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Purpose

This study investigates whether foreign directors from positive peace cultures enhance a firm’s environmental, social and governance (ESG) performance. Grounded in Social Learning Theory, we argue that such directors facilitate the diffusion of ethical values and sustainable governance practices in boardrooms.

Design/methodology/approach

Using a sample of 26,744 firm-year observations of Chinese firms listed on the Shanghai and Shenzhen stock exchanges from 2009 to 2024, we construct a novel board-level Positive Peace Index (PPI) based on the PPI scores of foreign directors’ countries of origin obtained from the Institute for Economics and Peace (IEP). We then estimate a lead-lag OLS model, regressing ESG performance, measured using the Huazheng ESG composite score, on PPI alongside relevant control variables.

Findings

Firms with foreign directors from stronger positive peace cultures (i.e. a higher average of positive peace level on the board) demonstrate superior ESG performance, particularly in product quality, corporate governance, and environmental protection. The positive effect of PPI is more pronounced in firms with less government intervention, lower CEO power, and more frequent board meetings, reflecting conditions that foster open dialog and social learning. Importantly, PPI provides explanatory power beyond Hofstede’s cultural dimensions and generic board diversity measures.

Originality/value

This study introduces positive peace culture as a novel, values-based lens for examining the cultural influence of foreign directors on ESG, addressing prior mixed findings in the literature. By moving beyond Hofstede’s framework, we respond to calls for more nuanced, context-sensitive cultural metrics (Chanchani and MacGregor, 1999; Doupnik and Tsakumis, 2004). Our findings carry practical implications for firms, investors, and policymakers in emerging markets, advocating for thoughtful board composition strategies that prioritize cultural values such as positive peace that are aligned with ethical and sustainable business practices.

Peace, as a foundation for sustainable societal stability, emphasizes ethical decisions and responsible governance that balance economic, social, and environmental development (Groff and Bouckaert, 2015). Institutions including the United Nations Global Compact (UNGC), the Institute for Economics and Peace (IEP), and the Hague Centre for Global Justice have promoted peace initiatives. In 2013, the UNGC introduced “Business for Peace” to encourage firms to manage risks, reduce harm, and foster peace in workplaces, markets, and communities (Fort and Schipani, 2004; Oetzel et al., 2010; UNGC, 2015). Given the growing global focus on peace as a central theme of the 21st century, this study adds to the governance and ESG literature by using Social Learning Theory (Bandura, 1977) to explore how foreign directors' peace-oriented values shape boardroom behavior and ESG practices.

Corporate leaders’ cultural values significantly influence ESG. Culture, as a set of shared beliefs and attitudes, informs decisions and behavior. Michaelson (2022) notes that identity and actions are interlinked and shaped through social interactions. According to Bandura (1977), such values are learned through observation in social settings like boardrooms, supporting the view that directors can influence ESG through cultural modeling.

Existing research on cultural attributes and sustainability including ESG or corporate social responsibility (CSR) shows mixed results. For instance, in the context of China, while some studies find that attributes such as CEO or director foreign experience, board cultural diversity and board internationalization improve ESG/CSR performance or disclosure (Liu, 2024; Teng et al., 2025; Wu et al., 2024), other studies do not find foreign directors contribute to these outcomes (Lau et al., 2016; Liao et al., 2018). Others, however, report positive links between foreign directors or board cultural diversity and ESG/CSR in different contexts (Dodd et al., 2022; Luo et al., 2022; Muttakin et al., 2015). These inconsistencies may stem from broad or multifaceted measures of “foreignness” or cultural diversity. Instead, we focus on an underexplored factor—positive peace culture—as a more targeted and meaningful indicator of directors’ sustainability mindset.

According to Cohrs et al. (2013) and Galtung (1985), peace can be categorized as negative (absence of violence) and positive (sustainable societal peace). The IEP (2019, 2020) outlines eight pillars of positive peace, including free flow of information, sound business environment, equitable distribution of resources, high human capital, good relations with neighbors, acceptance of the rights of others, well-functioning government, and low corruption. As this form of peace promotes sustainability, it aligns closely with ESG and CSR (Guthrie, 2014). Hence, our study specifically examines the influence of positive peace culture. Drawing on social learning theory (Bandura, 1977), we argue that foreign directors from positive peace cultures promote ESG through modeling ethical behaviors and sharing experiences. These directors foster values of sustainability, thereby influencing native directors' mindset. Their credibility, derived from lived experience in peace-oriented societies, makes them effective change agents for advancing ESG practices.

China provides a compelling empirical context for our study, given its policy goal of a “harmonious society” and top-down ESG enforcement (Marquis and Qian, 2014). Amid rapid economic growth, ESG has gained importance as firms seek to address ethical lapses and enhancing legitimacy in China (Moon and Shen, 2010). Politically empowered local governments enforce ESG as part of performance evaluations (Lin et al., 2015). Meanwhile, China’s increasing use of foreign directors fosters social learning in boardrooms, especially in contexts where contract enforcement is weak (Luo et al., 2021).

Using 26,744 firm-year observations of Chinese firms (2009–2024), we find that foreign directors from countries with stronger positive peace culture (i.e. a higher average positive peace level on the board) are associated with better ESG performance. These directors enhance ESG particularly in the areas of product quality, corporate governance, and environmental protection, suggesting these as key channels of influence. We also identify contextual moderators. The effect of positive peace culture is stronger in firms with weaker CEO power, more frequent board meetings, and lower government intervention, mirroring conditions that promote open dialog and social learning. Endogeneity checks, including PSM, entropy balancing, and instrumental variable regressions, affirm our results. To further isolate the director-level influence from the firm’s geographic operational exposure to high positive peace countries, we conduct a robustness analysis by restricting the analysis is to firms with zero foreign sales and continue to observe similar results. Importantly, we show that our board-level positive peace measure (PPI) adds explanatory power beyond board cultural scores computed based on Hofstede’s cultural dimensions or generic board diversity measures.

Our study offers the following scholarly contributions. First, we extend the ESG and corporate governance literature by showing how directors’ positive peace culture, via social learning, shapes ESG. Chanchani and MacGregor (1999) argue that national culture is a complex and multifaceted construct, cautioning against over-reliance on any single cultural framework, including Hofstede’s, and highlighting the need for a more nuanced and context-sensitive approach in accounting research. Doupnik and Tsakumis (2004) also emphasize that Hofstede’s cultural dimensions represent only one perspective on national culture and advocate for exploring alternative cultural frameworks to enhance our understanding of how culture shapes organizational behavior. Our study, therefore, offers a new lens beyond Hofstede’s framework, highlighting the influence of directors’ beliefs, values, and social experiences grounded in positive peace orientation. Moreover, Huang and Watson (2015) note that ESG may be driven by altruistic motivations. In line with this, the positive peace culture of foreign directors may also reflect deeply rooted altruistic values, which can influence board decision-making and drive stronger ESG engagement. Second, we help explain the mixed findings of prior empirical research on foreign directors’ influence on ESG-related outcomes (e.g. Liu, 2024; Lau et al., 2016; Liao et al., 2018; Luo et al., 2022; Muttakin et al., 2015). We show that not all foreign directors enhance ESG; rather, those from positive peace cultures do. This introduces a novel and clearer, values-based cultural framework for future research.

Practically, our findings suggest that firms in emerging markets should consider directors’ cultural traits when appointing foreign board members. While we do not argue that firms should appoint foreign directors solely for ESG improvement, our evidence shows that positive peace-oriented directors support meaningful ESG, when given enabling environments such as frequent board interactions and reduced power imbalances. Firms with such boards are more likely to inspire trust through ethical practices, whereas homogenous or culturally misaligned boards may face skepticism or scrutiny. Finally, our study informs policymakers, especially in emerging economies, on attracting talent that supports sustainability. By encouraging the appointment of foreign directors with strong positive peace attributes, policymakers can promote ethical leadership and long-term ESG commitments. These directors influence local boards through shared values and social learning, helping firms go beyond compliance and contribute to a more harmonious society.

