Human Relations

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Organizational social capital, structure and performance Rhys Andrews Human Relations 2010; 63; 583 originally published online Mar 31, 2010; DOI: 10.1177/0018726709342931 The online version of this article can be found at: http://hum.sagepub.com/cgi/content/abstract/63/5/583

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human relations

Organizational social capital, structure and performance

human relations 63(5) 583–608 © The Author(s) 2010 Reprints and permission: sagepub. co.uk/journalsPermissions.nav DOI: 10.1177/0018726709342931 hum.sagepub.com

Rhys Andrews Cardiff University, UK

Abstract Organization theorists suggest that the social capital within organizations is a potentially powerful resource for improving organizational performance. In addition, organizational structures may strengthen or weaken the effects of social capital, by furnishing greater or fewer opportunities for its growth. This article explores the independent and combined effects of organizational social capital and structure on the performance of over 100 organizations between 2002 and 2005, using panel data. The statistical results suggest that cognitive and relational dimensions of social capital are positively related to performance, but that the structural dimension of social capital is unrelated to service outcomes. Further analysis revealed that organizational structure has complex and contradictory effects on the impact of each dimension of social capital. Keywords organizational performance, organizational social capital, public sector, quantitative analysis, structure Knowledge-based theories of the firm suggest that organizations are best viewed as ‘a social community specializing in speed and efficiency in the creation and transfer of knowledge’ (Kogut and Zander, 1996: 503). These theories assume that positive relationships among organization members are essential for knowledge transfer and creation to occur as effectively as possible. The social capital inherent in the social relations within an organization can, therefore, be regarded as a potentially critical asset in maximizing organizational advantage. Where there are high levels of collaboration and good will among organization members, firms may be able to reduce their reliance on cumbersome monitoring procedures, thereby lowering the transaction costs associated with accumulating Corresponding author: Rhys Andrews, Centre for Local and Regional Government Research, Cardiff Business School, Cardiff University, Cardiff CF10 3EU, Wales, UK. Email: [email protected]

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knowledge and stimulating innovation (Nahapiet and Ghoshal, 1998; Perry-Smith and Shalley, 2003). Organizational social capital consists of the structural (connections among actors), relational (trust between actors) and cognitive (shared goals and values among actors) dimensions of the relationships between organization members (Nahapiet and Ghoshal, 1998). Each of these dimensions of social capital is arguably a powerful force for improving organizational outcomes by facilitating transactions that result in knowledge diffusion and collective action. A small but growing number of empirical studies has examined organizational social capital and performance, using multivariate statistical techniques (e.g. Langbein and Jorstad, 2004; Leana and Pil, 2006). These studies suggest that high levels of social capital are associated with better organizational outcomes. For example, Leana and Pil’s (2006) analysis indicates that an aggregated measure of structural, relational and cognitive social capital is positively related to student test scores in a sample of 95 schools in an urban public school district in the northeastern United States. However, to date, few researchers have disaggregated each of the three dimensions of organizational social capital, despite claims that heterogeneous indices of social capital may mask important separate effects of its different dimensions (Knack, 2002). And, fewer still provide insights into some of the boundary conditions of the social capital-organizational performance relation that might reveal the contingent circumstances in which the hypothesized benefits of social capital are most likely to emerge. This is especially important since organizational social capital is not easily acquired but must be cultivated (Arregle et al., 2007; Dierickx and Cool, 1989). Collins and Smith (2006) find that each of the three dimensions of organizational social capital has positive statistically significant direct effects on the revenue and sales growth of 136 US technology companies, but that these effects are mediated through the capability to transfer knowledge. Tsai and Ghoshal’s (1998) study of the rate of product innovation in a large multinational electronics company indicated that trust improved performance by enhancing inter-unit resource exchange. Nevertheless, although there is some (albeit sparse) evidence on the moderating effects of knowledge-sharing on the relationship between organizational social capital and performance, researchers have so far paid scant attention to other potentially relevant boundary conditions of the relationship. In particular, there is currently little quantitative evidence on the moderating effects of organizational structure, despite the growing influence of this notion in studies of social capital at the individual level (see especially, Burt, 1997). According to Burt (1997), the benefits of social capital for employee performance are contingent on key aspects of the organizational structure which may enable it to flourish, especially the degree of specialization. By extension, the value of organizational social capital for organizational performance may also depend on the opportunities for its growth presented by an organization’s structure. In particular, principal–agent theories suggest that flatter or more informal organizational structures can encourage better knowledge transfer across the organization, and enable senior managers to resolve collective action problems without recourse to resource-hungry oversight arrangements (Miller, 1992). However, few researchers have sought to examine this potentially crucial aspect of the boundary conditions of the social capital–organizational performance relationship. Thus, despite ever-increasing interest in the value of organizational social capital,

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a number of important empirical questions remain under-explored. Which dimensions of organizational social capital are conducive to better performance? Are these moderated by important internal structural features? Do different structuring dimensions present greater or fewer opportunities for the positive impact of each dimension of social capital to be realized? By applying a statistical model of organizational social capital to the performance of a set of organizations, this article advances research on the social capital–performance relationship in three ways. First, it moves beyond a focus on either a single dimension of organizational social capital or an aggregated measure of the concept, to examine the association between three key dimensions of organizational social capital and performance. Second, it explores the connection between social capital, structure and performance at the organizational rather than the individual level. Third, it furnishes evidence on the complex interactive relationships between the different dimensions of organizational social capital and structure, and organizational performance. The article begins by formalizing the concept of organizational social capital and deriving hypotheses on the potential impact of its separate dimensions on performance. The potentially moderating influence of organizational structure on each of these dimensions is then explored. Thereafter, measures of performance, social capital, structure and appropriate controls are identified and described, before results of statistical models of organizational social capital and performance are presented. Finally, the article concludes by discussing the theoretical and practical implications of the findings.

