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Abstract

Despite decades of globalization, organization studies have consistently found evidence of community influences on firm behavior. In this study, we develop and test a nuanced theory on the relationship between community political conservatism and corporate social responsibility engagement by integrating social capital theory and the logic of appropriateness. We demonstrate that the influence of community political conservatism is contingent upon two types of community social capital: interfirm and cooperative social connectedness. These two types of social connectedness elicit the manifestation of two different aspects from community political conservatism: free-market and community orientations. While interfirm social connectedness enhances the negative relationship between community political conservatism and corporate social responsibility engagement, cooperative social connectedness weakens it.

Keywords

community influence corporate social responsibility political ideology social capital

Introduction

Recent organization studies have demonstrated that despite the globalization of economies, firm behavior is still subject to the enduring influence of the geographical communities in which the firms are headquartered (Marquis & Tilcsik, 2016; Tilcsik & Marquis, 2013). Corporate social responsibility engagement (CSR) has been a key research context in this literature (Marquis, Glynn, & Davis, 2007) because expectations related to CSR vary among local communities (Gardberg & Fombrun, 2006). Heavily influenced by top management teams who generally reside near headquarters (Kang, 2017; Swanson, 2008), the direction and policies of CSR represent the shared features of communities in which firms are based, such as beliefs, norms, identities, and social structures (Acosta, Acquier, & Gond, 2021; Marquis et al., 2007; Rubin, 2008; Tilcsik & Marquis, 2013). Among these local determinants for CSR is community political ideology, which reflects the cultural-cognitive processes of individuals and organizations in a particular geographical area (Scott, 1995). Ideologies are closely linked with CSR since they involve “fundamental conceptions of the role of the firm endemic in the society” (Detomasi, 2008, p. 816).

The current literature suggests a negative relationship between community political conservatism and CSR, highlighting the free-market orientation of conservatism, which is reflected in antagonism toward market interventions and an emphasis on economic growth (Di Giuli & Kostovetsky, 2014; Lee & Lounsbury, 2015; Rubin, 2008). However, we aim to add more depth to this model by drawing attention to an overlooked dimension of conservatism: community orientation, through which local constituents feel “a sense of agency” for the betterment and stability of their community (Janoff-Bulman, 2009; Malka, Soto, Cohen, & Miller, 2011). We note that while community orientation is known as a key difference from political liberalism, it would rather favor CSR (Haidt & Graham, 2007). The constituents of politically conservative communities often embrace two discernable identities in support of free-market and community orientations. As collective identities, these identities indicate a community’s shared purpose and core practices (Thornton, Ocasio, & Lounsbury, 2012). The relationship between community political conservatism and CSR, therefore, is more complex than currently described in the literature. A more fine-grained framework is warranted to better understand how the dual identities concerning community political conservatism influence CSR.

To fill this gap, our study investigates what triggers the contradictory sides of community political conservatism and drives CSR in different directions. We integrate the logic of appropriateness perspective (March, 1994) and social capital theory (Fukuyama, 1995; Putnam, 1993) to develop our nuanced framework. The logic of appropriateness is ideal for our task because it explains an actor’s behavioral choices when its multiple identities entail different rules of action (Weber, Kopelman, & Messick, 2004). The actor chooses action by answering a basic question: “What does a person such as I, or an organization such as this, do in a situation such as this?” (March, 1994, p. 57) The role of situational cues—contextual signs that prime the appropriate guideline for action formation (Malhotra, Zietsma, Morris, & Smets, 2021)—is thus critical. Given the plurality of identities that the actor carries, the behavioral choice of the actor is determined by which of its identities best matches the social situation in which it finds itself (March & Olsen, 2004; Weber et al., 2004). While the logic of appropriateness offers the mechanism at the individual level, it lacks explanations about the environmental situations that trigger a particular identity of the actor.

We complement our framework by drawing on the community social capital literature. Given the dual identities that are linked with political conservatism, free-market and community orientation, it is necessary to unveil the different situational cues that match them. The framing of the social situation is not an isolated process, rather, it is dependent on numerous interactions with other actors in their adjacent environments (Weber et al., 2004). The literature on community social capital illuminates this aspect. It delineates how social relationships within a community facilitate shared beliefs, norms, and coordination among local actors (Boix & Posner, 1998; Fukuyama, 1995; Ostrom & Ahn, 2009; Putnam, 1993, 2000). It is worth noting that, unlike micro-level social capital research that explores how different access to social capital controls or reinforces a focal actor’s ability to advance its interests (Bourdieu, 1986; Burt, 2000), community social capital highlights the impact of the accumulated social capital on a community or its constituents.

We suggest that, unlike what previous studies have predicted, the effect of community political conservatism on CSR is not always consistent. Instead, it is contingent on two different types of community social capital—interfirm and cooperative social connectedness—that activate contradictory sides of political conservatism. We focus on social connectedness which, as the structural dimension of community social capital, represents how connected local actors are to each other, in general, through social relationships that generate a “sense of belonging” (Putnam, 2000, p. 273). Interfirm social connectedness refers to the overall social connectedness of local firms that fosters group interests, while cooperative social connectedness refers to the more general social connectedness of local people that facilitates civic cooperation for the community interests (Knack & Keefer, 1997; Onyx & Bullen, 2000).

Our study contributes to research on community influences on CSR by adding more nuance to the analysis of political conservatism (Chin, Hambrick, & Treviño, 2013; Lee & Lounsbury, 2015; Rubin, 2008). We show that without further dissecting the internal complexity (free-market versus community orientation), we cannot see the full picture of the impacts of political conservatism on CSR (Feldman & Johnston, 2014). Next, we advance social capital theory by developing and empirically testing the idea that different types of community social connectedness can have contradictory implications for firm behavior depending on its types (Kwon & Adler, 2014). We thereby demonstrate that it is critical to distinguish the actual content transmitted through interactions from the mechanical function of social capital in facilitating coordination (Portes, 1998; Putzel, 1997). Lastly, we further develop our understanding of the mechanism behind the logic of appropriateness by shedding light on the importance of strong collectives that reinforce the imposition of the logics they entail.

Theoretical Background and Hypotheses

Community political conservatism and corporate social responsibility engagement

Community political ideology, or “the shared framework of mental models that groups of individuals possess” (Denzau & North, 2000, p. 4), influences a wide range of attitudes, preferences, judgments, and behaviors (Jost, Federico, & Napier, 2009). Organization studies have investigated the relationship between political ideology and CSR at both the organizational level (Chin et al., 2013; Chow, Louca, Petrou, & Procopiou, 2022; Gupta, Briscoe, & Hambrick, 2017) and the community level (Di Giuli & Kostovetsky, 2014; Lee & Lounsbury, 2015; Rubin, 2008). While the former accounts for the variations in CSR that are directly attributed to organizational members’ beliefs and values, the latter focuses on environmental pressures grounded in the spread of ideologies throughout a local community.

