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. 2022 Jun 28;21(5):1175–1189. doi: 10.1002/cb.2070

Shaping customer brand loyalty during the pandemic: The role of brand credibility, value congruence, experience, identification, and engagement

Raouf Ahmad Rather 1,✉, Linda D Hollebeek 2,3,4, Tan VO‐THANH 5, Haywantee Ramkissoon 6,7,8,9, Anu Leppiman 4,10,11, Dale Smith 12
PMCID: PMC9350360  PMID: 37521716

Abstract

While insight into consumer brand engagement, experience, and identification is rapidly developing, little remains known regarding the association of these, and related, concepts, as therefore explored in this article. Drawing on social identity theory and service‐dominant‐logic, this study develops and tests a model that explores the effect of customers' brand credibility, ‐value congruence, and ‐experience on their brand identification, and its subsequent effect on their brand advocacy, ‐attachment, and ‐loyalty. We also examine the potentially moderating role of consumers' engagement in affecting these relationships. To explore these issues, we collected tourist‐based survey data. To analyze the data, we used confirmatory factor analysis, followed by structural equation modeling. The findings reveal that brand value congruence, credibility, and experience exercise significant positive effects on customers' brand identification, which, in turn, impact their brand advocacy, attachment, and loyalty. Further, brand engagement is shown to moderate the association of these factors. We conclude by outlining key theoretical/practical implications that arise from this research.

1. INTRODUCTION

Brands play a critical role in developing customer/firm relationships, in turn contributing to business performance (Keller, 2012). For example, by developing a unique set of customer associations with a brand and by offering a clear identity, successful brands are able to differentiate their offerings from those of competitors and build customer loyalty to their brands (e.g., Aaker, 2012; Yoshida et al., 2021). However, at the same time, published research shows rising customer skepticism toward brands, as gaged by plummeting confidence in brands or brand‐related communications (Tuskej et al., 2013), which may be exacerbated at times of crisis (Aziz & Long, 2021; Molinillo et al., 2022). Therefore, adept management of the customer/brand relationship has never been more critical than today (Beverland, 2021).

However, despite this recognition, little remains known regarding the drivers and outcomes of customers' brand identification (Appiah et al., 2019; Krishna & Kim, 2021), particularly during the pandemic, which is expected to see unique dynamics (vs. regular market conditions; Hollebeek et al., 2021). For example, while Elbedweihy et al. (2016) argue that brand attractiveness is conducive to yielding customer/brand identification, concerned customers during the pandemic may be primarily driven by safety concerns (Kitz et al., 2021). As another example, Büyükdağ and Kitapci (2021) identify the role of brand self‐congruity in driving customers' identification with a brand, which―during a crisis (e.g., the pandemic)―may be complemented or superseded by factors including the brand's perceived care, protection, or security. In other words, during crises such as COVID‐19, consumer behavior is expected to display unique or different dynamics (e.g., by exhibiting elevated perceived risk/fear; Rather, 2021a; Ramkissoon, 2020), thus likely challenging some of the insight professed in the literature under regular market conditions and requiring further investigation.

In response to this gap, we explore the drivers, dynamics, and outcomes of customers' identification with a brand during the pandemic. Extending prior research (e.g., Büyükdağ & Kitapci, 2021; Hultman et al., 2016; Stokburger‐Sauer et al., 2012), we envisage customer‐perceived brand credibility, value congruence, and brand experience to drive their brand identification, which we―in turn―expect to impact their brand advocacy, attachment, and loyalty during COVID‐19. For example, customer‐perceived value congruence, defined as a patron's perceived similarity of his/her personal values and those of the brand (Elbedweihy et al., 2016), is expected to be paramount during (vs. pre)‐the pandemic, given customers' typically elevated safety concerns. Relatedly, customers' brand experience, or their response evoked by brand‐related stimuli (Brakus et al., 2009), is also expected to differ during (vs. pre‐) the pandemic. For example, while customers may traditionally aim to optimize their (e.g., hedonic) brand experience, during the pandemic their focus is likely to shift (e.g., by focusing on keeping themselves safe; Itani & Hollebeek, 2021). Therefore, by exploring the drivers, dynamics, and consequences of customers' brand identification during the pandemic, we expect our analyzes to offer important, novel insight.

Customer engagement has been defined as a customer's resource investment in his/her brand interactions (Kumar et al., 2019), revealing its inherently interactive nature (Behnam et al., 2021; Munaro et al., 2021). During the pandemic, customer/brand interactions have been severely impacted (e.g., through lockdowns/social distancing; Aziz & Long, 2021), thus impacting customers' brand engagement (vs. pre‐the pandemic), which―however―remains scant (Hollebeek et al., 2021), revealing an important gap. We, therefore, explore customer engagement's moderating role in the association of customer‐perceived brand credibility, value congruence, and experience on the one hand, and brand advocacy, attachment, and loyalty on the other. We expect engagement to exert a moderating (vs. mediating) role, as the strength of the association of customer/brand identification and its respective drivers/outcomes is anticipated to differ for customers displaying high (vs. low) brand engagement. For example, the association of brand credibility and ‐identification is expected to be stronger for highly (vs. low) engaged customers, who typically spend more time/effort on their brand interactions (Hollebeek et al., 2014; Kumar & Pansari, 2016), strengthening their bond with the brand (Bowlby, 1977).

Based on this rationale, this article's contributions to the branding‐ and consumer behavior literature are as follows. First, we develop and test a framework that examines the effects of customer‐perceived brand credibility, value congruence, and experience on their brand identification, which we posit to subsequently affect customers' brand advocacy, attachment, and loyalty, as outlined. As noted, while existing studies have addressed these variables, little remains known regarding their conceptual association during (vs. pre‐) the pandemic, thus warranting further research. Specifically, these analyzes are of value, as the more marketers are able to foster customer identification with their brands during the pandemic, the higher their expected sales, contributing to the firm's pandemic recovery, survival, and performance (Krishna & Kim, 2021; Molinillo et al., 2022). During the pandemic, the brand's ability to foster the development of customer/brand identification is of particular importance, as at times of crisis, customers are especially likely to patronize those brands that align with their values and give them hope (e.g., for a return to pre‐pandemic life; Hollebeek et al., 2021).

