# Beacons not burdens: Business groups and corporate social performance around the world

Sorin M. S. Krammer, Vlad-andrei Porumb, Yasemin

Zengin-Karaibrahimoglu, Joel Bothello

► To cite this version:

Sorin M. S. Krammer, Vlad-andrei Porumb, Yasemin Zengin-Karaibrahimoglu, Joel Bothello. Beacons not burdens: Business groups and corporate social performance around the world. Global Strategy Journal, 2024, 14 (4), pp.709 - 753. 10.1002/gsj.1515. hal-05511785v2

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# Beacons not burdens: Business groups and corporate social performance around the world

Sorin M. S. Krammer<fnref n="1" />,<fnref n="2" /> ID

Vlad-Andrei Porumb<fnref n="3" />

Yasemin Zengin-Karaibrahimoglu<fnref n="4" />

Joel Bothello<fnref n="5" />

## Correspondence

Sorin M. S. Krammer, Surrey Business School, University of Surrey, Guildford, UK.

Email: s.krammer@surrey.ac.uk

## Abstract

**Research Summary:** Prior studies on business groups (BGs) have predominantly focused on the impact of group affiliation on financial performance. In contrast, we argue that BG affiliates will outperform standalone firms in terms of corporate social performance (CSP) and that this effect will be positively moderated by the strength of formal and informal institutions. Moreover, we examine also differences among BGs and hypothesize that diversification and hierarchy of the group will negatively affect the CSP of affiliates. Employing a panel of 4368 firms from 43 countries between 2003 and 2016 and a propensity score matching approach in our regressions, we find robust support for these predictions. Our findings advance two distinct strands of literature on BGs and, respectively, corporate social responsibility.

**Managerial Summary:** BG are a common organizational structure in many countries. Despite this, we still do not know much about them beyond their financial performance. In this study, we focus on examining the impact of BG affiliation on non-financial performance (i.e., CSP) in the light of growing societal grand challenges. Using an international dataset of several thousands of firms, we find out that BG affiliates exhibit superior CSP results compared to non-affiliated firms.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2024 The Author(s). *Global Strategy Journal* published by John Wiley & Sons Ltd on behalf of Strategic Management Society.

<footnote n="1">¹Surrey Business School, University of Surrey, Guildford, UK</footnote>

<footnote n="2">²Southampton Business School, University of Southampton, Southampton, UK</footnote>

<footnote n="3">³Alliance Business School, University of Manchester, Manchester, UK</footnote>

<footnote n="4">⁴Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands</footnote>

<footnote n="5">⁵John Molson Business School, Concordia University, Montreal, Canada</footnote>
These positive effects of affiliation are increased in environments with strong formal and informal institutions but reduced within groups that are more diversified and hierarchical. Our findings showcase the importance of BGs in tackling some of today's grand challenges and provide support for more nuanced approaches to study BGs across countries.

### KEYWORDS

business groups, corporate social performance, institutions, organizational structure

# 1 | INTRODUCTION

Defined as federations of legally independent firms bound together through equity and social ties, business groups (BGs) have become ubiquitous across both developed and developing markets (Bucheli et al., 2019; Carney et al., 2011; Castaldi et al., 2019). Through intra-group trading and resource-sharing arrangements, BGs function as a unique hybrid between hierarchical organizations and arm's length transactions, which often grants them important advantages compared to conventional, standalone firms (Dau et al., 2021; Granovetter, 1995; Iona et al., 2013). Subsequently, the bulk of the literature on BGs has focused on comparing the financial performance of BG affiliates to non-affiliates to gage the potential value of affiliation (Carney, 2008; Colli & Colpan, 2016; Mukherjee et al., 2018).

While this important body of work provides multiple insights into the financial benefits of BG affiliation, it has paid far less attention to non-financial ramifications, namely policies and practices around environmental and social issues (Choi & Wang, 2009). This omission is particularly important since addressing “grand challenges” like inequality, poverty, environmental degradation, or climate change (George et al., 2016; Kolk & Van Tulder, 2010; Krammer, 2024; Krammer et al., 2023) has become a strategic imperative for long-term market success and a priority for the development of efficacious organizational responses to these issues (Habib & Hasan, 2019; Lu et al., 2023). In this regard, BGs present an important, yet under-explored, organizational context that may play an important role in addressing societal problems by, for instance, building critical infrastructure (Gao et al., 2017; Mukherjee et al., 2018) or tackling sustainability challenges (Choi & Wang, 2009). By extension, we also lack a proper understanding of the boundary conditions for BGs' role in this area, and particularly, how their internal idiosyncrasies may shape the behavior and non-financial performance of affiliated firms (Chittoor et al., 2015).

Targeting these salient questions, we focus on the effects of BG affiliation on the non-financial performance of firms, as proxied by corporate social performance (CSP) indicators (Ioannou & Serafeim, 2012; Napier et al., 2023). Defined as “policies, programs, and observable outcomes as they relate to the firm's societal relationships” (Wood, 1991), CSP metrics are common proxies for evaluating a firm's impact on its stakeholders, namely employees, clients, and the local community (Brammer & Pavelin, 2006; Cornelius et al., 2008), “on issues related to the environment, animals, discrimination, charitable contributions, and human rights” (Dikolli et al., 2022, p. 865).¹

Employing transaction costs economics (TCE) arguments (Roberts & Greenwood, 1997; Williamson, 1981), we propose that BG affiliates will outperform non-affiliates in terms of CSP
<figure><img src="image_3.png" /></figure>

due to their superior ability to reduce the transaction costs and informational asymmetries associated with social and environmental activities. Specifically, we theorize that certain characteristics that generate an advantage for BG affiliates in terms of financial performance—namely, reputation (Chittoor et al., 2015; Gao et al., 2017), internal trading arrangements (Belenzon et al., 2013; Birhanu & Wezel, 2022), and external networks (Belderbos & Sleuwaegen, 1996; Lincoln & Sargent, 2018)—will also impact non-financial performance through a reduction of search, contracting, and monitoring costs of CSP practices vis-à-vis non-affiliated firms. Specifically, CSP requires firms to engage in activities and initiatives that often do not have immediate or direct financial payoffs, but rather help in building long-term legitimacy and trust with their stakeholders (Gao et al., 2017). As such, we argue that BG affiliates are better equipped, compared to standalone firms, to accomplish these non-financial goals.

Moreover, we consider TCE as applied to context (North, 1991) and propose that the benefits of BG affiliation will be further shaped by country-specific institutional arrangements, as reflected by formal institutions (e.g., regulations, policies, and legal systems) and informal ones (e.g., norms, values, and relational networks), all of which reduce the search, information, bargaining, and enforcement costs of affiliates (Chittoor et al., 2015; Granovetter, 2005). Lastly, we also investigate some group-specific contingencies by arguing that groups that are more hierarchical and diversified—two key dimensions of BG heterogeneity (Ramachandran et al., 2021; Yiu et al., 2007)—will score lower on CSP than those that are not, as these characteristics will increase coordination and sharing costs of CSP best practices across BG affiliates (Kang, 2013).

We test these theoretical conjectures using 29,886 firm-year observations from 4368 firms across 43 countries between 2003 and 2016. Our results indicate robustly that, on average, group affiliates have higher CSP than non-affiliates and that affiliation with more hierarchical and diversified groups diminishes CSP benefits, consistent with our hypotheses. Regarding the social value of BGs, we find that greater formal and informal institutional pressures toward social and environmental behaviors across countries further enhance the CSP performance of affiliates.

We advance three contributions. First, we develop a theoretical framework that applies TCE rationales (Yiu et al., 2005) to explain why BG affiliates are more successful than non-affiliates in terms of non-financial performance. In this way, we expand the BG literature (Carney et al., 2018) by considering non-financial implications of group affiliation. Specifically, we answer prior calls to fill in the existing “nexus between corporate social responsibility and business groups” (Choi & Wang, 2009) as an avenue to address their social and ecological footprint (Wiessner et al., 2024) and respond to today’s grand challenges (George et al., 2016).

Second, our findings showcase the pivotal ability of formal and informal institutional contingencies to reinforce the relationship between BG affiliation and social and environmental performance of firms in a comparative, multi-country setting. Notably, this result is at odds with one of the dominant views of BGs in the literature (i.e., the institutional voids perspective) and asserts the need for more nuanced theoretical approaches when analyzing BGs in an international setting (Carney et al., 2018). In addition, while global strategy scholarship has paid attention to BGs (Carney et al., 2011; Dau et al., 2021; Mukherjee et al., 2018; Yiu et al., 2007), most contributions remain conceptual or confined to single-country settings, which in turn curb their academic generalizability and policy applications. In particular, longitudinal investigations of how country characteristics affect BG formation and performance, as well as the interplay between BG characteristics and institutions, are two areas where scholarship needs more empirical attention (Aguilera et al., 2019; Bucheli et al., 2019).
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Finally, we theorize how different internal group characteristics (e.g., the group's hierarchy and diversification) affect non-financial performance of its affiliates. Our insights complement recent findings in this literature regarding the significance of internal factors such as ownership, diversification profiles, or operational structures (Bouquet & Birkinshaw, 2008; Desender & Epure, 2021; Gu et al., 2019; Ramachandran et al., 2021) for organizational performance. Moreover, by exploring unrelated (i.e., cross-industry) diversification of BGs, we complement prior insights on the relationship between BG affiliation and international expansion (Cho et al., 2023; Gaur & Kumar, 2009), providing a more refined view of these strategies.

2 | THEORETICAL BACKGROUND

2.1 | Business groups and transaction cost rationales

Much of economic activity outside Anglo-Saxon economies is accounted for by BGs, which are federations of legally independent firms bound together through formal equity arrangements as well as informal ties (Chittoor et al., 2015; Joe & Oh, 2018; Khanna & Rivkin, 2001; Mahmood et al., 2017). There is striking heterogeneity of BGs across the world; Carney et al. (2018) identify different forms such as *chaebols* in South Korea, *grupos economicos* in Latin America, *keiretsu* in Japan, and *business houses* in India.

In addition to form, BGs also vary across a number of dimensions (Granovetter, 1995, 2005), including solidarity and identity, relationships to the state, and importantly, ownership structure and level of diversification (Khanna & Yafeh, 2007). For instance, South Korean chaebols are tightly controlled by a single chairman and feature little diversification, while Chilean BGs, in contrast, are often government-controlled and highly diversified—often tasked with state-building activities (Cuervo-Cazurra, 2006). BGs are conceptually distinct from related forms of organizational structures such as multidivisional enterprises (that are consolidated in one single entity) and alliances (that are often “looser” and more temporary in nature); instead, BGs have an “intermediate” level of binding where affiliates are connected together through personal and operational ties, with some form of controlling interest that often features ties to the state (Colli & Colpan, 2016; Granovetter, 1995).

The existence and characteristics of BGs have been explained primarily through TCE accounts (Dau et al., 2021; Granovetter, 1995; Khanna & Palepu, 1999; Yiu et al., 2007). TCE offers conceptual explanations for decisions to either purchase resources from (and outsource functions to) the market versus develop them within a firm (Williamson, 1981). Essentially, it proposes that external transaction costs—search, contracting, monitoring, coordination, etc.—as well as internal costs—monitoring, divergence, incentives, etc.—are key determinants of these “make or buy” decisions. Within the context of BGs, TCE has been used by strategy scholars to explain the group structure as an intermediate, hybrid organizational form (Granovetter, 1995, 2005) that is, in some contexts, more efficient than either markets or hierarchies.

BGs provide a structure for affiliates to benefit from reduced transaction costs by internalizing trading arrangements, pooling resources, and sharing information, while still maintaining more autonomy and flexibility than in other forms of organization such as the multidivisional enterprise (Khanna & Palepu, 1999; Yiu et al., 2007). This average reduction in search, contracting, monitoring, and coordination costs is highlighted as a key advantage of the BG structure over typical standalone firms (Williamson, 1981). Specifically, the ties between affiliate firms
<figure><img src="image_5.png" /></figure>

facilitate intra-group trading arrangements (Chang & Hong, 2000), access to internal capital markets (Belenzon & Berkovitz, 2010), knowledge spillovers (Lamin, 2013), and the development of group-level reputation (Gao et al., 2017). By reducing average transaction costs vis-à-vis the external market, prior studies suggest that BG membership creates value that can improve affiliates' performance (Khanna & Rivkin, 2001), although in specific circumstances it may also create some disadvantages (Gaur & Kumar, 2009).

## 2.2 | BG affiliation and non-financial performance

While prior studies have extensively examined how affiliation impacts financial performance (Carney et al., 2011), we complement this line of inquiry to investigate whether BG affiliation can also generate important implications in terms of non-financial performance, commonly operationalized as CSP (Napier et al., 2023; Waddock & Graves, 1997), which comprises “policies, programs, and observable outcomes as they relate to the firm’s societal relationships” (Wood, 1991). CSP is a common metric for evaluating a firm’s impact not only on stakeholders—such as employees, clients, and the local community (Brammer & Pavelin, 2006; Cornelius et al., 2008)—but also on broader “grand challenges” related to, for instance, environmental degradation, poverty, and modern slavery (Dikolli et al., 2022).² More recent work in this area has shifted the focus toward examining what organizational forms are most efficient for improving CSP (Cuypers et al., 2021; Luo & Kaul, 2019).

We build on these insights and focus on identifying how BGs may be more efficient than their standalone counterparts in improving CSP. Specifically, we suggest that some of the same mechanisms within the group that improve financial performance can also reduce the internal costs associated with improving non-financial performance, namely: (1) reputation (Gao et al., 2017; Khanna & Yafeh, 2007; Morck & Nakamura, 2005); (2) internal trading arrangements (Belenzon & Berkovitz, 2010; Chang & Hong, 2000); and (3) external access to networks and markets (Lamin, 2013). However, we suggest that these mechanisms may even be more important for improving CSP, given that BGs are more concerned than their standalone counterparts about developing and maintaining long-term legitimacy and building trust with their stakeholders (Gao et al., 2017). We proceed to explain how each of these mechanisms results in improved CSP for affiliates compared with non-affiliates.

First, group reputation serves as an important mechanism for reducing transaction costs associated with improving CSP, leading to higher non-financial performance for affiliates compared with non-affiliates. Specifically, we contend that the group’s “generalized favorability” (Lange et al., 2011)—that is, the reputation of trustworthiness, favorability, and reliability established with customers, various stakeholders, and communities over the history of the firm—spills over to other firms in the group, thereby reducing the internal costs for affiliates to develop CSP compared with non-affiliates (Bothello et al., 2023). This is borne out by anecdotal evidence: Gao et al. (2017) note, for instance, how the closure of an automobile division in India’s Mahindra Group (and the loss of 500 jobs) was not met with riots and social unrest, largely because of the trust the company had forged with the local community. Similarly, Mukherjee et al. (2018) document multiple instances of BGs in India and Korea that invest in building schools, hospitals, universities, and other facilities for the benefit of their employees, stakeholders, and communities across the entire group.

Secondly, the internal trading arrangements within BGs reduce the internal costs associated with developing CSP-enhancing competences compared with acquiring such resources from the
market. Through kinship, religious, ethnic, or caste-based networks among affiliates (Leff, 1978), as well as interlocking directorates (Granovetter, 1995), affiliate firms benefit from access to tangible and intangible group resources (Chang, 2006) unavailable to non-affiliates. While these resources have been linked to financial performance via enhanced efficiency (Chang & Hong, 2000), they also affect non-financial performance through the deployment of talented human capital (e.g., corporate social responsibility (CSR)) across the group, as well as through the sharing of CSP-enhancing best practices. As such, the internal trading arrangements for human capital and information within the group would serve to reduce the costs of developing CSP for affiliates compared with non-affiliates.

Finally, BG membership provides better access to external networks as well as information and knowledge about markets that are not equally available to non-affiliates. As Lamin (2013) identifies, social ties between affiliates lead to the acquisition of information about new markets, access to third-party referrals, and reduction of transaction costs involved with new partners. Likewise, BGs can be conceptualized as key actors in embedded group networks, which in turn facilitate strategic and economic outcomes by virtue of efficiencies in resource exchange (Chen & Jaw, 2014). Thus, these resources and capabilities can improve both the financial and non-financial performance of affiliates. For instance, many firms seeking to improve their CSP engage in cross-sector partnerships with charities and other non-profit organizations but find the selection process to be rife with conflict and information asymmetry (Ahmadsimab & Chowdhury, 2021). Given the superior access to information (more specifically, third-party referrals), BG affiliation allows for a better selection of partners for environmental and social purposes (Seitanidi & Crane, 2009) compared with standalone firms.

Taken together, these benefits offered by the group structure are likely to sustain a positive association between BG affiliation and CSP, mainly through a reduction in the internal costs required to develop CSP. We note that this is likely to reflect corporate strategy: BG scholars note, for example, that CSP variation between affiliates and non-affiliates may be “motivated by group-wide strategies and considerations … it is not uncommon for BGs to have group-wide CSR themes as building blocks for their corporate strategies” (Ararat et al., 2018: p. 914). Subsequently, our first hypothesis states that:

**Hypothesis 1.** BG affiliates will outperform unaffiliated firms in terms of CSP.

## 2.3 | The role of the external environment: the moderating effects of formal and informal institutions

Global strategy scholars postulate that firm strategies and behavior are shaped by institutional constraints that affect the costs of doing business in different countries around the world (Peng et al., 2008; Krammer, 2018). Such constraints and influences can be formal—referring to constitutions, laws, property rights, and other codified rules and regulations that govern market interactions—or informal nature—customs, traditions, codes of conduct, etc. (North, 1991; Roberts & Greenwood, 1997). Given that both types of institutions have been identified in the BG literature as shaping both group behavior and strategy (Granovetter, 1995, 2005), we turn our attention to the external organizational environment and how institutions impact the association between firms’ affiliation to a BG and their CSP efforts.
<figure><img src="image_6.png" /></figure>

The prevalence of BGs in many emerging and developing economies (Hoskisson et al., 2013) is often viewed as an organizational response to “institutional voids,” that is, contexts where market-supporting institutions such as property rights, rule-of-law, and contract enforcement mechanisms are missing or dysfunctional (Khanna & Palepu, 2000; Khanna & Rivkin, 2001; Manikandan & Ramachandran, 2015). BGs therefore offer a structural alternative to markets featuring increased transaction costs (Granovetter, 1995): specifically, through the internalization of market features, BGs act as a “safe haven” from the risks of these environments for affiliated firms (Belenzon et al., 2013; Carney et al., 2011). The lack of these formal institutions in certain countries is the predominant explanation for why BG affiliates outperform non-affiliates in terms of financial performance (Guillen, 2000; Peng et al., 2008). Effectively, the group arrangement substitutes for these missing or weak institutional arrangements (Chittoor et al., 2015; Khanna, 2000).

However, recent studies reveal that BGs persist even in contexts with well-developed institutions (Carney et al., 2018). The main reason for this persistence is their ability to develop advantages in terms of pooling internal resources (Lamin, 2013; Siegel & Choudhury, 2012), arbitraging across diversified product portfolios (Manikandan & Ramachandran, 2015), and competing successfully in different international markets (Castellacci, 2015). This ability to leverage synergies across affiliates in different industries and/or countries enables BGs to reduce transaction costs also in the context of mature, developed economies, allowing them to surpass in terms of performance standalone firms (Carney et al., 2018). In fact, recent research suggests that the BG affiliation effect on performance improves as formal legal and market institutions (particularly capital markets) develop (Chittoor et al., 2015).

We bridge this line of inquiry and theorize about how BG affiliation affects non-financial performance under various institutional contingencies. Specifically, we propose that the strength of both *formal* and *informal* institutions will strengthen the impact of BG affiliation on non-financial performance of affiliated firms. Prior research has focused on how countries with stable and structured *formal institutions* feature also regulatory frameworks (voluntary or mandatory) that target environmental, labor, and social issues, thus generating regulatory pressures and incentives to improve CSP (Ioannou & Serafeim, 2012; Matten & Moon, 2008). In such scenarios, the internal coordination mechanisms of BGs allow them to mobilize their group resources efficiently and help affiliates respond to such policy and regulatory pressures in an efficient and effective manner (Lee et al., 2016). Specifically, BGs can act as an efficient hub for exchanging know-how and tailoring affiliates' responses to the institutional requirements in place (Gao et al., 2017). As such, we propose that stronger *formal institutions* will create an environment that allows BG affiliates to further capitalize on their inherent efficiency-related advantages and outperform non-affiliates in terms of CSP (Khanna & Palepu, 2010; Commander et al., 2023).

