Introduction

Customer engagement (CE) has been viewed as a strategic imperative for a firm’s competitive advantage (Ostrom et al., 2015) and financial performance (Roy et al., 2018). Van Doorn et al. (2010) argue that marketers should consider more than the quality and value of what they offer, focusing instead on consumer-based metrics in evaluating the company’s performance, such as customer commitment (Bansal et al., 2004), brand experience (Brakus et al., 2009), brand–customer connections (Fournier, 1998), and consumer identification (Ahearne et al., 2005). Paying closer attention to these customer-centric approaches, the concept of CE is suggested as a strategy for building long-term, sustainable competitive advantages (Kumar and Pansari, 2016). For example, global companies such as Heineken and Tesla have made considerable investments in customer engagement initiatives because highly engaged customers tend to be more loyal, cost less in terms of maintaining the relationship, and refer more business, making them more profitable in the long run (Nyadzayo et al., 2020).

While CE has been defined in various ways as a broad concept, including affective, cognitive, and behavioral dimensions, there has been consensus among researchers regarding its nature as a multi-dimensional behavior construct. Defining CE as a “customer’s behavioral manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers” (Van Doorn et al., 2010, p. 254), the literature has been developed and validated a comprehensive scale to measure four dimensions of CE’s behavioral aspects, called customer engagement behaviors (CEB): purchases, referrals, influence, and knowledge (Kumar and Pansari, 2016; Prentice and Loureiro, 2018; Junaid et al., 2020). Barari et al. (2020) also argue that attitudinal CE acts as a driver of behavioral outcomes, including purchases, while behavioral CE has the potential to influence firm performance directly. Put differently, compared to attitudinal or psychological aspects, behavioral aspects contribute more directly to a firm, such as enhancing service quality through knowledge sharing and firm profitability through purchases. Thus, investigating the behavioral aspects of CE provides more insightful theoretical and managerial implications regarding relative importance of CEB types to a firm and allocation of financial resources to different types of CEBs.

Highlighting the importance of CEB, engagement theory argues that favorable experiences with or attributes of a brand or firm evoke customers’ emotions and attitudes, ultimately leading to CEB (Pansari and Kumar, 2017). The current study draws upon engagement theory to examine how corporate reputation based on customer perspectives influences customer identification and brand love, which result in CEB. Previous studies have found that CEB is stimulated by brand reputation (Choi and Burnham, 2020) and the social value of a reputable brand (Prentice and Loureiro, 2018). Van Doorn et al. (2010) conceptually propose that firm-based factors (e.g., brand characteristics and firm reputation) can facilitate CEB. In addition, Walsh and Beatty (2007) insist that research on reputation should concentrate on end customers who primarily create revenue streams for the firm. Yet, very little research has empirically investigated the impact of corporate reputation on CEB. In light of this research void, this study contributes to the CEB literature by identifying customer-based corporate reputation (CBR) as an antecedent of CEB.

Furthermore, previous studies exploring the relationship between corporate reputation and consumer voluntary behaviors have included only partial facets of CEB, such as spending and feedback (Walsh et al., 2014; Choi and Burnham, 2020), word of mouth (Jalilvand et al., 2017; Walsh et al., 2009), or helping the company (Bartikowski and Walsh, 2011). There is little empirical research that aggregates the four types of CEB as an outcome of corporate reputation. Table 1 summarizes the previous research on the impact of corporate reputation on customer behaviors that are similar to types of CEB. Thus, this study extends the current body of knowledge of CEB by investigating comprehensive types of CEB.

Table 1 Literature review regarding the impact of corporate reputation on CEB dimensions
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Additionally, this research uses industry type—product or service—to ascertain the difference in the indirect effect of CBR on CEB through customer identification and brand love. Given that service businesses are distinct from product businesses, it is useful to understand whether the role of CBR in leading to CEB is more important in the former than the latter. Finally, the current study shows the relative impact of the five dimensions of CBR on the different types of CEB. This finding not only makes insightful theoretical contributions but also sheds light on managerial implications, suggesting that marketers should allocate their resources to factors that build reputation effectively and efficiently to elicit different forms of CEB.

Theoretical background and hypotheses development

Engagement theory

In the past, a firm’s relationship with customers had been limited to purchasing behaviors, but researchers have argued that the relationship should include long-term cooperation with the customers (Pansari and Kumar, 2017; Harmeling et al., 2017). Relationship marketing has also stressed the importance of the long-term relationships with customers because these relationships boost the firm’s productivity and efficiency (Morgan and Hunt, 1994). Thus, firms should not only improve the quality of these relationships, but should also encourage customers to participate in marketing activities such as suggesting ideas for offering improvement and promoting their business to other customers.

