ESG Ratings and Financial Performance in the Global Hospitality Industry

Abstract

Existing research critically examines the influence of environmental, social, and governance (ESG) ratings on corporate financial performance (CFP), with outcomes varying considerably. This study employs a dataset of publicly traded firms across 16 countries within the hospitality sector from 2005 to 2022 to examine the ESG-CFP relationship. Fixed effects regression results demonstrate a positive linkage between ESG ratings and CFP, utilizing both comprehensive ESG ratings and discrete pillar ratings. These findings remain robust across various performance measures including return on assets, return on equity, and Tobin’s Q. Heteroscedasticity and endogeneity concerns are mitigated through generalized least squares and two-stage least squares methods, respectively. Moreover, the positive impact of ESG on CFP exhibits greater potency in the United States relative to other countries and was more pronounced during the COVID-19 era. These findings offer valuable insights for business executives, investors, and policymakers in supporting ESG initiatives, guiding investment decisions, and formulating effective policy directives.

1. Introduction

The United Nations-endorsed Principles for Responsible Investment pioneered the concept of environmental, social, and governance (ESG) to underscore the significance of sustainable investment.1 In recent years, many scholars and investors have shown interest in the correlation between a firm’s ESG and corporate financial performance (CFP). Concurrently, numerous governments have established regulations for corporate sustainability initiatives and mandate firms to enhance the transparency of ESG reporting (Taherdangkoo et al., 2017). Thus, companies are motivated to incorporate sustainable development strategies for an enduring advantage. However, ESG undertakings, such as procuring eco-friendly infrastructure, fostering an environment-friendly reputation, and implementing green programs, necessitate persistent financial backing, escalating the risk of financial constraints that negatively affect the company’s financial performance (Branco & Rodrigues, 2006). In this study, we investigate the relationship between ESG and CFP within the global hospitality sector to augment our comprehension of the economic repercussions of ESG.

We investigate the ESG effect utilizing a sample of companies in the hospitality sector for three key reasons. First, the hospitality sector is pivotal in stimulating local economic growth and enhancing employment prospects.2 Second, despite its considerable economic benefits, the hospitality sector has taken few initiatives to contribute significantly toward global sustainable development goals (Wu & Pearce, 2013). Third, the growth of the hospitality sector is inherently linked to social sustainability (Moscardo & Murphy, 2014). For instance, sub-sectors within hospitality are susceptible to accidental events and negative publicity, such as the gaming and entertainment industries, potentially engendering an adverse societal impact that impairs corporate reputation and long-term performance. Consequently, social responsibility is vital, yet it receives insufficient attention within the hospitality sector. In this study, we scrutinize the relationship between ESG and CFP to enhance our comprehension of a firm’s sustainable development and underscore the role of ESG in societal advancement and economic growth.

Myriad studies probe the association between ESG and CFP, yet they yield diverse outcomes, encompassing positive, negative, non-linear, U-shaped, and seemingly negligible correlations (Brammer et al., 2006; Ersoy et al., 2022; Fatemi et al., 2015; Crisóstomo et al., 2011). Additionally, firms’ ESG initiatives vary with industry characteristics (S. Lee et al., 2013; Casado-Díaz et al., 2014; Ionescu et al., 2019). Thus, insights from ESG research in other industries might not directly apply to the hospitality sector. Considering the vast array of businesses subsumed within hospitality, it is essential to examine ESG influences in this industry, mitigating the effect of sectoral discrepancies and promoting the comprehension of ESG functions in this specific industry (McIntosh et al., 1995). Additionally, environmental, social, and governance activities constitute three independent pillars of ESG efforts. Utilizing a single composite ESG rating might not fully capture a firm’s pursuits toward sustainable development (Alareeni & Hamdan, 2020). Limited studies address ESG implications using individual ESG pillars in the hospitality industry. In this study, we examine the relationship between ESG and CFP using the composite ESG rating and the three ESG pillars to enhance our understanding of the ESG effect. Moreover, we perform an extensive examination to ascertain if the impact of ESG on CFP in the hospitality industry diverges across countries and between pre- and post-COVID periods (Eccles et al., 2014; Keceli & Cankaya, 2020; Siueia et al., 2019; Nicola et al., 2020; Sigala, 2020).

Using a sample comprising publicly traded hospitality firms across 16 countries, we employ fixed effects ordinary least squares (OLS) regression methodologies to scrutinize the correlation between ESG and CFP. Our findings reveal that the composite ESG rating exerts a substantial positive influence on CFP, mirroring the impact of the individual ESG pillars. Interestingly, the correlation between ESG and CFP intensifies in the United States relative to other nations and is amplified during the COVID-19 pandemic. Within the scope of this research, we gauge corporate performance from a tripartite perspective, using market performance, as denoted by Tobin’s Q, and accounting performance, as signified by return on asset (ROA) and return on equity (ROE). The main results persist when applying generalized least squares (GLS) and two-stage least squares (2SLS) regression methodologies.

The study contributes to the literature in several different ways. Firstly, this research enriches the ESG scholarship by presenting empirical insights regarding the relation between ESG activities and CFP within the global hospitality sector, where ESG is integral to enduring corporate growth yet is often neglected (S. Lee et al., 2013). Our analysis bears implications for hospitality industry leaders making ESG investment determinations. Secondly, most investigations evaluate ESG effects utilizing the composite ESG score, overlooking the distinct influence of ESG pillar components (Abdi et al., 2022; Taherdangkoo et al., 2017). We secure individual ratings for each ESG pillar and independently examine their relationships with CFP. Thirdly, we accentuate the nation-specific disparities in the correlation between ESG and CFP, emphasizing that regional factors may have significant implications when examining ESG influences. Fourthly, we elucidate the moderating role of the COVID-19 pandemic in the ESG-CFP relationship, emphasizing the significance of global health crises.

The arrangement of this study is as follows: Section 2 discusses pertinent theories that support the ESG-CFP relationship. Section 3 encompasses a literature review and the formulation of research hypotheses. Section 4 offers a detailed description of the sample, the variables, and the research methodology. Empirical findings are presented and analyzed in Section 5. Finally, Section 6 concludes the study.

2. Theoretical Framework

2.1. Signaling Theory

ESG activities are frequently viewed as signals through which firms convey information about their values, qualities, and efforts to consumers, investors, and other related parties. Signaling theory effectively explains behavior when two parties (individuals or organizations) possess unequal access to information. The sender must decide whether and how to communicate the information, while the receiver must determine how to interpret the signal. At its core, signaling theory aims to mitigate information asymmetry between the parties (Connelly et al., 2011).

In recent decades, corporate brands have heavily invested in sustainability to enhance their reputations, responding to increasing expectations for such practices (Torelli et al., 2012). In the digital age, brand value creation appears to have shifted toward information sharing and signaling among firms, consumers, and independent entities such as online reviewers and social media influencers (M. T. Lee et al., 2022). As a result, the content and manner of firms’ signals in this interconnected environment significantly influence brand valuation.

The 2015 Nielsen Global Corporate Sustainability Report highlights that nearly 66% of consumers worldwide are willing to pay a premium for products from sustainable brands.3 Moreover, over 80% of millennials expect their favorite companies to make public commitments to good corporate citizenship. Similarly, Cowan and Guzman (2020) find that positive sustainability signals from corporate brands correlate with higher sales growth—both domestically and internationally—and greater brand equity. Conversely, Sen and Bhattacharya (2001) show that consumers may undervalue sustainability efforts, suggesting that such initiatives can increase costs without yielding the anticipated benefits. While most evidence supports the view that ESG initiatives signal positively to consumers and investors, there are instances where misalignment between consumer values and ESG efforts may result in unintended negative perceptions.

2.2. Legitimacy Theory

Suchman (1995) defines legitimacy as “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions”. A business organization must justify its existence through legitimate economic and social actions that contribute to both the society in which it operates and the broader environment (Burlea & Popa, 2013).

In the Spanish context, Reverte (2009) identified that the key variables explaining firms’ corporate social responsibility (CSR) ratings are media exposure, firm size, and industry, particularly those in environmentally sensitive sectors. These variables are linked to public or social visibility, suggesting that legitimacy theory is the most pertinent framework for understanding CSR disclosure practices of publicly listed Spanish firms. Similarly, in Bangladesh, Khan et al. (2013) demonstrate that firms with higher foreign ownership tend to report more CSR disclosures as a legitimacy strategy to address the concerns of ethical foreign investors.

In summary, legitimacy theory asserts that firms undertake CSR or ESG activities to preserve their social license to operate and validate their existence within the framework of societal norms and values. Such actions can enhance their public image, improve investor perception, and mitigate potential regulatory or societal risks. By aligning their practices with societal expectations, legitimacy theory forecasts a positive ESG-CFP relationship, provided the firm successfully demonstrates its legitimacy through effective ESG initiatives.

2.3. Stakeholder Theory

The concept of CSR—the idea that businesses must assume responsibility to society and a broader range of stakeholders beyond shareholders—gained wider acceptance in the 1960s (H. Wang et al., 2016). In response, economist Milton Friedman introduced the Friedman doctrine in 1970, arguing that a company holds no social responsibility to society, with its sole obligation being to its shareholders (Friedman, 2007). However, CSR gained further prominence in the 1980s following the rise in stakeholder theory, introduced by Edward Freeman in 1984, where he defined a stakeholder as “any group or individual who can affect or is affected by the achievement of the firm’s objectives” (Freeman, 2010). According to this theory, firms must consider not only their owners and customers, but also employees, the local community, the environment, consumer advocates, special interest groups, and other relevant parties.

