fewer resources in their home (Jencks & Phillips, 1998; Meier & O’Toole, 2003). Thus, a higher percentage of ethnic minority (African American students and Hispanic students) and low-income students may be negatively associated with students’ academic performance.

Meanwhile, school resources have a controversial relationship with their performance; some find the relationship significant while others find it insignificant, but recent studies with well-made research designs find that resources are associated with better student achievement (Meier & O’Toole, 2003). In this regard, the current study expects that better teacher resources (more experience, higher salary, lower turnover rates) and better school resources (bigger class size, more instructional expenditure per pupil, and higher previous performance) are positively related to students’ performance.

Findings

Table 1 shows descriptive statistics and correlation coefficients among variables. The correlation analysis demonstrates that bonding social capital and bridging social capital are positively, slightly highly correlated, but the correlation coefficient between the two social capital measures is not strong enough to conclude that they are identical (r = .40, p < .000). The results are interesting for two reasons. First, they are not negatively correlated. Given the limited time and resources that superintendents hold, it is expected that developing and managing one aspect of social capital cancels out superintendents’ time and efforts to develop and manage the other aspect of social capital. However, the finding shows that superintendents’ developing bonding social capital, for instance, does not negate his or her developing bridging social capital. It may be that superintendents tend to balance both aspects of social capital for better performance management. Second, nonetheless, they are not strongly correlated, which means they are identical measures.

Table 1.

Descriptive Statistics and Correlation Coefficient (N = 1,008).

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
(1) TAKS pass rates	1
(2) Bonding social capital	.15	1
(3) Bridging social capital	−.07	.4	1
(4) Financial difficulty	−.02^a	−.08	−.02	1
(5) Bonding × FD	−.01^a	−.07	−.02^a	.99	1
(6) Bridging × FD	−.02^a	−.09	−.02^a	.98	.98	1
(7) % Black student	−.23	−.09	.03^a	.15	.14	.15	1
(8) % Hispanic student	−.3	−.08	.06^a	−.07	−.07	−.06^a	−.17	1
(9) % Low-income student	−.44	−.02	.06^a	−.09	−.09	−.01	.18	.66	1
(10) Teacher’s experience	.19	.13^a	.08	−.14	−.13	−.13	−.17	−.08	−.06^a	1
(11) Teacher’s salary	−.01^a	−.11	.16	−.06	−.06	−.05^a	0	.2	−.05^a	.37	1
(12) % Teacher turnover	−.33	−.04^a	−.08	−.06	−.06^a	−.05	.20^a	.12	.17	−.41	−.3	1
(13) Class size	−.2	−.17	.06^a	.56	.54	.055	.21	.13	.00^a	−.25	.24	.04^a	1
(14) Per pupil instructional expenditure	−.11	.07	.04^a	−.83	−.81	−.81	−.12	.08	.12	.19	.12	.06^a	−.65	1
(15) Lagged TAKS pass rates	.92	.17	−.05^a	−.03^a	−.03^a	−.03^a	−.26	−.34	−.51	.25	.04^a	−.36	−.21	−.06^a	1
M	71.08	17.17	11.24	0.17	2.44	1.78	8.84	29.65	51.74	11.9	36.58	19.17	12.55	4,370.07	74.05
SD	17.05	2.12	2.4	2.54	44.37	29.41	12.97	26.17	18.2	2.52	2.87	9.55	2.57	1,149.2	13.57
Minimum	6	10	5	−34.74	−694.72	−451.57	0	0	0	0.25	22.27	0	3.6	1,861	16
Maximum	100	24	23	6.4	115.24	64.02	100	100	99.25	19.35	47.71	77.78	33.87	15,066	100

Note. TAKS = Texas Assessment of Knowledge and Skills.

Not significant at 95% confidence interval.

Among other variables, the dependent variable and its lagged variable are highly correlated (r = .92, p < .000). High correlation between the two variables supports O’Toole and Meier’s (1999) model that an organization has inertia, so current performance is generally predicted by previous performance. The high correlation later leads to a high value of R² in the analysis. Once a lagged variable is controlled, there remains limited room for other variables to explain the variation of the dependent variable.⁷ Thus, any statistically significant findings from the analyses can be interpreted as significant predictors for the dependent variable.