Highlighting the importance of engaging behaviors beyond purchases, engagement theory claims that customers contribute to brands when they perceive a close connection to those brands (Kumar and Pansari, 2016). Specifically, the level of the engagement can be determined by the customers’ positive attitudes toward the brands as well as the emotional connectedness they feel with the firm (Pansari and Kumar, 2017). Furthermore, these attitudes and emotions are influenced by experiences with the brands, including customers’ memories of product performance and brand associations such as reputation and personality, which ultimately result in customer engagement (Harmeling et al., 2017). Engagement theory, therefore, provides a basis for explaining the impact of CBR on CEB, as well as the role of customer perceptions (i.e., customer identification and brand love) mediating between CBR and CEB.

Customer-based corporate reputation (CBR)

Researchers have conceptualized corporate reputation either from an economic perspective or through the lens of institutional theory (de Leaniz and del Bosque Rodríguez, 2016). The economic perspective regards corporate reputation as insiders’ and outsiders’ appraisals and expectations of certain organizational attributes (Weigelt and Camerer, 1988). From this perspective, because corporate reputation is heavily influenced by the firm’s previous financial performance (e.g., accounting profitability and risk), prior attempts to determine the relationship between corporate reputation and firm value (or performance) tended to “be victimized by a circularity—firm value improves reputation which improves firm value ad infinitum” (Black et al., 2000, p. 33).

On the other hand, the institutional view characterizes corporate reputation as a comprehensive or global impression that reflects perceptions of certain stakeholders (e.g., customers, employees, investors, etc.) (Fombrun and van Riel, 1997). Corporate reputation is interpreted as a collective representation of both the financial and non-financial aspects of a firm’s past behaviors and outcomes, and provides valuable results to multiple stakeholders (Rindova et al., 2005). Adapting the institutional view, most previous research has investigated the consequences of corporate reputation, but has tended to include constructs that are not related to customers’ responses, such as firm sales, financial performance, and market share (Robert and Dowling, 2002; Wei et al., 2017).

However, a firm’s corporate reputation may not be consistent across all stakeholders (Nguyen and Leblanc, 2001). Researchers argue that corporate reputation should be assessed as customers’ attitude-like judgments of a firm’s demeanor and actions because customers are a crucial stakeholder group and a primary generator of a firm’s revenue (Walsh and Beatty, 2007; Bartikowski and Walsh, 2011). Capturing the diverse facets of customer perceptions or opinions, Walsh and Beatty (2007) conceptualize CBR as “the customer’s overall evaluation of a firm based on his or her reactions to the firm’s goods, services, communication activities, interactions with the firm and/or its representatives or constituencies (such as employees, management, or other customers) and/or known corporate activities” (p. 129).

As mentioned earlier, existing empirical studies are limited by their lack of investigation of variables related to customers’ emotions, attitudes, and behaviors as consequences of corporate reputation. Moreover, prior studies have used the reputation scores provided by a third party (i.e., the Fortune magazine index1). Also, even if research includes the reputation based on customers’ attitudes and behaviors, their studies have adapted a short version2 of scale items that measures customers’ broad perceptions of corporate reputation. Given the importance of corporate reputation from customers’ perspective, Walsh and Beatty, (2007) develop five dimensions of corporate reputation based on customers’ evaluations or perceptions, called CBR. Customer orientation is how customers perceive employees’ willingness to satisfy customer demands. Good employer refers to customers’ perceptions of how the company treats its employees and pays attention to their interests. Product and service quality reflects how customers perceive the quality, innovation, value, and reliability of the firm’s offerings. The reliable and financially strong company dimension is concerned with customers’ perceptions of the company’s competence, solidity, and profitability. Lastly, the social and environmental responsibility refers to customers’ beliefs about the company’s role in society and toward the environment.

The impact of CBR on CEB

The management literature has identified a partner’s reputation as an important component of joint projects (Jemison and Sitkin, 1986). They imply that stakeholders’ perceptions of a good corporate reputation can lead to goodwill toward the company (Fombrun, 1996). Consistent with engagement theory, when customers have a feeling of emotional connection to or favorable perceptions of a firm, they are more likely to contribute to that firm. Kumar and Pansari, (2016), focusing on the wider customer–firm relationship beyond just transactions, suggest four behavioral dimensions of CE, that is, CEB: purchases, referrals, influence, and knowledge. Customer purchases contribute directly to firm’s value over the long term as a crucial revenue source. Gatti et al. (2012) found that corporate reputation has been found to have a positive impact on purchase intentions through perceived product quality (Gatti et al., 2012) and favorable emotions (Kim and Lennon, 2013). Similarly, CBR positively influences customers’ share of wallet through commitment (Walsh et al., 2014) and recency–frequency–monetary value through perceived value and risk (Walsh et al., 2018).

