The Impact of ESG Performance of Acquirer on the Long-Term Performance of Cross-Border Mergers and Acquisitions of China A-Share Listed Companies: An Analysis Based on Two-Way Fixed Effect and Threshold Effect

Abstract

As Environmental, Social, and Governance (ESG) gradually become the common language for sustainable development of international society and international cooperation in China, it is worth discussing whether ESG practices can help Chinese enterprises shape a responsible international image, overcome the liability of foreignness (LOF) and improve the long-term performance of cross-border mergers and acquisitions (M&As). On the basis of theoretical discussion, combined with the panel data of cross-border M&As of China A-share listed companies from 2010 to 2021, this paper empirically examines that the ESG performance of acquirers has a significant positive impact on the long-term performance of cross-border mergers and acquisitions (M&As) of China A-share listed companies. Furthermore, the ESG performance of environment and governance dimensions and heavily polluting enterprises has stronger incentive effects on the long-term performance of cross-border M&As. The ESG performance of the acquirer positively affects the long-term performance of cross-border M&As of China A-share listed companies by acquiring capital market resources, product market competitiveness, regulatory legitimacy, and enhancing internal synergy.

1. Introduction

With the globalization of the economy, cross-border mergers and acquisitions (M&As) have become an important means for Chinese enterprises to expand into international markets, acquire strategic resources, and enhance competitiveness [1,2]. Chinese enterprises can seek key strategic assets such as knowledge, technology, and brand through overseas mergers and acquisitions of enterprises from developed countries, so as to realize the transition of capabilities [3,4,5,6]. In 2023, the total value of overseas M&As announced by Chinese enterprises was USD 39.83 billion, a 20.3% year-on-year increase, achieving month-on-month growth for three consecutive quarters. Among these, the M&A value involving countries jointly built under the “Belt and Road Initiative” increased by 32.4% year-on-year [7]. This active trend is expected to continue until 2025. The total transaction volume of Chinese enterprises’ cross-border M&A market in the first quarter reached 8.9 billion U.S. dollars, a 77% year-on-year increase [8]. At present, although the number of Chinese enterprises participating in cross-border M&As continues to rise, the proportion of those ultimately achieving good long-term performance remains relatively small, and many cross-border M&As struggle to realize their initial objectives [9].

Internationalization of enterprises is not a smooth road. Transnational operations face significant differences in system, culture, and economy between the home and host countries [10]. As outsiders, multinational enterprises naturally encounter discriminatory treatment and additional operational burdens when interacting with key stakeholders such as governments, consumers, and suppliers in host countries (the costs of unfamiliarity, relationships and discrimination [10]) or “Liability of Foreignness”(LOF) [11]. This disadvantage is rooted not only in geographical or cultural distance, but also in structural factors such as lack of legitimacy and asymmetric information [11]. Specifically, in cross-border M&As, due to a lack of understanding and adaptation to the host country’s institutional environment (such as legal, political, and social systems), acquirers face the issue of “lack of legitimacy,” making it difficult to gain local recognition and trust. Simultaneously, compared to domestic enterprises, acquirers often have insufficient knowledge of the target company, the local market, and business practices, forming the problem of “information asymmetry”. In the current complex and volatile global situation, with intensified geopolitical conflicts, the role of LOF in hindering enterprises ‘international market expansion has become increasingly prominent, and its significant threat to the long-term performance of cross-border M&As has been widely recognized [12]. Meanwhile, this challenge is particularly severe for enterprises in emerging economies such as China [1]. These enterprises often face a double disadvantage compared to multinational enterprises from developed countries [13]. In addition to LOF, another additional disadvantage arises from the institutional environment differences between the home country and the developed host country (e.g., market maturity, regulatory transparency, intellectual property protection), the level of development, and potential national image stereotypes (such as “low-end manufacturing” and a “lack of institutions”) [14]. This additional disadvantage may exacerbate mistrust and discriminatory treatment among host country stakeholders (e.g., vigilance over incentives for technology transfer, higher scrutiny of compliance), making it more costly to gain legitimacy and build trust, which in turn poses greater barriers to post-M&A integration and long-term performance [15]. However, existing research indicates that active corporate social responsibility (CSR) can help multinational enterprises, especially those from emerging economies with relatively weak institutional environments, alleviate the deficiencies of their home country systems (e.g., corruption, imperfect regulation) and mitigate negative stereotypes caused by these institutional deficiencies. This can effectively help overcome LOF, especially the additional disadvantages associated with “emerging economy identity,” and promote overseas survival and value creation [13].

In this context, Environmental, Social, and Governance (ESG) practices are considered crucial non-market strategies for companies in emerging economies like China to address their inherent dual disadvantages [16]. Drawing upon the Sustainability Accounting Standards Board (SASB) definition, ESG encompasses a range of Environmental, Social, and Governance practices and performances of a company that can significantly affect its financial performance and long-term value [17]. ESG extends beyond the social and environmental responsibilities emphasized by CSR by also evaluating a company’s internal structure, transparency, and decision-making mechanisms through the governance dimension [18]. The three pillars of environment, society, and governance are not isolated entities but are interdependent and mutually reinforcing. Environmental and social sustainability constitute the core of sustainable development. Organizations directly implement sustainable development requirements by actively considering environmental factors and managing their social impacts [19]. Their fundamental aim is to foster the healthy evolution of the environment and the harmonious progress of society. Governance is viewed as a foundational element intrinsically linked to the effective consideration of environmental and social factors within an organization and is considered key to addressing environmental and social issues. Together, these elements form a critical pillar for maximizing an organization’s contribution to sustainable development and ensuring its own long-term viability [19]. In ESG rating evaluations, various institutions synthesize the assessment results of the E, S, and G components, and the resulting comprehensive ESG index reflects an organization’s overall performance in pursuing sustainable development. With the increasing prominence of global sustainability challenges, such as climate change and socioeconomic inequality, and the rise of global sustainable investment concepts, a growing number of investors and institutions are integrating ESG performance into their investment decisions. The ESG framework has become a significant tool and a “common language” for the international community to measure and promote sustainable development due to its comprehensiveness [20]. Consequently, the adoption of ESG has become an irreversible trend for Chinese enterprises venturing overseas and a key driver for enhancing their international competitiveness and achieving sustainable development [21]. For Chinese companies seeking strategic assets (such as technology and brand) to facilitate capability transition, ESG practice is not merely a compliance requirement but also a strategic instrument for proactively bridging institutional gaps, reshaping their international image, and building long-term trust [1]. Faced with the liability of foreignness (LOF) during internationalization, enterprises in emerging economies are increasingly adopting non-market strategies, including social responsibility initiatives, as a response [22,23], seeking synergy and complementarity between internationalization and ESG strategies [24].

Although existing research has touched upon the role of ESG in enterprise internationalization, a systematic investigation focusing on its long-term performance in cross-border M&As remains a significant gap. A significant body of literature primarily discusses the impact of ESG on internal corporate performance [25]. These studies generally find that positive ESG performance was associated with enhanced financial performance, higher innovation levels, lower financing constraints, and increased corporate value [25]. These findings affirm the importance of ESG from the perspective of internal operations and provide a foundation for this study to explore the role of ESG in the more complex context of cross-border M&A scenarios.

Previous studies have begun to focus on the relationship between ESG and cross-border M&As, but mainly concentrating on the initial stages of M&As. Qiao Lu (2015) revealed that strong corporate social responsibility can significantly improve the completion rate of cross-border M&As [9]. Jiang Qiankun et al. (2024) corroborate this view [26], finding that positive ESG performance is also associated with a higher cross-border M&A success rate. While these studies offer preliminary support for the idea that ESG plays an active role in the M&A process, they do not delve into the long-term performance impact following M&A completion.

Xie Hongjun et al. (2024), from the perspective of international direct investment (FDI), pointed out that social inclusion, as exhibited by ESG, helps overcome the LOF and positively affects FDI inflows [27]. This finding aligns with the theoretical basis of this study, suggesting that ESG may mitigate outsider disadvantage during internationalization by enhancing legitimacy and building trust. However, the focus of this study is on FDI attraction rather than post-merger firm performance. Shen Minghao et al. (2024) found that media attention to ESG significantly promoted the number and scale of digital cross-border M&As [28], which emphasized the importance of ESG information in M&A decisions, but also failed to examine long-term integration and performance after M&As. Based on the above, the existing literature provides valuable insights for understanding the potential role of ESG in corporate operations and internationalization processes. However, in-depth and focused research is still lacking regarding how ESG systematically affects the long-term performance of cross-border M&As. This study aims to fill this research gap by examining the impact of acquirer ESG performance on the long-term performance of cross-border M&As and its underlying mechanisms, and further analyzing the threshold effect of host country institutional complexity in this relationship, thereby providing a more comprehensive understanding of the role of ESG in corporate internationalization strategies.

