The impact of environmental, social, and governance (ESG) practices on customer behavior towards the brand in light of digital transformation: perceptions of university students

Abstract

In the digital transformation era, environmental, social, and governance (ESG) practices increasingly shape customers’ behavior (CB) toward brands, serving as frameworks that not only correspond with consumer values but also impact their trust, loyalty, and engagement with companies. However, prior studies have not extensively investigated this issue. Hence, this study, based on stakeholder theory, seeks to examine the effect of ESG on CB toward brands under the moderating effect of DT. To this end, data was collected from 306 students from Yemeni universities via an online questionnaire and analyzed using PLS-SEM via SmartPLS software. The results showed a direct relationship between ESG and CB. Specifically, the environmental dimension had the strongest effect on CB, followed by the social dimension and governance dimension. The results also found that DT moderates the relationship between the environmental dimension of ESG and CB, in contrast, the effect of DT on the relationship of the social dimension of ESG or the governance dimension of ESG on CB is not significant.

Keywords:

• Environmental
• social, and governance (ESG)
• customer behavior
• digital transformation

Reviewing Editor:

• Kaouther Kooli, Bournemouth University, United Kingdom of Great Britain and Northern Ireland

Subjects:

• Environmental Studies
• Environmental Management
• Environment and Business

1. Introduction

In an era marked by heightened environmental awareness and social justice movements, the influence of Environmental, Social, and Governance (ESG) factors on consumer choices and brand loyalty has become increasingly significant. As consumers become more aware of the ecological footprints and social impacts of their purchasing decisions, companies are recognizing the critical need to align their business strategies with ESG principles not merely as a compliance measure but as a core component of their market appeal and competitive strategy (Lee & Rhee, 2023). Indeed, some companies intentionally base their operations on these core principles, making them the foundation of their organizational practices and strategies (Nugroho et al., 2024). This thorough and thoughtful approach not only satisfies the needs of discerning customers who are increasingly aware of these issues, but it also generates a profound sense of satisfaction and fulfillment within the company, giving it a competitive edge in the marketplace (Al-Hakimi et al., 2022; PWC, 2023).

Interest in ESG continues to grow across different sectors. Major global corporations like Kia, Hyundai, and Samsung now view ESG management as crucial for their survival. They are concentrating on developing new and renewable energies and expanding the adoption of electric cars (Koh et al., 2022). ESG significantly affects corporate value, and it is seen as a fundamental value intimately linked to the long-term survival and success of businesses (Bae et al., 2023). The significance of corporate ESG management is consistently highlighted for both academics and practitioners. Rezaee (2016) suggested that a firm can enhance its sustainability by focusing on both financial value and non-financial aspects, like ESG. Before that, Jones (1995) maintained that a company’s ethical conduct boosts its competitiveness through the development of positive and sustainable stakeholder relationships. While numerous studies have been performed on ESG, most of these studies have primarily focused on corporate financial performance (Qureshi et al. 2021; Saygili et al., 2022; Zhao et al., 2018), while few studies have concentrated on consumer behavior (e.g., Bae et al., 2023). In addition, studies that addressed the effect of corporate ESG management on consumer behavior, particularly those utilizing primary data like surveys, are quite scarce (Lee & Rhee, 2023). Specifically, empirical research that explores the effect of ESG practices by connecting them with customer behavior towards the brand are not extensively investigated. Thus, it is essential to examine how corporate ESG management influences customer behavior towards the brand, leading to the following research question:

• RQ1. How does ESG practices affect customer behavior towards the brand?

Indeed, ESG practices play a significant role in shaping customer behavior towards brands, and their importance is further amplified by digital technologies that enhance these practices within companies (Zhao & Cai, 2023). In line with this, digital transformation (DT) can fulfill the requirements for disclosing and managing ESG information within firms. This not only improves the timeliness and comprehensiveness of ESG disclosures, but also enhances the efficiency and ease of managing and operating ESG information. Consequently, this helps bolster firms’ ability to implement ESG practices and enhance their performance (Wang & Esperança, 2023). DT is the process of incorporating digital technologies into all facets of a business, resulting in a fundamental alteration of the firm’s operations and the manner in which value is provided to customers (Vial, 2021). In general, the process of digitalization has a transformative impact on the allocation of company resources, mostly due to the consequences of information sharing and integration (Andersson, 2003), which addresses corporate requirements regarding ESG disclosure (Sedunov, 2017). Furthermore, the implementation of DT initiatives has the potential to decrease expenses associated with meeting social responsibility commitments and enhance the effectiveness of accountability processes (Bhandari et al., 2022). This, in turn, establishes a basis for enhancing ESG performance. Hence, it is contended that the examination of the impact of DT on the relation between ESG practices and CB towards brand requires additional research, leading to the following research question:

• RQ2. Is the relation between ESG practices and customer behavior towards the brand moderated by DT?

