This study aims to investigate the relationship between ESG commitment and brand value in the banking industry, exploring the moderation effect of bank size and risk.
Based on a sample of 120 banks operating worldwide in the period 2009–2022, a panel regression with fixed effects is used to explore the relationship between ESG score, a proxy of ESG commitment and brand value. The brand value was retrieved from the Brand Finance database, and the ESG score from the Morgan Stanley Capital International (MSCI) dataset.
The results reveal that the ESG score does not impact brand value. However, when considering the moderating effects of bank size and risk, a significant positive relationship emerges. For large and risky banks, ESG commitment positively affects brand value. Analyzing the individual ESG pillars' impact shows that only the governance pillar is the most influential factor in this effect. Results are robust to different controls.
These results have theoretical and practical implications. From a theoretical standpoint, our results provide useful insights to explore in more detail how the adoption of sustainable practices by banks influences customers' behaviors and the antecedents of financial brand value. From a practical point of view, the work offers food for thought for bank managers in order to understand how the market evaluates bank commitment to sustainability and which areas investors consider most important.
This work sheds light on the relationship between ESG commitment and brand value that is still unexplored in the banking literature. Second, we provide evidence on the mechanisms (moderation effect) that could impact such a relationship. To the best of our knowledge, both contributions are novel in the banking literature.
1. Introduction
There is a growing consensus that the sustainability of company behaviors has gained a critical role in current competitive scenarios, representing a key issue for both financial and nonfinancial companies (Porter and Kramer, 2006).
In the banking literature, sustainability has captured attention over time. In recent decades, banks have been involved in crisis events, with significant negative consequences on the global economic and financial systems. As a result, banks have been pushed to review their management approaches by adopting responsible economic and social behaviors while implementing governance structures to prevent mismanagement (Murè et al., 2021). Given the pivotal role of banks for a sustainable economic development, banking scholars have extensively analyzed the effects that the adoption of sustainable behaviors, from an economic, social and governance point of view, has on different bank performance indicators including profitability and stability/probability of default (Andrieş and Sprincean, 2023; Di Tommaso and Thornton, 2020; Galletta et al., 2023), confirming a growing alignment with prior literature (Chiaramonte et al., 2022) on the positive effects of sustainability on bank performance and resilience in crisis contexts.
A topic that has not been explored in the banking literature concerns the effects that the adoption of sustainable behaviors has on the banks' brand value. For service companies, the brand is a key success factor (Berry, 2000) because of the difficulty of differentiating products that do not have physical differences (Zeithaml, 1981). Moreover, in the financial and/or telecommunications sector, where competitive pressures are very high globally, it is pivotal to create a strong brand not only in the market but also in the mind of the customer (Bamert and Wehrli, 2005; Keller, 2003).
In this regards, marketing scholars have provided robust evidence of a positive relationship between sustainability-oriented behaviors and brand outcomes (Akbari et al., 2021; Yu et al., 2024, 2025), whereas the banking literature has remained relatively silent on this point, despite the fact that the complexity and opacity of financial products amplify the importance of brand value in building customer trust and reducing perceived risk (Stigler, 1961; Stiglitz, 1987). Therefore, the brand value depends on the reputation that the bank maintains in the minds of its customers. Moreover, to sustain their reputation in the market, and hence their brand value, banks are actively engaged in responsible and sustainable behaviors that generate profits and impact the working conditions of employees, the environment and the local community. Consequently, the question that needs to be answered is whether and to what extent the adoption of sustainable behaviors can help increase the banks' brand value.
Building upon this gap in the literature, this study empirically tests the relationship between sustainability commitment (proxied by the ESG rating) and banks' brand value by using the Brand Finance database that provides the brand value of 500 banks operating globally. From this database, we extracted a sample of about 120 banks in the time span 2009–2022, for which the ESG rating was also available, retrieved from the database of the Morgan Stanley Capital International (MSCI). The results add a novel contribution to the literature, as they reveal that the overall ESG rating does not exert a significant direct impact on brand value, nor do the individual ESG pillars show a direct effect. However, the moderating effects of bank size and risk are significant: larger and riskier banks derive greater brand value benefits from their sustainability commitment – an effect driven mainly by the governance pillar. These findings are robust across alternative specifications, endogeneity checks and sample selection bias tests. By doing so, the study complements and extends prior findings (e.g. Forliano et al., 2025; Bo and Battisti, 2024), where similar multi-layered relationships between ESG and corporate outcomes are examined.
Overall, our results contribute to the literature on sustainability in the banking industry in two main ways. First, we empirically investigate whether a bank's sustainability commitment impacts brand value and which ESG pillar is more important in explaining this effect, thereby addressing a significant gap in the extant literature. Second, we provide evidence on the mechanisms – specifically the moderating effects of bank size and risk – that condition this relationship, thus introducing novel insights aligned with the increasing attention to bank-level heterogeneity in sustainability impact studies (European Banking Authority, 2022). To the best of our knowledge, both contributions are new to the banking literature, thus expanding the scope of existing sustainability research into the brand management domain.
These results also offer theoretical and practical implications. From a theoretical point of view, this work fills a significant gap in the banking literature regarding the link between sustainability and brand value, identifying key drivers that influence this relationship. In contrast to marketing literature that predominantly explores customer-level mediators (Akbari et al., 2021; Yu et al., 2024), our study highlights the moderating role of bank-related variables (size and risk), which are particularly important from both a business model and supervisory perspective. From a practical point of view, the findings provide useful insights for bank managers seeking to understand how the market evaluates sustainability efforts and which ESG dimensions matter most important to investors and stakeholder. Moreover, from a supervisory angle, the evidence reinforces the importance of banks' governance structures in enhancing brand value through greater customer and social legitimacy – as insight into clear regulatory relevance (European Banking Authority, 2022).
2. Theoretical background and hypotheses development
The demand from citizens, clients, employees, public institutions, etc., for greater attention to corporate management practices has made the concept of sustainability – articulated in its three pillars of environmental, social and governance (ESG) – an emerging strategic approach that is not only useful for gaining long-term competitive advantages but also for increasing corporate resilience in times of crisis (Lokuwaduge and Heenetigala, 2017). The theoretical foundation of this approach lies in the recognition that corporate behavior should not solely focus on profit but also include commitments toward the society in which the company operates. Porter and Kramer highlight the principle of shared value, where companies are committed to creating economic value that at the same time addresses the needs and challenges faced by society (Porter and Kramer, 2011). Therefore, responsible and sustainable behavior is an extension of business ethics and managerial morality, which should be aimed not only at complying with laws but also at responding to public pressure and social expectations. Therefore, sustainability can be seen as a principle of business ethics aimed at achieving benefits for all stakeholders (Singh et al., 2022).
This perspective draws on stakeholder theory and on the social contract perspective, which suggests that an implicit contract between the company and the society in which it operates exists, with reciprocal rights and responsibilities (Freeman, 1984). Consequently, businesses and the society in which they operate depend on each other (Porter and Kramer, 2006). Specifically, Freeman (1984) argues that systematically addressing the interests of stakeholders is essential for corporate success. Thus, companies should manage their relationships with stakeholders through strategies that benefit business outcomes (Backhaus et al., 2002; Donaldson and Preston, 1995; Jones, 1995). Since corporate decisions influence society in the same way that stakeholder decisions influence businesses, companies take initiatives that meet the needs of stakeholders while maximizing their performance. Hence, sustainability investments would follow a logic of business results while simultaneously addressing stakeholders' demands for responsibility (Bresciani et al., 2023). In this context, a large body of literature highlights the benefits of sustainability commitment. Responsible and sustainable companies avoid social and organizational costs, reduce the risks of litigation and sanctions, and at the same time, they can improve employee satisfaction and enhance the company's external image and reputation (Zasuwa and Wesołowski, 2024). This would lead to better relationships with various stakeholders and potentially improve overall corporate performance.
From an empirical viewpoint, although results are not conclusive, the literature seems to converge on identifying a positive relationship between a company's commitment to sustainable behavior and various measures of financial performance and/or its antecedents (Galema et al., 2008; Margolis et al., 2009; Whelan et al., 2021). Specifically, the literature shows that sustainable behavior is positively related with, among other things, business process efficiency, reduced energy consumption, the attraction, retention and motivation of good employees, customer loyalty and satisfaction (Albuquerque et al., 2019; Bhattacharya et al., 2008; Boehe and Cruz, 2010; Cahan et al., 2015; Pérez and Rodríguez Del Bosque, 2015; Walsh and Bartikowski, 2013).
2.1 Sustainable management and brand value - H2
The brand is a critical asset for companies, enabling consumers to make choices based on attributes like reputation or image, rather than just the product itself (Ind, 1997). A strong brand builds trust, particularly when customers are deciding to purchase intangible services. This is especially true for service companies, such as banks, where the brand helps customers to build a mental image of the service and reduce the complexity and perceived risks associated with purchasing nonphysical goods (Berry, 2000; Stigler, 1961; Stiglitz, 1987). As a result, in a resource-based perspective, the brand is a strategic asset, allowing companies to generate higher profits and protect their offerings from competitors (Berry, 2000). Additionally, to boosting profitability, a strong brand enhances customer loyalty (Capizzi and Freguson, 2005), allowing firms to be more resilient to price fluctuations, improve the effectiveness of marketing and expand their brand into new areas.
Brand value is an assessment of the strength of a brand (He and Calder, 2020). Brands reflect a customer's complete experience with a product (Keller and Lehmann, 2006). Brands with positive attributes are more likely to be perceived as valuable by consumers, resulting in their buying behavior (He and Calder, 2020) and inducing higher profits; thereby, a brand can be a valuable financial asset for the company (Sinclair and Keller, 2017).
In recent decades, consumers have placed increasing emphasis on the social responsibility of brands, making sustainable practices a key factor in building reputation and recognition (Fatma et al., 2015; Gugler and Shi, 2009; Öberseder et al., 2013; Papasolomou and Vrontis, 2006). A well-established line of research in marketing literature explores how responsible behavior influences customers' perception of a brand (Lemon et al., 2001). Scholars highlight that customers consider CSR commitment when they decide to purchase goods and services, and are more likely they prefer socially responsible firms, and are willing to pay a premium price (Bhattacharya and Sen, 2004; Sen and Bhattacharya, 2001). Kitzmueller and Shimshack (2012) state that “firms use CSR to differentiate and advertise their product or to build brand loyalty” and “CSR is meant to transmit a positive signal about firm quality and type.” According to (Brickley et al. (2003), a company's reputation for responsible behavior is an essential part of its brand value, and (Holt et al. (2004) argue that social responsibility impacts how socially conscious consumers evaluate brands. Referring to the brand value chain model, firms sustainability commitment contribute to customer mind-set namely “everything that exists in the minds of customers with respect to a brand (e.g. thoughts, feelings, experiences, images, perceptions, beliefs and attitudes)” that is an antecedent of market performance and hence of brand value (Hoeffler and Keller, 2002; Keller, 2003).