Based on LOF, this paper explores the impact of the ESG performance of Chinese listed companies on the long-term performance of cross-border M&As and their internal mechanisms from the stakeholder perspective. We empirically analyze the cross-border M&A events initiated by China A-share listed companies from 2010 to 2021. The potential contributions of this paper are as follows: First, it expands the perspective of cross-border M&A performance research. Compared to the existing literature focusing on corporate characteristics (e.g., management capabilities, resources, experience) and external environmental factors (such as geographical distance and institutional differences), this paper provides a novel perspective for understanding the long-term results of cross-border M&As from the perspective of the external informal system (ESG rating). This offers enlightening insights for Chinese enterprises seeking to build a competitive advantage in cross-border M&As. This study not only has practical guidance value for enterprises to improve the effectiveness of cross-border M&As, but also has positive significance for promoting the high-quality development of the Chinese ESG ecosystem and constructing a Chinese ESG discourse system in the international market. Third, this study innovatively introduces and verifies host country institutional complexity as an important threshold variable based on institutional theory. It finds that this complexity can enhance ESG’s positive effect on the long-term performance of cross-border M&As, a nuance not fully discussed in the previous literature. This expands the situational boundary of ESG value creation, deepens the research of institutional theory in the context of cross-border M&As and ESG, and broadens the application scope of institutional theory, providing a more comprehensive and dynamic perspective for other scholars seeking to understand the factors affecting the long-term performance of cross-border M&As.

2. Theoretical Analysis and Research Hypotheses

2.1. Liability of Foreignness

Hymer (1960) first proposed the concept of “overseas operating costs” to highlight the additional risks and costs incurred by multinational enterprises in overseas expansion [29], and Zaheer (1995) systematically introduced this phenomenon into “LOF”. Following thorough research on LOF by Western scholars [11], it is generally accepted that the lack of legitimacy and asymmetric information arising from the differences between home and host countries in legal norms, cultural customs, business practices, stakeholder preferences, and behavioral patterns are key determinants of LOF [30]. These disadvantages place multinational firms at a competitive disadvantage when operating in host markets compared to domestic firms and significantly impact the long-term performance of cross-border M&As [31].

2.1.1. Lack of Legitimacy

From a sociological perspective, legitimacy refers to the state in which an action or organization is considered desirable and acceptable within a particular system of social beliefs, norms, and values [32]. Multinational enterprises, as “outsiders” entering new markets, naturally face legitimacy deficiencies in regulatory, normative, and cognitive dimensions, which are directly related to their survival and development in host countries and profoundly affect the long-term performance of cross-border mergers and acquisitions [33].

The lack of regulatory legitimacy manifests in the lack of adaptability of multinational enterprises’ business conduct to the formal institutional environment of host countries, such as laws, regulations, and policies, which may lead to obstacles in obtaining necessary business licenses, land resources and government contracts, and require additional resources and time to adjust their business models to comply with local regulations. Long-term lack of regulatory legitimacy will increase the operating costs, legal risks, and may lead to conflicts with regulators, thus significantly damaging the long-term performance of cross-border M&As [34].

The lack of normative legitimacy stems from the conflict between the behavior of multinational enterprises and the informal social norms, cultural customs, ethics, and other deep-rooted structures of host countries [35]. Ignoring or violating local social norms and cultural practices can lead to friction and conflict in employee recruitment, labor relations, community interaction, etc., damaging their social reputation, affecting employee belonging and productivity, increasing management costs, and negatively impacting post-merger integration and synergies, ultimately affecting long-term performance [34].

The lack of cognitive legitimacy reflects the degree of understanding, acceptance, and trust of multinational enterprises among stakeholders in host countries [36]. This deficiency is often influenced by cultural differences, value conflicts, nationalist sentiments, and stereotypes [35,36]. A lack of cognitive legitimacy will diminish the credibility of enterprises, increase friction with suppliers, customers, and other transactional partners, and elevate transaction costs [34]. Negative perceptions may also trigger prejudice and resistance from stakeholders in the host country, making it difficult for multinational enterprises to gain market share and thereby hindering the long-term success of M&As.

2.1.2. Information Asymmetry

Information asymmetry is another important dimension of LOF besides lack of legitimacy, primarily manifesting in two aspects: first, a lack of understanding of the host country market, institutional environment, and target enterprise information; second, an insufficient understanding of the identity, products, and services of multinational enterprises by stakeholders in the host country [34].

On the one hand, for multinational corporations, the host market constitutes a relatively unfamiliar external environment wherein legal regulations, business practices, consumer preferences, and so forth may differ substantially from those of the home country [36]. In the early stage of M&A, asymmetric information can lead to difficulties in accurately evaluating the target enterprise’s value and potential risks, as well as discrepancies in the understanding of accounting standards, tax systems, labor regulations, and other host country specificities. This can result in excessive M&A premiums and unforeseen obstacles and costs during the post-M&A integration process. In the later stage of M&A, a lack of knowledge regarding local business practices and market dynamics will also impede multinational companies’ ability to formulate effective business strategies, cause them to miss market opportunities, and even expose them to the risk of opportunistic behavior, ultimately affecting the long-term profitability and market competitiveness of the M&A [37].

On the other hand, stakeholders in host countries are inclined towards mistrust and negative expectations due to a lack of familiarity with “foreign” multinational enterprises. Consumers may be unfamiliar with foreign brands or influenced by nationalist sentiments, leading them to favor local products even if the quality and price of foreign products are more favorable. This can directly constrain the sales and market share of M&A enterprises in host countries and impede long-term development [38]. Moreover, suppliers may demand more stringent terms of cooperation due to concerns about risks associated with partnering with foreign companies, such as supply chain instability and cultural conflicts. This can escalate the operating costs of M&A enterprises, thereby posing a threat to the long-term performance of cross-border M&As [36].

2.2. Acquirer ESG Performance and Liability of Foreignness

Strong ESG performance not only internally reflects the enterprise’s commitment to environmental protection, social responsibility, and standardized governance, but is also regarded as a crucial indicator to evaluate the enterprise’s stable operation ability, risk management level, and long-term value creation potential [38]. For parties involved in cross-border M&As who are facing the LOF dilemma, proactively enhancing ESG performance offers an effective mitigation strategy. This strategy not only helps to compensate for the aforementioned legitimacy deficits but also significantly alleviates information asymmetry among stakeholders in the host country, ultimately contributing to improved long-term M&A performance [34].

2.2.1. Acquirer ESG Performance Addresses Lack of Legitimacy

The acquirer’s strong ESG performance can enhance its legitimacy in the host country in multiple dimensions, thus effectively addressing the inherent legitimacy disadvantages of outsiders.

At the regulatory legitimacy level, the positive ESG practices of the acquirer convey a strong compliance willingness and firm commitment to sustainable development to the host government [39,40]. For instance, positive environmental practices and adherence to local environmental regulations reduce the likelihood of government scrutiny regarding environmental risks such as potential pollution, reflecting the contribution of the environmental dimension to regulatory legitimacy. This behavior not only lessens the government’s assessment of the acquirer’s environmental and social risks but also fosters government trust, thereby potentially leading to less stringent investment reviews, expedited approval processes, and even the acquisition of certain policy support, thus creating a more relaxed and favorable external environment for smooth post-merger operation [40].

Secondly, at the normative legitimacy level, stakeholders such as the host society, community organizations, and non-governmental organizations evaluate the behavior of enterprises based on their specific social values and ethical standards. For host stakeholders, there is a greater willingness to cooperate with and provide resources to enterprises whose ESG norms align with their own [34]. Active engagement in social responsibility initiatives, such as participating in community development projects or safeguarding employee rights, can enhance the acquirer’s reputation among local communities and non-governmental organizations, reflecting the positive impact of the social dimension on normative legitimacy. Strong ESG performance can help the company garner more attention and support from potential partners, which in turn incentivizes the acquirer to conduct business in the host market [40,41,42].

At the level of cognitive legitimacy, the acceptance and recognition of the acquirer by the host people’s and consumers’ acceptance and recognition of the acquirer directly influence its market performance. Consumers often rely on the perception of the overall image of the company to make purchase decisions [43]. Acquirers can gradually enhance their reputation and brand image in local markets by providing high-quality and environmentally friendly products and services, implementing responsible marketing strategies, establishing efficient consumer protection mechanisms, and disclosing their ESG-related information in an open and transparent manner [44,45,46]. This positive image-building helps to dispel negative perceptions that may arise from their “foreign” identity, enhances consumer and potential partners’ trust and identification, and thus lays a solid foundation for post-acquisition market expansion, customer relationship maintenance, and long-term business growth.

2.2.2. Acquirer ESG Performance Addresses Information Asymmetry

The positive ESG performance of the acquirer can also can also serve as a powerful strategic signal to effectively compensate for the information asymmetry between the stakeholders of the host country. Given that ESG practices often necessitate long-term investment and continuous improvement [46]. Therefore, strong ESG performance can clearly convey the commitment and strategic intention of the enterprise to long-term sustainable development, thus effectively alleviating the concerns of stakeholders in the host country that the enterprise may conceal material adverse information, and demonstrating the firm pursuit of legal compliance and integrity. Transparent ESG disclosure, encompassing environmental performance data, social responsibility reports, and corporate governance structures, can provide host governments, investors, consumers, suppliers, and other stakeholders with a clear understanding of the acquirer’s operations and values, thereby reducing uncertainty stemming from information asymmetry [47,48]. This helps transnational enterprises win the goodwill and trust of key stakeholders such as target enterprises, consumers, suppliers, and trade unions, and helps enterprises gain support from host governments to mitigate their doubts and excessive interference in TNCs’ behavior and facilitate overcoming market access barriers.