H. Wang et al. (2016) show that companies that actively engage with stakeholders tend to display superior social performance and higher CSR standards, contributing to long-term sustainable growth. However, a limitation arises as companies face resource constraints, leading to potential conflicts of interest among stakeholder groups competing for financial resources and managerial attention. The challenge for many corporations is determining how managers should prioritize the needs of diverse stakeholders (H. Wang et al., 2016).

3. Literature Review and Hypothesis Development

3.1. ESG Practices in the Hospitality Industry

Simultaneously fostering the local economy, expanding the hospitality sector might impose adverse environmental implications. Take hotels as an example; typically situated near heritage locations, they draw in large volumes of tourists, thus escalating the environmental detriment triggered by human interaction (Kirk, 1998; Legrand, 2021). Even though stakeholders across diverse sectors emphasize sustainability and voice the necessity for global attainment, the practical application of sustainability approaches, in reality, continues to be daunting (Higgins-Desbiolles, 2010). Research delving into ESG protocols within the hospitality industry primarily targets developed nations or conducts assessments with a minimal sample of fewer than 20 firms, culminating in an informational deficit regarding the ESG impact in the hospitality sector (Carlsen et al., 2001; Kasim, 2007; Holcomb et al., 2007; Scanlon, 2007; Bohdanowicz & Zientara, 2008).

Nonetheless, sustainability is a crucial factor in facilitating the advancement of the hospitality industry. Firstly, due to the resource-intensive nature of the hospitality sector (Gil et al., 2001), it is imperative to establish sustainable management systems for coping with the constraints of worldwide resource paucity (J. Lu & Nepal, 2009). Sustainability crises undermine the prospects of hospitality firms and their clientele, as climate change renders numerous global destinations less appealing. In more severe cases, rising sea levels threaten to inundate hospitality industry properties (Legrand & Matthew-Bolofinde, 2022). Secondly, consumers’ burgeoning focus on sustainability is reflected in their willingness to financially support corporate initiatives to bolster energy efficiency and environmental conservation (Laroche et al., 2001; Rivera, 2002). The hospitality industry relies heavily on both natural resources and human capital. Consequently, integrating ESG practices is essential not only for implementing effective food waste management systems and preserving clean water but also for ensuring the fair treatment of employees and fostering community engagement (Back, 2024). As such, exploring the implementation of sustainability strategies within the hospitality industry will contribute to the expanding body of the literature on the ESG effect.

3.2. ESG Ratings and Firm Performance

Assessing ESG impact proves challenging.4 Existing inquiries into the ESG-CFP interconnection yield inconclusive outcomes. According to the conventional neoclassical perspective, the investment expenditure required for corporations to undertake ESG initiatives supersedes the returns accruing to the corporation (Palmer et al., 1995). Moreover, firms committed to ESG norms persistently generate non-positive returns to shareholders (Lyon et al., 2013). L. Wang et al. (2024) demonstrate that ESG ratings have a significant and negative impact on the stock performance of publicly listed Chinese firms. Baklaci et al. (2024) demonstrate that ESG exchange-traded funds underperform conventional exchange-traded funds in many aspects. Conversely, recent research illustrates that the ramifications of ESG adoption vary among corporations across distinct industries (Elzahar et al., 2015; Moon, 2007). ESG adherence in some sectors exhibits a neutral effect, suggesting corporations equilibrate the cost of ESG against the financial return they generate (Lahouel et al., 2019).

Contrarily, stakeholder theory substantiates a positive association between ESG activities and CFP (Ionescu et al., 2019). The returns from ESG investments can surpass the associated costs, resulting in a favorable ESG influence on CFP (Aouadi & Marsat, 2018). This can be attributed to various factors. Firstly, a superior ESG rating corresponds to reduced financial risk, positively impacting investors’ propensity to invest in the enterprise (Benlemlih & Girerd-Potin, 2017; Jo & Na, 2012). Nguyen et al. (2022) find that among financial performance metrics such as ROA, ROE, and Tobin’s Q, the latter is most positively influenced by ESG activities, highlighting investors’ growing interest in firms actively engaging in ESG initiatives. Secondly, corporations’ ESG endeavors enhance employees’ job satisfaction, improving their operational and financial performance (Edmans, 2011). Thirdly, the economic advantage of ESG activities becomes more conspicuous when a company embraces a long-term investment approach as opposed to a short-term strategy (Statman & Glushkov, 2009), since the ESG effort is more prone to bolster corporate competitiveness, curtail business risks, and augment financial profitability over a more extended period (Moravcikova et al., 2015). Fourthly, firms may be subject to higher debt and equity financing costs if they lack social responsibility, escalating the likelihood of financial constraints (El Ghoul et al., 2011; Goss & Roberts, 2011). Fifthly, ESG activities can augment the firm’s societal reputation and elevate customer loyalty, fostering customer repurchase behavior (Pérez & del Bosque, 2015) and reducing price sensitivity by narrowing the perceived quality gap between firms (Boehe & Cruz, 2010).

Pursuing a different trajectory, the implications of each ESG pillar on CFP remain ambiguous. The first ESG pillar is the environment. Consumers demonstrate sensitivity to environmental disclosure information (Jacobs et al., 2010). Specific research indicates that a corporation’s disclosure of environmental initiatives has a positive bearing on CFP, implying that the adoption of eco-friendly policies can foster corporate growth (Emeka-Nwokeji & Osisioma, 2019; Murray et al., 2006; Saleh et al., 2011). Nevertheless, some academics argue that the environmental impact across diverse organizations is not universally applicable (Elsayed & Paton, 2005). Initiatives like becoming a climate leader may not resonate with market interest and might trigger negative financial consequences for the company (Fisher-Vanden & Thorburn, 2011). Moreover, firms might commit to environmental projects to fulfill obligatory governmental stipulations at the expense of shareholders, engendering negative financial implications (Reid & Toffel, 2009). Besides the potential positive and negative effects, a neutral correlation between environmental actions and CFP could be attributed to the firms experiencing audit threats, compelling them to make environmental disclosures (Nakao et al., 2007; Lyon & Maxwell, 2011).

The second ESG pillar pertains to the social dimension. Escalated expenditure on social initiatives aids in preserving and cultivating stakeholder relationships, diminishes the company’s operational costs, and enhances CFP (Fombrun et al., 2000). Moreover, nurturing strong stakeholder relationships may confer intangible value on a corporation (Hillman & Keim, 2001). Liu et al. (2024) find that employee stock ownership plans positively influence corporate ESG ratings in a sample of 4464 publicly listed Chinese firms. Nevertheless, some studies also negatively correlate social initiatives and CFP (Emeka-Nwokeji & Osisioma, 2019). Given the diverse industries in which companies operate, a negative linkage might exist between social initiatives and CFP (Brammer et al., 2006; Fisher-Vanden & Thorburn, 2011). Other research implies that social endeavors and CFP could be neutrally connected (Patten, 1991).

The third ESG pillar refers to corporate governance. Numerous studies exhibit a positive correlation between corporate governance and CFP (Brown & Caylor, 2006; Emeka-Nwokeji & Osisioma, 2019; Xie et al., 2019). Superior governance can preempt financial crises (Nollet et al., 2016). Furthermore, an elevated governance pillar score signifies reduced information asymmetry, thereby ensuring optimal benefits for the stakeholders (Patten, 1991). Shaikh (2022) also finds that among the three ESG pillars, governance exerts the strongest positive impact on financial performance.

Despite the heterogeneous outcomes of ESG effects in the previous literature, we postulate that corporations in the hospitality sector are more inclined to exhibit a positive ESG-CFP relationship due to the significant emphasis on sustainable development within this industry. Indeed, Bianco et al. (2023) demonstrate that ESG certifications can enable a hotel to achieve higher occupancy rates and increased revenue per available room, particularly when it is the first in its local area to obtain such a certification. Moreover, ESG dimensions are three independent aspects jointly capturing the company’s performance of sustainability (Galbreath, 2013). Evaluating ESG performance using individual dimension ratings can furnish supplementary information beyond what is provided by employing a singular composite ESG rating as a measure (Ionescu et al., 2019; McWilliams et al., 1999). Consequently, it is imperative to scrutinize the ESG effects utilizing both composite and disaggregated dimension ratings. Based on the discussions above, we derive the following hypothesis:

Hypothesis 1.

ESG ratings are positively related to CFP in the hospitality industry.

3.3. Role of Regional Factors in the ESG-CFP Relationship

Existing research suggests that merely scrutinizing the effect of ESG on CFP is insufficient; additional variables are in play and geographic factors warrant further exploration (S. Lee et al., 2013). First, historical evidence suggests that in the US, ESG disclosures are positively correlated with improved CFP (Eccles et al., 2014). In contrast, the performance of companies from other countries does not uniformly inspire optimism. Notably, for Europe and Latin America, there is no discernible correlation between ESG disclosure and CFP (Keceli & Cankaya, 2020). Conversely, sub-Saharan country samples illustrate a positive association between ESG disclosure and CFP (Siueia et al., 2019). In Australia, however, the relationship between ESG disclosure and CFP emerges only in the context of high performance (Gholami et al., 2022). Similarly, in China, the positive relationship between ESG and financial performance is observed specifically among Growth Enterprise Market companies, smaller firms with growth potential that do not meet the full listing requirements of the main board of the Hong Kong exchange (Zheng et al., 2022).