Second, we explore customer engagement's moderating role in the proposed associations. While most empirical research views engagement as a driver or mediator affecting particular hypothesized relationships (e.g., Algharabat et al., 2020; Harrigan et al., 2018; Naeem & Ozuem, 2021), we posit that the strength of the explored associations will vary across customers displaying different engagement levels. For example, for a low (vs. highly) engaged customer, we expect to see a weaker (stronger) association of customer‐perceived value congruence and brand identification, as the former (vs. latter) invests less into his/her brand relationship. We, therefore, expect that the more customers are willing to put into their interactions, the stronger the hypothesized relationships will be. Our empirical findings, indeed, confirm engagement's moderating role in these associations, raising important (e.g., managerial) implications. For example, though customers may report an excellent brand experience, their behavioral (repurchase) intent may remain modest, if their brand engagement remains below par (Khan, Hollebeek, & Islam, 2020).

The paper unfolds as follows. We review important literature and develop a conceptual framework and set of hypotheses in Section 2, followed by an overview of the methodology in Section 3. Section 4 reports on our main findings, after which we outline the major implications that arise from this research in Section 5.

2. LITERATURE REVIEW AND CONCEPTUAL DEVELOPMENT

We next review key literature, from which we develop a set of hypotheses, as summarized in Figure 1.

FIGURE 1.

FIGURE 1

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Proposed framework

2.1. Social identity theory

Social identity theory (SIT) offers an important theoretical foundation for (e.g., brand) identification in marketing and organizational research (Ahearne et al., 2005; Raza et al., 2020). SIT posits that people develop or maintain their self‐identity based on their affiliation with or membership to specific groups (Tajfel & Turner, 1985). In organizational research, (employee) identification has received in‐depth attention (Bhattacharya & Sen, 2003) and has emerged as a critical driver of employee‐ and organizational performance (Lam et al., 2013). Likewise, in marketing, customers' brand identification, or the degree to which customers identify with a brand, has been shown to yield enhanced customer outcomes (e.g., higher loyalty) (Büyükdağ & Kitapci, 2021).

In this article, we primarily examine customers' identification with a brand, or the degree to which a patron identifies with a brand based on its (e.g., relational/symbolic) characteristics. Existing research has also examined the impact of customer‐perceived brand identification on specific consumer behavior outcomes, including (re)purchase intent (Tuskej et al., 2013), positive word‐of‐mouth (Hultman et al., 2016), and in/extra‐role behavior (Ahearne et al., 2005). Extending this insight, we explore customers' brand identification vis‐à‐vis brand credibility, value congruence, experience, engagement, advocacy, attachment, and loyalty, as outlined.

2.2. Customer engagement

Interest in customer engagement (CE) has rapidly surged in the last decade (Brodie et al., 2011; Hollebeek et al., 2021). Various engagement‐related terms have been proposed, including consumer‐, customer‐, and brand engagement and so forth (Alexander et al., 2018; Brodie et al., 2013), exposing the concept's growing significance.

First, CE has been defined as “a psychological state, which occurs by virtue of interactive customer experiences with a focal object,” (Brodie et al., 2011, p. 258). Extending this viewpoint, Hollebeek et al. (2019, p. 171) conceptualize CE as “a customer's motivationally driven, volitional investment of focal operant resources (including cognitive, emotional, behavioral, and social knowledge/skills), and operand resources (e.g., equipment) in brand interactions.” Relatedly, Vivek et al. (2012, p. 133) conceptualize CE as “the intensity of an individual's participation in and connection with an organization's offerings and/or organizational activities, which either the customer or the organization initiates,” as adopted in this study. The specific objects with which a customer may engage include branded products, services, frontline employees, and firms, to name a few (Taheri et al., 2014), revealing its interactive nature (Naeem & Ozuem, 2021).

Second, most authors view CE as a multidimensional concept that comprises emotional, cognitive, and behavioral facets (Hollebeek et al., 2014; Kumar & Pansari, 2016; Vivek et al., 2014). While cognitive CE refers to a customer's level of mental elaboration in his/her interactions with a brand, emotional CE denotes the extend of the individual's affect committed to his/her brand interaction (Rather & Hollebeek, 2020; Rather & Hollebeek, 2021).

Third, several authors have explored CE's conceptual associations. For example, Harrigan et al. (2018) and Khan, Hollebeek, Fatma, et al. (2020) examine its direct effect on brand experience/loyalty in the social media/online community contexts. Moreover, Rather et al., (2018) and So et al. (2021) explore the CE/loyalty interface for hotel/airline brands. However, as outlined, scholarly acumen of CE's potentially moderating effect remains limited (Prebensen et al., 2015; Thakur, 2019), as, therefore, explored in this study.

2.3. Brand credibility/identification interface

Credibility is a crucial success factor for brands. Based on signaling theory, Erdem and Swait (1998, p. 192) define brand credibility as a customer's level of trust in a brand based on his/her perceived believability of its information, promises, and actions (Erdem & Swait, 2004; Molinillo et al., 2022).

When a brand has built a positive social identity, its propensity for customer/brand identification rises (Kumar & Kaushik, 2018). That is, customers are expected to identify more with brands they perceive as trustworthy (vs. non‐trustworthy; Hollebeek & Macky, 2019), thus contributing to their self‐definition (Raza et al., 2020; Tuskej et al., 2013). Therefore, by instilling brand confidence, customer‐perceived brand credibility is expected to drive the individual's brand identification (Ahearne et al., 2005; Becerra & Badrinarayanan, 2013). Consequently, as customer‐perceived brand credibility grows, we expect their brand identification to rise in parallel. We posit:

H1: Customer‐perceived brand credibility positively affects customer brand identification.

