An expanded model of bank reputation in the context of the Covid-19 crisis: a vietnamese contribution.

Reputation is a crucial intangible asset of any business. The model of corporate reputation determinants, including both cognitive and emotional dimensions and their interactions, may vary in different contexts and industries. The purpose of this paper is to examine the determinants of bank reputation in the context of the Vietnam banking sector during the Covid-19 crisis. The conceptual framework was developed from both exploratory research with in-depth interviews and the literature. A structural equation model linking both emotional and cognitive antecedents to each other and bank reputation is tested using data from a sample of 318 Vietnamese individual bank customers. The research results indicate that apart from customers' perceptions about their banks' products and services, social responsibility, vision and leadership, financial capacity, customer satisfaction and trust which are suggested from the literature, banks' ability to provide risk management solutions to customers also has a positive impact on bank reputation. In addition, customer trust totally mediates the effects of customers' perceptions about their banks' offerings and social responsibility on bank reputation. The findings imply multiple ways in which both cognitive and emotional variables should be considered to build bank reputation, in which, building customer trust and providing risk management solutions to customers are the keys. The study is noteworthy that given a special research context, it finds the invalidity of some bank characteristics in signalling bank reputation though they have been repeatedly mentioned as determinants of corporate reputation from the relevant classical postulates.

Introduction

The role of corporate reputation in a business has been affirmed in many theories and endorsed in a great number of empirical studies. According to the resource-based view, corporate reputation has all characteristics of an intangible resource which could ensure sustainable competitive advantage for a firm including “valuable”, “inimitable”, “non-substitutable” and “unique” (Barney 1991; Coombs 2007). From the perspective of the signalling theory, reputation is considered as a market signal for a business’s crucial features that could initiate more profitable sales by mitigating customers’ perceived risks and thereby, reducing time and efforts spent on bargaining (Almeida and Coelho, 2019; Podolny, 1993). The strong impact of corporate reputation on various proxies of business performance such as profit growth, return on equity, and return on assets has been widely affirmed in the literature (Arbelo and Pérez, 2001; Roberts and Dowling 2002; Eberl and Schwaiger 2005). In the stock market, a reputed firm could attain more favourable assessments while reducing investors’ uncertainty, therefore, often gains better forecasts of earnings and higher market-to-book value of equity compared to other competitors (Srivastava et al. 1997; Jones et al. 2000). Especially, when the market experiences an unexpected downturn, a favourable reputation could save firms from a sharp decrease in their shares’ value (Rose and Thomsen 2004). In the bank marketing context, improving bank reputation is considered as a good way to enhance customer loyalty (Bontis et al., 2007; Manohar et al., 2019; Narteh and Braimah 2019; Özkan, 2019; Ruiz et al. 2016), and thereby, sustain banks’ financial performance (Deephouse 1997, 2000; Doan et al. 2020). The role of corporate reputation in the banking industry is even more highlighted due to its nature of service intangibility which creates more information asymmetry and uncertainty (Kim and Choi 2003; Walsh and Beatty 2007).

The novel coronavirus disease, also known as SARS-CoV-2 or Covid-19 originating in China at the end of 2019 has continued to spread globally (Ye et al. 2020). This pandemic not only results in a rapid increase in deaths but also causes mental issues such as anxiety and fear, psychological distress, sleep disturbance, etc. (Duong 2021; Feng et al. 2020; Lee et al. 2020) and severely affects financial well-being due to job loss and pay cut (Barrafrem et al. 2020; Tran et al. 2020). During this struggling period, many individuals are living on “the brink of the financial meltdown”, hoping to meet monthly and even daily financial needs while worrying about future finances. Over the years, improving customers' perception of financial health has become the core goal of many commercial banks in the world, thereby helping customers have a good life and increasing customer engagement (Shiller 2012). As demand for financial services is relatively sensitive to customers’ perceived risks and uncertainties, the Vietnam banking sector has been badly affected by the Covid-19 pandemic since early 2020. According to the State Bank of Vietnam (2020), the credit growth in the Vietnam banking system was only between 0.1% to just below 2% during the period from January to April 2020, much lower than that of the same period in 2019 (between 2 and 4%). Those figures imply early adverse impacts of the Covid-19 crisis on consumption and investment among bank customers as resulted from their uncertainties about the economic outlook. This frame may also change customers’ expectations from the banking system and hence, the way they evaluate bank reputation. To our best knowledge, Ruiz et al. (2014) is the only research that examines the reputation of Spanish financial institutions among their customers in the context of economic crisis. However, given the unprecedented detrimental impacts of the pandemic on various aspects of social and economic life at a global scale and the vulnerability of Vietnam economy (as compared to Spain), it is worthwhile to revisit the research by Ruiz et al. (2014) in the context of the Covid-19 crisis. Specifically, this study aims to answer the question regarding what are the factors that affect Vietnamese customers’ perception of bank reputation during the Covid-19 crisis.

In this study, based on the literature about corporate reputation and the theoretical underpinnings of the signalling theory, we first explored the antecedents of bank reputation during the Covid-19 period with in-depth interviews on 20 Vietnamese bank customers to propose a conceptual model and relevant hypotheses. A quantitative survey was then conducted on 318 bank customers from all walks of life for testing the hypothesized relationship. Notably, based on the findings, brand communication, technology innovation, and working environment demonstrate no significant impact on bank reputation though they have been repeatedly mentioned as determinants of corporate reputation in the relevant literature. These anomalies provide an important theoretical contribution regarding the validity of a firm’ past actions or characteristics, as signals, in contributing to its reputation. Specifically, this implies the possibility of the moderating roles of contextual factors on these relationships. Moreover, this research also gives insights into the interaction among antecedents of bank reputation by examining the mediation effects of two emotional factors including customer satisfaction and trust in the impacts of customers’ perceptions about banks’ products and services, social responsibility, communication, technology application and risk management capacities (cognitive factors) on bank reputation.