Based on the above analysis, the acquirer can effectively mitigate the LOF it faces in the host market by actively improving ESG performance, specifically by enhancing its legitimacy and compensating for information asymmetry. The improvement of legitimacy can win more resources, support, and recognition for the enterprise, reduce operating costs and transaction costs; the mitigation of information asymmetry can help build trust, promote cooperation, and enhance market competitiveness. Finally, these positive effects will directly promote the long-term value creation of cross-border M&As.

Based on the above analysis, the following hypothesis is proposed:

Hypothesis 1.

Strong ESG performance of acquirers can enhance their legitimacy and compensate for information asymmetry, effectively alleviate their LOF, and subsequently improve the long-term performance of cross-border M&As.

2.3. Mediating Role of External Resource Acquisition and Internal Synergies

Based on the analysis of LOF in cross-border M&As, an acquirer can improve the long-term performance of cross-border M&As by improving ESG performance, and the key mechanism underlying this influence is that strong ESG performance significantly enhances the acquirer’s ability to obtain strategic resources from key stakeholders, thereby compensating for the LOF caused by information asymmetry and lack of legitimacy in cross-border M&As, and ultimately improving the long-term performance of cross-border M&As. Drawing on Dong Cong et al. (2024) [49], we divide the resources provided by stakeholders into external resources and internal resources, and develop our mechanism analysis and hypotheses from these perspectives.

2.3.1. Acquirer ESG Performance and External Resource Acquisition

The positive ESG practices of acquirers can effectively alleviate the obstacles to external resource acquisition caused by LOF. First, ESG performance can affect listed companies’ access to capital market resources provided by investors and creditors, thus alleviating financing constraints caused by asymmetric information [50]. In practical economic activities, a company’s ESG development capability serves as an important indicator of its sustainable development potential, correlating with a stronger corporate reputation, enhanced financial performance, positive social standing, and lower policy risk, thus holding significant signal value for investors [51]. Within the host market environment characterized by asymmetric information, high-quality ESG performance and rating results can function as conveying positive information about the listed company’s stable operation, risk management, and sustainable development capacity to investors. This assists them in making more rational investment decisions and reduces the risk premium demands arising from asymmetric information. Strong ESG performance by the acquirer will encourage investors to form a more favorable evaluation of the listed company, enhance their investment willingness, lower its financing costs, and ease external financing constraints, providing necessary financial support for post-merger integration and development.

Second, ESG performance can influence multinational M&A companies to acquire competitive resources from consumers and suppliers in host countries, thus enhancing cognitive legitimacy and normative legitimacy and building trust. Strong ESG performance can help listed companies establish a responsible and sustainable corporate image and reputation among consumers and upstream and downstream companies in host countries, meet local social expectations for environmental protection and corporate social responsibility, and enhance their cognitive legitimacy [26]. Simultaneously, positive ESG practices directly reflect the enterprise’s respect for and compliance with the informal social norms, cultural customs, and ethics of the host country, thus bolstering their normative legitimacy [34]. On the one hand, it enhances consumer stickiness and supplier trust, enhances their willingness to cooperate, and makes the company more attractive in the host country market, easier to obtain market share and establish stable supply chain cooperation relations. On the other hand, a strong ESG reputation can not only enhance a company’s market competitiveness but also help offset the negative impact of potential adverse events on listed companies, strengthening their ability to withstand risks and maintain smooth operations. More importantly, positive ESG practices can reduce friction arising from cultural conflicts or differences in values, foster more harmonious cooperative relationships, and facilitate integration into the local business ecosystem, enabling more effective acquisition of various resources needed within the product market.

Thirdly, strong ESG performance can also improve the host government’s recognition of the acquirer’s legitimacy and reduce the restrictions caused by a lack of regulatory legitimacy. Active ESG practices by enterprises, such as complying with local environmental protection laws and regulations, actively participating in community development, and protecting employees’ rights and interests, can effectively enhance regulatory and normative legitimacy in the eyes of the host government. This makes it easier for business management behaviors to gain government recognition, thereby reducing the host government’s questioning and potential excessive intervention in enterprises, helping to lessen investment review and restrictions, and lowering political risks and regulatory costs [52]. The greater the regulatory legitimacy obtained through positive ESG practices, the more conducive it is to reducing the strictness of enterprise investment review, shortening the approval process, and lowering the corresponding government relationship costs. It may even lead to the acquisition of certain resource support and policy preferences, creating a more relaxed and favorable external environment for smooth post-merger operation, which is conducive to the long-term development of multinational enterprises.

Therefore, when facing the LOF inherent in cross-border M&As, strong ESG performance can serve as a reliable strategic signal and a positive social behavior to significantly reduce the negative impact of outsiders’ disadvantages, create favorable conditions for enterprises to obtain key external resources, and lay a solid foundation for the long-term development of multinational enterprises.

Based on the above analysis, the following hypothesis is proposed:

Hypothesis 2a.

Proactive ESG practices of acquirers alleviate information asymmetry and improve the long-term performance of cross-border M&As by acquiring capital market resources provided by investors and creditors.

Hypothesis 2b.

Proactive ESG practices of acquirers enhance cognitive legitimacy and normative legitimacy by facilitating the acquisition of market competitiveness resources provided by consumers and suppliers, and improve the long-term performance of cross-border mergers and acquisitions.

Hypothesis 2c.

Proactive ESG practices of acquirers enhance the long-term performance of cross-border M&As by obtaining regulatory legitimacy in host countries.

2.3.2. Acquirer ESG Performance and Internal Synergy Enhancement

Strong ESG performance by the acquirer can effectively alleviate internal synergy barriers arising from cross-cultural and information differences by proactively gaining and maintaining the support of shareholders, management, and employees of both entities, and significantly enhance the internal legitimacy of the cross-border M&A. The internal legitimacy of cross-border M&A emphasizes the degree of support from shareholders, management, and employees of both parties [53]. First, positive ESG practices can build consensus among employees and enhance team cooperation efficiency [54]. When the acquirer’s company upholds a commitment to environmental protection, social responsibility, and good governance, employees are more likely to find common values and goals, and thus are more willing to work towards a common corporate vision, reduce differences caused by cultural and value disparities, improve team cohesion and cooperation efficiency, and promote effective integration of cross-cultural teams. Secondly, a transparent ESG governance structure and information disclosure mechanism can establish clear communication channels, reduce information asymmetry among management, and improve decision-making efficiency [55]. In addition, strong ESG performance can send signals to shareholders regarding the long-term sustainable development of the enterprise, enhancing their confidence and support for the M&A strategy, thus reducing internal resistance. Therefore, the improvement of internal legitimacy can accelerate the integration of resources and capabilities, reduce operating costs, improve the ability of multinational enterprises to respond to market changes, and ultimately improve the long-term performance of cross-border M&As.

Based on the above analysis, the following hypothesis is proposed:

Hypothesis 2d.

The positive ESG practices of acquirers enhance the internal legitimacy by fostering internal synergy, and then improve the long-term performance of cross-border M&As.

2.4. The Threshold Effect of Institutional Complexity

Institutional theory emphasizes that organizational behavior and performance are deeply influenced by the institutional environment in which they are embedded [56]. In contrast to traditional theories emphasizing internal resources, capabilities, or strategic choices of organizations, institutional theory argues that for survival and development, organizations need not only to pursue efficiency and profits but, more importantly, to gain the approval and legitimacy of their social environment [56,57]. Institutional complexity is an important concept in institutional theory, specifically when an organization encounters incompatible rules from multiple institutional logics [58]. The application of institutional complexity allows for a nuanced distinction of multiple institutional logics, their interactions, and field characteristics, thereby revealing how these factors uniquely affect enterprise ESG practices [58]. Cross-border M&As inherently involve two distinct institutional environments: the acquirer’s home country and the target company’s home country. Multinational firms’ efforts to address the LOF also necessitate that acquirers navigate diverse laws and regulations, regulatory requirements, social norms, and stakeholder expectations, which collectively constitute institutional complexity. Multinational enterprises face interwoven and sometimes conflicting institutional demands, such as home and host country policies, industry norms, and capital market needs, which pose significant challenges to ESG practices [59]. Therefore, we contend that the impact of ESG performance is not uniform across all institutional environments but is moderated by the complexity of host country institutions.

Regarding legitimacy issues related to LOF, higher institutional complexity increases the difficulty of acquiring and maintaining legitimacy due to the need to address more diverse regulatory requirements, more intricate social norms, and more varied stakeholder claims. Strong ESG performance, particularly a positive stance on environmental protection, social responsibility, and corporate governance, can be viewed as a crucial “legitimacy asset” [32]. In host countries with high institutional complexity, the value of this “legitimacy asset” may be more prominent because it helps firms overcome institutional barriers, obtain operating licenses, win government support, and establish good relationships with local communities, thus having a stronger positive impact on the long-term performance of M&As.

