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RESEARCH ARTICLE

OPEN ACCESS

# Does Institutional Ownership Structure Reduce Greenhouse Gas Emissions? An In-Depth Study of Corporations Social Responsibility of European-Listed Firms

Daniele Giordino<fnref n="1" /> ID | Elisa Ballesio<fnref n="1" /> ID | Aradhana Galgotia² | Laura Broccardo³ ID

**Correspondence:** Laura Broccardo (laura.broccardo@unito.it)

**Received:** 28 April 2025 | **Revised:** 18 September 2025 | **Accepted:** 1 October 2025

**Keywords:** carbon neutrality | environmental performance | greenhouse gas emission | institutional investors | ownership concentration

## ABSTRACT

Motivated by the growing attention and concerns surrounding climate change and the potential role of institutional investors' ownership concentration (OC) in reducing corporations' greenhouse gas (GHG) emissions, this article explores the relationship between various forms of institutional ownership and firms' GHG emission intensity. To do so, the authors employ an extensive dataset of 628 European-listed corporations with observations from 2015 to 2022. This manuscript method consists of linear regression models. This study's empirical results underline the positive and significant effect financial institutions, pension funds, governments, and foreign institutional investors' OC have on companies' GHG emissions. On the other hand, the regression models present empirical evidence suggesting a negative and significant effect between cross holdings OC and firms' GHG emissions. Finally, the authors identify a negative and non-significant relationship between “other” institutional investors and organizations' GHG emissions. These findings are robust since the authors have conducted several regression analyses with different approaches and have addressed potential endogeneity bias. The present article makes significant contributions to the scholarly literature and regulatory practice underlying the active role corporate governance and institutional investors have in supporting a carbon-neutral future.

## 1 | Introduction

The Earth's climate system is undergoing profound alterations caused by human activities (Wang et al. 2019; Wu et al. 2023). Over the last few decades, businesses' impact has become increasingly apparent, thus creating a sense of urgency amongst various stakeholders to establish policies (Li, Zhang, et al. 2021), laws, and practices aimed at reducing environmental degradation and promoting environmentally responsible behaviors and strategies (Battisti et al. 2022; Benlemlih and Yavaş 2023; Li, Zhang, et al. 2021; Muktadir-Al-Mukit and Bhaiyat 2023). In response to the preceding issue, the notion of carbon neutrality has garnered significant traction as a practical attempt at

reducing and mitigating the effects of climate change (Benlemlih and Yavaş 2023; Huovila et al. 2022; Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022). This led to the formulation of the Paris Agreement (UNFCCC 2015), promoting the objective of climate neutrality. In order to strengthen the goals and principles of the Paris Agreement, the European Union (EU) has developed the European Climate Law, which establishes the mandatory objective of achieving net zero by 2050 (European Commission 2023). In fact, scholars argue that the European Commission represents one of the major regulatory forces in advancing carbon neutrality and promoting environmental sustainability (Velte 2023). This underscores Europe as a prominent contextual setting for exploring the role of institutional

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© 2025 The Author(s). Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.

<footnote n="1">¹Department of Management “Valter Cantino”, University of Turin, Turin, Italy | ²School of Business, Galgotias University, Greater Noida,</footnote>

<footnote>India | ³Department of Management, University of Turin, Turin, Italy</footnote>
investors' inclusion of sustainability-related aspects (Li, Zhang, et al. 2021; Velte 2023). Specifically, the above-mentioned initiatives aim to mobilize and pressure various stakeholders into adopting greenhouse gas (GHG) emission reduction logics, thus fostering the diffusion of the carbon neutral economy (Awan et al. 2022).

According to scholarly research, institutional investors are amongst the most influential company stakeholders, as they control the largest portion of the capital market (Deegan 2019) and have the ability to guide entities toward integrating ethical, environmental, and social considerations into their practices and strategic orientation (Velte 2023; Wu et al. 2023). Despite their prominent role, scholars emphasize the need for further empirical research to clarify the relationship between institutional investors' ownership and organizations' strategic orientation and performance (Callahan et al. 2024; Drobetz et al. 2024; Rahim et al. 2024; Velte 2023; Velte 2024a). The above-discussed research gap is particularly evident with respect to the influence of institutional investors' OC on organizations' commitment to environmental and social sustainability (Breitenstein et al. 2021; Cheng et al. 2022; Giordino et al. 2024, 2025; Mishra 2022; Tonelli et al. 2025). While some studies have begun to address this issue, the available empirical evidence remains limited and fragmented, characterized by varying classifications of institutional investors and inconsistent findings (García-Sánchez, Rodríguez-Ariza, et al. 2020; Giordino et al. 2024, 2025; Tonelli et al. 2025; Velte 2023; Velte 2024a; Wei et al. 2024). For instance, several authors have tried to investigate the link between institutional investors' OC and corporate social responsibility (CSR) (Chen and Xie 2022; Mishra 2022), yet their findings remain inconsistent due to divergent categorizations of institutional investors and the heterogeneous measures employed to capture CSR. Part of the scholarly literature argues that institutional investors' OC has a positive impact on firms' environmental, social, and ethical practices (Breitenstein et al. 2021; Cheng et al. 2022; Giordino et al. 2024; Mishra 2022). On the other hand, some authors present empirical data corroborating the hypothesis that institutional investors' OC can negatively impact firms' CSR endeavors and disclosure (Velte 2023; Wei et al. 2024). Hence, the absence of agreement among authors and the conflicting evidence presented emphasizes the necessity for further empirical investigation that examines the impact of institutional investors' OC on organizations' environmental, social, and ethical practices. This inconsistency highlights the need for a more systematic and granular body of research that can provide clearer insights into the nature of the relationship between institutional investors' OC and organizations' commitment to environmental sustainability. Scholars hypothesize that the focus of most studies on institutional investors' OC as broad categories, rather than granular classifications, contributes to the contrasting results and limits the potential managerial and normative implications of previous research (Beck and Ferasso 2023; Callahan et al. 2024; Drobetz et al. 2024; Rahim et al. 2024; Velte 2023; Velte 2024a; Wang et al. 2023). Henceforth, in an effort to address the above-detailed limitations and research gaps, this manuscript examines the impact of institutional investors' OC on organizations' sustainability practices and performance by categorizing institutional investors into more heterogeneous and granular groups. Specifically, the authors classify institutional investors into six main categories, as suggested by

García-Sánchez, Rodríguez-Ariza, et al. (2020) and Giordino et al. (2024, 2025). These categories capture not only their investment time frames but also their horizons, objectives, needs, characteristics, influence, preferences, and management strategies (Callahan et al. 2024; Giordino et al. 2024, 2025; Tonelli et al. 2025; Velte 2023; Velte 2024a; Wang et al. 2023). The adopted categorization of institutional investors aims to provide a more detailed and comprehensive understanding of their role in firms' environmental performance, thereby addressing the limitations and research gaps of prior scholarly research (Callahan et al. 2024; Drobetz et al. 2024; Rahim et al. 2024; Velte 2023; Velte 2024a; Wang et al. 2023).

The current scholarly literature on institutional investors' OC primarily examines its potential association with organizations' CSR at an aggregate level, rather than focusing on the specific relationship between institutional investors' OC and measurable aspects of firms' environmental performance (Benlemlih et al. 2023; Cohen et al. 2023; Safiullah et al. 2022). Consequently, several scholars have highlighted the need for research that identifies and tests the link between institutional investors' OC and its impact on quantifiable environmental performance outcomes, rather than limiting the analysis to broader CSR or general environmental considerations (Benlemlih et al. 2023; Cohen et al. 2023; Safiullah et al. 2022; Zaman et al. 2020). In an attempt to address the identified research gaps and given the importance of GHG emissions for the ultimate objective of climate change, this manuscript seeks to examine the relationship between different forms of institutional investors' OC and firms' GHG emission intensity (considered as an environmental proxy for organizations' Benlemlih et al. 2023; Zaman et al. 2020). In doing so, this manuscript combines the call for a more granular classification of institutional investors with the need to move beyond aggregate measures and focus on quantifiable aspects of organizations' environmental performance.

This leads to our main research question (RQ):

**RQ1.** Does institutional investors (six main categories) OC have an impact on organizations' GHG emission intensity?

This article positions itself within the neo-institutional theoretical framework (DiMaggio and Powell 1983) since the awareness of climate change and GHG emissions is likely to promote institutional investors' interest in adopting managerial decisions that pursue environmental sustainability and lower GHG emissions.

In this empirical investigation, the authors utilize a regression analysis with balanced panel data of over 600 European companies as their sample. The authors gathered observations from 2015 up to the business year 2022. The authors conducted several tests to ensure this manuscript's results were robust and controlled for endogeneity and self-selection bias. The study's findings indicate a negative and significant relationship between cross holdings' OC firms' levels of GHG emissions (Cheng et al. 2022; Ducassy and Montandrau 2015; Rees and Rodionova 2013). The obtained empirical results support previous scholarly literature concerning financial institutions' OC (Motta and Uchida 2018; Oh et al. 2011; Prado-Lorenzo et al. 2009; Rees and Rodionova 2013; Velte 2023; Wang et al. 2019), foreign institutional investors' OC (Chan 2010; Dyck
et al. 2019; Kim et al. 2016; Krueger et al. 2020; Mbanyele 2023), governments' OC positive effect on firms' environmental practices and performance (Clò et al. 2017; Li and Zhang 2010; Motta and Uchida 2018), since this manuscript's regression models underline a positive and significant relationship between the foregoing institutional investors' OC and firms' reduction of GHG emissions. Moreover, this manuscript's findings support the notion of pension funds' OC positive and significant effect on firms' environmental performance (Dyck et al. 2019; Kim et al. 2019; Oh et al. 2011; Rees and Rodionova 2013). Finally, this empirical research contradicts previous knowledge by suggesting a negative non-significant effect between "other" investors' OC and companies' environmental performance (Li, Zhang, et al. 2021), in terms of GHG emissions.

This manuscript carries both theoretical and practical contributions. First, this article broadens the literature on institutional investors' OC and their influence on companies' environmental performance (Benlemlih et al. 2023). Second, this paper broadens our understanding of institutional investors' contribution in promoting carbon neutrality (Benlemlih and Yavaş 2023; Huovila et al. 2022). Third, the obtained results further underline the importance of the institutional investors classification developed by García-Sánchez, Rodríguez-Ariza, et al. (2020) and Giordino et al. (2024). Indeed, this manuscript's empirical findings underline the effect various forms of institutional investors' OC have on companies' environmental performance, precisely GHG emission intensity. Fourth, this manuscript further corroborates the neo-institutional theory's appropriateness for investigating institutional investors OC's impact on firms' GHG emissions (DiMaggio and Powell 1983). Finally, this manuscript should prove of particular interest to policy makers and governmental institutions since it underscores a granular understanding of institutional investors' impact and interest in relation to firms' GHG emission intensity. Henceforth, given the geographical focus of this manuscript, European national and supra-national institutions could gather interesting insights that could shape their policy and norms given their net zero objective by 2050 (European Commission 2023).

The paper is organized as follows: Section 2 provides a concise review of the literature on the selected topic, the theoretical framework used, and subsections outlining the formulation of the research hypotheses. Section 3 outlines the empirical research framework adopted and the sample composition, sources, and descriptive statistics. Sections 4 and 5 present the obtained findings alongside the authors' discussion. Lastly, Section 6 details the concluding remarks of this manuscript, and it lists its implications, limitations, and future research directions.

# 2 | Literature Review and Formulation of Hypothesis

## 2.1 | Environmental Performance and Its Benefits

Scholarly research highlights many reasons as to why organizations may want to pursue initiatives associated with improved environmental performance (Talwar et al. 2023; Talwar et al. 2021). Given the growing concerns associated with climate change, governmental entities are formulating norms and

regulations pressuring companies to address their environmental impact and meet the regulatory goals associated with carbon neutrality (Benlemlih and Yavaş 2023; Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022). The above-mentioned efforts create a dichotomy in which organizations can either benefit from institutional incentives or face environmental penalties that can translate into additional costs. Indeed, environmental responsibility and sustainability practices are believed to mitigate the adverse effects and costs traditionally associated with environmental crises, thus supporting companies' resilience and financial performance (Benlemlih and Cai 2020). However, scholarly literature reports how institutional incentives are amongst the most prominent benefits associated with organizations' alignment with environmental behaviors. Specifically, organizations' actions towards carbon neutrality ameliorate their reputation, thus reducing potential costs associated with financial penalties stemming from legal proceedings and regulatory penalties (Gomez-Trujillo et al. 2020). Furthermore, scholarly articles highlight how organizations' ability to ameliorate their reputation and visibility through environmental practices and performance may easily attract institutional investors seeking to reduce their portfolio risk (Gillan et al. 2021), thus underscoring the notion of institutional incentives associated with it. Amongst those institutional investors, empirical evidence highlights the role of banks and credit institutions. Indeed, firms with low climate and carbon risks may benefit from institutional incentives by gaining access to credit more easily and at a lower yield (Seltzer et al. 2022). Henceforth, organizations that do not engage in environmental behavior are likely to suffer from additional costs from less favorable credit lines. On the other hand, empirical evidence underscores how organizations that do not engage in environmental practices and behaviors are likely to experience a higher increase in their cost of capital following natural disasters, compared to those that do engage with environmental practices and behaviors (Bonetti et al. 2023). Consequently, according to the preceding literature and reported benefits associated with solid environmental performance, firms must establish practices to reduce their climate and carbon risk and improve their environmental sustainability (Benlemlih et al. 2023). In addition, several stakeholders are actively advocating for firms to prioritize environmental sustainability, thus further corroborating the relevance of the topics and thematic areas taken into consideration in this manuscript.

