Abstract
This study contributes to the development of knowledge on transferring the concept of customer-based brand equity to a tourism destination context. Keller’s brand equity pyramid is utilized as the comparison framework to reveal similarities, but also overlaps, differences and gaps on both the conceptual and measurement level of existing brand equity models for destinations. Particularly, the inner core of the model depicts the complex mechanisms of how destination resources transform into benefits for tourists overlooked by prior research. This study proposes a customer-based brand equity model for destinations, which consists of five dependent constructs, including awareness, loyalty, and three destination brand promise constructs constituting the inner core of the model, namely, destination resources, value in use, and value for money. The model was repeatedly tested for the leading Swedish mountain destination Åre, by using a linear structural equation modeling approach. Findings confirm the path structure of the proposed model.
Keywords
Introduction
Countries, regions, cities and even small locations and resorts make efforts to strengthen their destination brands, aiming at differentiating themselves from competitors to convey a unique value proposition and, in the end, attract visitors and facilitate repeat visitation, readiness to pay a premium price, and positive word of mouth (Blain, Levy, and Ritchie 2005; Pike 2005). Destination management organizations (DMOs) invest substantial budgets into the design of logos, development of slogans, publication of brochures, creation of websites, organization of events, and the implementation of a variety of additional branding efforts. Thus, an issue that inevitably arises is whether these efforts help destinations reach their marketing goals? Do they really create successful and fundamentally memorable brands?
To answer these questions, tourism research usually employs customer-based approaches for the conceptualization and measurement of brand equity with emphasis on consumers’ response to a brand name (Gartner 2009; Christodoulides and de Chernatony 2010; Davcik, da Silva, and Hair 2015; Round and Roper 2015). As shown in the literature review below, previous research widely adopted Aaker’s (1991, 1996) and Keller’s (1993) conceptualization of customer-based brand equity (CBBE). It derives from cognitive psychology and focuses on multidimensional memory structures, like awareness, image perception, quality and value assessments, as well as loyalty. Destination brand equity studies have developed reliable, valid, parsimonious, and theoretically sound measurement constructs that can be implemented with “pen and paper” instruments, thereby demonstrating managerial usefulness as diagnostic tools, capable of identifying areas for improvement and how the brand is perceived by customers. Although scholars emphasize that the complexity and multidimensionality of destinations compared with goods complicates the measurement of CBBE in a destination context (Boo, Busser, and Baloglu 2009; Pike 2009; Gartner 2009), destination brand equity studies directly transfer conceptualization and measurement approaches developed for product brands, especially consumer packaged goods (Christodoulides and de Chernatony 2010). Indeed, tourism literature exhibits a lack of a sound theoretical discussion regarding the dimensionality of model constructs, measurement scales, and the linkages between core model dimensions under the supposition of tourism as a service industry. Nevertheless, the understanding of the mechanisms behind the formation of attitudes that tourists develop toward destination brands has become a managerial task of ultimate importance (Davis, Piven, and Breazeale 2014; Jung, Kim, and Kim 2014). Thus, in the absence of a CBBE theory adapted to the peculiarities of destinations, tourism research risks drawing the focus away from the essence of a destination brand and its value, thereby losing its managerial relevancy.
Christodoulides and de Chernatony (2010) suggest that the selection of model constructs should align with the brand category (product type), thus incorporating service-specific dimensions that drive customer-based brand value. We similarly believe that destination branding research could largely benefit from the contemporary service-oriented marketing perspective (Li and Petrick 2008). Tourism literature traditionally addresses the heterogeneous and customer-centric nature of tourism. For example, Debbage and Daniels (1998) argue that the “tourist industry as a mode of production is enormous, highly commodified, and structured in ways that are fairly similar to other sectors of the economy” (ibid., 18). They further emphasize that tourism is “no single product but, rather, a wide range of products and services that interact to provide an opportunity to fulfil a tourist experience that comprise both tangible parts (e.g., hotel, restaurant, or air carrier) and intangible parts (e.g., sunset, scenery, mood)” (ibid., 23). Furthermore, in order to address the complexity of tourism as an economic sector, the tourism marketing literature introduced the concept of tourism destination viewed as a marketplace where tourism demand and supply finally meet (Murphy 1985; Goodall and Ashworth 1988; Buhalis 2000; Beritelli, Bieger, and Laesser 2014). Thus, Murphy, Pritchard, and Smith (2000) define a tourism destination as “an amalgam of individual products and experience opportunities that combine to form a total experience of the area visited” (ibid., 44).
While experiences exist in consumers’ minds, destinations and tourists co-create places where the tourist experience may occur. Destinations co-create experiences of individual tourists by offering the functional, emotional, and symbolic value of the visitation (i.e., the brand) (Gnoth 2007). In turn, tourists choose between available products and services, directly participate in activities, interpret the elements of the physical environment devoted to tourism consumption, and allocate their own resources, including time, money, efforts, and skills (Mossberg 2007; Arnould, Price, and Tierney 1998; Fuchs 2004; Gnoth 2007; Pettersson and Getz 2009). By utilizing a destination’s products, services, and other tangible and intangible resources (e.g., natural amenities, local culture, and atmosphere of the place), tourists experience the destination and evaluate whether their experience was valuable (i.e., value in use) (Vargo and Lusch 2004; Moeller 2010).
