Abstract
Purpose
This research aims to determine to what extent corporate social responsibility (CSR) actions developed by bank entities in Spain improve the vulnerable customers' emotions and quality perception of the banking service. Consequently, this increases the quality of their relationship regarding satisfaction, trust and engagement.
Design/methodology/approach
Data from 734 vulnerable banking customers were analyzed through structural equations modeling (EQS 6.2) to test the relationships of the proposed variables.
Findings
Vulnerable customers' emotional disposition exerts a strong influence on their perceived service quality. The antecedent effect is concentrated primarily on the CSR towards the client, with a residual secondary weight on the CSR towards society. These positive service emotions are determinants of the outcome quality perceived by vulnerable customers, directly in terms of higher satisfaction and trust and indirectly through engagement.
Practical implications
This research contributes to understanding how financial service providers should adapt to the specific characteristics and needs of vulnerable clients by adopting a strategy of approach, personalization and humanization of the service that seems to move away from the actions implemented by the banking industry in recent years.
Originality/value
This study has adopted a theoretical and empirical perspective on the impact of CSR on service emotions and outcome quality of vulnerable banking customers. Moreover, banks can adopt a dual conception of CSR: a macro and external scope toward society and a micro and internal scope toward customers.
Keywords
Citation
Monferrer Tirado, D., Vidal-Meliá, L., Cardiff, J. and Quille, K. (2023), "Vulnerable customers' perception of corporate social responsibility in the banking sector in a post-crisis context", International Journal of Bank Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJBM-03-2023-0162
Publisher
:Emerald Publishing Limited
Copyright © 2023, Diego Monferrer Tirado, Lidia Vidal-Meliá, John Cardiff and Keith Quille
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
The last decade has been marked by complexity and turmoil in the markets resulting from successive critical events worldwide, such as the economic and financial crisis of the early 2010s, the Covid-19 pandemic crisis, Russia's invasion of Ukraine and the recent failures of Credit Suisse, Silicon Valley Bank and Signature Bank. These events have brought significant economic, social and emotional repercussions for individuals and companies (Bugandwa et al., 2021; Moliner et al., 2019), significantly increasing the client's vulnerability. In the banking sector, this vulnerability profile is of particular interest, mainly due to (1) the relationship between the bank and the client, with a long-term component and (2) the product/service on which such a relationship of maximum involvement for the customer is built (such as the customer's money).
Vulnerable customers are diverse regarding geography, income and life cycle. However, they all have one thing in common; they are not receiving the support they need from their financial institution (Bond and D'Arcy, 2021). Then, while all customers generally want reliable, easy-to-use and accessible banking services, vulnerable customers may have unique needs requiring additional targeted strategies (de la Cuesta et al., 2021, 2022; Xiao and Porto, 2022). For instance, they may require more tailored services, better access to customer service, enhanced communication, or products designed to prevent financial hardship. This places considerable pressure on systems currently in place for managing customers with financial difficulties and on the resources needed to attend to them adequately (de la Cuesta et al., 2021, 2022; Le et al., 2021). Therefore, banks should take on the responsibility, in corporate terms, to embed vulnerability, be it by designing products, communications, treatments, or inclusive channels and guarantee adequate levels of care (Amine and Gatfaoui, 2019; de la Cuesta et al., 2021, 2022; Le et al., 2021; Xiao and Porto, 2022). Failing to do so could lead to regulatory scrutiny and penalties, increased customer churn, reputational damage and missed opportunities for building customer loyalty and trust (Financial Conduct Authority, 2017). Today, banks can improve their services to vulnerable customer segments. But what elements are crucial to achieving it?
The degree of commitment of bank entities in applying corporate social responsibility (CSR) is a central element when maintaining and strengthening the relationship that vulnerable customers establish with their financial service providers (Fatma and Rahman, 2016; Herold et al., 2020; Khan et al., 2016; Moliner et al., 2020). This research contributes to understanding banking entities' relational strengthening processes with vulnerable clients when providing services based on CSR policies. This initial step is important for understanding the needs of this customer profile and identifying potential investment areas in terms of CSR banks' practices (van Hierden et al., 2021). Specifically, this research aims to determine, in the Spanish context, to what extent vulnerable customers improve their emotions and quality perception of the banking service and, therefore, the quality of their relationship in terms of satisfaction, trust and engagement based on CSR actions developed by their bank entities. To this end, in a complementary way to the traditional definition of CSR focused on the activities subject to its application, this work adopts a CSR approach based on stakeholder theory (Freeman, 2010; Moliner et al., 2020; Waheed et al., 2021). Concretely, we adopt a conception of CSR typically applied by bank entities focused on a macro/micro duality. The macro horizon is linked to society with the general public and external significance (Herold et al., 2020), while the micro scope is mainly focused on the internal and particular treatment offered to the client (van Hierden et al., 2021). This work empirically supports the usefulness of stakeholder theory as a complementary approach in the conception of the dimensionality of CSR. From a managerial perspective, we enhance the need to adopt a strategy of approach, personalization and humanization, that seems to move away from the actions implemented by the banking industry in recent years.
Section 2 reviews the vulnerable customers in the bank context, and Section 3 defines corporate responsibility in the banking sector. Section 4 elaborates on the hypothesis development. Section 5 deals with the research methodology; after this, the analysis and findings are presented in Section 6. Finally, the discussion of theoretical and managerial implications and conclusions, followed by limitations and opportunities for future research, are presented in Sections 6 and 8.
2. The vulnerable consumer in the banking sector
According to the Financial Conduct Authority (FCA) UK definition, “a vulnerable customer is someone who, due to their circumstance, is especially susceptible to detriment, particularly when a firm is not acting with appropriate levels of care.” In 2018 a European Commission study stated that the consumer vulnerability index in Europe was above 43% (in 2016, it was 35%). According to the FCA's Financial Lives survey run in February 2020, 46% of adults in the United Kingdom displayed vulnerability. In October 2020, this figure reached 53%. This trend continued in the following months. The National Australia Bank has renewed its Customers Experiencing Vulnerability Framework 2021–2023, given that 66% of people experience some level of financial vulnerability and stress, and 17% of people over 60 have experienced financial abuse. In the same line, according to the Consumer Financial Protection Bureau's (CFPB) definition, 40% of US consumers are financially vulnerable. With these data, customer vulnerability cannot be considered by banks as a specific problem of limited scope, since it is expected that most people will experience some vulnerability in their lifetime.
Factors determining a client's vulnerability can be very diverse such as capacity, resilience, health and life events, affecting people of a heterogeneous background (de la Cuesta et al., 2021). Based on these particular conditions, vulnerable customers often face a wide range of barriers in their relationships with banks, which can impact their ability to successfully manage their finances effectively, even putting them at risk of financial exploitation. First, regarding capacity, the most evident determinant may be the customers' limited financial resources, hindering the payment of fees associated with banking products and services. In addition, the lack of access to credit and other financial products is based on the strict lending policies and higher entry barriers imposed by financial institutions in recent years. However, the economic condition would not be the only determinant of vulnerability to consider. Another common problem is limited access to banking services, as they may struggle to visit bank branches or use online banking due to physical or cognitive impairments (FCA, 2015) or perhaps due to technological barriers associated with the lack of familiarity with digital media. Compounding this issue is poor financial literacy, as many may not know or understand financial products and services to make informed decisions (Lusardi and Mitchell, 2014). In this line, vulnerable customers may be more susceptible to financial exploitation and fraud through scams or predatory lending practices (DeLiema and Conrad, 2017).
Second, associated with conditioning factors of health and life events, the different global crises in previous years (with economic, health and social focus), have empowered an increase in seeking online support for domestic abuse and mental health. The number of people suffering grief has also risen. Others have experienced financial vulnerabilities by losing jobs (Thomson et al., 2020). All of this generates new resilience determinants, related to a low capacity to bear financial or emotional shocks. Even clients with previous wealthy positions could suddenly have a low capacity to bear financial or emotional unexpected negative impact (Money and Mental Health Policy Institute, 2021). Therefore, although vulnerable customers might not be considered the most profitable segment for a bank, it is essential to understand that not all vulnerable people live in poverty or have low incomes, i.e., anyone could become vulnerable (de la Cuesta et al., 2021; Thomson et al., 2020).
For banks, the consequences of customer vulnerability can be multifaceted (FCA, 2017). First, they may experience increased financial risks associated with lending, such as higher default rates and non-performing loans, which can impact the bank's profitability and asset quality. Additionally, there may be regulatory implications and compliance requirements to address vulnerability and ensure fair treatment of customers. Failure to meet these obligations can result in legal consequences, fines and reputational damage for the bank. Finally, neglecting vulnerable customers can lead to customer attrition, with a loss of trust and customer dissatisfaction, impacting the bank's customer base and long-term profitability. On the contrary, banks prioritizing customer-centric practices and offering accessible and supportive services to vulnerable customers may be more likely to attract and retain new customers by improving the quality of the relationship with customers, through greater engagement, satisfaction and loyalty (Fornell et al., 2020; Kosiba et al., 2020). Overall, improving service quality and engagement among vulnerable customers is essential for fulfilling ethical and legal responsibilities, and contributing to the overall well-being of society, and strengthens the bank's reputation as an inclusive, socially responsible institution (Mogaji et al., 2021).
Therefore, banks are expected to provide vulnerable customers with an appropriate level of commercial attention (customized, flexible, accessible, and fair), which can help them manage their financial situation more effectively. To that end, they should understand the vulnerability features of their target market and their main customer base (de la Cuesta et al., 2021, 2022; Le et al., 2021; Xiao and Porto, 2022). This anticipates a growing need for personal and manual intervention in automated processes and for financial institutions to be availed of reliable proof of the outcomes experienced throughout the customer journey. This implies costs, such as developing and provisioning tailored products and services, additional staff training, enhanced customer service and improved accessibility. However, these costs could be strategic investments that yielded longer-term returns by enhancing customer loyalty, financial resilience and the bank's reputation.
In conclusion, service providers should evolve towards a transformative perspective when assuming their functions (Hanafizadeh and Amin, 2022; Le et al., 2021), whereby the fair treatment of vulnerable customers is fully integrated into corporate culture across departments, not only in specific teams working in customer services but also in debt collection. In this context, the degree of commitment of bank entities in applying CSR is a central element when maintaining and strengthening the relationship that vulnerable customers establish with their financial service providers (Fatma and Rahman, 2016; Herold et al., 2020; Khan et al., 2016; Moliner et al., 2020).