## 2.2 | Theoretical Foundation and Hypothesis Formulation

### 2.2.1 | Neo-Institutional Theory

The authors of this paper draw from neo-institutional theory, as it provides an appropriate theoretical foundation for studies examining the relationship between OC and GHG emissions (Benlemlih et al. 2023). In fact, the foregoing theory has become a popular notion within CSR research regarding understanding and explaining how firms generally respond to environmental and social challenges and activism (Ball and Craig 2010). Neo-institutional theory, or “new institutionalism” is defined as an approach that examines the constraining and enabling effects of informal and formal regulations on the behavior of groups and individuals (DiMaggio and Powell 1983). Neo-institutional
theory postulates that individuals and groups are subjected to
institutional isomorphism, leading them toward a dominant
form and practices (Benlemlih et al. 2023). As a matter of fact,
according to neo-institutional theory, organizations and in-
dividuals are spurred by pressures in broader society, and by
conforming to norms, regulations, and routine interests that
are held in high regard by the community (i.e., by adopting spe-
cific organizational structures and policies), they might demon-
strate their compliance with institutional demands (Alshbili
et al. 2019; Patten and Crampton 2004).

According to the neo-institutional theory, institutional investors' behavior would be influenced by three institutional factors, namely coercive/regulative isomorphism, mimetic/cultural isomorphism, and normative isomorphism (Jahid et al. 2023) (Figure 1).

The neo-institutional theory posits that coercive/regulative isomorphism arises from informal and formal constraints exerted on organizations by external entities and individuals upon whom they rely (DiMaggio and Powell 1983). Regarding this isomorphism, a great deal of studies emphasize how crucial the legal environment is to reducing environmental degradation and encouraging environmentally responsible behaviors and strategies (Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022). As coercive pressure tends to make firms and individuals behave more responsibly (Jahid et al. 2023), the authors expect institutional investors to encourage environmental performance and demand sustainable behaviors from businesses they invest in.

DiMaggio and Powell (1983) define mimetic/cultural isomor-
phism as the company's tendency to imitate the behaviors of
"model organizations" in situations of uncertainty. Institutional
investors are inclined to synchronize their environmental ob-
jectives with those of low-emissions organizations in order to
enhance their ethical credibility, comply with institutional de-
mands, enhance their involvement in environmental matters,
advocate for the climate, and manage their climate-related risks
(Benlemlih et al. 2023).

Concerning normative isomorphism, the neo-institutional the-
ory holds that formal and informal pressures placed on organi-
zations would lead these latter to act in a professionally correct
manner (Martínez-Ferrero and García-Sánchez 2017; DiMaggio
and Powell 1983).

<figure><img src="image_2.png" /><figcaption>**FIGURE 1** | Conceptual theoretical framework. Authors' own elaboration based on Jahid et al. (2023) initial proposition.</figcaption></figure>

Regarding the context analyzed in this study, Benlemlih et al. (2023) argue that institutional investors make similar managerial choices in favor of reduced pollution if they are aware of climate-change-related issues.

2.2.2 | Hypothesis Formulation

To ensure consistency in comparing the extensive range of em-
pirical findings in the existing literature, the authors employed
six categories of institutional investors, based on the manuscripts
of Giordino et al. (2024, 2025), Velte (2023), García-Sánchez,
Aibar-Guzmán, and Aibar-Guzmán (2020) and García-Sánchez,
Rodríguez-Ariza, et al. (2020). Specifically, the above-cited
studies highlight that these categories of institutional investors
enable researchers to establish heterogeneous classifications
that account for similarities in mission, investment horizons,
and strategic attitudes, thereby overcoming the limitations of
less granular categorizations. Indeed, five of the six categories
comprise institutional investors that fall within a clearly defined
group of entities exhibiting comparable attitudes. The only ex-
ception is the category of “other” institutional investors since
it includes charities, insurance companies, index funds, etc.
These sub-groups were combined into a single category because
they typically maintain relatively small OC, which limits the
feasibility of analyzing them separately without undermining
their statistical power. Furthermore, as detailed in the follow-
ing sections, these entities were grouped together because they
generally exert weaker governance influence compared to the
other categories among other common characteristics. Second,
these categories were chosen to expand upon previous research
regarding the influence of institutional investors' OC on GHG
emissions. While the literature on institutional investors mainly
focuses on one single and general category of investors without
differentiating them (Benlemlih et al. 2023; Cohen et al. 2023;
Safiullah et al. 2022), this study provides a first attempt to show
a granular and heterogeneous exploration of the impact that
each dimension of institutional investors' OC has on firms' GHG
emissions intensity. Moreover, Table A1 details some of the most
relevant studies focusing on institutional investors OC.

2.2.3 | Cross Holdings

Within corporate governance, institutional investors often employ equity ownership to influence interconnected firms (Brooks et al. 2018; He et al. 2019). Indeed, their strategic use of ownership allows cross-holdings to exercise control over the governance of companies within their investment portfolio (Gao et al. 2019; Kang et al. 2018). The justification for this involvement is based on the significant agency costs that arise from the inherent misalignment of objectives in cross-holdings (Ojo 2013).

Studies indicate that enterprises engaged in cross-holdings ex-
perience adverse effects on their CSR and environmental, so-
sial, and governance performance (Rees and Rodionova 2013).
This negative impact can be due to cross-holdings' inclination
towards favoring their interests rather than promoting long-
term benefits, which may derive from social and environmen-
tal performance (Kavadis and Thomsen 2023). Furthermore,
cross-holdings have a tendency to diminish the other investors' control over decisions (Correa-Garcia et al. 2020) as they exert greater control through elevated levels of OC (He et al. 2019), thus impeding, for example, environmentally friendly actions. This is attributable to the fact that parent companies establish policies and processes aligned with the overarching vision of the group, thus potentially overshadowing the interests of other investors and external stakeholders (García-Sánchez, Rodríguez-Ariza, et al. 2020). Indeed, the preceding practice could lead to lower degrees of CSR actions and environmental performance (Correa-Garcia et al. 2020; Rees and Rodionova 2013). However, some academic research presents non-confirmatory findings, thus underlining the need to gather additional empirical evidence to elucidate the relationship that exists between cross holdings' OC and corporations' sustainability practices (García-Sánchez, Rodríguez-Ariza, et al. 2020). From our chosen theoretical framework perspective, given their focus on operational efficiency, firms are likely to experience lower degrees of coercive pressure and mimetic isomorphisms (Jahid et al. 2023). As a result, notwithstanding the nuances above and the organizational structure and processes that shape and influence corporations' behaviors (neo-institutional theory Section 2.2) concerning environmental performance, the following hypothesis is proposed:

**H1.** Cross holdings OC negatively influence companies' GHG emission reduction.

### 2.2.4 | Financial Institutions

The literature has contradicting empirical findings regarding the influence of financial institutions' OC on CSR practices. On the one hand, due to the comprehensive and rigorous laws on sustainable finance that have been enforced in recent years (such as those by the European Union) (Velte 2023) and the tremendous public scrutiny they are subjected to, especially during times of financial volatility (Chalmers and van den Broek 2019), financial institutions have been focusing on improving their image and reputation (García-Meca and Pucheta-Martínez 2018), through sustainable programs (Mishra 2022). Consequently, financial institutions are keenly interested not only in firms' financial performance but also in the environmental and social practices of the business they are invested in (Motta and Uchida 2018). Furthermore, as they act as lenders, banks demand sustainable behavior from firms to increase business value and lower risk (García-Sánchez, Rodríguez-Ariza, et al. 2020). Indeed, empirical evidence suggests that financial institutions' OC drives CSR (Oh et al. 2011), fostering environmental performance (Rees and Rodionova 2013). In addition, enterprises that have implemented carbon reduction initiatives may qualify for concessional loans with comparatively reduced interest rates (Wang et al. 2019).

On the other hand, another body of literature attributes a short-term orientation to financial institutions (Bushee 1998; Oh et al. 2011) and, as a result, a reduced tendency to support sustainable actions and behavior in the companies they are invested in (Johnson and Greening 1999), given that the benefits of such acts typically emerge in the long term (Falck and Heblich 2007). Indeed, some empirical studies have found no

influence between financial institutions' OC on firms' strategy (Dam and Scholtens 2012) and sustainable behavior (Johnson and Greening 1999).

However, despite the abovementioned contradictions in the literature, the authors support a positive influence of financial institutions' OC on firms' environmental performance. This is in harmony with the abovementioned works of Wang et al. (2019), Rees and Rodionova (2013) and Oh et al. (2011). More specifically, this latter paper, despite attributing a short-term orientation to financial institutions, argues and further demonstrates that financial institutions might be compelled to adopt a long-term orientation in order to support those investments that could increase the firms' long-term value; otherwise, they would be unable to sell their shares without having a negative impact on the stock prices of the companies (García-Sánchez, Aibar-Guzmán, and Aibar-Guzmán 2020; Oh et al. 2011). Furthermore, studies suggesting that financial institutions show a reduced tendency to support sustainable actions are based on dated empirical evidence, referring to a period when environmental and social considerations were not as widely recognized or prioritized by stakeholders as they are today. More recent research highlights how over the years both attitudes and social expectations have shifted, thus highlighting the need for financial institutions to address environmental concerns (Giordino et al. 2025; Wang et al. 2019).

Moreover, the neo-institutional theory upholds that financial institutions' OC benefits enterprises' environmental performance. Specifically, their highly regulated environment is likely to encourage environmentally responsible behaviors and strategies given the coercive/regulative isomorphism (Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022). The foregoing logic is also relevant to financial institutions from the perspective of informal pressures, thereby underscoring the role of normative isomorphism (Martínez-Ferrero and García-Sánchez 2017). Moreover, given the prominent role that financial institutions have and the competitive market in which they operate, our chosen theoretical framework underscores the importance for financial institutions to pursue best practices, thereby highlighting the influence of mimetic/cultural isomorphism (DiMaggio and Powell 1983). Finally, institutional investors possess knowledge of climate-change-related matters, which prompts them to make decisions promoting decreased pollution (Benlemlih et al. 2023), such as, for instance, making the firms they are invested in reduce GHG emissions. Consequently, the authors of this manuscript propose the following research hypothesis:

**H2.** Financial institutions' OC positively influences firms' GHG emissions reduction.

### 2.2.5 | Foreign Institutional Investors

Foreign institutional investors are one of the institutional investors recognized in the current literature due to their ability to affect an organization's governance (Admati and Pfleiderer 2009; Aggarwal et al. 2011; Kavadis and Thomsen 2023), innovativeness (Guadalupe et al. 2012; Luong et al. 2017), and investments over the long term (Bena et al. 2017). Furthermore, foreign institutional investors will promote better environmental
performance in their portfolio firms to mitigate the exposure of their portfolios to the adverse spillover effects of environmental events and regulatory risks resulting from changes in norms in their home countries (Krueger et al. 2020; Mbanyele 2023; Li, Wang, and Wu, 2021). Due to their typically little engagement with the companies they invest in (Lel 2019), foreign institutional investors tend to be more independent and monitor firms more closely than domestic investors (Fang et al. 2015; Mbanyele 2023; Li, Wang, and Wu, 2021). As foreign institutional investors are characterized by a long-term investment horizon, they prioritize creating long-term value rather than engaging in short-term speculation (Bena et al. 2017). As a result, the findings above further highlight how foreign institutional investors, particularly those from countries with high environmental pressure, tend to push for more stringent environmental policies (coercive/regulative isomorphism) and better environmental performances in the firms they are invested in (Chan 2010; Kim et al. 2016), to achieve long-term benefits (Dyck et al. 2019). Empirical evidence indicates that foreign institutional investors play a significant role in promoting corporate sustainability by enhancing environmental performance (Ahmed et al. 2023; Dyck et al. 2019). Moreover, they also serve as a disciplinary role in carbon engagement (Mbanyele 2023). Furthermore, companies seeking to meet foreign institutional investors' expectations regarding environmentally responsible practices (Li, Zhang, et al. 2021), as well as those willing to attract foreign institutional investors (Yu and Zheng 2020), may be motivated to enhance their environmental performance and engagement (mimetic/cultural and normative isomorphism as detailed by our chosen theoretical framework) (Kordsachia et al. 2022). This, in turn, strengthens their brand image and market positioning, thereby contributing to their long-term competitiveness and attractiveness (Dyck et al. 2019), while supporting risk mitigation (Mallin 1999). Thus, foreign institutional investors' OC ought to encourage companies to improve their environmental practices to foster their environmental performance. As a result, based on scholarly findings and the adopted theoretical framework, the authors of this manuscript propose the following hypothesis:

**H3.** *Foreign institutional investors' OC positively influences companies' carbon emissions reduction.*

### 2.2.6 | Governments

The influence of governments on organizations they are invested in has been widely studied in the literature (Aguilera et al. 2021; Pearce et al. 2009; Tian and Estrin 2008). In the realm of corporate sustainability, there are contradicting positions. On the one hand, several studies highlight the positive influence of governments' OC on firms' sustainability practices (i.e., Ahmed et al. 2023; Li and Zhang 2010; Motta and Uchida 2018). On the other hand, a different body of literature emphasizes how governments have no impact on firms' pursuit of sustainability (i.e., Dam and Scholtens 2012; Lamoureux et al. 2019). Although the literature presents conflicting results, the authors support governments' OC's positive influence on corporations' environmental sustainability. Several elements and concepts support the preceding notion. First, it is governments' duty to pursue sustainable development from an environmental and social

point of view (García-Sánchez, Rodríguez-Ariza, et al. 2020). Consequently, their investment strategies are typically focused on the long term and consider environmental, social, and ethical considerations (Aguilera et al. 2021; Rees and Rodionova 2013) rather than being driven solely by short-term profit motives (Eng and Mak 2003). This is especially relevant when it comes to our manuscript's contextual focus given Europe's strategic direction (Velte 2024b). Moreover, governments' interest in addressing climate change has increased over time as they are in charge of implementing the 2030 Agenda into national objectives and institutional arrangements (García-Sánchez et al. 2022). As a consequence, governments might impose sustainability goals on the companies they are invested in by encouraging the adoption of environmentally friendly initiatives (García-Sánchez et al. 2022; Li and Zhang 2010). Empirical evidence indicates that public ownership has a mitigating effect on enterprises' GHG emissions and carbon intensity (Clò et al. 2017). However, it is essential to note that Clò et al. (2017) findings are limited to the European electricity industry; thus, empirical bodies of work should explore whether that relationship applies to different contexts.

