The purpose of this paper is to further the consumer services theory in financial services marketing by examining how perceived benefits influence consumer intention-to-use a co-branded credit card and further how intention-to-use is moderated by involvement.
A conceptual model is developed and tested. A convenience sample of users of a co-branded credit card was surveyed. The responses were analyzed using structural equation modeling.
Results show a strong association between perceived benefits and co-brand equity and between co-brand equity and co-brand preference, as well as between perceived benefits and intention-to-use. The research also identifies four perceived benefits of a co-branded credit card. They also show that highly involved consumers are less affected by perceived benefits than their low involvement counterparts.
Further research might consider co-branding across categories of services and explore the ambivalent results of co-brand preference in the mode. This research is limited by the use of a convenience sample and a cross-sectional survey. A probability sample and a longitudinal element to the study would have added weight to the study’s findings.
Managers with co-branding responsibilities should focus on improving the perceived benefits of co-branded credit cards.
This study has a wider application to understanding how co-branding services may be applied in not-for-profit situations, specifically affinity card co-branding, thus generating greater revenue for charitable and social concerns.
This research advances research in the financial services consumer theory by demonstrating a strong association between perceived benefits and intention-to-use a co-branded credit card, distinguishing between the behavioral traits of consumers with high and low levels of involvement. It thus advances the consumer theory in co-branding.
Wang, S. and Farquhar, J. (2018), "Co-branded services: perceived benefits and involvement of co-branded credit cards", International Journal of Bank Marketing, Vol. 36 No. 5, pp. 969-987. https://doi.org/10.1108/IJBM-05-2017-0098Download as .RIS
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Copyright © 2018, Emerald Publishing Limited
Co-branding (Newmeyer et al., 2014) and allied constructs such as ingredient branding (Desai and Keller, 2002), brand extensions (Balachander and Ghose, 2003) and composite branding (Park et al., 1996) are strategies where two or more brands come together with the purpose of offering elements of each of their brands to the customer (Simonin and Ruth, 1998). Co-branding is becomingly an increasingly important strategy as a means of adding value and increasing brand equity for the brands that constitute the alliance. In spite of the popularity of co-branding as a business strategy, academic investigation has lagged somewhat with a number of areas meriting deeper investigation. In the area of services branding, authors have observed that further work is needed in the area of co-branding (Brodie et al., 2009; Newmeyer et al., 2014). Research into co-branding has indicated that more studies are required into how service brands can benefit from forming an alliance (Helmig et al., 2007). Much of the work into co-branding has focused on the strategic management of co-branding (e.g. Abratt and Motlana, 2002; Bengtsson and Servais, 2005; Washburn et al., 2000), suggesting that consumer perspectives, in particular consumer intentions in the services branding theory (O’Cass and Grace, 2004). Existing studies into consumers’ behavioral intent have suggested that it is positively influenced by indirect effects of service quality and value (Cronin et al., 2000). It has also been noted that the likelihood of intention-to-use a service may be increased by perceived benefits (Wang et al., 2006).
Both the financial services and the airlines sector face major challenges with their brands offering them the means of responding (Clive, 2015). Co-branding offers companies in these sectors a means of increasing their brand equity (see e.g. us.cathaypacific.com/offers/credit card). Factors such as these have stimulated interest in brands and in particular the detail of co-branding (Wong and Merrilees, 2007).
Objective and intended contribution
This study, accordingly, aims to extend the co-branding consumer theory by examining the influence of perceived benefits on intention-to-use. To achieve this, a model of perceived benefits and intention-to-use a co-branded service (credit card) is developed and then tested on a sample of co-branded card users. The objective is to examine the impact of perceived benefits of co-branded card on consumers’ brand preference, brand equity and intention-to-use. A secondary objective is to examine how consumer involvement moderates these relationships.
The intended contribution is to both scholars and banking or marketing professionals. While extant studies often focus on one or two of the axioms of the theory, here authors test an integrated picture of perceived benefits of co-branded card (i.e. credit card preferential treatment, peripheral product and services of tourism, core product and services of tourism, and other special treatments). Further, the authors examine the indirect effect that consumer involvement has on established relationships in the proposed equity-preference-intention model. Another aspect of the contribution is that extant scholarship on brand equity and brand preference (e.g. Cobb-Walgren et al., 1995; Chen and Chang, 2008; Wang, 2014) has not been examined as a function of co-branded credit card in both banking and marketing. Furthermore, the model will be tested in an industry that has yet to be examined with respect to co-branded credit card.