Furthermore, stronger formal institutions will also mean less friction in terms of successfully conducting business in these environments. Prior research on firm strategy in underdeveloped institutional settings suggests that firms often need to invest in various non-market strategies such as building political connections (Krammer & Jimenez, 2020; Mahmood et al., 2017) or even engaging in bribery (Jiménez et al., 2022; Krammer, 2019), all to be able to capitalize on their existing competitive advantage. Having strong formal institutions in place means a reduction of these transaction costs of doing business, which frees up resources (human, capital, know-how, and other forms of organizational slack) to be deployed for improving non-financial outcomes such as CSP.

Given these additional benefits to affiliates operating in better regulatory environments, we hypothesize that:
**Hypothesis 2a.** Stronger formal institutions will positively moderate (i.e., strengthen) the effects of BG affiliation on CSP.

Moreover, when formal institutions are weak, informal institutions may compensate for this shortcoming by providing the necessary support for economic activities in these jurisdictions (Krammer, 2019; Nason & Bothello, 2023; Saka-Helmhout et al., 2020). These informal institutional elements comprise norms, behaviors, and attitudes of individuals (based on family, ethnic, religious, caste, professional, or other social linkages), which allow for the development of network relations with important economic functions in these markets, such as contract enforcement or reduction of informational asymmetries through alternative informal levers (e.g., trust). We, therefore, propose that better *informal institutions* will also enable BG affiliates to capitalize on their inherent advantages and have better CSP outcomes than non-affiliated firms. Several reasons support our conjecture.

First, strong informal institutions will further enhance the commitment of BG affiliates to CSP through reputational effects. Maintaining a good and credible reputation is paramount for affiliates, and tailoring their non-financial performance to their stakeholder expectations in different markets is likely to result in above-average social and corporate outcomes and a successful projection of a favorable group identity (Mukherjee et al., 2018). In environments where formal institutions are under-developed, informal ones prevail largely through the power of social networks and trust between organizations, individuals, and governments (Krammer, 2019). This issue reinforces the need for BG affiliates to align their agendas with those of the communities they serve by undertaking more CSP, in line with their superior abilities as part of a larger group of firms (Bothello et al., 2023) and the opportunity to spread these benefits throughout the group (Mukherjee et al., 2018).

Second, the reliance of informal institutions on social ties and networks will reinforce the internal TCE drivers of BG affiliates to engage in CSP in response to the environmental and social contexts in which they operate. In this way, BG affiliates will ensure both their legitimacy and boost their performance with benefits to the while group. Anecdotal accounts already support this conjecture: in East Asia, for instance, *keiretsu* and *chaebol* firms often provide social services to employees that would otherwise not be available through the welfare system (Matten & Moon, 2008), while in India, group affiliates are more likely than unaffiliated firms to locate manufacturing facilities in under-developed regions (Fisman & Khanna, 2004). Furthermore, in many collectivist countries (across Europe, Asia, South America, and Africa), BGs are seen as having an implied social contract with the state, representing national interests in exchange for state support and protection (Carney, 2008).

Given all the above, we argue that strong informal institutions will further enhance existing BG advantages toward producing superior CSP results. We therefore propose that:

**Hypothesis 2b.** Stronger informal institutions will positively moderate (i.e., strengthen) the effects of BG affiliation on CSP.

## 2.4 | The role of the internal environment: the effects of group characteristics on CSP of affiliates

While we expect BG affiliates to outperform non-affiliated firms when it comes to CSP, BGs themselves vary also significantly in terms of structure. As such, we focus on intra-group
<figure><img src="image_7.png" /></figure>

heterogeneity, and how it affects the transaction costs for affiliates seeking to improve CSP. Specifically, we identify two key dimensions of BG variance, namely *hierarchical structure*—where a BG contains multiple layers of ownership (Wang et al., 2022)—and *diversification*—where the group operates across multiple industries (Ararat et al., 2018; Yiu et al., 2007). We posit that these two group characteristics impair the CSP of affiliates for several reasons.

First, hierarchical group arrangements will make it more costly and difficult for BG affiliates to improve CSP. Hierarchical structures involve affiliates being organized into a “pyramid” rather than a “web” (Dau et al., 2021), with the ultimate goal of increasing control rather than improving exchanges within the group (Altomonte & Rungi, 2013; Belenzon et al., 2019). Thus, when power is hierarchically concentrated (Bae et al., 2002; Morck et al., 2005), decision-making and resource exchange across the group are impeded, introducing friction to internal trading arrangements and access to external markets. Hierarchy, in other words, introduces more transaction costs for lower-echelon affiliates seeking to improve their CSP.

Second, hierarchical group arrangements will also make CSP more expensive and less desirable by reducing the overall emphasis on organizational reputation. Prior research on the effects of hierarchy on groups suggests that as concentration increases toward the top of the group structure, controlling interests become less concerned with reputation (Delgado-García et al., 2010; Rees & Rodionova, 2014) and more inclined toward “private corruption” (Rodriguez et al., 2006). This shift in preferences for more hierarchical BGs results in both making CSP activities of affiliates less supported and financially feasible (Ghoul et al., 2017; Webb et al., 2014). Subsequently, affiliates in more hierarchical groups would be less likely to improve their reputation by undertaking more CSP efforts than those in “flatter” groups.

Finally, more hierarchical structures exacerbate informational asymmetries and reduce network benefits in relation to CSP activities. The concentration of power within BGs, particularly in extreme situations (e.g., one or two apex firms dominating the group), results in a strong focus on priorities for the collection and usage of information that is salient for the needs and strategies of those firms and commonly at the expense of those toward the bottom of the hierarchy (Kandel et al., 2019). The benefits of networks in relation to CSP improvements (e.g., knowledge exchange, efficiency spillovers, etc.) are best realized by firms that share as many as possible peer connections in these groups (Altomonte & Rungi, 2013). In turn, hierarchical structures reduce drastically these benefits, making it more costly and difficult to transfer knowledge between affiliates toward improving their CSP (Belenzon et al., 2019).

Given the above rationales, we hypothesize that:

**Hypothesis 3a.** The degree of hierarchy of the BG will have a negative effect on the CSP of affiliates.

Apart from hierarchy, another important strategic consideration for BGs is the level of diversification pursued by the organization (Manikandan & Ramachandran, 2015; Ramanujam & Varadarajan, 1989; Yiu et al., 2007). While prior studies have identified that related and unrelated diversification is, in general, associated with improved CSP (Kang, 2013), this relationship may not hold within the context of BGs. Carney et al. (2011), in their meta-analysis of 141 BG studies, find that high levels of group diversification are negatively associated with financial performance. They propose that greater diversification may be indicative of empire-building or “tunneling” behaviors, where controlling interests take advantage of information asymmetry to appropriate cash flows from minority shareholders (Mitton, 2002; Morck & Yeung, 2003; Su & Tan, 2018). From a TCE perspective, this implies that affiliation across rather
than within industries—reflecting a BG's *unrelated* diversification—is associated with greater costs around search and information, as well as coordination and integration. Building upon this logic, we expect that BG diversification will reduce the non-financial performance of affiliates for two main reasons.

First, greater inter-industry differences from unrelated diversification will make the transfer of resources (particularly knowledge, information, and human resources) from one affiliate to another more expensive (Chang & Hong, 2000; Krammer, 2016). This is especially pertinent in the case of CSP best practices, which may not be transferrable when firms are not in the same or even proximate industries. Relatedly, diversification is documented to create information asymmetries (Cahan et al., 2005), thereby impairing transparency that would otherwise improve CSP (Cho et al., 2015). As such, the costs of developing CSP internally are likely to be higher for affiliates in groups featuring unrelated diversification compared with those that have related diversification.

In addition, unrelated diversification is usually driven by the self-serving financial rationales of the controlling firms (Claessens et al., 2002; Su & Tan, 2018), which in turn will reduce the mandate to develop CSP. Unrelated diversification involves expansion into a new market, industry, or technological domain (Hoskisson et al., 2005; Bae et al., 2011; Krammer, 2016), which, in standalone firms, represents a common strategy for risk-mitigation. Within BGs, however, unrelated diversification may instead be associated with self-dealing, tunneling, and political rent-seeking (Ararat et al., 2018; Claessens et al., 2002). In this sense, expansions into new markets or industries may be pursued as means to fortify controlling interests within the group and satisfy “empire-building” (Khanna & Yafeh, 2007) rather than a focus on non-financial aims like CSP. This extra-financial objective implies that controlling interests will be less likely to fund or even support the social and environmental performance of affiliates (Su & Tan, 2018). Subsequently, extensive diversification will shift the focus toward financial objectives, resulting in lower CSP affiliate engagement than otherwise.

Summing up these ideas, we propose that:

**Hypothesis 3b.** The degree of diversification of the BG will have a negative effect on the CSP of affiliates.

# 3 | METHODS

## 3.1 | Data and sample

We draw on several sources to construct our dataset, starting from the full universe of listed firms³ with available environmental and social performance scores included in the Thomson Reuters-Refinitiv ESG database (formerly known as Asset 4). We collect an initial sample of 32,242 firm-year observations (4631 firms) between the years 2003 and 2016. Our sample period ends in the year 2016, which is a significant point in terms of social and environmental reporting.⁴ We further proceed to obtain information regarding firms' BG affiliation, using data on ultimate owners and subsidiaries provided by the Orbis database from Bureau van Dijk (BvD). We collect firm-level stock market data from DataStream and accounting data from Worldscope. Furthermore, we employ country-level data from the World Economic Forum-COMPETITIVENESS Report, World Bank's Worldwide Governance Indicators (used in Kaufmann et al., 2009), World Federation of Exchanges, Botero et al. (2004), Hofstede (2001), La Porta
<figure><img src="image_8.png" /></figure>

et al. (2006).⁵ Table A1 in Appendix A provides definitions of our variables together with details on the sources used to construct our dataset. After eliminating all missing firm-specific, our final sample of affiliated and non-affiliated firms consists of 29,886 firm-year observations for 4368 firms from 43 countries between the years 2003 and 2016.⁶

## 3.2 | Dependent variable

As mentioned in previous studies, the construction of a measure that would gage the full meaning of CSP comes with challenges (Ioannou & Serafeim, 2012; Ringov & Zollo, 2007). While the need for a multidimensional measure of CSP is highlighted by Waddock and Graves (1997), the relative importance of each dimension in the overall construct is not widely agreed upon in the literature. We operationalize non-financial performance using the dimensions of environmental and social performance scores, assigning equal weights to both, in line with Waldman et al. (2006) and Ioannou and Serafeim (2012).

Our scores are derived from Refinitiv ESG, as the most common source of data for academic scholars from various disciplines who aim to construct reliable firm-level measures of CSP (e.g., El Ghoul et al., 2017; Ioannou & Serafeim, 2012; Kölbel et al., 2017; Rees & Rodionova, 2014). A company's overall CSP is based upon a commitment to a series of best practices along select Environmental and Social metrics: for the Environmental dimension, this entails evaluating a company's commitment to—and effectiveness in—developing products and services that have a minimal ecological impact, as well as its minimization of ecological impact from production and operational processes (Shrivastava, 1995). The social dimension, on the other hand, reflects a firm's efforts and achievements in fostering reputation and good stakeholder relationships, consisting of responsibility to customers through the production of quality goods and services but also to the wider community (local, national, or global) through ethical conduct (e.g., avoiding bribery and corruption) and acts of citizenship (e.g., donations or volunteering). The social dimension is also heavily contingent upon labor relations, measured by policies around job benefits, health and safety, diversity and opportunity, and training and development. A detailed overview of the environmental and social constructs in Refinitiv ESG scores and their use in academic studies has been reviewed in the study of Lys et al. (2015) and de Villiers et al. (2022). Following their recommendations, our resulting composite dependent variable is measured yearly at the firm-level and its score ranges from 1 to 100.

Within the ESG framework, each pillar plays a distinct role. While the Environmental (E) and Social (S) pillars focus on a company's impact on the environment and society, respectively, the Governance (G) pillar stands out as a distinct dimension that is internally oriented (Trahan & Jantz, 2023). Thus, unlike the E and S pillars, which assess specific practices and impacts and reflect the overall non-financial performance of a firm, the G pillar emphasizes the internal organizational framework, including certain mechanisms, policies, and processes that guide corporate decision-making and behavior (Crifo et al., 2019). Following Ioannou and Serafeim (2012), Odziemkowska and Henisz (2021), Lys et al. (2015), and Desender and Epure (2021), we choose not to focus on the “G” component in the construction of our dependent variable (DV), since it mostly represents actions directed toward the board of directors or management, making it structurally different from the “E” and “S” pillars, which cater to greater societal concerns.
## 3.3 | Independent variables

### 3.3.1 | BG affiliation

We capture *BG Affiliation* with a dummy variable that takes the value of 1 if the firm is affiliated with a BG and 0 otherwise. We determine affiliation to a BG by analyzing ownership data for all firms from the BvD Orbis database, a prominent source of ownership data (e.g., Belenzon & Berkovitz, 2010; Bena & Ortiz-Molina, 2013; Bothello et al., 2023; Cucculelli & Marchionne, 2012). In line with Masulis et al. (2011), we start the identification of BGs by differentiating between widely held and controlled firms. Moreover, we identify the ultimate owner to determine the controlling firms within the BG. Following Bothello et al. (2023), we impose a filter of at least 25% of a firm's voting rights to establish the controlling shareholder. Further, we check if the shareholder that complies with this restriction—and has the highest controlling share—is independent. When independent, the shareholder is considered the ultimate owner. Otherwise, we continue searching until an ultimate owner is identified. Following Cucculelli and Marchionne (2012), we identify the ultimate owner by analyzing all publicly listed firms in the world with a BvD independence indicator and excluding firms with less than 25% direct or indirect ownership.⁷

### 3.3.2 | Formal and informal institutions

We construct two indices that seek to capture *formal* and *informal* institutional aspects that are salient for firms' non-financial performance (Helmke & Rosenbluth, 2009). Specifically, to gauge the strength of *formal institutions* that are relevant for CSP, we employ two variables (i.e., *Ethical Behavior* and *Protect Minority Shareholders*) from the Global Competitiveness Index (GCI) from the World Economic Forum, which have been employed by prior studies in this literature (Golesorkhi et al., 2019; Ng et al., 2015; Seyoum, 2009; Yiu & Makino, 2002). The first component, *Ethical Behavior*, captures the level to which firms have ethical behavior in interactions with public officials, politicians, and other enterprises, on an increasing scale from 1 to 7. *Protect Minority Shareholders* is defined as the extent to which the law offers protection of minority shareholders' interests in a specific country, increasing on a scale of 1 to 7. We perform factor analysis to capture these two dimensions in a single measure of formal institutions (Table A2 in Appendix A).

For *informal institutions*, we focus on the societal norms in a country as captured by the degree of democracy as well as the importance of society/community for individuals (Kaufmann et al., 2018; Pathak & Muralidharan, 2016). In line with prior studies in this area, we expect that in societies that are both very democratic and exhibit strong social values, the informal pressures to deliver non-financial performance will be greater (Silver & Dowley, 2000). Empirically, we measure these dimensions using data from the World Value Survey, which has often been employed to capture informal institutional aspects (Muralidharan & Pathak, 2017; Tolmie et al., 2020). Specifically, the *Level of Democracy* (V114-"How democratically is this country being governed today?", on a 10-point scale) and *Importance of Society* (V74-"It is important to this person to do something for the good of society," on a scale of 1–6). Similarly to the formal pillar, we perform factor analysis on these two variables to obtain our composite measure of informal institutions (Table A3 in Appendix A).⁸
<figure><img src="image_9.png" /></figure>

### 3.3.3 | BG diversification and BG hierarchy

Finally, we follow Khanna and Yafeh (2005) and operationalize *BG Hierarchy* as the number of formal ownership relations between the ultimate owner and subsidiaries, and *BG Diversification* represents the number of *unrelated* industries where affiliated firms within BG operate.

*BG Hierarchy* is a BG-level construct that measures the total number of levels of all listed and unlisted subsidiaries within BG. For example, we take the case of a BG that has two subsidiaries, Companies A and B. Company A has one subsidiary, X. Company B has two subsidiaries, W and V, with W itself having one subsidiary. Considering the indirect shareholdings, the BG is assigned a level of *BG Hierarchy* of 3, representing the maximum level of subsidiaries within the group.⁹ For illustrative purposes, please refer to the example of TAV Havalimanlari Holding A.S. (level of hierarchy is 5) listed in Table A4 (Appendix A). *BG Diversification* is measured as the total number of two-digit standard industrial classification codes in which the affiliated firms within BG operate. For example, if a given BG has 10 subsidiaries operating in six unrelated industries, then the *BG Diversification* receives a value of 6.

### 3.4 | Control variables

To minimize the potential for confounding and alternative explanations, we employ a large battery of controls both at the country and firm-level. Following Khanna and Yafeh (2005) and Ioannou and Serafeim (2012), at the country level, we use *Competition, Anti-self-dealing index, Control of corruption, Left/center ideology, Union density, Labor market efficiency, Country debt over assets, SRI index, Power distance index, Individualism, Quality of infrastructure, Balance of trade, Trade, and Market size* to control for the influence of political, educational, labor, financial, economic, and cultural systems on firms' CSP.

We complement these country controls with a battery of firm-level controls which includes *Firm size, Return on assets (ROA), Leverage, Volatility, Market-to-book value, Closely held shares, Foreign shareholding, Institutional shareholding, Reputation monitoring, and CSR award* (for definitions see Table A1 in Appendix A). We winsorize all continuous variables used throughout our tests at the 1% and 99% levels to mitigate the effect of potential outliers. Further, for ease of interpretation, we standardize all continuous variables with zero mean and unit variance.