2.4. Brand value congruence/identification interface

Consumer/brand value congruence denotes the degree of match between a customer's personal values and his/her perceived brand values (Edwards & Cable, 2009), as rooted in self‐congruity theory (Sirgy et al., 1991). For example, a brand user may assess to what extent it matches his/her values, from which the individual is likely to decide whether to continue using the brand (Tuskej et al., 2013). Through this psychological comparison, the customer will tend to use those brands that exhibit a higher (vs. lower) match with his/her personal values (Elbedweihy et al., 2016; Hu et al., 2019). Thus, value congruence is likely to positively affect customer‐perceived brand identification (Rather & Camilleri, 2019; Tuskej et al., 2013), yielding self‐brand congruity a key precursor of customer/brand identification (Ahearne et al., 2005; Tuskej et al., 2013). Bhattacharya and Sen (2003, p. 77) illustrate: In the identification process, “a state of self‐categorization into organizationally defined categories” aids consumers to match‐up their personal features/characteristics (e.g., values) with those of the focal object/brand. Thus,

H2: Customer‐perceived brand value congruence positively affects customer‐perceived brand identification.

2.5. Brand experience/identification interface

Early brand experience research emerged in the mid‐1990's (Brakus et al., 2009; Schmitt & Zarantonello, 2013), which recognized the inherently experiential (i.e., value‐in‐use) nature of offerings, beyond mere value‐in‐exchange. Existing studies typically focus on particular brand experience facets, such as a brand's utilitarian, esthetic, or intellectual experience and their respective effect on customers' behavioral outcomes (e.g., purchase; Zarantonello & Schmitt, 2010; Jaziri, 2019; Rather, 2020).

However, most customers are affected by a range of experiential factors (Jaziri, 2019; Vo‐Thanh et al., 2021), through which they identify with their chosen brands. In this vein, Brakus et al. (2009, p. 53) conceptualize brand experience as the customer's “sensations, feelings, cognitions, and behavioral responses evoked by brand‐related stimuli that are part of a brand design and identity, packaging, communications, and environments.” Brand experience covers consumer's entire purchase journey, including all of his/her brand touch‐points (Lemon & Verhoef, 2016; Schmitt & Zarantonello, 2013). Under rising competition, marketers are advised to differentiate their brands by providing a distinctive customer experience, which is conducive to building customer/brand identification (Stokburger‐Sauer et al., 2012; Vo‐Thanh & Kirova, 2018). We propose:

H3: Customer brand experience positively impacts customer/brand identification.

2.6. Brand identification/advocacy interface

Brand advocacy denotes a customer's supporting (e.g., referral/recommendation) behavior for a brand (Xie et al., 2019), thus offering an important success factor for brands, including by stimulating sales growth (Bhattacharya & Sen, 2003), as surmised in the Net Promoter Score (Reichheld & Sasser, 1990). Brand advocacy may occur socially and/or physically. While social advocacy denotes a customer's recommendation of a brand to others or his/her defense of a brand when it is attacked (Clark et al., 2020; Ramkissoon et al., 2018), physical advocacy reflects a customer's brand purchase/consumption (Stokburger‐Sauer et al., 2012).

Ahearne et al. (2005) suggest the existence of a strong, positive relationship between customer/brand identification and extra‐role behaviors. Likewise, brand advocacy has been shown an important outcome of customer/brand identification (Stokburger‐Sauer et al., 2012). Studies also report a positive, significant association of customer/brand identification and positive brand‐related word‐of‐mouth (e.g., Tuskej et al., 2013). Consequently, based on social identity theory, customers who have a strong bond with a brand and who identify with the brand will be more inclined to promote the brand to others (Hultman et al., 2016). Thus,

H4: Customer/brand identification positively affects customer brand advocacy.

2.7. Brand identification/brand attachment interface

While related, brand identification and ‐attachment are rooted in distinct theoretical foundations. First, brand identification reflects the degree to which a customer identifies with a brand (e.g., through a perceived match of his/her personal, and the brand's, values). In social identity theory, brand identification is viewed as a customer's affiliation with a brand based on its perceived fulfillment of the individual's social identity needs. That is, customers utilize brands to describe their social identity, as derived from the symbolic value of their brands they use (Bhattacharya & Sen, 2003; Hollebeek & Rather, 2019). Therefore, customers articulate their social identity to a social group based on their identification with particular brands (Molinillo et al., 2022).

Second, brand attachment, as conceptualized in attachment theory (Bowlby, 1977), reflects a customer's emotional connection with a brand, characterized by a fear of loss (Thomson et al., 2005). Based on attachment theory, brand attachment reveals an individual's positive beliefs about, and emotional connection to, a brand, where particular brand aspects are self‐defining and/or self‐referential (Schmalz & Orth, 2012). Taking an attachment theory‐informed perspective suggests that the higher one's brand attachment, the greater one's connection to the brand (Huang et al., 2017; Thomson et al., 2005). Elevated brand attachment sees stronger emotions, including passion, affect, and separation distress (Bowlby, 1977). That is, customers feel safe when consuming those brand(s) to which they are emotionally attached (Molinillo et al., 2022). We, thus, propose that they will form an attachment to a brand if they are bonded with it. Therefore,

H5: Customer‐perceived brand identification positively impacts customer brand attachment.