Conceptualizing the three aspects of CEB as customers’ indirect contributions to firms, Pansari and Kumar, (2017) identify customer referrals as incentivized referrals that help attract customers. Because referred customers are more profitable (Schmitt et al., 2011), referrals contribute indirectly to firm performance. Customer influence refers to their impact, especially through social media. Similarly, research demonstrates that positive perceptions of corporate reputation lead customers to engage in word-of-mouth behaviors (Jalilvand et al., 2017). The final indirect contribution, knowledge, is customers’ active involvement in enhancing the firm’s offerings through suggestions/feedback (Kumar and Pansari, 2016). Choi and Burnham (2020) reveal that the positive impact of brand reputation, through self-expressive brand perceptions, leads to knowledge sharing with the brand.

In sum, because highly reputed companies usually have favorable attributes that customers prefer, the customers may support the companies through various forms of CEB (Bartikowski and Walsh, 2011). Focusing on an aggregation of CEB, the following hypothesis is proposed.

Hypothesis 1

CBR has a positive direct impact on CEB.

Customer identification and brand love as mediators between CBR and CEB

Customer identification

Individuals desire a relatively secure and stable sense of self-identity within specific situations in order to function effectively (Schwalbe and Mason-Schrock, 1996). Such self-identity helps individuals situate themselves in particular contexts and influences what they do, think, and even consume (Ashforth, 1998). This notion is consistent with cognitive consistency theory, which argues that individuals aim to sustain psychological harmony among their beliefs, attitudes, and behaviors. Along with this view, research on consumer behaviors has revealed that customers may identify with a specific brand when they view it as a reference group (Escalas and Bettman, 2005). They may also identify with a firm based on their perceptions of the firm’s characteristics (Dutton et al., 1994), or with the firm’s various attributes, such as products, services, and brands (Underwood et al., 2001).

Customer identification is a cognitive state of consumer connection and closeness to a firm (Dutton et al., 1994), occurring through customers’ subjective comparisons of their own identities to the firm (Martínez and Bosque, 2013). Bhattacharya and Sen (2003) argue that self-categorization into organizational characteristics can be fundamental to the process of self-identity construction. Corporate reputation can be an important driver in building customers’ identification with a firm. In line with this notion, studies have demonstrated how customer identification is influenced by organizational characteristics, such as corporate reputation (Keh and Xie, 2009) and brand prestige and distinctiveness (Wolter et al., 2016).

Researchers have also suggested that customer identification with a brand or firm may impact brand-related buying behaviors (Algesheimer et al., 2005) as well as a strong customer–firm relationship (Bhattacharya and Sen, 2003), possibly leading to discretionary behaviors that benefit the firm. When customers perceive that brands or firms help their self-identity, they are more likely to endorse these brands or firms (Ruane and Wallace, 2015); share their knowledge or ideas with the brands or firms (Choi and Burnham, 2020); engage in extra-role behaviors (i.e., positive referrals, recruiting other customers, suggesting product improvements, and proactive communication about anticipated problems) (Ahearne et al., 2005); and perform customer voice behaviors, including promotive and prohibitive voices (Ran and Zhou, 2020). Keh and Xie, (2009) also argue that customer identification can play a mediating role in the relationship between corporate reputation and purchase intention, implying that customer identification has a mediating effect between CBR and CEB.

Hypothesis 2

Customer identification mediates the positive relationship between CBR and CEB.

Brand love

Brand love is defined as “the degree of passionate emotional attachment a satisfied customer has for a particular trade name” (Carroll and Ahuvia, 2006, p. 81). Shaver et al., (1987) assert that a driver of the love emotion can be an assessment that the loved one has something the individual desires, likes, or needs. Batra et al., (2012) find that high quality is an antecedent of brand love because customers are attracted to the brands or firms that provide benefits. Customers may view and feel emotional attachment to highly reputable brands or firms due to the latter’s superiority. In other words, when customers believe a firm has a favorable reputation, they are more likely to have emotional connectedness with that firm, such as brand love, and in turn, engage in various forms of goodwill toward the firm (Bartikowski and Walsh, 2011; Kim and Lennon, 2013). This view fits with engagement theory, which claims that CEB is influenced by perceptions of emotional connectedness with a firm, which are derived from positive experiences with or attributes of the firm (e.g., reputation).