Table 2 shows the results of the weighted least square analyses.⁸ Model 1 in the table shows that the coefficient for bonding social capital is negative and statistically significant (t-statistics: −2.66). That is, a superintendent’s bonding social capital is negatively associated with a district’s performance. The opposite is found for bridging social capital in Model 1. The coefficient for bridging social capital is positive and statistically significant (t-statistics: 4.46), which indicates that a superintendent’s bridging social capital enhances a school district’s performance. As previous studies on social capital argue, bonding social capital is limited in the acceptance of new ideas and circulates redundant resources, while bridging social capital is open to networks with different ideas and various resources being shared. As a result, organizations may benefit more from a top manager’s bridging social capital. These findings support the first two hypotheses of this study.

Table 2.

Impact of Bonding and Bridging on Organizational Performance.

	Model 1	Model 2
Variables	Coefficient	Coefficient
Bonding social capital	−0.136***	−0.302***
	(0.051)	(0.074)
Bonding Social Capital × Financial Difficulty		0.147***
Bonding Social Capital × Financial Difficulty		(0.043)
Bridging Social Capital	0.234***	0.276***
	(0.052)	(0.066)
Bridging Social Capital × Financial Difficulty		−0.094**
Bridging Social Capital × Financial Difficulty		(0.039)
Financial Difficulty	−0.225*	−1.695**
	(0.119)	(0.719)
% Black Student	−0.008	−0.057***
	(0.010)	(0.011)
% Hispanic Student	0.005	−0.004
	(0.008)	(0.008)
% Low-Income Student	−0.059***	−0.027**
	(0.011)	(0.012)
Teacher’s Experience	0.112*	−0.144***
	(0.059)	(0.055)
Teacher’s Salary (×1,000)	−0.069	0.177***
	(0.061)	(0.068)
% Teacher Turnover	−0.056***	−0.078***
	(0.018)	(0.019)
Class Size	−0.052	−0.474***
	(0.104)	(0.108)
Per Pupil Instructional Expenditure	−0.001**	−0.002***
	(0.000)	(0.000)
Previous Year’s TAKS Pass Rate	0.815***	0.833***
	(0.017)	(0.016)
Constant	26.844***	30.474***
	(3.167)	(3.323)
Observations	1,008	1,016
R ²	.960	.946
Adjusted R²	.960	.945

Note. Standard errors in parentheses. A year dummy variable for 2005 not reported. TAKS = Texas Assessment of Knowledge and Skills.

p < .1. **p < .05. ***p < .01.

In addition to bonding and bridging social capital, financial difficulty is found to be negatively associated with organizational performance, although its statistical power is weak (t-statistics: −1.89). Thus, as revenue per pupil becomes lower than its expected value, a school district does not achieve better performance.

However, Model 2 in Table 2 shows that bonding and bridging social capital moderate the negative impacts of financial difficulty in different ways. The coefficient for interaction terms between bonding social capital and financial difficulty is 0.147 with t-statistics of 3.41. While the impact of bonding social capital is negative and statistically significant (t-statistics: −4.08) in Model 2, its interaction term with financial difficulty is positively associated with TAKS pass rates. Findings for bridging social capital are just the opposite: The interaction term between bridging social capital and financial difficulty is negatively associated with TAKS pass rates (t-statistics: −2.41). That is, a superintendent’s bonding social capital reduces the negative impacts of financial difficulty.

The contingent effects of bonding and bridging social capital are clearly shown in the following two figures in which financial difficulty values are measured with changes of the mean of financial difficulty by its standard deviation. As shown in Figure 1, bonding social capital has a negative association with TAKS pass rates, but the slope of its negative association is attenuated as school districts experience more financial difficulty, and when financial difficulty becomes one standard deviation above the mean (the solid line in the figure), bonding social capital leads to positive TAKS pass rates. Meanwhile, as shown in Figure 2, more bridging social capital increases TAKS pass rates, but its positive association becomes negative when financial difficulty becomes greater than one standard deviation above the mean (the solid line in the figure). The two figures clearly show the different effects of bonding and bridging social capital on TAKS pass rates contingent on the level of financial difficulty.

Figure 1.

Contingent effects of bonding social capital.

Figure 2.

Contingent effects of bridging social capital.