Although empirical evidence on the relationship between sustainability and brand value are not conclusive, the literature highlights that better ESG performance can positively impact a brand's image and increase consumer trust (Ramesh et al., 2019; Lee et al., 2022) and hence has positive impact on the financial value of a brand (Melo and Galan, 2011; Pope and Kim, 2022).
In the banking sector, as a part of the service industry, the brand plays a key role in managing the relationship with customers. Financial products are characterized by standardization, high complexity and opacity. Therefore, the brand in the banking sector plays an effective way of differentiation and is considered as a tool to reduce perceived risk (Van Heerden and Puth, 1995) and to increase customer (Capizzi and Ferguson, 2005). As financial scandals and irresponsible practices have eroded shareholder, employee and customer trust, banks have increased their commitment towards more sustainable behaviors, such as environmental protection, social banking and ethical governance, as part of the efforts to restore their social legitimacy and also to promote trust and credibility (Pérez and Bosque, 2014; Schultz et al., 2013). ESG activities are a way of signaling to consumers (Fombrun and Shanley, 1990; Porter and Kramer, 2006), aiming to build a strong bank reputation for the social quality of its activities. Therefore, scholars highlight that ESG commitment could impact banks' brand image, reputation and loyalty (Capizzi and Ferguson, 2005; Pratihari and Uzma, 2018). Therefore, our first hypothesis is as follows:
ESG commitment positively affects a bank's brand value.
Although a positive relationship has been hypothesized between sustainable commitment and banks' brand value, it is further hypothesized that this link is jointly moderated by the size and risk of the bank. The literature has already explored company size as a moderator of the relationship between ESG/CSR practices and firm value. Scholars highlight that company size is a demographic characteristic associated with various aspects of business operations. In detail, company size is associated with characteristics such as visibility, the availability of financial and organizational resources, competitive and contractual strength toward customers, suppliers and competitors, operational efficiency, etc. (Fiegenbaum and Karnani, 1991). All of these aspects can impact companies' willingness to undertake ESG projects and their success. Empirical evidence suggests that large companies are more likely to undertake successful ESG projects. Large companies are more visible in the environment in which they operate and, therefore, to creating favorable conditions for their survival, they are more motivated to increase their credibility and appear as responsible companies (Drempetic et al., 2019). Additionally, large companies are equipped with more resources (human and financial) that can be used in sustainability practices. Therefore, the positive effect of ESG strategies and practices on firm value is greater for large companies than for smaller ones (Abdi et al., 2022; D'Amato and Falivena, 2020). Mutatis mutandis, these arguments are also applicable to large banks, due to their greater availability of resources, their greater visibility among external stakeholders and their higher complexity both from an organizational and strategic standpoint. Furthermore, large banks are subject to greater market discipline compared to their smaller counterparts (Bertay et al., 2013) and to greater scrutiny by supervisory authorities and stakeholders. As a result, they are more motivated to adopt responsible and sustainable behaviors. Similarly, more risky banks are more visible and subject to greater scrutiny by the market and supervisory authorities, and they may be under greater pressure to adopt sustainable management practices (Costello et al., 2019). The Basel Committee on Banking Supervision and the European Banking Authority recalled the importance to adopt an ESG approach within bank risk management processes (Basel Committee on Banking Supervision, 2021; European Banking Authority, 2021). As larger and riskier banks tend to attract more attention, they suffer greater reputational losses when they are not compliant in terms of environmental, social and governance commitment. Therefore, these banks should have the greatest benefits from being ESG compliant. Thus, for larger and riskier banks, the relationship between ESG and brand value is positively and significantly sloped compared to the other banks.
Therefore, the second hypothesis is as follows:
The relationship between ESG commitment and brand value is jointly moderated by bank size and risk. For large and riskier banks, the relationship between ESG and brand value is positively and significantly sloped compared to the remaining banks.
3. Methodology: sample and variables
3.1 Sample and data collection
To test the two research hypotheses, the sample was constructed using the Brand Finance database, a provider of financial estimates on the brand value of leading companies operating worldwide (Pope and Kim, 2022). Brand Finance provides the brand value for 500 banks operating worldwide. In our study, we considered the top 100 banks in terms of brand value in the period 2009–2022. The choice to limit the analysis to these banks was due to the availability of data relating to the ESG rating. In fact, only a part of the 500 banks included in the Brand Finance database is included in the MSCI's ESG database. Considering that the ranking changes annually and that some banks enter and others exit from the top 100 positions, the number of sampled banks was 120. As regards the data collection, brand value was retrieved from the Brand Finance database. The data related to the ESG ratings of the sampled banks were collected from the Morgan Stanley Capital International (MSCI) database for the same period, 2009–2022. The use of this database is consistent with several recent studies (Albuquerque et al., 2019; Dunn et al., 2017; Pedersen et al., 2021; Sabbaghi, 2022). This database provides ESG ratings for approximately 8,500 companies globally. Each company is assessed based on its commitment to three key areas: (1) Environmental, meaning its commitment to preventing climate change, protecting natural resources, reducing pollution and waste, etc.; (2) Social, which refers to its commitment to improving labor relations, inclusion, community welfare and respect for human rights and (3) Governance, which involves adopting governance structures and mechanisms (e.g. number of independent directors, board diversity, board independence, etc.) for sound and responsible corporate management. Therefore, the ESG rating represents a measurement of a company's social responsibility approach and thus the potential risks the company may face in relation to its environmental, social, and governance choices. The financial information and balance sheet data of the banks under investigation were retrieved from the Bank Focus database of Bureau Van Dijk. Only banks with available observations for at least two consecutive years were included in the sample. The banks found to be useful for our analysis, due to having complete data, were 87, for a total of 724 bank/year observations
3.2 Variables
The dependent variable used to test the research hypotheses is the brand value of the banks, measured through the natural logarithm of the financial value attributed by the Brand Finance company. In the robustness tests, an alternative dependent variable was employed, calculated as the percentage of the brand's financial value relative to the bank's total assets. Regarding the independent variable of interest, it is represented by the level of commitment to sustainable management of the company, measured by the ESG rating assigned by a third-party agency, namely MSCI. The MSCI ESG rating scale is divided into 7 levels, from CCC to AAA, with a score ranging from 0 to 10, where 10 indicates the highest value and thus the best result achievable by a given company. The ESG rating is assigned by assessing corporate performance in the environmental, social and governance pillars. A score is assigned to each pillar (ranging from 0 to 10), reflecting the company's performance in the respective area. The score obtained in each pillar is, in turn, the result of evaluating a set of appropriately weighted elements that contribute to defining the company's overall commitment in a given area. Finally, the overall rating is the weighted average of the key issue scores (WAKIS) obtained in the three aforementioned pillars. Additionally, MSCI produces a normalized measure of the WAKIS named Industry-Adjusted Score (IAS), which is calculated by considering the company's position relative to other companies in the same sector. Therefore, this latter measure is not absolute but is explicitly intended to be relative to the standards and performance of a company's industry peers (Morgan Stanley Capital International, 2024). Therefore, in the analysis, the adjusted ESG score was used as the independent variable. In a robustness test, we verified that the results do not vary when using the nonadjusted ESG score (results not tabulated, but available upon request).
Finally, a set of control variables was used to avoid spurious effects in the relationship between the ESG score and brand value. Following the literature on the topic, the following control variables were considered (D'Amato and Falivena, 2020; Fatemi et al., 2018; Wong et al., 2021): bank size, calculated as the natural logarithm of total assets; bank age, calculated as the difference between the specific year and the date of the company's incorporation, with age taken as the natural logarithm. Additionally, the business model was considered as the ratio of loans to total assets, the proportion of intangible assets, bank growth measured as the growth of total assets, profitability measured as the ratio of net interest margin to average total assets in a given year, credit risk measured as the ratio of impaired loans to gross loans and overall risk, measured by the ratio of risk-weighted assets to total assets. Finally, in order to account for macroeconomic factors or regional differences, the GDP of the country in which the bank i is headquartered in the year t was also added. The models were estimated by including both time-fixed effects and bank-fixed effects. Variables with extreme values were winsorized at the 1–99% level. Table 1 presents a detailed description of the source and variable definitions.
Definition of variables used in the estimation
| Variable | Definition | Data source |
|---|---|---|
| Brand Value | Natural log of bank brand value | Brand Finance |
| Bank size | Natural log of the total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Bank age | Difference between a given year and the date of the company's incorporation | Our elaboration on data retrieved from Bank Focus |
| Business model | Ratio between loans and total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Intangible assets | Ratio between intangible assets to total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Asset growth | Growth ratio of total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Profitability | Ratio between net interest margin to average total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Credit risk | Natural log of the ratio between NPLs and gross loans of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| RWA/TA | Ratio between risk-weighted assets to total assets of bank i in the year t | Bank Focus |
| ESG score | ESG score of bank i in year t | MSCI database |
| Environmental score | Environmental score of bank i in year t | MSCI database |
| Social score | Social score of bank i in year t | MSCI database |
| Governance score | Governance score of bank i in year t | MSCI database |
| GDP | GDP growth | World Bank database |
| Variable | Definition | Data source |
|---|---|---|
| Brand Value | Natural log of bank brand value | Brand Finance |
| Bank size | Natural log of the total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Bank age | Difference between a given year and the date of the company's incorporation | Our elaboration on data retrieved from Bank Focus |
| Business model | Ratio between loans and total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Intangible assets | Ratio between intangible assets to total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Asset growth | Growth ratio of total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Profitability | Ratio between net interest margin to average total assets of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| Credit risk | Natural log of the ratio between NPLs and gross loans of bank i in year t | Our elaboration on bank balance sheet data retrieved from Bank Focus |
| RWA/TA | Ratio between risk-weighted assets to total assets of bank i in the year t | Bank Focus |
| Environmental score | Environmental score of bank i in year t | |
| Social score | Social score of bank i in year t | |
| Governance score | Governance score of bank i in year t | |
| World Bank database |
3.3 Descriptive statistics
This section presents the descriptive statistics of the main variables used in the analysis and the correlation matrix.
First, the banks included in the sample came from 26 countries, with a prevalence of Chinese and US banks. For the year 2022, the Chinese banks in the sample amount to 22, US banks to 18, 5 for the United Kingdom, Canada and Australia, and 4 for Japan. The remaining countries have between 1 and 3 prominent brands. An analysis of the time trend regarding the number/value of brands for China and the United States highlighted a significant contraction in the number and value of US bank brands, in favor of China, as reported in Figure 1.