The structure of this paper is as follows. First is a literature review and a brand equity, brand equity and intention-based conceptual framework with ensuing hypotheses. The following sections are methods, results and a discussion of the findings. The authors end with implications for the co-branding theory and for both banking practitioner, industrial practitioner and academic scholars.
Co-branding (Newmeyer et al., 2014) shares similar characteristics to ingredient branding (Desai and Keller, 2002), brand extensions (Balachander and Ghose, 2003) and composite branding (Park et al., 1996). All of these are strategies where two or more brands come together with the purpose of offering elements of each of their brands to the customer (Simonin and Ruth, 1998). Through co-branding, brands will offer the partner, or partners, access to a brand strategy, an alignment of brand values, marketing communication associations and an extended network of relationships (Motion et al., 2003). A stronger brand may ally itself with a vulnerable brand or brands to act as a discrete signal of quality to the consumer with the aim of building up consumer perceptions of the weaker brand or brands (Rao and Ruekert, 1994; Cunha et al., 2015). A benign view of this strategy is that the chances of a positive outcome for all strategic partners are increased regardless of the equities of the constituent brands before the alliance (Washburn et al., 2000). The brands in the alliance maintain their independence but develop a concerted strategy with the aim of provoking fresh and mutually beneficial evaluations from customers (Helmig et al., 2008).
There is a set of pre-conditions that favor co-branding success, such as a long-term agreement, the visibility of co-branders, congruence of brand identities (Xiao and Lee, 2014), launching of new products (Besharat, 2010) and the country-of-origin effect (Lee et al., 2013). These pre-conditions as well as the overall compatibility of brand partners (e.g. Cunha et al., 2015; Newmeyer et al., 2014) emphasize the importance of partner selection in co-branding endeavors, for example, brands who possess or need to build up brand equity. Existing studies into services branding suggest the existence of important relationships between brand image and customer perceptions of value (Brodie et al., 2009), the significance of communicating the brand’s value system through the customer experience (de Chernatony and Cottam, 2006) and the weight of value propositions in increasing brand equity (Marquardt et al., 2011).
Brand equity has long been viewed as a key marketing asset (Farquhar, 1989; Aaker, 1991) through its ability to engender a unique and welcoming relationship between a firm and its stakeholders (Capron and Hulland, 1999) and to promote long-term buying. Brand equity may be defined as the value that is added by a brand to a product (Farquhar, 1989; Aaker, 1991; Kamakura and Russell, 1993), as the differential effect of brand knowledge on a consumer’s response to the marketing of that brand (Keller, 1993). Therefore, the value of the brand name can be extended either by extending product lines or in ways that involve other brand names, as co-branding (Rao and Ruekert, 1994). Understanding the dimensions of brand equity and investing in this intangible asset can raise competitive barriers and drive brand wealth (Yoo et al., 2000). High equity brands appear to not be diminished by their pairing with low equity brands (Washburn et al., 2000).
A positive effect of brand equity has been observed on consumer preference and intention-to-purchase (Cobb-Walgren et al., 1995), with the capability of building long-term relationships with customers. However, it is brand preference that is more in tune with a liking or overall rating of a brand compared to other brands in a consumer’s evoked set (O’Cass and Lim, 2002). Consumers are biased or inclined toward those brands which they prefer or favor over other brands (Chang and Liu, 2009). Moreover, this preference is translated into action with Hellier et al. (2003) finding strong support for the relationship between brand preference and re-purchase intention. Primary brand associations, such as brand awareness and brand image influence brand preference, which ultimately affects purchase intention (Lim and O’Cass, 2001). How these findings relate to co-branding strategies has yet to be investigated.