In a time of financial difficulty, bridging social capital represented by weak ties may be fragile. A social relationship between two actors is reciprocal in that one can gain returns from the other by providing the other with something that the other wants. If an organization suffers from financial difficulty, the most necessary resource for the organization may be financial aid. However, financial support, if it is voluntary, may require a high threshold of reciprocity, and those who are linked with weak ties may not support one another as compared with those who are connected with strong ties. Thus, one can benefit more from one’s bonding social capital than bridging social capital when one faces a financial difficulty.

Table 3 shows the impact of bonding and bridging social capital on other performance measures of school districts. Overall, financial difficulty is not statistically significantly associated with average ACT or SAT scores, the percentage of students who score above 1,110 on the SAT, and the percentage of students who are admitted to college. The finding that financial difficulty is not statistically significant for those performance measures may not be surprising because revenue aims at a school district’s day-to-day operation, which is more associated with annual statewide TAKS performance for all students. Insignificant statistical results of financial difficulty make it hard to test the moderating role of bonding and bridging social capital. However, models without interaction terms consistently confirm the negative impacts of bonding social capital and the positive impacts of bridging social capital. This finding is a further reminder that bridging social capital improves organizational performance while bonding social capital can lead to lower organizational performance. If different environmental difficulties are included, it is worthwhile testing the moderating roles of bonding and bridging social capital. Future research needs to follow in this vein.

Table 3.

Other Performance Measure.

	Average ACT Score	Average ACT Score	Average SAT Score	Average SAT Score	Percent above 1110	Percent above 1110	College Pass	College Pass
Bonding social capital	−0.037*	−0.030	−1.961	−0.956	−0.630***	−0.762***	−0.328*	−0.272
	(0.022)	(0.024)	(1.216)	(1.524)	(0.178)	(0.196)	(0.168)	(0.181)
Bridging social capital	0.041**	0.038*	1.740	0.769	0.385**	0.363**	0.334**	0.292*
	(0.019)	(0.020)	(1.080)	(1.210)	(0.155)	(0.160)	(0.145)	(0.149)
Financial difficulty	−0.024	0.076	−1.726	2.992	0.309	−3.874**	0.012	0.385
	(0.034)	(0.196)	(2.626)	(15.778)	(0.320)	(1.841)	(0.245)	(1.469)
Bonding social capital × Financial difficulty		−0.009		−1.111		0.183		−0.077
Bonding social capital × Financial difficulty		(0.012)		(0.964)		(0.112)		(0.091)
Bridging social capital × Financial difficulty		0.005		1.259*		0.093		0.090
Bridging social capital × Financial difficulty		(0.010)		(0.733)		(0.085)		(0.074)
Observations	1,065	1,065	891	891	1,054	1,054	1,121	1,121
R ²	.414	.414	.340	.342	.312	.316	.328	.329

Note. Standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

All equations control for the same variables controlled in Table 2. They are percentage of Black, Hispanic, and low-income students; teacher’s experience; teacher’s salary; teacher’s turnover rates; class size; instructional expenditure per pupil; lagged TAKS pass rates; and a year dummy variable.

The next question is this: How do superintendents develop and manage their social capital? The following section will discuss a possible answer.

Discussion and Conclusion

Organizations require various types of resources to get things done. Monetary resources are one of the representative resources. Humans are also treated as important resources. The knowledge, skills, or abilities (KSA) of individuals within an organization determine the success of the organization (Lim, Mathis, & Jackson, 2010). Social capital goes further than the concept of human capital or human resources. Social capital focuses on not only an individual’s KSA but also the relationships that the individual holds. By being linked with others who possess what one needs, one can easily gain access to what one needs.

As previously discussed, there are at least two types of “know-whom”: bonding and bridging social capital. Bonding social capital links people with similar backgrounds so that ties among people in networks are strong (Putnam, 2000). Bridging social capital links people with different backgrounds who develop weak but diverse ties (Putnam, 2000). Both have advantages and disadvantages. In the sense that new ideas and different resources can circulate among diverse networks, bridging social capital can be more beneficial for organizations than bonding social capital. However, network participants with similar backgrounds tend to develop strong ties, and they firmly bond their relationships to buffer each other from environmental shocks. This study’s findings reveal the impacts of bonding and bridging social capital and their moderating effects on organizational performance contingent on the level of financial difficulty.