The chart illustrates trends in the number of bank brands and their average brand value for Chinese (CN) and US banks from 2009 to 2022. The horizontal axis displays years from 2009 to 2022. The left vertical axis is labeled “Number of Brands” (range: 0–25). The right vertical axis is labeled “Average Brand Value (billion USD)” (range: 0–25). The legend includes: Number of Brands CN, Number of Brands US, Brand Value CN, and Brand Value US. Two vertical bars per year represent the number of brands: 2009: CN 7, US 17; 2010: CN 9, US 18; 2011: CN 9, US 19; 2012: CN 11, US 20; 2013: CN 11, US 18; 2014: CN 13, US 19; 2015: CN 13, US 14; 2016: CN 14, US 14; 2017: CN 15, US 14; 2018: CN 15, US 14; 2019: CN 16, US 15; 2020: CN 20, US 15; 2021: CN 21, US 16; 2022: CN 20, US 16. Two lines represent the average brand value: Brand Value CN (billion USD, approximate): Starts around 5 in 2009, increases steadily through the mid-2010s, rises sharply between 2017 and 2019, reaching approximately 22–23, then slightly declines in 2020 and stabilizes around 22–23 by 2022. Brand Value US (billion USD, approximate): Starts around 5 in 2009 and increases gradually over time, reaching approximately 14 by 2019 and remaining relatively stable through 2022.Trend of the number and average value of Chinese and US bank brands (2009–2022). Source: Authors' own work
The chart illustrates trends in the number of bank brands and their average brand value for Chinese (CN) and US banks from 2009 to 2022. The horizontal axis displays years from 2009 to 2022. The left vertical axis is labeled “Number of Brands” (range: 0–25). The right vertical axis is labeled “Average Brand Value (billion USD)” (range: 0–25). The legend includes: Number of Brands CN, Number of Brands US, Brand Value CN, and Brand Value US. Two vertical bars per year represent the number of brands: 2009: CN 7, US 17; 2010: CN 9, US 18; 2011: CN 9, US 19; 2012: CN 11, US 20; 2013: CN 11, US 18; 2014: CN 13, US 19; 2015: CN 13, US 14; 2016: CN 14, US 14; 2017: CN 15, US 14; 2018: CN 15, US 14; 2019: CN 16, US 15; 2020: CN 20, US 15; 2021: CN 21, US 16; 2022: CN 20, US 16. Two lines represent the average brand value: Brand Value CN (billion USD, approximate): Starts around 5 in 2009, increases steadily through the mid-2010s, rises sharply between 2017 and 2019, reaching approximately 22–23, then slightly declines in 2020 and stabilizes around 22–23 by 2022. Brand Value US (billion USD, approximate): Starts around 5 in 2009 and increases gradually over time, reaching approximately 14 by 2019 and remaining relatively stable through 2022.Trend of the number and average value of Chinese and US bank brands (2009–2022). Source: Authors' own work
Table 2 presents the descriptive statistics of the dependent, independent and control variables. Specifically, the sampled banks have an average brand value of around $9 billion, with a maximum of approximately $81 billion. The highest brand value belongs to the Industrial and Commercial Bank of China Ltd (ICBC). Additionally, the banks in the sample have achieved an average ESG score of approximately 5.5, with a profitability of 2.4%, and an average size of $1,000 billion.
Descriptive statistics
| Variable | N | Mean | Std. Dev | Min | Max |
|---|---|---|---|---|---|
| Brand value (USD/billion) | 797 | 9.289 | 11.159 | 1.043 | 80.791 |
| Bank size (USD/billion) | 797 | 1000.00 | 0.952 | 66.10 | 5670.00 |
| Bank age (year) | 797 | 7.614 | 6.307 | 2 | 332 |
| Business model | 797 | 0.524 | 0.125 | 0.114 | 0.807 |
| Intangible assets (%) | 797 | 0.277 | 0.246 | 0.016 | 1.387 |
| Asset growth (%) | 797 | 7.075 | 8.041 | −12.617 | 52.500 |
| Profitability (%) | 797 | 2.403 | 1.221 | 0.536 | 10.567 |
| Credit risk (%) | 797 | 2.662 | 2.816 | 0.219 | 18.007 |
| RWA/TA (%) | 797 | 48.954 | 17.799 | 3.803 | 108.795 |
| ESG score | 797 | 5.58 | 2.235 | 0 | 10 |
| Environmental score | 797 | 5.36 | 2.320 | 0 | 10 |
| Social score | 797 | 4.93 | 1.198 | 1.400 | 9.78 |
| Governance score | 797 | 4.88 | 1.644 | 0.033 | 9.77 |
| GDP (%) | 797 | 2.731 | 3.417 | −11.167 | 10.636 |
| Variable | N | Mean | Std. Dev | Min | Max |
|---|---|---|---|---|---|
| Brand value (USD/billion) | 797 | 9.289 | 11.159 | 1.043 | 80.791 |
| Bank size (USD/billion) | 797 | 1000.00 | 0.952 | 66.10 | 5670.00 |
| Bank age (year) | 797 | 7.614 | 6.307 | 2 | 332 |
| Business model | 797 | 0.524 | 0.125 | 0.114 | 0.807 |
| Intangible assets (%) | 797 | 0.277 | 0.246 | 0.016 | 1.387 |
| Asset growth (%) | 797 | 7.075 | 8.041 | −12.617 | 52.500 |
| Profitability (%) | 797 | 2.403 | 1.221 | 0.536 | 10.567 |
| Credit risk (%) | 797 | 2.662 | 2.816 | 0.219 | 18.007 |
| RWA/TA (%) | 797 | 48.954 | 17.799 | 3.803 | 108.795 |
| 797 | 5.58 | 2.235 | 0 | 10 | |
| Environmental score | 797 | 5.36 | 2.320 | 0 | 10 |
| Social score | 797 | 4.93 | 1.198 | 1.400 | 9.78 |
| Governance score | 797 | 4.88 | 1.644 | 0.033 | 9.77 |
| 797 | 2.731 | 3.417 | −11.167 | 10.636 |
Table 3 shows the correlation matrix, which reveals that brand value is positively associated with the bank size (ρ = 0.8017, p < 1%) and negatively associated with credit risk (ρ = −0.1477, p < 1%). Regarding sustainability indicators, contrary to expectations, there is a negative and significant relationship between the ESG score (ρ = −0.1438, p < 1%) and brand value, as well as between the latter and the social pillar score (ρ = −0.1270, p < 1%) and the governance pillar score (ρ = −0.3075, p < 1%).
Correlation matrix
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Brand Value (ln) | 1 | |||||||||||||
| 2. Bank size (ln) | 0.8017** | 1 | ||||||||||||
| 3. Bank Age (ln) | 0.0502 | −0.1190** | 1 | |||||||||||
| 4. Business model | −0.2598** | −0.4401** | 0.0014 | 1 | ||||||||||
| 5. Intangible assets (%) | −0.0603† | −0.1922** | 0.0676† | 0.0072 | 1 | |||||||||
| 6. Asset growth (%) | −0.0149 | −0.1078** | −0.0324 | 0.0524 | −0.0775* | 1 | ||||||||
| 7. Profitability (%) | 0.0309 | −0.2822** | 0.1772** | 0.0574 | 0.1931** | 0.2791** | 1 | |||||||
| 8. Credit risk (%) | −0.1477** | −0.0938** | −0.0604† | −0.1861** | 0.1439** | −0.1745** | 0.3814** | 1 | ||||||
| 9. RWA/TA (%) | 0.1352** | −0.1678** | −0.1142** | 0.2844** | 0.0869* | 0.2650** | 0.5274** | 0.0338 | 1 | |||||
| 10. ESG score | −0.1438** | −0.1698** | 0.1396** | 0.0013 | 0.1247** | −0.0492 | −0.0945** | −0.0290 | −0.4199** | 1 | ||||
| 11. Environmental score | 0.2652** | 0.3505** | 0.1377** | −0.2401** | −0.0495 | −0.2402** | −0.2047** | −0.0259 | −0.4997** | 0.4469** | 1 | |||
| 12. Social score | −0.1270** | −0.0222 | 0.0493 | −0.2556** | 0.0714* | −0.0119 | 0.0164 | 0.1565** | −0.3492** | 0.6251** | 0.2399** | 1 | ||
| 13. Governance score | −0.3075** | −0.4396** | 0.1475** | 0.3621** | 0.1845** | 0.0957** | −0.0007 | −0.1775** | −0.0510 | 0.5814** | 0.0442 | 0.1493** | 1 | |
| 14. GDP | 0.1157*** | 0.0518 | −0.0834* | 0.1013** | −0.2311** | 0.1755** | 0.0476 | −0.2681** | 0.2779** | −0.1982** | −0.1926** | −0.2519** | −0.0814* | 1 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Brand Value (ln) | 1 | |||||||||||||
| 2. Bank size (ln) | 0.8017** | 1 | ||||||||||||
| 3. Bank Age (ln) | 0.0502 | −0.1190** | 1 | |||||||||||
| 4. Business model | −0.2598** | −0.4401** | 0.0014 | 1 | ||||||||||
| 5. Intangible assets (%) | −0.0603† | −0.1922** | 0.0676† | 0.0072 | 1 | |||||||||
| 6. Asset growth (%) | −0.0149 | −0.1078** | −0.0324 | 0.0524 | −0.0775* | 1 | ||||||||
| 7. Profitability (%) | 0.0309 | −0.2822** | 0.1772** | 0.0574 | 0.1931** | 0.2791** | 1 | |||||||
| 8. Credit risk (%) | −0.1477** | −0.0938** | −0.0604† | −0.1861** | 0.1439** | −0.1745** | 0.3814** | 1 | ||||||
| 9. RWA/TA (%) | 0.1352** | −0.1678** | −0.1142** | 0.2844** | 0.0869* | 0.2650** | 0.5274** | 0.0338 | 1 | |||||
| 10. | −0.1438** | −0.1698** | 0.1396** | 0.0013 | 0.1247** | −0.0492 | −0.0945** | −0.0290 | −0.4199** | 1 | ||||
| 11. Environmental score | 0.2652** | 0.3505** | 0.1377** | −0.2401** | −0.0495 | −0.2402** | −0.2047** | −0.0259 | −0.4997** | 0.4469** | 1 | |||
| 12. Social score | −0.1270** | −0.0222 | 0.0493 | −0.2556** | 0.0714* | −0.0119 | 0.0164 | 0.1565** | −0.3492** | 0.6251** | 0.2399** | 1 | ||
| 13. Governance score | −0.3075** | −0.4396** | 0.1475** | 0.3621** | 0.1845** | 0.0957** | −0.0007 | −0.1775** | −0.0510 | 0.5814** | 0.0442 | 0.1493** | 1 | |
| 14. | 0.1157*** | 0.0518 | −0.0834* | 0.1013** | −0.2311** | 0.1755** | 0.0476 | −0.2681** | 0.2779** | −0.1982** | −0.1926** | −0.2519** | −0.0814* | 1 |
Note(s): **, * and † denote significance at 1%, 5% and 10%, respectively
Finally, it is observed that the correlation coefficients between the independent and control variables are low, suggesting that multicollinearity is not a relevant issue.