Community political ideologies influence the identities of local actors and their attitudes toward various issues (Karthikeyan, Jonsson, & Wezel, 2016). Prior studies have focused on conflicting stances of two community political ideologies on CSR: liberalism and conservatism (Huber & Inglehart, 1995). According to the current literature, political liberalism—which shines a spotlight on various social issues, such as equality, human rights, and the natural environment (Schwartz, 1994)—supports CSR because it emphasizes cooperation between businesses and the government to improve societal welfare (Walters, 1977). In contrast, the literature argues that political conservatism advocates for values that are largely unfavorable to CSR, such as free-market capitalism, property rights, efficiency, and acceptance of socioeconomic inequality (Skitka & Tetlock, 1993; Tetlock, 2000). The underlying principle of CSR that the blind pursuit of profit can be socially harmful is contradictory to free-market capitalism, which supports profit maximization (Rubin, 2008). Those dichotomous views contend that political conservatism regards CSR as an unjustifiable cost (Walters, 1977).

When local actors resonate with conservative values, normative pressure to limit a firm’s engagement in social missions is generated. This behavioral prescription penetrates the decision-making of local firms headquartered in the community in two ways. First, since key decision-makers, such as executives, usually reside near their headquarters (Palmer, Friedland, & Singh, 1986; Porter, 1998), they bring locally shared conservative values to the decision-making process (Rubin, 2008). It is worth noting that CSR is primarily initiated and conducted around headquarters (Husted, Jamali, & Saffar, 2016) and is supervised by top management teams (Kang, 2017; Swanson, 2008). Second, even if the decision-makers do not themselves hold conservative values, they pay close attention to the beliefs and values that are widely shared among local stakeholders (Husted et al., 2016). As firms refer to other locally headquartered firms in seeking the standards of appropriate behaviors (Marquis et al., 2007), community political conservatism generates isomorphic pressure among local firms.

Given this mechanism, we predict that there is a negative relationship between community political conservatism and CSR. Although we aim later to illustrate more nuanced patterns of this relationship, the overall influence of community political conservatism might still appear to be negative, consistent with the current literature.

Hypothesis 1. The stronger the political conservatism in the community in which a firm is headquartered, the weaker the CSR displayed by the firm.

Multidimensional political conservatism and logic of appropriateness

Although the extant literature largely focuses on free-market orientation, community orientation is also fundamental to political conservatism. To conservatives, a local community is not simply a collection of individuals, but a cluster of institutions, groups, and families seeking moral integrity and a unique collective identity (Shweder, Much, Mahapatra, & Park, 1997). The maintenance of a common social identity is important, and adherence to group norms often outweighs personal beliefs and interests (Janoff-Bulman, 2009). Two specific moral values highlighted by “the ethics of community” are ingroup and authority values (Haidt & Graham, 2007). While the former indicates that political conservatism admires those who make sacrifices for the ingroup, the latter is linked with respect toward those who hold legitimate authority and exemplify positive leadership through magnanimity within a local community (Haidt & Graham, 2007). It follows that firms that make sacrifices for society through prosocial activities, commonly labeled as CSR, can be seen as admirable and, therefore, are well-received among conservatives.

It should be noted that strong religiosity among conservatives also contributes to community orientation. Religiosity is linked with prosocial values such as altruism, empathy (Saroglou, Pichon, Trompette, Verschueren, & Dernelle, 2005), and generosity (La Barbera & Gürhan, 1997). During religious activities, individuals enhance community orientation (Greenberg, 2000) by building a sense of agency and displaying prosocial behaviors (Malka et al., 2011), including environmental consumption (Peifer, Khalsa, & Ecklund, 2016) and charitable gifts (Hill & Vaidyanathan, 2011). In such an environment, CSR might be perceived as a medium through which this sense of prosocial agency can be realized (Basu & Palazzo, 2008).

Depending on which side of political conservatism (free-market or community orientation) is derived and signaled to local actors, community political conservatism can affect CSR in contradictory ways. The logic of appropriateness perspective suggests that when multiple identities provide an actor with alternative rules of action, only the rules that match the specific situation to which the actor is exposed are evoked (March & Olsen, 2004). In other words, the same actor can display highly different stances regarding an issue as their situational cues change (Weber et al., 2004). We complement this framework by incorporating two types of community social connectedness—interfirm and cooperative—that as key sociocultural features of a community, indicate social situations to which local actors tend to be exposed in their daily activities.

Two types of social connectedness

Social capital is a multifaceted concept whose meaning varies among studies (Adler & Kwon, 2002) because it can be formed with various elements such as social connectedness, social norms, generalized reciprocity, and social trust (Onyx & Bullen, 2000; Putnam, 1993). Following mainstream research on community social capital (Laursen, Masciarelli, & Prencipe, 2012), we focus on social connectedness (Nahapiet & Ghoshal, 1998). Often described as the macro-level accumulation of social ties (Balkundi & Harrison, 2006) and social networks (Putnam, 1993), community social connectedness emphasizes the “density” of an interlocking network of relationships or the general level of cohesiveness (Onyx & Bullen, 2000). The stronger the social connectedness is in a local community, the better the community facilitates shared beliefs and coordinated actions (Fukuyama, 1995; Putnam, 1993) and controls collective action problems (Ostrom & Ahn, 2009).

The key mechanisms underlying the function of social connectedness are information sharing and the development of norms. Frequent interactions naturally facilitate information sharing, which in turn enhances cooperation and mutual accountability (Sparrowe, Liden, Wayne, & Kraimer, 2001). When local actors learn more about each other, they become more confident in their shared beliefs and less prone to exhibiting deviant behaviors. According to social comparison theory (Festinger, 1954), interpersonal interactions are essential for the formation of norms because individuals weigh and revise their behavioral attitudes based on information about the thoughts and behaviors of others (Friedkin, 2001). Therefore, information sharing lays the foundation for the development of norms. Stronger social connectedness indicates that the behaviors of others are more predictable, and the incentive to show self-seeking opportunism is reduced (Wu, 2008). This helps sustain the shared norm by easing the process of monitoring and punishing the deviant behaviors of local actors (Bowles & Gintis, 2002).