Using a questionnaire developed from existing research, data were gathered from 306 students from Yemeni universities, this study contributes to the literature in two ways. First, it examines whether ESG practices affect CB towards brands. Unlike previous studies that examined the linkage between ESG practices and financial performance, the current study focused on the link of ESG practices and CB toward brands in the context of developing countries, such as Yemen. Furthermore, this study incorporated DT as a moderating factor in analyzing the relationship between ESG practices and CB, an aspect unexplored in previous literature, which contributes to enhancing understanding of the complex link between ESG practices and CB.

The remainder of the article is organized as follows: Section 2 covers the literature review and the development of hypotheses. Sections 3 and 4 present the methods employed and the findings of the study, respectively. Sections 5 provides a discussion of the findings, and finally, section 6 highlights the conclusions, along with the implications as well as limitations and future research.

2. Literature review and hypotheses development

2.1. Underpinning theory

Theoretically, this study adopted the stakeholder theory (Freeman, 1984) to examine the effect of ESG on CB toward brands under the moderating effect of DT. According to this theory, a stakeholder is any person or entity capable of influencing the organization’s objectives (Al-Swidi et al., 2022). Hence, consumers have the ability to take action against directors acting as representatives of the company if they fail to fulfill their duties effectively (Khalil & Khalil, 2022). From this perspective, for companies to thrive, they need to share information and expectations with their main stakeholders, including consumers (Hartmann et al., 2017). This enables stakeholders to stay informed about the firm’s sustainability efforts aimed at fostering societal sustainability (Huang et al., 2019). In this context, certain studies have suggested that the purchasing behavior of 92% of consumers are shaped by their awareness of firms’ sustainability practices (Herjanto et al., 2021). This is a significant consideration, with nearly 86% of consumers taking health and environmental factors into account when evaluating a product (Khalil & Muneenam, 2021). Consistent with this idea, stakeholder theory proposes two approaches to a balanced sustainability communication strategy: maintaining regular contact with consumers and fostering collaborative, interactive communication. Accordingly, we argue that a company’s sustainability efforts (such as ESG initiatives) can positively influence consumer behavior towards its brands (Khalil & Khalil, 2022), particularly in the era of digital transformation where a company’s digital capabilities are crucial for effectively disseminating information and meeting the expectations of key stakeholders, such as consumers.

2.2. ESG and customer behavior

According to Min-Kyu and Seong-Soo (2022), customers’ evaluations of companies are shaped by their ESG initiatives, particularly with regard to their brand reputation. Addressing environmental concerns is becoming more important, not only because of ethical considerations, but also because of the strategic edge it brings in terms of increased customer loyalty and increased profits (Billio et al., 2021). This trend can be linked to increasing environmental consciousness among individuals who are more aware of significant biological and environmental changes happening globally (Nugroho et al., 2024). Consequently, environmental considerations have become a valuable competitive asset. Numerous companies have realized the advantages of adopting eco-friendly measures within their corporate social responsibility (CSR) initiatives and have developed sustainable products to cater to the rising demand from environmentally aware consumers (Dedunu & Sedara, 2023). Based on the above, we assume that:

• H1: Environmental practices positively influence CB.