Second, the United States ranks among the highest globally in individualism and also scores significantly high on masculinity, according to Hofstede’s cultural dimensions.5 Shin et al. (2023) find that cultures characterized by high individualism or masculinity amplify the relationship between ESG and financial performance. The rationale is that in highly individualistic societies, ESG practices are less ingrained and thus must provide stronger financial incentives. Similarly, in societies with higher masculinity, ESG efforts are financially incentivized, whereas more feminine societies may view ESG as a firm’s social obligation, offering fewer financial rewards for such practices.

Third, compared to other nations, US firms focus more on regional diversification and strategize regional operations to cater to local market requirements, thereby capturing further market opportunities and augmenting profits (J. W. Lu & Beamish, 2004; Koh et al., 2009). Achieving regional diversification necessitates a company to acknowledge the variegated needs of stakeholders across political, economic, and cultural spheres, among others (Abrahamson & Fombrun, 1994). Furthermore, firms employing regional diversification strategies must accommodate an expanded spectrum of societal demands and diverse pressures (Sharfman et al., 2004). Moreover, research indicates that a firm’s ESG activities are intimately tied to stakeholder needs, and regional diversification bolsters firms in fulfilling their ESG obligations (Brammer et al., 2006). Hence, this study incorporates regional disparities to delve deeper into the influence of varying national contexts on ESG disclosure and CFP. Based on the discussions above, we derive the following hypothesis:

Hypothesis 2.

The positive ESG effect on CFP is more pronounced in the United States compared to other countries.

3.4. Impact of COVID-19 on the ESG-CFP Relationship

The COVID-19 pandemic has precipitated a significant upheaval in the global hospitality industry (Bai, 2020). Policy reactions to COVID-19 have constrained global hospitality operations by curtailing social activities and travel plans (Sigala, 2020). Past research confirms the substantial effects of non-financial events on equity markets; for instance, Taiwanese hotel industry stocks experienced a notable downturn in the month following the SARS outbreak (M. H. Chen et al., 2005). More recently, many scholars have delineated and explicated the devastating impact of COVID-19 on global economics and finance (Rehman et al., 2021; Arbulú et al., 2021). The deleterious effect of the pandemic on equity markets surpasses the damage wrought by economic crises (Baker et al., 2020). Liu et al. (2023) ascertain that equities in the hospitality sector undergo significant volatility following the dissemination of COVID-19 announcements. C. D. Chen et al. (2022) demonstrate that during the COVID-19 pandemic, hotel corporation stocks with higher ESG ratings acted as more defensive assets, offering investors a safe haven amid market turbulence. Consequently, in analyzing the ESG-CFP relationship, the pandemic’s influence cannot be overlooked. These preceding discussions provide the foundation for the following hypothesis:

Hypothesis 3.

The positive influence of ESG on CFP is more discernible during the COVID-19 pandemic than in prior periods.

4. Data and Methodology

4.1. Data

Data on the ESG of the hospitality industry were collected from the Bloomberg Terminal. Using the Bloomberg ESG Classification System (BECS), we selected all 89 international hospitality companies within the “Leisure Facilities & Services” category, encompassing “Hotels”, “Recreational Facilities”, and “Restaurants”. We also acquired datasets regarding ROA, ROE, and Tobin’s Q as dependent variables, alongside ESG and individual pillar scores as primary explanatory variables. Control variables encompass firm size, firm age, leverage, capital expenditure, the market-to-book ratio, dividend payout ratio, board size, the proportion of independent directors, CEO age, CEO tenure, and the dual role of the CEO and chairman. Any missing datasets, such as the dividend payout ratio, were manually supplemented by sourcing the information from the respective company’s website or annual report. The annual GDP growth data, sourced from the World Bank, represent the annual percentage change in GDP at market prices, adjusted to constant 2015 US dollars.6 The dataset represents all publicly listed hospitality firms globally for which Bloomberg provides comprehensive ESG and financial data. The sample begins in 2005 because this is the earliest year for which Bloomberg provides ESG data for the hospitality sector. However, it is important to note that ESG disclosures vary significantly across countries, and many firms—particularly in emerging markets—only began reporting ESG metrics in recent years.

Our sample spans 2005 to 2022, a period marked by substantial advancements in ESG reporting and evolving trends in the hospitality sector. In 2015, the Task Force on Climate-Related Financial Disclosures was established to develop recommendations for corporate disclosures, enabling investors and lenders to better assess climate-related risks.7 These guidelines achieved widespread global adoption. During this period, many countries also introduced mandatory ESG disclosure requirements for publicly listed firms.8 In the hospitality sector, technological innovations and sustainability concerns drove significant transformations. The most notable disruption was Airbnb’s 2008 entry, introducing home-sharing and short-term rentals, which exerted pressure on the revenues and profits of traditional hotel companies.9 Simultaneously, hospitality providers intensified sustainability efforts, including energy-efficient designs, renewable energy adoption, water conservation, and waste reduction initiatives.10

We also executed winsorization on all variables at the 1st and 99th percentiles. The final sample incorporates 1110 firm-year observations spanning 2005 to 2022, indicative of 86 distinct firms.

Table 1. Sample composition.

Country	Observations	%
Australia	33	2.97
Canada	24	2.16
China	54	4.86
United Kingdom	156	14.05
France	41	3.69
Germany	29	2.61
Hong Kong	51	4.59
India	30	2.70
Italy	18	1.62
Japan	42	3.78
Korea	8	0.72
Mexico	13	1.17
Philippines	11	0.99
Spain	32	2.88
Thailand	26	2.34
United States	542	48.83
Total	1110	100.00

Note: This table presents the compositional distributions of the entire sample, encompassing publicly listed global hospitality firms from 2005 to 2022.

delineates the sample composition across 16 countries, with the United States constituting the most extensive sample and accounting for 48.83% of total observations. The geographic distribution of the sample reflects the structure of the global hospitality industry, the concentration of publicly listed firms in specific regions such as the United States, and the fact that not all hospitality firms are publicly listed, particularly in emerging countries. Countries with fewer publicly listed firms, such as Korea and Mexico, naturally appear underrepresented. Although some countries are over- or underrepresented, we address potential geographic biases by employing country-level fixed effects in the regression models, which account for unobserved heterogeneity across countries.

4.2. Variables

Our dependent variable is CFP, which is represented by ROA, ROE, and Tobin’s Q. Dao and Ta’s (2020) meta-analysis on firm performance divides proxies for such performance into two principal categories, namely accounting-based measures such as ROA and ROE and a market-based ratio such as Tobin’s Q. Of the 245 studies, those deploying accounting indicators (ROA, ROE) comprise roughly 73.1% in contrast to 26.9% incorporating the market ratio (Tobin’s Q). An extensive body of the literature, encompassing Aouadi and Marsat (2018) and S. Lee et al.’s (2013) work, posits that Tobin’s Q also signals CFP. In alignment with the extant literature, we define Tobin’s Q as the ratio of a firm’s total market value to its book value of assets (Chung & Pruitt, 1994).

Our primary explanatory variables are the ESG score and individual ESG pillar scores. Bloomberg ESG ratings have been recognized as reliable sources for academic research (Abdi et al., 2022; Egorova et al., 2022). Leveraging public ESG data, Bloomberg assesses companies’ composite ESG scores on a scale from zero to a hundred. The environmental rating quantifies the impact of corporate operations on the environment, covering factors such as greenhouse gas and carbon dioxide emissions, energy and water consumption, pollutant levels, and additional ecological concerns. The social rating mirrors business–community interactions with elements like the proportion of female staff, community investment, accident rates, supplier management, output per employee, and research and development outlays. The governance rating includes various factors, such as board composition, the ratio of female directors, director autonomy, the average director age, board meeting frequency, and the engagement levels of independent and non-independent directors. A composite score, which amalgamates factors from all three ESG dimensions, measures overall ESG performance.

We incorporate temporally sensitive firm characteristics pertinent to the ESG-CFP relationship into our control variables (Li et al., 2018; D’Amato & Falivena, 2020; Abdi et al., 2022; Shakil, 2022). The regression model integrates firm-level control variables, encompassing firm size (FirmSize), firm age (FirmAge), the leverage ratio (Lev), capital expenditure (Capex), the market-to-book ratio (MTB), and dividend payout ratio (DivPay). It also subsumes board-level control variables such as board size (BoardSize) and the proportion of independent directors (IndeptDir). The regression schema incorporates executive-level control variables, comprising the CEO’s age (CEOAge), the CEO’s tenure (CEOTenure), and the dual role of the CEO and chairman (Duality). Following D’Amato and Falivena (2020), we utilize the firm’s age as a control variable. Numerous studies utilize the leverage and dividend payout ratios as control variables (Shakil, 2022; Li et al., 2018). A lower leverage ratio indicates reduced insolvency risk and lesser financial stress to pursue social responsibilities. The dividend payout ratio provides insights into the company’s worth (Gordon, 1959). Investors can infer a company’s expansion aspirations based on its dividend payout ratio. The GDP growth rate (GDPGrow) is also included as a control variable, as it accounts for country-level economic variations that may impact financial performance. Additionally, we consider country and year fixed effects (FEs) to regulate for time-constant attributes inherent in each nation and a specific annum. All variables are defined in

Table 2. Variable definitions.