Theoretical framework and hypothesis

Signalling theory and corporate reputation

Signalling theory emerges from the issue of information asymmetry in the communication process (Spence 2002). Specifically, a receiver may not directly understand the message sent between two parties. Instead, he or she must decode the messages about non-observable qualities based on more perceivable indicators. Spence (1973) is the pioneering author who proposed the first model of signalling. He took an example of how education functions as a signal for an individual in the labour market where potential employers may have insufficient information about job candidates’ capacities. Due to the issue of information asymmetries, job seekers, need to signal their abilities through the level of education they attain. Given better existing abilities and skills, candidates with better capacities bear fewer costs than others in pursuing higher education (Spence 1973). Therefore, higher education is a trustworthy signal for an individual’s capacities.

Similarly, reputation is also an unobservable quality of a business. Under the perspective of the signalling theory, Davies et al. (2003) define the corporate reputation as a reflection of past actions of the business, providing signals to stakeholders about possible future output. Upon this definition, the “past actions” of the firms will signal its reputation which, in turn, signal the firms’ future success. More specifically, reputation is also seen as a proxy for the quality of the company's products and services and, therefore, influences customers' purchasing decisions (Fombrun 1996). In addition, it is also the driving force to increase employee loyalty as well as attract a source of high-quality employees by giving signals about a great working environment (Fombrun and van Riel 1997).

The literature suggests two methods for conceptualizing corporate reputation: as a single-faceted or a multi-faceted construct. As a single-faceted concept, corporate reputation is measured as the stakeholders ‘overall evaluation of a business. However, this measurement does not reveal information about specific elements which contributes to a positive reputation and those which harms a reputation. The multi-faceted approach, therefore, is used more popularly in measuring corporate reputation. Based on this approach, there are several popular corporate reputation models emerged in previous studies such as Reputation Quotient (Fombrun et al. 2000), Corporate Reputation (Brady 2003), Reputation Index (Craven et al. 2003), a Formative Measure of Corporate Reputation (Helm 2005), and Reptrak Pulse (Ponzi et al. 2011). These measures were either revisited or expanded in different researching contexts using data collected from a single group of stakeholders or a mixed group of stakeholders. However, customers represent the most popular target sample for examining antecedents of corporate reputation since they have relatively comprehensive knowledge of the organizations, acquired through both mass media and their actual experiences with the business. This enables them to provide more consistent and reliable judgments about various dimensions of corporate reputation (Ruiz et al. 2014). According to Dowling (2001), a crucial criterion to select target groups for evaluating corporate reputation is that they should have a relationship with the business. Customers not only have direct associations with the firms as the customer–supplier relationship but also may form other types of relationships in the future as investors or even employees. Furthermore, the judgments they make about the suppliers result in stakeholders’ key decisions involved with purchasing, investment or selecting working environment—all of which are crucial for the firms’ survival and sustainable development (Walsh and Beatty 2007). Moreover, bank customers those open accounts and deposit money into a bank are not only customers but also investors of that bank. Their judgments about their banks, therefore, are crucial in measuring and evaluating bank reputation. Indeed, the literature presents rich empirical evidence in which bank reputation is widely measured upon customers’ surveys (Wang et al. 2003; Cintamür and Yüksel 2018; Narteh and Braimah 2019; Ruiz et al. 2014; Ruiz and García, 2019). In this study, we also select bank customers as the target sample to examine determinants of bank reputation. Table 1 presents detailed determinants of customers’ perception of corporate reputation in the literature.

Table 1

Determinants of corporate reputation

Groups	Determinants	References
Customers’ perceptions based on their own experiences	Offer/ Customer care/ Products and services	Akdag and Zineldin (2011); Bravo et al. (2009); Chen and Chen (2009); Fombrun et al. (2000); Highhouse et al. (2009); Kanto et al. (2016); Liu et al. (2017); Martín et al. (2006); Nguyen (2010); Walsh et al. (2009); Ruiz et al. (2014); Walsh and Beatty (2007)
	Social responsibility/Social action	Bravo et al. (2009); De Quevedo et al. (2007); Fombrun et al. (2000); Highhouse et al. (2009); Kanto et al. (2016); Liu et al. (2017); Martín et al. (2006); Sen and Bhattacharya (2001); Walsh and Beatty (2007)
	Innovation/ Technical application	Courtright and Smude (2009); Bravo et al. (2009); Martín et al. (2006); Walsh and Beatty (2007)
Customers’ perceptions based on mass media	Vision and leadership	Fombrun et al. (2000); Jin and Yeo (2011); Kanto et al. (2016); Liu et al. (2017); Martín et al. (2006); Mkumbuzi (2015); Sotillo (2010); Ruiz et al. (2014); Walsh and Wiedmann (2004)
	Working environment	Burke et al. (2011); De la Fuente and De Quevedo (2003); Fombrun et al. (2000); Kanto et al. (2016); Liu et al. (2017); Martin and Groen-in’t Woud (2011); Walsh and Beatty (2007)
	Financial capacity	De la Fuente and De Quevedo (2003); Fombrun et al. (2000); Kanto et al. (2016); Lange et al. (2011); Walsh and Beatty (2007)
Customers’ emotional factors	Satisfaction	Jamal and Naser (2002); Hansen and Sand (2008); Helm et al. (2010); Ladhari et al. (2011); Ruiz et al. (2014); Walsh et al. (2009)
	Trust	Newell and Goldsmith (2001); Rose and Thomsen (2004); Reputation Institute (2012); Ruiz et al. (2014); Walsh et al. (2009)

Methodology and hypothesis development

Stage 1: qualitative research

We first conducted qualitative research (Study 1) using structured in-depth interviews on bank customers to qualitatively explore relevant factors that influence their perception of bank reputation during the Covid-19 crisis. Specifically,20 individuals who are currently customers of several banks in Hanoi, including joint-stock, state-owned, private, and foreign-invested banks were invited to the 30-min interview upon their consensus in early March 2020. Based on the theoretical underpinnings of the signalling theory, during the interview, we give the respondent the lists of commercial banks and ask them to choose the most reputable bank based on their perception as well as underlying reasons for their selection. The findings from the interview research were then blended with the relevant literature in corporate reputation and bank marketing to conceptualize specific determinants of bank reputation as well as develop hypotheses and a conceptual model. A quantitative study using the survey method (Study 2) was followed to collect quantitative data for testing the conceptual model.