Our study addresses two types of social connectedness that appear in the heterogeneous social environments of a local community: interfirm and cooperative social connectedness. This classification is grounded in the premise that local constituents build connections for various purposes and values, so the overall connectedness at the community level can be split into discernable forms that facilitate different impacts on a community (Knack & Keefer, 1997; Rupasingha, Goetz, & Freshwater, 2006).

Interfirm social connectedness develops in a social environment in which interactions involve the decision-makers of local firms. Likewise, stronger interfirm social connectedness implies that those decision-makers are more widely linked through formal and informal channels in a community. As they have common interests in market activities, a business- or industry-centric motive is well-received during their interactions (Knack & Keefer, 1997; Olson, 1971). This instrumental motive is readily observable when a collective of firms initiates political lobbying to create a favorable regulatory environment (Lux, Crook, & Woehr, 2011) or when self-regulation is introduced to prevent more stringent public oversight (King & Lenox, 2000).

Cooperative social connectedness forms when local people engage in general social interactions that facilitate solidarity in a local community (Putnam, 1993). In such a community, the extended network of local people acts as the source of a cultural emphasis on widely shared moral order and community interests (Kwon & Adler, 2014). The interactions that comprise this type of social connectedness are likely to be oriented around family, community, and religion and, therefore, foster group spirit. Local people strengthen their identities as members of larger communities and naturally become accustomed to caring about the betterment of the society of which they are a part (Coalter, 2007; Neal & Walters, 2008).

Based on the logic of appropriateness, we argue that the different social situations emanating from these two types of social connectedness elicit and reinforce two contrasting sides of community political conservatism. Regarding interfirm social connectedness, the instrumental motive of interfirm networks matches the free-market orientation of political conservatism. Therefore, frequent interactions with other decision-makers of local firms will generate the situational cue that focusing on economic responsibilities rather than on social issues is what is expected of firms (Malhotra et al., 2021). Abolafia (2010) describes this interactive process as “the collective act of narrative construction” through which a coherent story about what action is appropriate is created and stabilized among firms. During interactions that involve firms’ decision-makers, it is deemed appropriate to overtly discuss the core mission of firms—profit maximization—rather than the firms’ social contributions. As a result, the effects of community political conservatism are expressed more clearly in a way that curbs CSR when a community has strong interfirm social connectedness.

The common mechanisms of social connectedness play an important role in facilitating this coordinated restriction on CSR. Previous studies illustrated the presence of active local interactions and information sharing among businesses through formal and informal channels, such as personal gatherings, business incubators, and trade shows (Kuhn, Galloway, & Collins-Williams, 2016). In the absence of interfirm social connectedness, even if political conservatism is prevalent, firms might be reluctant to reduce CSR due to uncertainty about other firms’ behaviors. Bohr (2014)’s analysis of American citizens indicates that conservatives reveal their indifference to environmental issues more clearly when they believe others will also not show pro-environmental behaviors. Similarly, without confirming other firms’ commitments, a firm may perceive controlling CSR on its own as risky: the firm could stand out as particularly irresponsible. However, more business-oriented discussions and interactions will allow firms to confirm the presence of a shared belief in emphasizing free-market capitalism and prioritizing economic responsibilities (Friedkin, 2001). The enhanced information sharing also helps identify deviants with notably high investments in CSR and impose social sanctions on them (Jones, Hesterly, & Borgatti, 1997). Social sanctions may include exclusion from normal interactions, a reduction in the number of contracts, and activities by political lobbies targeting such firms (Das & Teng, 2002). Firms could even share their knowledge about efficiency-driven but irresponsible behaviors, such as tax evasion, insider trading, or political bribery, thereby reducing their overall commitment to CSR (Aven, 2015).

To summarize, we contend that the situational cues from interfirm social connectedness derive free-market orientation from community political conservatism. The influence of community political conservatism is then shaped to limit CSR.

Hypothesis 2. The stronger the interfirm social connectedness in a given community in which firms are headquartered, the stronger the negative relationship between community political conservatism and the firms’ CSR.

With regard to cooperative social connectedness, the cooperative norms for community welfare fostered through social interactions reflect the community orientation of political conservatism. During frequent interactions with other community members, local people repeatedly receive the situational cue that contributing to the well-being of others and their entire community through prosocial activities is praiseworthy and well received in the community (Haidt & Graham, 2007). Therefore, despite the availability of multiple identities embedded in political conservatism, a specific identity of local constituents as community advocates is triggered by the corresponding sociocultural feature of the community (Malhotra et al., 2021). In such interactions, it is common and appropriate to discuss local matters such as how to build a better local community and identify who threatens or, conversely, contributes to the well-being of local people. A coherent narrative that praises social contributions is constructed and characterizes these interactions as well (Abolafia, 2010). Local people will see CSR, which is generally assumed to prioritize the common good over private interests, as appropriate behavior for a firm.

Cooperative social connectedness relies on the same mechanisms as interfirm social connectedness. Without strong cooperative social connectedness, the prevalence of community political conservatism by itself would neither solidify the positive perception of prosocial activities nor make local people act on their political beliefs. Although ideologies are held individually, they require a collective endorsement to be truly effective in influencing these individuals’ behaviors (Major, 1994; Thornton et al., 2012). Strong collectivity is particularly important when the group of individuals is dispersed over a large geographic area, such as a county or a state.

As local people engage more frequently in social interactions in which community orientation is highlighted, they confirm widely shared interests in the betterment of their communities and begin to actively promote prosocial behaviors. It was found, for example, that social interaction in urban parks and an attachment to a place can contribute to social cohesion (Peters, Elands, & Buijs, 2010). Normative pressure then develops in the local community to praise those firms that bear the additional costs for the community’s well-being and to publicly shame those that threaten it (Friedkin, 2004). Since conservatives tend to mete out harsher punishments to those who undermine the integrity of their communities, punitive measures—such as boycotts and political petitions—can be highly effective (Carroll, Perkowitz, Lurigio, & Weaver, 1987). The enhanced information sharing through frequent interactions will keep local people well-informed about which firms are involved in ethical or unethical behaviors (Jones et al., 1997). Even when the decision-makers’ personal beliefs do not resonate with conservatism, firms react to their local environments to attend to the beliefs and values that are predominant among local stakeholders (Husted et al., 2016).

In short, we argue that cooperative social connectedness creates situational cues that elicit the community orientation of community political conservatism. The effect of community political conservatism is shaped to endorse CSR.