Meanwhile, information asymmetry is another key problem faced by multinational enterprises in LOF. The acquirer needs to effectively communicate its capabilities, intentions, and values to the stakeholders of the target company. We believe that in host countries with higher institutional complexity, due to greater environmental uncertainty and information asymmetry, the positive signals transmitted by the acquirer’s positive ESG practices will be of higher value. Such signals can be more effective in reducing stakeholder skepticism, enhancing the acquirer’s reputation, and enhancing its local “credibility,” resulting in a more significant boost to M&A performance. Moreover, in cross-border M&As, when institutional complexity is high, it may trigger firms’ ability to reflect and improve their absorptive capacity, enabling them to innovate and absorb knowledge more effectively, thereby improving long-term performance across M&As [60,61].

Therefore, we believe that the complexity of the host country system will significantly moderate the effect of acquirer ESG performance on the long-term performance of cross-border M&As. By introducing this threshold variable, this study aims to better understand the strategic value of ESG behavior and its situational effects in different institutional environments, so as to provide more refined insights for cross-border M&A practice and theoretical development. Moreover, we can infer from the above analysis that in cross-border M&As occurring in host countries with high institutional complexity, when the ESG performance of the M&A partner effectively addresses complex institutions, fosters high trust, promotes efficient synergy, and generates significant competitive advantages, its positive impact on M&A performance will be more pronounced and valuable.

Based on this, the following hypothesis is proposed:

Hypothesis 3.

The impact of acquirer ESG performance on cross-border M&A performance exhibits a single threshold effect moderated by institutional complexity.

Figure 1 illustrates the theoretical analysis framework of Chapter 2, depicting the impact of the acquirer’s ESG performance on the long-term performance of cross-border mergers and acquisitions, the mechanisms, and the threshold effect of the host country’s institutional complexity. The ‘+’ in the image indicates a positive effect.

3. Research Design

3.1. Sample and Data

This study selects China A-share listed companies from 2010 to 2021 as the research object, and constructs the research sample based on the cross-border merger data of the Zephyr database. The selection of A-share listed companies as the research subject is mainly based on the following considerations: Firstly, China’s A-share market serves as the main stock trading market in China. Its listed companies are subject to a relatively complete regulatory framework concerning corporate governance, information disclosure, etc., thus providing relatively reliable and standardized financial and corporate behavior data. This is crucial for quantitative research. Secondly, this research focuses on China’s A-share listed companies, and its research results may be generalizable to other Chinese markets and newly industrialized economies. It can have a certain reference value. Specifically, China A-share listed companies have certain commonalities in ownership structure, corporate governance model, regulatory environment and development stage, and other types of listed companies in China. There is also a strong correlation between ESG performance and the long-term performance of cross-border M&As (e.g., Chinese companies listed in Hong Kong or overseas) and the macroeconomic and institutional context of China as a whole. In addition, the newly industrializing economies have significant differences in economic development level, institutional environment characteristics. There may be similarities with China in terms of possible institutional uncertainties, differences in regulatory effectiveness, and emphasis on environmental protection and social responsibility. ESG may play a similar role in the internationalization of companies in many emerging economies that are also facing the need to improve their competitiveness, acquire technology, and market share through internationalization. This study may provide some enlightenment for companies in these emerging economies.

After determining the initial study scope, we rigorously screened the sample: (1) excluded listed companies with missing data on key variables to ensure the validity and reliability of regression analysis; and (2) excluded listed companies with abnormal transactions, including listed companies marked ST and *ST during the study period. These companies often face financial difficulties or other abnormal operating conditions, and their M&A behavior may have special characteristics. After the above steps, this study finally collected 1129 samples of cross-border M&As.

3.2. Models

To examine H1, the following model is used:

$${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{i},\mathrm{t}}={\beta }_0+{\beta }_1{\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}+{\beta }_2{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i},\mathrm{t}}+\mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}+{\epsilon }_{\mathrm{i},\mathrm{t}}$$

(1)

where the subscripts i and t denote firm and year, respectively. ${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{i},\mathrm{t}}$ measures the long-term performance of Chinese enterprises’ cross-border M&As of firm i in year t. ${\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}$ is the ESG score of firm i in year t, reflecting its comprehensive Environmental, Social, and Governance performance in that year. Year represents year dummy variables, and Industry represents industry dummy variables to control for annual and industry fixed effects, respectively. ${\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i},\mathrm{t}}$ denotes relevant control variables; ${\epsilon }_{\mathrm{i},\mathrm{t}}$ denotes the random error term; β₀ is the intercept term; and β₁ and β₂ are parameters to be estimated.

3.3. Variable Definitions

3.3.1. Dependent Variable

Common practices are referenced in the existing literature [62,63,64]. This paper uses Buy-and-Hold Abnormal Return (BHAR) in the event study method to estimate the long-term performance of China’s cross-border M&As. BHAR systematically studies the long-term market performance of sample company stock prices. This method aims to measure the excess performance of sample company stock returns relative to market portfolio returns after investors buy sample company stocks and hold them until the end of the inspection period [64]. As a rigorous theoretical framework, the event study method can deeply analyze the far-reaching impact of cross-border M&As on the long-term value of enterprises. BHAR is the excess return of buying a company’s stock and holding it until the end of a certain time. Different from Cumulative Abnormal Return (CAR), BHAR is less affected by the fluctuation of a company’s stock price and is more suitable for evaluating the long-term performance of listed companies in China after cross-border M&As, but CAR is a simple summation of daily excess returns and may be affected by sharp fluctuations in stock prices within the event window. In order to calculate BHAR accurately, it needs at least 3 years of investigation period. Because the data may also be disturbed by factors other than investigation events, it is very important to control these factors in order to reduce errors [64]. Drawing on the ideas of Fama and French (1993) [65], this paper adopts the influence of controlling company size and the owner equity market value ratio to calculate BHAR. The specific calculation steps are as follows:

(1) According to the company’s size and book-to-market ratio, a cross-grouping is conducted. Specifically, the companies are sorted into 5 groups according to their size in the kth year. At the same time, they are sorted into 5 groups according to their BE/ME value at the end of the kth-1 year. BE/ME = net assets per share/closing price at the end of the year. Finally, cross-group companies according to their size and BE/ME combinations. In each year, all sample companies are divided into 25 groups.

(2) Calculate the equal-weighted monthly average return for each portfolio. By combining the company size and BE/ME combinations, we calculate the equal-weighted monthly average return for 25 groups of companies. This process fully considers the weights of different companies in the sample group and ensures the fairness of the results. The calculation formula is as follows [65]:

$${\mathrm{R}}_{\mathrm{p}\mathrm{t}}={\displaystyle \frac{1}{{\mathrm{N}}_{\mathrm{B}\mathrm{E}/\mathrm{M}\mathrm{E},\mathrm{S}\mathrm{I}\mathrm{Z}\mathrm{E}}}}{\sum }_{\mathrm{t}=1}^{{\mathrm{N}}_{\mathrm{B}\mathrm{E}/\mathrm{M}\mathrm{E},\mathrm{S}\mathrm{I}\mathrm{Z}\mathrm{E}}}{\mathrm{R}}_{\mathrm{i}\mathrm{t}} ,\mathrm{p}\in (\mathrm{1,25}), \mathrm{t}\in (\mathrm{1,36})$$

(2)

$${\mathrm{R}}_{\mathrm{i}\mathrm{t}}={\displaystyle \frac{{\mathrm{P}}_{\mathrm{i}\mathrm{t}}-{\mathrm{P}}_{\mathrm{i},\mathrm{t}-1}}{{\mathrm{P}}_{\mathrm{i},\mathrm{t}-1}}}$$

(3)

${\mathrm{R}}_{\mathrm{p}\mathrm{t}}$ represents the weighted monthly average return of the same size and BE/ME cross-grouping of companies in the same year; ${\mathrm{N}}_{\mathrm{B}\mathrm{E}/\mathrm{M}\mathrm{E},\mathrm{S}\mathrm{I}\mathrm{Z}\mathrm{E}}$ is the number of companies in the same size and BE/ME cross-grouping; ${\mathrm{R}}_{\mathrm{i}\mathrm{t}}$ represents the stock return of the sample company for stock i in month t; and ${\mathrm{P}}_{\mathrm{i}\mathrm{t}}$ is the closing price of stock i in month t.

(3) After M&As, sample firm i continuously holds earnings for [0, T] in the middle month [64].

$${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{i},\mathrm{T}}={\sum }_{\mathrm{t}=0}^{\mathrm{T}}\mathrm{l}\mathrm{n}(1+{\mathrm{R}}_{\mathrm{i},\mathrm{t}})-{\sum }_{\mathrm{t}=0}^{\mathrm{T}}\mathrm{l}\mathrm{n}(1+{\mathrm{R}}_{\mathrm{p}\mathrm{t}})$$

(4)

where t = 0, 1, 2, 3… T, ${\mathrm{R}}_{\mathrm{i},\mathrm{t}}$ represents the monthly actual rate of return for firm i, and ${\tilde{\mathrm{R}}}_{\mathrm{i},\mathrm{t}}$ represents the corresponding expected rate of return, expressed by the combined monthly market rate of return.