The attributes indicated to be the most important factors affecting the customers’ perception of the bank reputation include (1) the customers’ evaluation of products and services, social responsibility, technology innovation, communication, and risk management based on their own experience; (2) customers’ commentary on other aspects that they have not experienced but can be “heard about” or known through the media or word-of-mouth effects, including the bank’s vision and leadership, working environment, and financial capacity; and (3) the emotional factors of the customer, including satisfaction and trust. This suits the conceptualization of corporate reputation with both cognitive and affective dimensions (Fombrun 1996; Siltaoja 2006). Customer satisfaction and trust are not only two key prerequisites of the business's reputation (Walsh et al. 2009; Helm et al. 2010; Ponzi et al. 2011) but also the consequences of customers’ interactions with their suppliers (Berry and Parasuraman 1991; Chaudhuri and Holbrook 2001; Cronin et al. 2000; Krepapa et al. 2003; Sekhon et al. 2014). However, there is hardly a study that detects the mediating role of customer trust and loyalty in explaining the effect of customers’ own experience about the banks and their perception of bank reputation. Moreover, in the context of the Covid 19 crisis, our qualitative study also reveals two additional factors that may affect bank reputation, including the quality of communication and risk management. Findings from the in-depth interview show that those factors help neutralize the uncertainty among bank customers about their financial health during the Covid-19 pandemic. As a result, they are impressed and highly appreciate banks that provide effective communication and demonstrate a high ability to manage risks. By adding these two factors into the bank reputation model, this research will yield noteworthy implications that not only expand the literature on determinants of bank reputation but also provide valuable suggestions for banks to maintain and enhance their reputation during the Covid 19 crisis. Figure 1 below presents the conceptual model of this research:

Fig. 1

Model 1

For clarifying the reasoning of each hypothesized relationship in our conceptual framework, we review the literature followed by the theoretical background and empirical evidence supporting the hypothesis.

Offerings and bank reputation

Amongst the perceptional factors affecting reputation, the quality of products and services is frequently found in numerous studies (Akdag and Zineldin 2011; Chen and Chen 2009; Kanto et al., 2016; Liu et al. 2017; Newman 2001; Roberts and Dowling 2002; Walsh et al. 2009) as the most crucial determinant of corporate reputation. Put it simply, a business could attain a favourable reputation if its offerings are perceived as high-quality. Product quality help companies maintain their prominence and obtain the trust of various stakeholders (Fombrun 1996). In the banking service context, Lewis and Soureli (2006) argued that exceptional service quality can create a “hallo effect” that affects other aspects of a bank's reputation. Besides, customer service-related aspects and the organization's treatment of employees is the most crucial factors in analyzing the service provider's reputation from customers’ point of view (Walsh et al. 2009). However, most studies using the generalized model do not integrate this factor since the analytical unit does not have a direct relationship with the organization, hence, it is impossible to evaluate the aspect of customer service, friendliness, or skills of the staff. According to Nguyen (2010), customer care is a crucial factor for service providers to build their own identity and reputation.

H1. Perceived quality of products and services has a positive effect on bank reputation.

Social responsibilities and bank reputation

Corporate Social Responsibilities (CSR) studies provide various approaches in defining and measuring perceptions of CSR. According to McGuire (1963), social responsibility means that businesses complete beyond their normal economic and legal obligations to demonstrate their social responsibilities. Carroll (1979) expands this definition and proposes that corporate social responsibility includes economic, legal, ethical, and other social expectations for organizations at a certain period. As environmental pollution becomes a critical issue around the world, the concept of firms’ social responsibility is expanded to include the responsibility for the society and the environment surrounding them (McIntosh and Mohan, 1999). As globalization takes place, Warhurst (2001) further broaden the concept of CSR as “the internalization of the business’ social and environmental impacts through proactive pollution prevention and social impact assessment to predict and avoid harms while optimizing corporate’ benefits”. In general, CSR is organizational behaviour and awareness beyond its basic responsibilities to benefit shareholders, customers, employees, society, and the environment.

Aspects related to corporate social responsibility, including social, philanthropy and environmental activities, are included in all generalized models of reputation. Consumers are increasingly appreciating CSR because they expect businesses to actively perform responsible actions (McWilliams et al. 2006). Moreover, Mattila et al. (2010) demonstrate that the messages of social responsibilities can reduce the negative impact of a media crisis on consumer perception, as proved in the case of infamous companies, such as oil and gas or tobacco companies, those sought to reimagine themselves from social projects. Therefore, the demonstration of social responsibility will help reinforce the organization's acceptance and reputation (Bravo et al. 2009; Highhouse et al. 2009; Kanto et al. 2016; Liu et al. 2017; Martín et al. 2006; Walsh and Beatty 2007).

H2: Perceived social responsibilities have a positive effect on bank reputation.

Brand communication and bank reputation

In service marketing, due to the lack of physical presence of services such as packaging and labelling, corporate branding is of the utmost importance. Brand communication ensures a brand idea or image is brought to the market to affect the perceptions of target audiences about the unique selling points and other branding messages. Nowadays, upon the technological advances in communication, brand communication could be done directly through the employees or various media through the process of service delivery. Brand communication could be conducted either one-way or two-way. This refers to whether the brand interacts with customers indirectly or directly and whether open dialogue with customers is available or not (Sahin et al. 2011). Brand communication could take two primary forms. The first includes communication activities in which the firms take initiatives in advertising a brand's message to consumers via media channels, and thereby, control how consumers think and feel towards the brand (Bansal et al. 2004). The second defines brand communication as the ability of an enterprise to proactively provide customers with timely and reliable messages or to solve service-related problems (Ball et al. 2004).

Findings from the in-depth interview also revealed that during the Covid-19 crisis, bank customers may face different types of financial obstacles. They, therefore, highly appreciate banks that take the initiatives to communicate with customers and give valuable information and advice. Correspondingly, brand communication can increase customers’ awareness of an organizations’ responsibility, transparency, ethics, and trustworthiness (Ball et al. 2004) that may enhance bank reputation. The literature suggests that media exposure, as an effort of brand communication, is a crucial determinant of corporate reputation (Liu et al., 2017). In this research, we take the definition of brand communication proposed by Ball et al. (2004) to provide a more comprehensive conclusion about the relationship between communication and bank reputation.