This study aims at contributing to the further development of the CBBE theory in a tourism destination context by bridging the gap between destination brand equity evaluation and the service nature of tourism consumption. After a review of the literature, a framework based on Keller’s (2008) brand equity pyramid is utilized to compare findings from previous destination brand equity studies. In subsequent sections, the conceptual model and hypotheses are presented. More precisely, in order to adjust the CBBE model for tourism destinations, we take into account the value-co-creation approach recently developed by service marketing scholars (Grönroos 2000, 2009; Vargo and Lusch 2004, 2008). We propose that the core component of the CBBE model is about customers’ evaluation of the destination promise to transform destination resources into value in use for the tourist. This approach is consistent with Gnoth’s (2007) conceptualization of destination brands viewed as a representation of functional, emotional, and symbolic values as well as the benefits tourists are promised to receive as the result of service consumption. We, therefore, suggest to integrate the concept of value in use of tourism destination visitation into the CBBE model. Finally, the influence of destination brand awareness on the evaluation of the destination promise is hypothesized, which, in turn affects actual behavior and behavioral intentions of tourists toward the destination.
Literature Review
Brand equity considers the differentiation effect that the customers’ knowledge of the brand has on the customers’ response to a product or service, the overall utility that customers place in a brand compared to its competitors (Keller 1993; Lassar, Mittal, and Sharma 1995; de Chernatony and McDonald 2003). It is also a measure of marketing efforts’ effectiveness (Keller 2008). Brand equity is defined as “assets and liabilities, including brand awareness, loyalty, perceived quality and brand associations linked to a brand’s name and symbol that adds to (or subtracts from) the value provided by a product or service to a firm and/or that firm’s customers” (Aaker 1996, 7–8). From a service marketing perspective, brand equity is the outcome of developing brand relationships (Grönroos 2000). Accordingly, Keller (2009) extended the CBBE model to reflect this relationship-building process between customers and the brand. His hierarchical “CBBE pyramid” describes four stages of brand development, including brand identity (brand salience), brand meaning (performance of tangible products and imagery related to intangible aspects of the brand), brand response (judgments and feelings), and brand relationships (resonance) aiming at the establishment of customer loyalty (Keller 2008, 2009).
Destination brand equity research focuses on the development of destination brand performance models, thus enabling the measurement of the marketing effectiveness of tourism destinations and the prediction of the destination’s brand development in the future. While destination brand equity measurement has only recently attracted attention, it is typically studied from the customers’ perspective. By applying Aaker’s (1996) and Keller’s (1993) CBBE concept, tourism scholars view the CBBE model for destinations as “the sum of factors contributing to a brand’s value in the consumer’s mind” (Konecnik and Gartner 2007, 401). Konecnik and Gartner (2007) were the first to apply the CBBE model in a destination context, arguing that the image construct should be isolated from other brand dimensions, such as awareness, quality, and loyalty. Additional authors examine the relationships between CBBE model dimensions (Boo, Busser, and Baloglu 2009; Pike, Bianchi, Kerr, and Patti 2010; Chen and Myagmarsuren 2010; Kladou and Kehagias 2014) or take out destination loyalty of the CBBE model (Horng, Liu, Chou, and Tsai 2012; Im et al. 2012; Bianchi, Pike, and Ling 2014). Other studies focus on the relationships between destination brand equity and social influence (Evangelista and Dioko 2011), destination involvement (Kim et al. 2009) or enduring travel involvement (Ferns and Walls 2012). Finally, one group of authors suggests that destination brand equity analysis should not be limited to the customers’ perspective but rather should integrate stakeholders, including entrepreneurs and residents (Garcia, Gómez, and Molina 2012).
Table 1 summarizes existing CBBE models for tourism destinations by relating model dimensions to the respective brand building blocks of Keller’s (2009) brand pyramid. It reveals similarities but also differences, overlaps, and gaps on both the conceptual and measurement levels of CBBE model specifications. As will be discussed in detail next, the framework assists in better understanding the complexity of relationships within CBBE models previously adopted and validated in a tourism destination context.
Comparison of CBBE Measurement Models in Previous Tourism Destination Studies.
The construct is included into the respective study, but it is considered outside of the CBBE model.