Research, more recently, has investigated co-branding outcomes between well and lesser known brands through a focus on co-branding information (Cunha et al., 2015) in a similar vein to research between brands of unequal equity. Consumer reactions to co-branding complementarity (Swaminathan et al., 2015) and the effect of the level of between-partner congruity on consumer response to co-branded products (Walchli, 2007) have also been examined. The growing stream of co-branding research has emphasized the relationship between attitude and behavioral intention (Helmig et al., 2007) and, specifically, the perceived benefits of co-branding (e.g. Bengtsson and Servais, 2005; Washburn et al., 2004). Intention-to-use is a combination of consumer interest in buying or using a product and the possibility of buying or using that product (see e.g. Nysveen et al., 2013). Perceived benefits are thought to influence a consumer’s intention-to-use a product/service. Intention-to-use has been studied in the field of information technology and specifically in mobile services, for example, Nysveen et al. (2005). Findings indicate that consumer intention-to-use mobile services, for example, was a function of motivational, attitudinal, social, and resource-related influences. Additionally, the researchers found that a mix of utilitarian and hedonic perceived benefits had direct effects on consumer intention-to-use. In a study into green branding, psychological as well as utilitarian benefits of green brands influenced purchase intentions were noted (Hartman and Apaolaza-Ibañez, 2012) Investigating the perceived risks and benefits in online shopping, the findings indicated that perceived benefits were positive predictors of future intentions to visit and purchase online (Forsythe et al., 2006).
Brand choice and intention-to-use may be influenced by the moderating variable of involvement (Fan et al., 2013; Wang, 2014). Involvement has been characterized as a person’s perceived relevance of an object based on inherent needs, values and interests (Zaichkowsky, 1985). The level of involvement that consumers have with a product or service is a function of the relevance of that product or service to their requirements, values and interests (Zaichkowsky, 1985). Highly involved consumers seek extensive information before making a purchase; processing all relevant information in detail, and applying more criteria to their purchasing decisions than their less involved counterparts (Laaksonen, 1994). Consumers, in a state of low involvement, behave passively in seeking and processing product information and do not take time to consider decision-related information. In these circumstances, their information processing is simple and relies on peripheral cues, such as the brand name of the product (Fan et al., 2013; Petty and Cacioppo, 1986). Consumers, who are involved with a particular brand, are more committed and more loyal to that brand. In the context of services, highly involved consumers show greater interest in building relationships with the service providers (Varki and Wong, 2003). Highly involved consumers are, therefore, less affected by brand information when making purchasing decisions. Research indicates that involvement with a product or service strengthens perceptions of attribute differences, perceptions of product importance and commitment to the brand (Swoboda et al., 2009; Von Riesen and Herndon, 2011). Research into co-branding and involvement is somewhat limited but so far, it has been noted that product involvement and consumers’ brand orientation influence the success of a co-branded offering (Helmig et al., 2007), indicating that further investigation into the relationship between involvement and co-branding is merited.
This study, accordingly, aims to extend the co-branding consumer theory by examining the influence of perceived benefits on intention-to-use, thus responding to limitations in current understanding of co-branding. Through defining and operationalizing a model of the influence of perceived benefits of a co-branded credit card, empirical support for this conceptualization is gained. In the next section, the hypotheses of the study are developed.
Conceptual model and research hypotheses
The framework and hypotheses of the study are presented in Figure 1, and developed in the rest of this section.
Co-branding influences brand equity perceptions of the constituent brands whether the constituents of these allied brands are high or low in equity (Washburn et al., 2000), and leads to the formulation of the following hypotheses:
The perceived benefits of a co-branded credit card positively affects brand equity.
Co-brand equity positively influences brand preference.
Co-brand equity positively influences intention-to-use.
Brand preference is considered an antecedent of brand equity (Cobb-Walgren et al., 1995). Preference for co-branded offerings seems as yet to be unexplored, so studies on brand preference informs the following hypotheses:
The perceived benefits of a co-branded credit card positively affect brand preference.
Co-brand preference positively influences intention-to-use.
Perceived benefits and intention-to-use a co-branded service
In this study, the direct impact of consumers’ perceived benefits of the co-branded service on intention-to-use, the indirect influence of consumers’ perceived benefits on the co-brand preference and co-brand equity are all hypothesized to influence consumer intention-to-use:
The perceived benefits of a co-branded credit card positively affect intention-to-use.