H3: Effective communication has a positive impact on bank reputation.

Technology innovation and bank reputation

A business's degree of innovation is an increasingly important aspect in evaluating a company's reputation. The analysis of this variable as a component of reputation has been applied in many studies (Walsh et al. 2009; Akdag and Zineldin 2011). The yearning for innovation not only shows the ability of the organization but also reflects its culture and identity. The superiority or popularity of the company, which is considered the premise of reputation, will be increased if the enterprise applies new technology in service provision or introduces superior and innovative products to the market. This will facilitate consumer interest and their positive attitude toward the business (Henard and Dacin 2010).

H4: Banks’ ability to apply new technology has a positive effect on bank reputation.

Risk management and bank reputation

One of the distinct characteristics of banking services is the high level of risks. These risks derive not only from the banks’ performance but also from many objective elements of the financial and business environment. Findings from the in-depth interview indicate that the bank's ability to manage risk is considered as one of the important factors displaying the banks’ ability to eliminate their default risks and insolvency risks while providing suitable risk management services that could protect customers against the potential loss caused by the Covid-19 crisis. The banks’ capacity in risk management is affirmed to be a crucial determinant of either bank performance or profitability (Hamid and Adel 2013; Indiael and Dickson 2013; Iwedi and Onuegbu 2014; Samuel et al. 2012). Moreover, Danjuma et al. (2016) also found a close association between a bank’s risk management ability and customer satisfaction—an antecedent of bank reputation. Bank customers, especially depositors are mostly risk-averse investors (Summers 2000). Meanwhile, financial variables such as stability, changes in profitability and the level of financial risk could affect investors’ evaluation of corporate reputation (Blajer-Gołębiewska and Kozłowski, 2016). The linkage between risk management and corporate reputation has been established in some previous studies. As the risk of reputation loss is derived from all company risks, the quality of enterprise risk management systems is found to influence reputation creation, enhancement, and protection (Gatzert and Schmit 2016; Pérez-Cornejo et al. 2019).

In this study, we hypothesize that:

H5: The ability to manage risk has a positive relationship with bank reputation.

Vision and leadership capacity and bank reputation

Leadership, reflected through the actions taken by company leaders, is an aspect appearing in many reputation-rating models (Bravo et al. 2009). According to Khurana (2002), the today criteria for evaluating a good leader have from the professionalism and honesty of the leader to his charisma and leadership skills. religion. A competent and influential leader, an intangible asset, can create a corporate governance process that enhances the reputation of the leader himself (Sotillo 2010); hence, establishing a process of "transferring reputation" from leader to organization. The literature review reveals mounting empirical evidence about the relationship between either corporate governance (Mkumbuzi 2015) or vision and leadership capacity on bank reputation (Jin and Yeo 2011; Kanto et al. 2016; Liu et al., 2017; Martín et al. 2006); Sotillo 2010; Ruiz et al. 2014).

H6: Customer evaluation of leadership capacity has a positive effect on bank reputation.

Working environment and bank reputation

This factor addresses the client's perceptions of how the organization and the managers treat employees, as well as their expectations about the capacities of the employees (De la Fuente and De Quevedo 2003). Upon the signalling theory, the extent to which a firm could attract talents, retain employees and provide high-quality training programs may become a signal which impresses other stakeholders and build a reputation for the firm, as the employer (Martin and Groen-in’t Woud 2011). In this regard, the employer and their manner in treating employees become the strategic protector of the organization’s reputation (Burke et al. 2011).

H7: Customer assessment of the working environment has a positive impact on bank reputation.

Financial capacity and bank reputation

Within most reputation rating models, this factor refers to the capability of companies in generating benefits to ensure survival and growth, as well as securing customer deposits in the banking sector. Positive financial indicators which signal good health and prestige of the bank will induce a favourable assessment among the public for the bank (Rose and Thomsen 2004). Specifically, the profitable performance of the business in the past will cause economic forecasters to provide a favourable prediction about the future value of the business and thereby, help strengthen the reputation of the business (Delgado et al. 2008). The linkage between financial capacity and corporate reputation and bank reputation, in particular, is affirmed in many previous studies (De la Fuente and De Quevedo 2003; Fombrun et al. 2000; Kanto et al. 2016; Lange et al. 2011; Walsh and Beatty 2007).

H8: Financial capacity has a positive effect on bank reputation.

Satisfaction and trust and bank reputation

Customer satisfaction is widely used as a metric in evaluating the effectiveness of a business’s marketing activities. Cronin et al. (2000) define customer satisfaction as the positive state of mind a customer obtain after consuming a product or experiencing a service given their comparison between what they received from the product or service and what they expect before their purchasing or consumption. In the context of the service sector, each consumer always establishes two service quality thresholds: the level that they desire and the acceptable one (Berry and Parasuraman 1991). The gap between them is known as the tolerance zone within which the customer is satisfied with the service they receive. If the service quality exceeds the desired level, the customer will be extremely satisfied and increase their loyalty. Previous studies have shown that customer satisfaction could be measured upon their satisfaction with each transaction or specific aspects with service providers (Andreassen 2000) and cumulative measures related to overall customer satisfaction based on all service experiences (Krepapa et al. 2003). However, Rust and Oliver (1994) recommend that the latter is more meaningful in predicting consumer behaviour. Previous studies mostly use cumulative measures in testing conceptual models (Gupta and Zeithaml 2006).

Trust is one of the factors determining customer loyalty (Chaudhuri and Holbrook 2001; Sirdeshmukh et al 2002). While reliability is an attribute of a brand, product, service, or organization; trust refers to how customers are willing to rely on or cooperate with the trustee on a perceptual basis (rational assessment of reliability) or an emotional basis (care and empathy) (Sekhon et al. 2014). Trust is driven by either trustworthiness—the expectation that what a company says or offers can be trusted through the keeping of its promises (Chaudhuri and Holbroook, 2001) or kindness—the degree to which the company cares about and dedicates itself to the well-being of its customers (Sirdeshmukh et al., 2002).