Variable	Definition
ROA	Return on assets. The firm’s net income divided by its total assets.
ROE	Return on equity. The firm’s net income divided by its shareholders’ equity.
TobinQ	Tobin’s Q. The firm’s total market value divided by its book value of assets.
ESG	The firm’s aggregate rating score encompassing environmental, social, and governance aspects.
E	The firm’s rating score pertaining to the environmental pillar.
S	The firm’s rating score pertaining to the social pillar.
G	The firm’s rating score pertaining to the governance pillar.
FirmSize	Firm size. The natural logarithm of the firm’s total assets.
FirmAge	Firm age. The years elapsed since the firm’s inception.
Lev	Leverage ratio. The firm’s total liabilities divided by its total assets.
Capex	Capital expenditure. The outlays made by the firm on the acquisition, upkeep, or augmentation of assets relative to its aggregate assets.
MTB	Market-to-book ratio. The firm’s total market value of equity divided by its book value of equity.
DivPay	Dividend payout ratio. The firm’s dividend payments divided by its net income.
BoardSize	Board size. The number of directors comprising the firm’s board of directors.
IndeptDir	Percentage of independent directors. The proportion of independent directors in service on the firm’s board of directors.
CEOAge	CEO’s age in years.
CEOTenure	CEO’s tenure. The duration for which an individual assumes the role of the company’s CEO.
Duality	The circumstance in which an individual concurrently assumes the roles of CEO and board chairman within the firm.
GDPGrow	Annual percentage change in GDP at market prices, adjusted for constant 2015 US dollars.

.

4.3. Methodology

We employ the following fixed effects OLS regression model to investigate whether ESG ratings are positively related to companies’ financial performance:

$$\begin{array}{ll}Per{f}_{it}=& {\beta }_0+{\beta }_{1}ES{G}_{it}+{\beta }_{2}FirmSiz{e}_{it}+{\beta }_{3}FirmAg{e}_{it}+{\beta }_{4}Le{v}_{it}+{\beta }_{5}Cape{x}_{it}+{\beta }_{6}MT{B}_{it}\\ & +{\beta }_{7}DivPa{y}_{it}+{\beta }_{8}BoardSiz{e}_{it}+{\beta }_{9}IndeptDi{r}_{it}+{\beta }_{10}CEOAg{e}_{it}+{\beta }_{11}CEOTenur{e}_{it}\\ & +{\beta }_{12}Dualit{y}_{it}+{\beta }_{13}GDPGro{w}_{it}+\mathrm{Country}\mathrm{FE}+\mathrm{Year}\mathrm{FE}+{\epsilon }_{it}\end{array}$$

(1)

where Perf_it is the CFP of firm i in year t, proxied by ROA, ROE, and Tobin’s Q. ESG_it is the composite ESG rating of firm i in year t. All other control variables are defined in Table 2.

We also use three ESG pillar ratings to measure their impact on CFP as follows:

$$\begin{array}{ll}Per{f}_{it}=& {\beta }_0+{\beta }_{1}ESGPilla{r}_{it}+{\beta }_{2}FirmSiz{e}_{it}+{\beta }_{3}FirmAg{e}_{it}+{\beta }_{4}Le{v}_{it}+{\beta }_{5}Cape{x}_{it}+{\beta }_{6}MT{B}_{it}\\ & +{\beta }_{7}DivPa{y}_{it}+{\beta }_{8}BoardSiz{e}_{it}+{\beta }_{9}IndeptDi{r}_{it}+{\beta }_{10}CEOAg{e}_{it}+{\beta }_{11}CEOTenur{e}_{it}\\ & +{\beta }_{12}Dualit{y}_{it}+{\beta }_{13}GDPGro{w}_{it}+\mathrm{Country}\mathrm{FE}+\mathrm{Year}\mathrm{FE}+{\epsilon }_{it}\end{array}$$

(2)

where ESGPillar represents the firm’s environmental (E), social (S), and governance (G) pillar ratings, respectively.

4.4. Descriptive Statistics

Table 3. Descriptive statistics.

Variable	Obs.	Mean	Std. Dev.	Min	P25	Median	P75	Max
ROA	1110	5.36	9.12	−97.00	1.53	4.62	9.27	50.00
ROE	1110	29.04	82.85	−204.42	5.34	14.80	29.30	654.00
TobinQ	1110	2.66	2.34	0.59	1.39	1.84	3.08	22.95
ESG	1110	36.39	10.33	6.86	29.80	34.51	43.40	73.20
E	1110	1.53	2.00	0.00	0.00	0.73	2.24	8.38
S	1110	1.92	1.50	0.00	1.25	1.40	2.17	8.47
G	1110	6.19	1.36	2.15	5.36	6.50	7.31	8.41
FirmSize	1110	3.39	0.55	1.64	3.06	3.42	3.78	5.10
FirmAge	1110	44.61	40.97	1.00	24.00	36.00	54.00	299.00
Lev	1110	44.82	43.88	0.00	22.27	37.18	55.28	389.20
Capex	1110	−0.06	0.06	−0.36	−0.08	−0.05	−0.03	−0.00
MTB	1110	17.89	65.47	0.11	1.99	3.70	7.45	552.00
DivPay	1110	63.10	266.03	0.00	0.00	34.50	60.50	8055.42
BoardSize	1110	9.59	2.58	2.00	8.00	9.00	11.00	20.00
IndeptDir	1110	62.24	22.24	0.00	44.40	66.70	81.80	100.00
CEOAge	1110	55.71	7.47	34.00	50.00	55.00	60.00	86.00
CEOTenure	1110	9.04	8.86	0.00	2.17	6.42	12.80	44.30
Duality	1110	0.23	0.42	0.00	0.00	0.00	0.00	1.00
GDPGrow	1110	2.16	3.09	−10.94	1.56	2.46	2.95	14.23

Note: This table delineates summary statistics for all variables. Table 2 furnishes the definitions of the variables.

portrays the summary statistics for all variables within the regression schemas. The ROA’s mean stands at 5.36%, indicating that corporations in the sector demonstrate potent profitability and exhibit a high capability to transmute their assets into earnings. Tobin’s Q presents a mean of 2.66, ranging from 0.59 to 22.95. Among the triadic dimension ratings of ESG, the governance rating exhibits the peak average value, intimating that hospitality sector corporations invest more effort into corporate governance than environmental and societal endeavors. The logarithm of firm size spans from 1.64 to 5.10, signifying considerable variation in size among hospitality industry corporations. The average leverage ratio is 44.82%, implying a middling debt proportion in the hospitality sector. The mean board size approximates ten directors, and the proportion of independent directors roughly equates to 62.24%. The average CEO’s age is 55.71 years. Approximately 23% of the corporations host a CEO who simultaneously functions as the board’s chairman.

We present the correlation matrix in

Table 4. Pearson correlation analysis.

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)	(17)	(18)	(19)
(1)	ROA	1
(2)	ROE	0.43 ***	1
(3)	TobinQ	0.50 ***	0.19 ***	1
(4)	ESG	−0.02	0.04	−0.03	1
(5)	E	−0.05 *	−0.04	−0.10 ***	0.54 ***	1
(6)	S	−0.06 *	0.03	−0.11 ***	0.61 ***	0.70 ***	1
(7)	G	0.20 ***	0.26 ***	0.05	0.31 ***	−0.16 ***	0.00	1
(8)	FirmSize	−0.17 ***	−0.16 ***	−0.33 ***	0.48 ***	0.32 ***	0.36 ***	0.05	1
(9)	FirmAge	0.02	0.05 *	−0.11 ***	0.24 ***	0.12 ***	0.09 ***	0.18 ***	0.21 ***	1
(10)	Lev	0.22 ***	0.17 ***	0.43 ***	0.22 ***	0.04	0.06 **	0.22 ***	0.02	0.26 ***	1
(11)	Capex	−0.17 ***	0.01	−0.21 ***	0.25 ***	0.12 ***	0.27 ***	0.09 ***	0.36 ***	−0.04	0.14 ***	1
(12)	MTB	0.12 ***	0.68 ***	0.11 ***	0.05 *	−0.03	0.00	0.19 ***	−0.14 ***	0.04	0.17 ***	0.06 **	1
(13)	DivPay	−0.03	−0.01	0.04	0.04	−0.02	−0.03	0.07 **	0.01	0.01	0.04	0.02	0.01	1
(14)	BoardSize	−0.10 ***	−0.00	−0.15 ***	0.26 ***	0.26 ***	0.14 ***	−0.04	0.42 ***	0.17 ***	0.02	−0.11 ***	−0.02	0.02	1
(15)	IndeptDir	0.17 ***	0.18 ***	0.14 ***	0.22 ***	−0.11 ***	0.00	0.66 ***	0.01	0.01	0.26 ***	0.04	0.14 ***	0.06 **	−0.06 *	1
(16)	CEOAge	−0.04	0.01	−0.13 ***	0.14 ***	0.17 ***	0.14 ***	0.02	0.15 ***	0.09 ***	−0.07 **	0.12 ***	0.03	0.02	0.05 *	−0.03	1
(17)	CEOTenure	0.14 ***	−0.04	0.12 ***	0.04	0.20 ***	0.15 ***	−0.21 ***	−0.05	−0.04	0.01	−0.04	−0.11 ***	0.04	−0.02	−0.13 ***	0.13 ***	1
(18)	Duality	0.05	−0.05 *	0.06 *	−0.10 ***	0.08 ***	0.01	−0.12 ***	−0.02	−0.10 ***	−0.10 ***	−0.11 ***	−0.03	0.05	−0.12 ***	0.02	0.23 ***	0.22 ***	1
(19)	GDPGrow	0.16 ***	0.04	0.12 ***	−0.15 ***	−0.10 ***	−0.14 ***	−0.11 ***	−0.16 ***	−0.08 ***	−0.05	−0.07 **	0.00	−0.02	−0.08 ***	−0.03	−0.09 ***	0.05 *	−0.02	1