2.8. Brand identification/brand loyalty interface

Oliver (1999) defines brand loyalty as a customer's deeply held intent to re‐patronize or repurchase a preferred brand. Based on social identity theory, customers displaying high (vs. low) brand identification are more likely to continue engaging with a brand, and thus, remain loyal to it (Tajfel & Turner, 1985; Yoshida et al., 2021). Brand loyalty comprises two components: (a) Attitudinal loyalty, exhibited by offering positive brand‐related word‐of‐mouth, recommending/referring the brand, and (b) Behavioral loyalty, or by repurchasing the brand (Haumann et al., 2016). Drawing on customer/brand identification research (e.g., Bhattacharya & Sen, 2003; Tuskej et al., 2013), customers are particularly likely to develop a connection with favorably perceived brands. Therefore, strong brand identification is key in developing enduring customer/brand relationships and loyalty (Villagra et al., 2021). We hypothesize:

H6: Customer/brand identification positively affects customer brand loyalty.

2.9. Moderating role of customer engagement

As noted, debate surrounds CE's conceptualization. For example, while authors like Taheri et al. (2014) and Vivek et al. (2012, 2014) define it as an individual's connection to and participation in an organization's activities or offerings, Hollebeek et al. (2014) refer to the concept as a consumer's positively‐valenced cognitive, emotional and behavioral activity during or related to [travel‐related] brand interactions. Moreover, Hollebeek et al. (2019) define CE as a customer's resource investment in his/her brand interactions. Therefore, the greater a customer's cognitive, emotional and behavioral investment in a destination brand (e.g., by learning about, discussing, or recommending the brand to others), the higher his/her brand engagement (Kumar & Pansari, 2016; So et al., 2021). In turn, the individual's engagement has been shown to yield important effects on consumers' (e.g., repurchase) behavior (e.g., Kumar et al., 2019; Munaro et al., 2021; Naeem & Ozuem, 2021).

While CE is oft‐cited as a driver or mediator of the customer experience, brand identification, and/or loyalty (Khan et al., 2020, b), its potentially moderating role remains tenuous, though it has gained some attention (Prebensen et al., 2015; Saleem et al., 2020). For example, Thakur (2019) examines engagement's moderating role in the relationship of customer satisfaction/loyalty in the mobile app‐based shopping context. The author suggests that highly (vs. low) engaged consumers tend to shop more often, revealing the concept's moderating role, akin to Cogut et al. (2020), who corroborate engagement's moderating role in the association of consumers' sustainability awareness and behavior. Relatedly, while Saleem et al. (2020) establish CE's moderating role in the association of customers' brand attitude and their environmentally responsible (sustainable) consumption behaviors, CE has also been shown to moderate the association of customer cocreation and their intent to recommend the brand (Rather et al., 2022).

However, despite this extant insight, little remains known about CE's potentially moderating role in impacting the association of brand credibility, value congruence, experience, attachment, advocacy, and loyalty, as therefore explored in this study. That is, as high (vs. low) engaged customers have been demonstrated to display differing behaviors (e.g., Hollebeek et al., 2014), further exploration of these associations is warranted. Specifically, we expect customer brand experience, brand credibility, and brand value congruity to exert a stronger effect on customer/brand identification for highly (vs. low) engaged customers. For example, the effect of a customer's brand experience on his/her brand identification is anticipated to be stronger for high (vs. less) engaged individuals, given his/her elevated engagement's stimulating or augmenting effect on this association (e.g., Rather & Hollebeek, 2021). Correspondingly, we posit:

H7a: Customer brand experience exerts a stronger effect on customer/brand identification for highly (vs. low) engaged customers.

H7b: Customer‐perceived brand credibility exerts a stronger effect on brand identification for highly (vs. low) engaged customers.

H7c: Customer‐perceived brand value congruity exerts a stronger effect on brand identification for highly (vs. low) engaged customers.

Likewise, we anticipate customer/brand identification to have a stronger impact on customers' brand attachment, advocacy, and loyalty for highly (vs. low) engaged customers. For example, buyers' high identification with a brand should yield their higher brand attachment (Sen et al., 2015), with a stronger association between these variables anticipated for highly (vs. low) engaged customers. That is, the more a customer engages with a brand, the more of his/her personal resources (s)he commits to his/her interactions with it (Hollebeek et al., 2019), in turn facilitating or strengthening the association of their brand identification on the one hand, and brand attachment (or advocacy, loyalty) on the other. We postulate:

H8a: Customer/brand identification exerts a stronger effect on brand attachment for highly (vs. low) engaged customers.

H8b: Customer/brand identification exerts a stronger effect on brand advocacy for highly (vs. low) engaged customers.

H8c: Customer/brand identification exerts a stronger effect on brand loyalty for highly (vs. low) engaged customers.

3. METHODOLOGY

3.1. Survey instrument

A questionnaire was employed to gauge the modeled constructs (Figure 1) using extant measures. Customer engagement was adopted from Rather et al. (2019), which is based on Vivek et al.’s (2014) three‐dimensional (emotional, cognitive, behavioral) scale. A sample item reads: “I am passionate about this brand.” Brand identification was gaged by utilizing Stokburger‐Sauer et al.’s (2012) five‐item scale, with a sample item “I identify strongly with this brand.” Brand experience scale was modified from Kumar and Kaushik's (2018) 12‐item scale, which is based on Brakus et al.’s (2009) multidimensional instrument. A measurement item entails: “This brand induces feelings and sentiments.”

We adopted brand value congruence by Hu et al.’s (2019) four‐item scale, with a sample item stating “My personal values match the values of this brand” (see Elbedweihy et al., 2016). We measured brand credibility by deploying Erdem and Swait's (2004) six‐item scale, with a sample item stating: “This brand has the ability to deliver what it promises.” Brand attachment was modified by applying Huang et al.’s (2017) measurement item scale. A sample item reads: “I am attached to this brand.” Brand advocacy was measured by utilizing Stokburger‐Sauer et al.’s (2012) three‐item measure, with a sample item stating: “I would recommend visiting this brand to others.” Finally, we measured brand loyalty with Kumar and Kaushik's (2017) instrument, with a sample measurement item reading: “I will visit this brand the next time I plan a travel”.