Furthermore, companies seeking to meet governments' expectations regarding environmentally responsible practices, as well as those aiming to demonstrate their commitment towards climate change, may be motivated to improve their environmental performance (Thornton et al. 2003; Zhang et al. 2008). Finally, based on the neo-institutional theory (Wang et al. 2019), the authors believe governments' OC promotes corporations' environmental actions aimed at nurturing their environmental performance. Specifically, our chosen theoretical framework underscores the connection between governments' OC and the coercive/regulative and normative isomorphism. Through formal and informal pressures, governments can foster the pursuit of specific actions whose purpose is to reduce organizations' environmental impact (Martínez-Ferrero and García-Sánchez 2017; Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022). Consequently, the authors propose the following hypothesis:

**H4.** *Governments' OC positively influences companies' GHG emissions reduction.*

### 2.2.7 | Pension Funds

Due to their OC in large publicly listed firms, pension funds have become significant players in the field of institutional investors (Sethi 2005). Pension funds exhibit a prolonged investing time frame (Cox et al. 2004; Gloßner 2019) and are thus highly motivated in promoting corporate environmental and social sustainability in the firms they invest in (Velte 2023). Existing research indicates that the OC of pension funds is expected to have a positive impact on the environmental and social performance of the enterprises they invest in (Kim et al. 2019; Oh et al. 2011). These findings align with those of Dyck et al. (2019), who assert that pension funds, given their extended investment timeline, necessitate organizations to engage in environmental and social investments for future advantages, thereby improving their environmental sustainability and performance.

Furthermore, as in the case of financial institutions, pension funds are also subject to a great degree of public scrutiny and
regulatory pressures (coercive/regulative and normative iso-
morphism), thus leading them to invest in businesses with
high environmental or social orientation (Mishra 2022; Oh
et al. 2011) and avoiding highly polluting organizations (Bolton
and Kacperczyk 2021; Fernando et al. 2017; Sudheer 2014).

However, it is essential to acknowledge that García-Sánchez
et al. (2022) empirical findings indicate that pension funds' OC has
a negative impact on firms' commitment to SDGs. This suggests a
potential adverse relationship between pension funds and compa-
nies' social and environmental initiatives. Nevertheless, the same
study contends that in the case of globalized firms, the adverse ef-
fects of pension funds' OC are partially mitigated by the company's
global presence, which reduces the influence of pension funds. As
a result, within their sample, the impact of pension funds on cor-
porate governance and practices was minimal, leading to the ob-
servation of a negative effect (García-Sánchez et al. 2022).

The authors are in favor of the positive relationship between pen-
sion funds' OC and firms' environmental performance since most
of the scholarly empirical evidence supports the foregoing no-
tion (Dyck et al. 2019; Kim et al. 2019; Oh et al. 2011; Rees and
Rodionova 2013). Additionally, the adopted theoretical framework
further underscores the above proposed relationship. Pension
funds are under a great deal of public scrutiny (mimetic/cultural
isomorphism), and given their societal role, are often time tied to
formal and informal pressures that can deeply impact their invest-
ment strategy and focus (DiMaggio and Powell 1983).

Henceforth, the authors formulate the following hypothesis:

**H5. Pension funds' OC positively influences firms' GHG emissions reduction.**

2.2.8 | Other Institutional Investors

In accordance with García-Sánchez, Rodríguez-Ariza, et al. (2020) and Giordino et al. (2024), the authors decided to add a sixth category, with the aim of including those investors whose OC is typically smaller, within the sample analyzed in this paper. In doing so, we aim to address the feasibility challenges traditionally associated with these categories of institutional investors, as they typically exert weaker governance influence than other groups and maintain relatively low levels of OC (García-Sánchez, Rodríguez-Ariza, et al. 2020). Moreover, we followed the scholarly literature in grouping these institutional investors into a single category, as their investment and management styles are generally more passive, and their investment horizons often align (García-Sánchez, Rodríguez-Ariza, et al. 2020; Giordino et al. 2024; Velte 2023). Henceforth, following prior work, this classification of institutional investors accounts for charities, insurance companies, mutual funds, and index funds OC (i.e., Velte 2023; Ding et al. 2022).

Due to the values-driven nature of their mission, it is reason-
able to expect charities to align their investment behavior ac-
cordingly (Kreander et al. 2009), opting to invest in companies
that prioritize environmental and social sustainability (Sparkes
and Cowton 2004). Furthermore, charities are subjected to
regulatory pressures and, therefore, must increase their social
and environmentally sustainable performance through actions

and investment behaviors (Ahunov 2023). Henceforth, from a
neo-institutional theory perspective, the abovementioned logics
underscore the nature of coercive/regulative and normative iso-
morphism that deeply impacts charities' focus on environmental
and social sustainability issues. These findings and theoretical
considerations are in harmony with those of Cox et al. (2004),
who emphasize that charities' OC and companies' environ-
mental and social sustainability performance are positively
correlated, primarily due to the charities' long-term investment
perspective. Therefore, drawing from the results above, the
authors propose that charities' organizational culture benefits
enterprises' environmental performance, prompting them to de-
crease their GHG emissions.

There are contradicting positions in the scholarly literature concerning the impact of insurance companies' OC on firms' environmental performance. On the one hand, due to their long-term investment horizon (Nguyen et al. 2020) and the strict regulations on sustainable finance that have been implemented in the last few years (Velte 2023), insurance companies are strongly incentivized to promote CSR actions and behaviors in the businesses they are invested in (Ullah et al. 2019). The results of this study are consistent with the research carried out by Cox et al. (2004) and Johnson and Greening (1999), which highlight the positive association between insurance companies' OC and enterprises' environmental and social performance. The above-detailed results are further corroborated by our chosen theoretical framework since insurance companies must adhere to both formal and informal pressures from a multitude of stakeholders (DiMaggio and Powell 1983). In contrast, Oh et al. (2011) did not discover any empirical proof of the influence of insurance companies' OC on firms' sustainability performance. However, it is important to note that the findings of Oh et al. (2011) are based on a sample of Korean companies, whereas most studies reporting a positive link between insurance companies' OC and firms' environmental performance rely on European samples. Indeed, the European context is widely recognized as a leading actor in promoting carbon neutrality and advancing environmental and social sustainability; therefore, this difference could explain the above-reported discrepancy. In light of this contextual difference, and given the European focus of our sample, we align with the strand of literature that supports a positive relationship. However, due to this misalignment in the literature, it remains to be seen whether insurance companies would positively influence companies' environmental performance, thus highlighting the need to explore this potential relationship further. However, based on this manuscript's theoretical lens and the preceding scholarly literature, the authors align with the notion of insurance companies' OC positively influencing organizations' environmental practices and actions.

In the literature, there are contradicting opinions on the impact of
mutual funds' OC on companies' CSR practices and performance.
First, part of the scholarly literature empirically demonstrates
that, due to their short-term investment horizon (Oh et al. 2011),
mutual funds have no (Johnson and Greening 1999) or negative
(Li, Zhang, et al. 2021) influence on their investees' environmental
and social practices. However, other studies (i.e., Chen et al. 2020;
Yadav 2020) found contradicting results, highlighting how mutual
funds' OC positively influences corporations' CSR actions and
practices due to their stakeholders' growing interest in socially and
environmentally responsible investments (Li, Patel and Ramani, 2021; Mackey et al. 2007). Furthermore, as there is empirical evidence showing that sustainability (Hartzmark and Sussman 2019) and carbon performance (Bolton and Kacperczyk 2021) increase mutual funds' OC, organizations seeking to attract capital from mutual funds may be motivated to engage in environmental and social sustainability practices. Nevertheless, despite the conflicting results presented by the scholarly literature, the authors of this paper side with the scholarly literature reporting a positive relationship between mutual funds' OC and their investees' environmental and social practices. The chosen theoretical lens further reinforces that mutual funds are subject to both formal and informal pressures from a wide range of stakeholders, thereby underscoring the isomorphism proposed by the neo-institutional theory. Moreover, given the growing diffusion of environmental and social sustainability logics, we believe that the contradictory evidence can be attributed to differences in sample characteristics and the time frame of the observations. Recent studies, in fact, emphasize a positive link between mutual funds' OC and organizations' CSR performance (Chen et al. 2020; Giordino et al. 2024; Yadav 2020).

Lastly, concerning index funds, empirical evidence underlines their positive influence on companies' adoption of CSR practices (Chen et al. 2020). Indeed, index funds tend to focus on long-term investment horizons, thus promoting socially and environmentally responsible behaviors in their investees (Li, Zhang, et al. 2021). Furthermore, environmentally and socially responsible investment funds, accounted for within this category, are known for improving their investees' environmental and social sustainability (Dimson et al. 2015) and environmental performance (Kim et al. 2019).

Despite the literature being quite contradictory regarding “other” institutional investors, the authors of this manuscript support the notion of “other” institutional investors positively influencing companies’ environmental performance. First, according to the majority of the scholarly literature cited in this section, “other” institutional investors positively influence companies’ environmental practices. Second, institutional investors can signal potential clients that they are reliable and responsible by investing in socially responsible businesses and maintaining their sustainability ratings (Oh et al. 2011). Finally, this manuscript’s theoretical lens further reinforced the notion of “other” institutional investors’ positive effect on their investees’ CSR practices. Consequently, the authors of this manuscript propose the following hypothesis:

**H6.** "Other" institutional investors' OC positively influences firms' GHG emissions reduction.

# 3 | Material and Methods

## 3.1 | Research Design and Sample Composition

The authors utilize a balanced panel dataset including 4396 observations related to 628 European enterprises from 2015 to 2022. All retrieved variables and data are collected through the Thomson Reuters database. Consequently, the researchers excluded those companies for whom data on GHG emissions

or institutional ownership concentration was not accessible or available. The use of the Thomson Reuters database was deemed relevant because of its wide adoption within scholarly literature (García-Sánchez, Aibar-Guzmán, and Aibar-Guzmán 2020; García-Sánchez, Gallego-Álvarez, and Zafra-Gómez 2020; Mishra 2022).

When constructing the sample, the authors applied the following inclusion and exclusion criteria. First, companies whose headquarters are located within the European geographical context were included due to the geographical focus of this manuscript and the European greater focus and higher institutional pressure on organizations' environmental sustainability and performance (Velte 2023). Given the European Union context, numerous scholarly publications have structured their empirical investigation by collecting observations from various countries within the EU given their normative similarities (García-Sánchez, Aibar-Guzmán, and Aibar-Guzmán 2020; Velte 2024a). Henceforth, we deemed it appropriate to include in our sample companies from a multitude of European countries. Moreover, following Velte (2024a), we have also taken into account companies whose headquarters are located in the UK, considering their historical membership in the EU and the regulatory alignment that persisted beyond their departure.

Furthermore, given the manuscript's aim and scope detailing GHG emission as a proxy for environmental sustainability, the European context would provide interesting insights in light of its European Climate Law establishing the objective of achieving net zero GHG emissions by 2050 (European Commission 2023). Following the work of Velte (2023), we maintained the United Kingdom in our sample as a former member of the European Union. Second, organizations pertaining to the banking and insurance sector were excluded given their distinct accounting, governance, and capital structure standards which could introduce inaccuracies in our obtained findings (Doni et al. 2019). Third, organizations with a market capitalization below 250 million dollars were excluded to mitigate potential data unavailability issues (Chodorow-Reich et al. 2022). Finally, organizations with missing financial or non-financial datapoints were excluded, thereby greatly decreasing the size of our sample. Table 1 presents the details concerning the sample composition.

## 3.2 | Variables Description

Prior scholarly literature on institutional investors OC often relies on a single dimension of institutional investors by grouping them within one variable (Benlemlih et al. 2023; Cohen et al. 2023; Safiullah et al. 2022). Nonetheless, institutional investors have different needs, characteristics, and preferences affecting their influence on companies' environmental practices (as detailed in Section 2 of this manuscript). Therefore, to address the shortcomings of prior literature, the authors of this manuscript have followed the classification of institutional investors by García-Sánchez, Rodríguez-Ariza, et al. (2020). Six categories are constructed through Thomson Reuters' investors subcategories as outlined in Table 2.