Hypothesis 3. The stronger the cooperative social connectedness in a community where firms are headquartered, the weaker the negative relationship between community political conservatism and the firms’ CSR.

Method

Research setting and sample

Previous studies have established that United States counties provide meaningful boundaries in the context of sociopolitical environments (Jha & Cox, 2015; Lee & Lounsbury, 2015); therefore, we define local communities as US counties for this analysis. Following the mainstream research in the literature, we focus on the influence of communities in which firms are headquartered (Marquis, Davis, & Glynn, 2013; Tilcsik & Marquis, 2013). We compiled a dataset of the S&P 500 firms and collected their CSR data from MSCI ESG KLD Stats for the years 2000–2013. As our study is built on prior empirical findings (Di Giuli & Kostovetsky, 2014; Rubin, 2008), we selected a time frame that allowed us to make our analysis comparable with previous studies. Additionally, according to the KLD manual (MSCI, 2015), the database made some significant changes in 2014, including a notable alteration of its CSR components alongside MSCI’s acquisition of the GMI ESG Ratings. We acquired financial data from Compustat and replaced the missing values of a control variable related to research and development (R&D) with the industry mean (Bharadwaj, Bharadwaj, & Konsynski, 1999). While our main variables of interest were at the county level, this variable caused a substantial loss of the sample.

We combined the data with three county-level datasets from the US Census Bureau: the County Business Patterns (CBP), the demographic structure, and personal income. The CBP was used to collect data on social connectedness. As for community political conservatism, we collected county-level presidential election results in keeping with previous studies (Di Giuli & Kostovetsky, 2014; Rubin, 2008). Since county-level data were not easy to obtain, we acquired the data from diverse sources: the School of Public Affairs at American University (2019), CNN (2019), and The Guardian (2019). Our final sample was composed of 595 firms and 6093 observations.

Dependent variable: CSR

We based our measure of CSR on the KLD database. Designed in 1991 for institutional investors, KLD obtains relevant data from a variety of sources: annual reports, company websites, CSR reports, media, and other stakeholder-related data sources. KLD identifies strengths and concerns regarding CSR-related policies and activities in seven main categories: community, corporate governance, diversity, employee relations, environment, human rights, and products (MSCI, 2015). In evaluating each component for strengths and concerns, KLD assigns one to a firm if it meets its assessment criteria and zero if the assessment is otherwise.

Following the most widely used approach in the literature, we calculated our measure of CSR by summing up all of the strengths and subtracting all of the concerns for each firm based on the annual data (Gupta et al., 2017; Tang, Clyde, & Rothenberg, 2012). In an additional analysis, we tested our models on two separate measures that represented strengths and concerns respectively. To maintain the comparability of the values of our measure between years, we focused on the CSR components that were monitored throughout the entire period of our time frame (MSCI, 2015). Following prior studies (Husted et al., 2016; K.-H. Kim, Kim & Qian, 2018), we also ruled out corporate governance and product from our measure to focus on dimensions that are more directly tied to social values rather than economic returns. Corporate governance does not entail serious agency conflicts between managers and shareholders (Husted et al., 2016). CSR practices related to products often inherently involve a firm’s strategic efforts for additional quality control and product safety (Husted et al., 2016; Minor & Morgan, 2011). To ensure robust results, we tested our models on measures including all dimensions and found largely consistent results.

Independent variable: Community political conservatism

To measure community political conservatism, we followed previous studies and used the county-level presidential election results as a proxy (Di Giuli & Kostovetsky, 2014; Rubin, 2008). In countries where a strong representative democracy is established, the political system is designed to allow the ideological preferences of the electorate to be reflected through their voting patterns (Urbinati, 2006). The two major political parties in the United States—the Republican Party and the Democratic Party—are associated with political conservatism and liberalism, respectively. Party identification is known to represent the “most stable and influential political predisposition in the belief system of ordinary citizens” (Goren, Federico, & Kittilson, 2009, p. 805). Some studies have verified that the distinction between both political ideologies has remained strong in the United States as measured by the parties’ different positions (McCarty, Poole, & Rosenthal, 2006), the US Congress (Hetherington, 2009), and public opinion polls (Jost, 2006). Our measure for community political conservatism was the vote share (%) received by the Republican Party minus that received by the Democratic Party. Because presidential elections take place every four years in the United States, we followed the interpolation technique of previous studies to generate the expected values for the missing years and assumed a linear relationship over the adjacent years.

Moderators: Cooperative and interfirm social connectedness

We obtained the county-level data on social connectedness from the CBP of the US Census Bureau (Jha & Cox, 2015; D. Kim, Subramanian, Gortmaker, & Kawachi, 2006). This database provides subnational economic data at various levels of society. Two different types of social connectedness—interfirm and cooperative—were examined by proxy variables: the density of relevant social associations (e.g., religious organizations and recreational centers) in US counties. Rupasingha et al. (2006) devised this proxy for a more abstract concept of how connected local actors are, in general, in a community (Shideler & Kraybill, 2009). The critical role of associational activities has been highlighted in the literature on community social capital from the early days of theorization (Fukuyama, 1995; Putnam, 1993). In a tightly connected community, local actors are more likely to materialize their connectedness in the form of social associations (Rupasingha et al., 2006) which would, in turn, create further opportunities to strengthen such connectedness (Engbers, Thompson, & Slaper, 2017; Putnam, 1993). Recent studies in various disciplines have employed this method (Chetty, Hendren, Kline, & Saez, 2014; Jha & Cox, 2015).

We measured two types of community social connectedness by calculating the number of relevant social associations per 100,000 people in each county. While previous studies examined the overall social connectedness of a county as a single construct in their model, the purpose of our study is to add more depth to this view and to distinguish between interfirm and cooperative social connectedness (Knack & Keefer, 1997). As suggested by Rupasingha et al. (2006), we included religious and civic organizations, bowling centers, golf clubs, and recreational sports centers for the measure of cooperative social connectedness. Our measure for interfirm social connectedness was based on the number of business associations, which are key platforms for the associational life of firms (Campbell, 2007). According to the North American Cartographic Information Society, business associations are operating entities that mainly promote the business interests of their members through activities such as researching new products and services, developing market statistics, and lobbying public officials (Office of Management and Budget, 2017).