Note: This table exhibits the Pearson correlations among the variables. Table 2 furnishes the definitions of the variables. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

before performing the regression analyses. Though ESG does not demonstrate direct correlations with corporate performance, the individual ESG pillars reveal substantial negative or positive correlations. As anticipated, ROA, ROE, and Tobin’s Q are positively correlated. ESG and the three pillars are also positively intertwined. Most control variables significantly correlate with ROA, except firm age, the dividend payout ratio, the CEO’s age, and duality.

To ensure the robustness of our regression models, we performed a variance inflation factor (VIF) analysis to identify potential multicollinearity among the independent variables. The VIF results for all four baseline regressions are presented in

Table 5. Multicollinearity tests.

Variable	VIF Values
	(1)	(2)	(3)	(4)
ESG	1.54
E		1.24
S			1.24
G				2.03
FirmSize	1.93	1.76	1.80	1.70
FirmAge	1.21	1.20	1.19	1.24
Lev	1.26	1.25	1.24	1.24
Capex	1.42	1.41	1.44	1.41
MTB	1.11	1.10	1.10	1.11
DivPay	1.01	1.01	1.01	1.01
BoardSize	1.41	1.43	1.40	1.40
IndeptDir	1.18	1.14	1.12	1.94
CEOAge	1.15	1.15	1.14	1.14
CEOTenure	1.13	1.15	1.15	1.13
Duality	1.20	1.19	1.18	1.21
GDPGrow	1.04	1.04	1.05	1.05

Note: this table reports the VIF values to assess multicollinearity among the independent variables used in the regression models.

. According to Hair et al. (2013), a VIF value exceeding 10 indicates high multicollinearity, which could distort estimation results. In all models, the VIF values for the variables remain well below the threshold of 10, indicating no significant multicollinearity concerns.

5. Results and Discussion

5.1. ESG Effects on Financial Performance

Building on Equations (1) and (2), we utilize fixed effects OLS regression models to assess the impact of composite ESG ratings and individual ESG pillars on CFP.

Table 6. Baseline regressions of ROA on aggregate ESG ratings and individual ESG pillar ratings.

Variable	Dependent Variable = ROA
	(1)	(2)	(3)	(4)
ESG	0.21 ***
	(6.49)
E		0.54 ***
		(3.90)
S			0.68 ***
			(3.49)
G				1.24 ***
				(3.30)
FirmSize	−1.95 *	−1.14	−1.17	−0.60
	(−1.82)	(−1.13)	(−1.19)	(−0.59)
FirmAge	−0.02 **	−0.02 **	−0.02 **	−0.02 **
	(−2.50)	(−2.15)	(−2.19)	(−2.34)
Lev	0.06 ***	0.06 ***	0.06 ***	0.06 ***
	(9.62)	(9.36)	(9.42)	(9.28)
Capex	−20.53 ***	−22.39 ***	−23.65 ***	−21.88 ***
	(−2.63)	(−2.87)	(−2.98)	(−2.78)
MTB	0.01 ***	0.01 ***	0.01 ***	0.01 ***
	(4.05)	(4.14)	(4.06)	(3.56)
DivPay	−0.00 ***	−0.00 ***	−0.00 ***	−0.00 ***
	(−3.12)	(−2.64)	(−2.67)	(−2.75)
BoardSize	−0.23 **	−0.15	−0.10	−0.16
	(−2.09)	(−1.32)	(−0.88)	(−1.49)
IndeptDir	0.08 ***	0.10 ***	0.10 ***	0.07 ***
	(4.83)	(5.93)	(6.23)	(3.67)
CEOAge	−0.01	−0.01	−0.01	−0.01
	(−0.18)	(−0.17)	(−0.16)	(−0.35)
CEOTenure	0.17 ***	0.18 ***	0.18 ***	0.19 ***
	(5.58)	(5.78)	(6.01)	(6.52)
Duality	−1.02 *	−1.18 *	−1.04 *	−0.84
	(−1.66)	(−1.93)	(−1.68)	(−1.37)
GDPGrow	0.03	−0.06	−0.02	0.00
	(0.20)	(−0.42)	(−0.17)	(0.01)
Constant	5.95	6.49	4.86	−1.40
	(1.39)	(1.58)	(1.17)	(−0.32)
Country FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
Observations	1110	1110	1110	1110
R2	0.35	0.34	0.34	0.34

Note: This table presents the baseline regression outcomes of ROA on the firm’s ESG composite and individual pillar rating scores, respectively. Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

exhibits the findings. The regression results indicate that the firm’s ESG undertakings, gauged by an integrated ESG rating and trio ESG pillar ratings, are markedly positively linked to CFP, supporting Hypothesis 1. We find that the coefficient for ESG is 0.21 and statistically significant at the 1% level. The results suggest a positive ESG-CFP relationship in the hospitality sector, aligning with the discoveries in preceding studies (Alareeni & Hamdan, 2020). It appears that stakeholders recompense corporations for ESG activities within the hospitality sector.

Following Equation (2), the coefficients are notably positive when the triadic ESG pillar ratings assess the ESG activities. The affirmative influence of the environmental pillar on CFP implies that corporate actions to safeguard the environment and higher degrees of environmental disclosure amplify the firm’s positive image from the stakeholders’ perspectives. Customers may favor “green hotels” and demonstrate an increased propensity to finance environmental initiatives (Jacobs et al., 2010; Nor et al., 2016). Moreover, heightened participation in social activities enhances the firm’s operational and financial efficiency, positively impacting firm value (Ersoy et al., 2022; Xie et al., 2019). The results indicate that social activities significantly affect CFP, signifying that superior firm performance offsets the company’s expenses toward employees, customers, and communities and that investment in social activities can yield enduring benefits. Finally, the result aligns with the research probing the correlation between corporate governance disclosure and CFP (Rouf, 2011). Optimal corporate governance disclosure can aid companies in operating effectively, curtail information asymmetry, and mitigate corporate financial risk, thereby augmenting corporate value.

Regarding the control variables, the positive influence of leverage on CFP is significant, implying that greater financial leverage of a corporation enhances the CFP of publicly traded firms in the hospitality sector, in alignment with the overall perspective that leverage can serve as a crucial instrument for achieving long-term performance (Alareeni & Hamdan, 2020; Popli et al., 2017). Additionally, a firm’s age negatively impacts CFP, suggesting that younger firms tend to exhibit better CFP. The dividend payout ratio exerts a negative effect on CFP. As anticipated, more independent directors bolster CFP, and extended CEO tenure benefits CFP.

5.2. Alternative Performance Measures

Furthermore, we reassess the ESG-CFP relationship by substituting the dependent variable with ROE and Tobin’s Q. The regression results presented in

Table 7. Alternative performance measures of ROE and Tobin’s Q.