Social capital and organizational performance The concept of social capital has been conceptualized and operationalized in myriad alternative ways (see Leana and van Buren, 1999). At the heart of the concept is the notion that the relational resources within a community can be harnessed by certain actors to achieve desired outcomes (Bourdieu, 1980). Thus, if organizations can be regarded as ‘social communities where individual and social expertise is transformed into economically useful products and service’ (Kogut and Zander, 1992: 384), then relationships between organization members are a potentially ‘valuable resource for the conduct of social affairs’ (Nahapiet and Ghoshal, 1998: 243). Although some scholars focus exclusively on the bridging aspects of interactions connecting diverse actors as the source of social capital (e.g. Burt, 1997), others emphasize the bonding nature of the shared values that underpin such interactions (e.g. Coleman, 1994). Broadly speaking, social capital therefore encompasses ‘social networks and the norms of reciprocity and trustworthiness that arise from them’ (Putnam, 2000: 19). This implies that it is a multidimensional construct encompassing both structural (networks) and attitudinal (norms) features. The contrasting structural and attitudinal aspects of social capital are especially well expressed in Nahapiet and Ghoshal’s (1998) multidimensional formulation of the concept. In particular, they argue that organizational social capital comprises three key distinct (though interrelated) dimensions that may enable the unlocking of ideas and information that can positively influence organizational outcomes: structural (connections among actors); relational (trust among actors); and cognitive (shared goals and values among actors) (Nahapiet and Ghoshal, 1998). Each of these dimensions furnishes

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organization members with collectively-owned ‘assets’ that facilitate ‘some forms of social action while inhibiting others’ (p. 245). Structural social capital indicates the presence of a network of access to people and resources, while relational and cognitive social capital reflect the capability for resource exchange. As such, the presence of strong connections, high levels of trust and a shared sense of mission among organizational members represent assets that can be appropriated by organizational leaders seeking to improve decision-making and performance without recourse to potentially expensive control and monitoring procedures. Structural social capital is constituted by the ‘configurations of linkages between people and units’ (Nahapiet and Ghoshal, 1998: 244). Such connections between actors provide opportunities for them to gain access to relevant peers with desired sets of knowledge or expertise. Frequent interactions between organization members in different functional areas and departments, for example, are likely to positively influence the speed with which organizational learning can occur (Kogut and Zander, 1996). Miller (1992) argues that repeated successful bilateral interaction between agents may also increase cooperation rates, which, in turn, can have a beneficial influence on organizational performance. The existence of formal and informal network linkages between actors may therefore enhance organizational outcomes (Scott, 1999). Sparrowe et al. (2001) find that structures and processes of intra-organizational cooperation reinforced acceptance of mutual accountability among employees in 38 workgroups in five different industries, leading to greater work effort and better overall job and group performance. Formal and informal processes of collaboration and coordination within organizations can create networks of relationships that can be mobilized by senior managers for the benefit of organizational outcomes (Scott, 1999). Almost all organizations can benefit from appropriating collaborative relationships across their internal boundaries. By encouraging interaction between different departments within an organization, it becomes increasingly possible for senior managers to access vital information and knowledge ‘spillovers’ from across the organization to accomplish collective goals or obtain scarce resources (Willem and Scarborough, 2006). Thus, the first hypothesis is that: H1: Structural social capital is positively related to organizational performance.

Relational social capital refers to the underlying reciprocity that guides exchanges between organization members. According to Leana and van Buren (1999) this is reflected in the extent of associability (willingness to subordinate individual to collective goals) and trust (the norm underpinning reciprocity) within an organization. The present study focuses on the trust aspect of relational social capital rather than associability, which is much more closely linked to the shared goals and values at the heart of cognitive social capital. High levels of trust between organizational leaders and members may permit the transfer of sensitive information that is unavailable to those beyond the boundaries of trust. It also fosters collaborative action in the absence of formal mechanisms for that purpose (Coleman, 1990), and can diminish resistance to organizational change (Kramer, 1999). Moreover, resources previously assigned to monitoring employees can be more productively reinvested elsewhere if the ‘expectation among the multiple layers in a large firm that cooperative behaviour will be met in kind’ is fulfilled (Miller, 1992: 197).

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In a high trust environment, organization members may simultaneously perceive there to be strong support from leaders and a corresponding sense of obligation and attachment on their own part (Thau et al., 2007). Such positive intra-organizational relationships can, in turn, result in better employee performance (Cunningham and MacGregor, 2000). High levels of trust may increase bureaucratic efficiency and effectiveness by encouraging managers at different organizational levels to freely exchange ideas and information (Willem and Buelens, 2007). Shared norms of reciprocity both underpin access to such exchanges and provide the necessary motivation to do so, generating strong ties among members of the same community. Such solidarity within organizations can increase the prospect for negative externalities associated with closure to emerge, such as ‘groupthink’ that restrict the free flow of information and knowledge (Adler and Kwon, 2002). Nevertheless, strong relational ties are more typically linked with a host of positive externalities, including reduced turnover intention and stronger organizational commitment (Dirks and Ferrin, 2001), which can in turn lead to better outcomes (Benkhoff, 1997). As a result, it is anticipated that: H2: Relational social capital is positively related to organizational performance.

Finally, cognitive social capital is constituted by the broader organizational mission and values that form the context in which exchanges of knowledge and collective action take place. If organization members share and pursue a common strategic vision and goals, this may promote both integration and collective responsibility (Coleman, 1994). Cognitive social capital differs from relational social capital in that it relates to the extent to which subjective interpretations of organizational values and goals rather than feelings of trust are shared by the many actors within a given organization. Although it is possible to conceive of organizations in which it is a shared norm to not trust others in the organization, these two dimensions of social capital are nonetheless likely to be closely connected (see Sitkin and Roth, 1993). Shared interpretations of the values and mission of the organization furnish cognitive ‘templates for particular types of actors’ (Scott, 2001), which may enable them to cope with environmental uncertainty, potentially creating positive externalities for organizational performance. The ‘willingness and ability to define collective goals that are then enacted collectively’ (Leana and Van Buren, 1999: 542), is thus associated with greater overall synchronization of organizational effort. Highly diverse values among organizational members can exacerbate collective action problems associated with attempting to implement policies and strategies, such as the need for coalition building (Willem and Scarborough, 2006). The diffusion of knowledge and innovation, though premised on diverse contributions of opinion and experience, often requires a shared context to frame such contributions (Tagliaventi and Mattarelli, 2006). Similarly, effective communication of a strong sense of values and mission throughout an organization can galvanize managers and staff (Duncan et al., 1994). This is especially important in large organizations as leaders need to communicate with, and motivate, myriad diverse groups of employees in order to achieve desired goals (Selznick, 1957), leading to the expectation that: H3: Cognitive social capital is positively related to organizational performance.