On the other hand, the establishment of a robust presence on social media platforms can confer a distinct advantage to a firm by effectively highlighting its endeavors toward sustainability (Nugroho et al., 2024). Social responsibility initiatives can also enhance a company’s reputation and brand image. Regarding this, the findings of a consumer research survey conducted by Smartest Energy (2015) showed that sustainability is important to the majority of customers, specifically four out of five, exhibit a preference for purchasing products or services from firms that actively endorse and promote sustainability. The significance of ethical and responsible business practices in attracting customers and enhancing brand equity has been demonstrated via previous studies (e.g., Hur et al., 2014; Kang & Namkung, 2018; Tan et al., 2022; Vuong & Bui, 2023). The favorable perception of a company’s social responsibility actions by customers can significantly contribute to the creation and improvement of brand equity. From a strategic standpoint, active participation in social responsibility projects can contribute to the cultivation and preservation of a brand’s reputation. Hence, these projects might be seen as deliberate investments with long-term objectives. In a study conducted by Sharma and Jain (2019), it was demonstrated that the implementation of social responsibility programs had a beneficial impact on both brand equity and the reputation of a firm. According to the study conducted by Smith et al. (2001), it was shown that women tend to exhibit a greater degree of care towards ethical business duties in comparison to men. In a similar vein, the study conducted by Haski-Leventhal et al. (2017) revealed that individuals’ perceptions of CSR initiatives exhibit age-related differences. Based on the aforementioned insights, we put out the subsequent hypothesis:

• H2: Social practices positively influence CB.

Furthermore, the extant studies have explored the effect of governance practices on customers. In particular, Talesh (2015) suggests that corporate governance affects consumer ethics. Indeed, the governance practices of an organization significantly influence customers’ purchasing decisions. Furthermore, implementing a customer relationship leadership model enhances business performance through positive customer feedback on the company’s products (Galbreath & Rogers, 1999). As such, we argue that consumer buying decision and behavior towards the brands is influenced by the governance mechanisms in place in the company. When these mechanisms are open, transparent, and accountable, consumers are more likely to form stronger connections with the firm than ever before (Dedunu & Sedara, 2023). Thus, we suggest that:

• H3: Governance practices positively influence CB.

2.3. Moderate role of digital transformation

Businesses are shifting away from focusing exclusively on generating profits for shareholders and are instead aiming to expand benefits together with stakeholders - including employees, customers, suppliers, communities, and governments - to achieve mutual success for all parties involved (Fang et al., 2023). That is the purpose of ESG. Meanwhile, DT enables companies to enhance their ESG practices through more efficient resource management and reduced environmental footprints, leading to greater consumer trust and loyalty (Lu et al., 2024). By leveraging digital technologies, businesses can not only monitor and reduce their environmental impact more effectively but also engage with stakeholders in more meaningful ways, allowing for more transparent and ethical practices that attract socially conscious customers (Nambisan et al., 2019). This commitment to responsible practices is increasingly recognized and valued by consumers, often influencing their purchasing decisions and loyalty to brands that prioritize sustainability and ethical operations. Moreover, digital tools can facilitate better stakeholder engagement and communication, empowering customers to make informed choices that align with their values, thus driving positive changes in consumer behavior. In light of this, it can be assumed that:

• H4: The relation between environmental practices and CB is moderated by DT.

• H5: The relation between social practices and CB is moderated by DT.

• H6: The relation between governance practices and CB is moderated by DT.

3. Methodology

3.1. Sample and data collection

This study focused on university students as an appropriate sample for studying the effects of ESG practices on customer behavior amid digital transformation due to their familiarity with digital tools and heightened awareness of social and environmental issues. Furthermore, their purchasing habits and brand loyalty often reflect contemporary attitudes and values, providing valuable insights into emerging consumer trends that can guide businesses in adapting their ESG practices. Consistent with the goals of this research, a quantitative method was adopted, where data was gathered from a sample of public university students in Yemen through a cross-sectional survey conducted from mid-February to mid-April, 2023. For this purpose, a sample of 460 participants was selected according to a convenience sampling method due to the absence of a sample frame. This method is frequently employed in analogous research, such as those conducted by Al-Swidi et al. (2021) and Hanaysha et al. (2022). The survey questionnaire was disseminated in the Arabic language. In order to maintain consistency and accuracy, the original English form was translated into Arabic and subsequently translated back into English by a third-party.

Before providing answers to the research questionnaire, and to encourage participants to complete the questionnaire and increase the response rate, the survey included a statement assuring respondents of their anonymity. The goal is to gain respondent’s trust so that they are eager to answer each question on the research questionnaire comfortably and stress-free. Respondent’s recruitment is conducted ethically, and everyone volunteers to act as a respondent’s. Additionally, respondent’s permission was obtained to publish the results of the respondent’s answers regarding the completed questionnaire. We explain the purpose of this research and give Respondents the freedom to choose to answer each question or not. Furthermore, in this study, we have obtained informed consent from all participants involved. Before participating, respondents were informed about the purpose of the study, procedures, potential risks and benefits, and the rights of respondents. Participants were assured that their data would remain confidential and that they could withdraw from the study at any time without any repercussions. Consent was obtained both in writing and verbally, according to the respondent’s preference. This research was carried out according to ethical and regulatory guidelines governing research involving human participants.