The concept of business for peace highlights how firms can reduce conflict and foster peaceful societies, with ESG as a key mechanism (UNGC, 2015). Oetzel et al. (2010) identify five main ways MNCs can contribute to peace in conflict-prone areas. First, they promote economic development through investment, job creation, and the diffusion of knowledge and technology, thereby improving living standards and reducing violence (Fort and Schipani, 2004; Rogers and Ramsbotham, 1999). Second, businesses can engage in track-two diplomacy by mediating with political leaders to ease tensions (Westermann-Behaylo et al., 2015). Third, adopting global standards and codes of conduct fosters justice and strengthens the rule of law (van Tulder and Kolk, 2001). Fourth, ESG/CSR policies, such as those advancing gender equity and employee voice, support community peace by aligning firm goals with stakeholder interests (Aguilera et al., 2007; Spreitzer, 2007). ESG enhances accountability and legitimizes business in the peace agenda (Schouten and Miklian, 2020), reinforcing that “ethical business behavior leads to peace” (Oetzel et al., 2010, p. 352). Fifth, firms should assess conflict risks before entering sensitive regions to avoid aggravating local tensions, as unequal resource distribution can spark unrest (O’Neill, 2008).

Despite growing interest, empirical research on the ethical and contextual drivers of business for peace remains limited. Oetzel et al. (2010) call for studies examining factors like corporate leaders’ values. In response, we propose that directors’ positive peace culture, an ethical and contextual trait, shapes their capacity and motivation to pursue ESG as a pathway to business for peace (Aguilera et al., 2007; Guthrie, 2014).

Research on how directors’ cultural backgrounds influence ESG/CSR is growing (Jing et al., 2026) but yields mixed findings. Culture, defined as shared “beliefs, norms, and behavioral patterns of a national group” (Leung et al., 2005, p. 357), shapes individuals' values, thoughts, and actions. Leung et al. (2005) emphasize that the human mind adapts through interaction with its societal environment. Societal culture affects directors’ sense of social responsibility, and leaders’ values influence their strategies, therefore directors’ cultural values can affect ESG/CSR (Waldman et al., 2006).

Studies have examined the “foreignness” of directors. In China, Lau et al. (2016) find CSR improves with directors' foreign experience (e.g. overseas education) but not with the mere presence of foreign directors. Similarly, Liu (2024) links directors’ foreign experience with reduced firm carbon emissions. Liao et al. (2018) show CSR assurance is less likely in firms with foreign directors. El-Bassiouny and El-Bassiouny (2019) report positive effects of foreign directors on CSR disclosure in Egypt, but not in the US or Germany. Luo et al. (2022), using Chinese data, find foreign directors improve CSR performance.

Other works investigate the impacts of board cultural or nationality diversity on ESG/CSR disclosures or performance. Muttakin et al. (2015) find positive effects in Bangladesh. Comparable evidence is found in US (Dodd et al., 2022), EU (Bigelli et al., 2023), Australia (Mohy-ud-Din, 2023) and China (Teng et al., 2025; Wu et al., 2024). In contrast, Katmon et al. (2019) observe negative effects in Malaysia, while Barako and Brown (2008) find no significant relationship in Kenya. These mixed outcomes may stem from the ambiguity of “foreignness” and “cultural diversity,” which reflect multiple cultural dimensions with varying ESG impacts. We propose focusing on a specific, underexplored factor—foreign directors’ positive peace culture—as a clearer, more targeted lens to explain ESG variation.

Social Learning Theory (SLT) explains how individuals acquire attitudes and behaviors through observing and modeling others in social contexts (Bandura, 1977; Wood and Bandura, 1989). Based on SLT, we argue that foreign directors can serve as role models for ESG, with their behavior influencing Chinese directors and enhancing overall ESG performance. By exemplifying ethical decision-making and engaging in interpersonal exchanges (Forbes and Milliken, 1999), these directors help transmit positive peace values, thereby strengthening ESG performance.

SLT highlights the importance of observational learning, imitation, and modeling in behavioral development. Bandura (1977) shows that people acquire not only behaviors but also values and emotional responses by observing others. The boardroom provides such a social context. Directors from positive peace cultures internalize values such as equity, ethics, and cooperation, which are essential to ESG. Their behavior creates a reference point for native directors, as individuals tend to adopt behaviors linked to positive outcomes (Bandura, 1977). Foreign directors modeling ethical leadership and ESG commitment can thus shape broader boardroom conduct. Modeling includes not only behavior but also the values underpinning it (Bandura, 1977). Nielsen and Nielsen (2013) show that foreign directors bring diverse perspectives that enrich board decision-making, especially in complex areas like ESG. Bandura (1977) notes that credible, successful role models, such as reputable foreign directors, are especially influential.

Interactions among culturally diverse directors foster knowledge sharing and ethical standard setting. Homberg and Bui (2013) argue that cross-cultural board dynamics enhance innovation and broaden perspectives, supporting more comprehensive ESG strategies. Tihanyi et al. (2005) show that foreign directors transmit knowledge across borders and influence firm strategy, particularly in ESG. As ESG gains global attention, foreign directors from peace-oriented cultures are well-positioned to lead ESG initiatives.

Peaceful societies embed peace values into education, governance, and social policies, shaping the citizens’ ethical norms and management approaches (Schneider and DeMeyer, 1991). Social norms and civic values influence individuals' ESG-related behavior (Hoi et al., 2018). Guided by SLT, we argue that directors from positive peace cultures integrate these values into boardroom discussions, encouraging ESG-aligned decisions.

Such directors promote stakeholder harmony and democratic engagement on social and environmental concerns (Spreitzer, 2007). They may demonstrate greater ethical awareness and initiate constructive dialog, steering firms toward responsible practices. Given China’s push to enhance ESG (Gao and Hafsi, 2015; Lin et al., 2015; Moon and Shen, 2010) and its openness to foreign expertise, the Chinese context is conducive to social learning in boardrooms (Wood and Bandura, 1989). Directors from peace cultures can act as change agents, drawing on their values and experiences to shape sustainable business conduct.

According to the IEP (2019, 2020), positive peace is built on eight pillars. First, directors from such cultures support transparent ESG disclosures that enhance stakeholder decision-making. Second, they promote ethical business conduct that fosters stability and reduces legal uncertainty. Third, they advocate equitable resource distribution, supporting fair supply chains and corporate philanthropy. Fourth, they value human capital, promoting inclusivity, employee development, and workplace satisfaction.

Fifth, they encourage long-term stakeholder relationships through ethical partnerships and trust-building. Sixth, they defend human rights by advocating fair labor, safe working conditions, and environmental stewardship. Seventh, they reject corruption, favoring decisions that promote integrity and fair competition. Finally, they emphasize good governance, enhancing compliance, social trust, and political stability.

Through social learning, these directors expand native directors’ ESG perspectives, cultivating greater social awareness and pushing ESG beyond mere compliance. Such influence can enhance firm performance across various ESG domains, including product quality, community development, governance, diversity, environmental stewardship, and employee relations. These discussions lead to our first hypothesis (H1):

The positive peace culture of foreign directors is positively associated with a firm’s ESG performance.

We employ the following lead-lag ordinary least squares (OLS) model to examine the relationship between corporate boards' positive peace culture and the ESG performance of Chinese listed firms. Variable definitions are provided in  Appendix.

(Model 1)

Consistent with prior Chinese ESG studies (e.g. Huang and Duan, 2024; Li et al., 2022), we measure ESG performance (ESG) using the Huazheng ESG composite score provided by Sino-Securities Index Information Service from the WIND database. We adopt the Huazheng ESG composite score as the main measure of our dependent variable because it provides comprehensive coverage of Chinese listed firms over time, as well as extensive range of performance indicators that capture China’s social system and market characteristics, thereby demonstrating stronger alignment with China’s local institutional context (Huang and Duan, 2024). The Huazheng ESG composite scores measure sustainability initiatives across three dimensions: Environmental (E), Social (S), and Governance (G) under 16 themes, 44 key issues, and 80 performance indicators [1] (Sino-Securities, 2024). Each indicator is scored separately and adjusted by industry-specific factors before aggregating them into a composite score ranging from 0 to 100. A higher composite score indicates better ESG performance.