Destination Brand Salience
Brand salience, defined as “the strength of awareness of the destination for a given travel situation,” is the foundation of the CBBE model for destinations (Pike et al. 2010, 439). The majority of CBBE destination studies adopt Aaker’s (1996) concept of brand awareness, defined as the strength of the brand’s presence in the mind of the target audience (e.g., Boo, Busser, and Baloglu 2009; Kladou and Kehagias 2014; Konecnik and Gartner 2007). It is emphasized that “a place must be known to the consumer in some context before it can even be considered as a potential destination” (Gartner and Konecnik Ruzzier 2011, 473). This implies that potential tourists are familiar with the destination and that an image of the destination exists in their minds (Konecnik and Gartner 2007; Chen and Myagmarsuren 2010). Therefore, brand awareness—as the first step in brand equity creation—must be of a positive nature (Gartner and Konecnik Ruzzier 2011). The majority of destination brand equity studies include awareness defined as tourists’ ability to recall destination characteristics (e.g., Bianchi, Pike, and Ling 2014; Chen and Myagmarsuren 2010; Ferns and Walls 2012). Destination awareness exists on different levels, including brand recognition, recall, familiarity, top-of-mind awareness, recall of destination advertising, brand dominance, reputation, and brand knowledge. Furthermore, some authors address various information sources affecting destination image (Baloglu and McCleary 1999; Beerli and Martin 2004), and distinguish between informational destination familiarity (based on previously used information) and experiential destination familiarity (reflecting previous destination experience) (Baloglu 2001).
Overall, tourism research concludes that brand salience, defined as the strength of destination awareness, is an important first step in destination brand equity creation. However, there is no agreement on construct operationalization, as the only destination awareness measure consistently employed in previous studies is the ability to recall destination characteristics. The literature review reveals a need for further theoretical and methodological developments of the brand salience model block. Thus, for the purpose of operationalization and empirical validation of the awareness construct, this study emphasizes aspects of destination characteristics, recall, and the presence of information sources.
Destination Brand Performance and Imagery
Image and quality reflect specific characteristics of the destination and belong to the brand performance and imagery building block (Keller 2009). Destination brand equity studies usually consider attribute-based conceptualizations when measuring perceived destination image and quality (e.g., Horng et al. 2012; Kladou and Kehagias 2014; Pike et al. 2010). These studies adopt Keller’s (1993) conceptualization of brand image, defined as perceived destination brand reflected by a distinct set of associations, like knowledge, beliefs, feelings, and impressions about a destination that consumers hold in memory and associate to the destination name. In turn, brand quality is defined as perceived overall superiority of a (service) product (Aaker 1991; Bianchi, Pike, and Ling 2014; Boo, Busser, and Baloglu 2009; Keller 1993). Tourism studies follow Parasuraman, Zeithaml, and Berry’s (1985, 1988) quality concept that compares customers’ expectations and perceived performance, thereby reflecting an overall judgment toward the excellence of service delivery (Chen and Myagmarsuren 2010; Horng et al. 2012; Pike et al. 2010). Accordingly, destination brand quality is defined as “travelers’ perception of a destination’s ability to fulfil their expectation” (Ferns and Walls 2012, 29).
Previous studies typically address the specificity of tourism destinations by employing Echtner and Ritchie’s (1991, 1993) framework, further developed for destination image conceptualization by Gallarza, Saura, and Garcia (2002). Dimensions include attribute-based and holistic images, functional and psychological characteristics, as well as common and unique images of a destination. The approach presumes that destination brand image reflects those destination resources that make the destination attractive in the eyes of potential tourists (Horng et al. 2012). Similarly, destination brand quality refers to destination attributes perceived by tourists (Bianchi, Pike, and Ling 2014, 217). Konecnik and Gartner (2007) developed destination image and quality measurement scales by combining findings from in-depth interviews and previous research (Gallarza, Saura, and Garcia 2002; Mazanec 1994; Baker and Crompton 2000; Ekinci and Riley 2001; Murphy, Pritchard, and Smith 2000). These scales have been adopted and modified in later destination brand equity studies (e.g., Pike et al. 2010; Horng et al. 2012; Bianchi, Pike, and Ling 2014). However, there are only a few attributes employed by several studies simultaneously. Accommodation facilities is the most commonly utilized destination attribute employed for destination image and quality measurement. Fewer attributes comprise infrastructure, cleanliness, safety, history and culture, shopping, urban areas, dining, nightlife and entertainment, events, atmosphere, service personnel, communication, and language. While nature and scenery is the most commonly employed destination image attribute (Chen and Myagmarsuren 2010; Ferns and Walls 2012; Im et al. 2012; Konecnik and Gartner 2007), less frequent attributes include weather, activities, recreation opportunities, friendliness of locals, beaches, political stability, being featured in movies and on TV, religion, sightseeing, technology, water sports, and family vacation opportunities.
When it comes to the measurement of effects, a positive (inter-)relationship between attribute-based image and quality has been identified (Chen and Myagmarsuren 2010; Konecnik and Gartner 2007; Ferns and Walls 2012). However, other empirical results remain inconclusive. While a positive effect of brand awareness on the perceived quality of destination attributes is confirmed (Pike et al. 2010; Kladou and Kehagias 2014), the relationship is nonsignificant in Chen and Myagmarsuren (2010). To conclude, although literature has reached an agreement that destination-specific attributes should be applied when operationalizing destination brand performance and imagery, findings illustrate that attribute-based image and quality constructs greatly overlap on the measurement level. Therefore, following Ferns and Walls (2012), we propose that “destination brand experience,” manifested by attribute-based image and the quality of experienced destination attributes, can well constitute a single model construct.