Control variables

Our model accounts for some other factors that may affect CSR. We included firm size, the logarithm of the number of employees, to control the influence of visibility (Meyer & Höllerer, 2016). Second, we controlled for financial performance, the log-transformed and lagged net income, to consider a firm’s capacity to invest in CSR (Adams & Hardwick, 1998). Third, leverage, measured by the debt-to-asset ratio, was added to the model for the same reason (Brammer, Pavelin, & Porter, 2009). Fourth, we controlled for cash holdings, the ratio of cash to total assets, assuming that firms can divert firm values more flexibly when they hold more cash (Flammer, 2015). Fifth, R&D intensity, the R&D expense to asset ratio, was included in the model because it can lead to better CSR through product and process innovation (Padgett & Galan, 2010). Sixth, we controlled for organizational political conservatism, using an index that was devised by Gupta et al. (2017) based on the political donations of a company’s employees, to account for ideological influences emanating from the firms themselves. Next, we considered the direct effects of two types of community social connectedness, because community social capital in general facilitates coordination for CSR (Jha & Cox, 2015).

As county-level controls, we included per capita income, county population, and demographic structure (race and sex), which account for the economic and social environments of counties. Per capita income and county population were log-transformed. Demographic structure (sex) was measured as the percentage of the female population. Demographic structure (race) was based on Simpson’s (1949) diversity index, which assigns one to infinite diversity and zero to an absence of diversity. To consider industry-level shared behavioral patterns (Marquis & Tilcsik, 2016), we included industry CSR, which was measured by the industry mean of CSR. Lastly, year dummies were added.

Analysis

We used the hierarchical linear model (HLM) to test our hypotheses because our observations had a nested structure with multiple levels, and errors were correlated within clusters. Simultaneously using the county-level and firm-level variables also makes HLM more desirable for our analysis. Our model included three levels: individual observations (level one), firms (level two), and counties (level three). The maximum likelihood method was used to generate the estimates. For the regression assumptions, we conducted several tests. The Breusch-Pagan test and the likelihood-ratio test of the variance of the firm-level residuals indicated that there was heterogeneity among the firms. The Wooldridge test and the modified Wald test revealed the autoregressive structure of the within-firm errors and the groupwise heteroskedasticity, respectively. We used robust standard errors to address these issues. Lastly, the Hausman test indicated that certain estimators had systematic differences when the random-effects model was applied. To account for fixed effects, we centered variables by using firm or county means according to the level of the variables.

Results

We present the descriptive statistics and correlation matrix in Table 1. Significant correlation coefficients are bold-faced in Table 1. We also checked the variance inflation factors in a reduced regression model. All values were below 10, which suggested that multicollinearity was not a serious problem. In Table 2, we present the main results of our hypothesis tests based on the HLM models, starting from a baseline model with controls.

Table 1.

Descriptive statistics and correlation matrix.

Variables	Mean	Std.	1	2	3	4	5	6	7
1. CSR	0.72	2.29	1.00
2. Community political conservatism	−21.5	28.3	−0.17	1.00
3. Interfirm social connectedness	6.36	5.55	0.04	−0.33	1.00
4. Cooperative social connectedness	74.0	22.6	0.01	0.17	0.28	1.00
5. Industry CSR	0.69	0.55	0.27	−0.27	0.09	0.04	1.00
6. Firm size	2.83	1.32	0.19	−0.02	0.03	0.10	−0.04	1.00
7. Financial performance	9.65	0.12	0.23	−0.10	0.04	−0.04	−0.01	0.40	1.00
8. Leverage	0.23	0.18	−0.11	−0.01	0.04	0.01	−0.03	−0.09	−0.13
9. Cash holdings	9.67	9.54	0.06	−0.09	−0.11	−0.17	0.13	−0.17	−0.10
10. R&D intensity	1.02	0.90	0.17	−0.03	−0.12	−0.20	0.18	−0.19	−0.04
11. Organizational political conservatism	0.00	1.91	−0.12	0.18	−0.05	0.08	−0.11	−0.02	−0.03
12. Per capita income	10.8	0.35	0.19	−0.51	0.36	−0.04	0.16	0.01	0.16
13. Unemployment	6.27	2.16	0.09	−0.26	−0.13	−0.15	0.05	0.02	0.03
14. County population	13.8	1.04	−0.02	−0.36	−0.13	−0.67	−0.11	0.00	0.08
15. Demographic structure (race)	0.40	0.13	0.08	−0.67	0.10	−0.28	0.03	0.03	0.13
16. Demographic structure (sex)	51.1	1.04	0.02	−0.33	0.21	0.42	0.17	0.13	0.06
Variables	8	9	10	11	12	13	14	15	16
8. Leverage	1.00
9. Cash holdings	−0.21	1.00
10. R&D intensity	−0.17	0.41	1.00
11. Organizational political conservatism	−0.01	−0.09	−0.10	1.00
12. Per capita income	0.02	0.08	0.02	−0.16	1.00
13. Unemployment	0.03	0.12	0.00	0.07	0.03	1.00
14. County population	0.01	0.07	0.05	−0.08	0.17	0.19	1.00
15. Demographic structure (race)	0.02	0.07	0.00	−0.08	0.28	0.31	0.45	1.00
16. Demographic structure (sex)	0.05	−0.16	−0.20	0.01	0.15	0.09	−0.08	0.22	1.00

Note: Estimates are in bold when significant (p < 0.05).

Table 2.

Hierarchical linear models on CSR.