### 3.5 | Empirical approach: Propensity score matching

As illustrated in Table 1, affiliated and non-affiliated firms significantly differ from each other in various country- and firm-specific characteristics aspects. To ensure that these differences do not bias our results, we employ a propensity score matching (PSM) approach (Rosenbaum & Rubin, 1983) and match each BG-affiliated firm (treatment sample) with a non-affiliated firm (control sample) of similar characteristics. This matching reduces significantly the potential confounding impact of the differences in the observable characteristics between the two groups. We first compute propensity scores for each firm based on the observable firm-specific characteristics associated with BG affiliation. We further match affiliated and non-affiliated firms based on their propensity scores by using the nearest neighbor matching approach (within a caliper of 0.1). The matching process results in 9878 firm-years (4939 matched pairs) for BG affiliation analysis (Table A5, Appendix A). After we match the firms on a set of observable
<table><caption>TABLE 1 Summary statistics and univariate tests for subsamples (business groups [BG] affiliates vs. non-affiliated firms).</caption><thead><tr><th rowspan="3">Variables</th><th colspan="4">Full sample<br>(N = 29,886)</th><th colspan="2">BG<br>(N = 5924)</th><th colspan="2">Non-BG<br>(N = 23,962)</th><th colspan="3">Univariate test</th></tr><tr><th>Mean</th><th>Standard<br>deviation</th><th>Min</th><th>Max</th><th>Mean (A)</th><th>Standard<br>deviation</th><th>Mean (B)</th><th>Standard<br>deviation</th><th>Difference<br>(A - B)</th><th>t-Value</th><th>Significance</th></tr></thead><tbody><tr><td>CSP</td><td>55.07</td><td>29.15</td><td>5.93</td><td>98.1</td><td>56.46</td><td>29.09</td><td>54.73</td><td>29.15</td><td>1.730</td><td>4.114</td><td>***</td></tr><tr><td>BG Affiliation</td><td>0.198</td><td>0.399</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>-</td><td>-</td><td>-</td></tr><tr><td>BG Hierarchy</td><td>-</td><td>-</td><td>-</td><td>-</td><td>1.692</td><td>0.854</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>BG Diversification</td><td>-</td><td>-</td><td>-</td><td>-</td><td>1.152</td><td>0.670</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Formal institutions</td><td>0.0031</td><td>0.977</td><td>-3.12</td><td>2.03</td><td>-0.237</td><td>1.274</td><td>0.0624</td><td>0.879</td><td>-0.299</td><td>-17.091</td><td>***</td></tr><tr><td>Informal institutions</td><td>0.014</td><td>0.98</td><td>-3.31</td><td>1.31</td><td>-0.28</td><td>1.329</td><td>0.0867</td><td>0.857</td><td>-0.367</td><td>-20.238</td><td>***</td></tr><tr><td>Firm size</td><td>15.82</td><td>1.67</td><td>4.127</td><td>22</td><td>15.86</td><td>1.564</td><td>15.81</td><td>1.695</td><td>0.050</td><td>2.398</td><td>***</td></tr><tr><td>Return on assets (ROA)</td><td>5.419</td><td>7.959</td><td>-29.1</td><td>31.9</td><td>5.965</td><td>7.858</td><td>5.284</td><td>7.978</td><td>0.681</td><td>5.958</td><td>***</td></tr><tr><td>Leverage</td><td>25.1</td><td>18</td><td>0</td><td>79.8</td><td>24.92</td><td>17.6</td><td>25.14</td><td>18.1</td><td>-0.220</td><td>-0.860</td><td></td></tr><tr><td>Volatility</td><td>27.94</td><td>9.295</td><td>12.5</td><td>55.9</td><td>28.01</td><td>9.223</td><td>27.93</td><td>9.313</td><td>0.080</td><td>0.562</td><td></td></tr><tr><td>Market-to-book value</td><td>2.575</td><td>3.02</td><td>-3.94</td><td>20.6</td><td>2.598</td><td>3.162</td><td>2.569</td><td>2.983</td><td>0.029</td><td>0.631</td><td></td></tr><tr><td>Closely held shares</td><td>23.01</td><td>23.66</td><td>0.02</td><td>86.4</td><td>45.99</td><td>23.6</td><td>17.32</td><td>19.94</td><td>28.670</td><td>86.209</td><td>***</td></tr><tr><td>Foreign shareholding</td><td>5.872</td><td>14.33</td><td>0</td><td>97</td><td>12.24</td><td>21.99</td><td>4.299</td><td>11.14</td><td>7.941</td><td>26.939</td><td>***</td></tr><tr><td>Institutional<br>shareholding</td><td>5.771</td><td>8.444</td><td>0</td><td>80</td><td>3.811</td><td>7.924</td><td>6.255</td><td>8.498</td><td>-2.444</td><td>-20.945</td><td>***</td></tr><tr><td>Reputation monitoring</td><td>0.243</td><td>0.429</td><td>0</td><td>1</td><td>0.283</td><td>0.45</td><td>0.234</td><td>0.423</td><td>0.049</td><td>7.575</td><td>***</td></tr><tr><td>CSR award</td><td>0.435</td><td>0.496</td><td>0</td><td>1</td><td>0.462</td><td>0.499</td><td>0.428</td><td>0.495</td><td>0.034</td><td>4.650</td><td>***</td></tr><tr><td>Competition</td><td>4.975</td><td>0.382</td><td>3.647</td><td>5.89</td><td>4.928</td><td>0.537</td><td>4.986</td><td>0.332</td><td>-0.058</td><td>-8.044</td><td>***</td></tr><tr><td>Anti-self-dealing index</td><td>0.623</td><td>0.198</td><td>0.209</td><td>1</td><td>0.615</td><td>0.242</td><td>0.625</td><td>0.185</td><td>-0.010</td><td>-3.065</td><td>***</td></tr><tr><td>Left/center ideology</td><td>0.309</td><td>0.243</td><td>0</td><td>1</td><td>0.352</td><td>0.299</td><td>0.298</td><td>0.226</td><td>0.054</td><td>12.916</td><td>***</td></tr><tr><td>Union density</td><td>0.245</td><td>0.157</td><td>0.03</td><td>0.9</td><td>0.266</td><td>0.175</td><td>0.24</td><td>0.152</td><td>0.026</td><td>10.520</td><td>***</td></tr></tbody></table>
<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="3">Variables</th><th colspan="4">Full sample</th><th colspan="4">BG</th><th colspan="4">Non-BG</th><th colspan="4">Univariate test</th></tr><tr><th colspan="4">(N = 29,886)</th><th colspan="4">(N = 5924)</th><th colspan="4">(N = 23,962)</th><th colspan="4">(N = 23,962)</th></tr><tr><th>Mean</th><th>Standard deviation</th><th>Min</th><th>Max</th><th>Mean (A)</th><th>Standard deviation</th><th>Mean (B)</th><th>Standard deviation</th><th>Difference (A - B)</th><th>t-Value</th><th>Significance</th><th>Difference (A - B)</th><th>t-Value</th><th>Significance</th></tr></thead><tbody><tr><td>Labor market efficiency</td><td>5.059</td><td>0.57</td><td>3.592</td><td>5.86</td><td>4.801</td><td>0.647</td><td>5.122</td><td>0.531</td><td>-0.321</td><td>-35.370</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Country debt over assets</td><td>0.259</td><td>0.078</td><td>0.129</td><td>0.43</td><td>0.242</td><td>0.075</td><td>0.264</td><td>0.0778</td><td>-0.022</td><td>-19.981</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Power distance index</td><td>46.65</td><td>14.21</td><td>18</td><td>93</td><td>54.3</td><td>18.14</td><td>44.75</td><td>12.35</td><td>9.550</td><td>38.368</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SRI index</td><td>0.75</td><td>0.433</td><td>0</td><td>1</td><td>0.586</td><td>0.493</td><td>0.79</td><td>0.407</td><td>-0.204</td><td>-29.465</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Individualism</td><td>69.74</td><td>24.59</td><td>17</td><td>91</td><td>57.06</td><td>26.02</td><td>72.87</td><td>23.18</td><td>-15.810</td><td>-42.763</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Quality of infrastructure</td><td>5.622</td><td>0.675</td><td>3.357</td><td>6.69</td><td>5.429</td><td>0.93</td><td>5.67</td><td>0.585</td><td>-0.241</td><td>-19.045</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Balance of trade</td><td>-0.687</td><td>4.982</td><td>-9.52</td><td>19.1</td><td>0.765</td><td>5.892</td><td>-1.046</td><td>4.661</td><td>1.811</td><td>22.022</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Trade</td><td>71.44</td><td>86.04</td><td>24.7</td><td>468</td><td>114.9</td><td>130.4</td><td>60.69</td><td>66.67</td><td>54.210</td><td>31.019</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Market size</td><td>5.898</td><td>0.841</td><td>4.153</td><td>6.94</td><td>5.47</td><td>0.754</td><td>6.004</td><td>0.828</td><td>-0.534</td><td>-47.815</td><td>***</td><td></td><td></td><td></td><td></td><td></td></tr></tbody><tfoot><tr><td colspan="18">Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. A detailed description of all variables is provided in Table A1 in Appendix A.</td></tr><tr><td colspan="18">Abbreviation: CSP, corporate social performance; SRI, Socially Responsible stock market Index.</td></tr></tfoot></table>
characteristics, the differences between the two groups become largely insignificant (please see
Panel B of Table A5). This matched subsample of firms will be then used in all our econometric
testing.

4 | RESULTS

**4.1** | **Descriptive statistics**

Table 1 reports summary statistics for all variables used in our analysis, for the full sample (first column) and for the decomposed samples by BG affiliation (second and third columns). Additionally, in the fourth column of Table 1, we present univariate test statistics for mean differences in variables of affiliated and non-affiliated firms. Overall, the values in Table 1 are in line with previous literature (El Ghoul et al., 2016; Ioannou & Serafeim, 2012). In the full sample, the mean value of the CSP is 55.07. When the sample is decomposed by BG affiliation, CSP is significantly higher for affiliated firms relative to non-affiliated firms. Furthermore, 19.8% of our sample is composed of affiliated firms. Within affiliated firms, the average value of the BG Hierarchy is 1.152, indicating an average subsidiary level of 3.¹⁰ The average value of BG Diversification is 1.692, indicating that the affiliated firms are operating on average in five different industries.¹¹

Table 2 presents the correlation matrix, where CSP and BG characteristics have significant correlations with all country- and firm-specific variables. None of these correlations are above 0.8, which excludes a possible multicollinearity problem in our analysis. We further confirm this by testing the variance inflation factor (VIF) in the regression analyses for each variable and the mean VIF is 2.50.

**4.2** | **Main regression results**

Using the matched sample, we regress our measure of CSP on BG affiliation, after controlling for country and firm-specific variables (Hypothesis 1). All regressions employ robust standard errors and industry- and year-fixed effects. We find that the coefficient of our variable of interest, *BG Affiliation*, is positive and significant in Table 3, Model 2 ($\beta$ = .043, *p* < .01), which supports our H1.¹² In terms of economic significance, the BG affiliation increases CSP by 1.25 (we multiply the coefficient of *BG Affiliation* [0.043] by the standard deviation of CSP [29.15]), which corresponds to a 2.27% increase—that is, we divide the increase in CSP (1.25) by the unstandardized mean of CSP (55.07).

Further, we test the potential moderating effects of formal and informal institutional settings on the CSP performance of BG versus non-BG affiliates. Given our focus on testing independently the effects of the two types of institutions considered and their relative relatedness (correlation 0.38), which may entail multicollinearity, we chose to estimate these interactions separately as a reflection of our H2a and H2b. The results of Models 3 and 4 indicate positive and significant coefficients for the interaction term of *formal* and *informal* institutions ($\beta$ = .047, *p* < .01 and $\beta$ = .031, *p* < .01), confirming our theoretical conjectures that stronger institutions reinforce (strengthen) the positive effect of BG affiliation when it comes to non-financial (i.e., CSP) performance. To better understand the magnitude of these effects, we have
<table><caption>TABLE 2 Pairwise correlations.</caption><thead><tr><th>Variables</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th><th>(13)</th></tr></thead><tbody><tr><td>(1) CSP</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(2) BG Affiliation</td><td>0.02***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(3) BG Hierarchy</td><td>0.03**</td><td>0.03**</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(4) BG Diversification</td><td>0.14***</td><td>0.03**</td><td>0.67***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(5) Formal institutions</td><td>-0.04***</td><td>-0.12***</td><td>-0.11***</td><td>-0.20***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(6) Informal institutions</td><td>-0.12**</td><td>-0.15***</td><td>-0.21***</td><td>-0.26**</td><td>0.33**</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(7) Firm size</td><td>0.37***</td><td>0.01**</td><td>0.24***</td><td>0.29***</td><td>-0.16***</td><td>-0.11***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(8) Return on assets (ROA)</td><td>0.04***</td><td>0.03***</td><td>-0.04***</td><td>-0.01</td><td>-0.01**</td><td>0.02***</td><td>-0.08***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(9) Leverage</td><td>0.04***</td><td>0.00</td><td>0.03**</td><td>-0.03**</td><td>-0.09***</td><td>-0.06***</td><td>0.12***</td><td>-0.12***</td><td>1.00</td><td></td><td></td><td></td><td></td></tr><tr><td>(10) Volatility</td><td>-0.21***</td><td>0.00</td><td>-0.08***</td><td>-0.07***</td><td>-0.01**</td><td>0.02***</td><td>-0.30***</td><td>-0.25***</td><td>0.00</td><td>1.00</td><td></td><td></td><td></td></tr><tr><td>(11) Market-to-book value</td><td>0.02**</td><td>0.00</td><td>-0.05***</td><td>-0.02</td><td>-0.02***</td><td>0.02***</td><td>-0.15***</td><td>0.32***</td><td>0.00</td><td>-0.08***</td><td>1.00</td><td></td><td></td></tr><tr><td>(12) Closely held shares</td><td>-0.05***</td><td>0.48***</td><td>0.01</td><td>0.10***</td><td>-0.22***</td><td>-0.23***</td><td>-0.04***</td><td>0.01**</td><td>-0.02***</td><td>0.10***</td><td>-0.02***</td><td>1.00</td><td></td></tr><tr><td>(13) Foreign shareholding</td><td>-0.03***</td><td>0.22***</td><td>-0.02*</td><td>-0.04***</td><td>-0.02***</td><td>-0.06***</td><td>-0.06***</td><td>0.01***</td><td>-0.01</td><td>0.12***</td><td>0.02***</td><td>0.35***</td><td>1.00</td></tr><tr><td>(14) Institutional shareholding</td><td>-0.10***</td><td>-0.12***</td><td>-0.07***</td><td>-0.14***</td><td>0.08***</td><td>0.10***</td><td>-0.20***</td><td>0.02***</td><td>-0.01</td><td>0.07***</td><td>0.07***</td><td>-0.21***</td><td>0.01</td></tr><tr><td>(15) Reputation monitoring</td><td>0.49***</td><td>0.05***</td><td>0.07***</td><td>0.10***</td><td>-0.08***</td><td>-0.09***</td><td>0.21***</td><td>0.01*</td><td>0.02***</td><td>-0.11***</td><td>0.01**</td><td>-0.02***</td><td>0.01</td></tr><tr><td>(16) CSR award</td><td>0.52***</td><td>0.03***</td><td>0.01</td><td>0.06***</td><td>-0.08***</td><td>-0.06***</td><td>0.31***</td><td>0.04***</td><td>0.03***</td><td>-0.14***</td><td>0.01</td><td>0.00</td><td>0.00</td></tr><tr><td>(17) Competition</td><td>-0.10***</td><td>-0.06***</td><td>-0.11***</td><td>-0.23***</td><td>0.65***</td><td>0.34***</td><td>-0.11***</td><td>0.05***</td><td>-0.06***</td><td>-0.06***</td><td>0.05***</td><td>-0.15***</td><td>0.09***</td></tr><tr><td>(18) Anti-self-dealing index</td><td>-0.15***</td><td>-0.02***</td><td>-0.10***</td><td>-0.26***</td><td>0.29***</td><td>0.18***</td><td>-0.20***</td><td>0.06***</td><td>-0.04***</td><td>0.04***</td><td>0.06***</td><td>-0.11***</td><td>0.11***</td></tr><tr><td>(19) Left/center ideology</td><td>0.00</td><td>0.09***</td><td>0.01</td><td>0.09***</td><td>-0.09***</td><td>-0.37***</td><td>-0.04***</td><td>0.01</td><td>0.02***</td><td>0.09***</td><td>0.05***</td><td>0.08***</td><td>0.06***</td></tr><tr><td>(20) Union density</td><td>0.09***</td><td>0.07***</td><td>0.07***</td><td>0.16***</td><td>0.35***</td><td>-0.05***</td><td>-0.10***</td><td>-0.01*</td><td>-0.02***</td><td>0.04***</td><td>-0.05***</td><td>0.07***</td><td>0.09***</td></tr><tr><td>(21) Labor market efficiency</td><td>-0.17***</td><td>-0.22***</td><td>-0.12***</td><td>-0.27***</td><td>0.51***</td><td>0.44***</td><td>-0.01*</td><td>0.09***</td><td>-0.04***</td><td>-0.04***</td><td>0.08***</td><td>-0.35***</td><td>-0.09***</td></tr></tbody></table>

(Continues)
<table><caption>TABLE 2 (Continued)</caption><thead><tr><th>Variables</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th><th>(13)</th></tr></thead><tbody><tr><td>(22) Country debt over assets</td><td>-0.03***</td><td>-0.11***</td><td>0.02*</td><td>-0.05***</td><td>-0.18***</td><td>0.05***</td><td>0.10**</td><td>0.08***</td><td>0.11***</td><td>-0.03***</td><td>0.12***</td><td>-0.17***</td><td>-0.10***</td></tr><tr><td>(23) Power distance index</td><td>0.02***</td><td>0.27***</td><td>0.05***</td><td>0.13***</td><td>-0.51***</td><td>-0.31***</td><td>0.16***</td><td>0.00</td><td>0.02***</td><td>0.03***</td><td>-0.07***</td><td>0.45***</td><td>0.19***</td></tr><tr><td>(24) SRI index</td><td>0.15***</td><td>-0.19***</td><td>0.04***</td><td>0.10***</td><td>-0.10***</td><td>0.03***</td><td>0.18***</td><td>0.07***</td><td>0.02***</td><td>-0.12***</td><td>0.06***</td><td>-0.21***</td><td>-0.19***</td></tr><tr><td>(25) Individualism</td><td>-0.04***</td><td>-0.26***</td><td>0.01</td><td>-0.09***</td><td>0.28***</td><td>0.07***</td><td>-0.10***</td><td>0.02***</td><td>0.01*</td><td>-0.05***</td><td>0.12***</td><td>-0.49***</td><td>-0.19***</td></tr><tr><td>(26) Quality of infrastructure</td><td>-0.01**</td><td>-0.14***</td><td>-0.10***</td><td>-0.16***</td><td>0.53***</td><td>0.24***</td><td>0.09***</td><td>0.00</td><td>-0.06***</td><td>-0.09***</td><td>-0.02***</td><td>-0.17***</td><td>-0.03***</td></tr><tr><td>(27) Balance of trade</td><td>0.01**</td><td>0.14***</td><td>0.06***</td><td>0.09***</td><td>0.13***</td><td>-0.09***</td><td>0.00</td><td>-0.01</td><td>-0.04***</td><td>0.04***</td><td>-0.06***</td><td>0.23***</td><td>0.10***</td></tr><tr><td>(28) Trade</td><td>-0.06***</td><td>0.25***</td><td>-0.07***</td><td>-0.10***</td><td>0.17***</td><td>0.05***</td><td>-0.01*</td><td>0.04***</td><td>-0.03***</td><td>0.06***</td><td>-0.04***</td><td>0.33***</td><td>0.36***</td></tr><tr><td>(29) Market size</td><td>-0.08***</td><td>-0.25***</td><td>-0.03**</td><td>-0.09***</td><td>-0.22***</td><td>0.17***</td><td>0.16***</td><td>0.03***</td><td>0.04***</td><td>-0.06***</td><td>0.08***</td><td>-0.35***</td><td>-0.24***</td></tr><tr><td>Variables</td><td>(14)</td><td>(15)</td><td>(16)</td><td>(17)</td><td>(18)</td><td>(19)</td><td>(20)</td><td>(21)</td><td>(22)</td><td>(23)</td><td>(24)</td><td>(25)</td><td>(26)</td><td>(27)</td></tr><tr><td>(14) Institutional shareholding</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(15) Reputation monitoring</td><td>-0.06***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(16) CSR award</td><td>-0.09***</td><td>0.29***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(17) Competition</td><td>0.11***</td><td>-0.10***</td><td>-0.01</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(18) Anti-self-dealing index</td><td>0.19***</td><td>-0.02***</td><td>0.00</td><td>0.52***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(19) Left/center ideology</td><td>0.02***</td><td>0.03***</td><td>0.00</td><td>-0.14***</td><td>-0.11***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(20) Union density</td><td>-0.09***</td><td>0.05***</td><td>-0.05***</td><td>0.10***</td><td>-0.18***</td><td>0.11***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(21) Labor market efficiency</td><td>0.18***</td><td>-0.16***</td><td>-0.03***</td><td>0.93***</td><td>0.44***</td><td>-0.13***</td><td>-0.17***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(22) Country equity over assets</td><td>0.18***</td><td>-0.06***</td><td>-0.01</td><td>-0.15***</td><td>-0.18***</td><td>0.11***</td><td>-0.03***</td><td>0.19***</td><td>1.00</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>TABLE 2 (Continued)</caption><thead><tr><th>Variables</th><th>(14)</th><th>(15)</th><th>(16)</th><th>(17)</th><th>(18)</th><th>(19)</th><th>(20)</th><th>(21)</th><th>(22)</th><th>(23)</th><th>(24)</th><th>(25)</th><th>(26)</th><th>(27)</th></tr></thead><tbody><tr><td>(23) Power distance index</td><td>-0.24***</td><td>0.03***</td><td>0.11***</td><td>-0.32***</td><td>-0.12***</td><td>-0.08***</td><td>-0.28***</td><td>-0.43***</td><td>-0.28***</td><td>1.00</td><td></td><td></td><td></td><td></td></tr><tr><td>(24) SRI index</td><td>0.11***</td><td>0.04***</td><td>0.04***</td><td>-0.18***</td><td>-0.23***</td><td>-0.15***</td><td>-0.26***</td><td>0.12***</td><td>0.29***</td><td>-0.08***</td><td>1.00</td><td></td><td></td><td></td></tr><tr><td>(25) Individualism</td><td>0.32***</td><td>-0.03***</td><td>-0.09***</td><td>0.18***</td><td>0.21***</td><td>0.17***</td><td>-0.07***</td><td>0.43***</td><td>0.42***</td><td>-0.76***</td><td>0.23***</td><td>1.00</td><td></td><td></td></tr><tr><td>(26) Quality of infrastructure</td><td>0.00</td><td>-0.14***</td><td>0.00</td><td>0.59***</td><td>-0.05***</td><td>-0.16***</td><td>-0.02***</td><td>0.56***</td><td>-0.02***</td><td>-0.22***</td><td>0.20***</td><td>0.08***</td><td>1.00</td><td></td></tr><tr><td>(27) Balance of trade</td><td>-0.19***</td><td>0.00</td><td>0.02***</td><td>0.21***</td><td>-0.17***</td><td>-0.02***</td><td>0.46***</td><td>-0.06***</td><td>-0.25***</td><td>0.14***</td><td>-0.34***</td><td>-0.43***</td><td>0.16***</td><td>1.00</td></tr><tr><td>(28) Trade</td><td>-0.13***</td><td>0.00</td><td>0.07***</td><td>0.52***</td><td>0.30***</td><td>-0.09***</td><td>0.15***</td><td>0.10***</td><td>-0.26***</td><td>0.37***</td><td>-0.44***</td><td>-0.50***</td><td>0.25***</td><td>0.47***</td><td>1.00</td></tr><tr><td>(29) Market size</td><td>0.19***</td><td>-0.10***</td><td>-0.01*</td><td>-0.15***</td><td>0.03***</td><td>-0.17***</td><td>-0.60***</td><td>0.39***</td><td>0.40***</td><td>-0.13***</td><td>0.58***</td><td>0.45***</td><td>0.10***</td><td>-0.55***</td><td>-0.52***</td></tr></tbody></table>

Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. All variables are described in Table A1 in Appendix A.