Although most corporate reputation models only use cognitive factors, when reputation is measured upon customers’ perspectives, satisfaction and trust are employed as two emotional factors in the reputation model (Rose and Thomsen 2004; Hansen and Sand 2008; Ladhari et al. 2011). The direct experience with the supplier allows customers to assess a business’ image and reputation (Giogia et al. 2000). In this regard, the extent to which a customer satisfies and trust their suppliers, are the prerequisites of the business's reputation (Walsh et al. 2009; Helm et al. 2010; Ponzi et al. 2011).

H9: Customer satisfaction has a positive impact on bank reputation.

H10: Customer trust has a positive impact on bank reputation.

The intermediate role of satisfaction and trust

The quality of customer relationships is a vital concern of every company and is driven by trust and customer satisfaction (Cheng et al., 2008). Product and service quality is considered as the basic factor laying the foundation for customer satisfaction and trust, hence nurturing the long-term relationship between customers and their suppliers. The positive association between service quality and customer satisfaction has been affirmed in previous studies (Anderson et al. 1994; Berry and Parasuraman 1991; Rust and Oliver 1994). They find out that customers’ evaluation of service quality that they receive will form their satisfaction to the supplier. Rust and Oliver (1994) argue that improving service quality leads to a growth in perceived quality, therefore, increasing consumer satisfaction. Besides, trust includes a belief in the exchange of kindness, competence, honesty, and the ability to predict partners, and is seen as an essential element of successful relationships (Chaudhuri and Holbrook 2001). In traditional business environments, trust is often created in the process of customers observing and evaluating employees' knowledge and ability to respond, those are one of the aspects of service quality (Berry and Parasuraman 1991).

CSR is believed to have a direct effect on both trust (Chun and Bang 2016) and customer satisfaction (Brown and Dacin 1997). In other words, positively perceived CSR leads to a positive review of the company, which then favourably influences product or service rating, hence, satisfaction and trust.

The positive associations between brand communication and either customer satisfaction or trust are also affirmed in Grace and O’Cass (2005). Specifically, when customers form positive feelings and attitudes towards a certain brand, the message about the brand will be conveyed more effectively. As a result, a consumer's positive attitudes towards controlled communications patterns shape their attitudes about products according to what they think and feel and enhance their trust in the supplier. Communication is often used as a tool of relationship marketing aimed at enhancing customer relationship quality (Anabila et al. 2012; Chakiso 2015). The direct positive effect of brand communication on customer relationship quality and customer loyalty has also been confirmed in many previous studies (Jones and Farquhar 2003).

Nowadays, with the continuous development of science and technology in the context of the industrial revolution 4.0, banks can meet the transaction needs of customers anytime, anywhere with speed and accuracy while interacting more effectively with customers through “means” such as Internet Banking, Mobile Banking, and ATM systems. By applying technology to improve service quality and the value provided to customers, banks can enhance customer satisfaction and build trust from customers (Padmavathy et al. 2012).

Risk management is one of the inevitable needs of customers when assessing banking and financial services. A bank that could provide risk management tools and services to its customers will meet their expectations, and thus, easily acquire customer loyalty. In addition, the bank's commitment to managing financial risks through specific tools and services will help it build customers' confidence in its capacity as well as transparency and customer’s goodwill.

Based on the above analysis, we hypothesize the mediating role of satisfaction and trust as follows:

H11a: Satisfaction plays a mediating role in the relationship between perceptions of product quality and bank reputation.

H11b: Satisfaction plays a mediating role in the relationship between the customer's perception of social responsibility and bank reputation.

H11c: Satisfaction plays a mediating role in the relationship between the perception of communication quality and bank reputation.

H11d: Satisfaction plays a mediating role in the relationship between technology adoption and bank reputation.

H11e: Satisfaction plays a mediating role in the relationship between risk management and bank reputation.

H12a Trust plays an intermediate role in the relationship between the perceived quality of products and services and bank reputation.

H12b: Trust plays a mediating role in the relationship between a customer's perception of social responsibility and bank reputation.

H12c: Trust plays a mediating role in the relationship between the perceived quality of communication and bank reputation.

H12d: Trust plays a mediating role in the relationship between technology applicability and bank reputation.

H12e: Trust plays a mediating role in the relationship between risk management capabilities and bank reputation.

Stage 2: quantitative research

A survey method was employed to collect quantitative data for testing the conceptual model. A questionnaire was used as a tool for data collection. The detailed measurement properties of bank reputation and its potential determinants, including products and services, working environment, CSR, leadership capacity, financial capacity, satisfaction, and trust were selected from the relevant literature on bank reputation (Boshoff 2009; Fombrun et al. 2000; Helm, 2005; Ladhari et al. 2011; Lewis and Soureli 2006; Walsh and Beatty 2007). On the other hand, the new proposed constructs are scored based on measurement scales which were either adapted from literature on relationship quality or developed by the research team. Specifically, brand communication was measured with 5 items as proposed by Ball et al. (2006). In addition, a three-item scale was adopted to score technology application capacity was adapted from Padmavathy et al. (2012). Risk management was designed by the research team as a dummy variable which takes 1 if the provides risk management solutions to customers and 0 if otherwise. The Likert scale with a series of assessment statements about the object's attributes from completely agree to completely disagree is used for scoring latent constructs. Before the official survey, the questionnaire was distributed to 30 bank customers to collect their feedback on its quality and improve accordingly (Hague et al. 2004).

Hanoi city was selected as the venue for data collection since most commercial banks in Vietnam have either headquarters or transaction offices in this city. Based on a list of transaction offices of 29 banks across the city, 30 transaction offices are randomly selected for the intercept survey. Specifically, initial 600 paper-based questionnaires were distributed face-to-face to customers at 30 chosen transaction offices on a first-come-first-serve basis during March and April 2020. Due to the low response rate and missing data, only 318 responses are valid. Regarding sampling structure, customers of state-owned joint-stock banks, private joint-stock banks and foreign banks accounted for 56.3%, 32.4% and 11.3% accordingly. Although there is a large difference in the percentage of customers coming from these 3 groups of banks, this ratio is quite reasonable because it reflects the market share of banking services in Vietnam. Regarding gender, the majority of research samples (58.8%) are female customers. However, the level of difference between male and female customers is not significant. In terms of age, 74.5% of respondents are from 26 to 45 years old. This proportion is suitable since the young customer segment has long dominated the Vietnamese banking market. In addition, 95.9% of the respondents have a university education or higher. This almost absolute percentage is probably because the sampling was conducted in Hanoi, where the population has a high level of education. However, this can also be considered a reasonable rate because this segment has a high and stable income, playing an important role to banks.