(4) Average BHAR of sample combination N.

$${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{T}}={\displaystyle \frac{1}{\mathrm{N}}}{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{i},\mathrm{T}}={\displaystyle \frac{1}{\mathrm{N}}}{\sum }_{\mathrm{i}=1}^{\mathrm{N}}[{\sum }_{\mathrm{t}=0}^{\mathrm{T}}\ln (1+{\mathrm{R}}_{\mathrm{i},\mathrm{t}})-{\sum }_{\mathrm{t}=0}^{\mathrm{T}}\ln (1+\left.{\mathrm{R}}_{\mathrm{p}\mathrm{t}\mathrm{t}}\right)]$$

(5)

N is the number of samples, ${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{T}}$ represents the average continuous holding yield to maturity of the entire sample portfolio over a period of T months. BHAR represents the long-term performance of cross-border M&As for the sample companies after 12 months, 24 months, and 36 months.

3.3.2. Independent Variable

Referring to Xie Hongjun et al. (2022) [27], due to the late start and development of ESG in China, compared with Bloomberg and Wind, HuaZheng ESG data has the advantages of complete rating indicators, fast update, and easy availability of data. Moreover, HuaZheng ESG rating weights are set by industry, key issues are set according to about 70 three-level industries, and key issues in different industries are assigned different weights to rate the enterprise ESG. Overall, among the three ESG first-level indicators, the G dimension has a relatively high weight, with an industry average of 42.66%, the E dimension has a relatively low weight, with an industry average of 25.62%, and the S dimension has a medium weight, with an industry average of 31.72%. The rating method is reasonable, and this indicator has been recognized and applied by industry and academia. Therefore, HuaZhengESG rating data is selected as the core indicator to measure the ESG advantage of enterprises in this paper, and the data comes from Wind Information Financial Terminal. HuaZhengESG rating ranks all listed enterprises as 9, with grades from low to high as C, CC, CCC, B, BBB, A, AA, and AAA. Refer to Xie Hongjun et al. (2022) [27], benchmark analysis assigns 0.1 to 0.9 to the ESG rating of enterprises from low to high, and the larger the value, the higher the ESG rating.

3.3.3. Control Variables

In addition, control variables are included to exclude the interference of other potential factors, so as to more accurately identify the relationship between the core explanatory variables and the explanatory variables. Referring to Zhou Wei et al. (2025) and Buet al. (2022) [66,67], these control variables are divided into firm-level and host-country-level. The control variables at the firm-level include M&As in the same industry (Indre), M&A advisors (Advisors), firm size (Size), asset–liability ratio (Lev), firm performance (Roa), and proportion of independent directors (Indep), where “Indre” and “Advisors” are biclassified variables (Yes = 1. No = 0). Controlling these two variables can help us get rid of the potential impact of industry factors and professional services on M&A performance, so as to more clearly assess the independent impact of ESG performance on M&A performance [68]. Meanwhile, enterprise financial characteristics indicators and management governance indicators also have certain impacts on enterprise business status and M&A behavior to a certain extent [69]. ”Size” is calculated by taking the logarithm of total assets at the end of each year, indicating the size of the enterprise; ”Roa” is calculated by dividing a company’s net profit by its total assets, reflecting the profitability of the company; ”Lev” is expressed by the ratio of total liabilities to total assets, reflecting the solvency of the company; and ”Indep” is expressed by the number of independent directors divided by the total number of directors, reflecting the independence of the board of directors of the company. These factors may directly affect the business status and merger decision of the company. The above data are obtained from the Zephyr database and the CSMAR database.

The host-country-level control variable is institutional distance (SD), which reflects the differences between China and the target host country in political, legal, and other institutional environments. This difference may bring challenges to post-merger integration and operation, and then affect M&A performance [70]. Therefore, we refer to Liu et al. (2020) and use the World Bank Governance Index (WGI) to calculate the institutional distance between host countries and regions and China in 2010 [71], which is mainly reflected in six institutional dimensions: political stability and elimination of violenceism, legal system level, corruption control, supervision quality, government efficiency, discourse power, and accountability. The calculation formula is as follows [71]:

$${\mathrm{S}\mathrm{D}}_{\mathrm{j}\mathrm{t}}={\sum }_{\mathrm{i}}^6\left[{\left({\mathrm{I}}_{\mathrm{i}\mathrm{j}\mathrm{t}}-{\mathrm{I}}_{\mathrm{i}\mathrm{c}\mathrm{t}}\right)}^2/{\mathrm{V}}_{\mathrm{i}\mathrm{t}}\right]/6$$

(6)

where ${\mathrm{I}}_{\mathrm{i}\mathrm{j}\mathrm{t}}$ and ${\mathrm{I}}_{\mathrm{i}\mathrm{c}\mathrm{t}}$ are the scores of the jth country and China in the ith dimension in the tth year, respectively, and ${\mathrm{V}}_{\mathrm{i}\mathrm{t}}$ is the variance of all sample countries in the ith institutional dimension in the tth year, where the larger the SD value, the greater the institutional distance between the host country and China.

3.3.4. Threshold Variable

This study draws on the research method of Shen Liying et al. (2024) to quantify institutional complexity (IC) by using the standard deviation between the average scores of the six dimensions of the World Governance Index (WGI) of the host country. The data are from the WGI database [72]. The WGI index covers six key institutional dimensions: voice and accountability, government stability and non-violence, government efficiency, regulatory quality, rule of law, and corruption control. The larger the standard deviation, the more complex the institutional environment of the host country. For example, a country might exhibit strong rule of law but weak government effectiveness, leading to a higher standard deviation and thus indicating greater institutional complexity. The WGI database, provided by the World Bank, is a widely recognized and utilized source for cross-country governance indicators (Kaufmann et al., 2010) [73]. The calculation formula is as follows [72]:

$$\mathrm{I}\mathrm{C}=\sqrt{{\displaystyle \frac{\sum \left(\mathrm{I}-\overline{\mathrm{I}}\right)}{\mathrm{N}}}}$$

(7)

3.3.5. Intermediary Variable

(1) Drawing on Dong Cong et al. (2024), Zhu Jian et al. (2025), and Ni, J. et al. (2025) [49,74,75], we use the financing constraint index (FC) to measure the degree of capital market resources obtained by enterprises in cross-border mergers and acquisitions. The index comes from the CSMAR database. It should be noted that the larger the FC index, the more serious the financing constraints of enterprises and the more limited the capital market resources they can obtain. Therefore, in subsequent analysis and interpretation of the results, it is necessary to pay attention to the negative relationship between the FC index and M&A performance. For example, a multinational company with excellent ESG performance may be more likely to be favored by host investors, thus reducing its financing constraints, obtaining more capital support for post-merger integration and development, and ultimately improving long-term performance. Conversely, companies with poor ESG performance may face higher financing costs and stricter financing conditions, limiting their post-acquisition growth potential.

(2) Referring to Wei Zhihua et al. (2019) [76], we use the net commercial credit (NTC) obtained from suppliers to measure the competitiveness of the product market. The calculation formula is as follows: Net commercial credit (NTC) = (Accounts received in advance + accounts payable-accounts receivable-accounts prepaid)/operating income. A higher NTC value means a company has stronger bargaining power relative to its suppliers and customers, reflecting its competitive advantage in the product market. Multinational companies with good ESG performance may have higher brand reputation and customer loyalty, thus gaining a better position in upstream and downstream transactions, obtaining more net business credit, and supporting market expansion after M&As.

(3) Regulatory legitimacy (RL) refers to the measurement method of Han (2021) and Chen Deqiu et al. (2023) [77,78], using the natural logarithm of the number of overseas investment projects of Chinese enterprises subject to strict examination and/or termination by the host government +1 and taking negative treatment as the proxy variable of regulatory legitimacy (RL) of Chinese enterprises in that country. The data are from the China Global Investment Tracking (CGIT) Database developed by the American Enterprise Institute (AEI). The higher the PL value, the less regulatory pressure the firm faces in the host country and the higher its regulatory legitimacy. The firm with excellent ESG performance may pay more attention to coordination with local government and social norms, thus reducing the risk of being reviewed or terminated, enhancing its regulatory legitimacy in the host country, and creating favorable conditions for the smooth progress and long-term development of M&A activities.

(4) Internal synergy (IS), based on Li Ruijing et al. (2022) [79], is the natural logarithm of the internal control index from the DIB Internal control and risk management database after adding 1, used to measure the internal control quality of listed companies. A higher internal control index means that the enterprise has a more complete and effective internal management system, which can better integrate the resources and processes of both parties in the merger and achieve internal synergy. Enterprises with good ESG performance usually pay more attention to the improvement of corporate governance and internal management level, which helps them to integrate the target enterprise’s operations more effectively after the merger and ultimately improve the merger performance.

3.3.6. Statistical Analysis

Descriptive statistics of the main variables in this paper are shown in

Table 1. Descriptive statistics of variables.