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Moderating influence of organizational structure Although levels of collaboration, trust and shared mission within organizations are key dimensions of organizational social capital, the extent to which their benefits can be fully realized may be dependent on the presence of other favourable organizational characteristics. Principal–agent and structural hole theories indicate that organizational structures have major implications for the social capital–performance relationship. In particular, decentralized, informal and specialized organizational structures may enable the leadermember exchange and individual autonomy, which are thought key to the growth of social capital, to flourish more freely. While the links between human resource management and social capital are also likely to influence performance (for example, Lazarova and Taylor, 2009, suggest career management practices have divergent effects on each aspect of organizational social capital; see also Leana and van Buren, 1999), the present study explores the moderating influence of organizational structure. Organizational structure comprises broad ‘structural’ features, such as the overall physical size of an organization, and the ‘structuring’ activities, such as the decentralization of decision-making, that managers carry out. These latter activities actively shape the behaviour of organizational members. As such, they provide the institutional support for a host of other critical internal organizational elements, such as values and routines (O’Toole and Meier, 1999). Organization theorists suggest that there are three key ‘structuring’ dimensions that are susceptible to managerial control: centralization, formalization and specialization (see especially Hage and Aiken, 1967). The interaction between centralization, formalization and specialization and social capital is therefore likely to have substantial consequences for organizational performance, since ‘the design of organization is one of management’s major priorities’ (Child, 1984: 3). However, to date, empirical studies of this relationship have been conducted at the individual rather than the organizational level. According to Burt (1997), the value of social capital to individual employees is greater in loosely structured settings, where rules and procedures are few, and the prospect of defining one’s social role is correspondingly increased. Thus, the benefits of each dimension of social capital for organizational performance may only be realized where an organization’s structure permit them to thrive. For example, organizations that exhibit lower levels of centralization and formalization, and a higher degree of specialization may garner greater benefits from the social capital inherent in relationships between members because there are fewer constraints on organizational members seeking to access and transfer resources. By contrast, centralized, formal and less specialized organizational structures may prevent the emergence of social capital by constricting its free development (though this is arguably a Western-centric perspective, see for example, Taylor, 2007). Nevertheless, it is still possible to advance cogent theoretical interpretations of how the moderating effects of structure may vary in strength and direction for each dimension of social capital. Principal–agent theory highlights that when principals (e.g. organizational leaders) seek to motivate agents (e.g. organizational members) to perform certain desired tasks, they incur considerable transaction costs owing to incomplete information on task performance (Eisenhardt, 1989). To resolve this agency-dilemma, principals are likely to

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implement a variety of mechanisms in order to achieve greater alignment between their own interests and those of the agent. Aside from the use of financial incentives and performance monitoring, the design of suitable organizational structures may represent an especially desirable means of securing cooperation in the long-run. By establishing stable expectations about rules, roles and relationships, structuring activities can enable organizational leaders to positively influence the commitment of members (Sappington, 1991). Top management’s efforts to structure the organization in a manner conducive to resolving agency dilemmas may therefore focus in large part on the relative degree of centralization, formalization and specialization. From a principal–agent perspective, less hierarchical structures may afford greater opportunities for the free transfer of valuable knowledge, and for the resolution of collective action problems without recourse to formal control mechanisms (Miller, 1992). In particular, the absence of centralized decision-making processes increases the prospect of managers and workgroups independently establishing connections across different functional groupings to bring together relevant stakeholders to maximize organizational advantage. Similarly, decentralization implies that senior managers have faith in the ability of middle managers to make key decisions, thereby increasing the positive effects of trusting relationships for organizational performance. However, it is possible that these benefits of decentralization for the organization will be gained at the expense of a strong sense of mission, since senior managers may have less direct control over the goal orientation of their subordinates (Arrow, 1991). It is, therefore, hypothesized that: H4a: Decentralization will strengthen the relationship between structural social capital and organizational performance. H4b: Decentralization will strengthen the relationship between relational social capital and organizational performance. H4c: Decentralization will weaken the relationship between cognitive social capital and organizational performance.

Principal–agent theories also indicate that the information asymmetries that exist between senior managers and subordinates are often overcome by imposing strict guidelines for carrying out operational procedures (see, for example, Jensen and Meckling, 1976). Empirical studies suggest that such high levels of formalization can reduce the harmful effects of role ambiguity among staff (see, for example, Rizzo et al., 1970), and may therefore better equip them to reap the benefits of the resources latent within their social relationships. However, the motivation of employees to master new tasks and look for innovative solutions to operational problems may increase in the absence of formal rules and procedures (Parker, 1986). Low levels of formalization could therefore enhance the potentially positive impact of organizational social capital by placing fewer barriers on its development. The absence of confirmatory evidence on both these perspectives (see, for example, Dalton et al., 1980; Schmid, 2002) implies that formalization may have inconsistent, contradictory or even no meaningful moderating effects on the relationship between organizational social capital and performance, leading to the null hypotheses:

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H5a: Low levels of formalization will be unrelated to the relationship between structural social capital and organizational performance. H5b: Low levels of formalization will be unrelated to the relationship between relational social capital and organizational performance. H5c: Low levels of formalization will be unrelated to the relationship between cognitive social capital and organizational performance.

Burt’s (1997) influential work on the contingent value of social capital suggests that occupational specialization can enable employees to reap the benefits of social capital. If managers or workgroups have few peers able to carry out their duties, they are better placed to define the terms of their role, increasing their chances of subsequently exploiting wider opportunities for unlocking and transferring new knowledge and ideas (Burt, 2004). This implies that the greater the professional autonomy experienced by organization members, the more motivation and skill they may be able to bring to bear on making connections between diverse groups and ideas. Similarly, the opportunity for managers and workgroups to reap the benefits of their expertise will likely be greater where there are trusting relationships between principal and agents. Although specialization can generate tensions between the norms of certain professional groupings and those of an organization as a whole, it is nonetheless conceivable that, in general, professional autonomy elicits a strong sense of mission. Thus: H6a: Specialization will strengthen the relationship between structural social capital and organizational performance. H6b: Specialization will strengthen the relationship between relational social capital and organizational performance. H6c: Specialization will strengthen the relationship between cognitive social capital and organizational performance.