Prior research has identified the behavioral outcomes of brand love. Customers with strong brand love tend to engage in positive word of mouth (Amaro et al., 2020), talking about the brand or firm to others (Coelho et al. 2019; Rodrigues and Brandão, 2020), and brand advocacy, promoting or defending it to other consumers (Coelho et al., 2019). Similarly, Junaid et al. (2020) find that brand love has a positive impact on the four dimensions of CEB—buying, referrals, influence, and feedback—which reflects the theory of engagement (Pansari and Kumar, 2017). Furthermore, brand love not only makes customers more loyal but also leads them to perform behaviors such as investing their resources in the brand or firm (Bagozzi et al., 2017; Batra et al., 2012), having a long-term relationship and paying premium prices (Bairrada et al., 2018). Although prior studies have investigated various behavioral outcomes that reflect the characteristics of CEB, most do not investigate the overall framework that integrates the four dimensions of CEB: purchase, referrals, influence, and knowledge.

Hypothesis 3

Brand love mediates the positive relationship between CBR and CEB.

Industry types as moderators: Product vs. service

The effect of cognitive and emotional responses on customer behaviors or contributions may be evident across all industries, but the magnitude of the effect varies (Pansari and Kumar, 2017). This implies that the mediating effect of customer identification and brand love between CBR and CEB varies depending on industry type (product vs. service). According to Bettencourt and Brown, (1997), frontline employees in the service industry can induce favorable emotions by providing customers with exceptional service. Specifically, heterogeneity in all the service transactions is more likely to influence customer emotions, as service employees interact with customers by concerning themselves with how to satisfy customers’ needs and improve their attitudes toward the company. Furthermore, in the case of experience services, whereby customers can evaluate quality and outcomes only after consumption, they can use corporate reputation as a reliable indicator of the firm’s competencies (Nguyen and Leblanc, 2001). Due to a lack of tangible customer assessments, customers in the service industry may rely more on intangible sources to evaluate a firm and determine their future behaviors toward it (Jackson et al., 1995). Thus, the role of reputation in developing perceptions of identification and brand love may be more important in the service than in the product industry.

Customers are more likely to share their experiences with services than products (Perry and Hamm, 1969), making them to more engage in referral behaviors and suggest ideas to service firms. Service firms focus on building customer relationships because they know that the strong firm–customer relationship may be an important intangible source of customers’ evaluations of them (Pansari and Kumar, 2017). Hur et al. (2018) have found that customer identification has a positive impact on CEB in various service industries, such as banking. Although no studies have investigated the differences in the relationships between service and product firms, the former are more likely to benefit from customer identification because customers rely more on company attributes in contexts that have difficulty differentiating their offerings from those of their competitors (i.e., the service industry) (Bhattacharya and Sen, 2003). Drawing upon the engagement theory and referring to high customer satisfaction and highly positive emotions such as “true love,” Pansari and Kumar (2017) argue that customers in this stage are “engagement focused,” and that positive emotions may enhance customer engagement in the service industry but not the product industry. Additionally, Van Doorn et al. (2010) argue that firm-based attributes, such as size, characteristics, and industry nature, should be considered in light of moderators between customer-based factors (e.g., satisfaction, trust/commitment, identity) and CEB. Hence, strong customer identification and brand love may play a more important role in shaping CEB in the service industry than in the product industry.

Hypothesis 4

Industry type moderates the mediation mechanisms, such that the mediation effect of (a) customer identification and (b) brand love between CBR and CEB is stronger for service firms than for product firms.

Customer identification and brand love

Bhattacharya and Sen (2003) note that customer–firm identification leads customers to feel a psychological attachment to the firm. According to the self-inclusion theory of love (Aron and Aron, 1986), individuals want to be part of the other. Adapting this theory to the brand marketing literature, Albert et al. (2008) claim that just as individuals share similar values and humor with their partners, image or identity congruity between a customer and a brand enhance the feeling of love toward the brand. Carroll and Ahuvia (2006) argue that brand love is a more intense emotional attachment than liking because it integrates the brand into the customer’s identity. Similarly, Coelho et al. (2019) find that identification, one of the dimensions of brand community, positively influences brand love as it relates to individuals’ assessments of belonging to a brand community (Dholakia et al., 2004). Kim and Lee (2020) also demonstrate that customer identification with a brand has a direct and positive impact on brand love. Thus, this study postulates that customer identification directly and positively influences brand love.

Hypothesis 5

Customer identification has a positive impact on brand love.

The conceptual framework of this study is portrayed in Fig. 1.