3. Theoretical framework: the corporate social responsibility in the context of banks
There is a long and varied history associated with the evolution of the concept of CSR (Dmytriyev et al., 2021). For a transactional extreme, Friedman (1970) states that corporate responsibility is to conduct the business following the manager's desires, “which generally will be to make as much money as possible while conforming to the basic rules of the society, both those embodied in law and those embodied in ethical custom”. Friedman sees CSR as an inappropriate use of a company's resources that would result in spending money for the general social interest.
In a second relational extreme, new theories emerge. Carroll (1991) presented the “Pyramid of Corporate Social Responsibility” and defined the economic, legal, ethical and philanthropic responsibilities of organizations. Carroll (1999) also asserted that, to a certain extent, social responsibility could be linked to economic returns for the firm. However, new keystone obligations are now considered. First, an ethical responsibility to do what is right even when not required by law. Second, a philanthropic responsibility to contribute to society's projects even when they're independent of the particular business. Following a similar approach, the triple bottom line (Elkington, 1997) is a form of CSR that identifies the three areas of activity on which the company must obtain sustainable results: economic, social and environmental. This supposes finding a point of exchange of interests maintained in the long term, in which firm managers should not only measure their results in economic terms but also in terms of the company's social impacts, always conducting this with respect to the environment. More recently Freeman (2010) adds a new theoretical relational perspective for CSR, the theory of stakeholders. Freeman describes the corporate environment as an ecosystem of related groups, all of which must be considered and satisfied to keep the company healthy and successful in the long term.
Paying attention to the position recently adopted by banks, this industry seems to serve as a practical example regarding these different ways of understanding and applying CSR. Starting from the more transactional extreme, throughout the past decade several social and political forums positioned banks as one of the agents contributing to the vulnerability of the citizen. Indeed, banks went under increasing pressure due to a lack of ethical behavior and commitment to their CSR (Bugandwa et al., 2021; Herold et al., 2020; Rundle et al., 2021). For instance, in Australia the Royal Commission Report (Hayne, 2019) identified a system of greed in which financial gain was the core motivation. Among other cases, charging fees to the dead for financial advisory services that were never provided, offering credit to those who could not pay, or selling inappropriate products (Rundle et al., 2021). In Spain an expansionary banking policy was marked by the deceptive marketing of complex products to clients without the capacity to evaluate their implications, such as preferred shares. And, in US the bank Wells Fargo deceived shareholders by creating 3.5 million false accounts (CNBC, 2018).
This unethical behavior has not gone unnoticed by the principal recipient of banking activity, the customer, which could have contributed to generating a growing climate of disaffection with their banks and mistrust of the services they can provide (Bugandwa et al., 2021; Herold et al., 2020). In a 2013 survey of consumers across Europe, banking was ranked at the bottom regarding responsibility compared to other industries (European Commission, 2013). More recently, only 20% of Australian customers believe that banks, in general, are ethical (Deloitte, 2018). Financial services are at the bottom of the Edelman Trust Barometer (2020), which contrasts with the banks' CSR reports and major global policies, such as the Principles for Responsible Banking promoted in September 2019 by 30 leading founding banks from various countries through the United Nations Environment Program Finance Initiative (UNEP FI), in line with the Sustainable Development Goals (SDGs). These Principles exemplify a general commitment, committing around 80% of the investment industry, with 290 banks from 73 countries, which means more than 45% of the world's banking industry assets (US$ 84trn), according to UNEP FI, and represent a clear attempt to redirect the CSR behavior of banks towards new perspectives of a more relational nature. Thus, banking institutions seem to follow a double standard when implementing CSR, which can lead to the development of completely different perceptions on the part of the client about CSR depending on the specific agent on which they are considering it. Therefore, it is essential to adopt a conceptualization of CSR that allows differentiating this duality at the macro level under a more external and general approach and at the micro level under a more internal approach focused on the relationship with the customer.
In this regard, we adopt the CSR definition proposed by El Akremi et al. (2018, p. 623) which includes “an organization's context-specific actions and policies that aim to enhance the welfare of stakeholders by accounting for the triple bottom line of economic, social and environmental performance”. This definition allows adopting a complementary vision between the relational theories of CSR, adding an important nuance when identifying CSR activities (Pratihari and Uzma, 2018). This new nuance focuses on the interested parties receiving such activities (Moliner et al., 2020; Pérez and Rodríguez, 2015; Waheed et al., 2021). Therefore, stakeholder theory is a fundamental approach to investigating the scope and consequences of companies' CSR strategies (Freeman, 2010; Moliner et al., 2020; Waheed et al., 2021). From this perspective, the stakeholders are the main objectives of CSR, understood as a set of economic, social and environmental activities that the company undertakes to fulfill its obligations with each of these (El Akremi et al., 2018; Khan et al., 2016). Pratihari and Uzma (2018) consider that CSR initiatives should help all stakeholders achieve their personal goals and establish strong and positive ties with them.
Stakeholders have been classified according to multiple criteria (Moliner et al., 2020; Waheed et al., 2021). Taking into account the specific purpose of our research, based on the differentiation of CSR actions in terms of macro and micro duality, we focus on two specific interest groups, as in Moliner et al. (2020): (1) society in general, which would include the set of actions developed by the bank under a macro scope in areas such as charitable activities, community development and protection of the natural environment; and (2) the customer in particular, including those actions focused at the micro level on the main recipient agent of the entity's relational activity, such as comprehensive and honest communication of products and services and the management of customer claims.
4. Hypothesis development
Based on the above rationale, we review relevant literature on our critical concepts of CSR, emotions, outcome quality, satisfaction, trust and engagement in the banking service context and develop our hypotheses in Sections 4.1 and 4.2. We also introduce our theoretical framework in Figure 1.
4.1 The influence of the vulnerable customer's perceived CSR on their perceived outcome quality
There is acceptance in the literature of the positive effects of firms' social and sustainable programs on relationship quality and customer emotions (Chen, 2015; Ha et al., 2014; Pérez and Rodríguez, 2015). After an adverse period, like the Covid-19 pandemic and subsequent economic crisis, customers would reward banks' responsible activities, improving their relationship behaviors and attitudes (Chen, 2015; Fatma and Rahman, 2016; Pérez and Rodríguez, 2015). As mentioned previously, this research is based on the different perception that vulnerable customers can have about the CSR actions carried out by their banks, in terms of the macro (society) and micro (client) duality.
On the one hand, concerning society, the willingness of companies to implement social programs (corporate donations to social causes, participation in community activities, sponsorship of local events or environmental concerns, etc.) would positively affect customers' emotions (Chen, 2015; Liu et al., 2014). Clients in general, as citizens, have experienced various negative global events in recent years, which have awakened their feelings associated with solidarity, empathy, responsibility and commitment to the protection of common causes that mark social welfare. Regardless of its more or less direct affectation, the “citizen client” has become aware that there are universal causes of a social nature that are not the responsibility of one or the other, but rather represent a shared responsibility for which all parties must contribute to building a better society. Based on this, it may become a relevant factor for clients to perceive that their companies, such as their banks, through their macro scope CSR practices, are actively involved in the same problems that concern them (Luo and Bhattacharya, 2006; Peloza and Shang, 2011). This would lead to an emotional alignment of mutual support with positive consequences for the client. In the particular case of the vulnerable consumer, characterized by conditions that affect their emotional sensitivity, and who may be more dependent on their banks and more sensitive to their practices, this influence can have a multiplicative effect.
On the other hand, customer quality focuses on the central stakeholder of the company, the client, taking the customer needs as a structural pillar (Ha et al., 2014). Boles et al. (2001) suggest that the organization's dominant culture with a positive orientation to relational services is based on a proactive concern for the customer. For this, firms must understand their function regarding the customer without strictly focusing on the commercial perspective (Pérez and Rodríguez, 2015). More specifically, vulnerable clients' have been marked in recent years by an opinion against the bank, either because of their own unsatisfactory experiences with the services, or because of the image from several social and political forums pointing to the lack of ethics and social commitment in certain situations (Bugandwa et al., 2021; Herold et al., 2020; Rundle et al., 2021). All this may have led to a climate of greater mistrust before using the service. In this context, the vulnerable customer will reward and respond positively to those banks that break this trend by addressing the specific needs and challenges of this customer group (Estrada et al., 2020; FCA, 2021; Moliner et al., 2020). In this sense, it would no longer be enough to incorporate internal CSR mechanisms and policies toward the client. It will be essential to make them perceptible to the client in order to reverse and reinforce the emotional disposition with which the client faces the service.
This obliges firms to nurture their relationships with vulnerable customers by offering them a service tailored to their needs and paying close attention to the circumstances in which this service will be delivered (Ha et al., 2014; Torres et al., 2012). Recent works point out some of the actions to be valued (European Commission, 2021; Pew, 2023): developing financial education programs and initiatives to improve financial and digital literacy to empower vulnerable customers to make informed financial decisions and effectively navigate digital banking services; promoting fair and transparent practices to prioritize the well-being of vulnerable customers; developing more flexible and personalized services tailored to the particular needs of these clients in order to actively contribute to their financial inclusion and expanding the access to alternative financial services. These actions could increase the expected benefits of vulnerable customers through a high level of service quality and significantly contributes to fostering their positive relational attitudes.
Therefore, the higher the social and customer quality, the greater the service emotions generated, which leads us to present the following hypotheses:
The vulnerable client's perceived CSR on the society provided by their bank positively affects service emotions.
The vulnerable client's perceived CSR on the client provided by their bank positively affects service emotions.
There is a considerable discrepancy among scholars when determining the content of emotions. The most common classification differentiates between positive and negative emotions (Laros and Steenkamp, 2005). The main advantage of this classification is its simplicity and the assumption that it is an approximation of the customer's attitude. However, its main disadvantage is that it does not detect specific, relevant information about customer's feelings (Bagozzi et al., 1999, 2016), which implies a loss of explanatory power in the behavior model (Idrovo et al., 2020; Moliner et al., 2019). After a compelling analysis of the construct in the marketing context, the classification proposed by Russell (1980) is the most robust due to its level of specificity and its applicability to a wide range of services and scenarios (Martin et al., 2008). This model argues that the best description of the interrelationship between the different types of emotions is by a spatial model of various affective components related to emotions, defined as a combination of the degree of pleasure and the degree of arousal (Idrovo et al., 2020; Moliner et al., 2019). It is important to note that emotions always have a specific referent, and individuals can react differently to the same event or experience (Bagozzi et al., 1999).