To construct our test variables, we obtained the overall score of Positive Peace Index (PPI) for each country from the IEP. Since 2009, the IEP assesses the level of positive peace each country under the guidance of an international panel of independent experts using eight pillars of positive peace: free flow of information, sound business environment, equitable distribution of resources, high levels of human capital, good relations with neighbors, acceptance of the rights of others, well-functioning government, and low levels of corruption (IEP, 2019).

We first assign each director on the corporate board with the raw PPI overall score based on their nationality. The raw PPI overall score ranges on a scale from 1 to 5, with 1 (5) representing the highest (lowest) level of positive peace (IEP, 2019). As a lower raw PPI overall score indicates greater positive peace, we multiply the score by negative one for ease of interpretation and label this transformed variable as PPI_INV. Thus, a higher PPI_INV captures greater positive peace. We then construct our measure which captures the positive peace culture on corporate board namely PPI, as the average of PPI_INV assigned to each director based on their country of nationality. A higher PPI indicates a higher average positive peace level on the board [2]. Therefore, a positive coefficient on PPI supports H1, where a higher level of social learning of positive peace mentality facilitated by foreign directors is associated with stronger ESG performance.

We control for board characteristics that influence ESG performance. These include CEO power proxied by CEO-Chairperson duality (Duality), which inhibits ESG (Bigelli et al., 2023; Muttakin et al., 2018), and board size (B_Size), which enhances it (Beji et al., 2022). We also control for board gender diversity (B_Female) and independence (B_Ind), as both are associated with stronger ESG outcomes (Beji et al., 2022; Bigelli et al., 2023; McGuinness et al., 2017).

Model (1) further includes firm-level controls. ESG engagement is expected to be positively driven by firm size (Firm_Size), which captures exposure to stakeholder pressures; firm age (Firm_Age), which reflects visibility and reputation; and profitability (ROA), which is linked to ESG engagement (Cho et al., 2010; Orlitzky, 2001; Teng et al., 2025; Wu et al., 2024). Leverage (LEV) accounts for creditor constraints on ESG, while slack resources (Slack) enable discretionary ESG spending (Seifert et al., 2004). We control for listing exchange (Exchange), foreign sales (Foreign) to capture institutional and international ESG pressures (Marquis and Qian, 2014). We further control for state ownership (SOE), given policy-driven ESG in SOEs (Lin et al., 2015). Shareholder power (TOP1) also affects ESG decisions (Lin et al., 2015), as does media exposure (Media) (Marquis and Qian, 2014). Year and industry fixed effects are included, with standard errors clustered at the firm level. All continuous variables are winsorized at the 1st and 99th percentiles.

We begin with 41,725 firm-year observations of Chinese firms listed on the Shanghai and Shenzhen stock exchanges from 2009 to 2024. The sample starts in 2009 when the PPI data became available (IEP, 2019). We exclude 482 firm-years due to missing ESG data, 800 firm-years in the financial, investment, and insurance sectors due to differing regulations, and 1,309 firm-years involving financially distressed or suspended firms. An additional 12,390 firm-years are removed due to missing data in CSMAR and CNRDS, yielding a final sample of 26,744 firm-year observations.

Board director nationality is manually extracted from firms’ annual reports and verified through company websites and Chinese search engines (Baidu, Sina and Iwencai). Each foreign director is assigned a raw PPI overall score (IEP), forming the basis of our test variable, PPI. Our final sample includes 1,560 foreign directors from 30 countries or jurisdictions. Panel A of Table 1 shows the distribution, with the largest share from the US (35.45%), followed by Taiwan (14.62%) and Canada (11.22%). Directors from Singapore, Japan, the U.K., France, Australia, Germany, Italy, the Netherlands, and Thailand constitute the remaining 31.15%.

Table 1

Statistics of foreign directors and positive peace index

Panel A: Nationality distribution of foreign directors
CountryNumber% Total
Australia583.72%
Austria80.51%
Belgium100.64%
Brazil60.38%
Canada17511.22%
Denmark80.51%
France674.29%
Germany392.50%
India50.32%
Indonesia60.38%
Israel181.15%
Italy281.79%
Japan855.45%
Malaysia110.71%
Netherlands201.28%
New Zealand70.45%
Portugal50.32%
Tunisia10.06%
Saudi Arabia20.13%
Singapore935.96%
Slovakia10.06%
South Africa20.13%
South Korea60.38%
Spain80.51%
Sweden20.13%
Switzerland120.77%
Taiwan22814.62%
Thailand191.22%
U.K774.94%
U.S55335.45%
Total1,560100.00%
Panel B: Yearly Raw positive peace index of China and foreign directors’ home countries
Country2009201020112012201320142015201620172018201920202021202220232024
Australia1.731.731.731.731.751.741.761.751.751.721.711.721.711.731.671.73
Austria1.851.831.851.841.831.821.881.861.871.841.851.881.901.901.871.90
Belgium1.921.881.881.881.871.891.881.891.911.891.891.871.861.851.831.85
Brazil2.842.812.812.812.802.802.822.922.972.993.003.093.133.123.113.12
Canada1.721.721.721.721.721.711.731.721.721.711.691.751.731.751.731.75
Denmark1.481.471.471.471.481.481.491.511.511.491.461.471.451.441.441.44
France1.941.911.901.911.911.911.931.921.911.891.871.921.901.891.871.89
Germany1.791.781.771.751.751.731.741.751.761.761.741.761.751.741.691.74
India3.303.323.333.333.323.353.343.323.293.263.263.263.253.253.253.25
Indonesia3.403.393.383.363.333.303.313.283.263.233.223.233.213.203.263.20
Israel2.562.532.512.512.502.492.492.472.482.472.442.472.392.402.442.40
Italy2.292.292.302.312.302.312.312.292.272.262.242.252.242.222.242.22
Japan1.951.931.961.941.891.831.831.821.811.801.791.791.781.781.761.78
Malaysia2.992.942.932.922.892.862.882.892.872.772.752.742.752.742.732.74
Netherlands1.671.661.651.641.651.641.651.651.641.631.621.691.721.701.721.70
New Zealand1.811.801.781.791.771.741.741.731.731.721.691.651.661.651.651.66
Portugal2.002.002.002.001.991.981.961.971.921.951.951.951.951.941.981.94
Tunisia3.153.153.053.033.043.033.023.013.022.982.962.973.013.023.023.03
Saudi Arabia3.373.363.403.373.273.273.273.253.293.263.243.233.213.143.153.14
Singapore1.931.901.901.871.851.821.821.821.811.791.761.791.801.791.731.79
Slovakia2.382.372.362.382.372.372.422.422.442.422.392.342.352.342.362.34
South Africa3.133.133.133.123.093.103.083.083.103.103.073.073.073.093.033.09
South Korea2.152.112.082.072.042.032.062.072.011.961.921.931.941.971.991.97
Spain2.152.142.132.142.152.162.152.132.122.122.082.172.162.182.172.18
Sweden1.501.491.491.481.501.461.491.491.491.481.461.471.461.461.471.46
Switzerland1.591.591.581.581.591.551.541.541.531.511.511.521.501.501.451.50
Taiwan2.572.542.522.512.502.472.462.442.432.412.382.342.332.332.302.33
Thailand3.213.193.173.153.133.173.183.153.133.093.043.043.043.033.033.03
U.K1.881.871.891.891.891.861.861.881.911.911.911.981.981.982.001.98
U.S1.901.931.941.942.002.002.021.992.092.122.132.242.212.182.192.18
China3.343.333.293.283.303.273.263.233.213.163.133.133.103.083.083.08

Note(s): A lower raw PPI indicates a greater level of positive peace

Panel B of Table 1 reports the raw overall PPI scores of foreign directors’ home countries from 2009 to 2024. Lower raw overall PPI scores indicate greater positive peace. Directors from Denmark, Sweden, and Switzerland, consistently display the lowest scores, suggesting the strongest positive peace orientation. Most foreign directors come from countries with higher positive peace levels than China, though the degree of difference varies. However, directors from countries like India, Indonesia, Saudi Arabia, and Brazil are assumed to exhibit relatively weaker positive peace attitudes, as their home countries show higher PPI scores than China, particularly in recent years [3].