In all, the study encompassed a total of 460 participants, of which 355 were successfully obtained. Out of these, 306 people provided complete and usable data, which is a reasonable sample size for performing PLS-SEM analysis (Hair et al., 2018). To obtain higher precision in calculating the minimum sample size, we assessed the statistical power with ‘G*Power’, following the recommendations of Faul et al. (2007). Taking into account a statistical power of 80%, an effect size of 0.15, and a significance level of 5% as described by Cohen (2013), the analysis indicated that at least 85 cases were required (refer to Appendix 1). Therefore, the sample size selected for this study, which comprised 306 cases, was considered adequate. Additionally, the sample size of 306 respondents met the established standard, which was determined as ‘ten times the largest number of structural paths directed at a particular latent construct in the structural model’ (Hair et al., 2011, p. 144). Table 1 provides a summary of sample characteristics

Table 1. Sample characteristics.

Demographic information	Categories	Frequency	(%)
Gender	Male	264	86.2
	Female	42	13.7
Education level	Bachelor	142	46.4
	Master	121	39.5
	Ph.D.	43	14.0
Age	20–30	162	52.9
	31–40	100	32.6
	41–50	30	9.8
	More than 50 years	14	4.5

3.2. Measures

Prior to the commencement of data collecting, measures were taken to mitigate potential data bias and enhance the dependability and accuracy of the scale. This involved the administration of face and content validity tests. Initially, a group of four scholars critically evaluated the survey questionnaire, offering insightful comments and recommendations aimed at enhancing the pertinence and comprehensibility of the interrogative items. Subsequently, a preliminary assessment was carried out with a sample of five individuals from the designated population in order to ascertain the accurate comprehension of all the questions as originally intended.

Overall, the questionnaire was divided into two sections: the first section covers the demographic information of the participants while the second section contains items that measure the variables of the study, which were evaluated on a five-point Likert scale (1 = strongly disagree to 5 = strongly agree). The measures of the variables were adopted from previous studies; ESG was measured with ten items that evaluated its three main dimensions, namely environmental, social and governance, adopted and adapted from Moisescu (2015), Maignan (2001), and Tripopsakul and Puriwat (2022). CB toward brands was assessed using a set of three items, adopted and adapted from Rich et al. (2010) and Kosiba et al. (2020). Finally, DT was measured using three items, derived from Hossain et al. (2020). The questionnaire items are provided in Appendix 2.

3.3. Common method bias

Before testing the hypotheses, we utilized Harman’s single-factor test, as recommended by Podsakoff et al. (2012), to check for any potential common method bias (CMB) issues. The test results showed that CMB was not a concern, with only 29% of the variance explained by a single factor, well below the 50% threshold, thus confirming the absence of CMB in the dataset. Additionally, we applied an alternative method suggested by Fuller et al. (2016), which involved analyzing the collinearity variance inflation factor (VIF) using SmartPLS to detect CMB. The analysis revealed that VIF values were under the acceptable limit of 3, further supporting the absence of CMB concerns in the data.

4. Data analysis and results

In this study, we analyzed the proposed model using the PLS-SEM method in SmartPLS 4, adhering to the procedures specified by Ringle et al. (2005). The frequent use of PLS-SEM in administrative research is due to its several benefits, highlighted by Gelaidan et al. (2023) and Goaill and Al-Hakimi (2021) and Goaill et al. (2023). This approach is particularly beneficial for smaller sample sizes (Henseler et al., 2009) and in research focused on predictive accuracy (Al-Swidi et al., 2023, 2024). PLS-SEM demonstrates superior statistical power compared to covariance-based SEM (CB-SEM), particularly in complex models with smaller samples. Overall, the PLS framework includes two interdependent models: the ‘measurement model’ and the ‘structural model’.