Fig. 1
figure 1

Conceptual model

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Research method

Data collection and sampling

As this study investigates corporate reputation based on customer perceptions (i.e., CBR), customers’ opinions of corporate reputation should be measured. We adapted the 88 companies in the B2C industry from Fortune 500, including banking, airlines, hospitality, telecommunication, grocery/department stores, and consumer goods manufacturers/retailers. As a preliminary study, we surveyed 22 MBA students on their awareness of companies/brands. The 20 companies, which have more than a “6” on a seven-point Likert scale for company/brand awareness, were selected for further analysis (10 in the product industry; 10 in the service industry). Based on the preliminary study, we developed 20 survey questionnaires that differed only in the given company, with identical questions in the subsequent sections. Respondents were randomly assigned to one of the 20 questionnaires.

The data were gathered from MTurk using an online survey, which helps to minimize potential interviewer-related bias (Hair et al., 2009). Because customers’ evaluations of corporate reputation, customer identification, and brand love should be based on their consumption experiences, respondents who had not had a transaction with the given company did not participate in the survey. After removing eight incomplete data, a total of 335 usable data (product firm: n = 144; service firm: n = 191) were collected for hypothesis testing. The participants were mainly Caucasian (61.7%) and 52.6% were female. Their ages ranged from 18 to 65 (59.2% were 35 years or older) and 35.4% had household income of more than $70,000. In addition, differences in the demographic profiles between two groups (product vs. service) were tested through a Chi-square comparison analysis. The results confirmed that there are no differences in demographic information (p > 0.05).

Measurement

Scale items to measure CBR were selected from those developed by Walsh et al., (2009). They suggest five dimensions that represent CBR—customer orientation, good employer, product and service quality, reliable and financially strong company, and social and environmental responsibility—and conceptualized it as a reflective second-order construct. Three items were adapted from Tuškej et al., (2013) to measure customer identification. The measures of brand love were adapted from Carroll and Ahuvia, (2006). Lastly, the scale items developed by Kumar and Pansari, (2016) were used to measure the following dimensions of CEB: purchase, referrals, influence, and knowledge. All responses were measured with a seven-point Likert scale (e.g., 1 = Strongly disagree, 7 = Strongly agree). The scale items of the constructs are presented in Table 2.

Table 2 Measures and confirmatory factor analysis
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Data analysis and results

Common method variance (CMV) testing

The results of the factor loading analysis, which extracts all measures into one factor (Harman, 1967), showed 0.462 of the total variance extracted (< 0.50). Common latent analysis loading all measures of each construct onto a single factor (Podsakoff et al., 2003) also revealed that the value of common variance was 0.397, which was satisfactory (< 0.50). A Chi-square difference test confirmed no significant difference between an unconstrained and a zero-constrained model (Δχ2 = 22.42, Δdf = 36, p > 0.05). Taken together, the results confirmed that CMV was not problematic for this study.

Measurement model testing

The dimensionality and psychometric properties of the constructs were assessed via standard partial least squares structural equation modeling (PLS-SEM), which enables to test complex models including second-order constructs (Henseler et al., 2009). The measurement model was examined including composite reliability (CR) to assess internal consistency and average variance extracted (AVE) to evaluate the convergent and discriminant validity. Because the constructs had Cronbach's alphas of above 0.70, convergence or internal consistency was adequately confirmed (Hair et al., 2009). Each construct had AVE of above 0.50 and CR values of above 0.70, indicating satisfactory convergent validity (Fornell and Larcker, 1981) (see Table 2). Discriminant validity was also supported as the square root of AVE of each construct was greater than the estimated correlation values among other constructs (Hair et al., 2017) (see Table 3). Additionally, the heterotrait–monotrait (HTMT) ratio of correlations confirmed discriminant validity of constructs involved in the measurement model as all values of HTMT did not exceed the threshold level of 0.85 (Hair et al., 2017).

Table 3 Discriminant validity testing
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The model’s explanatory power can be assessed through R2 values (Henseler et al., 2016). The Goodness of Fit (GoF) index for PLS-SEM was measured by calculating the geometric mean value of AVE values and the average R2 values for endogenous constructs (Tenenhaus et al., 2005). The following equation is used to assess the model fit:

$${\text{GoF }} = \, \surd \left( {{\text{AVE }} \times R^{2} } \right)$$

Wetzels et al. (2009) suggest that 0.1, 0.25, and 0.36 are cutoff values that represents small, medium, and large, respectively. Generating a GoF index value of 0.71, the research model provides an acceptable large model fit.