Involvement and co-branding behavior
A consumer’s involvement with the product or service category is an important consideration as it may indirectly influence various relationships in brand outcomes in co-branded credit card. Involvement refers to the perceived importance of specific products or services based on customer needs, values and interests (Mittal, 1995). Customers may have varying levels of involvement on dissimilar product categories (Bloch and Richins, 1983). Flynn and Goldsmith (1993) further suggest that highly involved customers are inclined to display better loyal buying behavior. In this study, the potential moderating effects of involvement in co-branding (Helmig et al., 2007; Mazodier and Merunka, 2014) and perceived benefits in services (Kinard and Capella, 2006) consist of part of the conceptual model. Meanwhile, several categories of benefits are summarized according to Park (2010), Martín et al. (2011) and Boer and Gudmundsson (2012), which are included in the measurement instrument (see Table II) as are the moderating effects of involvement. Thus, authors consider indirect effects due to the consumer’s involvement in the industry. Specifically, involvement may moderate the effects that consumer involvement has on established relationships in the proposed equity-preference-intention model. However, it has yet to be examined if and to what extent that consumer involvement indirectly impacts the established relationships in the proposed equity-preference-intention model. We thus propose the following hypotheses:
The relationship between perceived benefits of co-branded credit card and co-brand equity is intensified when the consumer is highly involved.
The relationship between perceived benefits of co-branded credit card and intention-to-use is intensified when the consumer is highly involved.
The relationship between perceived benefits of co-branded credit card and co-brand preference is intensified when the consumer is highly involved.
The relationship between co-brand preference and intention-to-use is intensified when the consumer is highly involved.
The relationship between co-brand equity and co-brand preference is intensified when the consumer is highly involved.
The relationship between co-brand equity and intention-to-use is intensified when the consumer is highly involved.
Methodology and analysis
To measure the perceived benefits of a co-branded credit card, 13 items were adopted from studies by Park (2010), Martín et al. (2011), Boer and Gudmundsson (2012) and Akram et al. (2014). To measure co-brand equity, three items were adapted from the study by Aaker (1991). To measure co-brand preference, two items were adapted from the studies by Jamal and Goode (2001), and Chen and Chang (2008). To measure intention-to-use, six items were modified from studies by Kuhl (1985), Ganesh et al. (2000), Gomez et al. (2006) and Fock et al. (2005). Finally, for involvement, nine items were adopted from the work by Zaichkowsky (1994). A Likert-type response of five points was used for perceived benefits, co-brand equity and co-brand preference. The involvement items were measured with a seven-point semantic differential scale. As the samples for the study were Chinese speaking, the questionnaire items were translated from English to Chinese in a tripartite process that included language, back-translation and a third-party re-translation for conceptual consistency. The instrument was pre-tested and revised in the light of the pre-test, for example, the items of airline mileage points was changed to airline miles in all instances.
The sample for the survey was drawn from air passengers using or having used a co-branded credit card. All respondents were over the age of 20 as it is the minimum age requirement for having a credit card in Taiwan, where the study took place. Potential respondents were approached at different times of the day and different days of the week to establish variance in the sample. Data were collected during a one-month period at an international airport in a predominantly Chinese-speaking location. The researchers obtained 398 usable samples from the 500 questionnaires distributed. After excluding incomplete questionnaires, a 79.6 percent response rate was obtained. The sample characteristics are listed in Table I.
Exploratory factor analysis (EFA)
An EFA test of perceived benefits revealed four factors, namely, credit card preferential treatment (four items); peripheral product and services of tourism (three items); core product and services of tourism (three items); and other special treatments (three items). EFA was used to check for any notable deviation from the structure of the adapted constructs. The data were checked for conformity to multi-normality requirements prior to using SEM model testing (McDonald and Ho, 2002). The models were tested in a two-stage structural equation framework, using confirmatory factor analysis (CFA) to evaluate construct validity regarding convergent and discriminant validity before performing structural path analysis. The sample size (n=398) was sufficiently large to compensate for likely model misspecification and model complexity (Hair et al., 2006). The findings were checked for possible univariate and multivariate outliers but revealed no significant violations. Kurtosis values ranged from −0.58 to 1.26 and skewness from −0.29 to 0.86, satisfying usual evaluation criteria (Mardia, 1985) (Table II).