Research context, methods and data The panel dataset for the analysis consists of a maximum of 136 English single and upper tier local governments (county councils, London boroughs, metropolitan districts and unitary authorities). These local governments are elected bodies, with a Westminsterstyle cabinet system of political management, which is usually made up of senior members of the ruling political party. The politicians collectively decide policy on the basis of advice and guidance from professional local government managers. The local governments operate within statutorily defined geographical areas, employ professional career staff and receive approximately two-thirds of their income from the central government. They are large multipurpose governments providing a range of public services, including education, social care, environmental services, housing, welfare benefits and leisure and

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cultural services. As such, they employ around 2 million staff and account for around 10 percent of national GDP, equating to approximately £100 billion per annum. Thus their management and performance is a major concern and has lead over recent years to a growing interest in their accomplishments from governments, citizens and academics (see Walker and Boyne, 2006).

Dependent variable Organizational performance in the public sector is complex and multidimensional. Public organizations are typically required to meet multiple and potentially conflicting organizational goals (Rainey, 1993). Moreover, their achievements are judged by a diverse array of constituencies, such as taxpayers, staff and politicians. The criteria, weighting and interpretation of performance indicators are thus all subject to ongoing debate and contestation among key stakeholders (Boyne, 2003). The analysis presented here focuses on the views of the primary external stakeholder on the service performance of English local governments: UK central government. In England, central government performance classifications are important (though contestable) means for assessing the achievements of local governments. Central government provides the majority of their funding and monitors administrative accountability on behalf of citizens. A local government function classified as ‘poor’ may be externalized, new management imposed, or stricter regulation introduced. By contrast, those regarded as ‘excellent’ may benefit from ‘lighter-touch’ inspections and freedom from some central controls (Downe and Martin, 2007). The major external assessment of English local government performance carried out by central government inspectors during the study period was the yearly Comprehensive Performance Assessment (CPA) conducted by the Audit Commission. For the four years covered by this analysis (2002–05), this classified the service performance of local governments by making judgements about their achievements in six key service areas (education, social care, environment, housing, libraries and leisure and benefits) together with their broader ‘management of resources’ (Audit Commission, 2002, 2003, 2004, 2005). Each service area is given a score from 1 (lowest) to 4 (highest), which is based predominantly on achievements on ‘objective’ statutory performance indicators that are independently audited and checked for accuracy, but also supplemented by inspections of service plans and standards. The service scores are then weighted by the Audit Commission to reflect the relative importance and budget of the service area (children and young people and adult social care = 4; environment and housing = 2; libraries and leisure, benefits and management of resources = 1). Finally, these weighted scores are summed to provide an overall service performance judgement, ranging from 15 (12 for county councils, which do not provide housing or benefits services) to 60 (48 for county councils). Because these scores are not directly comparable across all types of authority, each government’s score is taken as a percentage of the maximum possible score. By providing an overall judgement on the achievements of local governments, the core service performance score therefore represents a good proxy for their ability to meet the multiple goals that they are required to accomplish.

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Independent variables Data collection  Data on perceptions of organizational social capital and structure were derived from a large-scale electronic survey of managers in English local governments exploring a series of management, organizational and policy-related issues carried out each summer from 2001 to 2004. In each year, a representative sample of 72 local governments was surveyed, while in 2001 and 2004 a census of the population of 148 organizations was undertaken.1 Information (including email addresses) for up to three key senior managers at the centre of the organization and four middle managers in each of the six major service areas were provided by the corporate policy unit in the governments participating in the study. Questionnaires were then delivered as an Excel file attached to an email. Informants had eight weeks to answer the questionnaire, save it and return it by email (Enticott, 2003). Three reminders were sent to informants who had not responded. Time-trend tests for non-respondent bias (Armstrong and Overton, 1977) revealed no significant differences in the views of early and late respondents in any of the years in which the survey was carried out. To ensure that the survey met established standards of social science research ethics, the objectives of the study were clearly stated on the front page of the questionnaire. In addition, participants were informed of all aspects of the research, assured of their right to respond and of the arrangements made to safeguard data during and after the study, in order to ensure confidentiality. A survey piloting process in 17 local governments resulted in improvements to many of the survey questions, reducing the likelihood of item ambiguity and evaluation apprehension (Tourangeau et al., 2000). Multiple informant data were collected from senior and middle managers as research has shown that attitudes differ between these hierarchical levels (see Payne and Mansfield, 1973). In each participating organization, questionnaires were sent to at least three senior and four middle managers. In 2001, the total sample consisted of 121 organizations, with a 56 percent (1259) informant response rate. In 2002 and 2003, the total sample was 77, with response rates of 65 percent (922) and 56 percent (790) respectively. In 2004, the total sample was 136, with a response rate of 54 percent (1052).2 Organizational social capital  The structural dimension of organizational social capital was gauged by adapting two of Miller’s (1983) measures of process integration asking informants about the extent of ‘coordination and joint-working’ and ‘cross-departmental and cross-cutting working’ within their organizations. These items were combined in a single index that demonstrated good inter-item reliability (Cronbach’s Alpha score of .73; see Nunnally, 1978). To estimate the degree to which individuals within the same organizations responded similarly, the intra-class correlation coefficient ICC(1) was calculated for the index (see Schneider et al., 2003). ICC(1) compares the between-organization sum of squares with the total sum of squares on the basis of a one-way analysis of variance in which the independent variables is organizational membership. The resulting value was .46, signifying a statistically significant level of perceptual agreement, thereby justifying the aggregation of the scale to an organizational level (p > .001). Although the index does not fully tap the density of formal and informal network connections enjoyed