To address prior research limitations (Mishra 2022; Velte 2023), this manuscript takes a novel approach by considering all
<table><caption>TABLE 1 | Sample breakdown by its GICS industry sector and headquarter location.</caption><thead><tr><th colspan="3">Country</th><th colspan="3">GICS industry sector</th></tr><tr><th>Headquarter location</th><th>No. of firms</th><th>Percentage</th><th>Sector name</th><th>No. of firms</th><th>Percentage</th></tr></thead><tbody><tr><td>Austria</td><td>9</td><td>1.4%</td><td>Communication Services</td><td>35</td><td>6%</td></tr><tr><td>Belgium</td><td>17</td><td>2.7%</td><td>Consumer Discretionary</td><td>88</td><td>14%</td></tr><tr><td>Cyprus</td><td>3</td><td>0.5%</td><td>Consumer Staples</td><td>51</td><td>8%</td></tr><tr><td>Czech Republic</td><td>1</td><td>0.2%</td><td>Energy</td><td>31</td><td>5%</td></tr><tr><td>Denmark</td><td>13</td><td>2.1%</td><td>Health Care</td><td>63</td><td>10%</td></tr><tr><td>Estonia</td><td>1</td><td>0.2%</td><td>Industrials</td><td>157</td><td>25%</td></tr><tr><td>Finland</td><td>17</td><td>2.7%</td><td>Information Technology</td><td>51</td><td>8%</td></tr><tr><td>France</td><td>60</td><td>9.6%</td><td>Materials</td><td>57</td><td>9%</td></tr><tr><td>Germany</td><td>72</td><td>11.5%</td><td>Real Estate</td><td>63</td><td>10%</td></tr><tr><td>Greece</td><td>11</td><td>1.8%</td><td>Utilities</td><td>32</td><td>5%</td></tr><tr><td>Guernsey</td><td>3</td><td>0.5%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Hungary</td><td>2</td><td>0.3%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Iceland</td><td>4</td><td>0.6%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Italy</td><td>30</td><td>4.8%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Jersey</td><td>2</td><td>0.3%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Luxemburg</td><td>11</td><td>1.8%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Malta</td><td>3</td><td>0.5%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Monaco</td><td>2</td><td>0.3%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Netherlands</td><td>22</td><td>3.5%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Norway</td><td>26</td><td>4.1%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Poland</td><td>18</td><td>2.9%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Portugal</td><td>5</td><td>0.8%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Republic of Ireland</td><td>14</td><td>2.2%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Romania</td><td>4</td><td>0.6%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Russia</td><td>28</td><td>4.5%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Slovenia</td><td>1</td><td>0.2%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Spain</td><td>23</td><td>3.7%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Sweden</td><td>56</td><td>8.9%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Switzerland</td><td>44</td><td>7.0%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>United Kingdom</td><td>126</td><td>20.1%</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Total</td><td>628</td><td>100.0%</td><td>Total</td><td>628</td><td>100%</td></tr></tbody></table>

institutional investors who hold a stake in a particular company without setting any restrictions or exclusion criteria based on their ownership percentage.

From the GHG dimension, prior scholarly studies rely on information obtained through the Carbon Disclosure Project (CDP), thus measuring GHG performance based on voluntary participation and content analysis (Chithambo et al. 2020). Although GHG data obtained through the preceding sources

may offer reliable and accurate information, it is necessary to observe that studies focusing solely on firms' voluntary disclosure may fail to evaluate their GHG performance appropriately. Indeed, organizations may engage in projects such as the CDP to demonstrate their environmental commitment to sustainability disclosure rather than actual low levels of GHG emissions (Benlemlih et al. 2023; Cohen et al. 2023; Safiullah et al. 2022). Thus, the authors of this study utilize a quantifiable and verifiable metric to assess the environmental impact of corporations.
<table><caption>**TABLE 2** | Classification and subcategories of Institutional investors.</caption><thead><tr><th>Category of institutional investors</th><th>Subcategories established by definitiv</th></tr></thead><tbody><tr><td>Cross holdings</td><td>"Corporation" and "Holding company"</td></tr><tr><td>Financial institutions</td><td>"Bank and trust"</td></tr><tr><td>Foreign institutional investors</td><td>Investment entities and advisors whose national headquarters differs from the selected company headquarter</td></tr><tr><td>Governments</td><td>"Government agency" and "Sovereign wealth fund"</td></tr><tr><td>Pension funds</td><td>"Pension funds"</td></tr><tr><td>Other institutional investors</td><td>"Charity", "Index funds", "Insurance companies" and "Mutual funds"</td></tr></tbody></table>

Therefore, the authors deemed using GHG emission intensity per million-dollar sale to signify a corporation's GHG emission. Furthermore, the researchers deemed the use of GHG emission per million-dollar sales as it provides a comparative measure that accounts for company size and sales volume (Benlemlih et al. 2023).

In line with previous scholarly studies (Mishra 2022), the authors of this manuscript employ various control variables that may impact the relationship between GHG emissions per dollar sales and institutional investors' OC. The selected control variables detail both financial and governance control variables, thus providing a detailed and comprehensive analysis. Table 3 lists all variables and their definition and abbreviations; the source of all these variables is Thomson Eikon Database.

### 3.3 | Research Design

To study the relationship between GHG emissions and institutional investors' OC, the following regression models are employed:

$$ (1) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{CrossOC} + \text{Controls} + \varepsilon $$

$$ (2) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{FinOC} + \text{Controls} + \varepsilon $$

$$ (3) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{ForeOC} + \text{Controls} + \varepsilon $$

$$ (4) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{GovOC} + \text{Controls} + \varepsilon $$

$$ (5) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{PenOC} + \text{Controls} + \varepsilon $$

$$ (6) \text{GHGEmSale}_{it} = \alpha_0 + \beta_1 \text{OtherOC} + \text{Controls} + \varepsilon $$

The above listed baseline regression model equations indicate as their dependent variable GHGEmSale and as independent

variables the various ownership dimensions identified. The scope of the preceding equations is to estimate the association between companies' GHG emissions and their ownership structure. The authors incorporate time, country and firm variables (controls) into all specifications. In Table 3, the definitions of all the variables are detailed.

The above detailed panel data regressions are based on significant Lagrange multiplier tests, Hausman tests, and F-tests. Fundamentally, all equations use fixed effects, firm-level clustered standard errors, incorporating control variables.

## 4 | Results

### 4.1 | Descriptive Statistics

This section includes the descriptive statistics of the several variables used in this research. Table 4 provides each variable's mean, standard deviation, and total number of observations.

Table 4 shows that the dependent variable (GHGEmSale) has an average value of 3.73 metric tonnes of GHG emitted per million dollar sales revenues, with a standard deviation of 2.516. On the other hand, the independent variables' descriptive statistics are as follows: CrossOC has an average value of 0.70 and a standard deviation of 2.88; FinOC reports a mean value of 0.09 and a standard deviation of 0.610; ForeOC's average is 0.57 and it has a standard deviation of 2.75; GovOC has an average value of 0.19 and a standard deviation of 0.57; PenOC stands at an average value of 0.02 with a standard deviation of 0.42; and OtherOC's mean stands at 0.01 with a standard deviation of 0.29.

The authors made sure to test the correlation between the various variables employed within this manuscript's empirical design by performing Pearson's correlation matrix (Table 5). From the correlation matrix, it is possible to observe that in no specification does the correlation exceed 0.8, thus supporting the notion that this manuscript's empirical sample does not suffer from multicollinearity issues.

### 4.2 | Empirical Findings

The authors developed the following baseline regression models to test whether the hypothesis reported within Section 2 of this manuscript could be accepted. All six baseline regression models incorporate firm, industry, country, and year-fixed effects as control variables. Table 6 presents the baseline regression models' obtained findings. First, the analysis results concerning model (1) indicate that cross-holding ownership has a negative yet significant effect ($b=-2.93$; $p<0.01$) on companies' GHG emission intensity. On the other hand, model (2) underlines the positive and significant effect ($b=2.01$; $p<0.05$) financial institutions ownership concentration has on companies' GHG emissions, thus improving their environmental performances and contribution towards a carbon-neutral future. Furthermore, through model (3), the authors can observe the positive and significant effect foreign institutional investors OC ($b=1.62$; $p<0.05$) have on companies' GHG emissions. Moreover, the present manuscript presents empirical evidence suggesting the
<table><caption>TABLE 3 | Variable definition.</caption><thead><tr><td>Variable</td><td>Abbreviation</td><td>Definition</td></tr></thead><tbody><tr><td>GHG emission/$ sales</td><td>GHGEmSale</td><td>GHG emissions concerning organizations scope one and two (which include carbon dioxide [CO<sub>2</sub>], methane [CH<sub>4</sub>], nitrous oxide [N<sub>2</sub>O], hydrofluorocarbons [HFCS], perfluorinated compound [PFCS], sulfur hexafluoride [SF6] and nitrogen trifluoride [NF3]) calculated in metric tonnes emitted per million of $ sales revenue.</td></tr><tr><td>Cross holding ownership concentration</td><td>CrossOC</td><td>Total cross holding ownership concentration.</td></tr><tr><td>Financial institutions ownership concentration</td><td>FinOC</td><td>Total financial institutions ownership concentration.</td></tr><tr><td>Foreign institutional investors ownership concentration</td><td>ForeOC</td><td>Total foreign institutional investors ownership concentration.</td></tr><tr><td>Government ownership concentration</td><td>GovOC</td><td>Total government ownership concentration.</td></tr><tr><td>Pension funds ownership concentration</td><td>PenOC</td><td>Total pension funds ownership concentration.</td></tr><tr><td>Other institutional investors ownership concentration</td><td>OtherOC</td><td>Total insurance companies, index funds, mutual funds and charities ownership concentration.</td></tr><tr><td>Total debt to total assets</td><td>Lev</td><td>Leverage ratio in percentage of total amount of debt relative to assets.</td></tr><tr><td>CAPEX absolute value</td><td>Capex</td><td>Capital expenditure of a company during a fiscal year. Calculated as x-1.</td></tr><tr><td>Governance pillar score</td><td>Gov</td><td>Corporate governance pillar which measures the company's systems and processes how they act in the best interest of its long term shareholders.</td></tr><tr><td>Board Size</td><td>BoardSize</td><td>The natural logarithm of the number of directors on an organization board.</td></tr><tr><td>Board Independence</td><td>BoardInd</td><td>The ratio between independent board members and the total number of directors on an organization board.</td></tr><tr><td>Board Gender Diversity</td><td>BoardGen</td><td>Detailed as Blau index of board gender diversity.</td></tr><tr><td>Social pillar score</td><td>Soc</td><td>Social pillar score which measures a company's capacity to generate trust and loyalty amongst its customers, workforce and society because of its best management practices</td></tr><tr><td>Dividend per share</td><td>DivShare</td><td>Dividend paid per each share</td></tr><tr><td>Cash and cash equivalents</td><td>Cash</td><td>Total short-term and highly liquid investments that are easily convertible into known amounts of cash with insignificant risk of changes caused by interest rates.</td></tr><tr><td>Firm size</td><td>TotAss</td><td>Firm size measured as the natural logarithm of a company's total assets</td></tr><tr><td>R&D intensity</td><td>RD</td><td>Research and development expenses/revenues</td></tr><tr><td>Return on asset</td><td>ROA</td><td>The authors control for financial performance through company's ROA</td></tr></tbody></table>

positive and significant relationship between governments' OC ($b=4.97; p<0.001$) and corporations' GHG emission intensity. Model (5) indicates that a positive and significant relationship ($b=2.66; p<0.01$) also exists between pension funds OC and

organizations' GHG emissions. However, the baseline regression model (6) indicates that "other" institutional investors OC have near-insignificant consequences on corporations' GHG emission intensity ($b=-1.15; p>0.1$).
<table><caption>**TABLE 4** | Descriptive statistics.</caption><thead><tr><th>Variable</th><th>Number of Obs</th><th>Min.</th><th>P25</th><th>Mean</th><th>Median</th><th>P75</th><th>Max</th><th>Std. dev.</th></tr></thead><tbody><tr><td>GHGEmSale</td><td>4.107</td><td>-0.331</td><td>1.821</td><td>3.737</td><td>3.973</td><td>6.124</td><td>8.277</td><td>2.516</td></tr><tr><td>CrossOC</td><td>4.107</td><td>0.000</td><td>2.501</td><td>0.707</td><td>5.002</td><td>6.125</td><td>10.003</td><td>2.887</td></tr><tr><td>FinOC</td><td>4.107</td><td>0.000</td><td>0.529</td><td>0.098</td><td>1.057</td><td>1.586</td><td>2.114</td><td>0.610</td></tr><tr><td>ForeOC</td><td>4.107</td><td>0.000</td><td>2.390</td><td>0.579</td><td>4.780</td><td>7.171</td><td>9.561</td><td>2.758</td></tr><tr><td>GovOC</td><td>4.107</td><td>0.000</td><td>0.496</td><td>0.198</td><td>0.992</td><td>1.489</td><td>1.985</td><td>0.573</td></tr><tr><td>PenOC</td><td>4.107</td><td>0.000</td><td>0.370</td><td>0.029</td><td>0.741</td><td>1.110</td><td>1.482</td><td>0.427</td></tr><tr><td>OtherOC</td><td>4.107</td><td>0.000</td><td>0.255</td><td>0.013</td><td>0.511</td><td>0.766</td><td>1.021</td><td>0.294</td></tr><tr><td>Lev</td><td>4.107</td><td>0.000</td><td>20.824</td><td>24.775</td><td>41.648</td><td>62.471</td><td>83.295</td><td>24.044</td></tr><tr><td>Capex</td><td>4.107</td><td>0.000</td><td>0.199</td><td>0.059</td><td>0.398</td><td>0.596</td><td>0.795</td><td>0.230</td></tr><tr><td>Gov</td><td>4.107</td><td>0.476</td><td>23.631</td><td>54.647</td><td>47.787</td><td>71.943</td><td>95.098</td><td>27.266</td></tr><tr><td>BoardSize</td><td>4.107</td><td>3.000</td><td>6.014</td><td>8.930</td><td>11.000</td><td>11.846</td><td>22.000</td><td>4.319</td></tr><tr><td>BoardInd</td><td>4.107</td><td>0.000</td><td>0.302</td><td>0.471</td><td>0.320</td><td>0.640</td><td>1.000</td><td>0.250</td></tr><tr><td>BoardGen</td><td>4.107</td><td>0.000</td><td>0.235</td><td>0.351</td><td>0.395</td><td>0.467</td><td>0.600</td><td>0.172</td></tr><tr><td>Soc</td><td>4.107</td><td>2.492</td><td>20.651</td><td>42.119</td><td>38.810</td><td>56.969</td><td>75.128</td><td>20.955</td></tr><tr><td>DivShare</td><td>4.107</td><td>0.000</td><td>73.378</td><td>9.227</td><td>146.756</td><td>220.134</td><td>293.512</td><td>84.760</td></tr><tr><td>Cash</td><td>4.107</td><td>0.000</td><td>1.411</td><td>1.953</td><td>2.821</td><td>4.231</td><td>5.641</td><td>1.629</td></tr><tr><td>TotAss</td><td>4.107</td><td>10.056</td><td>12.025</td><td>13.994</td><td>15.739</td><td>18.108</td><td>21.422</td><td>3.316</td></tr><tr><td>RD</td><td>4.107</td><td>0.000</td><td>0.028</td><td>0.041</td><td>0.042</td><td>0.052</td><td>0.083</td><td>0.014</td></tr><tr><td>ROA</td><td>4.107</td><td>-16.480</td><td>-5.716</td><td>5.047</td><td>6.671</td><td>17.434</td><td>29.821</td><td>13.363</td></tr></tbody></table>

Consequently, hypotheses concerning foreign institutional investors, governments, cross holdings, financial institutions, and pension funds OC can be accepted since the empirical evidence corroborates H1, H2, H3, H4, and H5. On the other hand, H6 cannot be accepted since the empirical analysis underlines no association between corporations' GHG emissions and “other” institutional investors OC.