Common method variance (CMV) testing
CMV is a potential problem in behavioral research (cf. Bagozzi and Yi, 1990; Cote and Buckley, 1987, 1988; Williams et al., 1989). Procedural remedies were adopted to eliminate CMV (Podsakoff et al., 2003), yielding insignificant conclusions (p=0.950, p>0.05) for CMV test by unmeasured latent method construct (Richardson et al., 2009). The validity of this study therefore appears not to be affected by CMV. When testing for CMV with Harman’s one-factor test, EFA generated three factors with none having a loading larger than 50 percent (Podsakoff and Organ, 1986). The differences in CFA were from a single factor and multi-factor structure (Lindell and Whitney, 2001), the Δχ2=2,139.86, Δdf=12, p=0 (Δχ2/Δdf=178.3217, multi-factor: χ2=1,072.448/df=312, one-factor: χ2=3,378.911/df=324), indicating that validity was not affected by CMV (Carson, 2007). In addition, we examined for nonresponse bias, by comparing early and late respondents across all variables in the study (Armstrong and Overton, 1977), finding that there was no significant difference across groups.
To examine the moderating effect of involvement, the sample was divided using the quartiles of the level of these involvement items. The authors first averaged the nine scores of involvement scale for each respondents and sorting all the average value of involvement. Then we grouped the respondents with top 100 (398/4, the first quartile) average scores of involvement scale as the “High involved” respondents, and the countdown to 100 (398/4, the last quartile) average sores of that as the “Low involved” ones (Chen and Chang, 2008). The first and last quartiles are defined as the high (μ=4.26/n=100) and low (μ=2.49/n=100) involvement groups, and are subsequently used for testing the causal relationships. In Table I, the respondents are grouped according to their level of involvement with the co-branded card. Results of multi-group analysis could be found in Table III.
Measurement model, reliability, and validity
The proposed measurement model was estimated using LISREL 8.80 (Jöreskog and Sorböm, 1993). The goodness-of-fit indices are summarized below. The χ2 statistics are significant at the 0.05 level. The values for comparative fit index (CFI), non-normed fit index (NNFI), root mean square error of approximation (RMSEA) and standardized root mean residual (SRMR) were considered acceptable for proposed model, based on the criteria suggested by Hu and Bentler (1999) and are as follows: 0.95 for CFI and NNFI, 0.06 for RMSEA and 0.08 for SRMR.
After testing the measurement model, the quality and adequacy of measurement model was further assessed by investigating unidimensionality, reliability, convergent validity and discriminant validity. First, unidimensionality was assessed on the basis of principal component analyses performed on all items. All items loaded on 0.65 or higher on the hypothesized factors and no profound cross-loading was identified on the EFA findings. With regard to composite reliability, all the composite reliability values exceed 0.9 exceeding suggested benchmarks (Bagozzi and Yi, 1988). Next, in a CFA setting, convergent validity was assessed by examining t-statistics related to the factor loadings. All t-statistics are statistically significant at the 0.05 level, suggesting that all indicator variables provided good measures to their respective construct and supporting claims for convergent validity (Hoyle and Panter, 1995).
The AVE values are at or higher than 0.50, once again supporting convergent validity (Fornell and Larcker, 1981). Finally, discriminant validity is assessed using the procedure recommended by Bagozzi and Phillips (1982). A series of χ2-difference tests are performed on the nested models to assess whether the χ2 values are significantly lower for the unconstrained models where the ϕ coefficient is constrained to unity. The critical values related to the χ2-difference at the 0.05 significance level are higher than 3.84 in all possible pairs of constructs, and this outcome gives support to discriminant validity. The studied constructs meet the commonly recognized reliability and validity standards. The overall fit of the model is reasonable. Simultaneous maximum-likelihood-estimation procedures are used to examine relationships among perceived benefits of the co-branded credit card and its sub-dimensions, perceived benefits of co-branded credit card, co-brand equity, co-brand preference and intention-to-use (see Table III).
Measurement scales and summary statistics are given as follows.
Perceived benefits of co-branded credit cards (mean=3.98, CR value=0.925, AVE=0.87):
No annual fee or reduced annual fee.
Welcome gifts for submission or approval of application.
First transaction reward.
Airline miles in all instances.
Bonus miles during birth month.
Discount on in-flight, duty-free products.
Special services and priority for seamless global trips (priority access to VIP lounge, boarding, reservation services and luggage handling).
Free pickup and reserved parking services.
Travel insurance services.
Better airline ticketing services.
VIP medical services.
Free tickets and seat upgrade.