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by organization members, it represents a reasonable proxy for the frequency with which they were likely to have interacted across functional boundaries (see Langbein and Jorstad, 2004). Informants were asked whether ‘there is a high level of trust between top-management and staff’ and if ‘there is a high level of trust between top-management and politicians’ in order to assess the relational dimension of social capital. These survey items were developed from those utilized in Cusack’s (1999) study of social capital and local government performance. A relational social capital index was then created by combining these measures. This index demonstrated a good inter-item reliability score of .68 (Nunnally, 1978). The ICC(1) value for the index was .53 (p > .001). These measures tap levels of trust among three key organizational groupings within English local governments, and provide a good approximation for the degree of trust among leaders and members that is central to theoretical perspectives on the trust–performance relation (see Cunningham and MacGregor, 2000). The cognitive dimension of social capital was evaluated by enquiring about the extent to which the local government’s ‘mission, values and objectives are clearly and widely owned and understood by all staff’ and the extent to which the organization concentrated on achieving its ‘mission, values and objectives’. These measures are based on those used by Tsai and Ghoshal (1998) to gauge the extent to which a vision is both shared and pursued within an organization. The resulting cognitive social capital index evinced an acceptable Cronbach’s Alpha score of .61 (see Loewenthal, 1996). The ICC(1) value for this index was .38 (p > .001). Table 1A in the Appendix provides the full descriptions for all these items. To ensure the analysis was focused on organizational rather than individual social capital the survey items were all pitched at the organizational level. The use of two items to gauge each dimension of social capital was deemed appropriate for the purposes of this analysis given the absence of well-validated indices measuring organizational social capital in the public sector. The measures of structural, relational and cognitive social capital were entered separately in the statistical models to ensure that distinctive individual effects were revealed.3 Organizational structure  Organization theorists suggest that relative levels of centralization, formalization and specialization are the three principal ‘structuring’ dimensions, which may influence organizational choices and outcomes (see Dalton et al., 1980; Hage and Aiken, 1967). To gauge these dimensions of the structure of their organizations, informants were therefore asked to indicate the extent to which ‘the decision to take appropriate corrective action usually comes from top management’ (high centralization); whether ‘written policies and procedures are important in guiding the action of employees’ (high formalization); and if staff were ‘frequently’ transferred or seconded to ‘different departments/services’ (low specialization). These measures are based on single item questions used in prior research (Subramanian and Nilakanta, 1996). There is growing evidence on the reliability of such single item measures (e.g. Nagy, 2002; Wanous and Hudy, 2001). The direction of each of the items was reversed in order to tap the degree of opportunity that the organization structure presented for managers and workgroups to

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make their own decisions (decentralization), bypass formal procedures formalization (reversed) and reap the benefits of their occupational specialisms (specialization).

Control variables External constraints  Seven measures were selected to control for the impact of external constraints on performance. Two proxy measures for the prosperity of local residents were used in the analysis. The first was the number of single parent households in each local government area as a percentage of all households identified in the 2001 UK national census, since pressures of time and money on such households are likely to impede positive contributions to service provision (Chambaz, 2001). The second was the percentage population growth recorded in the 2001 census. New residents in areas with growing populations are likely to be economically skilled and socially enterprising, thereby generating positive externalities for local governments (Armstrong and Taylor, 2000). Three dimensions of diversity of service need are measured: age, ethnicity and social class. The proportions of the various sub-groups within each of the different categories identified by the 2001 national census within a local government’s jurisdiction (e.g. ages 0–4, Black African, large employers and higher managerial occupations) was squared and the sum of these squares subtracted from 10,000. The resulting measures are the equivalent of the Hehrfindahl index used by economists to measure market concentration and diversity. The measures give a proxy for ‘fractionalization’ within an area, with a high score on the index reflecting a high level of diversity (see Trawick and Howsen, 2006). Local governments serving big populations can accrue economies of scale by distributing fixed costs over more units of output (Boyne, 2003). The relative size of local governments was measured using population figures for each local area from the 2001 census. Public organizations in densely populated areas can reap scope economies by offering multiple services from the same site (Grosskopf and Yaisawamg, 1990). Population figures were therefore divided by the area served by each local government to measure density. Service expenditure  Performance may vary because of the financial resources expended by individual organizations. Local governments with relatively high levels of financial resource capacity can therefore pay their way to success by investing in better quality staff or new methods of working (Boyne, 2003). Potential spending effects were controlled by using revenue expenditure figures per capita.

Data analysis Pooled Ordinary Least Squares (OLS) regression models were used to model the separate and combined effects of social capital and structure on organizational performance. This method has been applied in numerous studies of organizational performance in the public sector using panel data (e.g. Meier and Nicholson-Crotty, 2006; Pitts, 2005). The variables used in the regression models were available for four years from 2001 through 2004; these data were pooled and panellized by year and unit of analysis. Some cases

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could not be matched when the survey variables and performance measures were mapped, owing to survey attrition and missing data within the respective datasets. The statistical analysis of the relationship between organizational social capital and performance was therefore conducted on an unbalanced non-compact panel of 113 organizations in 2001, 73 in 2002, 73 in 2003 and 128 in 2004.4 Pooled OLS models are often affected by serial correlation and heteroscedasticity. The inclusion of dummy variables for the first three years of the survey corrected the presence of serial correlation. This is the standard correction for short panels such as the one used here (Beck and Katz, 1995; Stimson, 1985). Robust estimation of the standard errors corrected for the presence of non-constant error variance (White, 1980). Although dummy variables for the individual units of analysis are sometimes used to deal with heteroscedasticity, this is both cumbersome and generates extremely high levels of multicollinearity within such a short panel. Moreover, since the panel is unbalanced, non-compact and contains time invariant control variables, two-way fixed effects regression is deemed inappropriate. Indeed, the costs of such an approach often exceed any potential benefits (see Meier et al., 2000). The average Variance Inflation Factor score for all the independent variables used in the pooled models is about 2.7, indicating that the results presented here are unlikely to be distorted by multicollinearity (Bowerman and O’Connell, 1990).