Abbreviations: BG, business group; CSP, corporate social performance.
<table><caption>TABLE 3 Business groups (BGs) affiliation and non-financial performance.</caption><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th><th>Model 6</th></tr></thead><tbody><tr><td><strong>H1: BG Affiliation</strong></td><td></td><td><strong>0.043***</strong><br>(3.147)</td><td><strong>0.051***</strong><br>(3.700)</td><td><strong>0.049***</strong><br>(3.602)</td><td></td><td></td></tr><tr><td>Formal institutions</td><td></td><td></td><td>0.012<br>(0.976)</td><td></td><td></td><td></td></tr><tr><td><strong>H2a: BG<br>Affiliation × formal<br>institutions</strong></td><td></td><td></td><td><strong>0.047***</strong><br>(4.494)</td><td></td><td></td><td></td></tr><tr><td>Informal institutions</td><td></td><td></td><td></td><td>-0.010<br>(-1.068)</td><td></td><td></td></tr><tr><td><strong>H2b: BG<br>Affiliation × informal<br>institutions</strong></td><td></td><td></td><td></td><td><strong>0.031***</strong><br>(2.913)</td><td></td><td></td></tr><tr><td><strong>H3a: BG Hierarchy</strong></td><td></td><td></td><td></td><td></td><td><strong>-0.062***</strong><br>(-6.275)</td><td></td></tr><tr><td><strong>H3b: BG<br>Diversification</strong></td><td></td><td></td><td></td><td></td><td></td><td><strong>-0.062***</strong><br>(-5.784)</td></tr><tr><td>Firm size</td><td>0.306***<br>(32.930)</td><td>0.305***<br>(32.802)</td><td>0.307***<br>(33.056)</td><td>0.306***<br>(32.740)</td><td>0.315***<br>(23.610)</td><td>0.318***<br>(23.591)</td></tr><tr><td>Return on assets (ROA)</td><td>0.012<br>(1.117)</td><td>0.012<br>(1.147)</td><td>0.012<br>(1.117)</td><td>0.012<br>(1.119)</td><td>0.003<br>(0.171)</td><td>0.003<br>(0.177)</td></tr><tr><td>Leverage</td><td>-0.021***<br>(-2.640)</td><td>-0.021***<br>(-2.613)</td><td>-0.020**<br>(-2.513)</td><td>-0.021***<br>(-2.634)</td><td>-0.048***<br>(-4.224)</td><td>-0.053***<br>(-4.648)</td></tr><tr><td>Volatility</td><td>-0.066***<br>(-8.218)</td><td>-0.066***<br>(-8.171)</td><td>-0.065***<br>(-7.982)</td><td>-0.067***<br>(-8.225)</td><td>-0.103***<br>(-8.675)</td><td>-0.101***<br>(-8.564)</td></tr><tr><td>Market-to-book value</td><td>6.712***<br>(4.497)</td><td>6.614***<br>(4.427)</td><td>6.564***<br>(4.385)</td><td>6.779***<br>(4.531)</td><td>11.458***<br>(5.574)</td><td>11.947***<br>(5.794)</td></tr><tr><td>Closely held shares</td><td>-0.028***<br>(-3.392)</td><td>-0.026***<br>(-3.194)</td><td>-0.027***<br>(-3.331)</td><td>-0.027***<br>(-3.335)</td><td>-0.022**<br>(-2.020)</td><td>-0.020*<br>(-1.914)</td></tr><tr><td>Foreign shareholding</td><td>0.000<br>(0.052)</td><td>0.001<br>(0.167)</td><td>0.001<br>(0.190)</td><td>0.001<br>(0.106)</td><td>0.028***<br>(4.128)</td><td>0.027***<br>(3.968)</td></tr><tr><td>Institutional<br>shareholding</td><td>-0.007<br>(-0.912)</td><td>-0.007<br>(-0.950)</td><td>-0.007<br>(-0.969)</td><td>-0.008<br>(-1.030)</td><td>0.000<br>(0.037)</td><td>0.000<br>(0.043)</td></tr><tr><td>Reputation monitoring</td><td>0.701***<br>(44.016)</td><td>0.702***<br>(44.084)</td><td>0.705***<br>(44.192)</td><td>0.701***<br>(44.023)</td><td>0.697***<br>(32.464)</td><td>0.696***<br>(32.448)</td></tr><tr><td>CSR award</td><td>0.644***<br>(41.544)</td><td>0.645***<br>(41.585)</td><td>0.644***<br>(41.568)</td><td>0.645***<br>(41.597)</td><td>0.574***<br>(26.276)</td><td>0.574***<br>(26.286)</td></tr><tr><td>Competition</td><td>-0.129***<br>(-6.860)</td><td>-0.128***<br>(-6.795)</td><td>-0.145***<br>(-7.509)</td><td>-0.129***<br>(-6.778)</td><td>-0.141***<br>(-5.507)</td><td>-0.144***<br>(-5.626)</td></tr><tr><td>Anti-self-dealing index</td><td>0.050***<br>(4.658)</td><td>0.050***<br>(4.653)</td><td>0.044***<br>(4.129)</td><td>0.050***<br>(4.571)</td><td>0.029*<br>(1.858)</td><td>0.024<br>(1.539)</td></tr><tr><td>Left/center ideology</td><td>-0.032***<br>(-5.314)</td><td>-0.032***<br>(-5.387)</td><td>-0.032***<br>(-5.267)</td><td>-0.032***<br>(-5.028)</td><td>-0.071***<br>(-8.821)</td><td>-0.070***<br>(-8.580)</td></tr></tbody></table>
<figure><img src="image_10.png" /></figure>

<table><caption>TABLE 3 (Continued)</caption><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th><th>Model 6</th></tr></thead><tbody><tr><td>Union density</td><td>0.027***<br>(2.957)</td><td>0.026***<br>(2.854)</td><td>0.019**<br>(2.045)</td><td>0.028***<br>(3.041)</td><td>0.080***<br>(6.816)</td><td>0.088***<br>(7.380)</td></tr><tr><td>Labor market efficiency</td><td>-0.141***<br>(-11.431)</td><td>-0.140***<br>(-11.351)</td><td>-0.147***<br>(-11.600)</td><td>-0.142***<br>(-11.023)</td><td>-0.122***<br>(-7.143)</td><td>-0.126***<br>(-7.389)</td></tr><tr><td>Country debt over assets</td><td>-0.029***<br>(-3.148)</td><td>-0.027***<br>(-2.986)</td><td>-0.024***<br>(-2.670)</td><td>-0.029***<br>(-3.201)</td><td>-0.049***<br>(-3.891)</td><td>-0.058***<br>(-4.528)</td></tr><tr><td>Power distance index</td><td>-0.014<br>(-1.150)</td><td>-0.015<br>(-1.245)</td><td>-0.011<br>(-0.874)</td><td>-0.007<br>(-0.568)</td><td>0.029*<br>(1.924)</td><td>0.030*<br>(1.950)</td></tr><tr><td>SRI index</td><td>0.207***<br>(10.710)</td><td>0.207***<br>(10.724)</td><td>0.201***<br>(10.278)</td><td>0.205***<br>(10.578)</td><td>0.100***<br>(3.713)</td><td>0.116***<br>(4.305)</td></tr><tr><td>Individualism</td><td>0.151***<br>(11.572)</td><td>0.147***<br>(11.217)</td><td>0.147***<br>(11.174)</td><td>0.154***<br>(11.149)</td><td>0.115***<br>(6.742)</td><td>0.110***<br>(6.510)</td></tr><tr><td>Quality of infrastructure</td><td>0.142***<br>(12.498)</td><td>0.143***<br>(12.532)</td><td>0.135***<br>(11.742)</td><td>0.145***<br>(12.266)</td><td>0.172***<br>(11.117)</td><td>0.171***<br>(11.077)</td></tr><tr><td>Balance of trade</td><td>-0.025***<br>(-2.849)</td><td>-0.025***<br>(-2.902)</td><td>-0.020**<br>(-2.218)</td><td>-0.023**<br>(-2.482)</td><td>-0.040***<br>(-3.393)</td><td>-0.044***<br>(-3.717)</td></tr><tr><td>Trade</td><td>-0.033***<br>(-2.702)</td><td>-0.035***<br>(-2.950)</td><td>-0.026**<br>(-2.114)</td><td>-0.038***<br>(-3.117)</td><td>-0.058***<br>(-3.682)</td><td>-0.056***<br>(-3.535)</td></tr><tr><td>Market size</td><td>-0.244***<br>(-18.424)</td><td>-0.242***<br>(-18.285)</td><td>-0.228***<br>(-16.385)</td><td>-0.242***<br>(-18.329)</td><td>-0.221***<br>(-12.049)</td><td>-0.226***<br>(-12.394)</td></tr><tr><td>Constant</td><td>-0.293***<br>(-8.640)</td><td>-0.315***<br>(-9.096)</td><td>-0.311***<br>(-8.940)</td><td>-0.315***<br>(-9.087)</td><td>-0.153***<br>(-3.227)</td><td>-0.182***<br>(-3.805)</td></tr><tr><td>Observations</td><td>9878</td><td>9878</td><td>9878</td><td>9878</td><td>4712</td><td>4712</td></tr><tr><td>R<sup>2</sup></td><td>0.577</td><td>0.577</td><td>0.578</td><td>0.577</td><td>0.600</td><td>0.599</td></tr><tr><td>Industry fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year-fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>VIF</td><td>2.53</td><td>2.50</td><td>2.52</td><td>2.49</td><td>2.51</td><td>2.52</td></tr></tbody></table>

Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. All continuous variables are standardized to have a mean value of zero and a standard deviation of one. All variables are described in Table A1 in Appendix A. Robust t-statistics are in parentheses. Bold indicates testable hypotheses.

Abbreviation: DV, dependent variable; VIF, variance inflation factor.

also graphed the results of the two interactions behind our Hypotheses 2a and 2b (see Figures 1 and 2).

Finally, we test the effect of BG characteristics on CSP. Results in Table 3, Model 5, show that the coefficient of our variable of interest, *BG Hierarchy*, is negative and significant ($\beta = -.062, p < .01$), suggesting that affiliated firms in BGs with higher hierarchy have lower CSP, which is in line with our Hypothesis 3a. Furthermore, to test the impact of BG diversification on the CSP of BG-affiliated firms, we analyze the coefficient of *BG Diversification* in Table 3, Model 6. We find that the coefficient is negative and significant ($\beta = -.062, p < .01$), suggesting that the level of diversification of BGs is associated with a decrease in the CSP of affiliated firms, supporting the prediction of Hypothesis 3b. Following our theoretical
<figure><img src="image_11.png" /><figcaption>FIGURE 1 Business groups (BG) affiliation and corporate social performance (CSP): The effect of formal institutions. SD, standard deviation.</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>FIGURE 2 Business groups (BG) affiliation and corporate social performance (CSP): The effect of informal institutions. SD, standard deviation.</figcaption></figure>
<figure><img src="image_13.png" /></figure>

conjectures (which focus on the independent effects of hierarchy and diversification) and considering the high correlation between these two group characteristics (0.67), we do not test them jointly in an all-encompassing BG-affiliate model.

## 4.3 | Robustness checks

To further test the strength of our empirical results, we perform several additional analyses targeting different components of our DV, testing potential outliers, alternative methodological solutions to endogeneity, as well as additional explanatory variables. Overall, our main conjectures hold well across these additional tests, as follows.

First, we *test separately environmental versus social outcomes*. In our main results, we use a composite measure of CSP, which is computed by assigning equal weights to environmental and social scores. Nonetheless, to test the sensitivity of our findings to the potentially different information that is potentially contained in separate environmental and social scores, we use the two components of CSP as standalone dependent variables. The results presented in Table 4 support all our main findings.

Second, we *exclude potential outliers* (i.e., firms from Anglo-Saxon countries). Prior literature highlighted that BGs seem to be encountered less in Anglo-Saxon contexts (Yiu et al., 2007). Since our data includes many observations from Anglo-Saxon countries—such as the United States, United Kingdom, Australia, and Canada—we might run the risk of obtaining biased results due to systematic differences relative to other settings. We therefore eliminate any observations from our sample that pertain to affiliated or non-affiliated firms from these countries. By performing this step, we drop 55.12% of our sample. When re-estimating our tests with the reduced sample, the results presented in Table 5 support all our findings.

Third, to further strengthen our analysis and address the validity of our PSM approach, we also employed the “entropy balancing” technique as an additional robustness analysis. Entropy balancing is a commonly used alternative that can overcome certain shortcomings of PSM (Hainmueller, 2012; Testoni et al., 2022). Specifically, entropy balancing accounts for the different characteristics of two groups, creating a balanced sample with similar characteristics. This is done by re-weighting the observations in the sample so that the distribution of confounding variables in the two groups is as close as possible to the distribution in the population. Accordingly, in our case, we used entropy balancing to reweight the covariates of our BG-affiliated firms (*treatment group*) to eliminate the imbalance in firm characteristics of non-affiliated firms (*control group*). In Table 6, Panel A, we show that, after weighting using entropy balancing, firm characteristics of BG-affiliated and non-affiliated firms are similar. Regression results (Table 6, Panel B) support all our prior findings.

Fourth, we also investigate the potential *interplay between formal and informal institutions on BG diversification, hierarchy, and CSP*. Specifically, we are interested in whether institutions affect the association between both BG diversification and hierarchy and CSP. These results are not reported in the paper due to space constraints but are available upon request. Our findings suggest that while formal and informal institutions do not have an incremental impact on the association between BG Diversification and CSP, the negative effect of BG hierarchy on affiliated firms' CSP is less strong in countries with more developed formal institutions only.

Finally, to rule out potential alternative explanations for our Hypotheses 3a and 3b with respect to unobserved BG-characteristics that might affect the relationship between BG
<table><caption>TABLE 4 Robustness—Testing separately Environmental and Social dimensions of corporate social performance.</caption><thead><tr><th></th><th>Model 1<br>DV: ENV</th><th>Model 2<br>DV: SOC</th><th>Model 3<br>DV: ENV</th><th>Model 4<br>DV: SOC</th><th>Model 5<br>DV: ENV</th><th>Model 6<br>DV: SOC</th><th>Model 7<br>DV: ENV</th><th>Model 8<br>DV: SOC</th><th>Model 9<br>DV: ENV</th><th>Model 10<br>DV: SOC</th></tr></thead><tbody><tr><td><strong>H1: BG Affiliation</strong></td><td>0.038***<br>(2.686)</td><td>0.041***<br>(2.996)</td><td>0.049***<br>(3.339)</td><td>0.047***<br>(3.321)</td><td>0.044***<br>(3.067)</td><td>0.048***<br>(3.422)</td><td></td><td></td><td></td><td></td></tr><tr><td>Formal institutions</td><td></td><td></td><td>0.013<br>(1.039)</td><td>0.009<br>(0.725)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>H2a: BG<br>Affiliation × formal<br>institutions</strong></td><td></td><td></td><td>0.058***<br>(5.183)</td><td>0.031***<br>(2.862)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Informal institutions</td><td></td><td></td><td></td><td></td><td>0.010<br>(0.975)</td><td>-0.029***<br>(-3.041)</td><td></td><td></td><td></td><td></td></tr><tr><td><strong>H2b: BG<br>Affiliation × informal<br>institutions</strong></td><td></td><td></td><td></td><td></td><td>0.033***<br>(2.988)</td><td>0.025**<br>(2.295)</td><td></td><td></td><td></td><td></td></tr><tr><td><strong>H3a: BG Hierarchy</strong></td><td></td><td></td><td></td><td></td><td></td><td>-0.083***<br>(-8.219)</td><td>-0.033***<br>(-3.142)</td><td></td><td></td><td></td></tr><tr><td><strong>H3b: BG<br>Diversification</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.078***<br>(-6.859)</td><td>-0.038***<br>(-3.428)</td><td></td></tr><tr><td>Firm size</td><td>0.283***<br>(28.434)</td><td>0.287***<br>(30.004)</td><td>0.285***<br>(28.742)</td><td>0.288***<br>(30.124)</td><td>0.287***<br>(28.735)</td><td>0.284***<br>(29.587)</td><td>0.322***<br>(21.994)</td><td>0.266***<br>(18.873)</td><td>0.324***<br>(22.061)</td><td>0.269***<br>(18.946)</td></tr><tr><td>Return on assets (ROA)</td><td>0.001<br>(0.125)</td><td>0.022*<br>(1.948)</td><td>0.001<br>(0.091)</td><td>0.021*<br>(1.930)</td><td>-0.000<br>(-0.016)</td><td>0.023**<br>(2.043)</td><td>-0.001<br>(-0.076)</td><td>0.007<br>(0.390)</td><td>-0.001<br>(-0.065)</td><td>0.007<br>(0.389)</td></tr><tr><td>Leverage</td><td>-0.003<br>(-0.379)</td><td>-0.037***<br>(4.383)</td><td>-0.002<br>(-0.265)</td><td>-0.036***<br>(-4.313)</td><td>-0.002<br>(-0.282)</td><td>-0.038***<br>(-4.528)</td><td>-0.031***<br>(-2.594)</td><td>-0.059***<br>(-4.931)</td><td>-0.038***<br>(-3.138)</td><td>-0.062***<br>(-5.145)</td></tr><tr><td>Volatility</td><td>-0.070***<br>(-8.289)</td><td>-0.053***<br>(-6.250)</td><td>-0.068***<br>(-8.076)</td><td>-0.052***<br>(-6.131)</td><td>-0.073***<br>(-8.567)</td><td>-0.051***<br>(-6.055)</td><td>-0.106***<br>(-8.349)</td><td>-0.087***<br>(-7.020)</td><td>-0.103***<br>(-8.223)</td><td>-0.085***<br>(-6.926)</td></tr><tr><td>Market-to-book value</td><td>1.808<br>(1.184)</td><td>10.705***<br>(7.029)</td><td>1.747<br>(1.143)</td><td>10.672***<br>(6.995)</td><td>2.031<br>(1.328)</td><td>10.787***<br>(7.055)</td><td>10.261***<br>(4.968)</td><td>11.140***<br>(5.381)</td><td>10.860***<br>(5.231)</td><td>11.448***<br>(5.525)</td></tr></tbody></table>
<figure><img src="image_14.png" /></figure>