Variable Type	Variable	N	MAX	Min	Mean	SD
Dependent Variable	BHAR	1129	6.962	−0.763	0.041	0.513
Independent Variable	ESG	1129	0.620	0.021	0.210	0.101
Threshold Variable	IC	1129	0.988	0.120	0.497	0.200
Intermediary Variable	FC	1129	0.921	0.0001	0.410	0.276
	NTC	1129	2.020	−1.286	−0.081	0.251
	RL	1129	−0.693	−2.398	−1.198	0.621
	IS	1129	6.803	0	6.320	0.787
Control Variables	SD	1129	6.206	0.709	4.560	1.180
	Indre	1129	1	0	0.479	0.620
	Advisors	1129	1	0	0.072	0.300
	Size	1129	28.181	19.560	22.430	1.346
	Lev	1129	1.100	0.008	0.476	0.200
	Roa	1129	0.418	−0.797	0.041	0.024
	Indep	1129	80	20	37.581	6.732

. It can be seen that BHAR is distributed between −0.763 and 6.962, with an average of only 0.041, indicating that the long-term performance level of cross-border M&As of Chinese enterprises varies greatly, and there is still much room for improvement; the average ESG performance is 0.210, the minimum value is 0.021, and the maximum value is 0.620, which shows that ESG performance of different enterprises varies greatly. The dispersion degree and difference level of the other variables are basically consistent with the existing literature, indicating that the variables selected in this paper are generally reasonable.

4. Results

4.1. Baseline Regression

The baseline regression results of model (1) are shown in

Table 2. Baseline regression results.

	(1)		(2)
Variable	BHAR	p-Value	BHAR	p-Value
ESG	0.731 *** (3.912)	0.000	1.023 *** (5.297)	0.000
SD			−0.679 *** (−3.614)	0.000
Indre			0.349 *** (3.276)	0.000
Advisors			−0.005 (−0.847)	0.176
Size			1.271 *** (4.043)	0.002
Lev			−0.103 (−0.236)	0.270
Roa			0.081 (1.272)	0.198
Indep			0.013 (0.946)	0.162
Cons	0.103 ** (2.412)	0.024	1.034 *** (3.037)	0.000
Industry	No		Yes
Year	No		Yes
obs	1129		1129

Note: t statistics in parentheses. ** p < 0.05, *** p < 0.01. Year and Industry represent fixed year and industry effects. “Yes” indicates that the variable is controlled; “No” indicates it is not.

. Column (1) only controls the fixed effects of year and industry, and column (2) adds control variables to mitigate the missing variable bias. The results show that the ESG regression coefficients are significantly positive regardless of whether other control variables affecting the long-term performance of cross-border M&As of listed companies are added, indicating that the ESG performance of the acquirer has a positive effect on the long-term performance of cross-border M&As of listed companies. Take column (2) as an example; its economic significance is that the ESG of the acquirer increases by 1 unit, and the long-term performance level of cross-border M&As of listed companies increases by 1.023 units, which is consistent with the expectation of hypothesis 1. Based on the discussion of LOF in the previous section, the ESG performance in the benchmark regression results has a significant positive impact on the long-term performance of cross-border M&As, indicating that positive ESG practices help the acquirer overcome the LOF caused by asymmetric information and lack of legitimacy in the host market, thus promoting long-term performance improvement. Good ESG signals reduce communication costs with local stakeholders and enhance trust.

4.2. Robust Test

4.2.1. Alternative Dependent Variable

Change in Return on Assets (ΔROA) in the financial indicator method is often used to estimate the long-term performance of cross-border M&As of Chinese enterprises. ΔROA can directly reflect the actual impact of M&A activities on enterprise profitability and asset operation efficiency, so as to evaluate the long-term effect of cross-border M&As more comprehensively. This paper draws lessons from Wu Chen Shihua et al. (2013) and Cai and Sevilir (2012) and measures it as the change in total asset return rate in the two years before and after the first announcement date of M&As [64,80]. The specific calculation is as follows: first, the return on total assets (ROA) for each year is normalized according to industry standards (manufacturing is classified by secondary code, others are classified by primary code); then, the ROA for the two years before the merger (t − 2 years, t − 1 years) is subtracted from the ROA for the two years after the merger (t + 1 years, t + 2 years), which is △ROA. As shown in the estimation results in

Table 3. Robustness test.

	(1)		(2)		(3)		(4)
Variable	ESG	p-Value	ESG	p-Value	ESG	p-Value	ESG	p-Value
	Alternative Dependent Variable		Alternative Dependent Variable		Bilateral Tailing		Change Time Span
BHAR			0.981 ***	0.000	1.528 ***	0.000	1.823 ***	0.000
					(0.628)		(0.698)
ΔROA	1.023 ***	0.000
	(3.094)
Cons	4.261 ***	0.000	−0.212 *	0.086	3.870 **	0.031	4.109 **	0.041
	(1.832)		(0.113)		(1.818)		(1.882)
R-squared	0.419		0.278		0.425		0.435
Controls	Yes		Yes		Yes		Yes
Industry	Yes		Yes		Yes		Yes
Year	Yes		Yes		Yes		Yes
obs	1129		1129		1129		1129

Note: t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Year and Industry represent fixed year and industry effects. “Yes” indicates that the variable is controlled.

(1), the coefficient for ESG remains significantly positive at the 1% level.

4.2.2. Alternative Independent Variable

This paper refers to relevant research and uses WindESG rating data as a proxy variable for enterprise ESG performance [27]. The data comes from the Wind database. Wind develops a set of scientific and rigorous rating methodology based on ESG core connotation, in line with international standards and evaluation framework, and according to the development characteristics of Chinese enterprises and the current situation of the capital market. The results are shown in Table 3 (2), where the ESG coefficient is 0.981 and significant at the significance level of 1%. This indicates that the ESG performance of the acquirer significantly promotes the long-term performance of cross-border M&As, whether HuaZheng ESG rating data or WindESG rating data are used as proxy variables, which is consistent with the regression results mentioned above and verifies the robustness of the conclusions of this paper.

4.2.3. Tail Reduction

After bilateral censoring and bilateral censoring at the 1% level for the explanatory variable cross-border M&A long-term performance, the core explanatory variable ESG and the control variable regression are performed on the new sample, respectively. The estimation results are shown in Table 3 (3). It can be seen that the ESG coefficient is still significantly positive at the 1% level after processing extreme observations and special observations.

4.2.4. Change Time Span

Considering that the epidemic situation after 2020 will have a certain impact on ESG performance and cross-border M&As of listed companies in China, a robustness test is conducted on the model, excluding the data after 2020 in this part. The results are shown in Table 3 (4). After changing the time span, the regression coefficient of ESG rating rises and is significant at 1% level, indicating that the impact of ESG performance of the acquirer on the long-term performance of cross-border M&As is still valid after excluding the impact of special events.

4.3. Endogenetic Test

4.3.1. Granger Causality Test

For hypothesis 1, the ESG performance of the acquirer has a significant positive effect on the long-term performance of cross-border M&As, and it cannot be ruled out that the long-term performance of cross-border M&As has an impact on ESG performance, and there is a two-way causal relationship between them. Therefore, this paper chooses the Granger causality test to test whether the long-term performance of cross-border M&As can predict the ESG performance of the acquirer.

The results are shown in

Table 4. Granger causality test results.

Equation	Exclued	Chi2	Prob
BHAR	ESG	7.214	0.010
ESG	BHAR	0.354	0.812

. As can be seen from row (3) of Table 4, in the equation with BHAR as the explanatory variable, if the joint significance of the ESG coefficient of the test variable (ESG variable is excluded from the equation), its chi-square statistic is 7.214, and the corresponding p-value is 0.010, so ESG is the Granger cause of BHAR. Similarly, BHAR is not the Granger cause of ESG.

4.3.2. GMM Models

In order to make the research conclusion more reliable, this paper also uses the first-order lag term (L.ESG) of ESG rating to carry out systematic GMM regression. The results are shown in column (2) of

Table 5. GMM regression model results.

Variable	BHAR
L.ESG	0.761 *** (6.721)
Controls	Yes
Industry	Yes
Year	Yes
AR (1)	−4.860
	[0.000]
AR (2)	−2.190
	[0.208]
Sargan	0.000
N	1129
R-square	0.365

Note: t statistics in parentheses. *** p < 0.01. Z value outside bracket of AR (1) and AR (2), p-value inside []. p-value of Sargan.

. The signs of the estimation coefficients of each variable are still consistent with the benchmark regression results, further indicating that ESG rating effectively promotes the common wealth level within the enterprise.

5. Extended Analysis

5.1. Threshold Effect Analysis

In this paper, the complexity of the host country system is taken as the threshold variable, and the threshold regression model is adopted and extended to a multi-threshold measurement model. The threshold value is judged according to the significance of the coefficient of iterative regression. The Bootstrap method is used to repeatedly sample 300 times to obtain the estimated value of three threshold models and the test results of the threshold effect. It is found that there is a single threshold for the long-term performance of cross-border M&As by ESG performance of the acquirer, and its threshold value is 0.323 (

Table 6. Threshold effect test results.

Threshold Variable	Model	F-Measure	p-Value	Bootstrap	Threshold Estimate
					I	II	III
IC	Single Threshold	6.71 **	0.013	300	0.323
	Dual Threshold	2.67	0.761	300	0.323	0.389
	Three Thresholds	3.14	0.592	300	0.323	0.389	0.711

Note: ** p < 0.05.

). The regression results for the threshold variables are reported in

Table 7. Threshold effect analysis results.