4.1. Measurement model

In this phase, an evaluation was conducted to assess the internal consistency of the scale items, with the aim of determining their reliability. The dependability of the constructs to indicators was demonstrated by factor loadings exceeding 0.70, as presented in Table 2 and Figure 2. Confirmatory factor analysis (CFA) was employed to evaluate the construct validity of the scale items, encompassing both convergent validity and discriminant validity. In order to achieve reliability, it is necessary for the values of Cronbach’s alpha (α) and composite reliability (CR) to surpass the threshold of 0.70, as suggested by Nunnally and Bernstein (1994). Furthermore, the construct validity was assessed through the examination of ‘convergent validity’ and ‘discriminant validity’. Hair et al. (2018) conducted a study. In order to establish convergent validity, it is necessary for the average variance extracted (AVE) value of each construct to surpass the threshold of 0.50, as stated by Hair et al. (2019).

Table 2. Reliability and convergent validity.

Construct	Code	Loading	Α	CR	AVE
E	E1	0.705	0.861	0.905	0.710
	E2	0.914
	E3	0.921
	E4	0.810
S	S1	0.948	0.934	0.949	0.884
	S2	0.970
	S3	0.901
G	G1	0.837	0.814	0.893	0.708
	G2	0.841
	G3	0.846
DT	DT1	0.862	0.858	0.858	0.779
	DT2	0.894
	DT3	0.891
CB	CB1	0.880	0.848	0.855	0.765
	CB2	0.882
	CB3	0.862

Furthermore, the study conducted by Henseler et al. (2015) employed the ‘heterotrait–monotrait (HTMT)’ method in order to assess and confirm the discriminant validity. Based on the findings of Kline (2011), it is recommended that the values inside the HTMT matrix should not be above 0.90, particularly in relation to the constructs. In our investigation, as depicted in Table 3, the results did not exceed this threshold. As demonstrated in Tables 2 and 3, all criteria pertaining to loadings, reliability, and validity were satisfied, hence confirming the validity of the measurement models. In general, the findings indicate that the constructs of the model (refer to Figure 1) possess both convergent and discriminant validity.

Figure 1. Research model.

Figure 2. Measurement model.

Table 3. Descriptive statistics and discriminant validity.

Construct	Mean	Std. devation	E	S	G	DT	CB
E	3.67	0.58
S	3.63	0.62	.069
G	3..75	0.62	.401	.249
DT	3.45	0.55	.089	.290	.230
CB	3.45	0.57	.516	.266	.353	.179

4.2. Structural model

The evaluation of the structural model involved the assessment of R², effect magnitude, and the predictive significance of the model. Additionally, bootstrapping was utilized to validate the research assumptions. In order to assess the validity of the assumptions and evaluate the suitability of the proposed model, the coefficient of determination (R²) was calculated at an aggregate level. This metric, as defined by Chin (1998), provides insights into the predictability of the model, with values of 0.67 indicating strong predictability, 0.33 indicating moderate predictability, and 0.10 indicating weak predictability. The findings suggest that the variables E, S, G, and DT collectively account for 33% of the variance in CB, which falls within the moderate range as depicted in Table 4.

Table 4. R², f², and effect sizes.

Construct	R^2	f^2	Effect size
CB	0.332
E	–	0.149	Medium
S	–	0.055	Small
G	–	0.031	Small
DT	–	0.012	Small

Additionally, the impact of latent variables on the dependent variable has been evaluated using f² analysis, which serves as a complement to R² analysis (Chin, 1998), as demonstrated in Table 4. In his study, Cohen (2013) employs f² values (0.35, 0.15, and 0.02) to emphasize the magnitudes of the effect sizes of the predictive factors as ‘large, medium, and small’ respectively. Consequently, the variables S, G, and DT exhibit a very small effect size (0.055, 0.031, and 0.012) on CB, whereas the variable E demonstrates a moderate effect size (0.149).

Furthermore, Hair et al. (2019) suggest that a positive value of cross-redundancy (Q²) indicates a strong predictive capability of the model. The findings shown in Table 5 indicate that the Q² value of the CB (dependent variable) is 0.236, hence validating the efficacy of the model for predictive purposes.

Table 5. Model’s predictive quality.

Total	SSO	SSE	Q²
CB	918.000000	700.975	0.236

Finally, the hypothesized relations in the model were examined, as depicted in Table 6 and Figure 3. The findings indicate that the paths (E→CB) (β = 0.356, p < 0.01), (S→CB) (β = 0.207, p < 0.01), and (G→CB) (β = 0.156, p < 0.01) exhibited positive and statistically significant relationships, providing support for hypotheses H1, H2, and H3.