Table 2 presents descriptive statistics for the main variables. The mean (median) of ESG is 4.301 (4.307), and for PPI, −3.170 (−3.160), with a range from −3.340 to −2.797. Board and firm characteristics are broadly consistent with prior Chinese studies (Luo et al., 2021; Marquis and Qian, 2014; Marquis and Bird, 2018; Wang et al., 2018a). The Pearson correlation matrix (Online Appendix 1) shows a positive and significant correlation between PPI and ESG. All variance inflation factors are below five, indicating no multicollinearity concerns.

Table 2

Descriptive statistics

VariableNMeanP25P50P75SDMinMax
ESG26,7444.3014.2634.3074.3500.0773.6284.615
PPI26,744−3.170−3.270−3.160−3.0900.107−3.340−2.797
Duality26,7440.2740010.44601
B_Size26,7442.1291.9502.2002.2000.1991.6102.710
B_Female26,7440.15200.1250.2220.13200.556
B_Ind26,7440.3760.3330.3640.4290.05500.571
Firm_Size26,74422.30021.33022.09023.0501.36519.4127.220
Firm_Age26,7442.1721.6102.4002.8300.86503.400
ROA26,7440.0390.0100.0400.0700.067−0.2600.220
LEV26,7440.4280.2600.4200.5800.2100.0500.980
Slack26,7440.0480.0100.0470.0880.071−0.1960.297
Exchange26,7440.6190110.48601
Foreign26,7440.12300.0040.1580.20900.876
SOE26,7440.3790010.48501
Top126,7440.3380.2200.3200.4400.1500.0800.740
Media26,7444.2793.2194.3445.3711.6260.6938.344

Column 1 of Table 3 presents the main results. The coefficient on PPI is positive and significant, supporting H1. Specifically, Chinese firms with foreign directors from countries with stronger positive peace cultures (i.e. a higher average positive peace level on the board) exhibit better ESG performance compared to those with foreign directors from weaker positive peace cultures or without foreign directors (i.e. a lower average positive peace orientation of the board). Control variable results are largely consistent with prior studies (Marquis and Qian, 2014; McGuinness et al., 2017; Teng et al., 2025; Wang et al., 2018b; Wu et al., 2024). Specifically, B_Ind, Firm_Size, ROA, Slack, Foreign, SOE, and Media are positively and significantly associated with ESG, while Firm_Age, Lev, and Exchange are negatively and significantly related to ESG.

Table 3

Main results, propensity score matching and entropy balancing

Dependent variable: ESGi,t
Full samplePropensity score matched sampleEntropy balanced sample
(1)(2)(3)
Constant3.938***4.034***4.003***
(121.267)(59.641)(92.080)
PPIi,t-10.014**0.034**0.030***
(2.023)(2.331)(3.367)
Dualityi,t-1−0.002−0.001−0.001
(−1.146)(−0.294)(−0.518)
B_Sizei,t-10.001−0.0070.003
(0.154)(-0.580)(0.405)
B_Femalei,t-1−0.002−0.010−0.010
(−0.338)(−0.870)(−1.387)
B_Indi,t-10.058***0.0480.053**
(4.183)(1.311)(2.324)
Firm_Sizei,t-10.018***0.016***0.016***
(23.140)(8.959)(14.939)
Firm_Agei,t-1−0.010***−0.003−0.004**
(−9.656)(−1.223)(−2.392)
ROAi,t-10.099***0.101***0.102***
(9.073)(3.306)(5.242)
LEVi,t-1−0.054***−0.036***−0.038***
(−12.308)(−3.182)(−5.588)
Slacki,t-10.038***0.055**0.033*
(4.467)(2.041)(1.942)
Exchangei,t-1−0.007***−0.006−0.005**
(−4.239)(−1.626)(−2.199)
Foreigni,t-10.009**0.013*0.007*
(2.537)(1.877)(1.694)
SOEi,t-10.011***0.0040.006*
(5.470)(0.725)(1.955)
Top1i,t-1−0.002−0.010−0.006
(−0.293)(−0.810)(−0.887)
Mediai,t-10.002***0.002*0.003***
(4.269)(1.710)(4.868)
Year fixed effects and industry fixed effectsYesYesYes
N26,7442,41026,744
Adjusted R20.1500.1330.166

Note(s): Variables are defined in  Appendix. Robust standard errors are clustered at the firm level. The t-statistics are in parentheses. *, **, and *** indicate significance at the 10, 5, and 1 percent levels (two-tailed), respectively

To address endogeneity concerns arising from non-random board composition, we conduct a PSM analysis. The treatment group comprises firms with foreign directors from countries with stronger positive peace cultures than China, while the control group includes firms with directors from weaker peace cultures or only Chinese directors. PSM reduces variation in observable confounders affecting ESG while isolating variation in board-level positive peace culture.

In the first stage, we estimate a logistic model regressing a binary variable, PPI_Dummy, on all control variables from Model (1). PPI_Dummy equals one if a firm’s PPI exceeds the annual median (treatment group), and zero otherwise (control group). Using predicted probabilities, we match treatment and control firms using 1:1 nearest-neighbor matching with a 0.01 caliper, yielding 1,205 matched pairs (2,410 firm-year observations).

Covariate balance checks (Panel A, Online Appendix 2) confirm no significant differences in control variables post-matching, supporting the validity of our approach. Re-estimating Model (1) using the matched sample, Column 2 of Table 3 shows that the coefficient on PPI remains positive and significant, reinforcing support for H1.

We further apply entropy balancing to address selection bias on observables. Using the same PPI_Dummy from the PSM analysis, we define treatment (PPI_Dummy = 1) and control (PPI_Dummy = 0) groups. We balance the covariates drawn from Model (1) across the first three moments (mean, variance, skewness), ensuring that reweighted control group observations match the treatment group distribution.

Entropy balancing generates optimal weights for control observations while retaining the full sample. Panel B, Online Appendix 2 confirms minimal, statistically insignificant differences in covariates between groups, mitigating concerns over confounding effects. Re-estimating Model (1) using the reweighted sample, Column 3 of Table 3 also shows a positive and significant coefficient on PPI, reinforcing our main result.

To address concerns of omitted variable bias, we employ a two-stage least squares (2SLS) instrumental variable (IV) approach. We select an IV correlated with PPI but unrelated to ESG. Based on Giannetti et al. (2015), we use Policy, which is the number of years since the adoption of a foreign talent policy in the firm’s province, as the IV. Provinces with longer-standing policies are more likely to attract foreign directors, especially those from high positive peace countries.

Table 4 reports the IV results. In Column 1 (first stage), Policy is positively and significantly associated with PPI, indicating its effectiveness in promoting foreign director recruitment. In Column 2 (second stage), Predicted_PPI estimated from the first stage is positively and significantly related to ESG, reinforcing our main findings.