3.2. Sampling and data collection

Prior to administrating the main study, we pilot tested the questionnaire with 40 scholars to assess the quality of the instrument and resolve any concerns, as needed. The lead author invited these scholars to comment on the questionnaire's clarity and readability, which revealed no issues. In the main study, participants were asked to rate each measurement item on 7‐point Likert scales ranging from strongly disagree (1) to strongly agree (7).

To administer the main survey, we deployed a non‐probability convenience sampling approach in January 2021 in the tourism context. Specifically, five well‐known Indian tourism destination brands (i.e., Varinag, Srinagar, Kokernag, Gulmarg, and Phalgam) were used to collect the data, which offer a range of religious, adventure, leisure, and recreation activities (IBEF, 2020). The target population included domestic/foreign tourists aged 20 years and above, who had visited at least one of the outlined destination brands.

To obtain high‐quality data, the lead researcher and two well‐trained research assistants randomly approached customers leaving the destination brand at different exit points. To diminish coverage error, the research purpose was unveiled to the respondents (Molinillo et al., 2022). After circulating 500 surveys, 425 completed questionnaires were received, revealing an 85% response rate. After removing invalid questionnaires (e.g., those with missing data), 420 usable questionnaires were retained for the analysis. A minimum of 80 participants were used from each of the destination brands. Descriptive statistics (see Tables 1 and 2) show that 54% of respondents were male (46% female), and 72% visited the destination brand for leisure/adventure reasons, followed by 17% (religious reasons), and 11% for business purposes.

TABLE 1.

Respondents' demographic/travel characteristics

Variables Categories % Respondents
Gender Male 54% 227
Female 46% 193
Age (years) 20–30 30% 126
31–40 21% 89
41–50 26% 110
Above 51 23% 94
Reason for traveling Leisure 41% 172
Adventure 31% 131
Religious 17% 71
Business 11% 46
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TABLE 2.

Psychometric properties―measurement items and descriptive statistics

Constructs and items SL M SD
Customer Engagement (CE)
Enthused Participation
I spend plenty of my time in this brand 0.93 5.23 1.45
I am passionate about this brand 0.91 5.65 1.32
My days will not be the same without visiting this brand 0.90 5.24 1.27
Conscious Attention
I love to learn more about this brand 0.94 5.52 1.21
I pay plenty of attention to anything about this brand 0.91 5.76 1.14
Anything linked to this brand captures my attention 0.93 5.74 1.12
Social Connection
I love to visit this brand with my friends 0.90 5.68 1.76
I enjoy this brand most when I am with others 0.93 5.87 1.68
Brand Experience (BX)
Sensory Brand Experience
I find this brand interesting in a sensory way 0.91 5.87 1.01
This brand builds a strong impression on my senses, visually and in other ways 0.96 5.46 1.02
This brand does not appeal to my senses (r) 0.97 5.42 1.04
Affective Brand Experience
This brand is an emotional area 0.92 5.48 1.94
This brand induces feelings and sentiments 0.86 4.82 1.11
I do not have strong emotions for brand (r) 0.87 3.98 1.42
Behavioral Brand Experience
This brand gives me bodily experiences 0.82 3.09 1.46
I involve in physical activities‐, behaviors while visiting this brand 0.91 4.18 1.32
This brand is not activity oriented (r) 0.93 4.95 1.22
Intellectual Brand Experience
This brand encourages my curiosity and problem‐solving 0.88 4.64 1.33
I think a lot, when I visit this brand 0.91 5.09 1.19
This brand does not make me think (r) 0.96 4.99 1.13
Brand Identification (BI)
I identify strongly with this brand 0.88 4.80 1.22
I feel a strong sense of belonging with this brand 0.95 4.99 1.30
This brand embodies what I believe in 0.93 4.87 1.32
This brand has a great deal of personal meaning for me 0.92 4.23 1.04
This brand is like a part of me 0.95 4.90 1.22
Brand Value Congruence (BVC)
What this brand stands for, is important to me 0.94 4.59 1.25
This brand's culture and values fits well with the things, which I value in life 0.95 4.62 1.28
My personal values matches with values of this brand 0.92 4.74 1.25
Things, which I value in life are similar, that this brand values 0.82 4.76 1.09
Brand Credibility (BC)
This brand has the capability to deliver what it promises 0.94 4.84 1.27
This brand's product/service claims are believable 0.95 4.78 1.01
This brand reminds me of somebody who is competent and identifies what she/he is doing 0. 87 4.78 1.01
This brand offers what it promises 0.93 5.15 1.14
This brand has a name, which you can trust 0.95 4.66 1.08
Eventually, my experience with the brand n leads me to expect it to maintain its promises 0.85 5.30 1.20
Brand Loyalty (BL)
I will visit this brand the next time I plan a travel 0.87 515 1.26
I intend to keep visiting this brand 0.90 5.35 1.13
Brand Advocacy (BAD)
I would recommend visiting this brand to others 0.92 5.13 1.25
I love to talk about the good points of this brand to people I know 0.89 5.21 1.31
I have managed to convince other people to visit this brand 0.91 5.22 1.21
Brand Attachment (BAT)
I am delighted about this brand 0.91 4.52 1.31
I am attached with this brand 0.85 4.89 1.20
I am connected to this brand 0.81 4.71 1.10
I am captivated by this brand 0.83 4.31 1.26
I feel love toward this brand 0.91 4.55 1.24
I feel peaceful when visiting this brand 0.89 4.99 1.26
I feel affection toward this brand 0.94 4.56 1.23
I am friendly toward this brand 0.88 5.64 1.11
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3.3. Common method variance

We next evaluated the potential existence of common method variance (CMV) by using two methods. First, we executed Harman's single‐factor test to confirm that no single factor accounted for 50% or more of the observed variance (Podsakoff et al., 2003). The results suggested that the first factor accounted for a mere 28.3% of the variance observed in the data, suggesting that CMV is not an issue in the data. Second, the correlation matrix (Table 3) shows that none of the correlations exceeded .9, corroborating that the data is unaffected by common method bias.