## 4.3 | Robustness Checks of Baseline Results

As Benlemlih et al. (2023) emphasized in their comparative study of UK and USA companies, the attitudes of institutional investors, their sentiment towards carbon neutrality and pressure to reduce companies' GHG emissions might significantly differ based on the geographical and national contexts. Therefore, distinct pressures influence institutional investors' advocacy for GHG reduction initiatives. Consequently, given the previously discussed considerations, the authors of this manuscript conducted additional tests to check further the robustness of the baseline regression results presented in Table 6. Since over 30% of the sample comprises firms headquartered in the UK, the authors further enhance the robustness of this manuscript analysis by conducting six regression models excluding the subset of UK companies (Table 7). The results corroborate the findings associated with the baseline regression models in Table 6. Indeed, cross holdings institutional

investors have a negative and significant ($b = -2.50$; $p < 0.01$) relationship with companies' GHG emissions. On the other hand, financial institutions ($b = 1.64$; $p < 0.05$), foreign institutional investors ($b = 1.41$; $p < 0.05$), governments ($b = 4.59$; $p < 0.001$) and pension funds ($b = 2.26$; $p < 0.01$) OC contribute significantly and positively to companies' GHG emission intensity. Finally, model (6) further corroborates the empirical analysis conducted within Section 4.2 of this manuscript since the preceding model underlines the inverse and insignificant relationship that exists between “other” institutional investors OC and corporations' GHG emission ($b = -0.83$; $p > 0.1$).

Furthermore, the scholarly literature often divides various forms of institutional investors into two generic categories associated with their strategic and investment durations (García-Sánchez, Rodríguez-Ariza, et al. 2020; Oh et al. 2011; Velte 2023). Hence, their inclination towards mitigating corporate GHG emissions and advocating for a carbon-neutral future may vary depending on their investment strategy and short- and long-term attitudes (Brossard et al. 2013). Consequently, in an attempt to conduct additional robustness checks and deepen our current understanding of how investment time horizons and attitudes impact institutional investors' OC effect on organizations' GHG emissions, the authors of this manuscript classify all previously identified institutional investors into two groups: long-term investors (financial institutions, foreign institutional investors, governments,
<table><caption>TABLE 5 | Pearson correlation matrix.</caption><thead><tr><th>Variable</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></tr></thead><tbody><tr><td>(1) GHGEmSale</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(2) CrossOC</td><td>-0.173</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(3) FinOC</td><td>0.258*</td><td>-0.022*</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(4) ForeOC</td><td>0.166**</td><td>-0.060*</td><td>0.772***</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(5) GovOC</td><td>0.408***</td><td>-0.446</td><td>0.026</td><td>0.067*</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(6) PenOC</td><td>0.067**</td><td>0.040***</td><td>0.406***</td><td>0.296***</td><td>0.095***</td><td>1</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(7) OtherOC</td><td>-0.045</td><td>0.152**</td><td>0.154***</td><td>0.144***</td><td>0.015</td><td>0.101***</td><td>1</td><td>—</td><td>—</td></tr><tr><td>(8) Lev</td><td>0.033</td><td>0.037</td><td>0.016</td><td>0.014</td><td>0.038</td><td>-0.020</td><td>0.022</td><td>1</td><td>—</td></tr><tr><td>(9) Capex</td><td>0.435</td><td>0.104***</td><td>0.188***</td><td>0.058*</td><td>0.092*</td><td>-0.012</td><td>-0.011</td><td>0.041</td><td>1</td></tr><tr><td>(10) Gov</td><td>0.155*</td><td>0.070**</td><td>0.149***</td><td>0.154***</td><td>-0.051*</td><td>0.130***</td><td>-0.52*</td><td>0.120***</td><td>0.404***</td></tr><tr><td>(11) Soc</td><td>-0.031</td><td>0.183***</td><td>0.279***</td><td>-0.007</td><td>0.162***</td><td>-0.063**</td><td>0.078**</td><td>0.017</td><td>0.387</td></tr><tr><td>(12) DivShare</td><td>-0.016</td><td>-0.017</td><td>-0.022</td><td>-0.017</td><td>-0.021</td><td>-0.003</td><td>-0.015</td><td>0.031</td><td>-0.063**</td></tr><tr><td>(13) Cash</td><td>0.115*</td><td>-0.096</td><td>-0.071</td><td>-0.096</td><td>0.033*</td><td>0.021</td><td>-0.016*</td><td>0.039</td><td>0.173*</td></tr><tr><td>(14) TotAss</td><td>0.431**</td><td>-0.079**</td><td>0.050*</td><td>0.232***</td><td>0.127***</td><td>0.079</td><td>0.351</td><td>0.019*</td><td>0.059**</td></tr><tr><td>(15) ROA</td><td>-0.183*</td><td>-0.009</td><td>-0.018*</td><td>-0.071</td><td>-0.041</td><td>-0.318</td><td>-0.009</td><td>0.071</td><td>-0.024</td></tr><tr><td>(16) BoardSize</td><td>0.141</td><td>0.221</td><td>0.213**</td><td>0.141**</td><td>0.127*</td><td>0.036</td><td>0.040</td><td>0.133</td><td>0.210</td></tr><tr><td>(17) BoardInd</td><td>-0.120*</td><td>0.047</td><td>0.322**</td><td>0.420**</td><td>0.211*</td><td>0.139*</td><td>0.110</td><td>-0.208*</td><td>0.320</td></tr><tr><td>(18) BoardGen</td><td>-0.143*</td><td>0.022</td><td>0.139*</td><td>0.114*</td><td>0.240*</td><td>0.143</td><td>0.104</td><td>0.011*</td><td>0.109*</td></tr><tr><td>(19) RD</td><td>0.107</td><td>-0.213</td><td>0.156</td><td>0.125</td><td>0.184</td><td>0.087</td><td>0.048</td><td>-0.143*</td><td>0.297*</td></tr><tr><td></td><td>(10)</td><td>(11)</td><td>(12)</td><td>(13)</td><td>(14)</td><td>(15)</td><td>(16)</td><td>(17)</td><td>(18)</td><td>(19)</td></tr><tr><td>(10) Gov</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(11) Soc</td><td>-0.041</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(12) DivShare</td><td>-0.002</td><td>-0.031</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(13) Cash</td><td>-0.101*</td><td>0.007</td><td>-0.301*</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(14) TotAss</td><td>0.133***</td><td>0.229***</td><td>0.116***</td><td>0.033</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(15) ROA</td><td>0.091*</td><td>-0.097*</td><td>-0.159*</td><td>-0.177*</td><td>-0.071*</td><td>1</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(16) BoardSize</td><td>0.217</td><td>0.210*</td><td>0.179</td><td>0.140</td><td>0.125</td><td>0.212</td><td>1</td><td>—</td><td>—</td><td>—</td></tr><tr><td>(17) BoardInd</td><td>0.322*</td><td>0.241*</td><td>0.134</td><td>0.422</td><td>0.434</td><td>0.320**</td><td>0.203**</td><td>1</td><td>—</td><td>—</td></tr><tr><td>(18) BoardGen</td><td>0.128*</td><td>0.237*</td><td>0.104</td><td>0.114</td><td>0.139</td><td>0.114*</td><td>0.030</td><td>0.068</td><td>1</td><td>—</td></tr><tr><td>(19) RD</td><td>0.086</td><td>0.095</td><td>0.117</td><td>0.209</td><td>-0.127</td><td>0.223*</td><td>0.193</td><td>0.140</td><td>0.188</td><td>1</td></tr></tbody></table>

and pension funds) and short-term investors (cross-holdings and “other” institutional investors). Table 8 lists the obtained results concerning the two regression models conducted using the two dimensions above.

The obtained empirical results underline the positive and significant effect (b = 2.14; p < 0.01) long-term investors (LongOC)

have on companies' GHG emission intensity. On the other hand, the second regression model presents empirical results suggesting the negative and significant (b = -1.55; p < 0.05) correlation that exists between short-term institutional investors (ShortOC) and corporations' GHG emissions. Conclusively, the results of Table 8 align with the initial conclusions derived from the baseline regression models illustrated in Table 6.

<footnote>*p < 0.05;</footnote>

<footnote>**p < 0.01;</footnote>

<footnote>***p < 0.001.</footnote>
<table><caption>TABLE 6 | Baseline regression models.</caption><thead><tr><th rowspan="3"></th><th colspan="6">GHGEmSale</th></tr><tr><th colspan="6">Estimate (p value)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>CrossOC</td><td>-2.93** (0.007)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>FinOC</td><td>—</td><td>2.01* (0.030)</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>ForeOC</td><td>—</td><td>—</td><td>1.62* (0.045)</td><td>—</td><td>—</td><td>—</td></tr><tr><td>GovOC</td><td>—</td><td>—</td><td>—</td><td>4.97*** (0.000)</td><td>—</td><td>—</td></tr><tr><td>PenOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>2.66** (0.005)</td><td>—</td></tr><tr><td>OtherOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-1.15 (0.175)</td></tr><tr><td>Lev</td><td>0.67 (0.275)</td><td>0.80 (0.588)</td><td>0.87 (0.185)</td><td>0.81 (0.278)</td><td>0.86 (0.166)</td><td>0.18 (0.209)</td></tr><tr><td>Capex</td><td>-2.99* (0.033)</td><td>1.67* (0.027)</td><td>2.06 (0.060)</td><td>1.51* (0.045)</td><td>1.60 (0.061)</td><td>1.76 (0.720)</td></tr><tr><td>Gov</td><td>4.70*** (0.000)</td><td>5.29*** (0.000)</td><td>4.53*** (0.000)</td><td>4.37*** (0.000)</td><td>5.11*** (0.000)</td><td>4.71*** (0.000)</td></tr><tr><td>Soc</td><td>2.30*** (0.000)</td><td>1.89*** (0.000)</td><td>1.83*** (0.000)</td><td>1.96*** (0.000)</td><td>1.88*** (0.000)</td><td>1.84*** (0.000)</td></tr><tr><td>DivShare</td><td>-0.61 (0.075)</td><td>-0.23 (0.086)</td><td>-0.47 (0.060)</td><td>-0.38 (0.070)</td><td>-0.35 (0.690)</td><td>-0.32 (0.683)</td></tr><tr><td>Cash</td><td>0.93* (0.042)</td><td>0.75* (0.033)</td><td>0.91* (0.043)</td><td>0.50** (0.006)</td><td>0.51* (0.037)</td><td>0.57* (0.041)</td></tr><tr><td>TotAss</td><td>0.00*** (0.000)</td><td>0.00*** (0.000)</td><td>0.00*** (0.000)</td><td>0.00*** (0.000)</td><td>0.00*** (0.000)</td><td>0.00*** (0.000)</td></tr><tr><td>ROA</td><td>-0.01* (0.023)</td><td>-0.02* (0.048)</td><td>-0.01 (0.053)</td><td>-0.01** (0.008)</td><td>-0.01* (0.040)</td><td>-0.02* (0.036)</td></tr><tr><td>BoardSize</td><td>1.38 (0.063)</td><td>1.35 (0.063)</td><td>1.40 (0.061)</td><td>1.59 (0.067)</td><td>1.44 (0.066)</td><td>1.42 (0.066)</td></tr><tr><td>BoardInd</td><td>-1.24* (0.030)</td><td>-1.30* (0.033)</td><td>-1.45* (0.033)</td><td>-1.31* (0.033)</td><td>-1.30* (0.031)</td><td>-1.26* (0.035)</td></tr><tr><td>BoardGen</td><td>-3.09 (0.307)</td><td>-3.02 (0.305)</td><td>-3.12 (0.312)</td><td>2.99 (0.322)</td><td>2.68 (0.301)</td><td>3.14 (0.307)</td></tr><tr><td>RD</td><td>-0.122 (0.155)</td><td>0.126 (0.156)</td><td>0.193 (0.148)</td><td>0.172 (0.142)</td><td>0.178 (0.157)</td><td>-0.914 (0.166)</td></tr><tr><td>Observations</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td></tr><tr><td>R<sup>2</sup></td><td>0.2867</td><td>0.2968</td><td>0.2721</td><td>0.3274</td><td>0.3122</td><td>0.2801</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.2610</td><td>0.2604</td><td>0.2588</td><td>0.2922</td><td>0.2881</td><td>0.2460</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>IndustryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

Note: T-statistics based on robust standard errors adjusted for heteroskedasticity are reported in parentheses.