Figure 3. Structural model.

Table 6. Path coefficient.

H	Path	Coefficient	Standard error	T-value	p-Value	Result
H1	E → CB	0.356	0.058	6.125	0.000	Supported
H2	S → CB	0.207	0.058	2.840	0.005	Supported
H3	G → CB	0.156	0.058	3.540	0.000	Supported
H4	E*DT → CB	0.230	0.056	3.257	0.001	Supported
H5	S*DT → CB	−0.036	0.071	0.646	0.120	Not supported
H6	G*DT → CB	−0.088	0.056	1.553	0.519	Not supported

In addition to examining the linear pathways of our proposed model, we conducted an investigation into the moderating influence of DT. The findings indicate that ED has a positive and statistically significant moderating effect on the path from E*DT to CB (β = 0.230, p < 0.01). Therefore, based on the evidence presented in Figure 4, hypothesis H4 is justified. On the other hand, the paths (S*DT→CB) (β = −0.036, p > 0.05) and (G*DT→CB) (β = −0.088, p > 0.05) were shown to be statistically insignificant. As a result, hypotheses H5 and H6 do not receive support.

Figure 4. Moderating effect of DT in the E-CB link.

5. Discussion

Depend on stakeholder theory, we sought to examine the impact of ESG practices on CB toward brands under the effect of DT. Overall, the findings reveal that all ESG practices have a significant impact on CB toward brands. This suggests that customers are more likely to respond favorably and make purchases from companies that implement ESG practices. The findings are outlined and discussed as follows.

First, environmental practices have a positive effect on CB toward brand. This is aligning with prior studies conducted by Bae et al. (2023), which revealed that environmental factor has a significant positive effect on brand trust. In contrast, it contradicts the findings of Nugroho et al. (2024), which have demonstrated no effect of the environmental factor on Indonesian consumer behavior. In addition to Lee and Rhee’s (2023) study, which showed that environmental practices did not positively influence brand attitude, brand image, or brand attachment. Our results imply that the implementation of environmentally friendly practices by a company positively influences how customers perceive and interact with its brand, and thus customers are more likely to be loyal to brands they perceive as responsible and committed to environmental stewardship. Although environmental concerns may be overshadowed by immediate economic and survival needs due to ongoing conflicts and economic hardships. However, the study’s findings suggest that environmental consciousness is growing among young consumers, indicating a shift towards more sustainable consumer behavior even in less developed settings, such as Yemen.

Second, social practices have a positive effect on CB toward brand. This means that the social behaviors, norms, or activities practiced by the company positively influence how customers perceive and interact with its brand. As such, customers are more likely to feel more connected or loyal to brands that engage in social practices aligned with their own values or the norms of their community. This is consistent with prior studies conducted by Bae et al. (2023), which revealed that social factor has a significant positive effect on brand trust. In contrast, it contradicts the findings of Nugroho et al. (2024), which have demonstrated no effect of the social factor on consumer behavior. Indeed, social practices, such as community involvement or ethical business operations, can enhance the brand’s image, as customers view these brands more favorably, associating them with positive values (Bae et al., 2023). In a country like Yemen, companies that are seen as beneficial to the community and that uphold social justice are likely to be favored due to the social fabric and community-oriented culture, which aligns with the findings showing positive influences on customer behavior.

Third, our results reveal that governance practices have a positive effect on CB toward brand, which is similar to the results of Nugroho et al.’s (2024) study. On the contrary, it contradicts the findings of Bae et al. (2023), which have demonstrated no effect of the governance factor on brand trust. Overall, our results indicate that when a company employs governance practices that promote transparency and ethical behavior, customers tend to respond favorably, where institutional trust may be low due to political instability. This positive response can manifest as increased loyalty, higher levels of trust, and a greater willingness to purchase from or recommend the brand. Essentially, good governance practices enhance the brand’s reputation, which in turn positively influences how customers perceive and interact with the brand.