Table 4

Two-stage instrumental variable regression (2SLS) and other robustness tests

First stage of 2SLSSecond stage of 2SLSAlternate ESG measure with LSEG ESGAlternate ESG measure with CNRDS ESGAlternate PPI measureControlling for Hofstede’s cultural dimensionsControlling for board cultural diversityRuling out the impacts of geographic operational or sales exposure
Dependent variable: PPIi,t-1Dependent variable: ESGi,tDependent variable: ESG_Alt1i,tDependent variable: ESG_Alt2i,tDependent variable: ESGi,tDependent variable: ESGi,tDependent variable: ESGi,tDependent variable:
ESGi,t
(1)(2)(3)(4)(5)(6)(7)(8)
Constant−3.675***6.437***−1.053***4.306***−1.025***3.911***3.916***3.969***
(−242.980)(5.676)(−23.373)(9.237)(−24.589)(130.077)(129.922)(88.856)
Policyi,t-10.001***       
(3.170)       
Predicted_PPIi,t-1 0.711**      
 (2.274)      
PPIAlti,t-1    0.186***   
    (4.344)   
PPIi,t-1  0.202***0.546*** 0.014**0.015**0.021**
  (4.427)(5.544) (2.068)(2.233)(2.291)
PDIi,t-1     −0.002  
     (−0.991)  
IDVi,t-1     −0.001  
     (−0.785)  
MASi,t-1     0.011***  
     (2.707)  
UAIi,t-1     −0.003**  
     (−2.369)  
B_Cultural_Diversity      −0.003*** 
      (−3.394) 
Dualityi,t-10.010***−0.009**0.000−0.058**0.000−0.002−0.002−0.002
(7.500)(−2.487)(0.045)(−2.533)(0.079)(−1.418)(-1.475)(-0.999)
B_Sizei,t-1−0.051***0.036**0.0120.0280.015*0.0020.002−0.002
(−14.010)(2.210)(1.505)(0.423)(1.931)(0.417)(0.528)(−0.447)
B_Femalei,t-10.020***−0.052**−0.019**−0.023−0.021***−0.002−0.002−0.000
(21.710)(−2.255)(−2.539)(−0.305)(−2.921)(−0.556)(−0.499)(−0.033)
B_Indi,t-1−0.148***0.082***0.093***−0.3080.090***0.048***0.049***0.044**
(−2.830)(4.754)(3.525)(−1.421)(3.589)(3.687)(3.752)(2.178)
Firm_Sizei,t-1−0.036***−0.0040.042***0.0100.041***0.017***0.017***0.019***
(−13.560)(−0.392)(22.993)(0.907)(24.170)(27.416)(27.313)(17.530)
Firm_Agei,t-10.095***−0.024***0.003−0.126***0.004**−0.007***−0.007***−0.012***
(10.330)(−3.748)(1.564)(−8.424)(2.122)(−7.137)(−7.261)(−8.807)
ROAi,t-1−0.008***0.202***0.048***0.0670.048***0.113***0.113***0.088***
(−6.250)(4.271)(2.720)(0.453)(2.859)(9.325)(9.315)(5.470)
LEVi,t-10.034***−0.001−0.046***0.039−0.047***−0.053***−0.053***−0.058***
(10.400)(-0.053)(-6.293)(0.611)(−6.914)(−13.896)(−13.747)(−9.528)
Slacki,t-1−0.032***−0.0280.056***0.0670.052***0.049***0.049***0.020*
(−22.520)(−0.901)(4.069)(0.553)(4.000)(5.014)(5.059)(1.746)
Exchangei,t-1−0.036***−0.0010.004−0.255***0.002−0.006***−0.006***−0.007***
(−7.970)(−0.380)(1.515)(−10.024)(0.749)(−4.891)(−4.841)(−3.121)
Foreigni,t-1−0.018***−0.0150.0100.0370.012*0.011***0.011*** 
(−44.890)(−1.326)(1.497)(0.689)(1.904)(3.685)(3.804) 
SOEi,t-10.020***0.033***−0.005−0.046−0.005*0.010***0.010***0.015***
(21.710)(3.302)(−1.628)(−1.517)(−1.710)(6.610)(6.574)(5.340)
Top1i,t-1−0.148***0.023*0.013−0.0220.0140.0020.002−0.010
(−2.830)(1.903)(1.397)(−0.271)(1.550)(0.411)(0.389)(−1.327)
Mediai,t-1−0.036***0.014**0.012***−0.0000.012***0.002***0.002***0.002***
(−13.560)(2.558)(15.099)(−0.067)(15.351)(4.957)(4.936)(3.170)
Year fixed effects and industry fixed effectsYesYesYesYesYesYesYesYes
N26,74426,74423,00526,74426,74426,74426,74412,408
F-values10.03///////
Adjusted R20.2710.0970.2970.0250.2970.1460.1460.185

Note(s): Variables are defined in  Appendix. Robust standard errors are clustered at the firm level. The t-statistics are in parentheses. *, **, and *** indicate significance at the 10, 5, and 1 percent levels (two-tailed), respectively

To alleviate concerns about inconsistency due to the lack of standardization, methodology differences, and data variability among ESG rating scores by various agencies (Cheng et al., 2025; Li and Cheng, 2024; Zhong et al., 2019), we re-estimate Model (1) using two alternative ESG performance measures. Following Bigelli et al. (2023), we first use the ESG score provided by London Stock Exchange Group [LSEG] (formerly Refinitiv) to construct our alternative ESG performance measure (ESG_Alt1) for data available from 2009 to 2023. According to LSEG (2024), the ESG score (0–100) captures a firm’s relative ESG performance, commitment, and effectiveness using a data-driven methodology. It draws on more than 870 indicators across ten themes spanning environmental (e.g. resource use, emissions, innovation), social (e.g. workforce, human rights, community, product responsibility), and governance (e.g. management, shareholders, CSR strategy) pillars. Scores are benchmarked against industry peers for environmental and social dimensions and against country peers for governance, enhancing cross-sector and cross-market comparability. The model applies industry-specific materiality weightings and includes a controversies overlay that adjusts scores for verified negative events, scaled to firm size.

In addition, we use the overall ESG rating score provided by the Chinese Research Data Services platform (CNRDS) to construct our second alternate ESG measure (ESG_Alt2) (Ni, 2025; Zhan et al., 2025). The CNRDS ESG score captures indicators across dimensions including philanthropy, volunteer activities and social controversies, corporate governance, diversity, employee relations, environment, and products. CNRDS adopts a framework that is more closely aligned with internationally recognized ESG standards, while also incorporating ESG dimensions that reflect the Chinese institutional environment (Zhao, 2026). However, it tends to be biased toward large-cap firms with relatively high disclosure quality (Zhan et al., 2025).

The regression results reported in Column 3 and Column 4 of Table 4 continue to support our main finding as the coefficient of these alternate ESG measures remain positive and significant.

To capture the degree of positive peace cultural differences between foreign and Chinese directors, we construct an alternative measure, PPI_Alt, defined as the sum of “relative PPI_INV differences” between foreign directors’ home countries and China, scaled by the number of directors. The “relative PPI_INV difference” is calculated by subtracting the foreign director’s home country PPI_INV from China’s PPI_INV and dividing by the foreign country’s PPI_INV. A higher PPI_Alt indicates greater average positive peace on the board. Re-estimating Model (1) with PPI_Alt (Table 4, Column 5) yields a positive and significant coefficient, again supporting H1.

Prior studies have examined how Hofstede’s national culture dimensions (Hofstede, 1980, 2001) relate to ESG or CSR. Gallén and Peraita (2018) associate higher CSR disclosure with uncertainty avoidance in high-GDP countries, while Halkos and Skouloudis (2017) find the opposite. Kim and Kim (2010) report that CSR attitudes are positively linked to uncertainty avoidance, but negatively related to power distance and individualism. Soschinski et al. (2021) associate masculinity with weaker CSR practices. DasGupta (2025) shows that firms operating in cultures characterized by high power distance, strong individualism, long-term orientation, and indulgence are more likely to engage in ESG controversies. In contrast, cultures marked by high masculinity and strong uncertainty avoidance are associated with a lower likelihood of firm-level ESG controversies. Nicolo et al. (2025) show that national culture shapes ESG communication on Twitter, with firms in low power distance, highly individualistic, and more masculine societies exhibiting higher levels of ESG disclosure on the platform.

Accordingly, we control for board-level cultural differences using Hofstede’s cultural dimensions by averaging directors’ national scores. Power distance (PDI) reflects tolerance for unequal power; higher PDI may reduce board oversight of ESG (Kim and Kim, 2010; DasGupta, 2025). Individualism (IDV) reflects self-interest over collectivism; higher IDV may undermine public accountability and ESG (Kim and Kim, 2010; DasGupta, 2025). Masculinity (MAS) reflects emphasis on competition over cooperation; higher MAS may deter (Soschinski et al., 2021) or enhance ESG (Shin et al., 2023). Uncertainty avoidance (UAI) captures aversion to ambiguity. We make no directional prediction for MAS and UAI, given mixed evidence: it may either suppress controversial ESG to avoid legitimacy risk (Bansal and Roth, 2000) or hinder bold initiatives like green innovation (Gurler, 2026).