*p*<0.05;

**p**<0.01;

***p**<0.001.

## 4.4 | Endogeneity Concerns

Empirical analysis focusing on the link between corporate governance and firms' environmental performance is likely to be confronted with endogeneity concerns. Specifically, self-selection bias and reverse causality are believed to be the two main causes of endogeneity concerns in research outputs focusing on corporate governance and environmental sustainability. Henceforth, as supplementary tests, we adopt the propensity score matching (PSM) and Heckman two-step estimation as this manuscript's endogeneity checks.

In an attempt to address potential concerns attributable to self-selection bias, we employed the PSM approach (Attig and

Cleary 2014). Specifically, following the PSM technique, we divide the initial sample into two different subsets consisting of organizations that belong to the geographical context attributable to high and low degrees of GHGEmSale. In doing so, we are able to denote the two subsets with a binary dummy variable. It is important to note that after matching the sample, we conducted a balance test to assess whether any statistical disparities remained between the treatment and control groups. The results indicated no significant differences, thereby confirming the success of the matching procedure. For transparency, the covariate balance test is reported within Table A2. Thereupon, we re-estimate our models using the matched sample, and the obtained results, which are in line with our baseline regression models, are presented in Table 9.
<table><caption>**TABLE 7** | Regression analysis for robustness checks excluding UK companies' subset from the initial sample.</caption><thead><tr><th></th><th colspan="6">Regression without UK firms</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>CrossOC</td><td>-2.50** (0.008)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>FinOC</td><td>—</td><td>1.64* (0.025)</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>ForeOC</td><td>—</td><td>—</td><td>1.41* (0.040)</td><td>—</td><td>—</td><td>—</td></tr><tr><td>GovOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>PenOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>2.26** (0.003)</td><td>—</td></tr><tr><td>OtherOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.83 (0.158)</td></tr><tr><td>Observations</td><td>3204</td><td>3204</td><td>3204</td><td>3204</td><td>3204</td><td>3204</td></tr><tr><td>R-Squared</td><td>0.2785</td><td>0.2842</td><td>0.2615</td><td>0.3083</td><td>0.2980</td><td>0.2655</td></tr><tr><td>Adjusted R-Squared</td><td>0.2588</td><td>0.2609</td><td>0.2511</td><td>0.2827</td><td>0.2838</td><td>0.2315</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>IndustryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

<table><caption>**TABLE 8** | Regression analysis conducted with long and short term IIs dimensions.</caption><thead><tr><th></th><th colspan="2">Regression with long and short OC categorization</th></tr><tr><th></th><th>(1)</th><th>(2)</th></tr></thead><tbody><tr><td>LongOC</td><td>2.14** (0.008)</td><td>—</td></tr><tr><td>ShortOC</td><td>—</td><td>-1.55* (0.040)</td></tr><tr><td>Observations</td><td>4107</td><td>4107</td></tr><tr><td>R<sup>2</sup></td><td>0.2812</td><td>0.2582</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.2490</td><td>0.2394</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td></tr><tr><td>CountryFE</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td></tr></tbody></table>

Furthermore, to minimize self-selection bias and correct sample-induced endogeneity, we employed the Heckman two-step estimation method. Specifically, we started by running a probit regression estimating the conditional distribution of the treatments using a set of covariates that capture the relevant attributes. This process incorporates all control variables. In the second step, we add the resulting inverse Mills ratio (IMR) to our models. First, we generate dummy variables for institutional investors OC using the industry average as cut-off points. The estimated parameters are employed to calculate the IMR, which

is then included as an additional explanatory variable in the second stage estimation. As depicted in Table 10, the obtained results align with our baseline regressions. Henceforth, it is safe to assume that selection bias should not be a significant concern of this manuscript.

Finally, given our sample characteristics, we are unable to conduct a proper difference-in-difference design. Henceforth, to further ensure the obtained results, we opted for two-stage least squares (2SLS). Specifically, following Aggarwal et al. (2011) and Luong et al. (2017), we construct an instrumental variable that captures variation in ownership structure that is exogenous to organizations' GHG emissions. Fundamentally, we use time-varying membership in MSCI All Country World Index and define the instrument as a dummy variable that equals to 1 when a firm is a member of MSCI and 0 when it is not.

The selection of MSCI membership as an instrumental variable is based upon prior scholarly literature demonstrating that inclusion in MSCI can significantly influence a firm's visibility and attractiveness to institutional investors (Aggarwal et al. 2005; Chakrabarti et al. 2005; Ferreira and Matos 2008; Leuz et al. 2010). Indeed, MSCI membership is time-varying; thus, organizations can be added and removed from it. The above-mentioned changes are largely exogenous to the organization's own strategic decisions. However, they can fundamentally alter its ownership structure by increasing exposure to global capital markets, attracting/discouraging capital and investments from certain groups of institutional investors (Aggarwal et al. 2005; Chakrabarti et al. 2005; Ferreira and Matos 2008; Leuz et al. 2010). The foregoing dynamic makes

<footnote>*p < 0.05;</footnote>

<footnote>**p < 0.01.</footnote>

<footnote>*p < 0.05;</footnote>

<footnote>**p < 0.01.</footnote>
<table><caption>**TABLE 9** | Regression results obtained from PSM.</caption><thead><tr><th></th><th colspan="6">One-to-one PSM</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>CrossOC</td><td>-2.22** (0.007)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>FinOC</td><td>—</td><td>1.37* (0.033)</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>ForeOC</td><td>—</td><td>—</td><td>1.18* (0.046)</td><td>—</td><td>—</td><td>—</td></tr><tr><td>GovOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>PenOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>2.11** (0.003)</td><td>—</td></tr><tr><td>OtherOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.90 (0.149)</td></tr><tr><td>Observations</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.2493</td><td>0.2517</td><td>0.2438</td><td>0.2480</td><td>0.2682</td><td>0.2126</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>CountryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

<table><caption>**TABLE 10** | Regression results obtained from Heckman two stage approach.</caption><thead><tr><th></th><th colspan="6">Heckman</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>CrossOC</td><td>-2.13** (0.006)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>FinOC</td><td>—</td><td>1.17* (0.031)</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>ForeOC</td><td>—</td><td>—</td><td>1.11* (0.044)</td><td>—</td><td>—</td><td>—</td></tr><tr><td>GovOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>PenOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>1.99** (0.002)</td><td>—</td></tr><tr><td>OtherOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.78 (0.130)</td></tr><tr><td>Inverse mills ratio (IMR)</td><td>-181.32 (-0.35)</td><td>-187.91 (-0.37)</td><td>-179.44 (-0.37)</td><td>-183.17 (-0.34)</td><td>-182.88 (-0.33)</td><td>-183.06 (-0.36)</td></tr><tr><td>Observations</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td></tr><tr><td>Adjusted R-Square</td><td>0.2357</td><td>0.2310</td><td>0.2406</td><td>0.2433</td><td>0.2530</td><td>0.2121</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>CountryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

MSCI membership a source of exogenous variation in institutional ownership that allows us to better isolate causal effects while minimizing concerns of endogeneity. To assess the validity of the instrumental variable application, we have relied on the classic Hausman (1978) test. The Wu-Hausman test is significant, and the obtained results are the following: b = 3.330 (p = 0.067).

As the initial step, we regress the endogenous variable on all chosen instruments, thus ensuring they have undergone relevance and exogeneity checks (Velte 2024b). In doing so, we are able to extract the residual of the endogenous variable. Thereafter, in the second step, we substitute the endogenous variable with its corresponding residual to then regress the dependent variable, thus following Aggarwal et al. (2011) and Luong et al. (2017)

<footnote>*p<0.05;</footnote>

<footnote>**p<0.01.</footnote>

<footnote>*p<0.05;</footnote>

<footnote>**p<0.01.</footnote>
approaches. The following Table 11 details the obtained results, and it underscores that the regressions control for firm, country, industry, and year fixed effects.

## 5 | Discussion

This research presents empirical findings demonstrating that cross-holdings' OC negatively affects companies' GHG emissions reduction. The preceding result is in harmony with part of the earlier academic literature (Cheng et al. 2022; Ducassy and Montandrau 2015; Rees and Rodionova 2013). However, it contradicts some previously published articles that provided non-confirmatory findings (García-Sánchez, Gallego-Álvarez, and Zafra-Gómez 2020). Our results show that more significant levels of cross-holdings OC will likely translate into fewer efforts to reduce GHG emissions. Several reasons could explain this. First, cross-holdings OC is adopted as a means to influence interconnected firms (Brooks et al. 2018; Gao et al. 2019; He et al. 2019; Kang et al. 2018), prioritizing the parent company's interests rather than the long-term benefits linked to environmental and social practices (Kavadis and Thomsen 2023). Second, cross-holdings have been found to diminish the decision-making authority and influence of external stakeholders and investors as a result of the significant level of control they exert (He et al. 2019; Correa-Garcia et al. 2020). This elucidates the diminished levels of CSR practices (Cheng et al. 2022; Ducassy and Montandrau 2015; Rees and Rodionova 2013), therefore further demonstrating the negative influence of their OC on corporations' GHG emissions reduction.

Second, this article presents empirical results suggesting a positive and significant relationship between financial institutions' OC and firms' reduction in GHG emissions. The preceding

results support previous scholarly articles (i.e., Manogna and Mishra 2020; Motta and Uchida 2018; Oh et al. 2011; Prado-Lorenzo et al. 2009; Rees and Rodionova 2013; Velte 2023; Wang et al. 2019). However, the obtained findings contradict part of the scholarly literature, since scholars gather empirical evidence suggesting a negative effect (Johnson and Greening 1999) or even no significant relationship at all (Dam and Scholtens 2012) between financial institutions' OC and firms' CSR practices. The key drivers behind FI's efforts to promote the environmental performance of their portfolio organizations are described as follows, thereby supporting this manuscript's findings. First, financial institutions are subjected to strict regulations on sustainability (Velte 2023) and great public scrutiny (Chalmers and van den Broek 2019) and are thus incentivized to foster CSR practices within their portfolio firms (Motta and Uchida 2018; Prado-Lorenzo et al. 2009) to improve their image and reputation (Mishra 2022; García-Meca and Pucheta-Martínez 2018) and to legitimize their position to their stakeholders (Ben Fatma and Chouaibi 2021; Kim and Yi 2015). Second, since they act as lenders, financial institutions would encourage sustainable behavior to increase firms' long-term value and lower their risk (García-Sánchez, Gallego-Álvarez, and Zafra-Gómez 2020), and maintain, if not grow, their portfolio companies' capitalization (Oh et al. 2011). Third, carbon reduction strategies allow businesses to access bank loans at relatively lower interest rates (Wang et al. 2019). Fundamentally, this manuscript's empirical insights underscore how higher OC of financial institutions is likely to result in organizations' interest and needs to establish stringent practices and strategic visions focusing on the notion of a carbon-neutral economy.

Third, this manuscript presents empirical findings suggesting that foreign institutional investors' OC has a positive and significant effect on enterprises' GHG emissions reduction,

<table><caption>TABLE 11 | Regression results obtained from 2SLS (Second stage regression).</caption><thead><tr><th></th><th colspan="6">2SLS</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>CrossOC</td><td>-2.06** (0.006)</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>FinOC</td><td>—</td><td>1.14* (0.037)</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>ForeOC</td><td>—</td><td>—</td><td>1.05* (0.033)</td><td>—</td><td>—</td><td>—</td></tr><tr><td>GovOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>PenOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>1.77** (0.002)</td><td>—</td></tr><tr><td>OtherOC</td><td>—</td><td>—</td><td>—</td><td>—</td><td>—</td><td>-0.87 (0.151)</td></tr><tr><td>Observations</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td><td>4107</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.2143</td><td>0.2110</td><td>0.2230</td><td>0.2212</td><td>0.2311</td><td>0.2015</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Firm FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>CountryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>IndustryFE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

<footnote>*p < 0.05;</footnote>

<footnote>**p < 0.01.</footnote>
hence supporting previously published articles (Chan 2010; Dyck et al. 2019; Kim et al. 2016; Krueger et al. 2020; Mbanyele 2023). Indeed, foreign institutional investors typically have a long-term investment perspective and thus they are motivated to encourage CSR initiatives in the companies they invest in (Bena et al. 2017; Dyck et al. 2019). Furthermore, to mitigate their portfolio exposure to regulatory risks and other environmental events associated with climate change (Krueger et al. 2020; Mbanyele 2023), foreign institutional investors often advocate for stringent environmental practices and initiatives to ensure the improved environmental performance of their portfolio companies (Ahmed et al. 2023; Chan 2010; Kim et al. 2016). The notion mentioned above is further corroborated by the neo-institutional theory utilized in this investigation, as foreign institutional investors are aware of climate-change-related issues. Thus, they are incentivized to make decisions in favor of carbon neutrality (Benlemlih et al. 2023; Cohen et al. 2023; Safiullah et al. 2022). On top of that, companies striving to meet foreign institutional investors' environmentally responsible practices and expectations and those willing to attract foreign institutional investors (Yu and Zheng 2020) may seek to reduce their GHG emissions. The preceding action aims to nurture their brand image, market positioning, long-term competitiveness, and attractiveness (Dyck et al. 2019) and mitigate risks (Mallin 1999).