Results

The measurement scales employed in this study are tested following Anderson and Gerbing (1988)’s suggestion on the practical use of structural equation modelling. Specifically, both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to test for the convergent and discriminant validity of the measurement properties for 10 latent variables including customer perception and assessment of banking products and services, social responsibility, brand communication, technology application risk management, customer satisfaction, customer trust and bank reputation.

The factor loadings and t-values resulting from the CFA are presented in Table 2. According to Nunnally and Bernstein (1994), only items that loaded more than 0.5 should be retained. Figures, as shown in Table 2, indicate that all factor loadings are significant and greater than 0.4. Moreover, a CFA on the ten-factor model also indicates that the model demonstrates good fit with the data (CMIN/df = 2162; p = 0.000; RMR = 0.068; GFI = 0.87; CFI = 0.877; AGFI = 0.801). The convergent validity of the measurement scales used in this research is, therefore, confirmed. On the other hand, the EFA with principal factor as extraction method followed by a varimax rotation conducted in SPSS also revealed ten factors emerged as to how they were initially measured. We, therefore, confirm the construct validity and the unidimensionality for the measurement properties (Straub 1989).

Table 2

Confirmatory factor analysis results

Items	Mean	Standard deviation	Factor loading	t-value
SER1	2.53	1.158	0.644	12.425
SER2	2.54	1.201	0.657	12.737
SER3	2.57	1.186	0.903	19.959
SER4	2.61	1.183	0.877	19.15
SER5	2.57	1.200	0.829	–
ENV1	3.30	0.784	0.785	10.922
ENV2	3.34	0.808	0.755	10.87
ENV3	3.19	0.863	0.721	–
CSR1	3.19	0.849	0.774	9.229
CSR2	3.29	0.911	0.646	8.588
CSR3	3.14	0.917	0.627	–
LED1	3.63	0.867	0.671	8.84
LED2	3.17	0.803	0.697	8.957
LED3	3.58	0.866	0.701	–
FIN1	3.04	1.195	0.838	15.496
FIN2	3.31	1.124	0.857	15.874
FIN3	3.08	1.215	0.88	16.333
FIN4	3.16	1.136	0.761	–
COMU1	3.78	0.859	0.643	10.047
COMU2	3.81	0.973	0.644	10.059
COMU3	3.62	0.846	0.736	11.27
COMU4	3.58	0.904	0.678	10.53
COMU5	3.81	0.827	0.716	–
TECH1	2.34	0.975	0.563	9.273
TECH2	2.58	0.988	0.845	12.088
TECH3	2.56	1.009	0.779	–
SATIS1	3.30	0.911	0.739	–
SATIS2	3.76	0.927	0.727	9.035
SATIS3	3.12	0.996	0.437	6.467
TRUST1	3.03	1.062	0.687	8.427
TRUST2	2.92	1.051	0.704	8.53
TRUST3	3.14	1.172	0.566	–
REPU1	2.77	0.888	0.85	–
REPU2	2.89	1.105	0.814	14.975
REPU3	2.57	1.092	0.435	7.499
Model fit indicators: CMIN/df = 2.162; p = 0.000; RMR = 0.068; GFI = 0.87; CFI = 0.877; AGFI = 0.801; “–” denotes to 1

SER Products and services, ENVI Working environment, CSR Social responsibility, LED Vision and leadership, FIN Financial capacity, COMU Communication, TECH Technology innovation, SATIS Customer satisfaction, TRUST Customer trust, REPU Bank reputation

Table 3 demonstrates the reliability coefficients and results from the average variance extracted (AVE) test. According to the figures as presented in Table 3, the Cronbach’s alpha values of all ten variables are either just below 0.7 or higher than 0.7. This indicates their acceptable reliability. Furthermore, all AVE values were greater than the threshold level of 0.5 and also the square of correlations between every two constructs. We, therefore, further verify the convergent validity and discriminant validity of the measurement properties (Anderson and Gerbing 1988).

Table 3

Reliability coefficients and Average variance extracted (AVE) test

	SER	COMU	TECH	CSR	ENV	LED	FIN	SATIS	TRUST	REPU	Cronbach’s Alpha
SER	0.642										0.890
COMU	0.021	0.547									0.796
TECH	0.04	< 0.001	0.633								0.715
CSR	0.015	0.003	0.023	0.581							0.729
ENV	0.003	0.001	0.004	< 0.001	0.703						0.901
LED	0.063	0.014	< 0.001	0.001	0.003	0.587					0.811
FIN	0.08	0.032	< 0.001	0.014	0.005	0.004	0.727				0.762
SATIS	0.061	0.001	0.075	0.001	0.001	< 0.001	0.022	0.607			0.630
TRUST	0.158	0.023	0.003	0.046	0.003	0.016	0.02	0.02	0.579		0.696
REPU	0.187	0.022	0.017	0.03	0.001	0.016	0.127	0.055	0.112	0.654	0.713

Square roots of average variances extracted (AVEs) shown as bolded numbers

Based on the above results, we retain all measurement items for each construct in the conceptual model for further hypothesis testing.

A structural equation model linking 8 independent variables (products and services, corporate social responsibility, brand communication, technology application, risk management, working environment, financial capacity, and leadership) and 3 dependent variables (satisfaction, trust, and loyalty) was tested in AMOS 22. A path analysis procedure, as recommended by Oh (1999), is adopted to estimate direct relationships. On the other hand, we follow the guidelines for mediation tests suggested by Baron and Kenny (1986). Specifically, the mediation effect occurs when the impact of the independent variable (X) on the dependent variable (Y) operates through a third variable (M), also known as the mediator. In this way, perfect mediation occurs if the effect of X on Y decreases to 0 when M is included in the model while partial mediation occurs when the effect of X on Y decreases by a “nontrivial amount” with M in the model. Based on that, to test the mediating roles of customer satisfaction and customer trust, Model 2 (where customer satisfaction is removed) and Model 3 (where customer trust is absent) are constructed and compared to Model 1 (the original model with full hypothesized relationships).