<table><caption>TABLE 4 (Continued)</caption><thead><tr><th></th><th>Model 1<br>DV: ENV</th><th>Model 2<br>DV: SOC</th><th>Model 3<br>DV: ENV</th><th>Model 4<br>DV: SOC</th><th>Model 5<br>DV: ENV</th><th>Model 6<br>DV: SOC</th><th>Model 7<br>DV: ENV</th><th>Model 8<br>DV: SOC</th><th>Model 9<br>DV: ENV</th><th>Model 10<br>DV: SOC</th></tr></thead><tbody><tr><td>Closely held shares</td><td>-0.025***<br>(-2.911)</td><td>-0.023**<br>(-2.797)</td><td>-0.026***<br>(-3.072)</td><td>-0.024**<br>(-2.874)</td><td>-0.024***<br>(-2.833)</td><td>-0.026**<br>(-3.138)</td><td>-0.029**<br>(-2.568)</td><td>-0.010<br>(-0.949)</td><td>-0.028**<br>(-2.437)</td><td>-0.010<br>(-0.891)</td></tr><tr><td>Foreign shareholding</td><td>0.003<br>(0.476)</td><td>-0.001<br>(-0.187)</td><td>0.003<br>(0.503)</td><td>-0.001<br>(-0.172)</td><td>0.003<br>(0.411)</td><td>-0.001<br>(-0.234)</td><td>0.027***<br>(3.807)</td><td>0.026***<br>(3.740)</td><td>0.026***<br>(3.602)</td><td>0.025***<br>(3.648)</td></tr><tr><td>Institutional<br>shareholding</td><td>-0.011<br>(-1.328)</td><td>-0.003<br>(0.341)</td><td>-0.011<br>(-1.347)</td><td>-0.003<br>(-0.355)</td><td>-0.012<br>(-1.504)</td><td>-0.002<br>(-0.300)</td><td>-0.006<br>(-0.513)</td><td>0.007<br>(0.590)</td><td>-0.005<br>(-0.481)</td><td>0.007<br>(0.574)</td></tr><tr><td>Reputation monitoring</td><td>0.562***<br>(33.090)</td><td>0.752***<br>(46.160)</td><td>0.566***<br>(33.246)</td><td>0.754***<br>(46.188)</td><td>0.561***<br>(32.988)</td><td>0.751***<br>(46.185)</td><td>0.571***<br>(24.934)</td><td>0.734***<br>(33.282)</td><td>0.569***<br>(24.863)</td><td>0.733***<br>(33.299)</td></tr><tr><td>CSR award</td><td>0.587***<br>(35.363)</td><td>0.617***<br>(39.283)</td><td>0.585***<br>(35.334)</td><td>0.616***<br>(39.259)</td><td>0.586***<br>(35.344)</td><td>0.618***<br>(39.359)</td><td>0.520***<br>(22.106)</td><td>0.551***<br>(25.025)</td><td>0.521***<br>(22.129)</td><td>0.551***<br>(25.016)</td></tr><tr><td>Competition</td><td>-0.119***<br>(-6.089)</td><td>-0.120***<br>(-6.226)</td><td>-0.139***<br>(-6.948)</td><td>-0.131***<br>(-6.660)</td><td>-0.130***<br>(-6.532)</td><td>-0.112***<br>(-5.717)</td><td>-0.137***<br>(-5.117)</td><td>-0.126***<br>(-4.804)</td><td>-0.140***<br>(-5.254)</td><td>-0.128***<br>(-4.876)</td></tr><tr><td>Anti-self-dealing index</td><td>0.051***<br>(4.448)</td><td>0.042***<br>(3.908)</td><td>0.044***<br>(3.860)</td><td>0.039***<br>(3.552)</td><td>0.058***<br>(4.993)</td><td>0.035***<br>(3.139)</td><td>0.043***<br>(2.596)</td><td>0.011<br>(0.679)</td><td>0.036**<br>(2.210)</td><td>0.008<br>(0.499)</td></tr><tr><td>Left/center ideology</td><td>-0.026***<br>(-4.295)</td><td>-0.033***<br>(-5.507)</td><td>-0.026***<br>(-4.175)</td><td>-0.033***<br>(-5.402)</td><td>-0.022***<br>(-3.189)</td><td>-0.039***<br>(-6.019)</td><td>-0.052***<br>(-6.288)</td><td>-0.081***<br>(-9.724)</td><td>-0.050***<br>(-5.989)</td><td>-0.080***<br>(-9.611)</td></tr><tr><td>Union density</td><td>0.046***<br>(4.909)</td><td>0.001<br>(0.136)</td><td>0.039***<br>(3.975)</td><td>-0.003<br>(-0.339)</td><td>0.051***<br>(5.339)</td><td>0.000<br>(0.031)</td><td>0.097***<br>(7.940)</td><td>0.052***<br>(4.213)</td><td>0.106***<br>(8.600)</td><td>0.056***<br>(4.548)</td></tr><tr><td>Labor market efficiency</td><td>-0.117***<br>(-9.033)</td><td>-0.144***<br>(-11.343)</td><td>-0.125***<br>(-9.408)</td><td>-0.150***<br>(-11.358)</td><td>-0.129***<br>(-9.530)</td><td>-0.136***<br>(-10.251)</td><td>-0.108***<br>(-6.098)</td><td>-0.121***<br>(-6.601)</td><td>-0.113***<br>(-6.371)</td><td>-0.124***<br>(-6.752)</td></tr><tr><td>Country debt over assets</td><td>-0.034***<br>(-3.637)</td><td>-0.016*<br>(-1.707)</td><td>-0.032***<br>(-3.298)</td><td>-0.014<br>(-1.482)</td><td>-0.036***<br>(-3.835)</td><td>-0.017*<br>(-1.895)</td><td>-0.042***<br>(-3.189)</td><td>-0.050***<br>(-3.853)</td><td>-0.053***<br>(-3.973)</td><td>-0.055***<br>(-4.205)</td></tr><tr><td>Power distance index</td><td>-0.014<br>(-1.129)</td><td>-0.014<br>(-1.109)</td><td>-0.009<br>(-0.707)</td><td>-0.011<br>(-0.871)</td><td>0.006<br>(0.440)</td><td>-0.020<br>(-1.509)</td><td>0.023<br>(1.502)</td><td>0.031**<br>(2.004)</td><td>0.024<br>(1.512)</td><td>0.032**<br>(2.042)</td></tr><tr><td>SRI index</td><td>0.176***<br>(8.773)</td><td>0.211***<br>(10.652)</td><td>0.169***<br>(8.314)</td><td>0.207***<br>(10.335)</td><td>0.177***<br>(8.787)</td><td>0.206***<br>(10.384)</td><td>0.122***<br>(4.461)</td><td>0.064**<br>(2.257)</td><td>0.142***<br>(5.210)</td><td>0.074***<br>(2.594)</td></tr></tbody><tfoot><tr><td colspan="11" style="text-align: right;">(Continues)</td></tr></tfoot></table>
<table><caption>TABLE 4 (Continued)</caption><thead><tr><th></th><th>Model 1<br>DV: ENV</th><th>Model 2<br>DV: SOC</th><th>Model 3<br>DV: ENV</th><th>Model 4<br>DV: SOC</th><th>Model 5<br>DV: ENV</th><th>Model 6<br>DV: SOC</th><th>Model 7<br>DV: ENV</th><th>Model 8<br>DV: SOC</th><th>Model 9<br>DV: ENV</th><th>Model 10<br>DV: SOC</th></tr></thead><tbody><tr><td>Individualism</td><td>0.091***<br>(6.754)</td><td>0.185***<br>(14.085)</td><td>0.091***<br>(6.735)</td><td>0.185***<br>(14.010)</td><td>0.111***<br>(7.786)</td><td>0.178***<br>(12.808)</td><td>0.066***<br>(3.701)</td><td>0.151***<br>(8.729)</td><td>0.059***<br>(3.346)</td><td>0.149***<br>(8.649)</td></tr><tr><td>Quality of infrastructure</td><td>0.169***<br>(14.181)</td><td>0.096***<br>(8.406)</td><td>0.160***<br>(13.274)</td><td>0.091***<br>(7.843)</td><td>0.179***<br>(14.450)</td><td>0.089***<br>(7.569)</td><td>0.205***<br>(12.530)</td><td>0.115***<br>(7.319)</td><td>0.203***<br>(12.507)</td><td>0.114***<br>(7.269)</td></tr><tr><td>Balance of trade</td><td>-0.039***<br>(-4.193)</td><td>-0.008<br>(0.879)</td><td>-0.032***<br>(-3.412)</td><td>-0.004<br>(-0.442)</td><td>-0.029***<br>(-2.946)</td><td>-0.014<br>(-1.448)</td><td>-0.069***<br>(-5.639)</td><td>-0.005<br>(-0.365)</td><td>-0.074***<br>(-6.075)</td><td>-0.006<br>(-0.510)</td></tr><tr><td>Trade</td><td>-0.056***<br>(-4.351)</td><td>-0.010<br>(-0.803)</td><td>-0.044***<br>(-3.404)</td><td>-0.003<br>(-0.260)</td><td>-0.059***<br>(-4.622)</td><td>-0.010<br>(-0.840)</td><td>-0.055***<br>(-3.340)</td><td>-0.053***<br>(-3.365)</td><td>-0.052***<br>(-3.151)</td><td>-0.052***<br>(-3.291)</td></tr><tr><td>Market size</td><td>-0.202***<br>(-14.456)</td><td>-0.251***<br>(-18.571)</td><td>-0.186***<br>(-12.602)</td><td>-0.241***<br>(-17.033)</td><td>-0.204***<br>(-14.624)</td><td>-0.249***<br>(-18.462)</td><td>-0.187***<br>(-9.615)</td><td>-0.226***<br>(-11.954)</td><td>-0.192***<br>(-9.942)</td><td>-0.230***<br>(-12.160)</td></tr><tr><td>Constant</td><td>-0.225***<br>(-6.166)</td><td>-0.184***<br>(-5.216)</td><td>-0.221***<br>(-6.031)</td><td>-0.181***<br>(-5.108)</td><td>-0.224***<br>(-6.125)</td><td>-0.185***<br>(-5.248)</td><td>-0.067<br>(-1.339)</td><td>-0.041<br>(-0.842)</td><td>-0.102**<br>(-2.036)</td><td>-0.059<br>(-1.196)</td></tr><tr><td>Observations</td><td>9878</td><td>9878</td><td>9878</td><td>9878</td><td>9878</td><td>9878</td><td>4712</td><td>4712</td><td>4712</td><td>4712</td></tr><tr><td>R<sup>2</sup></td><td>0.502</td><td>0.556</td><td>0.504</td><td>0.557</td><td>0.503</td><td>0.557</td><td>0.539</td><td>0.566</td><td>0.537</td><td>0.566</td></tr><tr><td>Industry fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year-fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

Note: *** and * denote the significance level at 1%, 5%, and 10%. All continuous variables are standardized to have a mean value of zero and a standard deviation of one. All variables are described in Table A1 in Appendix A. Robust t-statistics are in parentheses.

Abbreviation: BG, business group; ENV, Environmental pillar of CSP; SOC, social pillar of CSP.
<figure><img src="image_15.png" /></figure>

<table><caption>TABLE 5 Robustness—excluding Anglo-Saxon countries.</caption><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th></tr></thead><tbody><tr><td><strong>H1: BG Affiliation</strong></td><td><strong>0.143***</strong><br>(7.009)</td><td><strong>0.196***</strong><br>(8.714)</td><td><strong>0.180***</strong><br>(8.208)</td><td></td><td></td></tr><tr><td>Formal institutions</td><td></td><td>0.007 (0.394)</td><td></td><td></td><td></td></tr><tr><td><strong>H2a: BG</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Affiliation × formal institutions</strong></td><td></td><td><strong>0.091***</strong><br>(6.664)</td><td></td><td></td><td></td></tr><tr><td>Informal institutions</td><td></td><td></td><td>0.008 (0.583)</td><td></td><td></td></tr><tr><td><strong>H2b: BG</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Affiliation × informal institutions</strong></td><td></td><td></td><td><strong>0.072***</strong><br>(5.269)</td><td></td><td></td></tr><tr><td><strong>H3a: BG Hierarchy</strong></td><td></td><td></td><td></td><td><strong>-0.045***</strong><br>(-3.065)</td><td></td></tr><tr><td><strong>H3b: BG Diversification</strong></td><td></td><td></td><td></td><td></td><td><strong>-0.062***</strong><br>(-3.832)</td></tr><tr><td>Firm size</td><td>0.281***<br>(19.112)</td><td>0.282***<br>(19.257)</td><td>0.284***<br>(19.441)</td><td>0.332***<br>(15.677)</td><td>0.338***<br>(15.937)</td></tr><tr><td>Return on assets (ROA)</td><td>0.050**<br>(2.437)</td><td>0.044**<br>(2.157)</td><td>0.042**<br>(2.085)</td><td>0.005 (0.188)</td><td>0.001 (0.041)</td></tr><tr><td>Leverage</td><td>-0.029**<br>(-2.264)</td><td>-0.027**<br>(-2.166)</td><td>-0.029**<br>(-2.297)</td><td>-0.072***<br>(-4.336)</td><td>-0.077***<br>(-4.689)</td></tr><tr><td>Volatility</td><td>-0.041***<br>(-2.981)</td><td>-0.043***<br>(-3.117)</td><td>-0.046***<br>(-3.326)</td><td>-0.079***<br>(-4.096)</td><td>-0.077***<br>(-3.999)</td></tr><tr><td>Market-to-book value</td><td>9.490***<br>(3.310)</td><td>8.895***<br>(3.147)</td><td>9.302***<br>(3.267)</td><td>17.213***<br>(5.519)</td><td>17.573***<br>(5.687)</td></tr><tr><td>Closely held shares</td><td>-0.008<br>(-0.644)</td><td>-0.016<br>(-1.229)</td><td>-0.014<br>(-1.113)</td><td>-0.043***<br>(-2.649)</td><td>-0.044***<br>(-2.696)</td></tr><tr><td>Foreign shareholding</td><td>-0.011<br>(-1.198)</td><td>-0.009<br>(-1.059)</td><td>-0.010<br>(-1.117)</td><td>0.035***<br>(3.563)</td><td>0.034***<br>(3.538)</td></tr><tr><td>Institutional shareholding</td><td>-0.001<br>(-0.045)</td><td>-0.002<br>(-0.124)</td><td>-0.006<br>(-0.445)</td><td>0.017 (0.964)</td><td>0.016 (0.932)</td></tr><tr><td>Reputation monitoring</td><td>0.775***<br>(35.428)</td><td>0.779***<br>(35.660)</td><td>0.767***<br>(34.989)</td><td>0.688***<br>(24.571)</td><td>0.687***<br>(24.505)</td></tr><tr><td>CSR award</td><td>0.636***<br>(27.835)</td><td>0.628***<br>(27.515)</td><td>0.635***<br>(27.825)</td><td>0.509***<br>(17.214)</td><td>0.508***<br>(17.207)</td></tr><tr><td>Competition</td><td>-0.098***<br>(-3.960)</td><td>-0.133***<br>(-5.153)</td><td>-0.123***<br>(-4.771)</td><td>-0.077**<br>(-2.314)</td><td>-0.077**<br>(-2.329)</td></tr><tr><td>Anti-self-dealing index</td><td>0.032*<br>(1.952)</td><td>0.014 (0.843)</td><td>0.061***<br>(3.385)</td><td>-0.023<br>(-0.992)</td><td>-0.025<br>(-1.087)</td></tr><tr><td>Left/center ideology</td><td>-0.036***<br>(-4.805)</td><td>-0.032***<br>(-4.140)</td><td>-0.022**<br>(-2.496)</td><td>-0.079***<br>(-8.190)</td><td>-0.076***<br>(-7.866)</td></tr><tr><td>Union density</td><td>-0.016<br>(-1.329)</td><td>-0.022*<br>(-1.703)</td><td>-0.014<br>(-1.113)</td><td>0.060***<br>(3.770)</td><td>0.065***<br>(4.053)</td></tr></tbody><tfoot><tr><td colspan="6">(Continues)</td></tr></tfoot></table>
<table><caption>TABLE 5 (Continued)</caption><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th></tr></thead><tbody><tr><td>Labor market efficiency</td><td>-0.081***<br>(-4.070)</td><td>-0.111***<br>(-4.911)</td><td>-0.107***<br>(-5.078)</td><td>-0.027<br>(-1.017)</td><td>-0.026<br>(-1.006)</td></tr><tr><td>Country debt over assets</td><td>0.047***<br>(3.150)</td><td>0.039***<br>(2.588)</td><td>0.048***<br>(3.175)</td><td>0.026 (1.327)</td><td>0.022 (1.092)</td></tr><tr><td>Power distance index</td><td>0.005 (0.316)</td><td>0.011 (0.707)</td><td>0.036**<br>(2.244)</td><td>0.042**<br>(2.240)</td><td>0.042**<br>(2.269)</td></tr><tr><td>SRI index</td><td>0.026 (0.825)</td><td>-0.006<br>(-0.170)</td><td>-0.008<br>(-0.255)</td><td>-0.066*<br>(-1.671)</td><td>-0.065*<br>(-1.649)</td></tr><tr><td>Individualism</td><td>0.215***<br>(11.710)</td><td>0.201***<br>(10.725)</td><td>0.262***<br>(13.270)</td><td>0.159***<br>(6.407)</td><td>0.164***<br>(6.632)</td></tr><tr><td>Quality of infrastructure</td><td>0.170***<br>(12.326)</td><td>0.165***<br>(11.987)</td><td>0.194***<br>(12.756)</td><td>0.164***<br>(9.127)</td><td>0.163***<br>(9.168)</td></tr><tr><td>Balance of trade</td><td>-0.034*<br>(-1.812)</td><td>-0.020<br>(-1.033)</td><td>-0.010<br>(-0.519)</td><td>-0.117***<br>(-5.072)</td><td>-0.122***<br>(-5.294)</td></tr><tr><td>Trade</td><td>-0.040<br>(-1.505)</td><td>-0.021<br>(-0.797)</td><td>-0.044*<br>(-1.670)</td><td>0.007 (0.229)</td><td>0.004 (0.144)</td></tr><tr><td>Market size</td><td>-0.135***<br>(-7.235)</td><td>-0.119***<br>(-6.370)</td><td>-0.134***<br>(-7.256)</td><td>-0.060**<br>(-2.359)</td><td>-0.060**<br>(-2.403)</td></tr><tr><td>Constant</td><td>-0.000<br>(-0.004)</td><td>-0.043<br>(-0.638)</td><td>0.041 (0.588)</td><td>0.373***<br>(4.287)</td><td>0.390***<br>(4.516)</td></tr><tr><td>Observations</td><td>4434</td><td>4434</td><td>4434</td><td>2298</td><td>2298</td></tr><tr><td>R<sup>2</sup></td><td>0.590</td><td>0.595</td><td>0.594</td><td>0.588</td><td>0.589</td></tr><tr><td>Industry fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year-fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. All continuous variables are standardized to have a mean value of zero and a standard deviation of one. All variables are described in Table A1 in Appendix A. Robust t-statistics are in parentheses. Bold indicates testable hypotheses.

Abbreviation: BG, business group.

structure and CSP, we also test for the potential effect of controlling shareholders by including shareholder fixed effects. These results (available upon request) are statistically similar to the ones presented in Table 3 Models 5 and 6 and support our Hypotheses 3a and 3b.

## 5 | DISCUSSION AND CONCLUSIONS

Compared with their standalone counterparts, BGs remain an understudied phenomenon in the global economy. Moreover, existing research on this topic remains divided about their impact, finding that they can both destroy or create financial value for affiliates depending on context. Subsequently, BGs have been depicted ambivalently through phrases such as “paragons or parasites” (Khanna & Yafeh, 2007) and “red baron or robber baron” (Perotti & Gelfer, 2001).