We re-estimate Model (1) with the inclusion of PDI, IDV, MAS, and UAI. As shown in Column 6 of Table 4, PDI and IDV of the Hofstede cultural dimensions are statistically insignificant while MAS is positively significant and UAI is negatively significant. However, the coefficient on PPI remains positive and significant, reinforcing our main finding. Interestingly, the coefficient on PPI is larger in magnitude than those for MAS and UAI, indicating a comparatively stronger effect.

Foreign directors contribute to national culture diversity on the board, potentially enhancing ESG through improved information exchange and stakeholder understanding (Estelyi and Nisar, 2016). However, cultural diversity may also lead to cross-cultural conflicts and communication barriers that hinder ESG or CSR (Katmon et al., 2019). Prior research offers mixed findings on cultural diversity, showing positive (Dodd et al., 2022; Muttakin et al., 2015; Aliani et al., 2024; Moisello et al., 2026), negative (Katmon et al., 2019), or insignificant (Barako and Brown, 2008) relationships with ESG or CSR.

To demonstrate that PPI captures more than cultural diversity, we re-estimate Model (1) by including a board cultural diversity measure (B_Cultural_Diversity), constructed following Frijns et al. (2016) and Luo et al. (2021) based on four Hofstede dimensions: power distance, individualism, masculinity, and uncertainty avoidance (see  Appendix). Results in Column 7 of Table 4 show that B_Cultural_Diversity is negative and significant while PPI remains positive and significant. This confirms that PPI and board cultural diversity are distinct, with PPI offering incremental explanatory power in explaining ESG variation.

Al-Najjar et al. (2025) link board cultural diversity to business internationalization, arguing that firms may appoint directors from specific countries to strengthen market access in those jurisdictions. Similarly, Belaounia et al. (2024) find that firms with greater foreign operations are more likely to recruit directors from those countries. Accordingly, foreign directors from high positive peace countries may enhance ESG performance particularly when Chinese firms have operational or sales exposure in those directors’ home markets. To disentangle the director-level influence from the firm’s geographic operational or sales exposure to countries with high positive peace, we restrict the analysis to a subsample of firms with zero foreign sales. Using a reduced sample of 12,408 firm-year observations, results show that the coefficient on PPI remains positive and significant (Table 4, Column 8), ruling out the explanation that our main finding is attributable to the impacts of geographic operational or sales exposure.

We further explore the mechanisms through which PPI enhances ESG by examining its effects on specific ESG dimensions using CNRDS data [4]. Following Bartov et al. (2021), we construct dimension-level performance scores by subtracting total concerns from total strengths for: product quality (ProdQuality), community development (CommunityDev), diversity practices (DivPrac), corporate governance (CorpGov), employee relations (EmpRelations), and environmental protection (EnvProtection). Re-estimating Model (1) with each dimension as the dependent variable, results in Table 5 show that PPI is positively and significantly associated with ProdQuality, CorpGov, and EnvProtection. This indicates that a higher average positive peace level on the board effectively promotes product quality, corporate governance and environmental stewardship, which are the key drivers of stronger overall ESG performance.

Table 5

The channels through which positive peace culture improve ESG performance

Dependent variable: ProdQualityti,t-1Dependent variable: CommunityDevi,t-1Dependent variable: DivPraci,t-1Dependent variable: CorpGovi,t-1Dependent variable: EmpRelationsi,t-1Dependent variable: EnvProtectioni,t-1
(1)(2)(3)(4)(5)(6)
Constant−0.515***−0.669***−0.362***−0.716***0.764***−0.816***
(−5.673)(−6.065)(−3.345)(−7.564)(8.742)(−6.563)
PPIi,t-10.458***−0.0770.0820.478***0.0790.584***
(3.926)(−0.551)(0.532)(3.854)(0.790)(3.778)
Dualityi,t-1−0.022**−0.0030.004−0.023**−0.009−0.001
(−2.434)(−0.267)(0.333)(−2.400)(−0.988)(−0.047)
B_Sizei,t-10.040*0.077***0.065**0.047**0.046**0.065**
(1.777)(3.033)(2.490)(2.006)(2.062)(2.174)
B_Femalei,t-1−0.0480.058*0.407***−0.025−0.0000.003
(−1.531)(1.673)(11.132)(−0.764)(-0.002)(0.068)
B_Indi,t-10.187**0.1070.163*0.161**0.0150.049
(2.491)(1.268)(1.845)(2.044)(0.203)(0.490)
Firm_Sizei,t-10.059***0.067***0.022***0.065***0.024***0.067***
(17.724)(16.523)(5.433)(18.365)(6.917)(14.044)
Firm_Agei,t-1−0.024***−0.027***−0.004−0.025***−0.021***0.002
(−4.101)(−4.174)(−0.577)(−4.080)(−3.704)(0.288)
ROAi,t-10.162**0.370***−0.0170.170**0.199***0.222**
(2.192)(3.862)(−0.196)(2.081)(2.628)(1.996)
LEVi,t-10.0120.054*−0.048*−0.013−0.0090.090***
(0.520)(1.808)(−1.664)(-0.516)(−0.363)(2.594)
Slacki,t-1−0.0390.036−0.078−0.024−0.0380.068
(−0.652)(0.473)(−1.064)(−0.355)(−0.600)(0.758)
Exchangei,t-10.057***0.140***0.061***0.059***0.034***0.080***
(7.566)(15.493)(6.501)(7.499)(4.471)(7.175)
Foreigni,t-10.079***0.0360.092***0.070***0.108***0.112***
(4.360)(1.586)(3.855)(3.592)(6.293)(4.319)
SOEi,t-10.000−0.027**0.051***−0.0030.002−0.013
(0.015)(−2.558)(4.705)(−0.287)(0.248)(−1.004)
Top1i,t-1−0.004−0.077***0.0020.0260.053**0.074**
(−0.172)(−2.629)(0.062)(1.006)(2.095)(2.028)
Mediai,t-10.009***0.020***0.014***0.013***−0.0020.017***
(3.868)(6.613)(4.839)(4.934)(−0.965)(4.921)
Year fixed effects and industry fixed effectsYesYesYesYesYesYes
N26,74426,74426,74426,74426,74426,744
Adj. R20.4890.3610.2660.4700.2330.182

Note(s): Variables are defined in  Appendix. Robust standard errors are clustered at the firm level. The t-statistics are in parentheses. *** indicates significance at the 1 percent level (two-tailed)

We explore three contextual factors, indicative of either external forces or internal environments within a firm, that can influence the relationship between PPI and ESG. These factors include local government intervention, CEO power, and board meeting frequency.

5.2.1 Local government intervention

In China, the central government delegates substantial authority to local governments, resulting in varying degrees of intervention across provinces (Luo et al., 2021; Qian and Roland, 1998). We examine whether the positive association between PPI and ESG depends on the level of local government intervention.

We hypothesize that this relationship is stronger under conditions of low government intervention. First, local officials driven by promotion incentives may influence firms to meet social or political goals (Chen et al., 2011), thereby pressuring firms to engage in ESG for legitimacy (Gao and Hafsi, 2015). For example, firms under high intervention often display stronger ESG due to state pressure (Zhang et al., 2021), which may dilute the marginal influence of foreign directors. Second, lower intervention allows greater decision-making autonomy (Luo et al., 2021), enabling foreign directors from countries with high positive peace to drive ESG more effectively and in line with global standards.

We use the inverse of the Government and Market Relationship (GMR) Index by Wang et al. (2018a) to proxy local government intervention (GI), where a higher GI indicates stronger intervention. Firms are split into high- and low-intervention groups based on the annual median GI. Results in Table 6 (Columns 1 and 2) show that PPI is insignificant under high intervention but positive and significant under low intervention, supporting our hypothesis that reduced government interference strengthens the impact of PPI on ESG.