Oliver (2014) claims emotions are gaining attention as a central element in service quality management; however, the literature does not offer precise models. Stauss and Neuhaus (1997) claim that satisfaction studies focus on the cognitive component, while they usually ignore the emotional feature of service quality. Regarding the role of emotion in service encounters and its relationship with fundamental concepts in service quality, there is some consensus that service quality consists of three primary aspects: outcome quality, interaction quality and physical service environment quality (Brady and Cronin, 2001). We are interested in outcome quality which refers to the customer's assessment of the core service and is the prime motivating factor for obtaining the services (e.g., haircut, massage, money received from ATM). More specifically, in the banking sector, outcome quality refers to the effectiveness of the financial institution's service provision to its customers (Monferrer et al., 2016, 2019b). It is concerned with what the customer receives from the service transaction. This aligns with the service-dominant logic and the customer engagement theory that customer emotions significantly influence their perceptions of service quality (Brodie et al., 2011). Specifically, in the context of vulnerable customers, who are generally more dependent on the service provider, service emotions could be a crucial determinant of how they perceive the quality of outcomes.
The literature on outcome quality identified the following conditions (Kaura, 2013; Kaura et al., 2015): service, product, price and access. Regarding service conditions, Amin and Isa (2008) noted that the clients' positive relational experiences in the financial sector depend on the efficiency of service provision. This could include attributes like empathy, reliability, responsiveness and assurance. When these conditions are met, customers see their relationship with the bank as sustainable over time (Zeithaml et al., 1990). Considering the product conditions, the wider the offer, the greater the opportunities to offer packages of services tailored to the vulnerable customer's needs (Korda and Snoj, 2010; Lassar et al., 2000; Tsoukatos and Mastrojianni, 2010), which positively affects their relationship with the bank (Strandberg et al., 2012). Next, price conditions are essential in the case of services since they are understood to indicate intrinsic quality (Kaura, 2013; Kaura et al., 2015). In the banking industry, transparency and fairness in setting prices lead to positive feelings toward the service provider (Lassar et al., 2000; Strandberg et al., 2012), especially for vulnerable customers. Finally, the ease of access to a product or service can affect the perceived outcome quality. If a service or product is easily accessible, especially for vulnerable customers who may face additional challenges when accessing services, it can increase the perceived outcome quality (Berry et al., 2002).
The vulnerable customer's service emotions directly and positively affect the perceived outcome quality.
4.2 The influence of the perceived outcome quality on the relationship between the vulnerable client and their bank
There is a consensus in the general literature regarding the effect of quality of service on relationship quality, linked to positive relational behavior of the client in terms of variables such as satisfaction, trust and engagement (Estrada et al., 2020; Monferrer et al., 2016). Vulnerable customers, who may heavily rely on their banking services due to physical, mental, or socioeconomic limitations, would not be an exception in this sense.
First, regarding the effects on satisfaction, the expectancy–disconfirmation paradigm suggests that customer satisfaction can be measured by evaluating perceived performance (outcome quality) against pre-purchase expectations (Oliver, 1999). Service quality and customer satisfaction are related constructs (Spreng and Mackoy, 1996). Service quality is an antecedent of customer satisfaction (Lee et al., 2000) in the sense that higher levels of service quality lead to higher satisfaction levels. Lassar et al. (2000) state that certain service quality conceptualizations may be better for specific services.; they suggest that outcome quality (technical quality) is better suited for banking because it significantly influences satisfaction, whereas most dimensions of an alternative conceptualization failed to be significant predictors. Maddern et al. (2007) found empirical support only for the outcome quality-satisfaction relationship in the financial services sector in the UK.
In this line, according to Delgado et al. (2003), brand trust is the confident expectations of the brand's reliability and intentions. Within the banking sector, trust means that the bank is trustworthy, honest, practices integrity and is reliable in delivering services to its customers. Gefen (2000) observed that trust could reduce the complexity of transactions and the perceived risk of the decision. When the degree of familiarity between customers and transaction security mechanisms is insufficient, trust helps reduce uncertainty, which is especially relevant in the financial sector. Previous studies have found that service quality positively influences trust, for instance, in the healthcare industry (Alrubaiee and Alkaa'ida, 2011), in a high-involvement, high-service luxury product (Chiou and Droge, 2006) and in the financial sector (Cho and Hu, 2009).
Based on the former discussions, this study argues that in the banking industry, service quality positively affects consumers' trust in the bank. In line with the literature, we hypothesize the following:
The vulnerable customer's outcome quality perception positively affects satisfaction with their bank.
The vulnerable customer's outcome quality perception positively affects the trust in their bank.
Previous studies have found that customer satisfaction has a positive and significant relationship with customer engagement. Carlson et al. (2019) find that customer satisfaction moderates the relationship between brand experience value and customer engagement. According to Simon and Tossan (2018), consumer satisfaction predicts customer engagement and Pansari and Kumar (2017) understand customer satisfaction as an antecedent of customer engagement. Furthermore, Brodie et al. (2011) suggest that some highly engaged consumers have previously experienced higher satisfaction levels. More recently, and related to the banking sector, Monferrer et al. (2019a) and Ananda et al. (2022) found that customer satisfaction is the most influential variable in generating customer engagement. As a result, a customer's satisfaction with a product or brand will influence their engagement with the brand/product (Thakur, 2018). Specifically, for vulnerable customers, satisfaction with a service or product might not only fulfill their immediate needs but also foster a sense of belonging and involvement, thereby enhancing their engagement.
When customers trust a brand, they will use more of its products, recommend it to others (Eggers et al., 2013), and consider it when making purchase decisions (Bhandari and Rodgers, 2018). Indeed, Sánchez et al. (2015) conclude that customer engagement toward a brand is higher if the customer perceives a higher level of trust. Agariya and Singh (2011) revealed that, in the banking sector, trust is among the six most often cited defining constructs in engaging relationships. Johnson and Grayson (2005) indicate that trust in a service provider is positively related to a customer's anticipation of future interactions. More precisely, Brown et al. (2009) stated that trust would affect the likelihood that customers disclose information to enable satisfactory service and engagement between service users and providers. Similarly, in the banking sector, Kosiba et al. (2020) found that trust influences customer engagement. Trust can foster a sense of security and comfort among vulnerable customers, which can encourage active and deep engagement with the service provider.
In line with the previous studies, we expect customer satisfaction and trust in the service provider will positively influence engagement. Thus, we hypothesize the following:
Higher satisfaction entails higher engagement in vulnerable customers.
Higher trust leads to higher engagement in vulnerable customers.
Figure 1 shows the model to be analyzed.
5. Methodology
Banking customers in Spain are characterized by some particularities which we believe make them an interesting target to study vulnerability. For instance, around 2007, preferred shares were marketed to investors as a relatively safe investment with attractive yields (Zunzunegui, 2014). However, its value declined sharply during the financial crisis, and many investors suffered significant losses, so the Spanish government was forced to intervene, and several banks were fined (El País, 2012). The preferred shares scandal highlighted the need for improved consumer protection measures and increased transparency in the financial sector.
Some Spanish bank customers prefer face-to-face banking services -due to various factors, including age, cultural norms and familiarity with traditional banking practices-particularly those who are not as comfortable with technology or prefer personalized service. However, banks in Spain have been closing physical branches and offices to reduce costs after the 2008 financial crisis (Martín et al., 2017) and in response to changing customer preferences and the shift towards online banking. This change has led to concerns among customers about access to financial services, particularly for vulnerable or older customers who may be less comfortable with online banking (Financial Times, 2022). The closure of offices has also led to concerns about job losses and the impact on local communities, particularly in rural areas where access to financial services is already limited.
5.1 Data collection and sample
The researchers signed a collaboration agreement with two relevant banks (both in the top ten banks based on total assets, according to Moody's international rating agency). This agreement allowed us to conduct interviews with customers in Spain. Before beginning the fieldwork, in August 2022, banking experts examined the questionnaire items, and we pre-tested them on a pilot group of 20 customers. This procedure helped to improve the wording of some of the questionnaire items and ensured the appropriate form, layout, sequence difficulty, length and completion time for the questionnaires. A team of researchers interviewed customers from September to October 2022. Interviews took place while customers were waiting to be attended to, and the sample included only regular customers of the branch. Interviews were used rather than self-completion to avoid question misinterpretations. The results were aggregated, thereby ensuring confidentiality. To guarantee that subjects in the final sample were associated with some potential vulnerability, we introduced various initial questions related to their educational level, occupation, income level and general assessment regarding their economic and social situation, following the inclusion criteria listed in Table 1. The fieldwork concluded with a final sample of 734 customers from 312 branches (with a maximum of 5 customers per branch). An analysis of the primary data revealed the principal sample characteristics (Table 2).
5.2 Measurement instruments
The questionnaire is divided into two blocks. The first block contains questions to identify the main sample characteristics, presented in Table 2. The second block comprises the scales used to measure the constructs associated with the relationship model proposed in this study. All the scales used had been devised by other authors, tested in previous studies and adjusted in our research to adapt to the banking context.
According to the stakeholder theoretical CSR approach, we use the two measurement scales developed by Liu et al. (2014) corresponding to each of the two agents analyzed: (1) society (macro scope of CSR), including actions developed by the bank in areas such as charitable activities, community development and protection of the natural environment; and (2) customer (micro scope of CSR), including actions such as honest communication of products/services and claims management. Both scales consist of five items scored on a five-point Likert scale, where 1 represents “total disagreement”, and 5 is “total agreement”, regarding the client's perception regarding the social actions carried out by your bank.