Special rates on tickets and hotels for frequent flyers.
Co-brand equity (mean=4.01, CR value=0.886, AVE=0.82).
I hold the leading co-branded credit card.
My airline co-branded credit card is synonymous with the airline.
This airline’s co-branded credit card provides good value for money.
Co-brand preference (mean=4.10, CR value =0.927, AVE=0.84)
This airline’s co-branded credit card is appealing to me.
I prefer this airline’s co-branded credit card to others.
Intention-to-use (mean=4.04, CR value =0.918, AVE=0.85).
I am willing to recommend the use of this co-branded credit card to others.
I am willing to use this co-branded credit card in the future.
I will recommend this co-branded credit card brand to my family.
I will recommend that my family purchase tourism relevant products/services using this co-branded credit card.
I prefer to use this co-branded credit card when I travel abroad.
I will keep using this co-branded credit card in purchasing tourism relevant products and services in the future.
Involvement (mean=3.39, CR value=0.909, AVE0.83).
Co-branded credit cards are important for me.
Co-branded credit cards are interested for me.
Co-branded credit cards are relevant to me.
Co-branded credit cards are exciting for me.
Co-branded credit cards are meaningful for me.
Co-branded credit cards are attractive notion to me.
Co-branded credit cards are valuable to me.
Co-branded credit cards demand a certain amount of involvement from me.
Co-branded credit cards are necessary for me.
With n=398, χ2=1,089.34(p=0.00, df=434), χ2/df=2.51, GFI=0.94, CFI=0.99, RMSEA=0.038.
In the next section, the findings of the survey are discussed.
The analysis reveals that for the full sample of users of the co-branded service (n=398) significant relationships between latent constructs match the hypothesized directions. The exception is H4 (perceived benefits of the co-branded credit card are associated with co-brand preference), which is supported by an earlier brand framework (Cobb-Walgren et al., 1995). This hypothesis is however supported for the high involvement sub-sample. Although it seems reasonable that perceived benefits should influence co-brand preference for the co-branded services, the analytic results did not support this assertion. This finding may be attributed to the accumulation process of the co-brand concept as initiated from the increase of co-brand equity, and then the formation of co-brand preference (Wang, 2014).
In the empirical model (see Figure 2), perceived benefits of co-branded credit card were proved to consist of four benefits of the co-branded credit card (preferential treatments; peripheral products and services of tourism; core products and services of tourism; and other special treatments) Meanwhile, perceived benefits of the co-branded credit card have significant positive effect on co-brand equity (H1) and intention-to-use (H6). Co-brand equity has significant positive effects on co-brand preference and intention-to-use, supporting H2 and H3 and again in line with findings in brand research (e.g. Cobb-Walgren et al., 1995). Finally, the effect of co-brand preference on intention-to-use is also significant, supporting H5. Again, these findings in this co-branding investigation are consistent with past branding researches (Cobb-Walgren et al., 1995; O’Cass and Lim, 2002).
The moderating effects of involvement in the model are somewhat interesting (see Figure 3). For the high involvement sample, the effect of perceived benefits of the co-branded credit card on co-brand equity, and co-brand equity on co-brand preference are not significant. For the low involvement group, both the effects of perceived benefits of the co-branded credit card on intention-to-use, and on co-brand preference are not significant. Further, the effect of perceived benefits of the co-branded card on credit card preferential treatment is insignificant. As to the effects of co-brand preference→intention-to-use, co-brand equity→intention-to-use, perceived benefits of co-branded credit card→peripheral products/services of tourism, perceived benefits of co-branded credit card→core products/services of tourism and perceived benefits of co-branded credit card→other special treatments, all of these hypotheses are significant for both high and low involvement sub-samples.
Overall, H5, and H3 are supported for both sub-samples. By investigating levels of involvement, distinctions between low and high involvement users surface in this study as broadly predicted in the involvement literature (see e.g. Fan et al., 2013; Petty and Cacioppo, 1986). H1and H2 are only supported for the low involvement sub-sample, and H6 and H4 are only supported for high involvement sub-sample. The results indicate that the moderating effect of involvement on the paths of perceived benefits of co-branded credit card→co-brand equity, co-brand equity→co-brand preference, perceived benefits of co-branded credit card→intention-to-use, perceived benefits of co-branded credit card→co-brand preference, perceived benefits of co-branded credit card→credit card preferential treatment do exist, supporting H7a, H7b, H7c and H7e. Involvement therefore moderates the effects of perceived benefits on intention-to-use the co-branded service, here the co-branded credit card.