First, Table 4 presents the results of the analysis including the correlation coefficients and the significance of the direct relationships in the proposed model.

Table 4

Results for hypothesis testing

Construct path	Model 1	Model 2	Model 3
SER – >  SATIS	0.149*	–	0.150*
CSR – > SATIS	0.001	–	0.04
COMU – > SATIS	0.033	–	0.032
TECH – > SATIS	0.396**	–	0.375**
RIM – > SATIS	0.04	–	0.049
SER – > TRUST	0.250**	0.251*	–
CSR – > TRUST	0.559**	0.552**	–
TECH – > TRUST	0.144*	0.130*	–
COMU – > TRUST	0.2*	0.199*	–
RIM – > TRUST	0.021	0.022	–
SATIS – > REPU	0.191*	–	0.220**
TRUST – > REPU	0.374*	0.410**	–
SER – > REPU	0.008	0.025	0.098*
ENV – > REPU	- 0.026	0.03	0.001
CSR – > REPU	0.02	0.028	0.222*
FIN – > REPU	0.234*	0.254*	0.215*
LED – > REPU	0.109*	0.1*	0.099*
TECH – > REPU	0.008	0.078	0.043
COMU – > REPU	0.090	0.097	0.010
RIM – > REPU	0.293**	0.297**	0.298**
Model fit indicators
CMIN/df	2.143	1.953	2.164
CFI	0.877	0.908	0.887
GFI	0.834	0.857	0.849
AGFI	0.829	0.824	0.814
RMR	0.07	0.063	0.066

*p < 0.05; **p < 0.001; SER Products and services, ENVI Working environment, CSR Social responsibility, LED Vision and leadership, FIN Financial capacity, COMU Communication, TECH Technology innovation, RIM Risk management, SATIS Customer satisfaction, TRUST Customer trust, REPU Bank reputation

The analysis results show that variables including customers’ perception about service quality and banks’ ability to apply technology have a positive impact on satisfaction and trust. However, two variables, including perceived corporate social responsibility and brand communication, only directly and positively influence customer trust without having significant impacts on satisfaction.

Of the 10 factors that affect the reputation of a bank as featured in our proposed conceptual model, there are only 5 factors that have a positive, direct and statistically significant impacts on a bank's reputation including customer satisfaction, customer trust, financial capacity, vision and leadership and banks’ capacity to manage risks (accept H5, H6, H8 H9 and H10 and reject H7).

Since corporate social responsibility, brand communication, and risk management have no impacts on customer satisfaction while risk management also does not have a statistically significant relationship with customer trust, based on the mediating conditions suggested by Baron and Kenny (1986), the hypotheses H11b, H11c, H11e and H12e are all rejected.

The test for mediation effects, therefore, was only applied to examine the mediating role of satisfaction in impacts of products and services and technology application on bank reputation as well as the mediating role of trust in the effects of 4 variables including products and services, corporate social responsibility, technology application and brand communication on bank reputation.

Table 4 also shows the path coefficients from the original model and the modified models (Figs. 2, 3). Those figures are employed to check the mediating conditions proposed by Baron and Kenny (1986).

Fig. 2

Model 2

Fig. 3

Model 3

In a comparison of path coefficients as shown for Model 1 and Model 2 (after customer satisfaction is removed), we found that in the original model (Model 1) and Model 2, the impacts of both customers’ perceptions about products and services and banks’ ability to adopt technology and bank reputation were not statistically significant. Based on the mediating conditions as proposed by Baron and Kenny (1986), these results confirm that customer satisfaction has no mediating role in these relationships (reject H11a and H11d).

Similarly, in a comparison of path coefficients as shown for Model 1 and Model 3 (after customer trust is removed), we found that in the original model (Model 1) and Model 3, the impacts of both brand communication and technology application on bank reputation are not statistically significant. Based on the mediating conditions as proposed by Baron and Kenny (1986), these results confirm that customer trust has no mediating role in these relationships (reject H12c and H12d).

However, compared to Model 1, after customer trust is removed from the original model, the relationship between either customer perceptions of banking products and services or the banks’ corporate social responsibility and bank reputation turn from insignificant to statistically significant. Based on the mediating conditions as proposed by Baron and Kenny (1986), these results confirm that customer perceptions of banking products and services and the banks’ corporate social responsibility have positive impacts on bank reputation. However, these relationships are totally mediated by customer trust (accept H1, H2, H12a and H12b).

Since technology application and brand communication have no impact on bank reputation even when customer satisfaction and trust are removed from the original model, we conclude that there is no relationship. relation between these two variables and bank reputation (reject H3 and H4).

Conclusion and practical implications

This research expands existing knowledge about bank reputation by adding new factors influencing bank reputation and providing insights into the relationships among cognitive and emotional determinants of bank reputation in the context of the Covid-19 pandemic. There are two primary sets of hypotheses in this study.