To measure the customer's emotional disposition towards the service generally received at their bank, we use the scale developed by Mazaheri et al. (2011) and Blasco (2014). This multidimensional scale of a reflective nature conceives these emotions based on two dimensions associated with individuals' emotional categories: pleasure (six items) and arousal (three items). Items are scored on a five-point Likert scale assessing different pairs of conflicting emotions, where 1 is always associated with the most negative emotion, and 5 represents the most positive emotion. Thus, for example, item 1 of the pleasure dimension assesses the customer's emotional disposition on the duality “Angry (value 1)/Glad (value 5)”.
To measure outcome quality, we take as a reference the work by Idrovo et al. (2020), using a reflective multidimensional scale that collects the customer's perception of the effectiveness of the bank's core service provision around four basic dimensions: service (four items), product (three items), price (five items) and access (four items). Items are scored on a five-point Likert scale, where 1 represents “total disagreement”, and 5 is “total agreement”, regarding the customer's perception of the quality associated with the different actions carried out by their bank.
Finally, the three constructs associated with the quality of the relationship experienced by the client are measured with three five-point Likert scales, where 1 represents “total disagreement”, and 5 is “total agreement”, regarding the degree of agreement on the part of the client with different statements associated with their relational behavior with the bank. The five-item scale proposed by Bloemer and Odekerken (2002) is used to measure satisfaction. Trust is measured through the scale developed by Camarero et al. (2005) composed of six items, and engagement is measured with the four-item scale of Blasco (2014). Table 3 summarizes the sources of the measurement scales used in the study.
5.3 Validity and scale reliability
We performed confirmatory factor analysis using structural equation modeling to refine the scales with EQS 6.2 multivariate software package. We used the maximum likelihood approach to estimate the parameters. Following Hair et al. (2010), we considered a model development strategy. To improve initial models, we conducted a refinement process that involved eliminating less relevant indicators based on the structures of the latent variables assumed for each construct. Jöreskog and Sörbom (1993) recommend examining the estimation parameters. We eliminated the indicators that did not satisfy the strong convergence condition, i.e., those having individual standardized coefficients (λ) lower than 0.6 and an average standardized factor loading of less than 0.7 (Hair et al., 2010; Steenkamp and van Trijp, 1991). We then verified the compliance with the weak convergence condition (Steenkamp and van Trijp, 1991) by analyzing the significance of the factor regression coefficients between indicators and their latent variables. To do this, we considered the Student t-value by imposing the maximum condition (t > 2.58; p = 0.01). Following this process, six indicators were removed: CSRS2, CSRC1, CSRC5, OUT14, SAT3 and TRU5 (Table 4). Finally, we monitored the evolution of the main model fit measurements as each indicator was eliminated. We conducted several verification tests to identify whether the above refinement tests negatively affected scale reliability (Table 4). For internal consistency, we tested Cronbach's alpha (α > 0.7), the construct composite reliability (CR > 0.7), and the analysis of variance extracted (AVE >0.5) (Churchill, 1979; Fornell and Larcker, 1981; Nunnally, 1967).
Next, we analyzed the convergent and discriminant validity. We tested convergent validity by returning to the confirmatory factor analysis performed at the start of the process and by confirming the high estimated value and significance of the correlations between the scales' dimensions. Table 5 presents the discriminant validity of the considered constructs assessed by AVE (Fornell and Larcker, 1981) and confidence interval tests (Anderson and Gerbing, 1988), confirming this condition.
5.4 Complementary data analysis
First, the variance inflation factor for the latent variables in our model verified the absence of any signs of multicollinearity. The results, with values between 2.111 and 7.651 (considerably lower than the maximum value of 10), suggested multicollinearity was not a problem in the study (Kock, 2015). Second, we performed a t-test of independent means on the dimensions of the variables in the model, using the first 45 and last 45 respondents. We can confirm the absence of non-response bias (Armstrong and Overton, 1977) as we found no significant differences between these respondents at the 0.05 level. Third, we used the Harman test to assess the possibility of common method variance bias (Harman, 1976). This test assumes that if this bias exists, from a factor analysis, one should expect a single factor to accumulate most of the covariance of independent and dependent variables (Podsakoff and Organ, 1986). Following Friedrich et al. (2009), MacKenzie and Podsakoff (2012) and Podsakoff et al. (2003), we carried out a factor analysis on the indicators resulting from refining the process using principal component analysis (Velicer and Jackson, 1990) in which we examined the unrotated factor solution. The factor analysis revealed several factors with eigenvalues greater than 1. These factors explain 78.511% of the variance among the 30 items, and the first of the factors accumulates 20.676%. Hence, since we identified several factors, and the first factor does not accumulate most of the variance, common method variance bias seems largely absent (Friedrich et al., 2009; MacKenzie and Podsakoff, 2012; Podsakoff et al., 2003).
6. Analysis and findings
Table 6 displays the covariance matrix resulting from the scale refinement process described in the previous sections. Based on this data, we also tested the hypotheses using structural equation models, which enabled us to simultaneously explore a series of dependence relationships (Hair et al., 2010). Figure 2 shows the step diagram of the resulting relationship model after its specification and identification.
The next step is to test the hypotheses with EQS 6.2. Looking at the results (Table 7), vulnerable customers' perception regarding CSR towards customers emerges as a primary determining factor in generating previous positive emotions associated with the bank service (H2: λ = 0.832, t = 6.903*). Although its effect is not so steep, the perception of CSR towards society reinforces the generation of that emotion under a secondary level of influence (H1: λ = 0.183, t = 4.500*). These previous positive emotions are determinants of the outcome quality perceived by vulnerable customers (H3: λ = 0.984, t = 7.306*), the latter being an essential factor in the development, maintenance and reinforcement of the quality of the relationship between the bank and the vulnerable customers. First of all and directly, regarding higher satisfaction levels (H4: λ = 0.845, t = 25.873*) and trust (H5: λ = 0.909, t = 22.694*). Finally, and indirectly through these two variables, raising the level of engagement that vulnerable customers generate towards their bank (through satisfaction H6: λ = 0.310, t = 6.242*; through trust H7: λ = 0.405, t = 8.002*).
Moreover, considering the total effects derived from the proposed effects model reveals the significant influence on the different antecedent and consequence factors and the reinforcement of the total influence of each pair of factors through indirect effects (Table 7). In summary, these results are consistent with the relationships between these constructs from three concatenated influence sequences: (1) positive perception regarding the CSR of the bank, (2) service quality (through emotions and outcome perceptions) and (3) relationship quality (represented through three main variables: satisfaction, trust and engagement). Specifically, and completing the results in Figure 3, these analyses support the differentiation in the levels of influence of CSR developed by banks to improve the relational links built with their vulnerable customers. From the comparison between paths 8 to 11 to paths 12 to 15, it is clear the primary role of CSR towards the customer concerning the secondary role of CSR towards society.
Finally, the study is completed with a replica of a control group of 722 non-vulnerable clients to assess to what extent the results show different behavior patterns in vulnerable clients concerning the proposed effects model. The results offer a different vision depending on the causal sequence analyzed: antecedent vs. result of the outcome quality. On the one hand, the results show an expected behavior when comparing the relational behavior of the client as a consequence of the quality of the service that has been provided (sequential phase of results). On the other hand, differences are observed when the focus is placed on the antecedent context in which the consumer values the quality of the service received. Although, in both cases, the positive influence between the variables is confirmed (CSR in its two variants, emotional disposition towards the service and outcome quality), there are evident differences in the weight of their effects (antecedent sequential phase).
First, regarding vulnerable consumers, the customer's emotional disposition strongly influences their perception of the service quality (λ = 0.984, t = 7.306*). In the case of non-vulnerable customers, a steep decrease in the weight of this effect is observed (λ = 0.595, t = 6.336*). Second, the customer's perception of the entity's CSR will be a determining factor in such a provision. In this line, regarding vulnerable clients, the antecedent effect is concentrated primarily on the CSR towards the client, with a residual secondary weight on the CSR towards society (λ = 0.832, t = 6.903* and λ = 0.183, t = 4.500 * respectively). On the other hand, the relative importance of these two variants of CSR tends to balance out in the case of non-vulnerable consumers due both to a decrease in the explanatory power of the CSR towards the customer and to the increase in the weight of the CSR towards society (λ = 0.426, t = 5.043* and λ = 0.285, t = 4.270* respectively).
7. Discussion and conclusions
Focusing on the particular context of vulnerable customers, our findings show that the customer's perception regarding the bank's CSR is a determining antecedent of positive emotion toward the outcome quality. Through the stakeholder theory, we adopt a dual perspective in the conception of the CSR that the client perceives: towards society as a whole (under a macro perspective) and towards the client in particular (under a micro perspective). Based on this, this research reveals that vulnerable customers' perception of CSR towards customers is a primary factor in eliciting previous positive emotions related to the bank's service (H2). While the effect is not as pronounced, the perception of CSR towards society also supports these emotions, albeit with a secondary degree of influence (H1). These previous positive service emotions directly and positively affect the outcome quality perceived by vulnerable customers (H3), which is essential in developing, maintaining and reinforcing the quality of the relationship between the bank and the vulnerable customers. If vulnerable customers perceive CSR, they are more likely to think that the bank cares about them and society and, consequently, have a higher commitment to the bank (Shah and Khan, 2020). This profitable result would benefit the sustainable development of the baking sector while enhancing the vulnerable customers' experience. This study also concurs with related studies by supporting that customer outcome quality perception significantly and positively affects customer satisfaction (H4) and trust in their bank (H5). Finally, higher satisfaction and trust entail higher engagement in vulnerable customers (H6 and H7).
7.1 Theoretical implications
The exponential growth in the number of customers subject to vulnerability has awakened the interest of the scientific community in the context of banking (Amine and Gatfaoui, 2019; de la Cuesta et al., 2021, 2022; Le et al., 2021; Xiao and Porto, 2022). Taking the perceived outcome quality by these clients as a central element, our study tries to contribute to this space by analyzing their antecedent and consequence behavioral position. Our results add to the existing consensus in the general literature regarding the effect of quality of service on relationship quality, finding a positive relational behavior of the client in terms of satisfaction, trust and engagement (Estrada et al., 2020; Monferrer et al., 2016). Concerning the antecedent context on which the service quality assessment is built, our work offers a particular vision of the vulnerable client in which the emotional component before the service would be essential. In turn, this emotional disposition will depend to a large extent on the client's perception regarding the bank's CSR, mainly directed towards themselves. This allows for combining a global vision of the banking service for vulnerable customers under a causal sequence of three linked elements: perception of social responsibility, quality of service on an emotional basis and quality of the relationship. Therefore, our work reflects the growing importance of new constructs associated with the relationship quality between customers and branches under a non-transactional emotional approach, which allows us to have a complementary vision of classic studies focussed on variables such as satisfaction, confidence and loyalty (Monferrer et al., 2016).