3.4 Methodology
To investigate the relationship between ESG score and brand value of banks, the following panel model was estimated:
Where the dependent variable Brand Value was measured using the natural logarithm of the financial brand value of bank i in year t. In the robustness tests section, model (1) was estimated using the ratio between brand value and total assets of bank i in year t as the dependent variable. On the right-hand side of the equation, the ESG score is the independent variable of interest, X is a matrix of bank-level control variables, and β1 and β2 represent the regression coefficients to be estimated. To control for time-invariant heterogeneity at the bank level and also for biases resulting from any omitted time-invariant variable, bank-level fixed effects (δ) were included. φ represents time fixed effects. Finally, εi,t is the random error term. To test Hypothesis 2, which concerns the moderating effect of bank size and risk on the relationship between ESG and Brand Value, two-way interaction terms between the ESG score, firm size and risk (measured as the ratio between RWA and total assets) were added to model (1), along with the remaining lower-order interaction terms and the three-way interaction term as follows in (2):
The models were estimated using bank-level clustered robust errors. To manage the impact of outliers, all variables with extreme values were winsorized at the 1% and 99% levels.
4. Results
This section presents the results of the estimates related to the research hypotheses. Table 4 shows the results of the model testing Hypothesis 1. The models are highly significant, and the Hausman test confirmed the appropriateness of the fixed-effects over the random-effects approach. Multicollinearity was not a severe problem given that the VIFs were below the threshold value of 4 (O'Brien, 2007). Column 1 presents the results of the model that includes only the control variables. In the remaining columns (2–5), the results that include the independent variable, namely the overall ESG score and the scores for each of the individual pillars, are reported. Although the sign of the independent variable coefficient is consistent with expectations, the results in column 2 indicate that the ESG variable does not have a significant impact on the brand value of banks (β = 0.004, p > 10%). Similar results are shown in columns 3, 4 and 5 regarding the relationship between the individual ESG pillars score and the brand value. Hence, we concluded that adopting a sustainable management approach does not have a direct impact on the brand value. Consequently, Hypothesis 1 is rejected.
Regression models
| Brand value | |||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| Bank size | 1.066*** | 1.057*** | 0.972*** | 1.011*** | 1.014*** |
| (7.29) | (7.56) | (7.38) | (7.82) | (7.76) | |
| Bank age | 0.083 | 0.00521 | 0.0190 | 0.00144 | 0.00737 |
| (0.45) | (0.03) | (0.10) | (0.01) | (0.04) | |
| Business model | 1.801*** | 1.874*** | 1.938*** | 1.892*** | 1.901*** |
| (3.71) | (4.02) | (4.21) | (4.24) | (4.16) | |
| Intangible assets | −0.233* | −0.197 | −0.181 | −0.197 | −0.195 |
| (−2.02) | (−1.48) | (−1.43) | (−1.49) | (−1.48) | |
| Asset growth | −0.003* | −0.00311 | −0.00291 | −0.00309 | −0.00305 |
| (−2.00) | (−1.58) | (−1.44) | (−1.56) | (−1.54) | |
| Profitability | 0.059 | 0.0240 | 0.0241 | 0.0252 | 0.0239 |
| (1.30) | (0.48) | (0.49) | (0.50) | (0.48) | |
| Credit risk | −0.047* | −0.0301 | −0.0297 | −0.0302 | −0.0307 |
| (−2.05) | (−1.14) | (−1.10) | (−1.13) | (−1.19) | |
| RWA/TA | 0.001 | −0.000136 | −0.000221 | −0.000314 | −0.000317 |
| (0.28) | (−0.03) | (−0.05) | (−0.07) | (−0.07) | |
| GDP | −0.011* | −0.008 | −0.009 | −0.008 | −0.008 |
| (−2.05) | (−1.45) | (−1.55) | (−1.44) | (−1.44) | |
| ESG score | 0.004 | ||||
| (0.23) | |||||
| Environmental score | 0.011 | ||||
| (0.87) | |||||
| Social score | 0.008 | ||||
| (0.47) | |||||
| Governance score | −0.002 | ||||
| (−0.14) | |||||
| Constant | −7.887** | −7.355* | −7.394* | −7.450* | −7.381* |
| (−2.76) | (−2.61) | (−2.58) | (−2.61) | (−2.55) | |
| Bank FE | yes | yes | yes | yes | yes |
| Year FE | yes | yes | yes | yes | yes |
| N | 1,004 | 797 | 797 | 797 | 797 |
| F | 48.99*** | 34.66*** | 33.77*** | 37.12*** | 35.64*** |
| R2 | 0.642 | 0.669 | 0.670 | 0.669 | 0.669 |
| Brand value | |||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| Bank size | 1.066*** | 1.057*** | 0.972*** | 1.011*** | 1.014*** |
| (7.29) | (7.56) | (7.38) | (7.82) | (7.76) | |
| Bank age | 0.083 | 0.00521 | 0.0190 | 0.00144 | 0.00737 |
| (0.45) | (0.03) | (0.10) | (0.01) | (0.04) | |
| Business model | 1.801*** | 1.874*** | 1.938*** | 1.892*** | 1.901*** |
| (3.71) | (4.02) | (4.21) | (4.24) | (4.16) | |
| Intangible assets | −0.233* | −0.197 | −0.181 | −0.197 | −0.195 |
| (−2.02) | (−1.48) | (−1.43) | (−1.49) | (−1.48) | |
| Asset growth | −0.003* | −0.00311 | −0.00291 | −0.00309 | −0.00305 |
| (−2.00) | (−1.58) | (−1.44) | (−1.56) | (−1.54) | |
| Profitability | 0.059 | 0.0240 | 0.0241 | 0.0252 | 0.0239 |
| (1.30) | (0.48) | (0.49) | (0.50) | (0.48) | |
| Credit risk | −0.047* | −0.0301 | −0.0297 | −0.0302 | −0.0307 |
| (−2.05) | (−1.14) | (−1.10) | (−1.13) | (−1.19) | |
| RWA/TA | 0.001 | −0.000136 | −0.000221 | −0.000314 | −0.000317 |
| (0.28) | (−0.03) | (−0.05) | (−0.07) | (−0.07) | |
| −0.011* | −0.008 | −0.009 | −0.008 | −0.008 | |
| (−2.05) | (−1.45) | (−1.55) | (−1.44) | (−1.44) | |
| 0.004 | |||||
| (0.23) | |||||
| Environmental score | 0.011 | ||||
| (0.87) | |||||
| Social score | 0.008 | ||||
| (0.47) | |||||
| Governance score | −0.002 | ||||
| (−0.14) | |||||
| Constant | −7.887** | −7.355* | −7.394* | −7.450* | −7.381* |
| (−2.76) | (−2.61) | (−2.58) | (−2.61) | (−2.55) | |
| Bank | yes | yes | yes | yes | yes |
| Year | yes | yes | yes | yes | yes |
| N | 1,004 | 797 | 797 | 797 | 797 |
| F | 48.99*** | 34.66*** | 33.77*** | 37.12*** | 35.64*** |
| R2 | 0.642 | 0.669 | 0.670 | 0.669 | 0.669 |
Note(s): ***, **, * and † denote significance at 0.1%, 1%, 5% and 10%, respectively, with t-statistics in parentheses
Regarding hypothesis 2, Table 5 presents the results of model 2, which includes the interaction effects. The results in column 1 show that the three-way interaction term is positive and significant (β = 0.0014, p < 5%). Therefore, bank size and risk significantly moderate the relationship between the ESG score and brand value. Columns 2–4 of Table 5 show the results of the model 2 estimated for the individual ESG pillars. While in columns 2 and 3, the three-way interaction terms are not significant, meaning that the slope of the relationship between the environmental/social pillar scores and brand value is not significantly dependent on bank size and risk, in column 4, the three-way interaction term is positive and significant (β = 0.0014, p < 5%). Consequently, the relationship between the governance pillar score and brand value is significantly jointly moderated by bank size and risk.
Results of the regression model with interaction effects
| Brand value | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.725* | 0.674* | 0.274 | 0.919** |
| (2.15) | (2.30) | (0.65) | (2.73) | |
| Bank age | 0.0967 | 0.0687 | 0.0900 | 0.0410 |
| (0.45) | (0.34) | (0.43) | (0.20) | |
| Business Model | 1.686*** | 1.721*** | 1.790*** | 1.769*** |
| (4.12) | (4.37) | (4.07) | (3.98) | |
| Intangible assets | −0.150 | −0.117 | −0.194 | −0.167 |
| (−1.23) | (−0.94) | (−1.52) | (−1.24) | |
| Asset growth | −0.00257 | −0.00230 | −0.00282 | −0.00227 |
| (−1.30) | (−1.16) | (−1.46) | (−1.22) | |
| Profitability | 0.0244 | 0.0292 | 0.0192 | 0.0300 |
| (0.55) | (0.63) | (0.41) | (0.61) | |
| Credi trisk | −0.0362 | −0.0369 | −0.0332 | −0.0335 |
| (−1.41) | (−1.40) | (−1.24) | (−1.32) | |
| RWA/TA | −0.0396 | −0.114 | −0.227† | −0.0303 |
| (−0.40) | (−1.38) | (−1.75) | (−0.29) | |
| GDP | −0.006 | −0.009† | −0.007 | −0.007 |
| (−1.20) | (−1.71) | (−1.51) | (−1.47) | |
| ESG score | 0.741 | |||
| (0.83) | ||||
| Environmental score | −0.135 | |||
| (−0.21) | ||||
| Social score | −1.567 | |||
| (−1.15) | ||||
| Governance score | 1.474† | |||
| (1.81) | ||||
| Bank size × RWA/TA | 0.00172 | 0.00516 | 0.011† | 0.0012 |
| (0.35) | (1.24) | (1.77) | (0.24) | |
| Bank size × ESG score | −0.0390 | |||
| (−0.88) | ||||
| RWA/TA × Esg score | −0.0269 | |||
| (−1.66) | ||||
| Bank size × RWA/TA × ESG score | 0.0014*a | |||
| (1.70) | ||||
| Bank size × Environmental score | 0.00160 | |||
| (0.05) | ||||
| RWA/TA × Environmental score | −0.00119 | |||
| (−0.10) | ||||
| Bank size × RWA/TA × Environmental score | 0.0002 | |||
| (0.29) | ||||
| Bank size × Social score | 0.0770 | |||
| (1.13) | ||||
| RWA/TA × Social score | 0.0173 | |||
| (0.71) | ||||
| Bank size × RWA/TA × Social score | −0.0009 | |||
| (−0.72) | ||||
| Bank size × Governance score | −0.075† | |||
| (−1.85) | ||||
| RWA/TA × Governance score | −0.028† | |||
| (−1.77) | ||||
| Bank size × RWA/TA × Governance score | 0.0014*a | |||
| (1.85) | ||||
| Constant | −0.240 | 1.602 | 9.156 | −3.583 |
| (−0.03) | (0.26) | (1.07) | (−0.52) | |
| Bank FE | yes | yes | yes | yes |
| Year FE | yes | yes | yes | yes |
| N | 797 | 797 | 797 | 797 |
| F | 49.13*** | 42.46*** | 49.28*** | 38.67*** |
| R2 | 0.688 | 0.693 | 0.683 | 0.688 |
| Brand value | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.725* | 0.674* | 0.274 | 0.919** |
| (2.15) | (2.30) | (0.65) | (2.73) | |
| Bank age | 0.0967 | 0.0687 | 0.0900 | 0.0410 |
| (0.45) | (0.34) | (0.43) | (0.20) | |
| Business Model | 1.686*** | 1.721*** | 1.790*** | 1.769*** |
| (4.12) | (4.37) | (4.07) | (3.98) | |