The first set was about the impacts of cognitive and emotional factors which are suggested from the literature on corporate reputation in the context of the banking sector. In line with previous studies, the findings indicate that customers’ perceptions about their banks’ products and services, social responsibility, vision and leadership, financial capacity, customer satisfaction and trust have positive impacts on bank reputation (Bravo et al. 2009; Fombrun et al. 2000; Highhouse et al. 2009; Ladhari et al. 2011; Lange et al. 2011; Martín et al. 2006; Reputation Institute 2012; Walsh and Beatty 2007). From the customer perspective, we also find a significant positive contribution of risk management to bank reputation. This finding is consistent with previous studies which examine such a relationship based on objective measurement (Gatzert and Schmit 2016; Pérez-Cornejo et al. 2019). Given the distinct features of banking products and services that are associated with a certain level of risk and uncertainty and the underdeveloped institutions in Vietnam, especially during the Covid-19 period, this study highlights the role of banks’ capacity to manage risks in enhancing bank reputation. However, contradicting the literature (Courtright and Smude 2009; García de los Salmones et al., 2009; Liu et al., 2017; Martin and Groen-in’t Woud, 2011), we find that neither brand communication, technological innovation nor working environment has a significant impact on bank reputation. Given that corporate reputation is enhanced by signals embedded in its past performances, the refutation of these hypotheses could be explained from the theoretical perspectives of the signalling theory. First, Searcy and Nowicki (2005) assert that not every signal is honest, however, only “honest” signals can be sustained. Based on the individual-selectionist approach in evolutionary theory, Dawkins and Krebs (1978) argue that deceptive signals may benefit individuals not endowed with the superior qualities as anticipated based on the signal. However, they are finally ignored by the receivers who, eventually, will realize that such signals do not entail any benefits for them. In the context of Vietnam, as a transitional economy, the poorly designed and weakly enforced institutions towards information transparency may lead to low confidence in information quality. This may become more severe during the Covid-19 crisis where the difficult economic conditions lead to the increase of fraudulent activities. These negative social experiences, hence, deteriorate individuals’ trust in the information they are exposed to (Schwertera and Zimmermann, 2020). In addition, the banks’ communication activities may not effective in meeting customers’ expectations as intended. As the customers perceive that the banks’ messages may not reflect the truth while the advice from banks is not helpful as expected, they may disregard this signal when evaluating bank reputation. Second, Grafen (1990) and Zahavi (1975) contend that costly signals can indeed be evolutionary stable since only individuals with superior qualities could sustain the handicaps that such signal entails. Likewise, Spence (1974) suggest that educational attainment could function as a stable signal in an employer-employee interaction since only individuals with high productivity could attain higher education at lower costs in terms of time and effort. Customers’ perception of corporate reputation is built upon some signals from the business’s past achievement as compared to other leading competitors (Fombrun 1996). In the context of the increasingly competitive banking market, most Vietnamese commercial banks employ marketing communication to send branding messages and deliver PR stories to customers in similar manners. Despite that in the conditions of Covid-19, the introduction of modern digital technologies and security technologies by banks naturally increased, the level of technological application among Vietnamese commercial banks are almost indifferent. In addition, the working environment in those banks is almost standardized. Therefore, banks’ ability to apply modern technology and working environment is not “stable” signals when Vietnamese customers evaluate their banks’ reputation. Customers use banking services and products for their not only immediate consumption that help satisfy material needs but also their financial security of future consumption that are more inclined to psychological needs (Chung‐ Herrera, 2007; Xiao and Noring, 1994). Consequently, the uncertainty and psychological distress caused by the Covid-19 pandemic may shape new customer expectations towards the role of commercial banks in their financial life. This, in turn, determines which signal is valid in evaluating bank reputation. Our abnormal findings provide an important theoretical contribution regarding the validity of a firm’ past actions, as signals, in contributing to its reputation. Specifically, the extent to which these performances could enrich corporate reputation may depend on various contextual factors that determine their honesty and stability.

The second set of hypotheses was about the mediating role of customer satisfaction and trust in the impacts of customers’ perceptions about banking products and services, social actions, technological application, communication, and risk management on bank reputation. Those perceptions are resulted from customers’ own direct experiences with their banks and are intricately linked to their benefits and value obtained from the banks. The results indicate that customer trust totally mediates the relationship between either customers’ perception about banking products and services or their banks’ social responsibility and bank reputation. For the remaining cases, no mediating effect was found. These findings indicate that although some interactions between a few determinants of bank reputation were found, in most cases, each factor, either cognitive or emotional, has its separate effect on bank reputation. Enhancing customer satisfaction and trust are, therefore, not enough to build a bank reputation. Instead, commercial banks should take account into detail every single factor that could influence their reputation.

In general, this study suggests some valuable implications for Vietnamese commercial banks towards the enhancement of their reputation in the Covid-19 conditions. The research indicates that both cognitive and emotional variables should be considered to build a reputation. Specifically, it is recommended that bank reputation should be built from a combined key strategy that aims at improving banking products and services, demonstrating social responsibility, installing high-quality risk management systems and solutions (for both the banks themselves and their customers) while strengthening and leveraging advantages resulting from leadership and financial capacity. Moreover, it is noted that all these efforts need to be signalled to customers through effective and reliable communication strategies. Put it simply, maintaining customer satisfaction and especially, customer trust is the central route to create, enhance, and protect bank reputation. This strategy is even more important where commercial banks are facing increasing competition while many aspects of banking practices have been standardized that making building reputation more difficult.

This research has some limitations. First, this research uses a sample drawn from Hanoi city with decent sample size and limited variety of demographic characteristics, hence, the representativeness of the sample as drawn is not perfect. Especially, the differences in social values and lifestyles among citizens from the North, the Middle and the South of Vietnam may affect the extent to which various signals of bank reputation could influence their perceptions. Second, this study only collects cross-sectional data, hence, it could not draw any conclusions about how the determinants of bank reputation and the magnitude of their impacts may vary over time, especially when the economic impacts of the Covid-19 pandemic become more severe. Third, although this research was conducted in the Covid-19 conditions, the features of the pandemic are not included and tested in the conceptual model. Fourth, this research has a limitation related to the measurement of risk management. In this study, this construct is only measured as a dummy variable for whether customers perceive that their banks provide any risk management solutions to them. This measurement could not reflect the level of effectiveness in risk management activities of commercial banks.

This research could be either revisited or expanded with the employment of a better sample that has a larger size, more diverse characteristics, and is collected from a wider range of venues in the North, the Central and the South of Vietnam to ensure better representativeness of the sample. In addition, given the context of the Covid-19 crisis, future research could replicate our findings in which some impacts or features of the pandemic could be examined as either control variables or moderators. It would also be interesting to revisit the effects of risk management, with a more detailed measurement scale, in other contexts where the nature of offerings to customers involves some risks and uncertainty other than banking services. Moreover, the contradicting findings of the impacts of brand communication, technological innovation, and working environment on bank reputation as compared to previous studies imply the possibility of moderators in those relationships, which are neglected in the literature. Drawn from the theoretical underpinnings of signalling theory, future research could further examine the moderating effects of factors that influence the extent to which an action or performance, as a signal, is perceived as honest and stable on its linkage to corporate reputation.