A contribution derived from this work would be related to the theoretical framework adopted around CSR. Based on the lack of consensus on its definition and in line with what has been recently defended by previous works from a theoretical point of view (DesJardins, 2020; Dmytriyev et al., 2021; Freeman and Dmytriyev, 2017), this work contributes to empirically support the usefulness of stakeholder theory as a complementary approach in the conception of the dimensionality of CSR. In this sense, it is not only necessary to delimit the areas of activity specific to CSR (traditionally associated with economic, social and environmental actions) but to determine the agents that are affected by the implementation of these actions and, therefore, the pursuit of its CSR objectives.
The approach adopted for the CSR investigation does not focus on the mere objective description of the entity's practices but on the subjective perception that its clients have about these practices and the effects this can be derived from. Specifically, the study's originality lies in a theoretical model that adopts a duality in the identification of the receptors of CSR actions: at the macro level under a more external and general approach focused on society and at the micro level under a more internal approach focused on the relationship with the customer. This conception of CSR is very useful for investigating the scope and consequences of the emotional and relational nature of a bank's CSR strategy in potential specific contexts. As our results show, the customer's perception regarding the banks' CSR does not have to be homogeneous and may differ depending on the agent on which such perception is formed. In this case, the perception of CSR on the client acquires a primary role in building a positive emotion towards the received outcome quality, as opposed to the perception of CSR on society, which would have a substantially lower secondary role. Furthermore, after comparing the results obtained on the control group of non-vulnerable clients, we observe new behavioral differences according to the client profile. Thus, even maintaining the primary and secondary role in both perceptions of CSR in the case of non-vulnerable customers, there would not be such marked differences between the two. In short, considering stakeholder theory as a complementary approach in the conception of CSR could favor its study in discriminatory and comparative terms, especially under perception approaches in the customer environment.
7.2 Managerial implications
In general terms, our results provide two fundamental messages aimed at improving bank services to vulnerable clients. On the one hand, a common result-oriented position is confirmed in the client (regardless of their condition of vulnerability) in building their relational behavior with their bank. Achieving a positive interrelation in customer satisfaction, trust and engagement will be directly determined by the customer's assessment regarding the quality of the service. On the other hand, and consequently, our work highlights the need for banking entities to focus their attention on background factors that reinforce and enhance the client's assessment of the service offered. In this regard, this research identifies two fundamental elements that, in the case of vulnerable customers, acquire great influence.
First, it is essential that banking entities can introduce mechanisms to positivize the customer's emotional disposition before the service. The problem does not seem to reside in what is offered to the client but rather in how it is offered. Marinkovic and Obradovic (2015) state that customers' emotional responses should be studied to attain quality relationships, especially in service failure and recovery. Some companies (including banks) have realized that appropriate emotional management could lead to business differentiation, especially in industries where emotions are typically ignored (Zárate and Matviuk, 2010).
Second, to enhance this positive emotional condition, banks must adopt a strategy for developing and implementing their CSR policies that prioritizes their responsibility towards the client. It is not enough for the client to passively see how their banks carry out large-scale social policies to develop the local economy and SDGs. The vulnerable client expects to be an active receiving agent, being able to feel, experience and perceive the responsible awareness and commitment assumed by their financial institution (Cartwright, 2015; Shah and Khan, 2020; Valls et al., 2020). In this sense, the vulnerable customer would reward the efforts of their banks to a greater extent: (1) provide them with more complete, transparent and understandable information on the services offered to them; (2) for a closer understanding of their specific needs; (3) for providing flexible responses to their doubts and more particular problems under conditions of ethics and honesty.
All this leads us to the need to adopt a strategy of approach, personalization and humanization of the service that seems to move away from the actions implemented by the banking industry in recent years. The upward trend in customer vulnerability figures (with values above 60% in developed economies) coincided with the implementation since the early 2010s of a pronounced cost reduction policy by banks that have been characterized, among other actions, by staff restructuring, branch closures, services limited to specific hours and days of the week, and promoting online banking over face-to-face personal attention. In figures, according to Garrido (2016), between 2008 and 2014, 29,000 branches were closed in the Eurozone, which represented the direct dismissal of over 200,000 workers who were previously providing direct customer service. Since then, this trend has continued to rise.
The events experienced in the last fifteen years lead us to understand that anyone could become vulnerable. This circumstance has germinated in society values such as humanity, solidarity and empathy with the problems of others. Perhaps this situation could become a turning point in which, as the stakeholder theory postulates, all the agents involved (among which we can identify the bank itself and the client as the main actors) find points of connection in their particular interests (Dmytriyev et al., 2021; Freeman and Dmytriyev, 2017). In this sense, committing to CSR activities and well-being in customer service can be an optimal differentiation strategy that allows for attracting new potential customers (Goyal and Chanda, 2017).
An example, within the Spanish context, is the case of Carlos San Juan, a 78-year-old retiree who promoted the campaign “I'm old, not an idiot” in 2022 against exclusion in face-to-face treatment of the collective in financial institutions (Financial Times, 2022). His campaign aroused a flood of support from all social aspects to the point of provoking a response from bank employers, the Government, and the Bank of Spain in the agreement of a preliminary draft law for the creation of the Independent Authority for the Defense of Financial Clients, through which the bank has committed to promoting immediate measures to guarantee care for vulnerable groups, including the elderly. These measures include favoring face-to-face care for these groups instead of being referred to other digital media or ATMs and extending service hours in the face of policies limiting reduced time slots. Also reinforcing human telephone attention for follow-up and consultation against using bots or automated systems. Other recommendations could be added, such as including vulnerability criteria in the individual customer classification and segmentation policy carried out by bank branches. This could lead to adopting adapted strategies and actions in certain branches with high percentages of clients with vulnerable conditions; such as the lower turnover of personnel with special training would generate a climate of greater familiarity and trust for the client.
8. Limitations and future lines of research
The study presents limitations that must be considered when evaluating our results and analysis. First, using cross-sectional data may be a limitation in drawing causal inferences; therefore, longitudinal data would allow for comparisons with results from a post-pandemic context. Moreover, complementary qualitative methods could be considered. Second, this study is limited to the Spanish banking sector, representing a specific population segment. It does not use random, stratified samples or analyze heterogeneous cultural and international contexts to generalize the results. Third, the sample comprised only vulnerable customers in two specific banks. Therefore, caution is warranted when generalizing the results. Finally, the pandemic context may imply a limitation. In a context of normality, certain behaviors could have occurred differently, especially the significance of CSR dimensions in service emotions; however, because such adverse situations affecting the behavior of vulnerable customers in the banking sector are rare, we believe this paper is a contribution.
This study also presents future research opportunities. First, we encourage broadening the scientific debate on the relationship between the banking sector and the (vulnerable) customers' perception of CSR. A future research line could explore how the CSR strategy is implemented in online environments where neither managers nor employees are present to co-create the service. Second, further exploration of the service emotions dimension would be of value to verify whether it is significant in normal circumstances and whether behavior remains the same as in a post-pandemic situation. Third, analyzing the causal model regarding customer age would also be a valuable line of study, assuming that Gen Z, millennials and seniors would behave differently, which could have meaningful repercussions for marketing strategies. Moreover, we also expect that non-vulnerable customers would behave differently. Finally, additional further exploration of other variables that determine relationship quality, such as loyalty, advocacy, self-brand connection, or WOM, together with the marketing outcomes contemplated (satisfaction, trust and engagement) may be of value to this body of work.