TABLE 3.

Inter‐construct correlations and square root of AVE

Construct α CR AVE BX BC BVC BAT BAD BI BL CE
BX .94 .84 .63 .83
BC .93 .91 .64 .52 .82
BVC .92 .86 .65 .61 .62 .84
BAT .93 .83 .58 .62 .53 .63 .85
BAD .88 .87 .59 .60 .59 .58 .59 .80
BI .95 .85 .58 .61 .62 .61 .65 .54 .83
BL .92 .87 .61 .53 .59 .62 .58 .62 .63 .82
CE .91 .82 .58 .52 .51 .60 .55 .61 .61 .57 .84
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Notes: AVE, average variance extracted; CR, composite reliability; α, Cronbach's alpha. Bold figures indicate square root of AVE. Off‐diagonal are correlations among factors.

4. ANALYSIS AND RESULTS

4.1. Confirmatory factor analysis

Structural equation modeling (SEM) was used to conduct confirmatory factor analysis (Bagozzi & Yi, 2012). A two‐stage structural equation modeling technique was adopted to test the research hypotheses by employing AMOS software (Anderson & Gerbing, 1988).

Customer engagement (CE) was adopted as a multidimensional, second‐order construct. We ran a confirmatory factor analysis (CFA) for CE as a three‐dimensional factor. The results reveal acceptable model fit: χ2 = 98.46, df = 43, χ2/df (2.28); NFI (.95); CFI (.95); GFI (.91); RMSEA (.054) (Byrne, 2013), validating CE's three‐dimensional operationalization (Hollebeek et al., 2014; Vivek et al., 2014). We next conducted a CFA on the measurement model comprising the full set of our latent constructs (48 items), revealing reasonable measurement model fit: χ2 = 851.523, χ2/df (2.41); CFI (0.95); NFI (0.93); GFI (0.91); RMSEA (0.063) (Bagozzi & Yi, 2012; Hair et al., 2010).

4.2. Reliability and validity assessment

Satisfactory scale reliability was attained, as indicated by the respective scales' Cronbach's alpha values, which exceeded the value of .70 (Hair et al., 2010). To evaluate convergent validity (CV), we examined the measurement item loadings and average variance extracted (AVE). First, the measurement item loadings for each of the variables exceeded the value of 0.50, suggesting CV (Hair et al., 2010; see Table 2). Second, we verified composite reliability (CR) scores for each of the modeled constructs (i.e., > 0.60; Fornell & Larcker, 1981). Moreover, we used discriminant validity (DV) testing based on Fornell and Larcker (1981). Table 3 indicates that the AVEs of all factors exceed their individual squared correlations, thus verifying DV of the modeled constructs.

4.3. Structural equation model results

Next, we tested the overall model (Figure 1), which generated the following fit indices: χ2 = 954.289, χ2/df = (2.69), CFI = (0.93), NFI = (0.93), GFI = (0.90) and RMSEA = (0.067), thus reflecting acceptable model fit.

4.4. Hypothesis testing results

The SEM results suggest that brand credibility (BC) affects brand identification (BI), exerting a strong effect (β = .54, t = 10.55, p < .001), thus supporting H1. Second, the results indicate that brand value congruence (BVC) exercises a significant, moderate positive impact on BI (β = .47, t = 6.14, p < .001), supporting H2. Third, brand experience (BX) exerts a strong, favorable effect on BI (β = .58, t = 12.54, p < .001), supporting H3. All three predictors collectively explained 61% of the observed variance in BI.

Fourth, as proposed in H4, BI favorably and strongly affects brand advocacy (BAD) (β = .55, t = 9.95). Fifth, as suggested in H5, BI positively influences brand attachment (BAT), exerting a moderate effect (β = .48, t = 9.95). Finally, the impact of BI on brand loyalty (BL) is extremely high (β = .62, t = 14.73), thus supporting H6. BI explained 58%, 57%, and 60% of observed variance in BAD, BAT, and BL, respectively (see Table 4/Figure 2).

TABLE 4.

Structural model results

Relationship R2 β t‐value Result
H1 BC → BI 0.61 0.54** 10.55 Supported
H2 BVC→ BI 0.61 0.47** 6.14 Supported
H3 BX → BI 0.61 0.58** 12.54 Supported
H4 BI → BAD 0.58 0.55** 9.95 Supported
H5 BI → BAT 0.57 0.48** 7.32 Supported
H6 BI → BL 0.60 0.62** 14.73 Supported
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Note: **Significant at p <.001.

FIGURE 2.

FIGURE 2

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Structural model

4.5. Moderating effect of customer engagement

To test H7a‐H8c (i.e., engagement's moderating effect), we divided the sample into two sub‐groups: Highly (n = 201) and low‐engaged (n = 219) customers. We used SEM‐based multi‐group analysis to match the variances in the coefficients of the structural pathways for the two sub‐samples (Prebensen et al., 2015; Thakur, 2019). The model (with engagement) revealed acceptable fit: χ2 = (358.86); df = (123); χ2/df = (2.91); CFI: (0.92); NFI: (0.93); CFI: (0.94); and RMSEA: (0.064). In Table 5, we report a greater effect of BX on BI for highly (β = 0.42; t = 8.63; p < .05) vs. low‐engaged customers (β = .34; t = 6.14; p < .05), supporting H7a. We also observe a stronger effect of BC on BI for highly (β = 0.41, t = 7.58; p < .05) vs. low‐engaged customers (β = .32, t = 4.36; p < .05), supporting H7b. Likewise, the impact of BVC on BI is greater for highly (β = .39; t = 6.32; p < .05) vs. low‐engaged customers (β = .30; t = 4.10; p < .05), confirming H7c.

TABLE 5.