DV: CSR	Model 1	Model 2	Model 3	Model 4	Model 5
H1: Community political conservatism (CPC)		−0.018* (0.009)	−0.014 (0.009)	−0.021* (0.009)	−0.018* (0.009)
H2: CPC × Interfirm social connectedness			−0.018* (0.007)		−0.021** (0.007)
H3: CPC × Cooperative social connectedness				0.004** (0.001)	0.005** (0.001)
Interfirm social connectedness	−0.013 (0.042)	−0.010 (0.043)	0.017 (0.047)	−0.012 (0.041)	0.020 (0.045)
Cooperative social connectedness	0.022* (0.010)	0.024* (0.010)	0.024* (0.010)	0.019† (0.010)	0.019† (0.010)
Industry CSR	0.910*** (0.083)	0.905*** (0.083)	0.902*** (0.083)	0.909*** (0.083)	0.907*** (0.083)
Firm size	−0.175 (0.125)	−0.176 (0.122)	−0.172 (0.122)	−0.178 (0.122)	−0.174 (0.122)
Financial performance	0.753* (0.302)	0.734* (0.300)	0.732* (0.304)	0.725* (0.302)	0.723* (0.307)
Leverage	0.400 (0.250)	0.379 (0.252)	0.378 (0.251)	0.356 (0.252)	0.352 (0.251)
Cash holdings	0.002 (0.005)	0.002 (0.005)	0.003 (0.005)	0.003 (0.005)	0.003 (0.005)
R&D intensity	0.072 (0.160)	0.072 (0.160)	0.067 (0.160)	0.064 (0.159)	0.058 (0.159)
Organizational political conservatism	−0.035* (0.016)	−0.034* (0.016)	−0.034* (0.016)	−0.033* (0.016)	−0.033* (0.016)
Per capita income	−0.722 (0.617)	−0.542 (0.645)	−0.544 (0.659)	−0.428 (0.597)	−0.419 (0.605)
Unemployment	−0.035 (0.034)	−0.038 (0.034)	−0.032 (0.034)	−0.031 (0.033)	−0.024 (0.033)
County population	0.511 (0.418)	0.476 (0.425)	0.506 (0.436)	0.517 (0.413)	0.555 (0.421)
Demographic structure (race)	1.312 (2.677)	1.467 (2.819)	1.912 (2.750)	1.346 (2.688)	1.844 (2.602)
Demographic structure (sex)	−0.155 (0.164)	−0.205 (0.166)	−0.221 (0.167)	−0.197 (0.167)	−0.214 (0.169)
Constant	−0.610* (0.237)	−0.446† (0.258)	−0.368 (0.264)	−0.404† (0.238)	−0.310 (0.241)
Year dummies	Yes	Yes	Yes	Yes	Yes
Number of firms	595	595	595	595	595
Number of counties	159	159	159	159	159
Number of observations	6,093	6,093	6,093	6,093	6,093
Log likelihood	−10963.2	−10959.0	−10954.3	−10952.2	−10946.1
Akaike information criterion	21988.4	21982	21974.6	21970.5	21960.1

Note: Robust standard errors in parentheses. Variables are centered at the corresponding level (i.e., firm or county level).

†

p < 0.1. *p < 0.05. **p < 0.01. ***p < 0.001.

In Model 2, we examine hypothesis 1, which predicts an overall negative relationship between community political conservatism and CSR. Consistent with previous studies, we found a negative effect of community political conservatism on CSR (p < 0.05). Model 3 provides the main test of hypothesis 2, which predicts that the negative effect of community political conservatism on CSR will be more pronounced when the counties in which firms are headquartered have stronger interfirm social connectedness. We found a negative and significant moderating effect of interfirm social connectedness (p < 0.05), supporting hypothesis 2. In Model 4, we test hypothesis 3, which predicts that the negative relationship between community political conservatism and CSR will be less pronounced when firms are headquartered in counties with strong community social connectedness. There was a positive and significant moderating effect of community social connectedness (p < 0.01), which lends support to hypothesis 3. Lastly, we present consistent findings of the moderating effects of social connectedness in the full model, Model 5.

Figure 1 displays the moderating effects of two types of community social connectedness on the relationship between community political conservatism and CSR. The solid and dotted lines, respectively, represent communities with relatively stronger (one standard deviation above the mean) and weaker (one standard deviation below the mean) community social connectedness. The directional changes of the slopes illustrate that the negative relationship between community political conservatism and CSR can be either more observable or disappear; depending on the levels of community social connectedness.

Figure 1.

The moderating effect of interfirm and cooperative social connectedness on the relationship between community political conservatism and CSR.

In Table 3, we present the results of an additional analysis in which we split our measure for CSR into the “doing good” and “avoiding bad” dimensions (Lin-Hi & Müller, 2013, p. 1928). While the combined measure is best for representing a firm’s overall commitment to CSR, this separation allows us to perceive a more nuanced relationship between community political conservatism and CSR. We measured the doing-good and avoiding-bad dimensions by summing up KLD strengths and concerns respectively. For the latter dimension, we reverse-coded the values so that firms that better prevented their involvement in wrongdoing had higher values.

Table 3.

Additional analysis: hierarchical linear models on two types of CSR.

DV: CSR	Model 1	Model 2	Model 3	Model 4
DV: CSR	Doing good		Avoiding bad
Community political conservatism (CPC)	−0.017* (0.008)	−0.016^† (0.008)	−0.001 (0.006)	−0.002 (0.006)
CPC × Interfirm social connectedness		−0.013* (0.006)		−0.008^† (0.005)
CPC × Cooperative social connectedness		0.001 (0.001)		0.003*** (0.001)
Interfirm social connectedness	0.001 (0.043)	0.020 (0.046)	−0.011 (0.023)	0.000 (0.023)
Cooperative social connectedness	0.015^† (0.009)	0.014 (0.009)	0.009 (0.006)	0.006 (0.005)
Industry CSR	0.183^† (0.094)	0.184^† (0.094)	0.754*** (0.088)	0.758*** (0.088)
Firm size	0.154 (0.111)	0.156 (0.111)	−0.341*** (0.077)	−0.341*** (0.077)
Financial performance	0.211 (0.342)	0.207 (0.346)	0.491** (0.191)	0.484* (0.191)
Leverage	0.340 (0.243)	0.331 (0.242)	0.035 (0.135)	0.017 (0.134)
Cash holdings	0.000 (0.004)	0.000 (0.004)	0.002 (0.002)	0.002 (0.002)
R&D intensity	0.062 (0.122)	0.056 (0.122)	0.007 (0.103)	−0.001 (0.102)
Organizational political conservatism	−0.027^† (0.015)	−0.027^† (0.016)	−0.006 (0.008)	−0.006 (0.007)
Per capita income	−0.385 (0.525)	−0.346 (0.520)	−0.193 (0.479)	−0.107 (0.460)
Unemployment	−0.031 (0.031)	−0.025 (0.031)	−0.009 (0.025)	−0.001 (0.024)
County population	0.657 (0.462)	0.691 (0.465)	−0.184 (0.303)	−0.140 (0.307)
Demographic structure (race)	1.614 (2.457)	1.893 (2.419)	−0.231 (2.014)	−0.126 (1.892)
Demographic structure (sex)	−0.191 (0.136)	−0.199 (0.137)	−0.017 (0.087)	−0.018 (0.087)
Constant	0.760** (0.235)	0.830*** (0.228)	−1.238*** (0.188)	−1.170*** (0.186)
Year dummies	Yes	Yes	Yes	Yes
Number of firms	595	595	595	595
Number of counties	159	159	159	159
Number of observations	6,093	6,093	6,093	6,093
Log likelihood	−9828.2	−9823.9	−8052.2	−8040.9
Akaike information criterion	19720.4	19715.8	16168.5	16149.7

Note: Robust standard errors in the parentheses. Variables are centered at the corresponding level (i.e., firm or county level).