Furthermore, while the economic and financial implications of BG affiliation have received the bulk of scholarly attention, we know very little about their non-financial performance. In
<figure><img src="image_16.png" /></figure>

<table><caption>TABLE 6 Robustness—entropy balancing results.</caption><thead><tr><th colspan="11">Panel A: Before and after weighting</th></tr><tr><th colspan="11">Before: without weighting</th></tr><tr><th rowspan="2"></th><th colspan="3">BG-affiliated</th><th colspan="3">Non-affiliated</th></tr><tr><th>Mean</th><th>Variance</th><th>Skewness</th><th>Mean</th><th>Variance</th><th>Skewness</th></tr></thead><tbody><tr><td>Firm size</td><td>0.031</td><td>0.863</td><td>0.278</td><td>-0.002</td><td>1.013</td><td>0.322</td></tr><tr><td>Return on assets (ROA)</td><td>0.052</td><td>0.461</td><td>-0.388</td><td>-0.007</td><td>0.476</td><td>-0.729</td></tr><tr><td>Leverage</td><td>-0.030</td><td>0.725</td><td>0.624</td><td>-0.019</td><td>0.767</td><td>0.651</td></tr><tr><td>Volatility</td><td>-0.042</td><td>0.897</td><td>0.733</td><td>-0.050</td><td>0.914</td><td>0.796</td></tr><tr><td>Market-to-book value</td><td>-0.007</td><td>0.000</td><td>3.469</td><td>-0.007</td><td>0.000</td><td>3.377</td></tr><tr><td>Closely held shares</td><td>0.897</td><td>0.939</td><td>-0.430</td><td>-0.279</td><td>0.670</td><td>1.353</td></tr><tr><td>Foreign shareholding</td><td>0.429</td><td>2.296</td><td>1.757</td><td>-0.118</td><td>0.589</td><td>3.885</td></tr><tr><td>Institutional shareholding</td><td>-0.230</td><td>0.874</td><td>3.225</td><td>0.059</td><td>1.005</td><td>1.805</td></tr><tr><td>Reputation monitoring</td><td>0.283</td><td>0.203</td><td>0.966</td><td>0.234</td><td>0.179</td><td>1.259</td></tr><tr><td>CSR award</td><td>0.462</td><td>0.249</td><td>0.152</td><td>0.428</td><td>0.245</td><td>0.289</td></tr></tbody><thead><tr><th colspan="11">After: with weighting</th></tr><tr><th rowspan="2"></th><th colspan="3">BG-affiliated</th><th colspan="3">Non-affiliated</th></tr><tr><th>Mean</th><th>Variance</th><th>Skewness</th><th>Mean</th><th>Variance</th><th>Skewness</th></tr></thead><tbody><tr><td>Firm size</td><td>0.031</td><td>0.863</td><td>0.278</td><td>0.031</td><td>0.991</td><td>0.317</td></tr><tr><td>ROA</td><td>0.052</td><td>0.461</td><td>-0.388</td><td>0.052</td><td>0.486</td><td>0.115</td></tr><tr><td>Leverage</td><td>-0.030</td><td>0.725</td><td>0.624</td><td>-0.030</td><td>0.782</td><td>0.649</td></tr><tr><td>Volatility</td><td>-0.042</td><td>0.897</td><td>0.733</td><td>-0.042</td><td>0.869</td><td>0.755</td></tr><tr><td>Market-to-book value</td><td>-0.007</td><td>0.000</td><td>3.469</td><td>-0.007</td><td>0.000</td><td>3.444</td></tr><tr><td>Closely held shares</td><td>0.897</td><td>0.939</td><td>-0.430</td><td>0.895</td><td>1.284</td><td>-0.178</td></tr><tr><td>Foreign shareholding</td><td>0.429</td><td>2.296</td><td>1.757</td><td>0.428</td><td>2.489</td><td>2.010</td></tr><tr><td>Institutional shareholding</td><td>-0.230</td><td>0.874</td><td>3.225</td><td>-0.229</td><td>0.788</td><td>3.111</td></tr><tr><td>Reputation monitoring</td><td>0.283</td><td>0.203</td><td>0.966</td><td>0.283</td><td>0.203</td><td>0.966</td></tr><tr><td>CSR award</td><td>0.462</td><td>0.249</td><td>0.152</td><td>0.462</td><td>0.249</td><td>0.152</td></tr></tbody><thead><tr><th colspan="11">Panel B: Regression result using balanced sample after weighting</th></tr><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td><strong>H1: BG Affiliation</strong></td><td><strong>0.048***</strong><br>(3.877)</td><td><strong>0.061***</strong><br>(4.786)</td><td><strong>0.053***</strong><br>(4.195)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Formal institutions</td><td></td><td>0.004<br>(0.289)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>H2a: BG</strong></td><td></td><td><strong>0.053***</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><strong>Affiliation × formal institutions</strong></td><td></td><td><strong>(5.153)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Informal institutions</td><td></td><td></td><td>0.004<br>(0.379)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

(Continues)
<caption>TABLE 6 (Continued)</caption>

Panel B: Regression result using balanced sample after weighting

<table><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th></tr></thead><tbody><tr><td><strong>H2b: BG</strong></td><td></td><td></td><td><strong>0.019*</strong></td><td></td><td></td></tr><tr><td><strong>Affiliation × informal institutions</strong></td><td></td><td></td><td><strong>(1.899)</strong></td><td></td><td></td></tr><tr><td><strong>H3a: BG Hierarchy</strong></td><td></td><td></td><td></td><td><strong>-0.062***</strong><br>(-6.275)</td><td></td></tr><tr><td><strong>H3b: BG Diversification</strong></td><td></td><td></td><td></td><td></td><td><strong>-0.062***</strong><br>(-5.784)</td></tr><tr><td>Firm size</td><td>0.292***<br>(34.872)</td><td>0.294***<br>(35.200)</td><td>0.294***<br>(35.118)</td><td>0.315***<br>(23.610)</td><td>0.318***<br>(23.591)</td></tr><tr><td>ROA</td><td>0.020**<br>(1.988)</td><td>0.019*<br>(1.925)</td><td>0.019*<br>(1.904)</td><td>0.003<br>(0.171)</td><td>0.003<br>(0.177)</td></tr><tr><td>Leverage</td><td>-0.016**<br>(-2.155)</td><td>-0.015**<br>(-2.037)</td><td>-0.015**<br>(-2.114)</td><td>-0.048***<br>(-4.224)</td><td>-0.053***<br>(-4.648)</td></tr><tr><td>Volatility</td><td>-0.059***<br>(-7.965)</td><td>-0.057***<br>(-7.733)</td><td>-0.060***<br>(-8.141)</td><td>-0.103***<br>(-8.675)</td><td>-0.101***<br>(-8.564)</td></tr><tr><td>Market-to-book value</td><td>10.346***<br>(6.292)</td><td>10.126***<br>(6.170)</td><td>10.466***<br>(6.363)</td><td>11.458***<br>(5.574)</td><td>11.947***<br>(5.794)</td></tr><tr><td>Closely held shares</td><td>-0.038***<br>(-5.353)</td><td>-0.040***<br>(-5.586)</td><td>-0.038***<br>(-5.280)</td><td>-0.022**<br>(-2.020)</td><td>-0.020*<br>(-1.914)</td></tr><tr><td>Foreign shareholding</td><td>0.004<br>(0.704)</td><td>0.004<br>(0.765)</td><td>0.004<br>(0.673)</td><td>0.028***<br>(4.128)</td><td>0.027***<br>(3.968)</td></tr><tr><td>Institutional shareholding</td><td>-0.016**<br>(-2.371)</td><td>-0.016**<br>(-2.425)</td><td>-0.016**<br>(-2.466)</td><td>0.000<br>(0.037)</td><td>0.000<br>(0.043)</td></tr><tr><td>Reputation monitoring</td><td>0.712***<br>(47.397)</td><td>0.714***<br>(47.677)</td><td>0.711***<br>(47.381)</td><td>0.697***<br>(32.464)</td><td>0.696***<br>(32.448)</td></tr><tr><td>CSR award</td><td>0.635***<br>(44.417)</td><td>0.635***<br>(44.582)</td><td>0.635***<br>(44.514)</td><td>0.574***<br>(26.276)</td><td>0.574***<br>(26.286)</td></tr><tr><td>Competition</td><td>-0.125***<br>(-7.086)</td><td>-0.140***<br>(-7.774)</td><td>-0.130***<br>(-7.289)</td><td>-0.141***<br>(-5.507)</td><td>-0.144***<br>(-5.626)</td></tr><tr><td>Anti-self-dealing index</td><td>0.032***<br>(3.056)</td><td>0.027**<br>(2.552)</td><td>0.036***<br>(3.426)</td><td>0.029*<br>(1.858)</td><td>0.024<br>(1.539)</td></tr><tr><td>Left/center ideology</td><td>-0.032***<br>(-5.716)</td><td>-0.031***<br>(-5.537)</td><td>-0.030***<br>(-4.910)</td><td>-0.071***<br>(-8.821)</td><td>-0.070***<br>(-8.580)</td></tr><tr><td>Union density</td><td>0.026***<br>(3.014)</td><td>0.021**<br>(2.416)</td><td>0.028***<br>(3.290)</td><td>0.080***<br>(6.816)</td><td>0.088***<br>(7.380)</td></tr><tr><td>Labor market efficiency</td><td>-0.146***<br>(-12.310)</td><td>-0.150***<br>(-12.401)</td><td>-0.152***<br>(-12.297)</td><td>-0.122***<br>(-7.143)</td><td>-0.126***<br>(-7.389)</td></tr><tr><td>Country debt over assets</td><td>-0.038***<br>(-4.452)</td><td>-0.036***<br>(-4.194)</td><td>-0.039***<br>(-4.566)</td><td>-0.049***<br>(-3.891)</td><td>-0.058***<br>(-4.528)</td></tr><tr><td>Power distance index</td><td>-0.009<br>(-0.812)</td><td>-0.003<br>(-0.258)</td><td>0.002<br>(0.121)</td><td>0.029*<br>(1.924)</td><td>0.030*<br>(1.950)</td></tr></tbody></table>
<table><caption>TABLE 6 (Continued)</caption><caption>Panel B: Regression result using balanced sample after weighting</caption><thead><tr><th>DV: CSP</th><th>Model 1</th><th>Model 2</th><th>Model 3</th><th>Model 4</th><th>Model 5</th></tr></thead><tbody><tr><td>SRI index</td><td>0.184***<br>(10.074)</td><td>0.179***<br>(9.654)</td><td>0.184***<br>(10.099)</td><td>0.100***<br>(3.713)</td><td>0.116***<br>(4.305)</td></tr><tr><td>Individualism</td><td>0.141***<br>(11.365)</td><td>0.142***<br>(11.532)</td><td>0.151***<br>(11.462)</td><td>0.115***<br>(6.742)</td><td>0.110***<br>(6.510)</td></tr><tr><td>Quality of infrastructure</td><td>0.140***<br>(12.670)</td><td>0.133***<br>(11.899)</td><td>0.145***<br>(12.722)</td><td>0.172***<br>(11.117)</td><td>0.171***<br>(11.077)</td></tr><tr><td>Balance of trade</td><td>-0.044***<br>(-5.125)</td><td>-0.039***<br>(-4.433)</td><td>-0.038***<br>(-4.233)</td><td>-0.040***<br>(-3.393)</td><td>-0.044***<br>(-3.717)</td></tr><tr><td>Trade</td><td>-0.037***<br>(-3.298)</td><td>-0.030***<br>(-2.644)</td><td>-0.040***<br>(-3.553)</td><td>-0.058***<br>(-3.682)</td><td>-0.056***<br>(-3.535)</td></tr><tr><td>Market size</td><td>-0.226***<br>(-18.225)</td><td>-0.214***<br>(-16.406)</td><td>-0.227***<br>(-18.304)</td><td>-0.221***<br>(-12.049)</td><td>-0.226***<br>(-12.394)</td></tr><tr><td>Constant</td><td>-0.269***<br>(-8.377)</td><td>-0.270***<br>(-8.361)</td><td>-0.269***<br>(-8.351)</td><td>-0.153***<br>(-3.227)</td><td>-0.182***<br>(-3.805)</td></tr><tr><td>Observations</td><td>29,886</td><td>29,886</td><td>29,886</td><td>4712</td><td>4712</td></tr><tr><td>R<sup>2</sup></td><td>0.581</td><td>0.582</td><td>0.581</td><td>0.600</td><td>0.599</td></tr><tr><td>Industry fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year-fixed effects</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. All continuous variables are standardized to have a mean value of zero and a standard deviation of one. All variables are described in Table A1 in Appendix A. Robust t-statistics are in parentheses. Bold indicates testable hypotheses.

Abbreviation: BG, business group; CSP, corporate social performance.

response to this paucity, we drew upon TCE arguments (Roberts & Greenwood, 1997; Williamson, 1981) to theorize about how a group structure would reduce transaction costs for affiliates in terms of developing CSP, thus allowing them to outperform non-affiliates. In line with TCE arguments applied to institutional context (North, 1991), we explored how the institutional environment (specifically the strength of formal and informal institutions) would heighten such effects. Finally, we focused solely on the subsample of BG-affiliates to also examine how two dimensions of group (hierarchy and diversification) would impact non-financial performance. Our empirical setting employed a large longitudinal dataset of 29,886 firm-year observations for 4368 firms from 43 countries between the years 2003 and 2016. Furthermore, it used the PSM technique to compare reliably the performance of affiliates versus non-affiliates and test causal inferences about the effects of BG ownership on performance.

Our results confirmed that, relative to non-affiliated firms, BG affiliates had better CSP. We attributed this effect to the reputation, internal resource and trading arrangements, and external access to networks and markets that reduced the search, contracting, monitoring, and coordination associated with improving CSP. Furthermore, our findings suggested that the positive effect of BG affiliation on CSP would be stronger in countries characterized by strong (formal and informal) institutions. These results are in line with the predictions of new-institutional economics, that the institutional environment can either increase or reduce risks and transaction
costs for firms (North, 1991). Therefore, both formal and informal institutional pressures—through strong regulatory frameworks and more emphasis on social and environmental issues—strengthen the BG affiliates' responses in terms of CSP. In our within BG-affiliates tests, we also found that higher levels of hierarchy in BGs were associated with a negative effect on the CSP of affiliated firms. The same logic held true for diversification: CSP of affiliates was negatively associated with the level of the group's unrelated diversification. In both cases, the negative impact implied higher degrees of pyramidization and “empire-building” in the group structure, which was associated with exploitative rather than supportive behaviors by controlling interests (Khanna & Yafeh, 2007; Morck et al., 2005).

Subsequently, this work advances the extant literature on several fronts. First, our theoretical framework taps into the firm-specific processes and strategic considerations for affiliates versus non-affiliates to engage in CSP-seeking actions. While most of the literature on non-financial performance focuses on external drivers (Delmas & Toffel, 2004; Montiel & Husted, 2009), we adopt a transaction-based view lens for our arguments and contend that BG affiliates will have access to more efficient pathways to perform on social and environmental measures versus non-affiliates. In this way, we also marry two distinct streams of research (i.e., BG studies and CSP studies) that otherwise have remained disjointed to date (Chittoor et al., 2015; Choi et al., 2018; Choi & Wang, 2009; Khanna & Rivkin, 2001; Yiu et al., 2007).

Second, we take a general approach to examining the contingencies of this relationship by focusing on the phenomenon of BGs in an international context. While many prior studies in this vein have focused on BGs from a single jurisdiction or country, we are interested in investigating the generic features of BGs and how different institutional levers may or may not spur CSP results for affiliates versus non-affiliates. Thus, our findings regarding the role of institutional contingencies (of formal and informal nature) suggest that stronger institutional environments support (i.e., further enhance) the positive effects of BG affiliation when it comes to CSP. This is at odds with one of the dominant rationales proposed in the literature, namely that BG structures will serve as scaffolds for performance in the context of institutional voids or that strong ties lead to economic entrenchment (Carney et al., 2018).

Lastly, we go beyond the simple dichotomy of affiliate versus non-affiliate performance by exploring also the existing heterogeneity across BGs. Our focus rests on two key strategies for performance (hierarchy/control and diversification) that have been traditionally the focus of strategy scholars. Consistent with our theoretical conjectures, we document a weakening of the relationship between BG affiliation and CSP for affiliates that are part of hierarchical and more diversified groups. These insights suggest that there are various nuances to be considered when examining the effects of BGs, in line with the complexities of their structure and the historical, sector, and country-specific forces that have molded its strategy and structure for a long time (Khanna, 2000). They also reconfirm the importance of classical strategies such as diversification and ownership (Ramachandran et al., 2021) as well as formal organizational structures (Bouquet & Birkinshaw, 2008) in determining both financial and non-financial performance of organizations. In considering CSP as a measure of performance, we also widen the area of inquiry into different types of non-financial value created (or impaired) by BG affiliation.

Notwithstanding these advances, our work is subject to several caveats that can be explored by future research. For instance, although we focus on two dimensions of institutional context and two dimensions of heterogeneity in group structure, BGs are highly diverse across many other dimensions (Carney et al., 2011; Colli & Colpan, 2016). Future studies should go deeper and explore heterogeneity across other dimensions, either in terms of country characteristics (e.g., political regimes, market size, corruption, etc.) or structure (international diversification,
<figure><img src="image_17.png" /></figure>

family ownership, political involvement, etc.) to determine how these factors affect the non-financial performance of affiliates. In addition, another limitation stemming from the operationalization of our DV. In this work, we have followed the consensus in the literature and employed CSP as a proxy for non-financial performance. However, as with other comparable metrics, the Refinitiv ESG scores are based on selected measures that may not fully capture the true impact of CSP. Future research could either use alternate non-financial measures to corroborate our findings or develop more direct measures to evaluate the social and environmental impact of BGs. A final limitation is associated with the endogenous nature of BG affiliation. While we mitigate this concern by using a matched sample and use of entropy balancing in additional tests, our matching procedure is limited by the absence of certain unobservable firm-level characteristics (e.g., social connections, strategic leadership) or any exogenous data (e.g., exogenous shock) potentially explaining the formation of BGs, which poses a challenge in a multi-country setting where mapping the social connections among affiliated firms, and finding an exogenous instrument valid in all countries is difficult.

Besides academic insights, our findings also bear important implications for practitioners and policymakers. Specifically, the main take-away of our study is to avoid any stereotyping regarding BGs and their impact on corporate and social outcomes. We thus show that in the case of CSP as a common non-financial metric, BG affiliates tend to outperform non-affiliated peers. Moreover, contrary to prior views in the literature that BGs proxy for better institutions (i.e., the “institutional voids” explanations) and that, as formal institutions develop, BGs will decline in importance and prevalence, we find that better institutions complement existing forces within groups that drive their affiliates to have better CSP scores.

Finally, we also explore the opposite effect and forces summoned up by greater diversification and hierarchies within BGs, which may detract from their focus on CSP. Together, these insights provide policymakers with new insights on the role that BGs may play in further advancing social and corporate benefits that increase the competitiveness of a domestic market. In turn, this suggests that BGs may provide an efficient avenue for economic development and institutional upgrading. For managers, they suggest a trade-off in terms of diversification and hierarchical structure, one that clearly favors financial results to the detriment of non-financial efforts needed to tackle the grand challenges we face today as a society and as a species.

## ACKNOWLEDGEMENTS

We thank Jonathan Doh, Ajai Gaur, and the participants of the JWB PDW, AIB conference and the research seminar at University of Exeter Business School, for useful comments on earlier drafts of this work. We are very grateful to the Handling Editor (Prof. Cecilia Gu) and two anonymous Reviewers for a an excellent, developmental review process which has helped us tremendously in improving this work.

## ORCID

Sorin M. S. Krammer https://orcid.org/0000-0002-5773-9514

## ENDNOTES

<footnote n="1">¹ Prior studies have used the Environmental, Social, and Governance (ESG) framework to capture firms' non-financial performance. Nonetheless, we choose not to focus on the “G” component, since it mostly represents actions directed towards the board of directors or management, making it structurally different from the “ES.”</footnote>
## REFERENCES

Aguilera, R. V., Marano, V., & Haxhi, I. (2019). International corporate governance: A review and opportunities for future research. *Journal of International Business Studies, 50*, 457–498.

Ahmadsimab, A., & Chowdhury, I. (2021). Managing tensions and divergent institutional logics in firm-NPO partnerships. *Journal of Business Ethics, 168*(3), 651–670.

Altomonte, C., & Rungi, A. (2013). Business groups as hierarchies of firms: determinants of vertical integration and performance. ECB Working Paper No. 1554. http://dx.doi.org/10.2139/ssrn.2269638

Ararat, M., Colpan, A. M., & Matten, D. (2018). Business groups and corporate responsibility for the public good. *Journal of Business Ethics, 153*(4), 911–929.

Bae, K., Kang, J., & Kim, J. (2002). Tunneling or value added? Evidence from mergers by Korean business groups. *The Journal of Finance, 57*(6), 2695–2740.

Bae, S. C., Kwon, T. H., & Lee, J. W. (2011). Does corporate diversification by business groups create value? Evidence from Korean chaebols. *Pacific-Basin Finance Journal, 19*(5), 535–553.

Belderbos, R., & Sleuwaegen, L. (1996). Japanese firms and the decision to invest abroad: business groups and regional core networks. *The review of Economics and Statistics, 78*, 214–220.

Belenzon, S., & Berkovitz, T. (2010). Innovation in business groups. *Management Science, 56*(3), 519–535.