Figures
Selection criteria for individuals in the final sample (n = 734)
| Factor | Inclusion criteria |
|---|---|
| Education level | No studies and primary education |
| Occupation | Student, retired and unemployed |
| Total monthly household income | Between 0 and 1500 € |
| General assessment regarding their economic and social situation | Values of 3 or less on a scale of 1–5 (where 1 = Very bad and 5 = Very good) |
Note(s): The final sample included all customers who meet the criteria associated with the personal assessment factor regarding their economic and social situation and at least two of the other three factors considered
Source(s): Authors own creation
General features of the individuals in the final sample
| Characteristics | Frequency | % | Characteristics | Frequency | % |
|---|---|---|---|---|---|
| Gender | Income level | ||||
| Men | 345 | 47.0 | 0–1000 € | 258 | 35.1 |
| Women | 389 | 53.0 | 1001–1500 € | 351 | 47.8 |
| Age | 1501–2000 € | 75 | 10.2 | ||
| 18–29 | 134 | 18.2 | 2001–2500 € | 28 | 3.8 |
| 30–39 | 136 | 18.6 | >2500 € | 22 | 3.1 |
| 40–49 | 131 | 17.9 | Occupation | ||
| 50–59 | 134 | 18.2 | Student | 73 | 9.9 |
| 60–69 | 104 | 14.2 | Employed | 285 | 38.8 |
| >70 | 95 | 12.9 | Homemaker | 83 | 11.3 |
| Education level | Retired | 169 | 23.0 | ||
| No studies | 45 | 6.1 | Unemployed | 124 | 17.0 |
| Primary education | 162 | 22.1 | Economic and social valuation | ||
| Secondary education | 151 | 20.6 | 1 | 154 | 21.0 |
| High school diploma | 216 | 29.4 | 2 | 228 | 31.1 |
| Higher education | 160 | 21.8 | 3 | 352 | 47.9 |
| Total | 734 | 100% | Total | 734 | 100% |
Source(s): Authors own creation
Scales used
| Variables | References | Items |
|---|---|---|
| CSR toward the society | Liu et al. (2014) | 5 |
| CSR toward the customer | Ha et al. (2014) | 5 |
| Emotions associated with service | Mazaheri et al. (2011), Blasco (2014) | 9 |
| Pleasure | 6 | |
| Arousal | 3 | |
| Outcome quality | Idrovo et al. (2020) | 16 |
| Service conditions | 4 | |
| Product conditions | 3 | |
| Price conditions | 5 | |
| Access conditions | 4 | |
| Customer satisfaction | Bloemer and Odekerken (2002) | 5 |
| Customer trust | Camarero et al. (2005) | 6 |
| Customer engagement | Blasco (2014) | 4 |
Source(s): Authors own creation
Summary of the results after factor, reliability and validity analyses
| Items | Load | t-value |
|---|---|---|
| CSR TOWARDS THE SOCIETY (α = 0.903; CR = 0.91; AVE = 0.71) | ||
| CSRS1: They are aware of social issues | 0.829 | 27.025* |
| CSRS2: They are committed to ethical principles | Deleted | |
| CSRS3: The premises are adapted and accessible to everybody | 0.709 | 21.573* |
| CSRS4: They are committed to improving the well-being of the neighborhood/city in which they operate | 0.919 | 31.861* |
| CSRS5: Incorporate measures for the protection of the general environment | 0.898 | 30.670* |
| CSR TOWARDS THE CUSTOMER (α = 0.901; CR = 0.91; AVE = 0.76) | ||
| CSRC1: In my branch, they are honest with their customers | Deleted | |
| CSRC2: They offer complete information on the different products transparently | 0.889 | 30.334* |
| CSRC3: They make an effort to learn about my needs | 0.815 | 26.420* |
| CSRC4: They have mechanisms in place to resolve customers' complaints | 0.914 | 31.742* |
| CSRC5: They fulfill their contractual obligations with the customer | Deleted | |
| EMOTIONS ASSOCIATED WITH THE SERVICE (CR = 0.84; AVE = 0.73) | ||
| Pleasure (α = 0.952; CR = 0.95; AVE = 0.77) | 0.979 | 22.428* |
| EMO1.1: Angry/Glad | 0.821 | Fixed |
| EMO1.2: Sad/Cheerful | 0.892 | 30.644* |
| EMO1.3: Unhappy/Happy | 0.903 | 31.267* |
| EMO1.4: Dissatisfied/Satisfied | 0.908 | 31.571* |
| EMO1.5: Disappointed/Excited | 0.890 | 30.502* |
| EMO1.6: Annoyed/Pleased | 0.851 | 28.355* |
| Arousal (α = 0.936; CR = 0.94; AVE = 0.83) | 0.707 | 17.656* |
| EMO2.1: Indifferent/Unexpected | 0.858 | Fixed |
| EMO2.2: Not amazed at all/Very amazed | 0.956 | 37.746* |
| EMO2.3: Not fascinated at all/Very fascinated | 0.924 | 35.735* |
| OUTCOME QUALITY (CR = 0.86; AVE = 0.61) | ||
| Service conditions (α = 0.909; CR = 0.92; AVE = 0.74) | 0.941 | 27.449* |
| OUT1.1: On the whole, the service I have received is fitting | 0.885 | Fixed |
| OUT1.2: Compared with other banks the level of quality here is acceptable | 0.897 | 35.954* |
| OUT1.3: I received the service I expected | 0.732 | 24.530* |
| OUT1.4: I am happy with the outcome I obtained | 0.925 | 38.499* |
| Product conditions (α = 0.931; CR = 0.93; AVE = 0.82) | 0.765 | 22.281* |
| OUT2.1: The variety and characteristics of the products offered are adequate | 0.936 | Fixed |
| OUT2.2: The convenience of the products offered is adequate | 0.951 | 48.105* |
| OUT2.3: Based on my experience, the overall quality of the products offered is adequate | 0.831 | 33.841* |
| Price conditions (α = 0.911; CR = 0.90; AVE = 0.65) | 0.665 | 15.864* |
| OUT3.1: The total cost that they generate is reasonable | 0.734 | Fixed |
| OUT3.2: Interest or commission payments are justified | 0.813 | 22.028* |
| OUT3.3: The charges I have to pay are normal for the quality of service offered | 0.887 | 24.107* |
| OUT3.4: There are no hidden costs in the services offered | 0.869 | 23.611* |
| OUT3.5: Information is provided about any modifications to charges | 0.807 | 21.848* |
| Access conditions (α = 0.825; CR = 0.83; AVE = 0.61) | 0.737 | 17.220* |
| OUT4.1: I usually get an agile and quick service | 0.770 | Fixed |
| OUT4.2: I do not have to go far to visit my bank branch | Deleted | |
| OUT4.3: The total effort I make to carry out the management in the bank is reasonable | 0.792 | 20.378* |
| OUT4.4: The number of tellers attending the public is sufficient | 0.786 | 20.252* |
| CUSTOMER SATISFACTION (α = 0.966; CR = 0.97; AVE = 0.88) | ||
| SAT1: My expectations have been met | 0.933 | 33.456* |
| SAT2: I am satisfied with the value for money offered | 0.915 | 32.328* |
| SAT3: I am satisfied with the service I have received | Deleted | |
| SAT4: I am satisfied with the company | 0.941 | 33.975* |
| SAT5: In general I am really satisfied | 0.959 | 35.162* |
| CUSTOMER TRUST (α = 0.927; CR = 0.93; AVE = 0.73) | ||
| TRU1: I trust the professional competence of the staff in my branch | 0.909 | 31.739* |
| TRU2: This branch has sufficient technical resources (installations, technology, etc.) | 0.795 | 25.627* |
| TRU3: The employees in this branch are sufficiently well trained | 0.747 | 23.444* |
| TRU4: I trust the good intentions of the staff in this branch | 0.897 | 31.075* |
| TRU5: I consider that behavior in general is ethical | Deleted | |
| TRU6: This bank is serious and keeps its promises | 0.901 | 31.267* |
| CUSTOMER ENGAGEMENT (α = 0.938; CR = 0.94; AVE = 0.79) | ||
| ENG1: I feel valued in my interactions with the branch | 0.866 | 29.184* |
| ENG2: I feel as though I have a personal relationship with my branch | 0.905 | 31.406* |
| ENG3: I consider that people in my branch are concerned about me as a person | 0.922 | 32.431* |
| ENG4: I feel an emotional link with my branch | 0.870 | 29.431* |
| Fit of the model: χ2/df = 487.782/261 = 1.868; NFI = 0.968; NNFI = 0.977; IFI = 0.981; CFI = 0.981; SRMR = 0.031; RMSEA = 0.034 | ||
Note(s): IR = individual reliability; CR = composite reliability; AVE = average variance extracted.*p < 0.001