| Intangible assets | −0.150 | −0.117 | −0.194 | −0.167 |
| (−1.23) | (−0.94) | (−1.52) | (−1.24) | |
| Asset growth | −0.00257 | −0.00230 | −0.00282 | −0.00227 |
| (−1.30) | (−1.16) | (−1.46) | (−1.22) | |
| Profitability | 0.0244 | 0.0292 | 0.0192 | 0.0300 |
| (0.55) | (0.63) | (0.41) | (0.61) | |
| Credi trisk | −0.0362 | −0.0369 | −0.0332 | −0.0335 |
| (−1.41) | (−1.40) | (−1.24) | (−1.32) | |
| RWA/TA | −0.0396 | −0.114 | −0.227† | −0.0303 |
| (−0.40) | (−1.38) | (−1.75) | (−0.29) | |
| −0.006 | −0.009† | −0.007 | −0.007 | |
| (−1.20) | (−1.71) | (−1.51) | (−1.47) | |
| 0.741 | ||||
| (0.83) | ||||
| Environmental score | −0.135 | |||
| (−0.21) | ||||
| Social score | −1.567 | |||
| (−1.15) | ||||
| Governance score | 1.474† | |||
| (1.81) | ||||
| Bank size × RWA/TA | 0.00172 | 0.00516 | 0.011† | 0.0012 |
| (0.35) | (1.24) | (1.77) | (0.24) | |
| Bank size × | −0.0390 | |||
| (−0.88) | ||||
| RWA/TA × Esg score | −0.0269 | |||
| (−1.66) | ||||
| Bank size × RWA/TA × | 0.0014* | |||
| (1.70) | ||||
| Bank size × Environmental score | 0.00160 | |||
| (0.05) | ||||
| RWA/TA × Environmental score | −0.00119 | |||
| (−0.10) | ||||
| Bank size × RWA/TA × Environmental score | 0.0002 | |||
| (0.29) | ||||
| Bank size × Social score | 0.0770 | |||
| (1.13) | ||||
| RWA/TA × Social score | 0.0173 | |||
| (0.71) | ||||
| Bank size × RWA/TA × Social score | −0.0009 | |||
| (−0.72) | ||||
| Bank size × Governance score | −0.075† | |||
| (−1.85) | ||||
| RWA/TA × Governance score | −0.028† | |||
| (−1.77) | ||||
| Bank size × RWA/TA × Governance score | 0.0014* | |||
| (1.85) | ||||
| Constant | −0.240 | 1.602 | 9.156 | −3.583 |
| (−0.03) | (0.26) | (1.07) | (−0.52) | |
| Bank | yes | yes | yes | yes |
| Year | yes | yes | yes | yes |
| N | 797 | 797 | 797 | 797 |
| F | 49.13*** | 42.46*** | 49.28*** | 38.67*** |
| R2 | 0.688 | 0.693 | 0.683 | 0.688 |
Note(s): ***, **, * and † denote significance at 0.1%, 1%, 5% and 10%, respectively, with t-statistics in parentheses
One tailed p-value
For a more detailed investigation of the joint moderating effect of bank size and risk on the relationship between ESG score and brand value, the slope of the relationship was estimated for different levels of bank size and risk. Table 6 presents the simple slope test of the relationship between ESG score and brand value for: (1) large banks with high risk; (2) large banks with low risk; (3) small banks with high risk; (4) small banks with low risk. The four groups of banks were defined based on the mean value of total assets and the RWA/TA ratio plus/minus one standard deviation.
Simple slope test of the relationship between ESG score and brand value at different levels of bank size and risk
| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| High size-High RWA | High size-Low RWA | Low size-High RWA | Low size-Low RWA | |
| Gradient of simple slope | 0.076* | −0.015 | −0.003 | −0.005 |
| (2.307) | (−0.407) | (−0.116) | (−0.237) |
| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| High size-High RWA | High size-Low RWA | Low size-High RWA | Low size-Low RWA | |
| Gradient of simple slope | 0.076* | −0.015 | −0.003 | −0.005 |
| (2.307) | (−0.407) | (−0.116) | (−0.237) |
Note(s): *denotes significance at 5%, with t-statistics in parentheses
As expected, in column 1 of Table 6, it emerges that for large and risky banks, the slope of the relationship between the ESG score and brand value is significant and positive (β = 0.076, p < 5%). Therefore, it can be concluded that ESG performance has a positive and significant impact on brand value only for the group of large and risky banks. Therefore, hypothesis 2 cannot be rejected. Figure 2 plots the relationships between ESG score and brand value for each of the four groups of banks. Figure 2 highlights that the line for large and risky banks is positively sloped, while the other lines are not.
The horizontal axis labeled “E S G level” has two categories: “Low E S G” and “High E S G”. The vertical axis labeled “Brand Value” ranges from approximately 11,5 to 16,5 in increments of 0,5. Four lines are shown, as indicated by the legend below the plot. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, the value increases from about 15,8 at Low E S G to about 16,3 at High E S G. For “High Size and Low R W A”, the value slightly decreases from about 15,6 to about 15,5. For “Low Size and High R W A”, the value remains nearly flat at around 13,9 across both E S G levels. For “Low Size and Low R W A”, the value shows a very small decrease from about 14,1 at Low E S G to just below 14,1 at High E S G. Note: All numeric values are approximated.Relationship between ESG score and brand value for different levels of bank size and risk. Source(s): Authors' own work
The horizontal axis labeled “E S G level” has two categories: “Low E S G” and “High E S G”. The vertical axis labeled “Brand Value” ranges from approximately 11,5 to 16,5 in increments of 0,5. Four lines are shown, as indicated by the legend below the plot. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, the value increases from about 15,8 at Low E S G to about 16,3 at High E S G. For “High Size and Low R W A”, the value slightly decreases from about 15,6 to about 15,5. For “Low Size and High R W A”, the value remains nearly flat at around 13,9 across both E S G levels. For “Low Size and Low R W A”, the value shows a very small decrease from about 14,1 at Low E S G to just below 14,1 at High E S G. Note: All numeric values are approximated.Relationship between ESG score and brand value for different levels of bank size and risk. Source(s): Authors' own work
Table 7 presents the results of the simple slope test of the relationship between the governance pillar score and brand value for different levels of bank size and risk.
Simple slope test of the relationship between governance pillar score and brand value for different levels of bank size and risk
| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| High size-High RWA | High size-Low RWA | Low size-High RWA | Low size-Low RWA | |
| Gradient of simple slope | 0.071* | −0.038 | 0.029 | 0.016 |
| (2.518) | (−1.298) | (0.800) | (0.861) |
| 1 | 2 | 3 | 4 | |
|---|---|---|---|---|
| High size-High RWA | High size-Low RWA | Low size-High RWA | Low size-Low RWA | |
| Gradient of simple slope | 0.071 | −0.038 | 0.029 | 0.016 |
| (2.518) | (−1.298) | (0.800) | (0.861) |
Denotes significance at 5%, with t-statistics in parentheses
In column 1 of Table 7, it emerges that for the large and risky banks, the slope of the relationship between the governance pillar score and brand value is significant and positive (β = 0.071, p < 5%). Therefore, it can be concluded that implementing sustainable governance has a positive and significant impact on brand value only for large and risky banks. Therefore, Hypothesis 2 cannot be rejected, even with reference to the governance pillar score.
In Figure 3, the relationships between governance pillar score and brand value for each of the four groups of banks are plotted. Once again, the line for large and risky banks is positively sloped, while the slopes of the other lines are not significantly different from zero.
The horizontal axis labeled “Governance score” has two categories: “Low Governance score” and “High Governance score”. The vertical axis labeled “Brand Value” ranges from approximately 11,5 to 16,0 in increments of 0,5. Four lines are plotted, as indicated by the legend below the graph. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, the value increases from about 15,5 at Low Governance score to about 15,7 at High Governance score. For “High Size and Low R W A”, the value decreases slightly from about 15,3 to about 15,1. For “Low Size and High R W A”, the value rises marginally from about 13,5 to about 13,6. For “Low Size and Low R W A”, the value increases slightly from about 13.7 to about 13.8 at High Governance score. Note: All numeric values are approximated.Relationship between governance pillar score and brand value for different levels of bank size and risk. Source(s): Authors' own work
The horizontal axis labeled “Governance score” has two categories: “Low Governance score” and “High Governance score”. The vertical axis labeled “Brand Value” ranges from approximately 11,5 to 16,0 in increments of 0,5. Four lines are plotted, as indicated by the legend below the graph. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, the value increases from about 15,5 at Low Governance score to about 15,7 at High Governance score. For “High Size and Low R W A”, the value decreases slightly from about 15,3 to about 15,1. For “Low Size and High R W A”, the value rises marginally from about 13,5 to about 13,6. For “Low Size and Low R W A”, the value increases slightly from about 13.7 to about 13.8 at High Governance score. Note: All numeric values are approximated.Relationship between governance pillar score and brand value for different levels of bank size and risk. Source(s): Authors' own work
5. Robustness tests
In this section, we present various tests to check the robustness of our previous results.
First, the previous models were estimated using an alternative dependent variable. In Table 8 was used the ratio between brand value and total assets of bank i in the year t as the dependent variable. For brevity, we reported only the results of model 2, which includes the moderation effects. The results shown in Table 8 are consistent with those presented in Table 5; therefore, Hypothesis 2 cannot be rejected. Hypothesis 1 is not supported (the results are not reported for brevity and are available upon request).