Judgments and Feelings
Most previous studies include consumers’ judgments and emotional responses toward the destination brand. These representations, however, remain fragmented and mutually inclusive. For instance, by adopting measures of quality experience, brand quality is conceptualized through brand performance dimensions in terms of “the destination’s ability to meet tourists’ functional needs” (Boo, Busser, and Baloglu 2009, 221). Accordingly, destination performance is defined as “perceived utility that one derives from visiting a destination relative to the cost of doing so” (Evangelista and Dioko 2011, 318). Thus, brand performance scales include overall quality and performance superiority. Moreover, in Evangelista and Dioko (2011) “trust” represents the “judgments and feelings” block and includes measures, like trustworthiness, being caring and not taking advantage of consumers. Similarly, overall quality is a measure of destination brand equity in Garcia, Gómez, and Molina (2012), while trust (reliability) and believability (credibility) appear as the brand meaning construct (Berry 2000). Finally, Im et al. (2012), Kladou and Kehagias (2014), and Bianchi, Pike, and Ling (2014) consider brand associations, but lack an agreement on how to conceptualize the construct. Overall quality and destination attitude is combined as brand associations by Im et al. (2012). By contrast, brand associations, defined as image perception, signal brand personality and trust (Kladou and Kehagias 2014). Similarly, brand “uniqueness” and “popularity” represent brand associations and perceived quality (Kim et al. 2009), while some authors use the notion of brand associations interchangeably with destination brand image (Bianchi, Pike, and Ling 2014).
Moreover, destination brand value is defined as Zeithaml and Bitner’s (2000) price-based concept of value in terms of customers’ perceived balance between a product’s price and utility (Boo, Busser, and Baloglu 2009; Evangelista and Dioko 2011; Bianchi, Pike, and Ling 2014). Measurements include value for money, reasonable price, and being a bargain. Likewise, prior research confirms that perceived quality influences value for money (Boo, Busser, and Baloglu 2009). However, this relationship is confirmed for only one out of two samples. Moreover, it is shown that destination awareness has a positive effect on brand assets (Kladou and Kehagias 2014; Pike et al. 2010), although this hypothesis was originally rejected (Boo, Busser, and Baloglu 2009). Furthermore, brand presentation influences the perception of brand meaning (Garcia, Gómez, and Molina 2012). Likewise, brand associations turn out to influence perceived quality of destination attributes (Kladou and Kehagias 2014). However, this reverse relationship is tested as a post hoc hypothesis, and, thus, it is insufficiently justified from a theoretical viewpoint. Few studies examine the relationship between brand equity and tourist satisfaction. More precisely, it is confirmed that the perceived quality of destination attributes influences satisfaction, while the relationship between attribute-based image and satisfaction is found to be nonsignificant (Chen and Myagmarsuren 2010). Finally, inconsistent path relationships, satisfactory yet not perfect goodness-of-fit indices and a correlation between image and quality is reported by Boo, Busser, and Baloglu (2009). The authors suggest that tourists’ previous experience might overshadow brand image.
To conclude, the examination of model dimensions representing the judgments and feelings block reveals that tourism literature emphasizes the judgments component, specified as overall quality and credibility of the destination brand. However, benefits of using the brand are only partly represented, for example, by image dimensions and destination satisfaction. With the sole exception of Garcia, Gómez, and Molina (2012), literature entirely ignores emotional response dimensions (e.g., fun and excitement), although Keller (2008) identifies them as significant for the judgments and feelings block. Finally, literature suggests that in a (e.g., tourism) service context, satisfaction should be “conceptualized as an attitude-like judgement after a purchase or an interaction with a services provider” (de Chernatony, Harris, and Christodoulides 2004, 22). Following these suggestions, this study integrates destination-specific emotional brand value dimensions as part of the brand equity measurement in a destination context.
Destination Brand Resonance
Loyalty and attachment are the dimensions of brand resonance at the top of the brand equity pyramid (Keller 2009). Loyalty constitutes the core of the destination’s brand equity model representing the level of attachment a potential tourist has to a destination brand (Horng et al. 2012; Kladou and Kehagias 2014). Destination loyalty implies that potential tourists have a greater confidence in the destination brand compared to its competitors, which translates into customers’ willingness to pay a premium price (Bianchi, Pike, and Ling 2014). Thus, behavioral brand loyalty refers to tourists’ repeat visits to a destination and positive word of mouth referrals (Konecnik and Gartner 2007), while attitudinal brand loyalty is manifested by tourists’ intention to revisit and recommend the destination to others as well as by the “brand commitment” in terms of individual preference and disposition toward a destination brand (Gartner and Konecnik Ruzzier 2011).