Variable	Dependent Variable = ROE				Dependent Variable = TobinQ
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
ESG	1.26 ***				0.05 ***
	(5.50)				(6.79)
E		2.04 **				0.09 ***
		(2.18)				(3.24)
S			6.74 ***				0.20 ***
			(5.16)				(5.56)
G				13.18 ***				−0.05
				(4.17)				(−0.74)
FirmSize	−24.55 ***	−18.60 ***	−21.49 ***	−15.67 **	−1.14 ***	−0.93 ***	−0.99 ***	−0.86 ***
	(−3.70)	(−2.94)	(−3.30)	(−2.58)	(−5.64)	(−4.74)	(−4.92)	(−4.35)
FirmAge	0.01	0.02	0.01	0.00	−0.01 ***	−0.01 ***	−0.01 ***	−0.01 ***
	(0.16)	(0.61)	(0.36)	(0.09)	(−7.13)	(−6.51)	(−6.63)	(−6.48)
Lev	0.12 ***	0.12 ***	0.13 ***	0.12 ***	0.03 ***	0.03 ***	0.03 ***	0.03 ***
	(3.47)	(3.37)	(3.74)	(3.54)	(10.78)	(10.68)	(10.87)	(10.73)
Capex	69.44 *	58.16	45.17	63.10 *	−7.33 ***	−7.75 ***	−8.12 ***	−7.75 ***
	(1.90)	(1.60)	(1.26)	(1.71)	(−4.02)	(−4.24)	(−4.46)	(−4.26)
MTB	0.83 ***	0.83 ***	0.83 ***	0.82 ***	0.00	0.00	0.00	0.00
	(8.82)	(8.79)	(8.85)	(8.80)	(0.67)	(0.74)	(0.59)	(0.92)
DivPay	−0.01 ***	−0.01 **	−0.01 **	−0.01 **	0.00	0.00	0.00	0.00
	(−2.62)	(−2.19)	(−2.09)	(−2.32)	(0.97)	(1.19)	(1.23)	(1.10)
BoardSize	1.29 *	1.89 **	2.16 ***	1.51 **	−0.03	−0.00	0.01	0.00
	(1.73)	(2.48)	(2.85)	(2.15)	(−0.96)	(−0.18)	(0.20)	(0.16)
IndeptDir	0.28 **	0.40 ***	0.42 ***	0.07	0.01 *	0.01 ***	0.01 ***	0.01 ***
	(2.07)	(3.00)	(3.21)	(0.52)	(1.90)	(3.13)	(3.44)	(3.22)
CEOAge	0.11	0.13	0.08	0.01	−0.02 ***	−0.02 ***	−0.02 ***	−0.02 ***
	(0.40)	(0.45)	(0.31)	(0.02)	(−3.13)	(−3.02)	(−3.11)	(−2.75)
CEOTenure	0.46 **	0.55 ***	0.51 ***	0.66 ***	0.03 ***	0.04 ***	0.03 ***	0.04 ***
	(2.41)	(2.90)	(2.70)	(3.52)	(4.12)	(4.39)	(4.41)	(4.66)
Duality	−16.79 ***	−17.44 ***	−16.91 ***	−14.80 ***	0.11	0.08	0.11	0.10
	(−3.84)	(−4.01)	(−3.87)	(−3.34)	(0.51)	(0.37)	(0.49)	(0.45)
GDPGrow	−0.18	−0.66	−0.49	−0.21	−0.01	−0.03	−0.02	−0.02
	(−0.15)	(−0.56)	(−0.42)	(−0.19)	(−0.23)	(−0.86)	(−0.64)	(−0.72)
Constant	33.20	31.04	29.31	−36.94 *	5.53 ***	5.51 ***	5.33 ***	5.35 ***
	(1.51)	(1.41)	(1.38)	(−1.67)	(5.38)	(5.48)	(5.20)	(5.06)
Country FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	1110	1110	1110	1110	1110	1110	1110	1110
R2	0.54	0.53	0.54	0.54	0.46	0.45	0.45	0.44

Note: This table shows the regression results of ROE and Tobin’s Q on the firm’s ESG composite and individual pillar rating scores, respectively. Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

align with the results yielded when employing ROA. Specifically, the coefficients for ESG stand at 1.26 and 0.05, respectively, and are significant at the 1% level. The coefficients for each ESG pillar rating are likewise significant, except for the coefficient on governance with respect to Tobin’s Q. In unison, the regression results suggest that enhanced efforts committed to both composite and individual pillar ESG ratings can augment CFP, providing additional backing to Hypothesis 1.

5.3. GLS and 2SLS Regressions

To mitigate the impact of heteroscedasticity in OLS regression and procure an unbiased estimate (Reed & Ye, 2011), we implement fixed effects GLS regressions and delineate the results in

Table 8. Heteroscedasticity assessment employing GLS regressions.

Variable	Dependent Variable = ROA
	(1)	(2)	(3)	(4)
ESG	0.21 ***
	(5.71)
E		0.54 ***
		(3.63)
S			0.68 ***
			(3.38)
G				1.24 ***
				(3.77)
FirmSize	−1.95 ***	−1.14 **	−1.17 **	−0.60
	(−3.27)	(−1.99)	(−2.03)	(−1.06)
FirmAge	−0.02 ***	−0.02 ***	−0.02 ***	−0.02 ***
	(−3.05)	(−2.63)	(−2.70)	(−2.84)
Lev	0.06 ***	0.06 ***	0.06 ***	0.06 ***
	(10.54)	(10.42)	(10.59)	(10.47)
Capex	−20.53 ***	−22.39 ***	−23.65 ***	−21.88 ***
	(−3.95)	(−4.29)	(−4.51)	(−4.19)
MTB	0.01 ***	0.01 ***	0.01 ***	0.01 ***
	(4.09)	(4.11)	(4.03)	(3.65)
DivPay	−0.00 **	−0.00 **	−0.00 **	−0.00 **
	(−2.40)	(−2.16)	(−2.16)	(−2.44)
BoardSize	−0.23 **	−0.15	−0.10	−0.16
	(−2.04)	(−1.32)	(−0.87)	(−1.40)
IndeptDir	0.08 ***	0.10 ***	0.10 ***	0.07 ***
	(4.06)	(5.00)	(5.34)	(3.30)
CEOAge	−0.01	−0.01	−0.01	−0.01
	(−0.21)	(−0.20)	(−0.19)	(−0.39)
CEOTenure	0.17 ***	0.18 ***	0.18 ***	0.19 ***
	(5.43)	(5.73)	(5.91)	(6.41)
Duality	−1.02	−1.18 *	−1.04	−0.84
	(−1.58)	(−1.81)	(−1.59)	(−1.29)
GDPGrow	0.03	−0.06	−0.02	0.00
	(0.19)	(−0.41)	(−0.16)	(0.01)
Constant	5.95	6.49	4.86	−1.40
	(1.44)	(1.54)	(1.17)	(−0.32)
Country FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
Observations	1110	1110	1110	1110

Note: This table displays the outcomes of heteroscedasticity assessments using GLS regressions. Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

. The coefficient on ESG and the triadic pillars persist in being significantly positive, in alignment with the baseline results.

Subsequently, we employ 2SLS regressions to assuage our regression models’ apprehension regarding the endogeneity issue. In line with preceding studies (Attig et al., 2016; Wintoki et al., 2012), we utilize the lagged ESG ratings as the instrumental variable. The second-stage results of the 2SLS regressions are presented in

Table 9. Endogeneity assessment employing 2SLS regressions.

Variable	Dependent Variable = ROA
	(1)	(2)	(3)	(4)
Predicted ESG	0.23 ***
	(5.56)
Predicted E		0.46 ***
		(2.97)
Predicted S			0.62 ***
			(2.92)
Predicted G				1.73 ***
				(4.88)
FirmSize	−2.89 ***	−1.87 ***	−1.93 ***	−1.31 **
	(−4.90)	(−3.37)	(−3.43)	(−2.42)
FirmAge	−0.02 ***	−0.02 ***	−0.02 ***	−0.02 ***
	(−3.61)	(−3.12)	(−3.20)	(−3.48)
Lev	0.06 ***	0.06 ***	0.06 ***	0.06 ***
	(11.44)	(11.26)	(11.40)	(11.42)
Capex	−16.01 ***	−18.28 ***	−19.42 ***	−17.08 ***
	(−3.12)	(−3.52)	(−3.72)	(−3.31)
MTB	0.01 ***	0.01 ***	0.01 ***	0.01 ***
	(4.00)	(4.06)	(3.98)	(3.39)
DivPay	−0.00 ***	−0.00 **	−0.00 **	−0.00 ***
	(−2.75)	(−2.44)	(−2.45)	(−2.80)
BoardSize	−0.16	−0.05	−0.01	−0.08
	(−1.47)	(−0.47)	(−0.06)	(−0.75)
IndeptDir	0.08 ***	0.10 ***	0.11 ***	0.06 ***
	(4.08)	(5.10)	(5.51)	(2.83)
CEOAge	0.01	0.01	0.01	0.00
	(0.36)	(0.41)	(0.40)	(0.00)
CEOTenure	0.16 ***	0.17 ***	0.18 ***	0.20 ***
	(5.52)	(5.95)	(6.13)	(6.77)
Duality	−1.07 *	−1.23 **	−1.11 *	−0.78
	(−1.74)	(−1.97)	(−1.78)	(−1.26)
GDPGrow	0.00	−0.08	−0.05	−0.01
	(0.01)	(−0.56)	(−0.34)	(−0.09)
Constant	−3.94	−1.00	−2.48	−10.35 ***
	(−1.26)	(−0.31)	(−0.78)	(−2.96)
Country FE	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes
Observations	1024	1024	1024	1024
R2	0.40	0.39	0.39	0.40

Note: The table reports the second-stage results of the 2SLS regression of ROA on the firm’s predicted ESG composite and individual pillar ratings, using the lagged ESG ratings as the instrumental variable. Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

. The F-value surpasses ten, implying that the instrumental variable is suitable and efficient. The coefficients for the composite and pillar ESG ratings predicted from the first stage remain significantly positive. Once again, the regression results correspond with the primary findings.

5.4. Subsamples of US and Non-US Firms

In response to the heterogeneity within country-specific contexts (Keceli & Cankaya, 2020; Siueia et al., 2019; Gholami et al., 2022), we partition the sample into two subgroups, US and non-US enterprises, given that the United States represents the single largest category, accounting for approximately half of the entire sample.