Regression results of the models with the Brand value/TA ratio as dependent
| Brand Value/TA | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.193 | −0.0241 | −0.0917 | 0.312 |
| (0.62) | (−0.11) | (−0.22) | (1.01) | |
| RWA/TA | 0.0597 | −0.0626 | −0.0660 | 0.0459 |
| (0.54) | (−0.91) | (−0.48) | (0.44) | |
| ESG score | 1.109 | |||
| (1.23) | ||||
| Environmental score | −0.487 | |||
| (−0.94) | ||||
| Social score | −0.443 | |||
| (−0.33) | ||||
| Governance score | 1.710* | |||
| (2.48) | ||||
| Bank size × RWA/TA | −0.00321 | 0.00247 | 0.00292 | −0.00252 |
| (−0.59) | (0.70) | (0.42) | (−0.49) | |
| Bank size × ESG score | −0.0573 | |||
| (−1.30) | ||||
| RWA/TA × Esg score | −0.0329† | |||
| (−1.75) | ||||
| Bank size × RWA/TA × ESG score | 0.00169*, a | |||
| (1.84) | ||||
| Bank size × Environmental score | 0.0179 | |||
| (0.70) | ||||
| RWA/TA × Environmental score | 0.00606 | |||
| (0.56) | ||||
| Bank size × RWA/TA × Environmental score | −0.000153 | |||
| (−0.28) | ||||
| Bank size × Social score | 0.0184 | |||
| (0.28) | ||||
| RWA/TA × Social score | −0.00442 | |||
| (−0.17) | ||||
| Bank size × RWA/TA × Social score | 0.000293 | |||
| (0.23) | ||||
| Bank size × Governance score | −0.0862* | |||
| (−2.58) | ||||
| RWA/TA × Governance score | −0.0309* | |||
| (−2.10) | ||||
| Bank size × RWA/TA × Governance score | 0.00159*a | |||
| (2.26) | ||||
| Constant | −3.885 | 0.817 | 1.937 | −6.129 |
| (−0.60) | (0.18) | (0.23) | (−0.95) | |
| Controls | yes | yes | yes | yes |
| Bank FE | yes | yes | yes | yes |
| Year FE | yes | yes | yes | yes |
| N | 797 | 797 | 797 | 797 |
| F | 17.62*** | 16.83*** | 17.25*** | 19.68*** |
| R2 | 0.271 | 0.301 | 0.259 | 0.274 |
| Brand Value/TA | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.193 | −0.0241 | −0.0917 | 0.312 |
| (0.62) | (−0.11) | (−0.22) | (1.01) | |
| RWA/TA | 0.0597 | −0.0626 | −0.0660 | 0.0459 |
| (0.54) | (−0.91) | (−0.48) | (0.44) | |
| 1.109 | ||||
| (1.23) | ||||
| Environmental score | −0.487 | |||
| (−0.94) | ||||
| Social score | −0.443 | |||
| (−0.33) | ||||
| Governance score | 1.710* | |||
| (2.48) | ||||
| Bank size × RWA/TA | −0.00321 | 0.00247 | 0.00292 | −0.00252 |
| (−0.59) | (0.70) | (0.42) | (−0.49) | |
| Bank size × | −0.0573 | |||
| (−1.30) | ||||
| RWA/TA × Esg score | −0.0329† | |||
| (−1.75) | ||||
| Bank size × RWA/TA × | 0.00169*, | |||
| (1.84) | ||||
| Bank size × Environmental score | 0.0179 | |||
| (0.70) | ||||
| RWA/TA × Environmental score | 0.00606 | |||
| (0.56) | ||||
| Bank size × RWA/TA × Environmental score | −0.000153 | |||
| (−0.28) | ||||
| Bank size × Social score | 0.0184 | |||
| (0.28) | ||||
| RWA/TA × Social score | −0.00442 | |||
| (−0.17) | ||||
| Bank size × RWA/TA × Social score | 0.000293 | |||
| (0.23) | ||||
| Bank size × Governance score | −0.0862* | |||
| (−2.58) | ||||
| RWA/TA × Governance score | −0.0309* | |||
| (−2.10) | ||||
| Bank size × RWA/TA × Governance score | 0.00159* | |||
| (2.26) | ||||
| Constant | −3.885 | 0.817 | 1.937 | −6.129 |
| (−0.60) | (0.18) | (0.23) | (−0.95) | |
| Controls | yes | yes | yes | yes |
| Bank | yes | yes | yes | yes |
| Year | yes | yes | yes | yes |
| N | 797 | 797 | 797 | 797 |
| F | 17.62*** | 16.83*** | 17.25*** | 19.68*** |
| R2 | 0.271 | 0.301 | 0.259 | 0.274 |
One tailed p-value
***, * and † denote significance at 0.1%, 5% and 10%, respectively, with t-statistics in parentheses
Second, we re-estimate our models using an alternative measure of ESG commitment. Given the poor correlation of the ESG scores of different providers (Berg et al., 2022), we measured the independent variable using the ESG score provided by Bloomberg. Similar to the ESG score provided by MSCI, Bloomberg ESG scores range from 0 to 10 (with 10 representing the highest score). The results of this test are in line with the previous. For brevity, in Table 9 we present only the models with significant results. The full table is available upon request.
Regression results using a different independent variable
| Brand value | ||
|---|---|---|
| 1 | 2 | |
| Bank size | 0.163 | 0.212 |
| (0.78) | (1.21) | |
| RWA/TA | 0.0476 | 0.0265 |
| (0.64) | (0.54) | |
| ESG score | 0.910 | |
| (1.32) | ||
| Governance score | 1.510* | |
| (2.25) | ||
| Bank size × RWA/TA | −0.0025 | −0.00352 |
| (−0.59) | (−0.52) | |
| Bank size × ESG score | −0.0473 | |
| (−1.30) | ||
| RWA/TA × Esg score | −0.0258† | |
| (−1.82) | ||
| Bank size × RWA/TA × ESG score | 0.00132*a | |
| (1.95) | ||
| Bank size × Governance score | −0.0662* | |
| (−2.68) | ||
| RWA/TA × Governance score | −0.0252* | |
| (−2.19) | ||
| Bank size × RWA/TA × Governance score | 0.0013*a | |
| (2.55) | ||
| Constant | −2.685 | −7.219 |
| (−0.69) | (−0.95) | |
| Controls | yes | yes |
| Bank FE | yes | yes |
| Year FE | yes | yes |
| N | 655 | 655 |
| F | 20.26*** | 22.86*** |
| R2 | 0.282 | 0.315 |
| Brand value | ||
|---|---|---|
| 1 | 2 | |
| Bank size | 0.163 | 0.212 |
| (0.78) | (1.21) | |
| RWA/TA | 0.0476 | 0.0265 |
| (0.64) | (0.54) | |
| 0.910 | ||
| (1.32) | ||
| Governance score | 1.510* | |
| (2.25) | ||
| Bank size × RWA/TA | −0.0025 | −0.00352 |
| (−0.59) | (−0.52) | |
| Bank size × | −0.0473 | |
| (−1.30) | ||
| RWA/TA × Esg score | −0.0258† | |
| (−1.82) | ||
| Bank size × RWA/TA × | 0.00132* | |
| (1.95) | ||
| Bank size × Governance score | −0.0662* | |
| (−2.68) | ||
| RWA/TA × Governance score | −0.0252* | |
| (−2.19) | ||
| Bank size × RWA/TA × Governance score | 0.0013* | |
| (2.55) | ||
| Constant | −2.685 | −7.219 |
| (−0.69) | (−0.95) | |
| Controls | yes | yes |
| Bank | yes | yes |
| Year | yes | yes |
| N | 655 | 655 |
| F | 20.26*** | 22.86*** |
| R2 | 0.282 | 0.315 |
One tailed p-value
Note(s): ***, * and † denote significance at 0.1%, 5% and 10%, respectively, with t-statistics in parentheses
Endogeneity is a recurrent issue in economic research. In this specific case, although the previous models were estimated using a fixed-effects model to control for time-invariant omitted variables, this does not eliminate the problem of endogeneity due to reverse causality or omitted time-variant variables. Therefore, a 2SLS-IV (Two-Stage Least Squares with Instrumental Variables) approach was used to address endogeneity. The company's sustainability performance, measured by the ESG score, is considered endogenous to brand value. Following the approach of Anginer et al. (2018) and Srivastava et al. (2022), the average ESG score of the country where bank i resides was used as an instrumental variable for the ESG score. The ESG score of country j, where bank i is based in year t, was calculated as the average ESG score of nonfinancial companies residing in country j at time t. All interaction terms involving the ESG score were also instrumented, with the interaction terms obtained by replacing the ESG score with the ESG score of the country. For brevity, Table 10 reports only the second-stage results for testing Hypothesis 1.
Results of the 2SLS-IV regression
| Brand value | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| ESG score | 0.0213†a | |||
| (1.53) | ||||
| Environmental score | 0.0242†a | |||
| (1.58) | ||||
| Social score | 0.0378†a | |||
| (1.52) | ||||
| Governance score | 0.0242†a | |||
| (1.56) | ||||
| Controls | yes | yes | yes | yes |
| Bank FE | yes | yes | yes | yes |
| Year FE | yes | yes | yes | yes |
| N | 724 | 724 | 724 | 724 |
| F | 51.06 | 51.92 | 48.44 | 52.48 |
| Under identification(χ2) | 91.262*** | 116.756*** | 64.751*** | 80.266*** |
| Weak identification(F) | 259.455 | 222.702 | 145.993 | 231.703 |
| Over identification(χ2) | 0.069 | 0.029 | 0.086 | 1.225 |
| Endogeneity test (χ2) | 2.394 | 0.989 | 2.316 | 6.539* |
| First-stage F-test (p value) | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
| Brand value | ||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 0.0213† | ||||
| (1.53) | ||||
| Environmental score | 0.0242† | |||
| (1.58) | ||||
| Social score | 0.0378† | |||
| (1.52) | ||||
| Governance score | 0.0242† | |||
| (1.56) | ||||
| Controls | yes | yes | yes | yes |
| Bank | yes | yes | yes | yes |
| Year | yes | yes | yes | yes |
| N | 724 | 724 | 724 | 724 |
| F | 51.06 | 51.92 | 48.44 | 52.48 |
| Under identification(χ2) | 91.262*** | 116.756*** | 64.751*** | 80.266*** |
| Weak identification(F) | 259.455 | 222.702 | 145.993 | 231.703 |
| Over identification(χ2) | 0.069 | 0.029 | 0.086 | 1.225 |
| Endogeneity test (χ2) | 2.394 | 0.989 | 2.316 | 6.539* |
| First-stage F-test (p value) | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
aOne tailed p-value
Note(s): *** and †a denote significance at 0.1% and 10%, respectively, with t-statistics in parentheses
The diagnostics for the first and second stages suggest the appropriateness of the approach used. However, it should be noted that the endogeneity test is significant only in the case of the model (column 4) with the governance pillar score as the independent variable (χ2 = 6.539, p < 5%). Therefore, it seems that the need to use a 2SLS-IV approach applies only to this model, as endogeneity should not be a relevant issue in the other three models. Although the results in Table 10 outline a somewhat different situation compared to those presented in Table 3, as the coefficients for the independent variables (namely the ESG score and the scores for the environmental, social, and governance pillars) show signs consistent with expectations, the level of significance is only marginal. Therefore, in line with the previous conclusions, hypothesis 1 is rejected due to insufficiently robust evidence. Table 11 presents the 2SLS-IV estimation results testing hypothesis 2. Once again, the diagnostics for the first and second stages indicate the validity of the approach used, and the endogeneity test is significant only in the case of the model (column 4) with the governance pillar score as the independent variable (χ2 = 4.801, p < 5%). Therefore, it appears that endogeneity is a relevant issue only for this model.