Hypotheses testing

The results of PLS-SEM, a bootstrapping procedure with 5,000 samples, showed that CBR is positively related to CEB (β = 0.21, p < 0.01) and customer identification positively influences brand love (β = 0.52, p < 0.001). Thus, the two hypotheses regarding the direct relationship, H1 and H5, were supported. The indirect effects between CBR and CEB through customer identification and brand love were also significant (β = 0.24, p < 0.001; β = 0.11, p < 0.01, respectively), supporting H2 and H3. Because our study focuses on the mediation as well as moderated mediation effects, we adapted a more rigorous analytical technique, PROCESS developed by Hayes, (2017). First, we performed mediation model analysis using the bootstrapping method in the PROCESS module (Model 6). As shown in Table 4, customer identification mediates the impact of CBR on CEB: Zero is not included between 95% lower CI and upper CI [0.16, 0.40]. Similarly, brand love mediates the relationship between CBR and CEB, and the 95% CI does not contain zero [0.08, 0.26]. Thus, H2 and H3 were also supported.

Table 4 Testing of mediation effect
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We also conducted PROCESS Model 58 to test the moderated mediation effect of an industry type. As given in Table 5, the effect of CBR on CEB through customer identification was significantly positive for service (β = 0.42, CI = [0.27, 0.58]), but not product (β = 0.12, CI = [-0.04, 0.28]) industries. The index of moderated mediation, indicating differences between the two groups, showed positive value, not containing zero between the lower CI and upper CI (β = 0.29, CI = [0.08, 0.52]). This revealed that there is a difference between the two industries, confirming that the CBR–customer identification–CEB mechanism is stronger in the service industry than in the product industry. Thus, H4a was supported. Additionally, the mediation effect of brand love was significantly positive for both product (β = 0.44) and service industries (β = 0.28). However, there is no difference in the CBR–brand love–CEB relationship across the industry type (β = -0.25, CI = [-0.54, 0.02]). Thus, H4b is not supported.

Table 5 Conditional indirect effects of CBR on CEB through customer identification and brand love moderated by firm type
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Post hoc analysis

To test the proposed structural model, we used the exogenous (i.e., CBR) and endogenous variables (i.e., CEB) as the reflective second-order constructs, as the developers of each construct suggest (Kumar and Pansari, 2016; Walsh and Beatty, 2007). However, each dimension of CBR represents a firm’s distinct aspect or activity. Likewise, each dimension of CEB indicates a different type of customer behavior. Thus, additional analysis was conducted to ascertain how differently each dimension of CBR influences each dimension of CEB. As shown in Table 6, customer orientation had a positive impact on the direct contributions (i.e., purchases) (βco-purchase = 0.17, p < 0.05), but did not influence indirect contributions (i.e., referrals, influence, and knowledge). The good employer dimension was not related to any type of CEB. The results also revealed that product and service quality dimensions had significant impacts on purchasing behavior (βP&SQ-purchase = 0.24, p < 0.01) and influence (βP&SQ-influence = 0.14, p < 0.05). The reliable and financially strong company dimension had the most positive influence on purchases (βR&FSC-purchase = 0.29, p < 0.001) and was significantly associated with influence (βR&FSC-influence = 0.18, p < 0.05). Interestingly, it had a negative impact on referring behavior (βR&FSC-referrals = -0.14, p < 0.05). Finally, social and environmental responsibility had a significant positive influence on all dimensions of CEB (βS&ER-purchase = 0.13, p < 0.05; βS&ER-referrals = 0.47, p < 0.001; βS&ER-influence = 0.32, p < 0.001; βS&ER-knowledge = 0.27, p < 0.001), but its impact on the direct contribution was the weakest.

Table 6 Testing of the direct impact of CBR on CEB (PLS-SEM)
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Taken together, the three dimensions of CBR—customer orientation, product and service quality, and reliable and financially strong company—demonstrated greater impacts on the direct contributions (i.e., purchases) than on the indirect contributions. This finding is consistent with Pansari and Kumar, (2017), namely that a customer who is satisfied with the relationship with a firm tends to engage more in direct contributions (purchases) than indirect contributions, such as advocating for the firm’s offerings and/or sharing knowledge with the firm (referrals, influence, and knowledge). However, being good employer and socially and environmentally responsible had no or a weak impact on the direct contribution, respectively.

Furthermore, the results indicated that customer orientation had no impact on referrals in the product industry, but a significant negative impact in the service industry (β = -0.16, p < 0.05). This may be because referrals are based on incentives or rewards. When customers perceive the reputation of a service firm from its customer-oriented service provision, they are less likely to engage in referral behaviors for self-benefits such as receiving incentives or rewards. Rather, their referrals may be voluntary and focus on benefits for the firm, which is the nature of CE (Van Doorn et al., 2010). Product and service quality are important drivers of purchases and influence in the service industry, whereas they are important for referrals and knowledge in the product industry. Lastly, social and environmental responsibility is a significant predictor of all types of CEB for service companies, but leads to only referrals and influence in product-based companies. This implies that such marketing activities are more crucial in assessing intangible businesses than tangible ones.