Statistical results Table 1 presents the descriptive statistics and correlations for all the measures used in the analysis.5 The descriptive statistics for the measures of social capital suggest that, on average, survey respondents perceived levels of cognitive social capital to be higher than those of either structural or relational social capital. Nevertheless, the mean scores for the perceptions of all the separate dimensions of social capital are above the median possible score, suggesting that, on average, respondents felt that the connections, trust and sense of shared values within their organizations were strong. Table 1 also illustrates that performance is positively correlated with each dimension of organizational social capital, with the strongest correlation found for relational social capital. In addition, there are positive correlations between the different dimensions of organizational social capital, especially between relational and cognitive social capital. This mirrors findings from previous cross-sectional snap-shot studies (Tsai and Ghoshal, 1998). Table 2 presents the relationship between the control variables and performance, and then the additional explanatory power offered by the measures of organizational social capital. The table highlights that, when entered alone, the control variables account for about 32 percent of the variation in the performance of this sample of organizations between 2002 and 2005. All the control variables have the expected signs, and nearly all (seven out of eight) are statistically significant. Performance is influenced by external constraints and service expenditure. In particular, the variables measuring prosperity, size and density have a significant positive association with performance, while those gauging diversity of service need have a significant negative association. Taken together, the R2 and the effects of the control variables suggest that the model provides a sound foundation for assessing the influence of organizational social capital.

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M

SD

1

2

3

4

5

6

7

8

9

10

11

12

13

14

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+p ≤ 0.10; *p ≤ 0.05; **p ≤ 0.01.

  1 Core service 68.30 8.90 performance   2 Structural 5.21 0.56 .16** social capital   3 Relational 4.87 0.69 .44** .34** social capital   4 Cognitive 5.43 0.55 .35** .43** .67** social capital   5 Decentralization 3.39 0.66 -.22** -.24** -.33** -.38**   6 Formalization 2.85 0.55 -.17** -.34** -.39** -.44** .26** (reversed)   7 Specialization 4.44 0.91 -.15** -.35** -.15** -.18** .18** .13*   8 Lone parent 22.89 5.89 -.12** .10+ -.12* .09 -.02 .10+ -.06 households   9 Population 0.77 0.85 .24** -.07 .14** .04 -.08 -.03 -.09+ .05 growth 10 Age diversity 8722.56 66.55 -.16* .05 -.11* -.14** .12* .06 -.11* .05 -.45** 11 Ethnic diversity 2569.17 2333.71 -.10+ -.02 -.18** .01 -.08 .07 -.14** .41** .28** -.39** 12 Social class 8777.83 65.65 -.20** .03 -.20** -.11* .01 .13* -.22** .17** -.12* .32** .39** diversity 13 Population 345829 258152 .04 .01 .11* .05 -.08 .00 -.15** -.29** .00 .17** -.19** .16** 14 Population 2505.93 2877.41 -.03 .06 -.16** .05 -.05 .03 -.07 .63** .15** -.21** .73** .14** -.45** density 15 Service 1176.36 288.61 .00 .12* .00 .19** -.23** -.04 -.19** .68** .06 -.06 .56** .27** -.32** .59** expenditure per capita



Table 1  Descriptive statistics and correlations

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Slope

Organizational social capital Structural social capital Relational social capital Cognitive social capital Control variables Lone parent households -.18+ Population growth .30** Age diversity -.23** Ethnic diversity -.55** Social class diversity -.001 Population (log) .10+ Population density (log) .31** Service expenditure per capita .21* F-statistic 16.16** R2 .32 Adj. R2 .30 N of observations 387

Slope -.05 .30** .19** -.30** .30** -.08 -.47** .02 .06 .35** .26** 21.60** .45 .43 387

+p ≤ 0.10; *p ≤ 0.05; **p ≤ 0.01. Standardized coefficients reported. Dummy variables for individual years not reported.

Akaike Information Criteria (AIC) and an F-test revealed that inclusion of the measures of social capital makes a statistically significant improvement to the explanatory power of the model of about 13 percent. However, the first hypothesis on the relation between organizational social capital and performance is not supported: the coefficient for structural social capital is not statistically significant. Hypothesis 2 is confirmed by the results shown in Table 2. Relational social capital has a statistically significant positive association with service performance. The third hypothesis is also supported by the statistical results. The coefficient for cognitive social capital has a positive sign, and is statistically significant. Table 3 presents the results of the inclusion of the structure measures, and the interactions between these measures and those for each dimension of social capital to explore the extent to which the relationship between social capital and performance may be contingent on structure. Table 3 shows that the separate effects of decentralization, formalization (reversed) and specialization do not alter the relationship between organizational social capital and performance. Moreover, AIC and an F-test showed that the structure base terms failed to add statistically significant explanatory power to the original model. To fully explore the extent to which the link between social capital and performance may be contingent on structure, it is therefore necessary to enter interaction terms in the statistical model. Since the level of collinearity for the base terms increases considerably when interacted variables are included in the equation, the variables are all mean-centred (see Aiken and West, 1991). This reduces the impact of multicollinearity (from an

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Human Relations 63(5) Table 3  Organizational social capital, structure and performance Independent variables

Slope

Organizational social capital Structural social capital (SSC) -.05 Relational social capital (RSC) .29** Cognitive social capital (CSC) .20** Organizational structure Decentralization -.01 Formalization (reversed) .05 Specialization -.05 Interacted terms Decentralization x SSC Decentralization x RSC Decentralization x CSC Formalization (reversed) x SSC Formalization (reversed) x RSC Formalization (reversed) x CSC Specialization x SSC Specialization x RSC Specialization x CSC Control variables Lone parent households -.29** Population growth .29** Age diversity -.09 Ethnic diversity -.48** Social class diversity .01 Population (log) .04 Population density (log) .34** Service expenditure per capita .25** F-statistic 17.77** R2 .45 Adj. R2 .42 N of observations 387

Slope -.09+ .30** .22** -.24 .09 .93** .23 .09+ -.11* -.05 -.06 .01 -.97** .15** .12* -.33** .31** -.03 -.48** -.02 .03 .34** .33** 17.23** .55 .52 387

+p ≤ 0.10; *p ≤ 0.05; **p ≤ 0.01. Standardized coefficients reported. Dummy variables for individual years not reported.

average VIF score of 64.45 for the uncentred interaction model to 18.95) and ensures that the interactions do not bias the coefficient estimates, thereby permitting substantive interpretations of the results. The interactions make a statistically significant addition to the model’s explanatory power of about 10 percent. The majority of the interacted terms are statistically significant, suggesting that the relative degree of decentralization, formalization and specialization is likely to have an important moderating effect on the relationship between organizational social capital and service achievements – at least for this sample of organizations. Two out of the three decentralization interactions are statistically significant: the coefficient for decentralization x RSC is positive, confirming the hypothesis 4b,

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while that for decentralization x CSC is negative, affirming hypothesis 4c. The coefficients for the formalization (reversed) interactions are all statistically insignificant, thereby confirming the null hypotheses 5a–5c regarding the moderating influence of formalization. Finally, each of the coefficients for the specialization interactions is statistically significant, though the sign for one of these (specialization x SSC) is not in the expected direction, contradicting hypothesis 6c.