Results of the 2SLS-IV regression testing the moderation effect of bank size and risk on the relationship between ESG score and brand value
| Panel A – regression results | Brand value | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.891*** | 0.700** | 5.878 | 0.683* |
| (3.51) | (2.93) | (0.75) | (2.43) | |
| RWA/TA | 0.121 | −0.0585 | 1.729 | 0.0672 |
| (1.19) | (−0.76) | (0.71) | (0.49) | |
| ESG score | 1.927* | |||
| (2.14) | ||||
| Environmental score | 0.353 | |||
| (0.46) | ||||
| Social score | 21.60 | |||
| (0.66) | ||||
| Governance score | 1.879† | |||
| (1.70) | ||||
| Bank size × RWA/TA | −0.00706 | 0.00224 | −0.0892 | −0.00443 |
| (−1.38) | (0.58) | (−0.72) | (−0.65) | |
| Bank size × ESG score | −0.105* | |||
| (−2.32) | ||||
| RWA/TA × Esg score | −0.0598**a | |||
| (−2.99) | ||||
| Bank size × RWA/TA × ESG score | 0.00321** | |||
| (3.17) | ||||
| Bank size × Environmental score | −0.0250 | |||
| (−0.66) | ||||
| RWA/TA × Environmental score | −0.0113 | |||
| (−0.73) | ||||
| Bank size × RWA/TA × Environmental score | 0.000736 | |||
| (0.96) | ||||
| Bank size × Social score | −1.105 | |||
| (−0.67) | ||||
| RWA/TA × Social score | −0.413 | |||
| (−0.75) | ||||
| Bank size × RWA/TA × Social score | 0.0212 | |||
| (0.76) | ||||
| Bank size × Governance score | −0.104† | |||
| (−1.88) | ||||
| RWA/TA × Governance score | −0.0626*a | |||
| (−2.24) | ||||
| Bank size × RWA/TA × Governance score | 0.00337* | |||
| (2.41) | ||||
| Controls | yes | yes | yes | yes |
| Bank FE | yes | yes | yes | yes |
| Year FE | yes | yes | yes | yes |
| N | 724 | 724 | 724 | 724 |
| F | 42.76*** | 61.49*** | 21.69*** | 43.30*** |
| Under identification(χ2) | 53.626*** | 28.727*** | 27.256*** | 29.737*** |
| Weak identification(F) | 45.217 | 45.505 | 25.689 | 26.966 |
| Over identification(χ2) | 0.843 | 0.025 | 3.225† | 2.266 |
| Endogeneity test (χ2) | 1.633 | 1.357 | 1.119 | 4.801* |
| First-stage F-test (p value) | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
| Panel A – regression results | Brand value | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| Bank size | 0.891*** | 0.700** | 5.878 | 0.683* |
| (3.51) | (2.93) | (0.75) | (2.43) | |
| RWA/TA | 0.121 | −0.0585 | 1.729 | 0.0672 |
| (1.19) | (−0.76) | (0.71) | (0.49) | |
| 1.927* | ||||
| (2.14) | ||||
| Environmental score | 0.353 | |||
| (0.46) | ||||
| Social score | 21.60 | |||
| (0.66) | ||||
| Governance score | 1.879† | |||
| (1.70) | ||||
| Bank size × RWA/TA | −0.00706 | 0.00224 | −0.0892 | −0.00443 |
| (−1.38) | (0.58) | (−0.72) | (−0.65) | |
| Bank size × | −0.105* | |||
| (−2.32) | ||||
| RWA/TA × Esg score | −0.0598** | |||
| (−2.99) | ||||
| Bank size × RWA/TA × | 0.00321** | |||
| (3.17) | ||||
| Bank size × Environmental score | −0.0250 | |||
| (−0.66) | ||||
| RWA/TA × Environmental score | −0.0113 | |||
| (−0.73) | ||||
| Bank size × RWA/TA × Environmental score | 0.000736 | |||
| (0.96) | ||||
| Bank size × Social score | −1.105 | |||
| (−0.67) | ||||
| RWA/TA × Social score | −0.413 | |||
| (−0.75) | ||||
| Bank size × RWA/TA × Social score | 0.0212 | |||
| (0.76) | ||||
| Bank size × Governance score | −0.104† | |||
| (−1.88) | ||||
| RWA/TA × Governance score | −0.0626* | |||
| (−2.24) | ||||
| Bank size × RWA/TA × Governance score | 0.00337* | |||
| (2.41) | ||||
| Controls | yes | yes | yes | yes |
| Bank | yes | yes | yes | yes |
| Year | yes | yes | yes | yes |
| N | 724 | 724 | 724 | 724 |
| F | 42.76*** | 61.49*** | 21.69*** | 43.30*** |
| Under identification(χ2) | 53.626*** | 28.727*** | 27.256*** | 29.737*** |
| Weak identification(F) | 45.217 | 45.505 | 25.689 | 26.966 |
| Over identification(χ2) | 0.843 | 0.025 | 3.225† | 2.266 |
| Endogeneity test (χ2) | 1.633 | 1.357 | 1.119 | 4.801* |
| First-stage F-test (p value) | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
aOne tailed p-value
Note(s): ***, **, * and †a denote significance at 0.1%, 1%, 5% and 10%, respectively, with t-statistics in parentheses
The results presented in Table 11 are consistent with those shown in Table 6. Therefore, the relationship between ESG and brand value is significantly moderated by bank size and risk (column 1). Moreover, governance appears to be the factor that drives this result (column 4). Figure 4, a) and b) present the relationship between ESG and brand value, and the relationship between Governance pillar score and brand value, respectively, at different levels of bank size and risk.
In graph (a), the horizontal axis labeled “E S G level” has two categories: “Low E S G score” and “High E S G score”. The vertical axis labeled “Brand Value” ranges from approximately 16 to 19 in increments of 0,5. Four lines appear, as indicated in the legend. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, Brand Value increases from about 17,8 at Low E S G score to about 18,6 at High E S G score. For “High Size and Low R W A”, it decreases slightly from about 17.82 to about 17,65. For “Low Size and High R W A”, it increases from about 16,3 to about 16,5. For “Low Size and Low R W A”, it decreases slightly from about 16,65 to about 16,5. In graph (b), the horizontal axis labeled “Governance score” includes “Low Governance score” and “High Governance score”. The vertical axis labeled “Brand Value” ranges from approximately 11 to 16 in increments of 0,5. The same four line styles represent the same Size and R W A combinations. For “High Size and High R W A”, Brand Value rises from about 13,6 at Low Governance score to about 14,6 at High Governance score. For “High Size and Low R W A”, it decreases slightly from about 13,5 to about 13,4. For “Low Size and High R W A”, it increases from about 12,2 to about 12,4. For “Low Size and Low R W A”, it decreases slightly from about 12,6 to about 12,4. Note: All numeric values are approximated.ESG/Governance score and brand value for dimension e risk. Source(s): Authors' own work
In graph (a), the horizontal axis labeled “E S G level” has two categories: “Low E S G score” and “High E S G score”. The vertical axis labeled “Brand Value” ranges from approximately 16 to 19 in increments of 0,5. Four lines appear, as indicated in the legend. A line with open circular markers represents “High Size, High R W A”. A line with filled circular markers represents “High Size, Low R W A”. A line with open square markers represents “Low Size, High R W A”. A line with filled square markers represents “Low Size, Low R W A”. For “High Size and High R W A”, Brand Value increases from about 17,8 at Low E S G score to about 18,6 at High E S G score. For “High Size and Low R W A”, it decreases slightly from about 17.82 to about 17,65. For “Low Size and High R W A”, it increases from about 16,3 to about 16,5. For “Low Size and Low R W A”, it decreases slightly from about 16,65 to about 16,5. In graph (b), the horizontal axis labeled “Governance score” includes “Low Governance score” and “High Governance score”. The vertical axis labeled “Brand Value” ranges from approximately 11 to 16 in increments of 0,5. The same four line styles represent the same Size and R W A combinations. For “High Size and High R W A”, Brand Value rises from about 13,6 at Low Governance score to about 14,6 at High Governance score. For “High Size and Low R W A”, it decreases slightly from about 13,5 to about 13,4. For “Low Size and High R W A”, it increases from about 12,2 to about 12,4. For “Low Size and Low R W A”, it decreases slightly from about 12,6 to about 12,4. Note: All numeric values are approximated.ESG/Governance score and brand value for dimension e risk. Source(s): Authors' own work
The results in Figure 4 are similar to those reported in Figures 2 and 3. The relationship between ESG score and brand value is positively and significantly sloped for the group of the largest and riskiest banks (β = 0.253, p < 0.1%) (Figure 4a). The same result applies to the relationship between Governance score and brand value (β = 0.280, p < 0.1%) (Figure 4b). For the remaining groups of banks, the slope of the relationship is not significantly different from zero.
This study is based on a sample consisting of 120 banks by brand value, as calculated by Brand Finance. This sample selection choice could have biased our estimates; therefore, the two-stage Heckman method was applied to control for potential sample selection bias. In the first stage, a probit model with a binary dependent variable was estimated to model the probability of a bank being included in the top 100 of the Brand Finance ranking. Based on the results of this first estimation, the inverse Mills ratio (IMR) was calculated. In the second stage, the model used to test the research hypotheses was estimated, with the IMR added as a regressor. The existence of sample selection bias can be excluded if the coefficient of the IMR variable is not significant. The binary dependent variable used in the first stage equals 1 if bank i at time t is included in the top 100 positions and 0 in all other cases. The results of the estimates are presented in Table 12.
Results of the two-stage Heckman method
| Prob.(100_position) | Brand value | |
|---|---|---|
| 1 | 2 | |
| Bank size | 6.592*** | 0.869*** |
| (7.46) | (3.84) | |
| Bank age | 1.575 | −0.170 |
| (0.99) | (−0.45) | |
| Business model | −0.376 | 1.506* |
| (−0.10) | (2.10) | |
| Intangible assets | 0.286 | −0.099 |
| (0.34) | (−0.58) | |
| Asset growth | −0.026 | −0.009** |
| (−1.60) | (−2.95) | |
| Profitability | 0.549 | 0.067 |
| (1.55) | (0.63) | |
| Credit risk | −0.031 | −0.012 |
| (−0.580) | (−0.36) | |
| RWA/TA | −0.066* | 0.003 |
| (−2.40) | (0.48) | |
| Bank stability | 0.323* | |
| (2.43) | ||
| ESG score | −0.109 | −0.029 |
| (−1.17) | (−1.48) | |
| Inverse Mills Ratio | −0.112 | |
| (−1.17) | ||
| GDP | −0.005 | |
| (−0.89) | ||
| Constant | −2.905 | |
| (−0.58) | ||
| Bank-fixed effects | Yes | Yes |
| Year-fixed effects | Yes | Yes |
| N | 365 | 252 |
| LR(χ2) | 247.74*** | 67.52*** |
| R2 | 0.688 | |
| F-test | 8.819*** |
| Prob.(100_position) | Brand value | |
|---|---|---|
| 1 | 2 | |
| Bank size | 6.592*** | 0.869*** |
| (7.46) | (3.84) | |
| Bank age | 1.575 | −0.170 |
| (0.99) | (−0.45) | |
| Business model | −0.376 | 1.506* |
| (−0.10) | (2.10) | |
| Intangible assets | 0.286 | −0.099 |
| (0.34) | (−0.58) | |
| Asset growth | −0.026 | −0.009** |
| (−1.60) | (−2.95) | |
| Profitability | 0.549 | 0.067 |
| (1.55) | (0.63) | |
| Credit risk | −0.031 | −0.012 |
| (−0.580) | (−0.36) | |
| RWA/TA | −0.066* | 0.003 |
| (−2.40) | (0.48) | |
| Bank stability | 0.323* | |
| (2.43) | ||
| −0.109 | −0.029 | |
| (−1.17) | (−1.48) | |
| Inverse Mills Ratio | −0.112 | |
| (−1.17) | ||
| −0.005 | ||
| (−0.89) | ||
| Constant | −2.905 | |
| (−0.58) | ||
| Bank-fixed effects | Yes | Yes |
| Year-fixed effects | Yes | Yes |
| N | 365 | 252 |
| LR(χ2) | 247.74*** | 67.52*** |
| R2 | 0.688 | |
| F-test | 8.819*** |
Note(s): ***, ** and * denote significance at 0.1%, 1% and 5%, respectively, with t-statistics in parentheses
In column 1 of Table 12, the first-stage estimates are presented based on a broader set of regressors than those used in the second stage. In column 2, the second-stage estimates are presented, where the coefficient of the IMR variable is not statistically significant at the 5% level, suggesting that sample selection bias should not be a relevant issue in this study.