†

p < 0.1. *p < 0.05. **p < 0.01. ***p < 0.001.

This additional analysis revealed that the negative moderating effect of interfirm social connectedness was clearly observable from the model on the doing-good aspect of CSR (p < 0.05) but only marginally from the one on avoiding bad (p < 0.1). The spread of free-market orientation allows firms to collectively control their social contributions, but this coordination does not notably extend to colluding in wrongdoings. Although such wrongdoings can be easy solutions to fulfill firms’ economic responsibilities, they have a negative spillover effect on other firms (Zavyalova, Pfarrer, Reger, & Shapiro, 2012). Since free-market capitalism highlights market players’ compliance with fair competition (Turner, 2008) irresponsible collusion may not be accepted well at the collective level.

Conversely, the positive moderating effect of community social connectedness was significant only in the model on the avoiding-bad aspect of CSR (p < 0.001). The spread of community orientation helps control firm behaviors that threaten the common good but does not encourage firms to bear extra costs for social contributions. This is consistent with the general tendency of conservatives to inflict harsher punishments on those who impair the integrity of their communities (Carroll et al., 1987). This result indicates that even when community orientation is boosted, the idea that the role of firms is limited to economic responsibilities largely persists among conservatives (Walters, 1977).

Discussion and Conclusion

We set out to develop a more nuanced model for the relationship between community political conservatism and CSR. The literature has consistently found that the more frequently the conservative values are espoused in a community, the weaker the commitment to CSR displayed by firms headquartered in the community due to the preference of conservatives for free-market capitalism (Di Giuli & Kostovetsky, 2014; Lee & Lounsbury, 2015; Rubin, 2008). We have challenged this view by shedding light on an overlooked value of political conservatism: community orientation (Haidt & Graham, 2007). By integrating social capital theory (Putnam, 1993) and the logic of appropriateness perspective (March & Olsen, 2004), we explain how the contradictory sides of political conservatism—free-market and community orientations—are triggered by two different types of community social connectedness. While interfirm social connectedness enhances the well-documented negative relationship between community political conservatism and CSR, community social connectedness mitigates this negative relationship. Our findings make contributions to several bodies of literature.

First and foremost, we contribute to the literature on CSR by advancing our understanding of the relationship between community political ideology and CSR. Political ideology has attracted much attention over the past decade, but most studies have concentrated on the impacts of personal or organizational ideologies (Chin et al., 2013; Chow et al., 2022; Collet, Carnabuci, Ertug, & Zou, 2022; Gupta et al., 2017; Semadeni, Chin, & Krause, 2022) with only a few exceptions (Di Giuli & Kostovetsky, 2014; Lee & Lounsbury, 2015; Rubin, 2008). Local processes of political ideology are still significantly understudied, although political ideology is frequently used to demarcate geographical boundaries as communities often have notably different political beliefs (McCarty et al., 2006). The lack of attention to local processes is problematic because the causal mechanism determining how political ideology affects firms is distinct at the community and firm levels. While previous studies have found critical conditions that facilitate the manifestation of individual or organizational ideologies—such as personal power (Chin et al., 2013), status (Collet et al., 2022), internal ideological support (Chin & Semadeni, 2017), and human capital intensity (Gupta et al., 2017)—little is known about such conditions at the community level. Our study takes one of the first steps to demonstrate the key role of collectives in either weakening or reinforcing ideological influences (Thornton et al., 2012). Since community-level processes depend on a considerable number of local constituents who are often widely spread over a geographical area, the coordination capacity of the collective is required for a shared political belief to materialize. Incorporating community social connectedness, which improves this coordination capacity, into the framework thus enables us to tease out more nuanced relationships between community political ideology and CSR.

In addition, our study illustrates the importance of considering various aspects of political ideology. Because the extant literature focuses on the classification of political liberalism and conservatism, the multifaceted nature of these ideologies is understudied (Feldman & Johnston, 2014). The prevailing dichotomous view of the political spectrum has impeded the use of more sophisticated models proposed in other disciplines (Haidt & Graham, 2007; Skitka & Tetlock, 1993), often simply portraying political conservatism as an everlasting obstacle to social welfare (Berrone, Gelabert, Massa-Saluzzo, & Rousseau, 2016). Our study demonstrates that the impact of political conservatism is not necessarily consistent but a result of “framing contests” wherein two types of community social connectedness elicit competing cognitive frames from political conservatism, which, in turn, impose contradictory guidelines for appropriate actions (Kaplan, 2008, p. 730). Therefore, the overall influence of political conservatism is an outcome of a contest between two collectives, one for the decision-makers of firms and the other for general local people, whose relative coordination capacity determines which identity of political conservatism dictates the overall influence in the end.

In a similar vein, our findings contribute to the broader literature on community influences on firm behavior. We reveal that community social capital might have more varied roles than currently described in the literature through its interaction with other local institutions for which collectivity matters. Previous studies have analysed community social capital in isolation from other local institutions, as their focus was on the direct influence of community social capital on firm behaviors (Jha & Cox, 2015; Kwon, Heflin, & Ruef, 2013; Laursen et al., 2012). However, in organization studies, geographical communities are now recognized as institutional fields in which various actors and multiple institutions are involved in affecting firm behavior (Marquis et al., 2013). Given the function of community social capital to facilitate collective action (Ostrom & Ahn, 2009), our results suggest that it is linked with the collective process of political ideology that spreads throughout a community (Ansari, Wijen, & Gray, 2013; Thornton et al., 2012). It is assumed that not only community political ideology but also many other local institutional processes require a collective endorsement to be fully influential (Berrone et al., 2016; Song, 2021). We suggest that future research consider the critical role of community social capital in either amplifying or limiting the influence of other institutions.

Next, we advance social capital theory by adding more depth to the current view of community social connectedness. While previous studies have examined the heterogeneity between various forms of community social capital—such as social trust, generalized reciprocity, and social connectedness (Jha & Cox, 2015; Kwon et al., 2013)—the heterogeneity accruing to each of these forms has not yet been empirically explored. Nevertheless, the fact that prior studies often produced inconsistent findings regarding the effect of community social connectedness (Hasan, Hoi, Wu, & Zhang, 2017; Jha & Cox, 2015; Knack, 2002) indicated that there might be an overlooked process through which the differing effects of social connectedness can be explained. Drawing on Knack and Keefer’s (1997) classification of instrumental and cooperative social connections, we demonstrate how two types of community social connectedness can produce different implications for firms and communities.