Table 10. Subsamples of US firms and firms from other countries.

Variable	Dependent Variable = ROA
	US Firms				Firms from Other Countries
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
ESG	0.25 ***				0.11 **
	(6.00)				(2.29)
E		0.30				0.70 ***
		(1.46)				(3.20)
S			0.49 **				0.86 **
			(2.07)				(2.43)
G				1.84 ***				−0.19
				(4.39)				(−0.23)
FirmSize	−0.65	0.72	0.76	1.18	−2.83	−2.31	−2.71	−2.30
	(−0.69)	(0.76)	(0.82)	(1.40)	(−1.25)	(−1.02)	(−1.25)	(−1.03)
FirmAge	−0.02	−0.01	−0.01	−0.02	−0.00	−0.00	−0.00	0.00
	(−1.12)	(−0.36)	(−0.72)	(−1.26)	(−0.37)	(−0.24)	(−0.00)	(0.06)
Lev	0.08 ***	0.08 ***	0.08 ***	0.08 ***	−0.01	−0.02	−0.01	−0.02
	(14.43)	(13.38)	(13.65)	(13.44)	(−0.42)	(−0.60)	(−0.47)	(−0.54)
Capex	−28.91 ***	−30.39 ***	−32.38 ***	−24.56 ***	−15.69	−16.63	−16.32	−16.57
	(−3.50)	(−3.51)	(−3.66)	(−2.98)	(−1.31)	(−1.40)	(−1.38)	(−1.46)
MTB	0.02 ***	0.02 ***	0.01 ***	0.01 ***	0.02 **	0.02 **	0.02 **	0.02 **
	(3.65)	(3.60)	(3.56)	(2.68)	(2.34)	(2.15)	(2.42)	(2.45)
DivPay	−0.00 ***	−0.00 ***	−0.00 ***	−0.00 ***	−0.01	−0.01 *	−0.01 *	−0.01
	(−3.89)	(−3.42)	(−3.42)	(−3.27)	(−1.52)	(−1.83)	(−1.68)	(−1.46)
BoardSize	−0.12	−0.06	−0.02	−0.14	−0.26	−0.29 *	−0.20	−0.16
	(−0.80)	(−0.39)	(−0.15)	(−0.96)	(−1.63)	(−1.68)	(−1.24)	(−1.14)
IndeptDir	0.05 **	0.10 ***	0.10 ***	0.03	0.09 ***	0.07 **	0.09 ***	0.09 ***
	(2.33)	(4.33)	(4.30)	(1.26)	(2.98)	(2.52)	(2.97)	(2.95)
CEOAge	−0.05	−0.06	−0.07	−0.09	−0.01	−0.02	−0.01	0.00
	(−0.90)	(−1.17)	(−1.22)	(−1.63)	(−0.13)	(−0.38)	(−0.11)	(0.07)
CEOTenure	0.26 ***	0.29 ***	0.29 ***	0.31 ***	0.04	0.01	0.03	0.04
	(6.09)	(6.33)	(6.40)	(7.11)	(1.05)	(0.38)	(1.00)	(1.20)
Duality	−0.15	−0.34	−0.23	−0.33	−1.14	−1.90	−1.73	−1.23
	(−0.21)	(−0.46)	(−0.31)	(−0.47)	(−0.84)	(−1.39)	(−1.24)	(−0.96)
GDPGrow	7.86 ***	5.17 ***	5.16 ***	3.71 ***	−0.13	−0.16	−0.13	−0.16
	(4.00)	(3.47)	(3.53)	(2.68)	(−0.71)	(−0.93)	(−0.75)	(−0.90)
Constant	−31.47 ***	−23.57 ***	−24.39 ***	−25.41 ***	11.81 *	14.67 ***	12.09 **	12.65 **
	(−4.99)	(−4.22)	(−4.45)	(−4.65)	(1.94)	(2.64)	(2.05)	(2.18)
Country FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	542	542	542	542	568	568	568	568
R2	0.47	0.44	0.44	0.46	0.32	0.32	0.32	0.31

Note: This table shows the regression results of ROA on the firm’s ESG composite and individual pillar rating scores for US and non-US firm subsamples. Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

reveals that the ESG coefficient is both more significant and larger in magnitude for US firms compared to non-US firms, supporting Hypothesis 2. These findings align with observations that ESG disclosures are positively correlated with superior CFP in US businesses (Eccles et al., 2014). Intriguingly, the governance and social coefficients are markedly positive for US firms, whereas the environmental and social coefficients are significantly positive for non-US firms. It infers that US firms prioritize corporate governance and social issues, which are critical components of firm performance. In contrast, non-US firms place greater emphasis on environmental and societal concerns.

5.5. Subperiods of Pre- and During COVID-19

According to the World Health Organization, the hospitality sector, constituting a significant portion of the tourism industry, experienced considerable repercussions from the COVID-19 pandemic.11 The recurring lockdown measures during the pandemic severely impacted the hotel industry, resulting in substantial financial distress for numerous firms.12 The pandemic might have escalated corporations’ financial risk and stock volatility to an unprecedented level (Shakil, 2022).

Following prior research, we reapply the regression analysis to a subsample characterized by abbreviated sample durations (Abdi et al., 2022; Moneva et al., 2020). Our sample is bifurcated into two subsections, 2005–2019 for the pre-COVID-19 phase and 2020–2022 for the COVID-19 phase. The baseline regression is executed by applying ROA on ESG and its three pillars. The outcomes are exhibited in

Table 11. Analysis of pre- and during COVID-19 subperiods.

Variable	Dependent Variable = ROA
	Pre-COVID-19				During COVID-19
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
ESG	0.14 ***				0.33 ***
	(3.88)				(4.75)
E		0.27				0.83 ***
		(1.62)				(2.91)
S			0.56 **				0.69 **
			(2.21)				(2.18)
G				0.77				2.67 ***
				(1.48)				(4.21)
FirmSize	−1.71	−1.12	−1.23	−0.90	−2.51 *	−0.78	−0.64	0.78
	(−1.19)	(−0.82)	(−0.93)	(−0.66)	(−1.73)	(−0.61)	(−0.47)	(0.68)
FirmAge	−0.01	−0.01	−0.01	−0.01	−0.04 **	−0.04 **	−0.04 **	−0.04 **
	(−1.63)	(−1.42)	(−1.44)	(−1.54)	(−2.42)	(−2.02)	(−2.14)	(−2.22)
Lev	0.07 ***	0.07 ***	0.07 ***	0.07 ***	0.06 ***	0.06 ***	0.06 ***	0.06 ***
	(9.28)	(9.23)	(9.21)	(9.08)	(3.51)	(3.21)	(3.34)	(3.47)
Capex	−22.24 **	−23.42 **	−24.42 **	−22.96 **	−2.40	−5.19	−4.34	5.04
	(−2.36)	(−2.50)	(−2.57)	(−2.39)	(−0.15)	(−0.31)	(−0.25)	(0.31)
MTB	0.01 **	0.01 **	0.01 **	0.01	0.02 ***	0.02 ***	0.02 ***	0.02 ***
	(1.98)	(2.03)	(1.98)	(1.64)	(3.74)	(3.92)	(3.93)	(3.45)
DivPay	−0.00 ***	−0.00 ***	−0.00 ***	−0.00 ***	−0.00	−0.00	−0.00	−0.00
	(−3.29)	(−2.96)	(−2.94)	(−2.98)	(−0.64)	(−0.61)	(−0.43)	(−0.85)
BoardSize	−0.16	−0.11	−0.07	−0.12	−0.28	0.04	0.07	0.04
	(−1.18)	(−0.76)	(−0.53)	(−0.97)	(−1.13)	(0.16)	(0.30)	(0.18)
IndeptDir	0.07 ***	0.08 ***	0.08 ***	0.07 ***	0.08	0.14 **	0.15 **	0.05
	(4.07)	(4.96)	(5.00)	(3.10)	(1.45)	(2.22)	(2.41)	(0.82)
CEOAge	0.09 *	0.09 *	0.09 *	0.09 **	−0.22 ***	−0.22 ***	−0.24 ***	−0.28 ***
	(1.91)	(1.87)	(1.88)	(2.00)	(−2.99)	(−2.87)	(−3.06)	(−3.75)
CEOTenure	0.18 ***	0.19 ***	0.19 ***	0.19 ***	0.08	0.09	0.12	0.18 **
	(5.54)	(5.71)	(5.84)	(5.98)	(1.08)	(1.22)	(1.61)	(2.36)
Duality	−0.53	−0.62	−0.49	−0.41	−0.64	−0.26	−0.58	1.05
	(−0.79)	(−0.92)	(−0.74)	(−0.62)	(−0.38)	(−0.15)	(−0.32)	(0.60)
GDPGrow	0.11	0.02	0.04	0.04	−0.15	−0.17	−0.14	−0.15
	(0.50)	(0.09)	(0.20)	(0.21)	(−0.63)	(−0.77)	(−0.61)	(−0.67)
Constant	1.91	2.31	1.56	−2.43	−3.77	−4.73	−6.22	−16.78 **
	(0.38)	(0.48)	(0.32)	(−0.51)	(−0.52)	(−0.65)	(−0.86)	(−2.31)
Country FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FE	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	852	852	852	852	258	258	258	258
R2	0.26	0.25	0.26	0.26	0.46	0.43	0.42	0.45

Note: This table shows the regression results of ROA on the firm’s ESG composite and individual pillar rating scores for the pre-COVID-19 period (2005–2019) and during the COVID-19 era (2020–2022). Table 2 provides the descriptions of the variables. The robust t-values are reported within parentheses below the corresponding coefficient. ***, **, and * represent the 1%, 5%, and 10% levels of significance, respectively.