Importance–performance map analysis

An importance–performance map analysis (IPMA) was conducted to identify antecedents with high importance but low performance for the target constructs (Ringle and Sarstedt, 2016). A one-unit increase in the performance of an antecedent variable will increase the performance of the target construct by the total effect size (i.e., importance) of the antecedent variable (Schloderer et al., 2014). As shown in Table 7 and Fig. 2, in the case of the target construct, that is, purchases, the importance of being a reliable and financially strong company was higher than other dimensions of CBR. This means that a one-unit point increase in the performance of a reliable and financially strong company (73.74 to 74.74) will increase the performance of purchases by 0.34 points. For the indirect contributions, referrals, influence, and knowledge, social and environmental responsibility had the highest importance scores (0.77, 0.41, and 0.37, respectively), but the performance was the lowest (64.75). This implies that if a company improves its social and environmental responsibility performance from 64.75 to 65.75, its performance in referrals, influence, and knowledge would increase by 0.77, 0.41, and 0.37 points, respectively. Thus, these findings of high importance and low performance show major areas that marketers could enhance (Schloderer et al., 2014).

Table 7 Importance–performance map analysis for CEB
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Fig. 2
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Importance–performance map analysis for the four dimensions of CEBs CO  = customer orientation; GE  = good employer; P&SQ  = product and service quality; R&FSC= reliable and financially strong company;S&ER =social and environmental responsibility. = Overall = Product = service

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Furthermore, for purchasing behaviors, customer perceptions of companies as reliable and financially strong were more significant in the product industry (0.41), whereas product and service quality had the highest importance score in the service industry (0.37). Thus, if product firms improve their performance as reliable and financially strong companies, from 69.07 to 70.07, their purchase performance would improve by 0.41. In the service industry, a one-unit increase in product and service quality performance, from 76.90 to 77.90, would increase purchases performance by 0.37 points. For influence performance, social and environmental responsibility was the most important factor in the service industry (0.39), while being a reliable and financially strong company was most important in the product industry (0.28). Similarly, for knowledge performance, product and service quality had the highest importance score in the product industry (0.37), but social and environmental responsibility was the most important factor in the service industry (0.48). These findings provide significant managerial insights regarding differentiated marketing activities as well as resource allocations across industry types.

Discussion and conclusion

Theoretical implications

Viewing CEB as customers’ behavioral manifestations (see Van Doorn et al., 2010), the current study tested an empirical model that introduces a firm-related antecedent of CEB, CBR. The research on CEB has focused mostly on customer-related determinants, such as customer satisfaction (Palmatier et al., 2006) and brand commitment (Garbarino and Johnson, 1999). Yet, the firm-related factors influencing CEB have received less attention. By measuring five dimensions of CBR, this study provides insights into how customer perceptions of corporate reputation based on diverse aspects of business activities influences CEB.

This study also incorporates customer-related factors, namely customer identification and brand love, as mediators. Drawing on engagement theory, it is confirmed that CBR positively influences customer identification and brand love, leading to CEB. This finding contributes insights to the body of knowledge regarding how customers’ attitudes built on CBR influence CEB. Specifically, customer identification and brand love have been less examined in the CEB literature. Van Doorn et al., (2010) also argue that the interplay among customer-based, firm-based, and context-based factors, such as moderators and mediators, can facilitate CEB. Junaid et al., (2020) suggest that the CEB research focused on customer factors (i.e., the brand love-CEB-customer well-being relationship) should be conducted in multiple product categories so as to compare the relationship across the different contexts. Along with this notion, this research establishes not only the mediating effect of customer identification and brand love but also the moderating effect of the firm type in an integrated empirical model for CEB research.

Additionally, the CBR–customer identification–CEB mechanism is stronger for the service industry than the product industry. Customers have more opportunities to engage in tasks that benefit the firm in the service industry than product industry (Bhattacharya and Sen, 2003; Pansari and Kumar, 2017). This study provides a more compelling explanation: when customers identify with a reputable service firm, they are more likely to engage with that firm. Even if the CBR–brand love–CEB link is significantly positive for both the product and service industries, there is no difference. Thus, regardless of industry types, brand love is an important customer attitudinal factor to connect their perception of corporate reputation to their prosocial behaviors for the firms. As few studies have empirically investigated the mediation effects of customer identification and brand love between CBR and CEB, the present study fills some of the gaps identified by other researchers (e.g., Van Doorn et al., 2010; Walsh et al., 2018).