This research responds to calls for further research into co-branding (Brodie et al., 2009), the co-branding of services (Helmig et al., 2007) and consumer intentions in services branding (O’Cass and Grace, 2004). The authors developed a conceptual model of perceived benefits and intention-to-use a co-branded service (co-branded credit card) with the important extension of the moderating effects of involvement on these relationships. The findings generate advances in services co-branding in several areas.
First, the study’s hypothesized relationships between perceived benefits, co-brand equity and intention-to-use are supported, signifying that perceived benefits can enhance co-brand equity and that co-brand equity in turn is positively linked to intention-to-use. This finding supports earlier work by Motion et al. (2003) on co-branding as a source of equity. The research finds, second, that those consumers who are highly involved perceive the advantages of the co-branded credit card, prefer it and are therefore likely to use it. Consumers, with lower levels of involvement, make decisions based on brand information, consistent with previous work in this area (Fan et al., 2013). While co-branded benefits do not lead to brand preference and intention-to-use, the findings suggest that increasing co-brand equity may be an path to reach consumers with lower levels of involvement. Specifically, preferential treatment appears not to work in promoting perceived benefits of co-branding for the less involved consumers.
The research also finds that the perceived benefits for the partner in the co-branded cards are positively reflected in four sub-dimensions (preferential treatment, tourism-related peripherals, tourism-related core products and services, and other special treatments). The most important sub-dimension of these benefits is special treatments. The study suggests that consumers are neither necessarily aware of the benefits of the co-branded service nor do they necessarily see them as important (the average value of involvement of the co-branded credit card is low). By focusing on the perceived benefits, this study indicates that co-brand equity and co-brand preference will be strengthened, which, in turn, will increase intention-to-use. Increased understanding of the level of involvement with co-branded services advances understanding in consumer behavior, specifically by once again distinguishing between consumers with high and low levels of involvement (see e.g. Laaksonen, 1994). According to the results, consumers with different involvement levels have different perceptions of the benefits of co-branded credit cards. Highly involved consumers care about the co-branded cards and card-related preferential treatments, while customers with low involvement emphasize its effects on brand equity. These differences subsequently result in different perceptions of co-brand equity, co-brand preference and intention-to-use indicating that involvement with co-branded services is an important moderator in predictions of intention-to-use, which is in tune with previous research (Varki and Wong, 2003; Kinard and Capella, 2006).
The research findings suggest implications for practice. Managers with co-branding responsibilities should focus on improving the perceived benefits of the co-branded service. This research has highlighted the importance of special treatments; therefore, the identification of those special treatments, which influence intention-to-use, becomes a high priority. Co-brand equity directly influences consumer intention-to-use; therefore, the brands should invest in building and sustaining equity in their brands and the alliance. The findings of this study may also be extended to affinity cards or co-branding activities dedicated to raising revenue for not-for-profit concerns (see e.g. Fock et al., 2005).
Future research directions
This study suggests a number of avenues for further research. This research has indicated distinctions between highly involved consumers and their less involved counterparts; however, more empirical research is needed into levels of involvement in services consumption and particularly its effects on co-branding. In particular, there is a need to explore the lack of positive significant effect between perceived benefits of co-branded credit cards and brand preference, and benefits of co-branded credit cards and intention-to-use. Co-brand preference is not particularly well supported in this research, indicating that this dimension needs to be better understood. This research has focused on one category of service, that is, co-branded credit cards; further research may consider perceived benefits and intention-to-use across differing categories of co-branded services such as hedonic and functional, high and low contact or even a combination of these categories.