Threshold Variable	Threshold Interval	Coefficient	p-Value	Controls	Fixed Effect	R-Square
IC	$\mathrm{I}\mathrm{C}\le 0.323$	1.401 **	0.017	Yes	Yes	0.057
	$\mathrm{I}\mathrm{C}>0.323$	2.308 ***	0.000

Note: t statistics in parentheses. ** p < 0.05, *** p < 0.01.

, where the estimated coefficient for ESG is significant at the 5% level when less than or equal to the threshold and significant at the 1% level when greater than the threshold. The study shows the following: With the increase in institutional complexity, the ESG performance of the acquirer promotes the long-term performance of cross-border M&As more significantly. When institutional complexity is less than 0.323, ESG score increases by 1% for every 1% increase, and the long-term performance of cross-border M&As increases by 1.401% after reaching the threshold. In a more complex institutional environment, the greater the institutional obstacles and uncertainties faced by multinational enterprises, the more positive ESG performance can help enterprises establish legitimacy, make up for information asymmetry, reduce operational risks, and obtain more support, so as to make up for LOF more effectively and improve M&A performance. In general, the ESG performance of the acquirer has a threshold effect on the long-term performance of cross-border M&As, especially for host countries with high institutional complexity, where the ESG effect of the acquirer becomes more prominent.

5.2. Mechanism Analysis

According to the theoretical analysis above, good ESG performance of the acquirer has a positive impact on the long-term performance of cross-border M&As through obtaining capital market resources, product market competitiveness, regulatory legitimacy, and enhancing internal synergy. This paper adopts the sequential test regression coefficient method Sobel test, to analyze the mediation effect. The mediation model is as follows:

$${\mathrm{I}\mathrm{V}}_{\mathrm{i},\mathrm{t}}={\alpha }_0+{\alpha }_1{\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}+\delta {\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i},\mathrm{t}}+{\mu }_{\mathrm{i}}+\mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}+{\epsilon }_{\mathrm{i},\mathrm{t}}$$

(8)

$${\mathrm{B}\mathrm{H}\mathrm{A}\mathrm{R}}_{\mathrm{i},\mathrm{t}}={\gamma }_0+{\gamma }_1{\mathrm{E}\mathrm{S}\mathrm{G}}_{\mathrm{i},\mathrm{t}}+{\gamma }_2{{\mathrm{I}\mathrm{V}}_{\mathrm{i},\mathrm{t}}+\delta \mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i},\mathrm{t}}+{\mu }_{\mathrm{i}}+\mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}+{\epsilon }_{\mathrm{i},\mathrm{t}}$$

(9)

In Formulas (8) and (9), ${\mathrm{I}\mathrm{V}}_{\mathrm{i},\mathrm{t}}$ is an intermediary variable that needs to be tested; ${\alpha }_1$ indicates the influence coefficient of ESG performance on the mediator variable; and ${\gamma }_1$ indicates the influence coefficient of ESG performance of the acquirer on the long-term performance of cross-border M&As under the control of intermediary variables. The Bootstrap 500 sampling test is used to analyze robustness.

As can be seen from

Table 8. Results of mechanism analysis.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Variable	NTC	BHAR	FC	BHAR	IS	BHAR	RL	BHAR
NTC		${0.268}^{\ast \ast \ast }$ (0.084) [0.000]
FC				${-0.204}^{ \ast \ast }$ (−0.171) [0.023]
IS						${0.105}^{ \ast \ast }$ (0.081) [0.012]
RL								${0.672}^{ \ast \ast }$ (0.030) [0.011]
ESG	${0.192}^{ \ast \ast \ast }$ (0.698) [0.000]	${0.423}^{ \ast \ast \ast }$ (0.168) [0.000]	${-0.327}^{ \ast \ast \ast }$ (0.060) [0.000]	${1.023}^{ \ast \ast \ast }$ (0.226) [0.000]	${0.798}^{ \ast \ast \ast }$ (0.270) [0.000]	${0.898}^{ \ast \ast \ast }$ (0.230) [0.000]	${1.869}^{ \ast \ast \ast }$ (0.185) [0.000]	${1.332}^{ \ast \ast \ast }$ (0.239) [0.000]
Cons	${0.124}^{\ast \ast }$ (0.014) [0.012]	${-0.107}^{ \ast }$ (0.051) [0.071]	${3.405}^{ \ast \ast }$ (0.109) [0.021]	${2.013}^{ \ast \ast \ast }$ (0.080) [0.000]	${5.161}^{ \ast \ast \ast }$ (0.321) [0.000]	${0.098}^{ \ast \ast }$ (0.531) [0.047]	${-0.602}^{ \ast }$ (0.518) [0.059]	1.003 *** (0.621) [0.000]
Soble	0.0432 *** (0.021) [0.004]		0.0830 *** (0.041) [0.000]		0.0218 * (0.018) [0.080]		0.1555 * (0.185) [0.063]
Mesomeric Effect	Partial Mediating		Partial Mediating		Partial Mediating		Partial Mediating
Bootstrap	Indirect Effect Significant		Indirect Effect Significant		Indirect Effect Significant		Indirect Effect Significant
Obs	1114	1114	1082	1082	1028	1028	993	993
R-squared	0.309	0.137	0.795	0.140	0.078	0.139	0.378	0.139

Note: t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. p-value inside [].

, the impact coefficient of the acquirer’s ESG performance on capital market resources, product market competitiveness, regulatory legitimacy and internal synergy in the estimation results of columns (2), (4), (6), and (8) is significantly positive, which verifies that good ESG performance is conducive to enterprises to obtain capital market resources, improve product market competitiveness, obtain regulatory legitimacy, and enhance internal synergy. The regression coefficients of capital market resource, product market competitiveness, regulatory legitimacy, and internal synergy on the long-term performance of cross-border M&As are also significantly positive, and the impact of the acquirer’s ESG performance on the long-term performance of cross-border M&As is not offset, and it passes the Sobel test and plays a partial mediating role. The estimation coefficients of the Bootstrap test are consistent, and the results are robust. In summary, the mediation effect test shows that stronger capital market resources and product market competitiveness help companies establish competitive advantages in host countries; higher regulatory legitimacy reduces operational risks and compliance costs; and stronger internal synergies improve integration efficiency and reduce barriers due to cultural and management differences. The ESG performance of the acquirer improves the long-term performance of cross-border M&As by acquiring capital market resources, improving product market competitiveness, obtaining regulatory legitimacy, and enhancing internal synergy.

5.3. Heterogeneity Analysis

5.3.1. Heterogeneity by ESG Fractal

Good ESG performance helps ease financing constraints, improve business efficiency, and reduce financial risks. Considering ESG is a multi-dimensional structure concept, the performance of the three sub-dimensions of environment, society, and governance may have different degrees of impact on the long-term performance of cross-border M&As. The ESG rating system of China Securities includes three dimensions: environment (E), society (S), and governance (G), and tests the impact of these sub-indicators on the digital cross-border M&As of enterprises one by one. The regression results are shown in the

Table 9. Heterogeneity by ESG Fractal analysis results.

	(1)		(2)		(3)
Variables	E	p-Value	S	p-Value	G	p-Value
BHAR	0.701 *** (0.154)	0.003	0.297 *** (0.209)	0.000	0.451 ** (0.058)	0.034
Cons	0.401 (0.339)	0.624	0.704 * (0.368)	0.065	1.110 *** (0.369)	0.000
Controls	Yes		Yes		Yes
Year	Yes		Yes		Yes
Industry	Yes		Yes		Yes
Obs	1129		1129		1129
R-squared	0.085		0.089		0.102

Note: t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Year and Industry represent fixed year and industry effects. “Yes” indicates that the variable is controlled.

, from which it can be seen that except the governance (G) dimension score has a significant impact on the long-term performance of cross-border M&As at the level of 5%, the environmental (E) and social (S) dimension scores have a significant impact on the long-term performance of cross-border M&As at the level of 1%. The comparison coefficient shows that the environmental dimension exerts the strongest promotion effect, the governance dimension takes the second place, and the social dimension has the smallest promotion effect. The possible explanation for this is that the connotation and importance of social responsibility may vary significantly in different cultural backgrounds [81]. Social responsibility is more deeply rooted in specific cultural values and social norms than environmental responsibility and corporate governance. Environmental responsibility is directly related to sustainable development and environmental protection, which are important policy issues in many countries, so positive environmental performance is more easily recognized. Good corporate governance reflects the normative and transparent nature of the acquirer, which helps reduce agency costs and gain the trust of investors and regulators, thereby enhancing legitimacy. Social responsibility is also important, but due to differences in social values and “implicit” social responsibility perceptions among different countries, its cross-cultural transmission may not be as effective as environmental and governance dimensions. Higher cultural distance means that the acquirer’s efforts and investments in social responsibility may not be accurately understood and fully recognized by stakeholders in the target country, and the legitimacy enhancement and stakeholder trust enhancement effect brought by it will be weakened accordingly, resulting in the promotion of social responsibility dimension to long-term performance of cross-border M&As is less than that of environment and governance dimension. The research of Ma Wenjie and Yu Bojian (2023) also supports this view [82]. For “implicit” social responsibilities, such as stable employment, the recognition degree of the foreign market is lower than that of the domestic market. This divergence leads to the image of corporate responsibility displayed by the social responsibility dimension being underestimated by foreign stakeholders, so the long-term performance promotion effect of cross-border M&As is weaker than other responsibility dimensions.