The findings were that bridging (bonding) social capital positively (negatively) influences organizational performance while its moderating role with financial difficulty negatively (positively) affects organizational performance: What does this imply for top managers? Certainly, the answer is not that one social capital is always preferred over the other. Rather, the current study suggests contingent effects of bonding and bridging social capital; that is, analyses on the situation that the organization faces should be done first. In school districts, every school faces different situations leading to different demands of bonding and bridging social capital. Moreover, the level of financial difficulty that school districts experience also varies. Therefore, the top managers should make a strategic decision of which social capital they emphasize and make use of more. Thus, to bond or to bridge is not an “either-or” question (Putnam, 2000, p. 23); it is a matter of “more or less” (Putnam, 2000, p. 23). Bonding and bridging social capital are like the two edges of a sword. Too much attention on one aspect of social capital in a time of peace can lead to the failure of an organization in a time of difficulty. Therefore, a top manager has to skillfully balance bonding and bridging social capital. Findings of this study suggest that strategic choices between bonding and bridging social capital are made contingent on the level of environmental uncertainty. As a result, the optimal balancing point between bonding and bridging social capital may be determined from a thorough analysis on environmental uncertainty. In practice, however, determining the exact level of environmental uncertainty may not be possible, but current statistical analyses or simulation techniques may help a top manager in predicting the level of environmental uncertainty, and based on the analyses, a top manager may be able to determine which social capital he or she can stress more or less.

An argument on balancing bonding and bridging social capital may not be new to some readers, but attention must be paid to the fact that developing and managing social capital is a product of a superintendent’s time and efforts to engage in relationships with others. Considering a busy schedule of a superintendent, managing social capital may generate high opportunity costs. Moreover, by putting more time and effort into managing one aspect of social capital may or may not be negatively associated with managing the other aspects of social capital. For example, too much time and effort in managing bonding social capital may allow less time and effort for managing bridging social capital due to the limited time and effort that a superintendent is able to exert. Thus, it may not be surprising if one finds a negative relationship between bonding and bridging social capital.

However, the current study finds a positive relationship between bonding and bridging social capital as shown in Table 1 (r = .40, p < .000). A superintendent’s development of bonding social capital does not necessarily mean loss of bridging social capital or vice versa. Thus, it is a top manager’s critical responsibility to balance bonding and bridging social capital contingent on the degree to which his or her organization is facing difficulty.

The current study utilizes the ongoing projects of superintendent management surveys. Using the same question items—a superintendent’s frequent interactions with his or her environmental actors—previous studies have captured managerial networking (see Meier & O’Toole, 2003, 2005) while the current study measures a manager’s bonding and bridging social capital. The meaningful difference between the previous managerial networking measures and the current bonding and bridging social capital measures is that previous managerial networking measures capture a whole-network management style (Meier & O’Toole, 2003) without differentiating the characteristics of networking partners, while the current bonding and bridging social capital measures capture homogeneous and heterogeneous characteristics of networking behaviors. Some may criticize the manipulation of the same question items to measure different concepts, but as no other data to measure bonding and bridging social capital are available, it may be more fruitful to differently assemble existing question items for new measures. In so doing, new aspects of a manager’s networking behaviors and their effects can be developed and investigated. However, for more concrete knowledge about the impacts of social capital, this study suggests that more refined measures of bonding and bridging social capital from different data sets need to follow.

Future research may also want to focus on the long-term effects of bonding and bridging social capital. An organizational system is by nature designed to be inertial because organizations’ bureaucratic structures pursue consistency and stability (Gerth & Mills, 1946; O’Toole & Meier, 2011). Thus, any impacts on organizations remain within the system and continually influence organizations over time. As a result, stressing bonding (bridging) social capital in a hard (good) time may lead to better organizational performance in the short term, but different outcomes may follow in the long term. Although the current study analyzes pooled cross-sectional data in two time periods, it is limited to observing the long-term effects of each social capital, and future research may want to track the long-term effects of each social capital by analyzing panel data.

Although the findings of this study need further empirical confirmation from future research, they are expected to make a theoretical contribution to the body of literature on social capital in the context of public organizations.

Footnotes

Acknowledgements

The author thanks Dr. Laurence O’Toole and Dr. Kenneth Meier for sharing the data with the author. The author also appreciates the comments from three anonymous reviewers.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Hankuk University of Foreign Studies Research Fund of 2014.

Notes

Author Biography

Sangyub Ryu is an assistant professor at the Department of Public Administration of Hankuk University of Foreign Studies in Korea. His research interests include modeling public management and investigating factors that influence organizational performance with special attention to collaborative networking.

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