Table 6

Cross-sectional analysis

Dependent variable: ESGi,t
SubsamplesGovernment interventionCEO powerBoard meeting frequency
HighLowHighLowHighLow
(1)(2)(3)(4)(5)(6)
Constant3.927***3.921***3.934***3.941***3.926***3.956***
(81.420)(106.705)(75.474)(143.342)(113.831)(72.019)
PPIi,t-10.0050.019**0.0070.015**0.015**0.012
(0.463)(2.318)(0.692)(2.333)(1.982)(0.981)
Dualityi,t-1−0.003−0.001//−0.001−0.003
(-1.166)(-0.670)//(-0.591)(-1.332)
B_Sizei,t-1−0.0040.0040.013**−0.005−0.0010.002
(-0.584)(0.815)(1.969)(-1.448)(-0.122)(0.361)
B_Femalei,t-1−0.004−0.0010.002−0.006−0.0040.004
(-0.502)(-0.240)(0.317)(-1.309)(-0.684)(0.496)
B_Indi,t-10.0280.082***0.080***0.039***0.065***0.040*
(1.460)(4.978)(3.934)(2.992)(4.263)(1.786)
Firm_Sizei,t-10.017***0.018***0.015***0.018***0.018***0.015***
(15.581)(21.161)(12.059)(30.922)(23.270)(11.805)
Firm_Agei,t-1−0.009***−0.010***−0.006***−0.010***−0.011***−0.007***
(-5.478)(-9.271)(-4.177)(-10.837)(-9.832)(-4.354)
ROAi,t-10.109***0.092***0.121***0.083***0.100***0.090***
(6.214)(7.170)(7.297)(7.034)(8.307)(4.795)
LEVi,t-1−0.051***−0.054***−0.044***−0.057***−0.053***−0.051***
(-7.999)(-10.883)(-6.612)(-15.230)(-11.235)(-7.369)
Slacki,t-10.033***0.040***0.046***0.034***0.029***0.063***
(2.595)(3.817)(3.278)(3.560)(2.911)(4.419)
Exchangei,t-1−0.003−0.010***−0.010***−0.007***−0.008***−0.003
(-1.230)(-5.320)(-3.946)(-5.486)(-4.868)(-1.360)
Foreigni,t-10.0080.009**0.0060.009***0.009**0.008
(1.470)(2.314)(1.302)(2.779)(2.431)(1.517)
SOEi,t-10.009***0.013***0.0020.018***0.012***0.008***
(3.207)(5.605)(0.573)(12.138)(5.668)(2.711)
Top1i,t-1−0.003−0.0000.008−0.0050.000−0.008
(−0.406)(−0.084)(1.002)(−1.093)(0.019)(−0.977)
Mediai,t-10.002***0.002***0.002***0.002***0.002***0.002**
(2.843)(3.570)(3.475)(4.415)(3.891)(2.505)
Year fixed effects and industry fixed effectsYesYesYesYesYesYes
N10,30916,43510,27216,47219,4877,257
Adjusted R20.1370.1590.1160.1750.1600.124
Coefficient comparison Test
PPI in the high versus low local government intervention (GI) subsamples: F-stat. = 50; p-value = 0.000
PPI in the high versus low CEO power (CEO_Power) subsamples: F-stat. = 47; p-value = 0.000
PPI in the high versus low board meeting frequency (B_Meet) subsamples: F-stat. = 50; p-value = 0.000

Note(s): Variables are defined in  Appendix. Robust standard errors are clustered at the firm level. The t-statistics are in parentheses. ** and *** indicate significance at the 5 and 1 percent levels (two-tailed), respectively

5.2.2 CEO power

Given the central role of CEO power in strategic decisions (Finkelstein, 1992), we examine its moderating effect on the PPI–ESG relationship through the lens of Upper Echelons Theory. CEO power reflects the ability to dominate decision-making and resist contrary feedback (Blagoeva et al., 2020). We argue that high CEO power weakens the positive impact of PPI on ESG for two reasons. First, powerful CEOs may prioritize self-interest and short-term gains, making them less inclined to support ESG investments (Muttakin et al., 2018). Second, power concentration can hinder collaborative governance, limiting the influence of foreign directors from positive peace cultures (Eisenhardt and Bourgeois III, 1988).

Using CSMAR and WIND data, we construct a CEO_Power index following Wu et al. (2011) and Finkelstein (1992), using eight variables across four power dimensions: structural, expert, ownership, and prestige (see  Appendix). Firms above (below) the industry median are classified as having high (low) CEO power. We re-estimate Model (1) in these two subsamples, excluding Duality due to its overlap with the CEO_Power index. Results in Table 6 show that PPI is insignificant under high CEO power (Column 3) but positive and significant under low CEO power (Column 4), indicating that effect of PPI on ESG is more pronounced when CEO power is limited.

5.2.3 Board meetings

Effective knowledge transfer between foreign and native directors depends on frequent interaction, allowing native directors to absorb strategic insights and ESG practices, particularly from those with positive peace culture backgrounds. Board meetings serve as a key forum for such exchange. More frequent meetings foster ongoing dialog and collaboration (Vafeas, 1999), helping foreign directors understand firm-specific challenges and enabling native directors to grasp ESG risks, opportunities, and best practices (Hussain et al., 2018). Thus, we expect the PPI–ESG relationship to be stronger when board meetings are more frequent.

We re-estimate Model (1) using subsamples split by industry-median board meeting frequency. As shown in Table 6, Columns 5 and 6, PPI is positive and significant in the high-frequency subsample but insignificant in the low-frequency group. This suggests that frequent board meetings enhance the ability of foreign directors from positive peace cultures to influence ESG through social learning and advisory roles.

Using China as the empirical setting, this study finds that firms appointing foreign directors from positive peace cultures (i.e. those with higher average positive peace level on the board) exhibit stronger ESG performance. These directors contribute significantly to product quality, employee relations, and environmental protection—key channels driving overall ESG. The positive effect of foreign directors’ positive peace culture is more pronounced in firms facing low local government intervention, less powerful CEOs, and more frequent board meetings.

Given the close link between ESG and positive peace, our study highlights the value of examining foreign directors through the lens of positive peace culture. This offers clearer insights than prior studies that report mixed or negative effects of foreignness or cultural diversity on ESG—likely due to broad or ambiguous definitions. By focusing on positive peace, we isolate a specific cultural attribute that consistently supports effective ESG engagement.

Our findings position positive peace culture as a key driver of ESG, particularly relevant in emerging economies that leverage foreign talent to advance responsible business practices. Drawing on Social Learning Theory, we show that foreign directors shape the cognitive and behavioral dynamics of boards, promoting meaningful ESG adoption. To maximize this impact, firms should prioritize appointing foreign directors from positive peace cultures and ensure they are empowered—rather than symbolic—to drive change.

Finally, it is important to disentangle whether the documented effects are partially driven by firms’ exposure to positive peace conditions in their foreign operating and sales environments. Although our robustness analysis yields similar findings using a subsample of firms without foreign sales, data limitations prevent us from constructing and directly controlling for a foreign sales–weighted PPI measure. Accordingly, our results should be interpreted with caution. Future research leveraging more granular, country-level foreign sales data could develop a sales-weighted foreign PPI metric to provide a more precise assessment of firms’ international exposure to positive peace conditions.