Characteristics of sample
|Age||Under 30 years||26||26.0||22||22.0||86||21.6|
|Above 51 years||10||10.0||2||2.0||21||5.3|
|Average monthly income||Less than 20,000||4||4.0||4||4.0||16||4.0|
|More than 80,001||23||23.0||14||14.0||65||16.4|
|Annual leisure expenditure||Less than 30,000||18||18.0||24||24.0||70||17.6|
|More than 150,001||15||15.0||9||9.0||51||12.8|
|Annual frequency by airplane||1–2 times||46||46.0||55||55.0||203||51.0|
|More than 10 times||5||5.0||1||1.0||9||2.3|
|Annual frequency of airline credit cards consumption in air transport/tourism services or products||1-2 times||49||49.0||73||73.0||227||57.0|
|More than 10 times||5||5.0||3||3.0||15||3.8|
|Annual expenditure of airline credit cards consumption in air transport/tourism services or products||Less than 30,000||25||25.0||50||50.0||127||31.9|
|More than 150,001||10||10.0||1||1.0||22||5.5|
Notes: “n” means number of sample; “μ” means average value of involvement
Results of EFA analysis on co-brand benefits
|Credit card preferential treatment||Peripheral product and services of tourism||Core product and services of tourism||Other special treatments|
|Welcome gifts for submission or approval of application||0.858|
|First transaction reward||0.790|
|No annual fee or reduced annual fee||0.707|
|Airline miles in all instances||0.558|
|Travel insurance services||0.790|
|Free pickup and reserved parking services||0.758|
|VIP medical services||0.838|
|Free tickets and seat upgrade||0.570|
|Special rates on tickets and hotels for frequent flyers||0.563|
|Better airline ticketing services||0.537|
|Discount on in-flight, duty-free products||0.784|
|Bonus miles during birth month||0.695|
|Special services and priority for seamless global trips (priority access to VIP lounge, boarding, reservation services and luggage handling)||0.519|
|Accumulated variance explained||24.089||45.241||63.231||80.639|
Notes: Results of EFA was generated from principal component analysis with rotated Varimax, accumulated variance explained had reached 80.639 percent; meanwhile, Kaiser-Meyer-Olkin 0.958, Barlett test 4,383.792, df=78, sig.=0.000
Structural parameter estimates and goodness-of-fit indices
|Moderating effects of involvement (H7a–H7b)|
|Hypothesized Paths||Hypothesis||Full sample||High involved||Low involved|
|Perceived benefits of co-branded credit card→co-brand equity||H1||0.748(14.970**)a||0.12(1.58)||0.48(6.86)**|
|Perceived benefits of co-branded credit card→intention-to-use||H6||0.143(2.813**)||0.61(10.68**)||0.11(1.35)|
|Perceived benefits of co-branded credit card→co-brand preference||H4||0.038(0.643)||0.46(7.86**)||0.09(1.13)|
|Co-brand equity→co-brand preference||H2||0.784(12.029**)||0.15(1.63)||0.89(16.21)**|
|Co-brand equity→ intention-to-use||H3||0.307(4.070**)||0.52(9.35**)||0.65(12.84**)|
|Perceived benefits of co-branded credit card→credit card preferential treatment||0.933(8.515**)||0.57(9.42**)||0.08(1.23)|
|Perceived benefits of co-branded credit card→peripheral products/services of tourism||0.931(8.484**)||0.35(3.74**)||0.69(13.74**)|
|Perceived benefits of co-branded credit card→core products/services of tourism||0.965(6.720**)||0.39(4.52**)||0.74(15.68**)|
|Perceived benefits of co-branded credit card→other special treatments||0.971(5.087**)||0.52(8.63**)||0.42(5.31**)|
|μHigh Inv. =4.26||μLow Inv. =2.49|
|Moderated path in the χ2-difference test||χ2-difference test between low and high involvement for moderated path|
|Perceived benefits of co-branded credit card→co-brand equity||H7a||Δχ2=6.28, df=1, p<0.05||H7a Supported|
|Perceived benefits of co-branded credit card→intention-to-use||H7b||Δχ2=5.94, df=1, p<0.05||H7b Supported|
|Perceived benefits of co-branded credit card→co-brand preference||H7c||Δχ2=5.39, df=1, p<0.05||H7c Supported|
|Co-brand preference→intention-to-use||H7d||Δχ2=1.58, df=1, p>0.05||H7d Not supported|
|Co-brand equity→co-brand preference||H7e||Δχ2=6.73, df=1, p<0.05||H7e Supported|
|Co-brand equity→intention-to-use||H7f||Δχ2=1.72, df=1, p>0.05||H7f Not supported|
Notes: aThe value in the parenthesis is t-value. **Denotes p⩽0.05
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