Belenzon, S., Berkovitz, T., & Rios, L. A. (2013). Capital markets and firm organization: How financial development shapes European corporate groups. *Management Science, 59*(6), 1326–1343.

Belenzon, S., Hashai, N., & Pataconni, A. (2019). The architecture of attention: Group structure and subsidiary autonomy. *Strategic Management Journal, 40*(10), 1610–1643.

<footnote n="2">² Prior studies have used the ESG framework to capture firms' non-financial performance. Nonetheless, we choose not to focus on the “G” component, since it mostly represents actions directed towards the board of directors or management, making it structurally different from the “ES.”</footnote>

<footnote n="3">³ We consider reputational effects to be strongest with listed firms, in line with Chittoor et al. (2015).</footnote>

<footnote n="4">⁴ This is when the Global Reporting Initiative (GRI) shifted from guidelines to establishing the first global standards for sustainability reporting. By choosing this cut-off point, we ensure that the influence of standardization on our analysis is avoided.</footnote>

<footnote n="5">⁵ For the missing data in the World Economic Forum-Competitiveness Report between the years 2003 and 2005, we coded with the average of non-missing values for the same country over the sample period.</footnote>

<footnote n="6">⁶ The characteristics of our final dataset are in line with Masulis et al. (2011), who use a dataset from 45 countries to examine family BGs around the world.</footnote>

<footnote n="7">⁷ Independence indicators assess the degree of independence of a firm with regards to its shareholders with scores ranging from “A—independent firms” with no more than 25% direct or indirect ownership and “B,” “C,” “D,” and “U” with having one or more known or unknown shareholders with an ownership percentage above 25%–50%, or above 50%, respectively.</footnote>

<footnote n="8">⁸ In the computation of the formal and informal institutions indices, for a significant number of countries, we have missing values for the entire sample period. Whenever the value of an item is missing for a country, we replaced the value with the mean value of all other countries in the same classification on the Inglehart-Welzel World Cultural Map.</footnote>

<footnote n="9">⁹ In our analysis, we constrained the number of levels to a maximum of 10.</footnote>

<footnote n="10">¹⁰ As the BG Hierarchy is measured by using the natural logarithm, we converted the average value into an actual number. Accordingly, affiliated firms' average subsidiary layer in the ownership chain is 3 out of 10.</footnote>

<footnote n="11">¹¹ As BG Diversification is measured by using the natural logarithm, we converted the average value into an actual number. Accordingly, affiliated firms operate in five different industries.</footnote>

<footnote n="12">¹² To avoid any potential bias that might be resulted from the use of a long list of country controls, in additional tests, we employ country-fixed effects instead of country controls. All analyses reported in Table 3 yield statistically similar results.</footnote>
<figure><img src="image_18.png" /></figure>

Bena, J., & Ortiz-Molina, H. (2013). Pyramidal ownership and the creation of new firms. *Journal of Financial Economics*, **108**(3), 798-821.

Birhanu, A. G., & Wezel, F. C. (2022). The competitive advantage of affiliation with business groups in the political environment: Evidence from the Arab Spring. *Strategic Organization*, **20**(2), 389-411.

Botero, J. C., Djankov, S., Porta, R. L., Lopez-de-Silanes, F., & Shleifer, A. (2004). The regulation of labor. *The Quarterly Journal of Economics*, **119**(4), 1339-1382.

Bothello, J., Ioannou, I., Porumb, V., & Zengin-Karaibrahimoglu, Y. (2023). Decoupling within business groups and the risk of perceived greenwashing. *Strategic Management Journal*, **44**(13), 3217-3251.

Bouquet, C., & Birkinshaw, J. (2008). Weight versus voice: How foreign subsidiaries gain attention from corporate headquarters. *Academy of Management journal*, **51**(3), 577-601.

Brammer, S. J., & Pavelin, S. (2006). Corporate reputation and social performance: The importance of fit. *Journal of Management Studies*, **43**(3), 435-455.

Bucheli, M., Salvaj, E., & Kim, M. (2019). Better together: How multinationals come together with business groups in times of economic and political transitions. *Global Strategy Journal*, **9**(2), 176-207.

Cahan, S. F., Rahman, A., & Perera, H. (2005). Global diversification and corporate disclosure. *Journal of International Accounting Research*, **4**(1), 73-93.

Carney, M. (2008). *Asian business groups: Context, governance and performance*. Chandos Publishing Limited.

Carney, M., Gedajlovic, E. R., Heugens, P. P. M. A. R., Van Essen, M., & Van Oosterhout, J. (2011). Business group affiliation, performance, context, and strategy: A meta-analysis. *Academy of Management Journal*, **54**(3), 437-460.

Carney, M., Van Essen, M., Estrin, S., & Shapiro, D. (2018). Business groups reconsidered: beyond paragons and parasites. *Academy of Management Perspectives*, **32**(4), 493-516.

Castaldi, S., Gubbi, S. R., Kunst, V. E., & Beugelsdijk, S. (2019). Business group affiliation and foreign subsidiary performance. *Global Strategy Journal*, **9**(4), 595-617.

Castellacci, F. (2015). Institutional voids or organizational resilience? Business groups, innovation, and market development in Latin America. *World Development*, **70**, 43-58.

Chang, S. J., & Hong, J. (2000). Economic performance of group-affiliated companies in Korea: Intragroup resource sharing and internal business transactions. *Academy of Management Journal*, **43**(3), 429-448.

Chang, S. J. (2006). Korean business groups: The financial crisis and the restructuring of chaebols. *Business groups in East Asia: Financial crisis, restructuring, and new growth*, 52-69.

Chen, Y. Y., & Jaw, Y. L. (2014). How do business groups' small world networks effect diversification, innovation, and internationalization? *Asia Pacific Journal of Management*, **31**, 1019-1044.

Chittoor, R., Kale, P., & Puranam, P. (2015). Business groups in developing capital markets: Towards a complementarity perspective. *Strategic Management Journal*, **36**(9), 1277-1296.

Cho, E., Chun, S., & Choi, D. (2015). International diversification, corporate social responsibility, and corporate governance: Evidence from Korea. *Journal of Applied Business Research (JABR)*, **31**(2), 743-764.

Cho, Y., Driffield, N., Banerjee, S., & Park, B. I. (2023). Returns to internationalization: Business group-affiliated firms vs standalone firms. *Management International Review*, **63**(4), 603-639.

Choi, J. J., Jo, H., Kim, J., & Kim, M. S. (2018). Business groups and corporate social responsibility. *Journal of Business Ethics*, **153**(4), 931-954.

Choi, J., & Wang, H. (2009). Stakeholder relations and the persistence of corporate financial performance. *Strategic Management Journal*, **30**(8), 895-907.

Claessens, S., Djankov, S., Fan, J. P. H., & Lang, L. H. P. (2002). Disentangling the incentive and entrenchment effects of large shareholdings. *The Journal of Finance*, **57**(6), 2741-2771.

Colli, A., & Colpan, A. M. (2016). Business groups and corporate governance: Review, synthesis, and extension. *Corporate Governance: An International Review*, **24**(3), 274-302.

Commander, S. J., Estrin, S., & De Silva, T. (2023). Political connections, Business Groups and Innovation. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4390224

Cornelius, N., Todres, M., Janjuha-Jivraj, S., Woods, A., & Wallace, J. (2008). Corporate social responsibility and the social enterprise. *Journal of Business Ethics*, **81**, 355-370.

Crifo, P., Escreg-Olmedo, E., & Mottis, N. (2019). Corporate governance as a key driver of corporate sustainability in France: The role of board members and investor relations. *Journal of Business Ethics*, **159**, 1127-1146.
Cucculelli, M., & Marchionne, F. (2012). Market opportunities and owner identity: Are family firms different? *Journal of Corporate Finance*, 18(3), 476-495.

Cuervo-Cazurra, A. (2006). Business groups and their types. *Asia Pacific Journal of Management*, 23(4), 419-437.

Cuypers, I. R. P., Hennart, J.-F., Silverman, B. S., & Ertug, G. (2021). Transaction cost theory: Past progress, current challenges, and suggestions for the future. *Academy of Management Annals*, 15(1), 111-150.

Dau, L. A., Morck, R., & Yeung, B. Y. (2021). Business groups and the study of international business: A Coasean synthesis and extension. *Journal of International Business Studies*, 52(2), 161-211.

de Villiers, C., Jia, J., & Li, Z. (2022). Corporate social responsibility: A review of empirical research using Thomson Reuters Asset4 data. *Accounting & Finance*, 62(4), 4523-4568.

Delgado-García, J. B., De Quevedo-Puente, E., & De La Fuente-Sabaté, J. M. (2010). The impact of ownership structure on corporate reputation: Evidence from Spain. *Corporate Governance: An International Review*, 18(6), 540-556.

Delmas, M., & Toffel, M. W. (2004). Stakeholders and environmental management practices: An institutional framework. *Business strategy and the Environment*, 13(4), 209-222.

Desender, K., & Epure, M. (2021). The pressure behind corporate social performance: Ownership and institutional configurations. *Global Strategy Journal*, 11(2), 210-244.

Dikolli, S. S., Frank, M. M., Guo, Z. M., & Lynch, L. J. (2022). Walk the talk: ESG mutual fund voting on shareholder proposals. *Review of Accounting Studies*, 27(3), 864-896.

Fisman, R., & Khanna, T. (2004). Facilitating development: The role of business groups. *World Development*, 32(4), 609-628.

Gao, C., Zuzul, T., Jones, G., & Khanna, T. (2017). Overcoming institutional voids: A reputation-based view of long run survival. *Strategic Management Journal*, 38(11), 2147-2167.

Gaur, A. S., & Kumar, V. (2009). International diversification, business group affiliation and firm performance: Empirical evidence from India. *British Journal of Management*, 20(2), 172-186.

George, G., Howard-Grenville, J., Joshi, A., & Tihanyi, L. (2016). Understanding and tackling societal grand challenges through management research. *Academy of Management Journal*, 59(6), 1880-1895.

Golesorkhi, S., Mersland, R., Randøy, T., & Shenkar, O. (2019). The performance impact of informal and formal institutional differences in cross-border alliances. *International Business Review*, 28(1), 104-118.

Granovetter, M. (1995). Coase revisited: Business groups in the modern economy. *Industrial and Corporate Change*, 4(1), 93-130.

Granovetter, M. (2005). Business groups and social organization. In N. J. Smelser & R. Swedberg (Eds.), *Handbook of economic sociology* (pp. 429-450). Princeton University Press.

Gu, Q., Lu, J. W., & Chung, C. N. (2019). Incentive or disincentive? A socioemotional wealth explanation of new industry entry in family business groups. *Journal of Management*, 45(2), 645-672.

Guillen, M. F. (2000). Business groups in emerging economies: A resource-based view. *Academy of Management Journal*, 43(3), 362-380.

Habib, A., & Hasan, M. M. (2019). Corporate social responsibility and cost stickiness. *Business & Society*, 58(3), 453-492.

Hainmueller, J. (2012). Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies. *Political Analysis*, 20(1), 25-46.

Helmke, G., & Rosenbluth, F. (2009). Regimes and the rule of law: Judicial independence in comparative perspective. *Annual Review of Political Science*, 12, 345-366.

Hofstede, G. (2001). *culture's consequences – second edition: Comparing values, behaviors, institutions and organizations across nations*. London: Sage.

Hoskisson, R. E., Johnson, R. A., Tihanyi, L., & White, R. E. (2005). Diversified business groups and corporate refocusing in emerging economies. *Journal of Management*, 31(6), 941-965.

Hoskisson, R. E., Wright, M., Filatotchev, I., & Peng, M. W. (2013). Emerging multinationals from mid-range economies: The influence of institutions and factor markets. *Journal of Management Studies*, 50(7), 1295-1321.

Ioannou, I., & Serafeim, G. (2012). What drives corporate social performance? The role of nation-level institutions. *Journal of International Business Studies*, 43(9), 834-864.

Iona, A., Leonida, L., & Navarra, P. (2013). Business group affiliation, innovation, internationalization, and performance: A semiparametric analysis. *Global Strategy Journal*, 3(3), 244-261.
<figure><img src="image_19.png" /></figure>

Jiménez, A., Hanoteau, J., & Barkemeyer, R. (2022). E-procurement and firm corruption to secure public contracts: The moderating role of governance institutions and supranational support. *Journal of Business Research, 149*, 640–650.

Joe, D. Y., & Oh, F. D. (2018). Spillover effects within business groups: The case of Korean chaebols. *Management Science, 64*(3), 1396–1412.

Kandel, E., Kosenko, K., Morck, R., & Yafeh, Y. (2019). The Great Pyramids of America: A revised history of US business groups, corporate ownership, and regulation, 1926–1950. *Strategic Management Journal, 40*(5), 781–808.

Kang, J. (2013). The relationships between corporate diversification and corporate social performance. *Strategic Management Journal, 34*(1), 94–109.

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2009). Governance matters VIII: Aggregate and individual governance indicators, 1996-2008. *World bank policy research working paper, 4978*. https://papers.ssrn.com/sol3/papers.cfm?Abstract_id=1424591

Kaufmann, W., Hooghiemstra, R., & Feeney, M. K. (2018). Formal institutions, informal institutions, and red tape: A comparative study. *Public Administration, 96*(2), 386–403.

Khanna, T. (2000). Business groups and social welfare in emerging markets: Existing evidence and unanswered questions. *European Economic Review, 44*(4–6), 748–761.

Khanna, T., & Palepu, K. (1999). Policy shocks, market intermediaries, and corporate strategy: The evolution of business groups in Chile and India. *Journal of Economics and Management Strategy, 8*(2), 271–310.

Khanna, T., & Palepu, K. (2000). Is group affiliation profitable in emerging markets? An analysis of diversified Indian business groups. *The Journal of Finance, 55*(2), 867–891.

Khanna, T., & Pileup, K. G. (2010). *Winning in emerging markets: A road map for strategy and execution*. Harvard Business Press.

Khanna, T., & Rivkin, J. W. (2001). Estimating the performance effects of business groups in emerging markets. *Strategic Management Journal, 74*(1), 45–74.

Khanna, T., & Yafeh, Y. (2005). Business groups and risk sharing around the world. *The Journal of Business, 78*(1), 301–340.

Khanna, T., & Yafeh, Y. (2007). Business groups in emerging markets: Paragons or parasites? *Journal of Economic Literature, 45*(2), 331–372.

Kölbel, J. F., Busch, T., & Jancso, L. M. (2017). How media coverage of corporate social irresponsibility increases financial risk. *Strategic Management Journal, 38*(11), 2266–2284.

Kolk, A., & Van Tulder, R. (2010). International business, corporate social responsibility and sustainable development. *International Business Review, 19*(2), 119–125.

Krammer, S. M. (2016). The role of diversification profiles and dyadic characteristics in the formation of technological alliances: Differences between exploitation and exploration in a low-tech industry. *Research Policy, 45*(2), 517–532.

Krammer, S. M. (2018). A double-edged sword? The antipodal effects of institutional distance on partner selection in cross-border alliances. *Journal of World Business, 53*(6), 930–943.

Krammer, S. M. (2019). Greasing the wheels of change: Bribery, institutions, and new product introductions in emerging markets. *Journal of Management, 45*(5), 1889–1926.

Krammer, S. (2024). No planet B available! A review of the climate book: The facts and solutions by Greta Thunberg. *Journal of Business Ethics, 194*, 229–232. https://doi.org/10.1007/s10551-023-05594-8

Krammer, S. M., & Jimenez, A. (2020). Do political connections matter for firm innovation? Evidence from emerging markets in Central Asia and Eastern Europe. *Technological Forecasting and Social Change, 151*, 119669.

Krammer, S. M. S., Lashitew, A. A., Doh, J. P., & Bapuji, H. (2023). Income inequality, social cohesion, and crime against businesses: Evidence from a global sample of firms. *Journal of International Business Studies, 54*, 385–400.

Lamin, A. (2013). Business groups as information resource: An investigation of business group affiliation in the Indian software services industry. *Academy of Management Journal, 56*(5), 1487–1509.

Lange, D., Lee, P. M., & Dai, Y. (2011). Organizational reputation: A review. *Journal of Management, 37*(1), 153–184.
La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (2006). What works in securities laws? *The journal of finance*, *61*(1), 1–32.

Lee, K., Choo, K., & Yoon, M. (2016). Comparing the productivity impacts of knowledge spillovers from network and arm's length industries: findings from business groups in Korea. *Industrial and Corporate Change*, *25*(3), 407–427.

Leff, N. H. (1978). Industrial organization and entrepreneurship in the developing countries: The economic groups. *Economic Development and Cultural Change*, *26*(4), 661–675.

Lincoln, J. R., & Sargent, M. (2018). Business groups as networks. In A. M. Colpan & T. Hikino (Eds.), *Business groups in the west: Origins, evolution, and resilience*. Oxford University Press. https://doi.org/10.1093/oso/9780198717973.003.0004

Lu, H., Liu, X., & Osiyevskyy, O. (2023). Doing safe while doing good: Slack, risk management capabilities, and the reliability of value creation through CSR. *Strategic Organization*, *21*(4), 874–904.

Luo, J., & Kaul, A. (2019). Private action in public interest: The comparative governance of social issues. *Strategic Management Journal*, *40*(4), 476–502.

Lys, T., Naughton, J. P., & Wang, C. (2015). Signaling through corporate accountability reporting. *Journal of Accounting and Economics*, *60*(1), 56–72.

Mahmood, I., Chung, C. N., & Mitchell, W. (2017). Political connections and business strategy in dynamic environments: How types and destinations of political ties affect business diversification in closed and open political economic contexts. *Global Strategy Journal*, *7*(4), 375–399.

Manikandan, K. S., & Ramachandran, J. (2015). Beyond institutional voids: Business groups, incomplete markets and organizational form. *Strategic Management Journal*, *36*, 598–617.

Masulis, R. W., Pham, P. K., & Zein, J. (2011). Family business groups around the world: Financing advantages, control motivations, and organizational choices. *The Review of Financial Studies*, *24*(11), 3556–3600.

Matten, D., & Moon, J. (2008). ‘Implicit’ and ‘Explicit’ CSR: A conceptual framework for a comparative understanding of corporate social responsibility. *Academy of Management Review*, *33*(2), 404–424.

Mitton, T. (2002). A cross-firm analysis of the impact of corporate governance on the East Asian financial crisis. *Journal of financial economics*, *64*(2), 215–241.

Montiel, I., & Husted, B. W. (2009). The adoption of voluntary environmental management programs in Mexico: First movers as institutional entrepreneurs. *Journal of Business Ethics*, *88*, 349–363.

Morck, R., Wolfenzon, D., & Yeung, B. (2005). Corporate governance, economic entrenchment, and growth. *Journal of Economic Literature*, *43*, 655–720.

Morck, R., & Nakamura, M. (2005). A frog in a well knows nothing of the ocean: A history of corporate ownership in Japan. In *A history of corporate governance around the world: Family business groups to professional managers* (pp. 367–466). University of Chicago Press.

Morck, R., & Yeung, B. (2003). Agency problems in large family business groups. *Entrepreneurship theory and practice*, *27*(4), 367–382.

Mukherjee, D., Makarius, E. E., & Stevens, C. E. (2018). Business group reputation and affiliates’ internationalization strategies. *Journal of World Business*, *53*(2), 93–103.

Muralidharan, E., & Pathak, S. (2017). Informal institutions and international entrepreneurship. *International Business Review*, *26*(2), 288–302.

Napier, E., Knight, G., Luo, Y., & Delios, A. (2023). Corporate social performance in international business. *Journal of International Business Studies*, *54*(1), 61–77.

Nason, R. S., & Bothello, J. (2023). Far from void: How institutions shape growth in the informal economy. *Academy of Management Review*, *48*(3), 485–503.

Ng, A., Ibrahim, M. H., & Mirakhor, A. (2015). Ethical behavior and trustworthiness in the stock market-growth nexus. *Research in International Business and Finance*, *33*, 44–58.

North, D. C. (1991). Towards a theory of institutional change. *Quarterly Review of Economics and Business*, *31*(4), 3–12.

Odziemkowska, K., & Henisz, W. J. (2021). Webs of influence: Secondary stakeholder actions and cross-national corporate social performance. *Organization Science*, *32*(1), 233–255.