Discussion This article expands on existing quantitative studies by systematically exploring the relationships between each dimension of organizational social capital and performance, and key boundary conditions of these relationships. The analysis indicated that relational and cognitive social capital are positively related to organizational performance, but that structural social capital is unrelated to performance. However, these relationships were also moderated by organizational structure. Decentralization strengthens the positive impact of relational social capital on organizational performance, but weakens the impact of cognitive social capital. Specialization, too, has mixed effects: boosting the positive impact of relational and social capital, but turning the neutral impact of structural social capital negative. On this occasion, the relative degree of formalization had no statistically significant moderating effects on the social–capital performance relationship. The findings have important theoretical and practical implications.

Theoretical implications Prior quantitative studies of organizational social capital and performance have typically focused on a single dimension of social capital, especially trust (e.g. Cunningham and MacGregor, 2000), or have aggregated the different dimensions of social capital (e.g. Leana and Pil, 2006). Moreover, there has been little systematic quantitative examination of the boundary conditions of the social capital-performance relationship (for an exception, see Collins and Smith, 2006). In particular, while there is growing evidence on the combined effects of social capital and aspects of structure at the individual level (e.g. Burt, 1997), the moderating effects of organizational structure remain unexamined. The analysis presented here highlights that each dimension of organizational social capital may have distinctive independent and moderated effects on performance. In particular, the relative degree of centralization and specialization within an organization are likely to influence the connection between organizational social capital and performance. The findings illustrate the need for researchers to disaggregate the different dimensions of social capital, and for managers to consider the relative merits of alternative approaches to developing organizational social capital. For instance, encouraging boundaryless careers may, in certain circumstances, damage relational and cognitive social capital (Lazarova and Taylor, 2009). The sample organizations do not appear to be eliciting performance gains from crossdepartmental coordination and collaboration. It is possible that the benefits of structural social capital are being counterbalanced by higher transaction costs. For instance,

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individuals spanning the boundaries within an organization may utilize their connections for the purposes of career advancement rather than organizational ends (see Raider and Burt, 1996). By contrast, high levels of trust between organizational leaders and members seem to be conducive to better outcomes. This reflects the available evidence from previous studies. For example, both Collins and Smith (2006) and Tsai and Ghoshal (1998) find that trust is a critical moderator of the relationship between resource exchange and organizational outcomes. Shared values and mission also appear to have a beneficial influence on organizational outcomes. Collins and Smith (2006) find that the positive effects of goal congruence on the capability to exchange knowledge lead to improvements in performance. It may also enable organizational leaders to infuse and sustain such a positive orientation towards a broader strategic vision (see Currie and Lockett, 2007, for a discussion of this issue). The decentralization interaction findings indicate that organizations characterized by trusting relationships among leaders and members appear to be likely to derive further benefits from decentralized decision-making. This mirrors prior studies that find that excessive supervision by organization leaders can crowd out norms of cooperation (Langbein, 2000). However, decentralization appears likely to reverse the positive effects of cognitive social capital for performance. Case study research has found that shared values may be dependent on the power of organizational leaders as suppliers of collective meaning (Ormrod et al., 2007). Where decision-making is not centralized, organizations may struggle to cultivate the benefits of goal congruence. Indeed, decentralization may allow alternative values to emerge, undercutting the benefits of a collective focus. The formalization interaction results suggest that the absence of written rules and procedures has no positive or negative effect on the relationship between organizational social capital and performance. It is conceivable that the costs and benefits of formalizing organizational rules and procedures are simply cancelling each other out. For example, while they can add clarity of purpose to boundary-spanning work (Borins, 1998), formal rules and procedures may also constrain the service innovations that are likely to result in better performance for this sample of organizations (Walker, 2008). The combination of high levels of specialization and structural social capital seems to damage performance, perhaps because professional autonomy undermines connections among different actors or functional departments. This may be an especially acute problem in large multi-purpose organizations where ‘occupational closure’ can buffer functional departments from external influences (Kitchener, 2000). By contrast, organizations benefiting from high levels of relational and cognitive social capital seem to do even better where there is a high degree of occupational specialization. Specialization may be critical to the emergence of both relational and cognitive social capital within organizations, as the propensity to trust likely increases where the perceived threat of job displacement recedes (Freeman, 1984). In addition, high levels of trust between leaders and members, and goal congruence may be critical for the realization of any potential benefits from professional expertise (Albrecht and Travaglione, 2003). These results therefore point towards a virtuous circle of specialization and the capability for resource exchange. The findings presented here suggest that relational social capital has strong positive independent and moderated effects on performance. This implies that organizations seeking to improve services through support for organizational social capital should

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prioritize this particular dimension. For example, appropriate Human Resource Management initiatives can contribute to greater trust between leaders and members (see Daley and Vasu, 1998), and can lead to better performance (Gould-Williams, 2003). Such a focus on relational social capital may also be more likely to generate positive externalities for performance when cultivated through decentralized decision-making and high levels of occupational specialization. Since cognitive social capital is positively related to organizational performance, its impact could be enhanced by the sort of ‘visioning’ exercises associated with its development (Denston, 2005). Nonetheless, the structuring activities of organizations are likely to have complicated implications for organizational leaders seeking to harness cognitive social capital. Although positive externalities associated with cognitive social capital may be strengthened by occupational specialization, they could be damaged by decentralized organizational structures. This indicates that organizations may encounter difficult trade-offs between alternative structuring activities when weighing the relative merits of different approaches to resolving principal–agent dilemmas. They may also face hard choices about the need to build relational or cognitive social capital in order to maximize the capability for resource exchange within the organization. Effective responses to these questions will reflect judgements about existing levels of social capital within the organization and the particular challenges that each dimension of social capital may be suited to addressing. For example, while trust is arguably the bedrock of all organizational exchanges, only high levels of cognitive social capital can embed the combination capability that underpins innovation (Nahapiet and Ghoshal, 1998).