Path comparison results across high/low engagement

Hypotheses High engagement Low engagement Result
β t‐value β t‐value
H7a BX → BI 0.42 8.63* 0.34 6.14* Supported
H7b BC → BI 0.41 7.58* 0.32 4.36* Supported
H7c BVC→ BI 0.39 6.32* 0.30 4.10* Supported
H8a BI → BAT 0.37 5.42* 0.33 6.65* Supported
H8b BI → BAD 0.36 4.63* 0.31 4.59* Supported
H8c BI → BL 0.45 9.23* 0.37 8.29* Supported
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Note: *p < .05.

We also observed a stronger effect of BI on BAT for highly‐ (β = 0.37, t = 5.42; p < .05) vs. low‐engaged customers (β = .33, t = 6.65; p < .05), supporting H8a. Similarly, the impact of BI on BAD was stronger for highly (β = .36; t = 4.63; p < .05) vs. low‐engaged customers (β = .31; t = 4.59; p < .05), confirming H8b. Finally, the influence of BI on BL is greater for customers exhibiting high (β = .45; t = 9.23; p < .05) vs. low engagement (β = .37; t = 8.29; p < .05), supporting H8c. We also examined the Chi‐square distributions, which showed a significant difference between the path coefficients for the high (χ2 = 4.529, df = 1, p < .05) vs. low‐engaged sub‐samples (χ2 = 5.643, df = 1, p < .05).

5. DISCUSSION AND IMPLICATIONS

5.1. Theoretical implications

Broadly, this research adds to the branding‐ and consumer behavior literature by examining the drivers, dynamics, and outcomes of customers' brand identification during the pandemic, which remains nebulous to date. In particular, given the pandemic's capacity to significantly alter customers' engagement and purchase behavior (e.g., Hollebeek et al., 2021), it is important to attain further insight into these dynamics. In other words, this study offers an early exploration of the effects of customer‐perceived brand credibility, value congruence, and experience on their brand identification, in turn impacting customer brand advocacy, attachment, and loyalty during the pandemic. The results supplement existing brand identification research, by linking the concept to brand credibility, vale congruence, and experience, thus extending authors including Büyükdağ and Kitapci (2021), Hultman et al. (2016), and Stokburger‐Sauer et al. (2012).

Second, we investigated CE's moderating role in the modeled associations. As most empirical studies focus on brand engagement's mediating role or main effects‐based associations (e.g., Harrigan et al., 2018; Khan, Hollebeek, Fatma, et al., 2020), scholarly acumen of its potentially moderating role remains limited, as noted. In particular, we envisage the existence of distinct brand identification‐related dynamics for highly (vs. low‐) engaged customers, as supported by the attained empirical results. The attained empirical findings confirm CE's moderating role in the proposed associations. That is, customers exhibiting elevated brand engagement see a stronger effect of their brand credibility, value congruence, and experience in driving their brand identification. Based on our findings, CE, therefore, plays a critical role in cultivating desirable consumer behaviors.

Likewise, customer/brand identification exerts a greater effect on brand advocacy, attachment, and loyalty for highly (vs. low)‐engaged customers. Therefore, while customers may (for instance) highly rate their brand experience, their repurchase intent may nevertheless fall short if their engagement remains low, thus offering important insight for managers. That is, the findings suggest that managers should focus on nurturing their customers' brand engagement, which―in turn―will stimulate their brand identification, advocacy, attachment, and loyalty. These contributions also raise further research opportunities (see Section 5.3).

5.2. Managerial implications

It is imperative for marketing/brand managers to understand the dynamics characterizing customer‐perceived brand performance indicators (e.g., Keller, 2012). Recognizing the importance of these issues, we explored the roles of brand credibility, value congruence, and experience in the development of customer/brand identification, which was found to―in turn―impact brand advocacy, attachment, and loyalty, yielding substantive managerial implications.

First, for H1‐2, we found that brand credibility and value congruence are critical in developing customer/brand identification. To optimize customer‐perceived brand credibility, cultivating brand engagement is important (Molinillo et al., 2022), which centers on customers' value‐laden brand interactions. In turn, these interactions will translate into valued customer relationships with their brands. Moreover, establishing perceived congruence among the customer's and the brand's values is also important, which can be communicated through a range of brand‐related artifacts (e.g., logo) or activities (e.g., service provision/recovery, brand‐related gamification/VR applications; Büyükdağ & Kitapci, 2021; Leclercq et al., 2020).

Second, H3 stipulated that customers' brand experience contributes to their brand identification, which consecutively contributes to brand advocacy (H4), attachment (H5), and loyalty (H5). The findings, therefore, reveal the utmost strategic importance of brand experience, which we recommend brand managers to focus on, not only in developing their offerings, but also in their market research. Given the multifaceted nature of brand experience (Brakus et al., 2009), managers have a choice of which specific brand experiences they wish to foster in their customers (e.g., sensory/intellectual), depending on the nature of their offerings. Relatedly, we recommend the strategic adoption of experiential marketing, which highlights the key role of the customer's experience (e.g., though (educational) site visits, make‐your‐own [product]; Lemon & Verhoef, 2016).

The results for H4‐H6 advocate brand identification's significant, positive effect on customers' brand advocacy, attachment‐, and loyalty. Thus, the more a customer identifies with a brand, the higher his/her expected brand advocacy, attachment, and loyalty. In turn, managers are advised to make the development of customers' brand identification a strategic priority. For example, by adding personalized features to their brand (e.g., through online platforms/mobile apps), customers' perceived brand identification and trust are expected to rise (Hollebeek & Macky, 2019).