Pathak, S., & Muralidharan, E. (2016). Informal institutions and their comparative influences on social and commercial entrepreneurship: The role of in-group collectivism and interpersonal trust. *Journal of Small Business Management*, *54*, 168–188.
<figure><img src="image_20.png" /></figure>

Peng, M. W., Wang, D. Y. L., & Jiang, Y. (2008). An institution-based view of international business strategy: A focus on emerging economies. *Journal of International Business Studies, 39*(5), 920-936.

Perotti, E. C., & Gelfer, S. (2001). Red barons or robber barons? Governance and investment in Russian financial-industrial groups. *European Economic Review, 45*(9), 1601-1617.

Ramachandran, J., Gopal, S., & Manikandan, K. S. (2021). Are there limits to diversification in emerging economies? Distinguishing between firm? level and business group strategies. *Journal of Management Studies, 58*, 1532-1568.

Ramanujam, V., & Varadarajan, P. (1989). Research on corporate diversification: A synthesis. *Strategic Management Journal, 10*(January), 523-551.

Rees, W., & Rodionova, T. (2014). The influence of family ownership on corporate social responsibility: An international analysis of publicly listed companies. *Corporate Governance: An International Review, 23*(3), 184-202.

Ringov, D., & Zollo, M. (2007). The impact of national culture on corporate social performance. *Corporate Governance: The international journal of business in society, 7*(4), 476-485.

Roberts, P. W., & Greenwood, R. (1997). Integrating transaction cost and institutional theories: Toward a constrained-efficiency framework for understanding organizational design adoption. *Academy of Management Review, 22*(2), 346-373.

Rodriguez, P., Siegel, D. S., Hillman, A., & Eden, L. (2006). Three lenses on the multinational enterprise: Politics, corruption, and corporate social responsibility. *Journal of International Business Studies, 37*, 733-746.

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. *Biometrika, 70*(1), 41-55.

Saka-Helmhout, A., Chappin, M., & Vermeulen, P. (2020). Multiple paths to firm innovation in sub-Saharan Africa: How informal institutions matter. *Organization Studies, 41*(11), 1551-1575.

Seitanidi, M. M., & Crane, A. (2009). Implementing CSR through partnerships: Understanding the selection, design and institutionalisation of nonprofit-business partnerships. *Journal of Business Ethics, 85*, 413-429.

Seyoum, B. (2009). Formal institutions and foreign direct investment. *Thunderbird International Business Review, 51*(2), 165-181.

Shrivastava, P. (1995). The role of corporations in achieving ecological sustainability. *Academy of Management Review, 20*(4), 936-960.

Siegel, J., & Choudhury, P. (2012). A reexamination of tunneling and business groups: New data and new methods. *The Review of Financial Studies, 25*(6), 1763-1798.

Silver, B. D., & Dowley, K. M. (2000). Measuring political culture in multiethnic societies: Reaggregating the World Values Survey. *Comparative Political Studies, 33*(4), 517-550.

Su, W., & Tan, D. (2018). Business groups and tax havens. *Journal of Business Ethics, 153*(4), 1067-1081.

Testoni, M., Sakakibara, M., & Chen, M. K. (2022). Face-to-face interactions and the returns to acquisitions: Evidence from smartphone geolocational data. *Strategic Management Journal, 43*(13), 2669-2702.

Tolmie, C. R., Lehnert, K., & Zhao, H. (2020). Formal and informal institutional pressures on corporate social responsibility: A cross-country analysis. *Corporate Social Responsibility and Environmental Management, 27*(2), 786-802.

Trahan, R. T., & Jantz, B. (2023). What is ESG? Rethinking the “E” pillar. *Business Strategy and the Environment, 32*, 4382-4391.

Waddock, S. A., & Graves, S. B. (1997). The corporate social performance-financial performance link. *Strategic Management Journal, 18*(4), 303-319.

Waldman, D. A., Siegel, D. S., & Javidan, M. (2006). Components of CEO transformational leadership and corporate social responsibility. *Journal of Management Studies, 43*(8), 1703-1725.

Wang, J. C., Yi, J., Zhang, X., & Peng, M. W. (2022). Pyramidal ownership and SOE innovation. *Journal of Management Studies, 59*(7), 1839-1868.

Webb, J. W., Ireland, R. D., & Ketchen, D. J., Jr. (2014). Toward a greater understanding of entrepreneurship and strategy in the informal economy. *Strategic Entrepreneurship Journal, 8*(1), 1-15.

Wiessner, Y. T., Giuliani, E., Wijen, F., & Doh, J. (2024). Towards a more comprehensive assessment of FDI's societal impact. *Journal of International Business Studies, 55*(1), 1-21.

Williamson, O. E. (1981). The economics of organization: The transaction cost approach. *American Journal of Sociology, 87*(3), 548-577.
Wood, D. J. (1991). Corporate social performance revisited. *Academy of Management Review*, *16*(4), 691–718.

Yiu, D., Bruton, G. D., & Lu, Y. (2005). Understanding business group performance in an emerging economy: Acquiring resources and capabilities in order to prosper. *Journal of Management Studies*, *42*(1), 183–206.

Yiu, D. W., Lu, Y., Bruton, G. D., & Hoskisson, R. E. (2007). Business groups: An integrated model to focus future research. *Journal of Management Studies*, *44*(8), 1551–1579.

Yiu, D., & Makino, S. (2002). The choice between joint venture and wholly owned subsidiary: An institutional perspective. *Organization Science*, *13*(6), 667–683.

**How to cite this article:** Krammer, S. M. S., Porumb, V.-A., Zengin-Karaibrahimoglu, Y., & Bothello, J. (2024). Beacons not burdens: Business groups and corporate social performance around the world. *Global Strategy Journal*, *14*(4), 709–753. https://doi.org/10.1002/gsj.1515
<figure><img src="image_21.png" /></figure>

APPENDIX A: ADDITIONAL INFORMATION

<table><caption>TABLE A1 Variable definitions, measures, and data sources.</caption><thead><tr><th>Category</th><th>Measure</th><th>Measurement</th><th>Source</th></tr></thead><tbody><tr><td>CSP</td><td>CSP</td><td>The equal-weighted rating of a firm's environmental and social performance</td><td>Thomson Reuters-Refinitiv ESG</td></tr><tr><td>BGs</td><td>BG Affiliation</td><td>An Indicator variable that takes the value of 1 if the firm is affiliated with a business group and 0 otherwise</td><td>ORBIS (BvD)</td></tr><tr><td></td><td>BG Diversification</td><td>The natural logarithm of the number of four-digit SIC codes the company operates in</td><td>ORBIS (BvD)</td></tr><tr><td></td><td>BG Hierarchy</td><td>The natural logarithm of the number of the maximum level of subsidiaries</td><td>ORBIS (BvD)</td></tr><tr><td rowspan="2">Formal and informal institutions</td><td>Formal Inst</td><td>An index number indicating the strength of formal institutions. To construct the index for formal institutions, we use factor analysis based on two variables Ethical Behavior and Protecting Minority Shareholders derived from the Global Competitiveness Index (GCI)</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Informal Inst</td><td>An index number indicating the strength of informal institutions. To construct the index for informal institutions, we use factor analysis based on two variables: Level of Democracy (V114_polit_right) and Importance of Society (V74 good_society) from the World Value Survey (WVS)</td><td>World Value Surveys (WVS)</td></tr><tr><td rowspan="7">Country-specific variables</td><td>Competition</td><td>The weighted average of domestic competition and foreign competition in a country</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Anti-self-dealing index</td><td>Average of ex ante and ex post private control of self-dealing</td><td>La Porta et al. (2006)</td></tr><tr><td>Left/center ideology</td><td>The Chief executive and largest party in Congress have a left/center political orientation</td><td>Botero et al. (2004)</td></tr><tr><td>Union density</td><td>The percentage of the total workforce affiliated with labor unions</td><td>Botero et al. (2004)</td></tr><tr><td>Labor market efficiency</td><td>The efficiency and flexibility of the labor market</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Country debt over assets</td><td>The average debt over assets ratio for all firms within a country-year</td><td>Worldscope</td></tr><tr><td>SRI index</td><td>An indicator variable that takes the value of 1 for countries where a socially responsible stock market index exists, 0 otherwise.</td><td>World Federation of Exchanges</td></tr><tr><td></td><td>Power distance index</td><td>The extent to which the less powerful members of organizations and institutions accept and expect that power is distributed unequally</td><td>Hofstede (2001)</td></tr></tbody></table>

(Continues)
<table><caption>TABLE A1 (Continued)</caption><thead><tr><th>Category</th><th>Measure</th><th>Measurement</th><th>Source</th></tr></thead><tbody><tr><td rowspan="10">Firm-specific variables</td><td>Individualism</td><td>The degree to which individuals are integrated into groups</td><td>Hofstede (2001)</td></tr><tr><td>Quality of infrastructure</td><td>The general state of infrastructure (e.g., transport, communications, and energy) in the country</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Balance of trade</td><td>Exports as a percentage of GDP—Imports as a percentage of GDP</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Trade</td><td>Exports as a percentage of GDP + Imports as a percentage of GDP</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Market size</td><td>A combination of country size and foreign markets</td><td>World Economic Forum-Competitiveness Dataset (2006–2015)</td></tr><tr><td>Firm size</td><td>The natural logarithm of total assets</td><td>Worldscope (WC02999)</td></tr><tr><td>Return on assets (ROA)</td><td>Industry-adjusted net income over total assets</td><td>Worldscope (WC08326)</td></tr><tr><td>Leverage</td><td>The ratio of total debt to total asset</td><td>Worldscope (WC08236)</td></tr><tr><td>Volatility</td><td>Daily stock return volatility over the fiscal year</td><td>Worldscope (WC08806)</td></tr><tr><td>Market-to-book value</td><td>The market value of equity over the book value of equity calculated at the fiscal year-end</td><td>Worldscope (MTVB)</td></tr><tr><td>Closely held shares</td><td>Percentage of shares held by investors owing more than 5%</td><td>Worldscope (WC08021)</td></tr><tr><td>Foreign shareholding</td><td>Percentage of shares held by foreign investors</td><td>Thomson Reuters-Refinitiv Eikon (NOSHFR)</td></tr><tr><td>Institutional shareholding</td><td>Percentage of shares held by investment firms</td><td>Thomson Reuters-Refinitiv Eikon (NOSHIC)</td></tr><tr><td>Reputation monitoring</td><td>An indicator variable that takes the value of 1 if the company monitors its reputation or its relations with communities, 0 otherwise.</td><td>Thomson Reuters-Refinitiv ESG</td></tr><tr><td>CSR award</td><td>An indicator variable that takes the value of 1 if the company received an award for its social, ethical, community, or environmental activities or performance, 0 otherwise.</td><td>Thomson Reuters-Refinitiv ESG</td></tr></tbody></table>

Abbreviations: BGs, business groups; BvD, Bureau van Dijk; GDP, gross domestic product.
<figure><img src="image_22.png" /></figure>

<table><caption>TABLE A2 Factor analysis—formal institutions.</caption><thead><tr><th colspan="5">Panel A: Principal-component factors (unrotated)</th></tr><tr><th>Factor</th><th>Eigenvalue</th><th>Difference</th><th>Proportion</th><th>Cumulative</th></tr></thead><tbody><tr><td>Factor1</td><td>1.704</td><td>1.409</td><td>0.852</td><td>0.852</td></tr><tr><td>Factor2</td><td>0.295</td><td></td><td>0.147</td><td>1</td></tr></tbody><tfoot><tr><td colspan="5">LR test: independent versus saturated: χ<sup>2</sup>(1) = 2.2e+04 Prob > χ<sup>2</sup> = 0.0000</td></tr></tfoot></table><table><thead><tr><th colspan="5">Panel B: Factor loadings (pattern matrix) and unique variances</th></tr><tr><th>Variable</th><th>Factor1</th><th>Uniqueness</th></tr></thead><tbody><tr><td>Ethical Behavior</td><td>0.9233</td><td>0.1475</td></tr><tr><td>Protecting Minority Shareholders</td><td>0.9233</td><td>0.1475</td></tr></tbody><thead><tr><th colspan="5">Panel C: Rotated orthogonal varimax (Kaiser off)</th></tr><tr><th>Factor</th><th>Variance</th><th>Difference</th><th>Proportion</th><th>Cumulative</th></tr></thead><tbody><tr><td>Forml_Inst</td><td>1.751</td><td>0.243</td><td>0.135</td><td>0.135</td></tr></tbody><tfoot><tr><td colspan="5">LR test: independent versus saturated: χ<sup>2</sup>(1) = 2.2e+04 Prob > χ<sup>2</sup> = 0.0000</td></tr></tfoot></table>

<table><caption>TABLE A3 Factor analysis—informal institutions.</caption><thead><tr><th colspan="5">Panel A: Principal-component factors (unrotated)</th></tr><tr><th>Factor</th><th>Eigenvalue</th><th>Difference</th><th>Proportion</th><th>Cumulative</th></tr></thead><tbody><tr><td>Factor1</td><td>1.004</td><td>0.008</td><td>0.502</td><td>0.502</td></tr><tr><td>Factor2</td><td>0.295</td><td></td><td>0.147</td><td>1</td></tr></tbody><tfoot><tr><td colspan="5">LR test: independent versus saturated: χ<sup>2</sup>(1) = 0.53 Prob > χ<sup>2</sup> = 0.4659</td></tr></tfoot></table><table><thead><tr><th>Variable</th><th>Factor1</th><th>Uniqueness</th></tr></thead><tbody><tr><td>Level of Democracy (V114_polit_right)</td><td>0.7085</td><td>0.498</td></tr><tr><td>Importance of Society (V74_good_society)</td><td>0.7085</td><td>0.498</td></tr></tbody><thead><tr><th colspan="5">Panel C: Rotated orthogonal varimax (Kaiser off)</th></tr><tr><th>Factor</th><th>Variance</th><th>Difference</th><th>Proportion</th><th>Cumulative</th></tr></thead><tbody><tr><td>Forml_Inst</td><td>1.00406</td><td></td><td>0.502</td><td>0.502</td></tr></tbody><tfoot><tr><td colspan="5">LR test: independent versus saturated: χ<sup>2</sup>(1) = 0.53 Prob > χ<sup>2</sup> = 0.4659</td></tr></tfoot></table>
<table><caption>TABLE A4 Example of hierarchical structure—TAV Havalimanlari Holding A.S.ª</caption><thead><tr><th>Subsidiaries</th><th>Country</th><th>Total (%)</th><th>Level of ownership</th><th>Level of subsidiary within the group</th></tr></thead><tbody><tr><td>1. AVIATOR NETHERLANDS B.V.</td><td>NL</td><td>100.00</td><td>1</td><td>2</td></tr><tr><td>1.1. ZAIC—A Limited</td><td>GB</td><td>15.00<sup>b</sup></td><td>2</td><td>3</td></tr><tr><td>1.1.1. Medunarodna Zracna Luka Zagreb D.D.</td><td>HR</td><td>100.00</td><td>3</td><td>4</td></tr><tr><td>1.1.1.1. MZLZ—Ugostiteljstvo D.O.O.</td><td>HR</td><td>100.00</td><td>4</td><td>5</td></tr><tr><td>1.1.1.2. MZLZ—Zastita D.O.O.</td><td>HR</td><td>100.00</td><td>4</td><td>5</td></tr><tr><td>1.1.1.3. MZLZ—Zemaljske Usluge D.O.O.</td><td>HR</td><td>100.00</td><td>4</td><td>5</td></tr><tr><td>1.1.1.4. MZLZ Hrana D.O.O.</td><td>HR</td><td>100.00</td><td>4</td><td>5</td></tr><tr><td>1.1.2. Upravitelj Zra Ne Luke Zagreb</td><td>HR</td><td>21.00<sup>b</sup></td><td>3</td><td>4</td></tr><tr><td>2. Batumi Airport</td><td>GE</td><td>100.00</td><td>1</td><td>2</td></tr><tr><td>3. Havaalanlari Arac Kiralama ve Yolcu Tasimaciligi A.S.</td><td>TR</td><td>100.00</td><td>1</td><td>2</td></tr></tbody></table>

Abbreviation: BvD, Bureau van Dijk.

ªTAV Havalimanlari Holding A.S. has 76 subsidiaries, we tabulated only 10 subsidiaries for illustrative purposes. Nonetheless, none of the other subsidiaries have a level of subsidiary bigger than 5.

ᵇIndicated the direct % of ownership. The total percentage of ownership is not specified. However, the company has a BvD independence indicator of “B,” indicating that the firms qualify the filter of “at least 25 percent of a firm’s voting rights to establish the controlling shareholder.”
<figure><img src="image_23.png" /></figure>

<table><caption>TABLE A5 Selection of the matched sample.</caption><caption>Panel A: Logit analysis of the BG affiliation</caption><thead><tr><th>Dependent variable: BG Affiliation</th><th>Coefficient</th><th>t-Value</th></tr></thead><tbody><tr><td>Firm size</td><td>0.106***</td><td>(4.86)</td></tr><tr><td>Return on assets (ROA)</td><td>0.121***</td><td>(4.21)</td></tr><tr><td>Leverage</td><td>-0.064***</td><td>(-3.07)</td></tr><tr><td>Volatility</td><td>-0.074**</td><td>(-3.50)</td></tr><tr><td>Market-to-book value</td><td>3.817</td><td>(1.01)</td></tr><tr><td>Closely held shares</td><td>1.182***</td><td>(63.66)</td></tr><tr><td>Foreign shareholding</td><td>0.083***</td><td>(5.55)</td></tr><tr><td>Institutional shareholding</td><td>-0.006</td><td>(-0.36)</td></tr><tr><td>Reputation monitoring</td><td>0.114***</td><td>(2.71)</td></tr><tr><td>CSR award</td><td>-0.020</td><td>(-0.53)</td></tr><tr><td>Constant</td><td>-1.345***</td><td>(-16.74)</td></tr><tr><td>Industry fixed effect</td><td>Yes</td><td></td></tr><tr><td>Year-fixed effect</td><td>Yes</td><td></td></tr><tr><td>Pseudo R<sup>2</sup></td><td>0.2427</td><td></td></tr><tr><td>LR χ<sup>2</sup> (p-value)</td><td>7222.12 (.000)</td><td></td></tr><tr><td>Observations</td><td>29,886</td><td></td></tr></tbody></table>

<table><caption>Panel B: Descriptive statistics for the matched sample</caption><thead><tr><th rowspan="2">Determinants of BG Affiliation</th><th>(A)</th><th>(B)</th><th rowspan="2">%bias</th><th colspan="2">t-Test</th></tr><tr><th>BG</th><th>Non-BG</th><th>t</th><th>p > |t|</th></tr></thead><tbody><tr><td>Firm size</td><td>-0.015</td><td>-0.066</td><td>5.4</td><td>2.660</td><td>.008</td></tr><tr><td>ROA</td><td>0.040</td><td>0.036</td><td>0.6</td><td>0.310</td><td>.759</td></tr><tr><td>Leverage</td><td>-0.030</td><td>-0.017</td><td>-1.4</td><td>-0.720</td><td>.473</td></tr><tr><td>Volatility</td><td>-0.023</td><td>0.013</td><td>-3.7</td><td>-1.850</td><td>.065</td></tr><tr><td>Market-to-book value</td><td>-0.007</td><td>-0.007</td><td>1.1</td><td>0.540</td><td>.589</td></tr><tr><td>Closely held shares</td><td>0.669</td><td>0.749</td><td>-8.5</td><td>-4.230</td><td>.000</td></tr><tr><td>Foreign shareholding</td><td>0.226</td><td>0.266</td><td>-3.1</td><td>-1.560</td><td>.120</td></tr><tr><td>Institutional shareholding</td><td>-0.173</td><td>-0.176</td><td>0.3</td><td>0.160</td><td>.870</td></tr><tr><td>Reputation monitoring</td><td>0.265</td><td>0.254</td><td>2.4</td><td>1.170</td><td>.242</td></tr><tr><td>CSR award</td><td>0.437</td><td>0.425</td><td>2.4</td><td>1.200</td><td>.231</td></tr><tr><td>Observations</td><td colspan="2">9878</td><td></td><td></td><td></td></tr></tbody></table>

Note: ***, **, and * denote the significance level at 1%, 5%, and 10%. All continuous variables are standardized to have a mean value of zero and a standard deviation of one. All variables are described in Table A1 in Appendix A. t-Values are presented in parentheses.

Abbreviation: BG, business group.