Finally, the results revealed that digital transformation positively moderates the effect of environmental practices on customer behavior toward the brand. This means that the introduction or enhancement of digital technologies in a company strengthens the impact that the company’s environmental practices have on how customers perceive and interact with the brand. Essentially, as a company becomes more digitally advanced, the positive effects of its environmentally friendly practices on customer attitudes and behaviors become more pronounced. This could be due to improved communication, more effective marketing of the company’s green initiatives, or enhanced customer engagement through digital channels. On the contrary, digital transformation did not moderate the relationship of social practices and governance on consumer behavior towards the brand. As such, whether a company is digitally advanced or not does not affect the impact that its social and governance practices have on how customers perceive or interact with the brand.

6. Conclusion

The present study investigated the impact of ESG parameters on CB in relation to a brand. The data was obtained through an online poll with a total of 306 participants. The hypotheses were examined through the utilization of Partial Least Squares Structural Equation Modelling (PLS-SEM). The research revealed a positive correlation between the three dimensions of environmental (E), social (S), and governance (G) within the ESG framework and customer attitudes and actions towards a particular brand. The findings of the study indicated that the environmental pillar exerted the most significant influence on CB towards a brand, with the social pillar and governance pillar following suit in terms of impact. Various sustainability practices had varying effects on client perceptions. Hence, it is imperative for companies to take into account the distinct impacts associated with each ESG pillar during its implementation and communication with customers.

6.1. Implications for theory

Theoretically, this study reinforces the notion that ESG practices are crucial for shaping consumer behavior towards brands. Consumers are increasingly likely to support and remain loyal to companies that demonstrate responsible ESG practices. This is a significant implication for theory as it underscores the evolving consumer values towards sustainability and corporate responsibility. Additionally, the findings suggest that digital transformation can enhance the effectiveness of environmental practices on consumer behavior. This introduces an important theoretical perspective that the integration of digital technologies can amplify the positive impact of sustainable practices on consumer perceptions and actions. This moderation suggests that digital technologies not only facilitate better communication and engagement but also heighten the visibility and perceived authenticity of a company’s ESG commitments.

Moreover, the study discusses varying impacts of different ESG components (environmental, social, governance) on consumer behavior, indicating that not all ESG factors equally influence consumer perceptions and loyalty. This is theoretically significant as it suggests a nuanced understanding of how different aspects of sustainability are valued by consumers, depending on cultural and demographic contexts and the need for further studies in this area. Furthermore, the study highlights a gap in empirical research, particularly in linking ESG practices directly with consumer behavior through primary data. This calls for more empirical studies that explore this relationship, suggesting a need to expand theoretical frameworks to include more diverse consumer datasets and methodologies. Finally, by conducting the study in a developing country context (Yemen), the study suggests that the theoretical implications of ESG practices on consumer behavior might vary significantly based on geographical and socio-economic contexts. This challenges existing theories to be more inclusive of diverse settings, thus enriching the understanding of global consumer dynamics in response to corporate sustainability practices.

6.2. Implications for managers and policymakers

First, this study provides empirical evidence supporting the direct impact of ESG practices on CB towards the brand. In order to uphold and enhance brand credibility, it is imperative to effectively convey a sustainable vision and integrate sustainability concerns within the company. The establishment of a brand that aligns with sustainable practices has the potential to foster trust and loyalty among customers, thereby serving as a viable approach to brand management.

Second, our study results can provide valuable insights for marketers seeking to comprehend the underlying rationale behind the prevailing patterns in integrated marketing communications strategies pertaining to ESG considerations. Accordingly, managers should integrate ESG factors as a core component of their business strategies, given the escalating significance of ESG practices in the prevailing competitive landscape. Importantly, managers should adopt ESG strategies to reflect the specific expectations and norms of their target markets and sectors, especially given the varying impacts of ESG practices on consumer behavior across different regions reported in previous studies. For policymakers, it is important to consider regulations and incentives that encourage companies to adopt robust ESG practices. Policies that support transparency, accountability, and ethical governance can enhance the overall business environment and foster trust and loyalty among consumers.

Third, the study highlights the role of DT in enhancing ESG practices, especially environmental ones. According to the findings, investments in technology that enhance the transparency and communication of ESG efforts can lead to greater customer engagement and satisfaction. Therefore, policymakers should support frameworks that facilitate digital advancements in companies, as these can improve the efficiency, comprehensiveness, and timeliness of ESG information management and disclosure. For managers, investing in digital technologies can amplify the benefits of ESG practices through better stakeholder engagement and operational efficiencies, which is consistent with the perspective of stakeholder theory. By taking these actions, society can play a crucial role in encouraging and incentivizing businesses to prioritize ESG practices, ultimately leading to a more sustainable and equitable future.