Finally, we established CE as a moderator in the relationship of the studied variables. We empirically show that CE affects the strength of the association of their perceived brand credibility, value congruence, and experience on the one hand, and brand identification on the other, with stronger effects observed for highly (vs. low)‐engaged customers. We, therefore, recommend managers to focus on developing (a) highly (vs. low)‐engaged customers, whose favorable brand experiences make a greater contribution to their brand attachment, advocacy, and loyalty. Highly‐engaged customers thus provide a greater return on the marketer's investment, not only through more frequent repurchase, but also by recommending the brand to others. Next, (b) given engagement's dynamic (vs. static) nature, we recommend managers to focus on elevating their currently low‐engaged customers' engagement. If these customers' engagement levels are lifted, their repurchase and referral value will rise in parallel (Kumar et al., 2010), boosting their (lifetime) value to the firm. As the cost of retaining a customer is far less than that of attracting a new one (Rather, 2021b; Reichheld & Sasser, 1990), this approach should yield significant strategic benefit, contributing to firm performance.

5.3. Limitations and future research

Despite its contribution, this study is subject to several limitations, opening up further research opportunities. First, as the proposed framework was developed in the tourism context, the attained results may not generalize to other contexts. We, therefore, recommend testing the model across different contexts/sectors, aiding its validation. Relatedly, researchers may wish to incorporate alternate brand‐related constructs in the model (e.g., brand love/commitment/trust) to yield further insight (Rather, 2018a, 2018b; Rather & Hollebeek, 2019; Villagra et al., 2021).

Second, we used a cross‐sectional survey for data collection purposes. However, given its snapshot‐based nature, researchers may wish to employ longitudinal research to explore the proposed model and its evolution over time, thereby offering enhanced insight into the interplay of these concepts and their respective development over time. We, therefore, expect this study's future replication through a longitudinal design to offer further insight.

Third, while we used CE as a moderating variable, other constructs may also moderate these associations (e.g., customer age/culture; Hollebeek, 2018). Therefore, further research may incorporate additional/alternate moderators, yielding further insight. Finally, given the current COVID‐19 pandemic, scholars may wish to replicate our research post‐the pandemic.

CONFLICT OF INTEREST

There is no conflict of interest.

ACKNOWLEDGMENTS

Authors are very thankful to editor/s and anonmyous reviewers for the insightful suggestions in improving the paper.

Biographies

Raouf Ahmad Rather is a Scientific Independent Researcher, India. His research interests centers on customer/tourist engagement, experience, co‐creation and tourism crises. His work has been appeared in well‐known marketing, hospitality, and tourism journals.

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Linda D. Hollebeek, Ph.D., is Professor of Marketing at IPAG Business School, Vilnius University, and Tallinn University of Technology. Her research on customer‐, consumer‐, and stakeholder engagement has published in the Journal of the Academy of Marketing Science, Journal of Service Research, and International Journal of Research in Marketing, among others. She has been named a Clarivate Highly Cited Researcher (2021, 2020), is included on Stanford University's Top 2% of Researchers (2021, 2020), and is listed on research.com's Top Business & Management Scientists (2021). Linda serves as Associate Editor of the Journal of Service Research, is the recipient of the 2020 SERVSIG Emerging Service Scholar Award, and is co‐editor of The Handbook of Research on Customer Engagement.

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Tan VO‐THANH is an Associate Professor at the Department of Marketing, Excelia Business School, France. He publishes in the areas of service digitalization, customer experience, sustainable tourism, hospitality management, customer engagement, consumer behavior, social entrepreneurship, service marketing, green HRM, and HRM. Tan's research has led to more than 50 publications in reputable academic journals, book chapters, and books. His recent research has appeared in well‐known management, marketing, hospitality, and tourism journals (e.g., Human Resource Management, Journal of Business Ethics, Information and Management, Journal of Business Research, International Journal of Hospitality Management, Journal of Sustainable Tourism, International Journal of Contemporary Hospitality Management, Technological Forecasting and Social Change, among others). Tan serves on the editorial boards of and as a reviewer for several international journals. He is also a member of the Board of Directors of the French Association of Tourism Management (AFMAT). Tan has received funding from organizations in France and Vietnam.

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Haywantee Ramkissoon is a Research (Full) Professor of Tourism Marketing and Management at the University of Derby, UK. She leads the visitor economy research group. She is also affiliated with the Johannesburg Business School, University of Johannesburg South Africa, Centre for Research and Innovation in Tourism (CRiT), Talylor's University, Malaysia and Excelsia School of Business in Australia. Her scholarship in sustainability and business research, for example, customer engagement, sustainable tourism, place attachment, tourism entrepreneurship, cultural tourism, pro‐environmental behavior public health, business innovation and public health has gained international significance evidenced by media coverage, prestigious awards and academic and industry keynotes. She engages in collaborative research with national and international academic and industry partners for the benefits of individuals and society. She serves on several editorial advisory boards of top‐tier journals and as a reviewer across disciplines. She has published widely and recognized as a highly cited researcher by Clarivate and Stanford's list of highly cited researchers.

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Anu Leppiman, Ph.D; Dr.Soc.Sci, is Contract Professor of Experience Marketing at Estonian Academy of Music and Theater, Tallinn University of Technology and University of Lapland. Her research centers on customer‐, consumer engagement and interactive consumer/brand relationships and value. She has worked in various teaching, supervision and research positions in Marketing. Anu is the Certified Experience Expert and Business Communication Consultant of the Experience Marketing Research Group at TalTech DLab. Her work has been published in many prestigious scientific journals and books, and she actively participates as a reviewer of research articles and in the Scientific Committee of Journals.

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Dale Smith is a Property Manager at Goodwood Park Healthcare Group Ltd. Auckland, New Zealand. His research interests centers on customer engagement, experience, and loyalty. His work has published in Journal of Retailing & Consumer Services, Journal of Service Marketing and so forth.

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Rather, R. A. , Hollebeek, L. D. , VO‐THANH, T. , Ramkissoon, H. , Leppiman, A. , & Smith, D. (2022). Shaping customer brand loyalty during the pandemic: The role of brand credibility, value congruence, experience, identification, and engagement. Journal of Consumer Behaviour, 21(5), 1175–1189. 10.1002/cb.2070

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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