Fourth, the findings align with part of the scholarly literature (Ahmed et al. 2023; Clò et al. 2017; Li and Zhang 2010; Motta and Uchida 2018), as it indicates that governments' OC has a positive and significant relationship with firms' environmental practices, thus promoting their environmental sustainability. However, part of the scholarly literature argues that government OC does not impact organizations' environmental sustainability practices and efforts, thus contradicting this manuscript and the preceding literature's empirical data (Dam and Scholtens 2012; García-Sánchez, Gallego-Álvarez, and Zafra-Gómez 2020; Lamoureux et al. 2019). Nonetheless, this article and previous scholarly studies' findings supporting the notion of governments' OC positive effect on corporations' environmental performance and practices are corroborated by governments' increased commitment to climate change and reaching environmental sustainable development (García-Sánchez et al. 2022; García-Sánchez, Rodríguez-Ariza, et al. 2020). Governments, being aware of climate change-related issues, are motivated to advocate for environmental sustainability, thus supporting the neo-institutional theory employed in this analysis (Wang et al. 2019). Furthermore, governmental entities are well known for their long-term orientation and, therefore, their investment strategies consider environmental, social, and ethical concerns (Aguilera et al. 2021; Eng and Mak 2003; Rees and Rodionova 2013). As a result, governments' OC leads to a reduction in corporations' GHG emissions, aligning with their governmental investors' interests and expectations concerning climate change and carbon neutrality (Thornton et al. 2003; Zhang et al. 2008).

Fifth, this manuscript presents empirical data highlighting a positive and significant relationship between pension funds' OC and companies' reduction of GHG emissions. This finding supports prior scholarly articles on the subject (i.e., Dyck et al. 2019; Kim et al. 2019; Oh et al. 2011; Rees and Rodionova 2013). The reasons underneath these results could be their long-term focus

(Cox et al. 2004; Gloßner 2019; Velte 2023) and the great degree of public scrutiny and regulatory pressures they are subjected to (Bolton and Kacperczyk 2021; Dyck et al. 2019; Fernando et al. 2017; Mishra 2022; Oh et al. 2011).

Finally, regarding the “other” institutional investors, previous empirical studies have found a positive relationship between charities (Cox et al. 2004; Kreander et al. 2009; Sparkes and Cowton 2004), insurance companies (Cox et al. 2004; Johnson and Greening 1999; Ullah et al. 2019), mutual funds (Chen et al. 2020; Manogna and Mishra 2020; Yadav 2020), and indexers (Chen et al. 2020; Dimson et al. 2015; Kim et al. 2019; Li, Zhang, et al. 2021). In contrast, other studies indicate no relationship between insurance companies' (Oh et al. 2011) and mutual funds' OC (Johnson and Greening 1999) and firms' CSR, while others report a negative effect of mutual funds' OC (Li, Zhang, et al. 2021). Nevertheless, our findings indicate the presence of a negative, but non-significant relationship between all the other institutional investors' OC and firms' GHG emissions reduction.

# 6 | Conclusions

This empirical investigation delves into the correlation between institutional investors' OC and corporations' GHG emissions. The authors employ a balanced panel data regression model for the empirical analysis. The necessary observations are obtained from the Thomson Reuters dataset, and the sample is composed of European publicly listed firms with data sources spanning from the business year 2015–2022. The selection of the foregoing contextual focus is informed by previous empirical bodies of work, thereby underscoring the similarities between organizations whose headquarters are located within EU countries (García-Sánchez, Rodríguez-Ariza, et al. 2020; Velte 2023; Velte 2024a). To construct a body of work that presents a comprehensive perspective on various institutional investors' OC on companies' GHG emissions, the authors employ García-Sánchez, Rodríguez-Ariza, et al. (2020) and Giordino et al. (2024, 2025) institutional investors categorization. Indeed, the preceding classification of institutional investors should enhance this article's comparability and reduce its limitations associated with fewer categories of institutional investors (Beck and Ferasso 2023; Breitenstein et al. 2021; Velte 2023). Listed below are this manuscript's practical and theoretical implications, and the study limitations and future research directions.

## 6.1 | Practical Contributions

The present study carries several practical implications. First, the obtained empirical results could be valuable for enterprises and organizations aiming to achieve a carbon-neutral future. Indeed, governmental entities and legislative bodies can establish regulations and laws to encourage the adoption of sustainable practices by corporations to reduce their GHG emissions intensity (Benlemlih and Yavaş 2023; Cohen et al. 2023; Huovila et al. 2022; Muktadir-Al-Mukit and Bhaiyat 2023; Rashidi-Sabet et al. 2022; Safiullah et al. 2022). The foregoing option could prove useful for firms operating in high-polluting and sensitive industry sectors. For example, governments' OC has the
potential to nurture corporations' initiatives aimed at reducing carbon emissions and promoting a greener future, particularly within sectors traditionally associated with poor environmental performance, such as the chemical industry sector (Benlemlih and Yavaş 2023).

Second, the findings discussed in this paper may offer valuable insights to corporations aiming to connect and attract specific dimensions of institutional investors. Moreover, it also underlines what institutional investors may deem relevant, thus providing companies with guidance on managing their relationships with these categories of institutional investors effectively (Giordino et al. 2024; García-Sánchez, Rodríguez-Ariza, et al. 2020).

Third, this empirical body of work might suggest how more than stakeholders and society's pressure towards carbon neutrality might be needed to ensure that institutional investors establish practices and processes to reduce their GHG emission intensity. Indeed, organizations may need help finding ways to implement processes and practices to reduce their carbon footprint (Gomez-Trujillo et al. 2020). Furthermore, this article underlines that parent companies and cross-holdings prioritize other operational and financial indicators over environmental sustainability and performance (Brooks et al. 2018; Gao et al. 2019; He et al. 2019; Kang et al. 2018).

Fourth, this article underlines the overall commitment of European companies to transforming their business models and processes to pursue a carbon-neutral future. Indeed, the foregoing need to change business practices and GHG emissions intensity may nurture new opportunities for corporations to establish new revenue streams through GHG-focused products, processes, and investments (Benlemlih et al. 2023; Van Zanten and Van Tulder 2018).

Finally, from a policy perspective, this manuscript underscores how initiatives like the European Climate Law (European Commission 2023) and the Paris Agreement (UNFCCC 2015) could positively contribute to reducing GHG emissions and increase institutional investors' attentiveness toward corporations' environmental sustainability. Specifically, within the context of the EU Corporate Sustainability Due Diligence Directive (European Commission 2024a), regulators could consider emphasizing the importance of supervisory mechanisms that specifically monitor organizations' ownership structure and cross-holdings as part of their governance frameworks to promote active environmental management practices. National supervisory authorities could cooperate with the European Securities and Markets Authority to develop standardized indicators on organizations' ownership structure, thereby promoting their inclusion within entities' due diligence obligations. In doing so, it would enable stakeholders and regulators to identify patterns where ownership concentration may hinder or incentivize active environmental performance enhancement. Furthermore, given the new Corporate Social Responsibility Directive (European Commission 2024b) and its related Sustainability Reporting Standards, this manuscript's empirical findings underscore the need for explicit disclosure requirements on organizations' ownership structure and its direct implications in shaping its governance mechanisms and strategic orientation. The above proposed action could be

operationalized by integrating ownership-related observations within existing frameworks and indicators such as ESG.

## 6.2 | Theoretical Contributions

Theoretically, the present empirical study expands the scholarly discourse surrounding institutional investors' OC and its impact on firms' environmental performance. Most prior studies focused on CSR practices and disclosure and the effect of various variables on board diversity and characteristics. Hence, this publication adds to the existing body of knowledge on the impact of institutional investors' OC on environmental performance (through a GHG emission proxy). This manuscript classifies institutional investors into multiple dimensions thanks to Giordino et al. (2024, 2025) and García-Sánchez, Rodríguez-Ariza, et al. (2020) works, and hence underlines the need for future scholars to distinguish institutional investors' effect on corporations' environmental performance. Furthermore, the preceding need to classify institutional investors into multiple dimensions helps academics understand potential reported differences among empirical findings of various bodies of research (Beck and Ferasso 2023; Mishra 2022; Velte 2023).

Second, the current scholarly literature focuses on the macroeconomic determinants of GHG emissions, giving little attention to how firms' ownership structure may influence GHG emissions and carbon neutrality (Benlemlih et al. 2023). However, the authors of this article fill this gap by exploring the effect various dimensions of institutional investors have in promoting GHG emissions reduction.

Third, previous scholarly literature explores the impact of institutional investors on CSR through disclosure practices and data from voluntary initiatives such as the CDP (Benlemlih et al. 2023). This manuscript fills the preceding research gap by utilizing an objective, verifiable measure of firms' environmental performance (GHG emissions).

Finally, this empirical body of work furthers our understanding of the neo-institutional theory and its application to institutional investors' OC effect on firms' environmental performance and carbon neutrality.

## 6.3 | Limitations and Directions for Future Research

This article has several limitations that present potential new avenues for future scholarly studies. First, the utilized dataset comprises observations from companies headquartered in several European countries. Moreover, due to differences in their reporting practices, banks and insurance companies have been omitted. Therefore, future studies should conduct empirical investigations with varying contextual focus. Indeed, the utilization of comparative studies between two countries with drastically different policies and legislations concerning GHG emissions and carbon neutrality could prove particularly interesting in underlining the effectiveness of various norms, policies, culture, and stakeholders (Benlemlih et al. 2023). Furthermore, future studies should explore industrial settings (such as banks
and insurance companies) (Dyck et al. 2019) to facilitate a more
nuanced examination of the correlation between institutional
investors' OC and corporations' GHG emissions. Addressing the
preceding research gap could help us understand policies and
legislation's impact on various industrial settings.

Second, this empirical work utilizes GHG emissions as an en-
vironmental performance indicator. Hence, future research
endeavors could employ other variables to gain a deeper under-
standing of the impact of institutional investors' OC on enter-
prises' environmental performance. Moreover, future studies
could use various variables concerning GHG emissions to
further clarify the relationship between various forms of in-
stitutional investors and corporations' GHG performance and
commitment to carbon neutrality.

Third, future studies might need to explore and test potential
moderators and mediators of the relationship between corpora-
tions' GHG emissions and various forms of institutional inves-
tors' OC. The foregoing notion is applicable to both firms and
boards characteristics, as well as other financial and economet-
ric measures and variables (Chen and Xie 2022).

Fourth, future scholarly literature might want to further explore
the mechanisms and practices employed by institutional in-
vestors to influence corporations' environmental management
practices. Specifically, it could yield insightful results to analyze
how each practice and mechanism established by institutional
investors to control their investment portfolio carries vari-
ous dimensions of impact in relation to firms corporate social
responsibility.

Finally, this empirical body of work is informed and limited
by neo-institutional theory. Therefore, future research endeav-
ors could explore the use of other theoretical frameworks such
as legitimacy and stakeholder theory to better understand the
motivations behind institutional investors' promotion of carbon
neutrality and enhanced environmental performance.

Acknowledgments

The authors have nothing to report. Open access publishing facilitated
by Universita degli Studi di Torino, as part of the Wiley - CRUI-CARE
agreement.

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<table><caption>TABLE A1 | Some of the most relevant articles focusing on institutional investors OC.</caption><thead><tr><td>Authors</td><td>Year</td><td>Title</td><td>Theoretical framework</td><td>Method</td><td>Findings</td><td>Proposed research gaps</td></tr></thead><tbody><tr><td>Aggarwal et al.</td><td>2005</td><td>Portfolio preferences of foreign institutional investors</td><td>Literature on investor protection, corporate governance and disclosure</td><td>US actively managed mutual funds. The authors utilized regressions to explore the proposed hypotheses.</td><td>US mutual funds outweigh countries with stronger shareholder rights and legal frameworks. Mutual funds support better disclosure.</td><td>The need for dynamic and time series analysis focusing on institutional investors. Specifically, investigation of various forms of institutional investors.</td></tr><tr><td>Aguilera et al.</td><td>2021</td><td>State ownership, political ideology, and firm performance around the world</td><td>Agency theory and institution-based view</td><td>Meta-analytic regression of observations pertaining to organizations from 131 countries</td><td>Negative association between state ownership and organizations performance. High political involvement constraints organizations agility and responsiveness.</td><td>They require a more granular exploration of institutional investors OC effect on companies performance.</td></tr><tr><td>Ahmed et al.</td><td>2023</td><td>Financial sanctions and environmental, social, and governance (ESG) performance: A comparative study of ownership responses in the Chinese context.</td><td>Agency theory</td><td>Focuses on Chinese non-financial firms and it uses fixed-effects regressions to explore the proposed hypotheses.</td><td>Government and foreign institutional investors OC have a positive link with organizations ESG.</td><td>They highlight the need to conduct cross-country investigations. Additionally, they underscore the need to explore the financial sector.</td></tr><tr><td>Alshbili et al.</td><td>2019</td><td>Ownership types, corporate governance and corporate social responsibility disclosures: Empirical evidence from a developing country.</td><td>Neo-institutional theory</td><td>Focuses on oil and gas companies experiencing sanctions. It uses fixed-effects regressions to explore the proposed hypotheses</td><td>Positive and significant effect of government ownership, joint ventures, foreign investors OC towards organizations CSR disclosure.</td><td>They underscore the need to employ theoretical frameworks such as legitimacy and institutional theory. Furthermore, it is important to test environmental and social sustainability proxies.</td></tr><tr><td>Bena et al.</td><td>2017</td><td>Are foreign investors locusts? The long-term effects of foreign institutional ownership</td><td>Short-termism and monitoring hypotheses</td><td>Cross country study with observations from 30 countries. The authors utilized fixed-effects regressions</td><td>Foreign institutional OC has a positive effect on organizations innovation, employment and long-termism</td><td>Further investigate the differences between foreign and domestic investors OC. Additionally, explore institutional investors from a more heterogeneous perspective.</td></tr><tr><td>Benlemlih et al.</td><td>2023</td><td>Institutional ownership and greenhouse gas emissions: A comparative study of the UK and the USA</td><td>Neo-institutional theory</td><td>Sample composed by firms from the USA and UK. The authors utilize fixed effect regressions</td><td>Institutional investors OC does reduce organizations GHG emissions.</td><td>Explore the proposed hypotheses through a more granular classification of institutional investors. Additionally, they underscore the need to conduct more cross-country investigations.</td></tr></tbody></table>