While most studies specify attitudinal destination brand loyalty as an isolated construct, literature lacks consensus on measurement items and scales. The most commonly, although inconsistently, utilized measures of attitudinal destination brand loyalty comprise preference (destination as preferred vacation choice) and willingness to recommend (e.g., Boo, Busser, and Baloglu 2009; Kladou and Kehagias 2014; Garcia, Gómez, and Molina 2012). Fewer studies additionally consider the intention to revisit (Konecnik and Gartner 2007; Ferns and Walls 2012; Im et al. 2012). Less common measures include overall loyalty (Boo, Busser, and Baloglu 2009; Garcia, Gómez, and Molina 2012), enjoying the destination (Boo, Busser, and Baloglu 2009; Kladou and Kehagias 2014), readiness to pay a premium price (Im et al. 2012), confidence (Horng et al. 2012) and meeting the expectations (Kladou and Kehagias 2014). Identifying the drivers behind destination brand loyalty is a crucial task in destination brand equity research. Thus, unsurprisingly, most studies testing path relationships are considering brand resonance.
Nevertheless, findings remain contradictory and inconclusive. For instance, the relationship between destination awareness and loyalty is confirmed by Pike et al. (2010), while other authors reject this hypothesis (Im et al. 2012). Furthermore, a positive influence of destination awareness on revisit intention can be demonstrated (Ferns and Walls 2012; Horng et al. 2012), while another study, again, rejects this hypothesis (Im et al. 2012). Similarly, the influence of attribute-based image on loyalty can be confirmed (Im et al. 2012), while other scholars reject the hypothesis on this relationship (Chen and Myagmarsuren 2010). Likewise, while some studies approve the influence of perceived quality of destination attributes on loyalty (Pike et al. 2010; Kladou and Kehagias 2014), this hypothesis is rejected by others (Chen and Myagmarsuren 2010; Bianchi, Pike, and Ling 2014). Finally, attribute-based image and quality positively influence travel intentions (Horng et al. 2012; Ferns and Walls 2012). However, this relationship turns out to be nonsignificant in Im et al. (2012). Findings are more consistent for destination judgments and feelings influencing destination brand resonance: literature agrees that brand associations (Im et al. 2012; Kladou and Kehagias 2014), perceived quality (Boo, Busser, and Baloglu 2009), social and self-image (Boo, Busser, and Baloglu 2009; Pike et al. 2010), value for money (Boo, Busser, and Baloglu 2009; Bianchi, Pike, and Ling 2014), and satisfaction (Chen and Myagmarsuren 2010) are antecedents of destination brand loyalty.
In conclusion, the issue of valid measurement of the brand resonance construct is not yet fully resolved. As it is difficult to distinguish between attitudinal and behavioral brand loyalty, brand resonance overlaps with destination judgments and feelings on the level of both constructs and single measures. For instance, “benefits” in Konecnik and Gartner (2007) and Pike et al. (2010), as well as “enjoyment” in Boo, Busser, and Baloglu (2009), Horng et al. (2012), and Kladou and Kehagias (2014), semantically belong to the judgments and feelings brand building block. Hence, this study focuses on destination preference, willingness to recommend, and intention to return as the most commonly utilized dimensions of attitudinal destination brand loyalty. At the same time, we emphasize the need for continuing the theoretical discussion on the phenomenon of destination brand loyalty and its operationalization.
Hierarchy of CBBE Dimensions in a Destination Context
Table 2 summarizes the findings from previous destination studies that go beyond the sole task of measuring CBBE model dimensions but also examine path-relationships between brand equity dimensions. The table highlights tested relationships between the four blocks of Keller’s (2008, 2009) brand equity pyramid. The synthesis of prior studies’ results enables the identification of gaps on the level of both the measurement and the structural composition of existing destination CBBE models.
Summary of Findings in Previous Tourism Destination Brand Equity Studies.
Note: AST = brand assets; AW = awareness; PQatt = perceived quality of destination attributes; IMatt = attribute-based image; BA = brand associations; PB = presented brand; BM = brand meaning; EX = destination experience; IM = social image and self-image; V = value for money; LOY = loyalty; VI = intention to (re)visit; OBE = overall brand equity; SAT = satisfaction; EXatt = experience of destination attributes; PQ = perceived destination quality; WtS = willingness to spend money.
Interestingly, findings support the framework’s hierarchical structure following Keller’s (2009) brand equity pyramid. Particularly, relationships between directly adjacent model blocks are consistently confirmed empirically. Notably, when the blocks located in the center of the model are omitted, findings from hypothesis testing are contradictory and disconfirmed (e.g., relationships between destination brand awareness and overall destination brand judgment dimensions, destination brand awareness and destination loyalty, as well as the impact of both attribute-based image and quality on loyalty).