5.3.2. Heterogeneity by Pollution Degree

The sensitivity of ESG rating may vary greatly among enterprises with different characteristics. For heavily polluting enterprises, ESG rating reflects their green production level to a large extent, and investors pay more attention to their pollution control. If the ESG rating is high, it may increase investors ‘investment willingness and thus improve cross-border M&A performance. Therefore, this paper performs group regression analysis according to heavily polluting enterprises. For heavily polluting enterprises, this paper selects B06, B07, B08, B09, B11, C17, C18, C19, C22, C25, C26, C27, C28, C29, C30, C31, C32, C33, and D44 enterprises as heavily polluting enterprises according to the classification standard of 2012. The fixed effects of year and industry are controlled, and grouped regression processing is carried out. The results show significant differences between groups, as shown in

Table 10. Heterogeneity by Pollution Degree analysis results.

	(1)		(2)
Variables	Heavily Contaminated	p-Value	Non-Heavily Contaminated	p-Value
ESG	1.312 *** (0.420)	0.000	0.765 ** (0.262)	0.041
Cons	0.342 *** (0.201)	0.000	2.410 ** (0.307)	0.013
Controls	Yes		Yes
Year	Yes		Yes
Industry	Yes		Yes
Obs	323		806
R-squared	0.151		0.162

Note: t statistics in parentheses. ** p < 0.05, *** p < 0.01. Year and Industry represent fixed year and industry effects. “Yes” indicates that the variable is controlled.

. The long-term performance and ESG ratings of cross-border M&As of heavily polluting enterprises show a significant positive correlation of ESG at the 1% level, and the ESG coefficient of heavily polluting enterprises is larger, indicating that the long-term performance of cross-border M&As of heavily polluting enterprises is more sensitive to ESG ratings. Enterprises undergoing cross-border mergers and acquisitions face the liability of foreignness due to a lack of understanding of the local market, culture, institutions, and other aspects. For heavily polluting enterprises, this disadvantage may be more prominent because they are more susceptible to strict supervision and negative attention from local communities, environmental organizations, and government departments. According to Compensatory Legitimacy Theory, when enterprises face lower inherent legitimacy due to their core business or industry characteristics (e.g., heavily polluting industries), they can compensate for their legitimacy deficit by demonstrating excellent performance in other areas [83]. The positive ESG performance of heavily polluting enterprises, especially efforts in environmental aspects, can compensate for their legitimacy deficit, help alleviate the liability of foreignness, and reduce operational risks. At the same time, high-quality ESG ratings can serve as a credible signal to investors, regulatory agencies, and the public, conveying the commitment of heavily polluting enterprises to sustainable development and environmental protection, ultimately enhancing the performance of cross-border mergers and acquisitions.

6. Conclusions

With the concept of sustainable development deeply rooted in people’s minds, ESG practices have garnered widespread attention from all walks of life at home and abroad [21]. This trend may reshape the competitive advantage of enterprises and have a profound impact on their international expansion. Therefore, this paper believes that ESG, as the core of the pursuit of sustainable development specific advantages, will become particularly important in China A-share listed enterprises’ cross-border M&As. This paper selects China A-share listed companies from 2010 to 2021 as the research sample to study the influence of ESG performance on the long-term performance of cross-border M&A and its mechanism. Good ESG performance of the acquirer can transmit positive signals to internal and external stakeholders, improve its legitimacy in cross-border M&As, and alleviate information asymmetry, thus overcoming inherent outsider disadvantages to some extent and improving the long-term performance of cross-border M&As. Second, there is a threshold effect of institutional complexity of “marginal increase” on the impact of ESG performance of the acquirer on the long-term performance of cross-border M&As. When the complexity of the host country system is high, the higher the signal value transmitted by positive ESG practice to stakeholders, the more positive the ESG effect will be amplified, and then the long-term performance of cross-border M&As will be improved more significantly. Thirdly, the mechanism study shows that the ESG performance of acquirers improves long-term performance of cross-border M&As by obtaining capital market resources, improving product market competitiveness, improving internal synergy effect and regulatory legitimacy, and intermediary variables play a part of intermediary role.

7. Policy Proposals

7.1. Corporate Level: Strengthen ESG Practices and Enhance Governance

China is in a critical stage of building a new and higher-level open economic system and striving to transition towards a sustainable development economic model. Given the significant value of ESG advantages in the international market, accelerating the advancement of ESG governance, optimizing the cultivation of responsible enterprises with ESG advantages, and striving to create new international competitive advantages are not only intrinsic requirements for adapting to the concept of sustainable development but also important ways to break through international barriers, convey the image of responsible enterprises and a major country, and build a community with a shared future for mankind. Therefore, based on the above research findings and referring to current research and empirical data, this paper puts forward the following policy recommendations:

At the corporate level, enterprises should strengthen their understanding and practice of ESG standards, incorporating ESG factors into their strategic planning and decision-making processes to enhance ESG governance. Firstly, enterprises should establish dedicated functional departments to promote ESG development and operations and actively learn about and align with the latest international ESG standards and practices, such as the Global Reporting Initiative (GRI), the Sustainability Accounting Standards Board (SASB), and the Task Force on Climate-related Financial Disclosures (TCFD). Secondly, enterprises can establish ESG indicator systems tailored to their specific industry characteristics, thereby forming a normalized ESG internal information collection and management mechanism, strengthening the quality of ESG information disclosure, meeting ESG regulatory policy requirements, and continuously improving the evaluation of the enterprise’s ESG performance by internal and external stakeholders. High-quality ESG information disclosure can send positive signals to host countries, enhance the legitimacy of enterprises, and reduce the “outsider disadvantage” resulting from information asymmetry, thereby improving the long-term performance of cross-border M&As. On the other hand, enterprises should integrate ESG principles into all aspects of production and operation. They should increase technological innovation in energy saving, emission reduction, and green environmental protection, reduce carbon and pollutant emissions, and continuously promote the green transformation, upgrading, and renovation of their dominant industries. This will stimulate innovation vitality, optimize resource allocation, and achieve a dual growth of economic benefits and social value, which not only aligns with sustainable development trends but also helps gain competitive advantages in the international market.

7.2. Industry Level: Role of Industry Associations

At the industry level, industry associations should play a guiding role. Industry associations should actively organize ESG training and exchange activities, share best practice cases, and promote enterprises in the industry to enhance ESG awareness and capabilities. Encourage the formulation of ESG guidelines and standards that meet industry characteristics to promote the sustainable development of the industry as a whole. Secondly, promote the construction of industry ESG evaluation systems. Third-party institutions are encouraged to develop and improve ESG evaluation systems for different industries, provide investors and stakeholders with more targeted and comparable ESG information, and guide resources to enterprises with better ESG performance.

7.3. Government Level: Improve Institutional Development and Provide Policy Support

At the government level, on the one hand, it is necessary to improve the ESG system construction, strengthen ESG audit supervision, and ensure the healthy and stable development of ESG market; at the same time, it is necessary to actively publicize and train ESG-related policies to enterprises, so as to promote the improvement of social responsibility and information transparency of enterprises. On the other hand, the government can formulate relevant policies to support international trade, such as cross-border M&As, and provide corresponding policy support and ESG resource guarantee, so that enterprises can overcome the disadvantages of outsiders to a certain extent, accelerate the transaction process, and improve the performance of M&As. This will provide a more favorable environment for cross-border M&As of Chinese enterprises, help enterprises obtain international competitive advantages, enhance market position, and promote the internationalization process of Chinese enterprises.

8. Future Research Prospects

This study provides valuable insights into the impact of ESG performance on the long-term outcomes of cross-border M&As. However, several avenues remain open for future research to further refine our understanding and provide more nuanced guidance for both practitioners and policymakers.

8.1. Sectoral and Geographic Granularity

Future research could delve deeper into the specifics of how ESG influences cross-border M&As across different sectors and geographic regions. While the core findings of this study have broad global relevance, particularly for emerging markets, differences in the maturity of ESG regulatory frameworks, investor focus, cultural values, and institutional environments across various markets and economies necessitate further investigation. Expanding the sample to encompass a broader range of companies from diverse countries and regions would enable the verification of the findings’ universality and the identification of any sector- or region-specific nuances.

8.2. ESG Dimensions and M&A Integration

Future research should examine the role of different ESG dimensions (Environmental, Social, and Governance) throughout the various stages of the M&A integration process. This could include analyzing how specific social responsibility practices facilitate cultural integration, or how strong governance mechanisms can improve the overall efficiency of the integration.

8.3. ESG Disclosure Quality and Impact

The quality of ESG disclosures, including their completeness, accuracy, and credibility, warrants further investigation in future research. Exploring how investors and other stakeholders interpret and utilize this information, and how it impacts cross-border M&A performance, would be of significant value.

Through the above efforts, future research will be able to more comprehensively and deeply understand the role of ESG in enterprise internationalization strategy, and provide more targeted guidance for enterprises and governments.