. The coefficients on the composite ESG rating are positive and statistically significant, aligning with the findings in our principal regressions. However, it is observable that the coefficient’s magnitude is more profound during COVID-19 than before, supporting Hypothesis 3. Additionally, the coefficients on environmental and governance pillars, while not significant pre-COVID-19, gain significance during the pandemic. This subperiod analysis suggests that our finding, namely the positive influence of hospitality industry firms’ ESG rating on CFP, gains salience amidst COVID-19. This aligns with the notion that stakeholders’ attention to ESG issues heightens during a global health crisis.

6. Conclusions

Using a sample of 86 publicly traded companies across 16 nations from 2005 to 2022, we explore the association between ESG ratings and CFP within the hospitality sector, where ESG stands as a pivotal investment catalyzing an organization’s growth potential and long-term evolution. Many studies probe the connection between ESG and financial performance, yielding a blend of empirical outcomes. This research manifests a positive ESG impact on corporate value in the global hospitality sector, applicable to composite ESG ratings and individual ESG pillar ratings. A suite of additional tests is conducted to ascertain the robustness of our findings. The foundational results persist for three alternative measures of firm performance (ROA, ROE, and Tobin’s Q). Additionally, concerns regarding heteroscedasticity and endogeneity are addressed using GLS and 2SLS regressions, respectively. These findings confirm Hypothesis 1, demonstrating that ESG ratings are positively associated with CFP in the hospitality industry. Furthermore, our findings demonstrate significant geographic heterogeneity. The positive ESG-CFP relationship is notably stronger for US firms compared to non-US entities, lending support to Hypothesis 2. In US firms, governance assumes a predominant role, whereas the environmental pillar is commanding in non-US companies. We also observe that the ESG-CFP linkage is stronger during the COVID-19 era than in the pre-pandemic period, especially for the environmental and governance pillars, supporting Hypothesis 3, which posits that the pandemic amplified ESG’s impact on CFP. These findings underscore the pivotal role of ESG in driving sustainable corporate value, particularly amid heightened uncertainty.

This study enhances the body of knowledge on ESG by scrutinizing the impact of ESG activities on CFP within the global hospitality sector. By utilizing cross-national ESG information and disaggregated pillar ratings on ESG, our conclusions proffer additional proof and enrich the comprehension of ESG implications. The cross-country variation and temporal analysis in the ESG-CFP relationship propose that ESG impact might diverge across geographical regions and temporal spans. Furthermore, our results hold practical value for executives and policymakers, supporting informed decision-making on ESG investments. The following subsections detail the study’s implications across four key areas, which are theoretical implications to the ESG literature, practical insights for corporate managers, policy recommendations to enhance ESG practices, and a discussion of the study’s limitations alongside future research opportunities.

6.1. Theoretical Implications

One of the most intriguing questions in ESG research is whether companies can perform well financially by doing good socially. If a strong business case exists for positive social action, all stakeholders—employees, customers, shareholders, the environment, and society at large—stand to benefit. Margolis et al. (2009) explored this question through a meta-analysis of 167 studies conducted over 35 years. Their findings indicate that while a positive relationship between CSR and CFP exists, it is not particularly strong. Notably, only 2% of the studies reviewed found that sustainability activities directly impose costs on shareholders. In the hospitality sector, Bianco et al. (2023) demonstrate that within the United States, sustainability certifications can improve key performance indicators such as occupancy rates. Extending this analysis to an international context, our study shows that hospitality firms with higher ESG commitments enhance their financial performance, as measured by ROA, ROE, and Tobin’s Q.

The findings of this study provide critical theoretical insights into signaling theory, legitimacy theory, and stakeholder theory concerning ESG ratings and CFP. From a signaling theory perspective, ESG ratings serve as credible signals that reduce information asymmetry by conveying a firm’s commitment to sustainability and resilience to investors and stakeholders. In the context of legitimacy theory, the results demonstrate how ESG initiatives help align corporate actions with societal norms and expectations, thereby enhancing legitimacy and contributing to improved financial performance. Finally, through the lens of stakeholder theory, the observed positive ESG-CFP relationship underscores the importance of addressing diverse stakeholder interests, including environmental stewardship, employee well-being, and governance practices. Together, these contributions enrich the theoretical understanding of ESG as a multidimensional construct that simultaneously reflects corporate responsibility and bolsters firm value through enhanced stakeholder engagement and societal alignment.

6.2. Implications for Corporate Managers

A McKinsey global survey reveals that 76% of executives believe CSR initiatives positively impact long-term shareholder value, while 55% agree that sustainability strengthens their company’s reputation.13 Our findings align with these perspectives, particularly regarding shareholder value. Emphasizing ESG initiatives that resonate with stakeholder expectations enhances both financial performance and corporate valuation. Additionally, our results suggest that US firms should prioritize robust governance mechanisms, whereas non-US firms may achieve greater benefits by focusing on environmental issues. These findings highlight the importance of tailoring ESG strategies to regional and industry-specific contexts, ensuring that initiatives align with the expectations and demands of various stakeholders to maximize their impact.

Managers in the hospitality sector should view ESG initiatives not merely as compliance or ethical obligations but as strategic assets that can drive financial performance and enhance corporate valuation. The amplified ESG-CFP relationship observed during the COVID-19 pandemic underscores the critical role of resilience-focused ESG strategies in navigating periods of crisis. Integrating such strategies into core business operations can help firms adapt to dynamic challenges while fostering long-term sustainability. By aligning ESG efforts with stakeholder interests and addressing region-specific priorities, corporate managers can not only mitigate risks and enhance resilience but also capitalize on opportunities for growth, innovation, and strengthened stakeholder trust. These efforts ultimately contribute to building a sustainable competitive advantage and securing enduring value for their organizations.

6.3. Implications for Policymakers

Our findings advocate for policy frameworks that incentivize ESG adoption, particularly in sectors like hospitality, where sustainable practices can significantly and positively influence economic and social outcomes. Policymakers should prioritize making ESG adoption an industry norm through government action, as it has the potential to drive both economic performance and societal benefits. The study’s insights on the heightened relevance of ESG during the COVID-19 era emphasize the necessity for policies that encourage resilience-focused ESG strategies. Beyond enhancing firm performance, ESG activities contribute to greater resilience in turbulent times (Xu et al., 2023), supporting stable and sustainable economic growth.

In this context, policymakers should establish regulatory frameworks that promote ESG transparency and standardize reporting metrics to reduce information asymmetry and enable more informed decision-making by investors and stakeholders. Given the observed geographic variation in the ESG-CFP relationship, region-specific policies that address unique ESG priorities are crucial for maximizing the impact of ESG initiatives. Furthermore, fostering collaboration between governments, industry leaders, and local communities can ensure ESG practices align with broader societal objectives while supporting economic resilience and long-term growth. By integrating these elements, policymakers can create a sustainable foundation for the hospitality sector and other industries alike.

6.4. Limitations and Future Research Directions

While this study provides significant insights into the ESG-CFP relationship, it is not without limitations. The analysis focuses exclusively on publicly traded hospitality firms due to the limited availability of ESG data from Bloomberg. This narrow scope may limit the generalizability of the findings to private enterprises, which might demonstrate unique ESG practices and financial outcomes. Additionally, reliance on Bloomberg ESG ratings may not fully capture the intricate nuances of sustainability practices across different organizations. The study’s focus on the hospitality sector, while valuable, inherently reflects the unique sustainability and reputational demands of the industry, which may not apply uniformly across other sectors with differing environmental and social priorities.

Regional disparities observed in the ESG-CFP relationship further underscore the potential influence of cultural and institutional factors, which were not explicitly controlled in this study. These disparities suggest that the ESG-CFP dynamic may vary based on national contexts, regulatory environments, and cultural norms. Such contextual factors highlight the need for further research to disentangle the role of these influences on the effectiveness of ESG strategies. Addressing these limitations through expanded datasets and more granular analyses could provide a more comprehensive understanding of the ESG-CFP nexus across diverse industries and regions. Methodologically, while robust regression techniques such as 2SLS were employed to address endogeneity, potential limitations remain. The validity of 2SLS depends heavily on the choice of instrumental variables, and alternative instrumental variables or methods, such as the generalized method of moments or quasi-experimental designs, could further strengthen the analysis.

Future research should explore the ESG-CFP relationship across various sectors and conduct cross-country comparisons to examine how cultural, regulatory, and institutional dynamics shape this linkage in different contexts. Additionally, longitudinal studies investigating the enduring impact of ESG initiatives on firm performance, particularly in the post-pandemic era, could offer critical insights into the long-term benefits of sustainability practices. These directions would not only enrich academic discourse but also provide actionable guidance for businesses and policymakers seeking to align ESG strategies with both financial performance and societal expectations.