As discussed, the conceptualization of model building blocks by existing studies remains fragmented. Only a few hypotheses are tested and confirmed by two or more studies. More precisely, the relationships between destination awareness and destination brand resonance dimensions (i.e., loyalty and (re)visit intentions), attribute-based quality and destination loyalty, as well as the relationships between destination awareness and attribute-based quality have been tested by two studies, while the positive influence of consistency of tourists’ self-image with destination brand on destination brand loyalty is the only relationship tested and confirmed by three studies (Bianchi, Pike, and Ling 2014; Boo, Busser, and Baloglu 2009; Pike et al. 2010).
Finally, previously tested hypotheses summarized in Table 2 reveal that most of previous studies analyzed relationships between brand equity dimensions and destination brand loyalty (Hunter and Schmidt 1990). However, literature lacks consistency especially regarding the conceptual interpretation of attribute-based brand image, overall brand image, and quality constructs, resulting in conceptual overlaps and measurement gaps of brand equity constructs. As a result, the primary focus of this paper is to clarify the structural relationships within the inner core of the CBBE model.
Research Framework
To resolve the aforementioned conceptualization and operationalization issues of destination brand equity modeling, we propose the application of the value co-creation framework (Vargo and Lusch 2004). Accordingly, attribute-based image and quality dimensions are related to the customers’ perception of promised, experienced, and retained performance of destination resources, which, in turn, contribute to the customers’ value in use (Grönroos 2009). Previous studies (Konecnik and Gartner 2007; Boo, Busser, and Baloglu 2009; Pike et al. 2010) point at the difficulties of model conceptualization and measurement primarily explained by the complexity and multidimensionality of tourism destinations compared to goods and services. The complexity of destination experiences is the primary reason why measurement scales developed for consumer products and services cannot be directly applied in a tourism destination context (Pike 2009; Gartner 2009). Indeed, a tourism destination, viewed as an amalgam of various service products and experience opportunities, is an ideal illustration of the value network concept, which accentuates the co-production and exchange of service offerings and value co-creation from a customer’s perspective (Murphy, Pritchard, and Smith 2000; Vargo 2009; Lusch, Vargo, and Tanniru 2010). Thus, as destinations represent inherent value creation processes triggered, co-produced, experienced, and evaluated by customers, the application of the value network in a destination context is justified to identify interactions that impact customers’ brand experience (Grönroos 2006; Baron and Harris 2010).
Gnoth (2007) conceptualizes destination brands as the representation of the functional, emotional, and symbolic values of a destination, as well as the benefits that tourists are promised to receive as the result of their service consumption (ibid., 348). This is consistent with the service marketing view on value co-creation, which distinguishes between value in use and value in exchange (Vargo and Lusch 2004; Grönroos 2009). While value in exchange is embedded in the exchanged product, value in use is created when goods or services are used (Vargo and Lusch 2004). Thus, value for a customer is created as a result of the interaction between a firm and a customer by the total experience of relevant experiential elements, including the firm’s resources, such as physical objects (e.g., goods), information, interactions with employees, systems, infrastructures, as well as other customers (Grönroos 2008). In many instances, these elements cannot be directly controlled by a firm (Vargo and Lusch 2004). Rather, core values, like the cultural, social, and natural dimensions of destination resources, are utilized as inputs for service provision aimed at satisfying tourists’ needs. Accordingly, a destination is viewed as a promise to transform customers’ resources, while the inherent value concept is communicated through the brand that, in turn, is collectively perceived by homogeneous tourist segments (Ek et al. 2008).
More theoretically, the destination promise, as the inner part of the customer-based destination brand equity (CBDBE) model, includes customers’ evaluations of tangible, intangible, and human resources offered by the destination, the value in use as tourists’ benefits from destination visitation, and finally, the price-based value as the destination’s value in exchange. Thus, destination resources as destination-specific dimensions of complex tourism experiences (Palmer 2010) include destination products and services, intangible characteristics of the destination, and social interactions. Most importantly, resource availability is unique for every destination (Zabkar, Brencic, and Dmitrovic 2010). Similarly, the combination of desired and experienced resources is unique for every tourist in a particular visitation context (Moeller 2010). Against this theoretical background, we propose that destination resources, customers’ benefits, and value for money together comprise the perceived destination brand promise reflected by the inner core of the destination brand equity model pyramid (Figure 1).
Tourism destination brand equity pyramid.
Conceptual Model and Hypotheses
Within the CBDBE model framework, attribute-based image and quality represent tangible, intangible, and social resources of the tourism destination. While studies integrating attribute-based image and quality simultaneously report high correlations between the constructs, conceptualization and measurement of these constructs greatly overlap (Konecnik and Gartner 2007; Ferns and Walls 2012). We resolve this issue by combining attribute-based image and quality into one single dimension as proposed by Ferns and Walls (2012). Thus, customers’ perception of promised, experienced, and retained performance on the level of destination resources contributes to the formation of tourists’ benefits from destination visitation (Larsen 2007). As the perception of destination resources represents the performance and imagery building block of the CBDBE model, the model hierarchy stipulates the relationship between destination awareness and customer’s perception of destination resources. Following Pike et al. (2010), Chen and Myagmarsuren (2010), and Kladou and Kehagias (2014), an integrative hypothesis has been formulated (Figure 2):
The conceptual model and hypotheses to be tested.