In this regard, we answer the literature’s call for more research on the negative impacts of community social capital (Kwon & Adler, 2014; Portes, 1998). Social capital theory has paid excessive attention to the positive influence of social capital on society (Kwon & Adler, 2014; Portes, 1998). In organization studies, under the assumption that some positive values are inherent to social capital, most studies have focused on what types of benefits community social capital offers to firms, including entrepreneurship (Kwon et al., 2013), innovation (Laursen et al., 2012), and CSR (Hasan et al., 2017; Jha & Cox, 2015). In contrast, we advance the idea that the impact of social capital is determined by the actual contents transmitted through social interactions (Portes, 1998; Putzel, 1997). While the extant literature lacks empirical support for this proposition (Kwon & Adler, 2014), we demonstrate how contradictory behavioral prescriptions are developed through two different types of social connectedness by incorporating the conflicting values of community political conservatism. Our findings suggest that future research should begin paying more attention to the contexts in which community social capital is formed rather than simply assuming better social coordination as a positive contributor to society.

Lastly, the integration of the logic of appropriateness perspective and social capital theory generates a useful framework that clarifies why the available appropriate rules of actions are activated to different extents. The mechanism of the logic of appropriateness involves the collective acts of logic construction and socialization (Abolafia, 2010; March & Olsen, 2004); therefore, community social connectedness, which facilitates the coordination of collectives, is bound to play a critical role in such construction and enforcement processes. Our framework can provide insights into other streams of research that examine institutionalized rules of action in general. For example, the institutional logics perspective has devoted significant attention to the dynamics of conflicting institutional logics (Greenwood, Raynard, Kodeih, Micelotta, & Lounsbury, 2011).¹ This perspective can employ our framework to examine how the different types of social connectedness act as the sources of situational cues that activate competing logics (Malhotra et al., 2021). While communities are regarded as valid spheres for developing institutional logics (Thornton et al., 2012), and the coordination of collectives has been emphasized in theorization (Ansari et al., 2013), the role of community social capital has not been fully explored yet.

Our study has some limitations that represent opportunities for future research. Because an examination of the macro-level process was the purpose of our study, we focused on the influence of community political conservatism on CSR. Nevertheless, key decision-makers in headquarters can promote their personal ideologies during the process where community political ideology penetrates a firm’s decision-making (Chin et al., 2013). Investigating this potential interaction between community and individual political ideologies will shed further light on the causal mechanism of ideological impacts on CSR.

Another limitation revolves around the fact that we examine only the impact of communities in which firms are headquartered. Such community impacts have been the main focus of the extant literature because the key decision-makers of firms are likely to live near their headquarters (Palmer et al., 1986; Porter, 1998) and also because firms are influenced by the local stakeholders of their headquarters’ locations (Husted et al., 2016; Marquis et al., 2013). If feasible, however, future research might attempt to study the effects of all the communities in which each firm is operating (Arenas, Murphy, & Jáuregui, 2020). For example, by assigning different weights to communities based on resource dependence, a more accurate picture of community influences on firm behavior can be drawn.

In addition, although social connectedness builds the foundations for other forms of social capital—such as reciprocity, trust, and norms (Putnam, 1993; Rupasingha et al., 2006)—these forms could have their own implications for the effect of community political conservatism (Knack, 2002). For example, while the influence of community social connectedness depends on the actual contents transmitted through social interactions, there is a possibility that generalized reciprocity always leads to positive changes in a local community due to its inherently positive value. Future research, therefore, needs to investigate whether other forms of social capital also internally have distinctive types that would activate different sides of political conservatism. This will be an essential step to clarify the extent to which the theoretical notion that the actual content determines the outcome of social capital is applicable to the mechanism of community social capital (Putzel, 1997).

Future research could further develop our measure for community social connectedness. Our measure, which is grounded in the method developed by Rupasingha et al. (2006), relies on social associations as cultural artifacts of more socially connected and active communities. This use of social associations has opened up new opportunities, as it allows for comparisons of an unprecedentedly large number of communities for social capital research (Rupasingha et al., 2006). Future research may further develop this proxy by taking into account the idiosyncrasies of individual social associations. For example, the varying size or political power of social associations can be incorporated into the equation so that the nuanced differences in community social connectedness are more accurately reflected in the proxy. Different weights can be given to different social associations depending on the contextual importance of the corresponding type of community social connectedness. Additionally, although we use proxies to explore our hypothesized relationships, qualitative research may benefit from in-depth interviews to deepen our understanding of the mechanism we explain.

To conclude, we have developed and empirically tested a theoretical framework that untangles the complex relationship between community political conservatism and CSR. By integrating social capital theory and the logic of appropriateness perspective, we illustrate how interactions between community political conservatism and social connectedness emerge to either facilitate or limit CSR. Unlike what is commonly portrayed in the literature, community political conservatism does not always weaken firms’ CSR but also has a “softer” side.

Footnotes

We wish to thank the senior editor Charlene Zietsma for her excellent support and guidance. We also thank the anonymous reviewers who have provided detailed and constructive feedback throughout the review process. Additionally,we are grateful to Christine Oliver,Maxim Voronov,Mike Valente,Charles H. Cho,Giovanna Michelon,Sonya Scott,and Noa Song for their valuable contributions to our research.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

ORCID iDs

Tony Jaehyun Choi

Yuval Deutsch

Author biography

Tony Jaehyun Choi is an assistant professor at the Rotterdam School of Management,Erasmus University. His research investigates institutional determinants for socially responsible behavior of firms. He mainly explores the roles of social control agents and socio-political environments. He holds a PhD in organization studies from the Schulich School of Business,York University.

Yuval Deutsch is a professor of strategic management and entrepreneurship at the Schulich School of Business,York University. He studies corporate governance,inter- and intra-organization prosocial behavior,and signaling. His work has been published in Management Science,Academy of Management Review,Organization Studies,Journal of Management,Journal of Organizational Behavior,and others.

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The Two Sides of Community Political Conservatism and CSR: Exploring the role of community social connectedness

Abstract

Keywords

Introduction

Theoretical Background and Hypotheses

Community political conservatism and corporate social responsibility engagement

Multidimensional political conservatism and logic of appropriateness

Two types of social connectedness

Method

Research setting and sample

Dependent variable: CSR

Independent variable: Community political conservatism

Moderators: Cooperative and interfirm social connectedness

Control variables

Analysis

Results

Discussion and Conclusion

Footnotes

Funding

ORCID iDs

Author biography

References