6. Discussion, implication and future research directions
Based on a sample of 120 banks included in the Brand Finance database, this work has investigated the relationship between the bank's ESG commitment, as proxied by the ESG score, and the brand value over the period 2009–2022. More importantly, it has also explored the joint moderating effect of bank size and risk on such a relationship. The core idea is that the bank's brand value is positively associated with the bank's ESG commitment. However, the main point of the study is that this relationship is significantly moderated by bank size and risk, meaning that the adoption of ESG practices has a relevant impact on the brand value, mainly for larger and riskier banks.
In contrast to existing literature that reports a positive association between CSR commitment and brand value in nonfinancial companies (Agus Harjoto and Salas, 2017; Melo and Galan, 2011), our results indicated that the ESG score does not significantly impact brand value in the banking industry. This finding was confirmed even when exploring the relationship between the ESG pillars' scores (environmental, social, and governance) and the brand value. Therefore, hypothesis 1 was rejected. However, when exploring the moderating role of bank size and risk, it was found that bank ESG commitment has a significant and positive impact on brand value only for larger and riskier banks. Additionally, a more detailed investigation revealed that for larger and riskier banks, only the governance pillar score has a significant and positive impact on brand value. Thus, the positive relationship between sustainability commitment and brand value is primarily driven by the adoption of sustainable governance practices, rather than environmental and social efforts. This result is in line with recent empirical evidence highlighting the significant and positive effect of the governance pillar on customer equity (Chow and Ho, 2024). Consequently, hypothesis 2 was not rejected. These findings were robust across various robustness tests, including changing the dependent variable, controlling for endogeneity and addressing sample selection bias.
A comprehensive interpretation of these results suggests that a commitment to sustainability is a relevant strategy for strengthening brand value only for larger and riskier banks, i.e. those that (1) have more adequate organizational and financial resources to successfully implement ESG projects, (2) are more visible in the market and more complex from a managerial and organizational point of views (Aouadi and Marsat, 2018), and most importantly, (3) with a potentially greater economic impact, as the shocks originating from larger and riskier banks have lasting effects on the whole economic and financial system compared to those originating from small and less risky banks (Alzuabi et al., 2021). Therefore, the largest and riskiest banks, in order to maintain their stability, have a great need for customer trust and social legitimacy. Thus, the adoption of sustainable management practices can contribute to achieving this goal. In addition, the governance pillar emerged as the main driver of the brand value of larger and riskier banks. This result is consistent with the literature and supervisory guidelines that recognize bank governance as a cornerstone of sound and prudent management (European Banking Authority, 2022; Srivastav and Hagendorff, 2016; Stulz, 2015). In the financial sector, ethics in banking behaviors influences customer and more generally stakeholder perceptions of risk and uncertainty in the banking system (Pérez and Rodríguez Del Bosque, 2015). Therefore, adopting governance mechanisms that increase transparency, compliance, prevent misconduct and/or opportunistic behaviors contributes to increasing customer trust, bank reputation and hence brand value.
6.1 Theoretical implications
In the marketing literature, studies on the impact of ESG commitment and brand value are rare, and even more so when the focus is on banking marketing. This study attempted to fill this gap by explaining the role of ESG on banks' brand value. Our results confirmed that ESG initiatives have an influence on banks' brand value, especially for larger and riskier banks, since such initiatives can increase customers' trust and therefore lead to the next purchase decision. Furthermore, the results highlighted that initiatives related to banks' governance, more than those related to environmental and social aspects, exert a positive and significant impact on brand value. Both these results are novel in the banking literature. Therefore, this study contributes to the banking marketing literature by providing an interpretative framework of the relationship between ESG and brand value and the mechanisms that explain its functioning. We think that these results provide useful insights to explore in more detail how the adoption of sustainable practices by banks influences customers' behaviors and the antecedents of financial brand value. One aspect that deserves further attention from scholars is the impact that governance mechanisms have on customer behaviors and antecedents of brand value. Governance has received widespread attention from scholars and regulators as a key factor to stimulate sound and prudent bank management. But how do customers evaluate bank governance? How does governance influence customer behaviors and thus the bank brand? These questions need to be explored in more detail.
Moreover, the study emphasizes the importance of examining moderating and mediating variables, in order to provide a more nuanced understanding of how sustainability practices can affect different aspects of bank performance.
6.2 Practical implications
Our findings have practical implications for banks and Supervisory Authorities. First, large and risky banks should pay attention to adopting sustainable practices. These banks are perceived as having a high impact on the financial system, so adopting a sustainable approach to banking business, especially regarding governance, can increase the market reputation of these banks and customer trust with a positive impact on their brand value. This result means that ESG initiatives and more specifically those related to governance could be not only a means to align with supervisory rules, but also as an important tool to increase brand image, reputation and therefore brand value (Ltifi and Hichri, 2022). Therefore, banks should enhance their ESG approach as a tool to improve long-term customer relationships, develop new market segments and ultimately their long-term performance. Consequently, banks have to consider very carefully the risks associated with the use of ESG initiatives for greenwashing purposes. The intent to mislead stakeholders regarding bank's ESG commitments violates the implicit social contract between companies and society, which requires the former to behave responsibly and transparently. This can seriously undermine stakeholders trust, resulting in long-term damage to the bank's reputation and ultimately to its performance (Birindelli et al., 2024; Galletta et al., 2024). Therefore, bank managers, when communicating their ESG initiatives, have to avoid (1) selective disclosure; (2) decoupling, where a company with poor ESG performance communicates positive performance; and (3) cognitive legitimacy, which is built on widely accepted social assumptions (Gregory, 2023). Among the three ESG dimensions, only the governance initiatives appear to be relevant for banks' consumers and therefore for brand value. Based on this result, ESG communication should focus on governance. Good governance is a key factor for the success of any bank. For large and risky banks, effective governance is particularly important. In these banks, the monitoring of managers to address conflicts of interest and effective risk management are central issues. Therefore, large and risky banks should adopt effective governance mechanisms and communicate these initiatives effectively to the market (Fatma and Rahman, 2016). From a supervisory perspective, authorities can use the guidelines on the effective governance mechanisms as a tool to raise awareness among banks towards the adoption of sustainable and responsible practices. This aligns with supervisory guidelines that emphasize the critical role of governance in maintaining financial stability and protecting stakeholder interests. However, these mechanisms can also have a direct impact on the reputation of the bank and on customer trust.
6.3 Future research directions
This research is not without limitations, primarily related to the sample and to the data provider for the brand valuations. The sample was restricted to 120 banks operating globally, which may not fully capture the diversity of the banking sector globally. Additionally, relying on a single provider for brand valuation, such as Brand Finance, could lead to biased results depending on the methodologies used. For example, different providers may focus differently on intangible assets, financial performance or brand strength when calculating brand value.
Given these limitations, future research should aim to expand the sample to include a broader set of banks from different regions, sizes, and business models to provide a more comprehensive analysis of the relationship between ESG practices and brand value. Additionally, the use of brand valuations from multiple providers, such as Interbrand or Kantar, could provide a more robust perspective, as each of these organizations employs distinct methodologies for assessing brand strength and value. Expanding the sample could also allow for more granular analysis of how different types of banks, such as retail-focused versus investment-focused banks, are affected by their ESG practices.
Finally, it would be useful to examine the role of other moderating variables, such as market competition, regulatory environments and cultural differences, in shaping the relationship between ESG scores, greenwashing behaviors (Cuomo et al., 2015) and brand value. These factors could offer deeper insights into how the broader business environment and regulatory landscape influence the effectiveness of sustainability initiatives in the banking sector.
6.3.1 Concluding remark
This research contributes to the growing literature at the intersection of sustainability and brand management by offering novel evidence on how ESG commitment relates to brand value in the banking industry – a sector where brand equity acts as a key reputational and trust-building mechanism (Berry, 2000; Stiglitz, 1987). Contrary to mainstream expectations derived from nonfinancial sectors (Melo and Galan, 2011; Akbari et al., 2021), our results show that ESG performance does not exert a direct and uniform influence on banks' brand value. Rather, the positive effects of ESG materialize only under specific institutional conditions (namely for large and risk-intensive banks), highlighting the relevance of bank-level heterogeneity and structural complexity in mediating sustainability outcomes (Aouadi and Marsat, 2018; European Banking Authority, 2022).
Most notably, among the three ESG pillars, governance stands out as the primary driver of brand value. This reinforces the idea that sound governance practices– anchored in transparency, accountability and internal control – are perceived by stakeholders as critical markers of credibility and legitimacy in the financial domain (Srivastav and Hagendorff, 2016; Stulz, 2015). This finding complements and extends recent research emphasizing the differentiated and often asymmetric impact of ESG dimensions on corporate outcomes (Bo and Battisti, 2024; Forliano et al., 2025), and invites scholars to avoid overly aggregated interpretations of ESG scores.
Additionally, our findings also raise a cautionary note regarding the reputational implications of greenwashing (Cuomo et al., 2015). As ESG becomes a strategic signaling tool, banks may face increasing temptation to selectively disclose or overstate their sustainability achievements. In such contexts, symbolic adoption of ESG practices, particularly in the absence of substantive governance reforms, can backfire, eroding trust and undermining long-term brand equity (Galletta et al., 2024; Birindelli et al., 2024; Gregory, 2023). This risk is particularly pronounced in financial institutions, where complexity and information asymmetry create fertile ground for decoupling strategies (Bo and Battisti, 2024).
In conclusion, this study calls for a more context-sensitive, governance-driven and integrity-based approach to ESG evaluation in banking. Future research should further investigate how different ESG configurations, beyond aggregated ratings, shape stakeholder perceptions and intangible value, while also exploring the institutional mechanisms that can deter opportunistic sustainability signaling and reinforce authentic commitments.