Hypothesis 1: The stronger the destination awareness, the more positive customers’ perception of (a) tangible, (b) intangible, and (c) social destination resources.
The value in use represents tourists’ state of being as the result of visiting the destination. In general, customer value is created within a dynamic and hierarchical means–end process of utilizing product attributes to obtain desired experiences, thus achieving the customer’s consumption purposes (Woodruff 1997). Sheth, Newman, and Gross (1991) identify emotional, social, and epistemic value as the most relevant perceived value dimensions. Emotional value is the utility derived from feelings or affections generated by a product. Social value represents the enhancement of a social self-concept. Epistemic value reflects the capacity of a product “to arouse curiosity, provide novelty, or satisfy a desire for knowledge” (ibid., 162). Emotional experience, social recognition, novelty, and knowledge constitute the dimensions of modifying a customer’s state of being and, consequently, represent value in use for a customer. Similarly, Holbrook’s (2006) customer value typology includes hedonic value as an intrinsic self-oriented pleasurable experience of fun or the aesthetic enjoyment as well as the extrinsic other-oriented social value of status enhancement or the improvement of the self-esteem in the result of consumption. The value in use of a destination can, thus, be exemplified based on Crompton’s (1979) classification of tourists’ benefits from destination visitation in terms of satisfying internal sociopsychological needs. These benefits include push-motivation factors, such as escape from routine environments, exploration and evaluation of self, relaxation, social recognition, social interaction, novelty seeking, and knowledge (Crompton 1979). Interestingly, Klenosky (2002) applies a means-end approach to examine relationships between pull and push motivation factors of destination choice. Pull factors (e.g., historical and cultural attractions, natural resources, and activities) are considered as means to achieve benefits (ends), which correspond to travel pull motivations (e.g., fun and enjoyment, self-esteem, and excitement). Similarly, Komppula (2005) applies Woodruff’s (1997) customer value hierarchy to illustrate the link between the tourist product and customers’ “desired consequence experiences” (ibid., 9). However, literature only partly reflects the value in use as a desired experiential state of being achieved in the course of tourism consumption and the fulfilment of needs. This, in particular, concerns the social value construct represented by the “social image” and “self-image” dimensions as discussed in Boo, Busser, and Baloglu (2009), Pike et al. (2010), and Evangelista and Dioko (2011).
Thus, we consider value in use as the dimension of the “judgments and feelings” brand building block and integrate destination-specific visitation benefits, such as emotional (hedonic), social, and epistemic value (Sheth, Newman, and Gross 1991; Holbrook 2006). The relationship between destination resources and value in use has been confirmed by Pike et al. (2010) as the positive influence of the quality of destination attributes on tourists’ self-esteem and social recognition. However, on a broader scale, this relationship derives from the inherent means–end logic of destination resources transformed into desired customer benefits (Chi and Qu 2008; Yoon and Uysal 2005; Zabkar, Brencic, and Dmitrovic 2010): This relationship is hypothesized as follows:
Hypothesis 2: The more positive the customers’ perception of (a) tangible, (b) intangible, and (c) social destination resources, the more positive the customers’ perception of value in use.
Three previous studies isolated value for money as a separate brand equity dimension (Boo, Busser, and Baloglu 2009; Evangelista and Dioko 2011; Bianchi, Pike, and Ling 2014). The construct belongs to the judgments and feelings brand building block and is consistent with the functional (economic) value, which Sheth, Newman, and Gross (1991) and Holbrook (2006) identify as part of customers’ perceived value. Moreover, from the service marketing perspective (Vargo and Lusch 2004; Grönroos 2008), price-based value constitutes the value in exchange and considers customers’ own resources used as inputs in the service process. Customers’ resources, however, include not only money, but also time, efforts, and skills (Fuchs 2004; Chen and Tsai 2007; Moeller 2010). Although the relationship between customers’ perception of destination attributes and value for money has not yet been tested as part of the CBDBE model, Chen and Tsai (2007) empirically confirm that attribute-based trip quality has a strong and positive impact on perceived value in terms of money, time, and effort. Therefore, the following hypothesis is formulated:
Hypothesis 3: The more positive the customers’ perception of (a) tangible, (b) intangible, and (c) social destination resources, the more positive the customers’ perception of value for money.
The study at hand follows Konecnik and Gartner (2007), Pike et al. (2010), Chen and Myagmarsuren (2010), Im et al. (2012), and Bianchi, Pike, and Ling (2014) when specifying destination loyalty as an attitudinal concept. Thus, the intention to revisit and recommend the destination as well as the destination preference are included in the model. Like Boo, Busser, and Baloglu (2009), Kim et al. (2009), Pike et al. (2010), Chen and Myagmarsuren (2010), Im et al. (2012), Kladou and Kehagias (2014), and Bianchi, Pike, and Ling (2014), the following hypotheses, which reflect the relationships between the “judgments and feelings” dimensions and destination loyalty, are formulated:
Hypothesis 4: The more positive customers’ perception of value in use, the stronger the loyalty to a destination.