Source(s): Authors own creation
Scale discriminant validity
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||
|---|---|---|---|---|---|---|---|---|
| 1 | CSR towards society | 0.84 | ||||||
| 2 | CSR towards customer | 0.40* [0.33; 0.46] | 0.87 | |||||
| 3 | Service emotions | 0.36* [0.29; 0.43] | 0.55* [0.49; 0.61] | 0.85 | ||||
| 4 | Outcome quality | 0.46* [0.39; 0.52] | 0.89* [0.87; 0.92] | 0.64* [0.58; 0.69] | 0.80 | |||
| 5 | Customer satisfaction | 0.43* [0.37; 0.50] | 0.69* [0.65; 0.73] | 0.57* [0.52; 0.63] | 0.81* [0.78; 0.84] | 0.94 | ||
| 6 | Customer trust | 0.47* [0.41; 0.53] | 0.83* [0.80; 0.86] | 0.52* [0.45; 0.58] | 0.86* [0.83; 0.89] | 0.82* [0.80; 0.85] | 0.85 | |
| 7 | Customer engagement | 0.43* [0.36; 0.49] | 0.63* [0.58; 0.68] | 0.57* [0.51; 0.63] | 0.66* [0.61; 0.71] | 0.63* [0.58; 0.67] | 0.64* [0.59; 0.68] | 0.89 |
Note(s): Below the diagonal: correlation estimated between the factors. Diagonal: square root of AVE. *p < 0.05
Source(s): Authors own creation
Descriptive statistics and covariance matrix for the variables (n = 734)
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | OUT1.1 | 1.093 | |||||||||||||||||||||
| 2 | OUT1.2 | 0.874 | 1.095 | ||||||||||||||||||||
| 3 | OUT1.3 | 0.741 | 0.708 | 1.305 | |||||||||||||||||||
| 4 | OUT1.4 | 0.931 | 0.989 | 0.776 | 1.186 | ||||||||||||||||||
| 5 | OUT2.1 | 0.637 | 0.701 | 0.621 | 0.764 | 1.131 | |||||||||||||||||
| 6 | OUT2.2 | 0.643 | 0.713 | 0.640 | 0.792 | 1.011 | 1.129 | ||||||||||||||||
| 7 | OUT2.3 | 0.651 | 0.663 | 0.602 | 0.727 | 0.864 | 0.873 | 1.101 | |||||||||||||||
| 8 | OUT3.1 | 0.474 | 0.524 | 0.691 | 0.576 | 0.566 | 0.619 | 0.597 | 1.768 | ||||||||||||||
| 9 | OUT3.2 | 0.446 | 0.489 | 0.609 | 0.516 | 0.521 | 0.544 | 0.554 | 1.148 | 1.372 | |||||||||||||
| 10 | OUT3.3 | 0.546 | 0.566 | 0.673 | 0.613 | 0.574 | 0.604 | 0.589 | 1.022 | 1.070 | 1.520 | ||||||||||||
| 11 | OUT3.4 | 0.608 | 0.624 | 0.691 | 0.666 | 0.632 | 0.660 | 0.664 | 0.970 | 0.974 | 1.201 | 1.560 | |||||||||||
| 12 | OUT3.5 | 0.528 | 0.555 | 0.685 | 0.630 | 0.568 | 0.590 | 0.591 | 0.988 | 0.908 | 1.132 | 1.215 | 1.675 | ||||||||||
| 13 | OUT4.1 | 0.611 | 0.526 | 0.679 | 0.578 | 0.437 | 0.484 | 0.490 | 0.552 | 0.496 | 0.594 | 0.625 | 0.586 | 1.623 | |||||||||
| 14 | OUT4.3 | 0.618 | 0.580 | 0.567 | 0.610 | 0.496 | 0.492 | 0.532 | 0.489 | 0.413 | 0.501 | 0.571 | 0.535 | 0.870 | 1.260 | ||||||||
| 15 | OUT4.4 | 0.597 | 0.562 | 0.610 | 0.645 | 0.496 | 0.502 | 0.523 | 0.475 | 0.423 | 0.479 | 0.543 | 0.560 | 0.960 | 0.831 | 1.476 | |||||||
| 16 | EMO1.1 | 0.533 | 0.505 | 0.610 | 0.552 | 0.436 | 0.455 | 0.479 | 0.489 | 0.409 | 0.478 | 0.509 | 0.486 | 0.580 | 0.450 | 0.498 | 1.155 | ||||||
| 17 | EMO1.2 | 0.464 | 0.466 | 0.585 | 0.490 | 0.386 | 0.420 | 0.408 | 0.474 | 0.403 | 0.412 | 0.411 | 0.469 | 0.509 | 0.432 | 0.453 | 0.868 | 1.046 | |||||
| 18 | EMO1.3 | 0.473 | 0.463 | 0.551 | 0.506 | 0.390 | 0.430 | 0.422 | 0.437 | 0.379 | 0.414 | 0.423 | 0.443 | 0.510 | 0.416 | 0.472 | 0.832 | 0.941 | 1.037 | ||||
| 19 | EMO1.4 | 0.488 | 0.511 | 0.577 | 0.545 | 0.438 | 0.466 | 0.448 | 0.506 | 0.424 | 0.480 | 0.487 | 0.481 | 0.534 | 0.398 | 0.507 | 0.847 | 0.863 | 0.874 | 1.128 | |||
| 20 | EMO1.5 | 0.427 | 0.462 | 0.532 | 0.509 | 0.415 | 0.440 | 0.414 | 0.429 | 0.360 | 0.409 | 0.427 | 0.424 | 0.432 | 0.365 | 0.461 | 0.733 | 0.753 | 0.776 | 0.879 | 0.986 | ||
| 21 | EMO1.6 | 0.396 | 0.405 | 0.478 | 0.461 | 0.372 | 0.388 | 0.388 | 0.393 | 0.341 | 0.364 | 0.381 | 0.370 | 0.399 | 0.348 | 0.436 | 0.659 | 0.664 | 0.687 | 0.788 | 0.806 | 0.888 | |
| 22 | EMO2.1 | 0.283 | 0.293 | 0.280 | 0.341 | 0.283 | 0.264 | 0.270 | 0.250 | 0.213 | 0.211 | 0.267 | 0.227 | 0.280 | 0.216 | 0.314 | 0.501 | 0.508 | 0.519 | 0.559 | 0.591 | 0.604 | 0.905 |
| 23 | EMO2.2 | 0.316 | 0.322 | 0.354 | 0.387 | 0.302 | 0.293 | 0.283 | 0.289 | 0.249 | 0.298 | 0.319 | 0.274 | 0.332 | 0.306 | 0.349 | 0.496 | 0.514 | 0.523 | 0.595 | 0.599 | 0.604 | 0.757 |
| 24 | EMO2.3 | 0.342 | 0.374 | 0.400 | 0.429 | 0.337 | 0.314 | 0.294 | 0.299 | 0.271 | 0.314 | 0.343 | 0.307 | 0.345 | 0.302 | 0.374 | 0.532 | 0.511 | 0.523 | 0.605 | 0.618 | 0.635 | 0.722 |
| 25 | ENG1 | 0.643 | 0.623 | 0.826 | 0.680 | 0.549 | 0.572 | 0.549 | 0.632 | 0.555 | 0.622 | 0.619 | 0.606 | 0.634 | 0.548 | 0.556 | 0.626 | 0.558 | 0.550 | 0.602 | 0.535 | 0.499 | 0.349 |
| 26 | ENG2 | 0.635 | 0.629 | 0.757 | 0.704 | 0.552 | 0.598 | 0.551 | 0.639 | 0.560 | 0.599 | 0.623 | 0.592 | 0.543 | 0.452 | 0.557 | 0.624 | 0.539 | 0.574 | 0.656 | 0.580 | 0.546 | 0.439 |
| 27 | ENG3 | 0.644 | 0.645 | 0.803 | 0.734 | 0.611 | 0.646 | 0.599 | 0.706 | 0.608 | 0.682 | 0.661 | 0.647 | 0.592 | 0.514 | 0.584 | 0.662 | 0.579 | 0.599 | 0.654 | 0.576 | 0.537 | 0.389 |
| 28 | ENG4 | 0.593 | 0.575 | 0.742 | 0.675 | 0.546 | 0.598 | 0.558 | 0.693 | 0.555 | 0.591 | 0.594 | 0.571 | 0.541 | 0.429 | 0.608 | 0.611 | 0.528 | 0.558 | 0.644 | 0.573 | 0.524 | 0.428 |
| 29 | SAT1 | 0.741 | 0.708 | 1.305 | 0.776 | 0.621 | 0.640 | 0.602 | 0.691 | 0.609 | 0.673 | 0.691 | 0.685 | 0.679 | 0.567 | 0.610 | 0.610 | 0.585 | 0.551 | 0.577 | 0.532 | 0.478 | 0.280 |
| 30 | SAT2 | 0.680 | 0.671 | 1.122 | 0.732 | 0.591 | 0.604 | 0.576 | 0.734 | 0.585 | 0.661 | 0.672 | 0.684 | 0.605 | 0.545 | 0.604 | 0.578 | 0.546 | 0.525 | 0.538 | 0.513 | 0.448 | 0.283 |
| 31 | SAT4 | 0.746 | 0.716 | 0.117 | 0.786 | 0.602 | 0.609 | 0589 | 0.641 | 0.573 | 0.669 | 0.684 | 0.661 | 0.633 | 0.566 | 0.601 | 0.644 | 0.572 | 0.557 | 0.560 | 0.521 | 0.476 | 0.307 |
| 32 | SAT5 | 0.726 | 0.691 | 1.131 | 0.771 | 0.617 | 0.630 | 0.606 | 0.658 | 0.584 | 0.664 | 0.677 | 0.674 | 0.628 | 0.568 | 0.609 | 0.623 | 0.562 | 0.541 | 0.547 | 0.518 | 0.461 | 0.299 |
| 33 | TRU1 | 0.759 | 0.714 | 0.885 | 0.754 | 0.581 | 0.584 | 0.586 | 0.523 | 0.493 | 0.593 | 0.621 | 0.604 | 0.600 | 0.606 | 0.599 | 0.534 | 0.484 | 0.472 | 0.471 | 0.435 | 0.404 | 0.284 |
| 34 | TRU2 | 0.602 | 0.555 | 0.698 | 0.589 | 0.453 | 0.449 | 0.461 | 0.458 | 0.411 | 0.501 | 0.527 | 0.480 | 0.509 | 0.521 | 0.521 | 0.380 | 0.347 | 0.340 | 0.340 | 0.317 | 0.272 | 0.193 |
| 35 | TRU3 | 0.736 | 0.671 | 0.633 | 0.726 | 0.580 | 0.595 | 0.558 | 0.419 | 0.417 | 0.510 | 0.558 | 0.502 | 0.519 | 0.499 | 0.497 | 0.424 | 0.399 | 0.401 | 0.414 | 0.369 | 0.343 | 0.263 |
| 36 | TRU4 | 0.726 | 0.655 | 0.813 | 0.716 | 0.564 | 0.568 | 0.569 | 0.496 | 0.484 | 0.570 | 0.600 | 0.600 | 0.555 | 0.584 | 0.588 | 0.509 | 0.428 | 0.433 | 0.439 | 0.390 | 0.367 | 0.240 |
| 37 | TRU6 | 0.760 | 0.760 | 0.911 | 0.825 | 0.659 | 0.672 | 0.646 | 0.581 | 0.557 | 0.653 | 0.731 | 0.688 | 0.626 | 0.583 | 0.666 | 0.563 | 0.497 | 0.504 | 0.526 | 0.471 | 0.437 | 0.294 |
| 38 | CSRS1 | 0.290 | 0.336 | 0.455 | 0.345 | 0.333 | 0.340 | 0.318 | 0.354 | 0.363 | 0.352 | 0.378 | 0.400 | 0.379 | 0.308 | 0.343 | 0.296 | 0.283 | 0.292 | 0.324 | 0.321 | 0.281 | 0.204 |
| 39 | CSRS3 | 0.324 | 0.350 | 0.399 | 0.363 | 0.323 | 0.321 | 0.333 | 0.335 | 0.360 | 0.368 | 0.445 | 0.411 | 0.297 | 0.270 | 0.342 | 0.314 | 0.264 | 0.278 | 0.322 | 0.305 | 0.310 | 0.231 |
| 40 | CSRS4 | 0.338 | 0.360 | 0.468 | 0.410 | 0.400 | 0.398 | 0.368 | 0.444 | 0.398 | 0.403 | 0.454 | 0.433 | 0.373 | 0.296 | 0.363 | 0.315 | 02.80 | 0.298 | 0.353 | 0.328 | 0.299 | 0.211 |
| 41 | CSRS5 | 0.262 | 0.289 | 0.406 | 0.297 | 0.342 | 0.345 | 0.281 | 0.355 | 0.317 | 0.320 | 0.366 | 0.390 | 0.327 | 0.261 | 0.297 | 0.260 | 0.236 | 0.233 | 0.285 | 0.273 | 0.254 | 0.169 |