6.3. Limitations

Regardless of the contributions mentioned earlier, more investigation is required due to the limitations of the study. First, the current study used cross-sectional data, limiting the ability to infer causation. This limitation arises because the impact of ESG practices unfold over time, a temporal dimension not accommodated by the empirical framework utilized. So, future research should seek to collect longitudinal data in order to capture conditional effects. Second, it is important to exercise prudence when extrapolating and broadening the results beyond the scope of this research. The conclusions are based on the opinions of students at public universities in Yemen. To validate these findings, further studies should be undertaken with diverse demographic groups or across various nations. Third, our study focuses exclusively on evaluating the moderating effect of DT among several potential moderators. Future research may consider any other moderating variables, such as culture, as the behaviors of customers towards ESG issues can be influenced by several cultural elements. Thus, examining results across different countries presents a promising avenue for future scholarly investigation. Some demographic characteristics of the sample (as shown in Table 1) can also be considered as control variables when examining the research model.

Authors contributions

Murad Baqis Hasan: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, and Revision. Ruchita Verma: Conceptualization, Data curation, Methodology, Writing – original draft. Dhanraj Sharma: Conceptualization, Data curation, Methodology, Writing – original draft. Sami A.M. Moghalles: Resources, Supervision, Reviewed the final draft of the paper, and Revision. Saqr Ali Saleh Hasan: Resources, Software, and Reviewed the final draft of the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be made available on request.

Additional information

Notes on contributors

Murad Baqis Hasan

Murad Baqis Hasan is a Ph.D student at the department of Financial Administration, School of Management, Central University of Punjab, Bathinda, India.

Ruchita Verma

Ruchita Verma is an Assistant Professor at the department of Financial Administration, School of Management, Central University of Punjab, Bathinda, India.

Dhanraj Sharma

Dhanraj Sharma is an Assistant Professor at the department of Financial Administration, School of Management, Central University of Punjab, Bathinda, India.

Sami A.M. Moghalles

Sami A.M. Moghalles is an Assistant Professor at the department of Marketing and Production, Thamar University, Dhamar, Yemen.

Saqr Ali Saleh Hasan

Saqr Ali Saleh Hasan is a lecturer at the department of Accounting, Thamar University, Dhamar, Yemen.

Appendix 1:

G*power parameters and output.

F tests: Linear multiple regression: Fixed model, R² deviation from zero.

Analysis: A priori: Compute required sample size.

Table

Input:	Effect size	f^2 = 0.15
Outputs:	α err prob	= 0.05
	Power (1-β err prob)	= 0.80
	Number of predictors	= 4
	Noncentrality parameter λ	= 12.7500000
	Critical F	= 2.4858849
	Numerator df	= 4
	Denominator df	= 80
	Total sample size	= 85
	Actual power	= 0.8030923

Appendix 2:

Questionnaire items.

Table

Statement	1	2	3	4	5
Environmental, Social, Governance (ESG): Moisescu (2015), Maignan (2001), and Puriwat and Tripopsakul (2022)
ESG (Environmental dimension)
The firm (or brand) makes every effort to minimize or eliminate harmful effects on the environment
The firm (or brand) reduces resource consumption as much as possible without harming the environment.
The firm (or brand) actively pursues using environmentally friendly materials.
The firm (or brand) focuses on the efficient administration of recycling and trash disposal activities.
ESG (Social dimension)
The firm (or brand) respects social norms, traditions, and culture.
The firm (or brand) benefits people’s long-term welfare and quality of life in society.
The firm (or brand) contributes to social and economic development.
ESG (Governance dimension)
The firm (or brand) fully complies with the law when carrying out its operations.
The firm (or brand) is concerned about carrying out its duties towards its partners and stockholders.
The ethical principles of the firm (or brand) have priority overachieving economic performance.
Customer behavior: Rich et al. (2010) and Kosiba et al. (2020)
I am passionate about using the brand.
I feel happy when I am interacting with this brand.
I feel very positive about this brand.
Digital transformation: Hossain et al. (2020)
I prefer to interact with companies through their websites and mobile apps rather than by phone or in person.
The increased use of digital platforms by companies has raised my expectations for faster customer service.
Being able to access product information and reviews online is very important to me.