Limitations While the statistical findings provide support for the positive influence of social capital, the study has clear limitations. Although the analysis is carried out at the organizational level, such an aggregative exercise inevitably obscures aspects of the relation between individual social capital and organizational performance. Subsequent research could build on this exploratory study by using multi-level modelling (see, for example, Langbein and Jorstad, 2004). This could furnish valuable quantitative evidence on the relative importance of individual versus organizational determinants of organizational outcomes (see Truss, 2001). It would also be necessary to conduct more detailed investigation at different levels of the organizational hierarchy to fully explore how social capital translates into better performance. For instance, organizational members often differentiate between the level of trust they experience among their peers and that placed in senior figures (see Luhmann, 1979). Comparisons of the relative salience of horizontal and vertical social capital for organizational performance could therefore contribute to the literatures on strategic integration (e.g. Hrebiniak and Joyce, 1984) and organizational identity (e.g. Ashforth and Mael, 1989). In addition, it is possible that some minimum amount of structural social capital must exist in order for the positive benefits of relational and cognitive social capital to be realized. Studies exploring how the interrelationships between structural, relational and cognitive social capital influence performance could answer this vital question.

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The analysis presented here does not explicitly model or explore the potentially damaging effects of social capital for organizations (see Edelman et al., 2004; Pennings and Lee, 1999). The possibility that the positive effect of organizational social capital may eventually turn negative as connections, trust and values sap resources, become exclusionary or increase rigidity (Adler and Kwon, 2002) was tested by including quadratic terms alongside the basic social capital terms in the second model shown in Table 2. However, this did not add any explanatory power to the model (results available on request). More needs to be done in future studies to assess in what circumstances and why organizational social capital may be a liability for performance. In particular, although existing empirical studies suggest that individuals brokering many network ties are able to enhance their salary (see Burt, 1997, 2004), it is conceivable that they do so through rent-seeking. Systematic evidence on the relationship between structural social capital and individual-level and organizational-level outcomes would thus constitute a substantial contribution to the literature on organizational social capital. This analysis has examined a particular group of public organizations during a specific time period. It would therefore be important to identify whether the relative importance of organizational social capital and structure differs over other time periods and in other organizational settings. For example, further research in private firms could cast light on the comparative generalizability of the results presented here. Public servants arguably engage in more pro-social behaviour than their private counterparts (see Brewer, 2003). The degree of social capital extant within the organizations analysed here may therefore be unrepresentative of that found in those operating within other sectors or industries. Different measures of organizational social capital may also influence different measures of performance, and their independent and moderated effects may be either stronger or weaker than the variables included in this model. In particular, studies investigating the impact of alternative measures of structural social capital, such as ‘network centrality’ (Freeman, 1979) and ‘network formality’ (Willem and Scarborough, 2006), might uncover different causal relationships than those found here. Moreover, given the strength of the finding for relational social capital, it seems reasonable to assume that a high level of trust between the sample organizations and their external stakeholders may have a similarly strong positive association with performance through its propensity to facilitate resource combination and exchange (De Wever et al., 2005). A research agenda that sought to systematically address these issues could therefore add considerable value to the literature on networks and organizational performance, as well as that on organizational social capital.

Conclusion This study examined the independent and combined effects of organizational social capital and structure on organizational performance. The findings indicate that organizations seeking to harness the benefits of organizational social capital for their performance may face important trade-offs between: a) fully realizing the positive effects of relational social capital by releasing opportunities for its development; and b) achieving performance gains by adopting a centrally driven approach towards achieving goal congruence. Overall, despite its limitations, the evidence presented here suggests that the first of these options may offer the greater prospect of success.

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Andrews Acknowledgement

The author would like to thank the Associate Editor Professor Samuel Aryee and three anonymous reviewers for their helpful and supportive comments on earlier drafts of this article.

Appendix Table 1A  Survey items used in the analysis Organizational characteristic

Survey item

Structural social capital Relational social capital Cognitive social capital Centralization Formalization Specialization

Co-ordination and joint working with other departments is a major part of our approach to the organization of services Cross-departmental/cross-cutting working is important in driving service improvement There is a high level of trust between top management and staff There is a high level of trust between officers and politicians The authority’s mission, values and objectives are clearly and widely understood and owned by all staff in the service The authority concentrates on achieving its mission, values and objectives When our results deviate from our plans, the decision to take appropriate corrective action usually comes from top management Written policies and procedures are important in guiding the action of employees We frequently transfer or second staff to different services/departments (inverted)

Notes 1

2

3

These cases are representative of the diverse operating environments faced by English local governments, including urban, rural and socio-economically deprived areas. For example, the population densities of the sample local governments range from 62 people per square kilometre to 14,916, with a standard deviation of 2964. Similarly, the percentage score on the UK central government’s index of multiple deprivation ranges from 4.9 to 58.2, with a standard deviation of 11.5, while a Herhfindahl index for the ethnic diversity of the sample governments ranges from 372 to 8452, with a standard deviation of 2362. To test for differences between included/omitted governments, independent sample t-tests were undertaken on all of the control variables. No statistically significant differences between the samples of local governments and the population were found. This highlights that the cases are representative of the diverse operating environments faced by English local governments. The combination of each of these dimensions into a single organizational social capital index demonstrated a very good inter-item reliability score of .79 (Nunnally, 1978). Nevertheless, the measures also exhibited discriminant validity. Principal components analysis using varimax rotation revealed that the variables composing the indices for structural, relational and cognitive social capital loaded on to three distinct factors corresponding to each dimension of social capital.

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4

Generalized Least Squares (GLS) regression revealed similar results to the pooled OLS models presented here. Similar results were also obtained using two-way fixed effects when the cases were restricted to the 73 organizations that were observed in all four years.

5

Before running the statistical models, skewness tests were carried out to establish whether each independent variable was distributed normally. High skew test results for population (1.93) and population density (1.81) indicated non-normal distributions. To correct for positive skew, logged versions of these variables were created.

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