Table A1

Variables definitions

Data source
Dependent variable in the main model
ESGNatural logarithm of Huazheng Environmental, Social, and Governance (ESG) composite scores
The Huazheng rating system uses a hierarchical aggregation system to compute the composite scores using over 80 fourth-tier performance indicators with over 300 underlying data points that supports 44 third-tier key issues and 16 second-tier themes across the E, S, and G dimensions (also known as the first-tier pillars). Each indicator is assigned a score of 0 (lowest) to 100 (highest) and multiplied by an industry-specific weight before being hierarchically aggregated into a score for each dimension. The final composite score is the weighted average score from the three dimensions
Huazheng (WIND database)
Test variable in the main model
PPIThe average of PPI_INV assigned to each director based on their nationality. PPI_INV is the raw positive peace overall score of a country each year multiplied by minus one. A higher PPI indicates higher average positive peace level on board. The raw positive peace overall score comprises eight pillars: free flow of information, sound business environment, equitable distribution of resources, high levels of human capital, good relations with neighbors, acceptance of the rights of others, well-functioning government, and low levels of corruptions (IEP, 2019)Directors’ nationality was manually collected from corporate annual reports and website
PPI was obtained from the IEP.
Control variables in the main model
DualityDichotomous variable equals 1 if the CEO serves as the Chairperson of the board of directors, and 0 otherwiseCSMAR
B_SizeNatural logarithm of the number of directors on boardCSMAR
B_FemaleProportion of female directors on boardCSMAR
B_IndProportion of the number of independent directors on boardCSMAR
Firm_SizeNatural logarithm of total assetsCSMAR
Firm_AgeNatural logarithm of the number of years since firm was listedCSMAR
ROANet income divided by total assetsCSMAR
LEVTotal debts divided by total assetsCSMAR
SlackFree cash flows scaled by total assetsCSMAR
ExchangeDichotomous variable equals 1 if the firm is listed on the Shenzhen Stock Exchange, and 0 if it is listed on the Shanghai stock exchangeCSMAR
ForeignForeign sales as a percentage of total salesCSMAR
SOEDichotomous variable equals 1 if firm is a state-owned entity, and 0 otherwiseCSMAR
Top1Shareholding ratio of the largest shareholderCSMAR
MediaNatural logarithm of the number of news articles about a focal firm in a given year plus 1CNRDS
Other variables used in tabulated additional and robustness analyses 
ProdQualityTotal strengths minus total concerns in the product quality categoryCNRDS
CommunityDevTotal strengths minus total concerns in the community development categoryCNRDS
DivPracTotal strengths minus total concerns in the diversity practices categoryCNRDS
CorpGovTotal strengths minus total concerns in the corporate governance categoryCNRDS
EmpRelationsTotal strengths minus total concerns in the employee relations categoryCNRDS
EnvProtectionTotal strengths minus total concerns in the environmental protection categoryCNRDS
GIThe annual Government and Market Relationship (GMR) Index is computed using three factors: (1) the ratio of provincial government revenue to its GDP; (2) the ratio of average time spent by a firm’s manager in dealing with government to their weekly average working hours; and (3) the ratio of government employees to provincial population (Wang et al., 2018a). GMR index is constructed in the way that a higher value captures a lower degree of government intervention in the local economy, hence we take the inverse value of GMR to proxy local government intervention (GI). Firms operating in a province with GI above (below) yearly median are assumed to subject to high (low) local government interventionWang et al. (2018a) 
CEO_PowerA CEO Power Index estimated based on the average value of the following eight variables that capture four CEO power dimensions (Wu et al., 2011)CSMAR, the Wind Economic (WIND) database
(i) CEO structural power proxied by two dichotomous variables equal 1, if the CEO also serves as the Chairperson or the CEO is an inside director, and 0 otherwise
(ii) CEO expert power proxied by two dichotomous variables equal 1, namely if the CEO has a professional certificate or the CEO tenure is longer than the median tenure of industry, and 0 otherwise
(iii) CEO ownership power proxied by two dichotomous variables equal 1, namely if the CEO has shareholdings of the firm or if the institutional shareholding of the focal firm is the below the industry median, and 0 otherwise
(iv) CEO prestige power proxied by two dichotomous variables equal 1, if the CEO holds at least a master’s degree or if the CEO has outside job opportunities (e.g. sitting on multiple boards)
Firms with above (below) industry median of CEO_Power are deemed to exhibit high (low) CEO power
B_MeetHigher versus lower board meeting frequency is determined by its industry-medianCSMAR
PolicyThe number of years since the foreign talent policy was adopted in the province in which the Chinese firms are headquarteredManual collection of the policy adoption years for each province from the official provincial government website
Predicted_PPIPredicted value of PPI obtained from the first stage of two-stage least squares regressionSee PPI
PPI_AltThe sum of the “relative PPI_INV differences” between foreign directors’ home countries and China, scaled by the number of directors. The “relative PPI_INV difference” is computed by subtracting the PPI_INV of foreign directors’ home countries from the PPI_INV of China, then divided by the PPI_INV of foreign directors’ home countries. A higher PPI_Alt indicates higher average positive peace level on boardSee PPI
ESG_Alt1Natural logarithm of the LSEG ESG rating scoreLSEG
ESG_Alt2Natural logarithm of the CNRDS ESG rating scoreCNRDS
PDIThe average of PDI assigned to each director based on their nationality. Power distance (PDI) reflects the degree of society’s acceptance about unequal power distributionHofstede’s official website
IDVThe average of IDV assigned to each director based on their nationality. IDV reflects the degree to which individuals prioritize own interests (i.e. individualism) as opposed to group interests (i.e. collectivism)Hofstede’s official website
MASThe average of MAS assigned to each director based on their nationality. MAS captures the degree to which a society is characterized with masculine values such as aggressiveness and competition for material outcomes, as opposed to feminine values such as modesty, equality and cooperationHofstede’s official website
UAIThe average of UAI assigned to each director based on their nationality. Uncertainty avoidance (UAI) reflects the extent to which a society resists uncertainty and ambiguityHofstede’s official website
B_Cultural_DiversityThe average of Hofstede cultural distance scores in all pairs of board directors for firm i calculated based on Frijns et al. (2016) and Luo et al. (2021). To calculate the cultural distance scores, each director is assigned with the four Hofstede’s cultural dimensions’ scores based on their nationality: (1) power distance; (2) individualism versus collectivism; (3) masculinity versus femininity; and (4) uncertainty avoidanceHofstede’s official website, Frijns et al. (2016), Luo et al. (2021) 
The following formula is used to estimate the distance for each cultural dimension between directors
CDTij = k=16[(IkiIkj)2/Vk]ij
where Iki is the score on cultural dimension k for a director i, and Ikj is the score on cultural dimension k for a director j. Vk is the in-sample variance of the specific cultural dimension score. CDTij captures the distance of specific cultural dimension between each two directors (i, j)
Firm-level board cultural diversity (B_Cultural_Diversity) is then measured with the average of cultural distances in all pairs of board directors using the following formula
B_Cultural_Diversitynt = i,jCDTij,ntm(m1)/2i<j
Where B_Cultural_Diversitynt reflects the board cultural diversity of firm n in year t, and m denotes the number of board members. CDT is scaled by the number of pairs of board members to normalize for the board size

1.

“E” dimension captures environmental performance including climate change, resource utilization, environmental pollution, green initiatives and environment management. “S” dimension assesses social responsibilities and captures performance in human capital development, product responsibility, social contribution/community development, supply chain management and data security and privacy. “G” dimension reflects performance in shareholders’ interest, governance structure and risk, information transparency, external punishments, and business ethics.

2.

For example, Firm A has fifteen Chinese directors, one director from the US and one director from Germany in 2017. In 2017, the raw PPI overall scores of China, the US and Germany are 3.21, 2.09, and 1.76, respectively. Their respective PPI_INV are: 3.21, −2.09, and −1.76. PPI for Firm A in 2017 is −3.06, calculated as: [(-3.21 *15) + (−2.09) + (−1.76)]/17.

3.

The 2024 ranking of PPI (from the lowest to highest raw PPI scores) for the following few countries in our sample are: Denmark [2], Sweden [4], Switzerland [5], China [67], Brazil [72], Saudi Arabia [76], Indonesia [81], and India [87]. This illustrates that our sample contains sufficient variations in directors’ PPI for examining our research question.

4.

We use CNRDS data as it provides “strengths” and “concerns” scores across six ESG dimensions similar to those by Bartov et al. (2021). Such dimensions data are not available from Huazheng.

The supplementary material for this article can be found online.

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