Lastly, by addressing their multiple dimensions as distinct individual factors, the current study contributes to the literature on corporate reputation and CEB, and does so by showing that each aspect of corporate reputation may play a distinctive role in leading to different forms of CEB. All aspects of CBR, except being a good employer, have significant impacts on purchases. Specifically, the impacts of customer orientation, product and service quality, and being a reliable and financially strong company on purchases are greater than on other CEB types. This finding provides empirical evidence for Pansari and Kumar’s (2017) conceptual research, which claims that direct contributions such as purchasing are more strongly influenced by cognitive evaluations (e.g., satisfaction, perception of reputation) than by emotional responses. In terms of the finding that being a good employer has no impact, it may be difficult for customers to evaluate the human resource management style of a certain company. Interestingly, the impacts of social and environmental responsibility are significant for all CEB types, and are stronger for the indirect contributions (referrals, influence, and knowledge) than the direct contributions (purchases). This implies that social and environmental responsibility is an effective marketing strategy for provoking various indirect types of CEB.

Managerial implications

Corporate reputation has received attention from practitioners because it benefits firms in multiple ways, such as improving their financial performance, allowing them to raise prices, and supporting the introduction of new products. In addition, marketers should understand that corporate reputation is a crucial resource that leads to customers’ favorable attitudes, resulting in CEB and possibly helping firms distinguish themselves from their competitors. For example, when customers share their knowledge with a firm to develop new offerings, the firm may be able to use the information to design unique offerings that better satisfy customers’ needs, which ultimately results in sustainable competitive advantages. In reality, many reputable firms utilize forums for customers to share ideas, e.g., Delta’s Ideas in Flight, Best Buy’s Blue Label Strategy, and BMW’s Innovation Lab (see Pansari and Kumar, 2017). Increased referrals and influence will be also marketing strategies to obtain new customers who are difficult to attract through typical communication channels.

Other than customer identification and brand love, practitioners should consider other factors derived from CBR. For instance, perceptions of a company and salesperson characteristics, self-expressive brand, and hedonic product positively influence customer identification and brand love (Carroll and Ahuvia, 2006; Keh and Xie, 2009). As a result, firms can increase CEB by enhancing customer identification and brand love through various characteristics. For instance, Harley Davidson customers who identify with the brand are more likely not only to consume the product but also to participate in fan clubs and share their experiences and knowledge with the firm. Thus, it is necessary for brand managers to establish reputable brand characteristics with which their customers can identify.

The findings of the post hoc analysis provide important managerial insights into effective resource allocation to each aspect of CBR. To increase customer purchases, the firms should primarily aim to be reliable and financially strong, followed by providing a high quality of product and service. Specifically, product firms should invest more in being reliable and strong companies, whereas the service providers should improve the quality of their offerings. To encourage influence behaviors, in the product industries, being a reliable and financially strong company is especially important to induce customer influence, and as such, product marketers should devote more resources to improving this aspect. We also find that while social and environmental responsibility is the most important dimension in CBR, the current market has under-performed in this regard. This finding implies that improvement of social and environmental responsibility should be a top priority to be a reputable firm. This type of marketing activity, moreover, is more crucial in the service industry than the product industry.

Limitations and future directions

Although this research sheds light on important issues, it has several limitations. Future research with larger samples and more diverse demographic profiles may increase generalizability. Also, this study uses 20 firms in the product and service industries, selected from Fortune 500. Although the study’s context is a B2C area that has a high possibility of CEB, the firms could be selected by considering various characteristics (e.g., level of customization). Studies with more firms could also increase generalizability.

In this study, customer identification and brand love are considered mediators linking CBR and CEB. As mentioned earlier, other constructs such as trust, commitment, and loyalty also can be considered as mediators. As Van Doorn et al., (2010) suggest, these factors can be considered as playing different roles in the research models, such as moderators between CBR and CEB. Future studies can also incorporate additional constructs as potential moderators, including customer-based factors (e.g., relationship length, satisfaction, and trust/commitment) and firm-based factors (e.g., firm size/diversification and brand characteristics). Lastly, future studies of other global markets could provide comparative analysis of different cultures.

Note

  1. 1.

    As a subjective evaluation of a company’s overall quality, prior studies have widely used the Fortune rating to measure corporate reputation (see Love et al., 2017; Roberts and Dowling, 2002). Fortune conducts annual “Most Admired Companies” surveys to assess eight attributes of the 10 largest companies in various industries (rating on a scale of 0 to 10). The attributes include management quality; product/service quality; financial soundness; innovativeness; long-term investment value; social responsibility to the community and the environment; use of corporate assets; and ability to attract, develop, and retain talented personnel. CBR encompasses factors that can be evaluated by customers.

  2. 2.

    Most studies that measure corporate reputation based on customer perceptions adapt the scales consisting of three or four items. For example, the four items that measure corporate reputation include whether the firm is: highly regarded, successful, well-established, and stable.