(Continues)
<table><caption>TABLE A1 | (Continued)</caption><thead><tr><th>Authors</th><th>Year</th><th>Title</th><th>Theoretical framework</th><th>Method</th><th>Findings</th><th>Proposed research gaps</th></tr></thead><tbody><tr><td>Chalmers et al.</td><td>2019</td><td>Financial volatility and public scrutiny as institutional determinants of financial industry firms' CSR</td><td>Institutional theory of CSR</td><td>Sample composed by 170 European firms. The authors employ fixed-effect regression models to test their proposed hypotheses</td><td>During times of high financial volatility, investors are likely to focus on firms CSR reporting. In doing so, organizations ameliorate their overall standing and attractiveness to external stakeholders.</td><td>Explore CSR reporting vs. actual CSR performance. Indeed, they underscore the need to focus on environmental and social proxies.</td></tr><tr><td>Cheng et al.</td><td>2022</td><td>Common institutional ownership and corporate social responsibility</td><td>Anti-competitive view and coordination view</td><td>Dataset composed of organizations from the USA. The authors employ regressions with fixed effects</td><td>Common institutional ownership has a negative and significant effect on organizations CSR, employee diversity and relations.</td><td>They underscore the need to explore other dimensions of institutional investors and their effect on social and environmental performance. Additionally, longitudinal qualitative studies could contribute to the literature.</td></tr><tr><td>Clò et al.</td><td>2017</td><td>Ownership and environmental regulation: Evidence from the European electricity industry</td><td>Mixed oligopoly model</td><td>Empirical analysis on 29 European countries. The authors employ panel data econometrics through fixed and random effects regressions.</td><td>Higher degrees of public ownership are positively associated with lower degrees of environmental degradation.</td><td>Explore the link between organizations environmental performance and their financial outcomes. Explore different designs of institutional ownership.</td></tr><tr><td>Cohen et al.</td><td>2023</td><td>Institutional investors. climate disclosure, and carbon emissions</td><td>Institutional investors' role in sustainability matters and voluntary climate related disclosure</td><td>Dataset composed of organizations from 51 countries. The authors utilized OLS regressions with multiple fixed effects.</td><td>Organizations with higher degrees of institutional investors are likely to disclose their climate related performance.</td><td>They underscore the need to untangle causality and further explore the role of organizations ownership concentration.</td></tr><tr><td>Dam and Scholten</td><td>2012</td><td>Does ownership type matter for corporate social responsibility?</td><td>Agency theory, instrumental stakeholder theory and ownership heterogeneity</td><td>Cross-sectional study of 691 European organizations. The authors employ OLS regressions with industry fixed effects.</td><td>Institutional investors and banks have no significant effect on organizations CSR. State ownership does have a positive effect on organizations commitment to CSR.</td><td>There is a growing need for longitudinal studies utilizing panel data. Furthermore, explore the effect of other institutional investors on firms CSR.</td></tr><tr><td>Fang et al.</td><td>2015</td><td>Foreign institutional ownership and the global convergence of financial reporting practices</td><td>Agency theory and international governance perspective</td><td>Large scale empirical analysis using cross-border equity holdings of institutional investors</td><td>Foreign institutional investors are more likely to engage with firms with a stronger focus on corporate governance.</td><td>Explore the governance mechanisms through which institutional investors engage and control firms. Explore a broader range of institutional investors.</td></tr></tbody></table>

(Continues)
<table><caption>TABLE A1 | (Continued)</caption><thead><tr><td>Authors</td><td>Year</td><td>Title</td><td>Theoretical framework</td><td>Method</td><td>Findings</td><td>Proposed research gaps</td></tr></thead><tbody><tr><td>García-Meca and Pucheta-Martinez</td><td>2018</td><td>How institutional investors on boards impact on stakeholder engagement and corporate social responsibility reporting</td><td>Agency and stewardship theory combined with the resource dependence theory.</td><td>Spanish non-listed firms. The authors utilize regression models with firm and year fixed effects.</td><td>Banks and insurance companies have a positive effect on organizations' environmental performance. Funds negatively influence organizations CSR practices.</td><td>The authors indicate the necessity to conduct similar studies within different contexts. Additionally, the authors underscore the need to explore various dimensions of institutional investors.</td></tr><tr><td>García-Sanchez et al.</td><td>2020</td><td>The effect of institutional ownership and ownership dispersion on eco-innovation</td><td>Resource-based theory, institutional theory and agency theory.</td><td>Sample composed by firms from 71 countries. The authors employ fixed effects regressions.</td><td>Long term institutional investors have a positive and significant effect on organizations eco-innovation. On the other hand, short term focus institutional investors have a negative effect on organizations eco innovation.</td><td>Future studies should further explore the various dimensions of institutional investors and their effect on organizations CSR and environmental proxies. There is a great need for a granular classification of institutional investors.</td></tr><tr><td>García-Sanchez et al.</td><td>2020</td><td>Do institutional investors drive corporate transparency regarding business contribution to the sustainable development goals?</td><td>Stakeholder theory</td><td>Sample composed by 989 international organizations. The authors employ probit panel data regressions with random effects.</td><td>Foreign institutional investors and pension funds have a significant effect on organizations sustainable development goals related disclosure.</td><td>Explore the dimension specific effect of a more granular division of institutional investors.</td></tr><tr><td>Giordino et al.</td><td>2025</td><td>The impact of institutional ownership structure on corporate ESG performance: empirical evidence for the European capital market</td><td>Legitimacy theory</td><td>Sample composed by European firms. The authors employ fixed effects regressions</td><td>The authors obtain empirical results indicating the positive effect various forms of institutional investors have on organizations ESG performance.</td><td>They underscore the need to explore environmental and social proxies.</td></tr><tr><td>Giordino et al.</td><td>2024</td><td>Institutional investors ownership concentration and its effect on disclosure and transparency of United Nations sustainable development goals.</td><td>Legitimacy theory</td><td>Sample composed by European firms. The authors employ fixed effects regressions</td><td>The authors obtain empirical results indicating the positive effect various forms of institutional investors have on organizations' SDGs disclosure.</td><td>They underscore the need to explore environmental and social proxies.</td></tr><tr><td>He et al.</td><td>2019</td><td>Internalizing governance externalities: The role of institutional cross-ownership</td><td>Theories of corporate governance externalities and market based mechanisms.</td><td>The authors utilize OLS regressions with fixed effects. The adopted sample is composed by international firms from various countries.</td><td>Institutional investors with higher cross-ownership in peer firms are more likely to vote against management and governance proposals.</td><td>Explore the links and relationships that exist within institutional settings. Widen the heterogeneity of institutional investors classification.</td></tr></tbody></table>

(Continues)
<table><caption>TABLE A1 | (Continued)</caption><thead><tr><td>Authors</td><td>Year</td><td>Title</td><td>Theoretical framework</td><td>Method</td><td>Findings</td><td>Proposed research gaps</td></tr></thead><tbody><tr><td>Luong et al.</td><td>2017</td><td>How do foreign institutional investors enhance firm innovation?</td><td>Agency theory</td><td>Data is gathered fro4.239 US companies. The adopted method consists of regressions.</td><td>Positive relationship between foreign institutional investors and innovation.</td><td>Further research should focus on the heterogeneity of institutional investors.</td></tr><tr><td>Mishra</td><td>2022</td><td>Does institutional ownership discourage investment in corporate R&D?</td><td>Agency theory and managerial career concerns</td><td>Dataset composed by firms from the S&P 1500. The authors employ regressions with fixed effects.</td><td>Institutional investors have a positive and U shaped effect on organizations research and development endeavors.</td><td>Explore cross-country effects. Explore how different institutional investors share organizations commitment to CSR.</td></tr><tr><td>Rahim et al.</td><td>2024</td><td>Country-level heterogeneity in foreign institutional investment horizons and firm value</td><td>Agency theory</td><td>Dataset composed by organizations from 32 countries. The chosen method consists of fixed effects regressions.</td><td>Long term institutional investors enhance organizations' value. Short-term institutional investors do not.</td><td>The effect of regulatory environments on shaping institutional investors' orientation and commitment.</td></tr><tr><td>Safiullah et al.</td><td>2022</td><td>Do all institutional investors care about corporate carbon emissions?</td><td>Active, exploitation and passive monitoring view</td><td>Dataset composed by 2106 firms from the USA. The authors employ fixed effects panel regressions.</td><td>Aggregate institutional ownership is negatively associated with carbon emissions. Stronger effects come from long term focused institutional investors.</td><td>Explore the impact of foreign vs. domestic institutional investors.</td></tr><tr><td>Velte</td><td>2024a</td><td>Institutional ownership and board governance. A structured literature review on the heterogeneous monitoring role of institutional investors</td><td>Governance mechanisms and ownership structure. Agency theory</td><td>Structured literature review.</td><td>A conceptual framework underscoring the current state of the art concerning institutional investors OC effect on various dimensions.</td><td>Further explore the link between heterogeneous institutional investors and organizations CSR. Explore the long term outcomes associated with holding institutions.</td></tr></tbody></table>
<table><caption>TABLE A2 | Balance test conducted on the matched sample.</caption><caption>Covariance balance test of the matched sample</caption><thead><tr><th rowspan="2">Variables</th><th colspan="2">Control (Controlrist dummy = 0)</th><th colspan="3">Treatment (Control dummy = 1)</th></tr><tr><th>Number of Obs.</th><th>Mean</th><th>Number of Obs.</th><th>Mean</th><th>Mean diff.</th></tr></thead><tbody><tr><td>CrossOC</td><td>2053</td><td>0.710</td><td>2053</td><td>0.704</td><td>-0.006</td></tr><tr><td>FinOC</td><td>2053</td><td>0.103</td><td>2053</td><td>0.092</td><td>-0.011</td></tr><tr><td>ForeOC</td><td>2053</td><td>0.572</td><td>2053</td><td>0.585</td><td>0.013</td></tr><tr><td>GovOC</td><td>2053</td><td>0.196</td><td>2053</td><td>0.200</td><td>0.004</td></tr><tr><td>PenOC</td><td>2053</td><td>0.028</td><td>2053</td><td>0.032</td><td>0.004</td></tr><tr><td>OtherOC</td><td>2053</td><td>0.012</td><td>2053</td><td>0.014</td><td>0.002</td></tr><tr><td>Lev</td><td>2053</td><td>24.631</td><td>2053</td><td>24.783</td><td>0.152</td></tr><tr><td>Capex</td><td>2053</td><td>0.058</td><td>2053</td><td>0.062</td><td>0.004</td></tr><tr><td>Gov</td><td>2053</td><td>55.001</td><td>2053</td><td>54.627</td><td>-0.374</td></tr><tr><td>Soc</td><td>2053</td><td>41.847</td><td>2053</td><td>42.124</td><td>0.273</td></tr><tr><td>DivShare</td><td>2053</td><td>9.161</td><td>2053</td><td>9.236</td><td>0.075</td></tr><tr><td>Cash</td><td>2053</td><td>1.948</td><td>2053</td><td>1.961</td><td>0.013</td></tr><tr><td>TotAss</td><td>2053</td><td>13.782</td><td>2053</td><td>13.998</td><td>0.216</td></tr><tr><td>ROA</td><td>2053</td><td>4.945</td><td>2053</td><td>5.052</td><td>0.107</td></tr><tr><td>BoardSize</td><td>2053</td><td>8.801</td><td>2053</td><td>8.936</td><td>0.135</td></tr><tr><td>BoardInd</td><td>2053</td><td>0.447</td><td>2053</td><td>0.478</td><td>0.031</td></tr><tr><td>BoardGen</td><td>2053</td><td>0.361</td><td>2053</td><td>0.350</td><td>-0.011</td></tr></tbody></table>

Biographies

Daniele Giordino is a Research Fellow at the Department of Management “Valter Cantino” of the University of Turin, Italy. He graduated from both a bachelor (BA) and a master (MSc) in Accounting and Finance at the University of Winchester, UK. His research interests focus on the Accounting field. In particular, he is interested in the development of future research on the following themes: SMEs, twin transition, CSR, digitalization and smart technologies.

Elisa Ballesio is a PhD student at the Department of Management “Valter Cantino”, at the University of Turin, Italy. She holds a bachelor’s degree in Corporate Communication Management and a master’s degree in Accounting, Financial Management and Control, both obtained from the University of Turin. In the past, she has worked as an R&D controller in the automotive sector. Her research interests focus on the sustainability and accounting fields. In particular, she is interested in sustainability reporting, gender parity, and the integration of Artificial Intelligence (AI) in accounting practices.

Aradhna Galgotia is an academic with strong research interests in AI, emerging technologies, organizational development, sustainability, and climate change. Her research has appeared in leading International journals, including the Journal of Enterprise Information Management, Journal of Knowledge Management, Sustainable Development, and the Journal of Global Information Management, among others.

Laura Broccardo is currently Associate Professor in Management Control and Accounting at the Department of Management “Valter Cantino”, University of Turin, Italy. The main research interests are in management accounting, cost management, strategic management, governance, SMEs, family business and the organizational and behavioral aspects of accounting. The researches publications focus on management control in profit and non-profit companies, smart city governance, business models and sustainable business models, sustainability and digitalization. The research is conducted both applying qualitative and quantitative methods and also literature reviews. Furthermore, she teaches management accounting, management control in SMEs, business organization courses and strategic planning and control course and she is involved in many research projects. She has published in a variety of prestigious international journals and she also serves as a reviewer for various prestigious international journals.