| 42 | CSRC2 | 0.758 | 0.690 | 0.659 | 0.754 | 0.562 | 0.588 | 0.568 | 0.467 | 0.460 | 0.543 | 0.576 | 0.577 | 0.561 | 0.548 | 0.577 | 0.507 | 0.441 | 0.439 | 0.454 | 0.390 | 0.376 | 0.270 |
| 43 | CSRC3 | 0.792 | 0.726 | 0.672 | 0.788 | 0.606 | 0.606 | 0.573 | 0.558 | 0.498 | 0.544 | 0.627 | 0.559 | 0.660 | 0.555 | 0.604 | 0.514 | 0.443 | 0.467 | 0.480 | 0.441 | 0.411 | 0.317 |
| 44 | CSRC4 | 0.807 | 0.763 | 0.737 | 0.829 | 0.610 | 0.663 | 0.621 | 0.513 | 0.491 | 0.567 | 0.618 | 0.610 | 0.605 | 0.604 | 0.608 | 0.527 | 0.479 | 0.473 | 0.500 | 0.446 | 0.405 | 0.259 |
| Observations | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | |
| Mean | 4.147 | 4.004 | 3.700 | 3.966 | 3.679 | 3.661 | 3.574 | 2.918 | 3.173 | 3.413 | 3.488 | 3.481 | 3.619 | 3.792 | 3.579 | 3.514 | 3.499 | 3.444 | 3.307 | 3.165 | 3.116 | 3.032 | |
| SD | 1.045 | 1.046 | 1.142 | 1.089 | 1.063 | 1.062 | 1.049 | 1.329 | 1.141 | 1.232 | 1.249 | 1.294 | 1.273 | 1.122 | 1.214 | 1.074 | 1.022 | 1.018 | 1.062 | 0.993 | 0.942 | 0.951 | |
| 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | OUT1.1 | ||||||||||||||||||||||
| 2 | OUT1.2 | ||||||||||||||||||||||
| 3 | OUT1.3 | ||||||||||||||||||||||
| 4 | OUT1.4 | ||||||||||||||||||||||
| 5 | OUT2.1 | ||||||||||||||||||||||
| 6 | OUT2.2 | ||||||||||||||||||||||
| 7 | OUT2.3 | ||||||||||||||||||||||
| 8 | OUT3.1 | ||||||||||||||||||||||
| 9 | OUT3.2 | ||||||||||||||||||||||
| 10 | OUT3.3 | ||||||||||||||||||||||
| 11 | OUT3.4 | ||||||||||||||||||||||
| 12 | OUT3.5 | ||||||||||||||||||||||
| 13 | OUT4.1 | ||||||||||||||||||||||
| 14 | OUT4.3 | ||||||||||||||||||||||
| 15 | OUT4.4 | ||||||||||||||||||||||
| 16 | EMO1.1 | ||||||||||||||||||||||
| 17 | EMO1.2 | ||||||||||||||||||||||
| 18 | EMO1.3 | ||||||||||||||||||||||
| 19 | EMO1.4 | ||||||||||||||||||||||
| 20 | EMO1.5 | ||||||||||||||||||||||
| 21 | EMO1.6 | ||||||||||||||||||||||
| 22 | EMO2.1 | ||||||||||||||||||||||
| 23 | EMO2.2 | 0.932 | |||||||||||||||||||||
| 24 | EMO2.3 | 0.832 | 0.947 | ||||||||||||||||||||
| 25 | ENG1 | 0.404 | 0.428 | 1.439 | |||||||||||||||||||
| 26 | ENG2 | 0.434 | 0.484 | 1.259 | 1.804 | ||||||||||||||||||
| 27 | ENG3 | 0.437 | 0.477 | 1.236 | 1.384 | 1.596 | |||||||||||||||||
| 28 | ENG4 | 0.457 | 0.490 | 1.145 | 1.536 | 1.382 | 1.861 | ||||||||||||||||
| 29 | SAT1 | 0.354 | 0.400 | 0.826 | 0.757 | 0.803 | 0.742 | 1.305 | |||||||||||||||
| 30 | SAT2 | 0.332 | 0.372 | 0.778 | 0.736 | 0.773 | 0.730 | 1.122 | 1.276 | ||||||||||||||
| 31 | SAT4 | 0.363 | 0.426 | 0.796 | 0.762 | 0.809 | 0.733 | 1.117 | 1.075 | 1.258 | |||||||||||||
| 32 | SAT5 | 0.351 | 0.409 | 0.775 | 0.755 | 0.804 | 0.721 | 1.131 | 1.103 | 1.133 | 1.235 | ||||||||||||
| 33 | TRU1 | 0.306 | 0.363 | 0.735 | 0.698 | 0.740 | 0.702 | 0.885 | 0.835 | 0.904 | 0.857 | 1.185 | |||||||||||
| 34 | TRU2 | 0.239 | 0.259 | 0.580 | 0.514 | 0.564 | 0.545 | 0.698 | 0.685 | 0.712 | 0.684 | 0.846 | 1.059 | ||||||||||
| 35 | TRU3 | 0.287 | 0.323 | 0.655 | 0.622 | 0.666 | 0.592 | 0.633 | 0.575 | 0.646 | 0.622 | 0.700 | 0.599 | 0.978 | |||||||||
| 36 | TRU4 | 0.270 | 0.337 | 0.690 | 0.669 | 0.704 | 0.670 | 0.813 | 0.793 | 0.862 | 0.822 | 0.959 | 0.793 | 0.684 | 1.133 | ||||||||
| 37 | TRU6 | 0.343 | 0.391 | 0.754 | 0.745 | 0.787 | 0.742 | 0.911 | 0.879 | 0.900 | 0.908 | 0.980 | 0.802 | 0.695 | 0.965 | 1.226 | |||||||
| 38 | CSRS1 | 0.262 | 0.275 | 0.447 | 0.437 | 0.479 | 0.438 | 0.455 | 0.455 | 0.418 | 0.408 | 0.470 | 0.365 | 0.330 | 0.424 | 0.452 | 1.052 | ||||||
| 39 | CSRS3 | 0.241 | 0.282 | 0.384 | 0.446 | 0.453 | 0.392 | 0.399 | 0.430 | 0.406 | 0.404 | 0.403 | 0.383 | 0.379 | 0.378 | 0.429 | 0.706 | 1.225 | |||||
| 40 | CSRS4 | 0.248 | 0.257 | 0.460 | 0.489 | 0.516 | 0.501 | 0.468 | 0.490 | 0.420 | 0.438 | 0.432 | 0.369 | 0.360 | 0.423 | 0.486 | 0.809 | 0.770 | 1.124 | ||||
| 41 | CSRS5 | 0.203 | 0.217 | 0.387 | 0.400 | 0.431 | 0.410 | 0.406 | 0.437 | 0.364 | 0.373 | 0.383 | 0.335 | 0.298 | 0.382 | 0.417 | 0.774 | 0.673 | 0.888 | 1.007 | |||
| 42 | CSRC2 | 0.318 | 0.371 | 0.678 | 0.637 | 0.724 | 0.633 | 0.659 | 0.590 | 0.763 | 0.658 | 0.726 | 0.570 | 0.750 | 0.687 | 0.736 | 0.351 | 0.339 | 0.359 | 0.310 | 1.034 | ||
| 43 | CSRC3 | 0.346 | 0.403 | 0.698 | 0.720 | 0.749 | 0.699 | 0.672 | 0.625 | 0.699 | 0.670 | 0.715 | 0.563 | 0.740 | 0.708 | 0.764 | 0.330 | 0.374 | 0.375 | 0.294 | 0.740 | 1.109 | |
| 44 | CSRC4 | 0.297 | 0.357 | 0.690 | 0.645 | 0.718 | 0.603 | 0.737 | 0.655 | 0.735 | 0.714 | 0.769 | 0.617 | 0.791 | 0.728 | 0.790 | 0.344 | 0.349 | 0.350 | 0.308 | 0.907 | 0.818 | 1.136 |
| Observations | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | 734 | |
| Mean | 2.970 | 2.953 | 3.509 | 3.276 | 3.416 | 3.109 | 3.700 | 3.605 | 3.786 | 3.753 | 3.990 | 4.032 | 4.214 | 4.029 | 3.878 | 3.173 | 3.446 | 3.115 | 3.105 | 4.176 | 4.006 | 4.130 | |
| SD | 0.965 | 0.973 | 1.199 | 1.343 | 1.263 | 1.364 | 1.142 | 1.129 | 1.121 | 1.111 | 1.088 | 1.029 | 0.988 | 1.064 | 1.107 | 1.025 | 1.106 | 1.060 | 1.003 | 1.017 | 1.053 | 1.065 | |
Source(s): Authors own creation
Summary of the results of the structural model
| Hyp | Load | t-value | Result | |
|---|---|---|---|---|
| 1 | CSR towards society → Emotions associated with service | 0.183 | 4.500* | Supported |
| 2 | CSR towards customer → Emotions associated with service | 0.832 | 6.903* | Supported |
| 3 | Emotions associated with service → Outcome quality | 0.984 | 7.306* | Supported |
| 4 | Outcome quality → Customer satisfaction | 0.845 | 25.873* | Supported |
| 5 | Outcome quality → Customer trust | 0.909 | 22.694* | Supported |
| 6 | Customer satisfaction → Customer engagement | 0.310 | 6.242* | Supported |
| 7 | Customer trust → Customer engagement | 0.405 | 8.002* | Supported |
| Total effects | Indirect effects | |||
| Path | Load | t-value | Load | t-value | |
|---|---|---|---|---|---|
| 8 | CSR towards society → Outcome quality | 0.180 | 5.629* | 0.180 | 5.629* |
| 9 | CSR towards society → Customer satisfaction | 0.152 | 5.644* | 0.152 | 5.644* |
| 10 | CSR towards society → Customer trust | 0.163 | 5.465* | 0.163 | 5.465* |
| 11 | CSR towards society → Customer engagement | 0.113 | 5.740* | 0.113 | 5.740* |
| 12 | CSR towards customer → Outcome quality | 0.818 | 5.288* | 0.818 | 5.288* |
| 13 | CSR towards customer → Customer satisfaction | 0.691 | 5.276* | 0.691 | 5.276* |
| 14 | CSR towards customer → Customer trust | 0.743 | 5.437* | 0.743 | 5.437* |
| 15 | CSR towards customer → Customer engagement | 0.515 | 5.201* | 0.515 | 5.201* |
| 16 | Emotions associated with service → Customer satisfaction | 0.831 | 7.273* | 0.831 | 7.273* |
| 17 | Emotions associated with service → Customer trust | 0.894 | 7.714* | 0.894 | 7.714* |
| 18 | Emotions associated with service → Customer engagement | 0.620 | 7.081* | 0.620 | 7.081* |
| 19 | Outcome quality → Customer engagement | 0.630 | 17.491* | 0.630 | 17.491* |
Note(s): Fit of the model: χ2/df = 631.141/274 = 2.303; NFI = 0.959; NNFI = 0.968; IFI = 0.973; CFI = 0.973; SRMR = 0.045; RMSEA = 0.042
*p < 0.001
Source(s): Authors own creation
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Acknowledgements
Lidia Vidal-Meliá was supported by the Margarita Salas postdoctoral contract MGS/202X/XX(UP2021-021) financed by the European Union-NextGenerationEU.