Hypothesis 5: The more positive customers’ perception of value for money, the stronger the loyalty to a destination.
Pilot Study Research Design
A pilot study was designed for international tourists with previous experience of the Swedish mountain destination Åre. Åre is the leading Swedish ski tourism destination that is actively expanding on international markets.
Previous studies focused primarily on top-of-mind aspects of awareness (e.g., Konecnik and Gartner 2007; Boo, Busser, and Baloglu 2009; Pike et al. 2010). However, Aaker (1996) points out that top-of-mind is difficult to measure when consumers already have direct product experience. Therefore, this study adopts metrics of brand knowledge and brand presence from Lehmann, Keller, and Farley (2008) and formulates eight awareness items as statements to be rated on a five-point Likert-type agreement scale ranging from 1 (strongly disagree) to 5 (strongly agree).
For tangible resources, a total of 36 items ranging from 1 = completely dissatisfied to 5 = completely satisfied is deduced from the literature on ski destinations (Hudson and Shephard 1998; Weiermair and Fuchs 1999; Fuchs 2002; Faullant, Matzler, and Füller 2008; Komppula and Laukkanen 2009). Six intangible destination resource items and four social destination resource items are similarly deduced from previous studies (Yoon and Uysal 2005; Chen and Tsai 2007; Konecnik and Gartner 2007; Chi and Qu 2008; del Bosque and Martin 2008; Faullant et al. 2008; Zabkar, Brencic, and Dmitrovic 2010) and are refined based on a content analysis of Åre-specific marketing communications and publications in media as well as customers’ narratives in social media blogs (Creswell 2009). The item rating ranges from 1 = strongly disagree to 5 = strongly agree.
Conceptualization of tourists’ value in use of destination visitation is limited to the emotional (hedonic) value of destination visitation, assuming that hedonic value is of primary importance for alpine ski tourism (Holbrook 2006). However, we acknowledge that the scope of value in use of destination visitation is broader and may include social value as well as other types of value dimensions (Sheth, Newman, and Gross 1991; Crompton 1979). The construct is operationalized by four emotional value items for ski destinations (Klenoski, Gengler, and Mulvey 1993). Value for money is operationalized by two items adopted from Boo, Busser, and Baloglu (2009) formulated as statements and rated on a five-point Likert-type agreement scale ranging from 1 (strongly disagree) to 5 (strongly agree). Finally, the study adopts the three most common measures of destination brand loyalty found in previous destination brand equity studies, comprising of willingness to recommend and to come back to the destination as well as destination preference as the measure of destination attachment (Konecnik and Gartner 2007; Boo, Busser, and Baloglu 2009). Loyalty items are rated on a 5-point Likert-type scale ranging from 1 = strongly disagree to 5 = strongly agree.
English, Swedish, and Russian questionnaires were prepared by native speakers, thus addressing the main target markets of the Swedish ski destination Åre. A pretest with 44 students allowed a split-half test to check for item reliability (Hair et al. 2010). Finally, a web survey was implemented to reach international guests after their visit to the destination. Target markets were examined using the number of overnight stays reported by the stakeholders SkiStar Åre and Holiday Club Åre, which represents approximately 96% of the international guest-base. Findings justified a proportional-stratified sampling strategy: e-mails were randomly selected from CRM databases of these stakeholders for each sample strata. As the goal was an accuracy of 95% at a significance level of 5%, target sample size was n = 384 (Creswell 2009).
In total, 5,668 web survey invitations were disseminated. Data were anonymously collected between April and May 2010. Final number of completed questionnaires is n=387 (response rate = 9%). The share of missing values was highest for items measuring tourists’ perception of tangible attributes. This can be explained by the service heterogeneity characteristics, implying that only core destination components are used by most respondents. Thus, items with more than 10% of missing values were removed, resulting in an exclusion of 25 of 36 tangible attribute-items. From a theoretical point of view, the removal of items illustrates a great degree of heterogeneity between consumers in terms of the combination of utilized destination resources as emphasized by Moeller (2010).
As suggested by Hair et al. (2010), missing-value imputation for resource variables was performed through means substitution. For the remaining variables, a listwise deletion of cases with missing values was applied. As a result, the number of usable cases is 248. Z-score examination revealed outliers (z > 3.29) being substituted with “the next highest score plus one” (Field 2005, 116). This type of score substitution affected 17 of 34 items. The number of adjusted scores varied from 1 to 4 per item and, therefore, did not exceed 2% per item.
Exploratory factor analysis (VariMax) examined factor structure, communalities, Kaiser–Meyer–Olkin (KMO) criteria and Cronbach’s alpha separately for those model constructs that could potentially have underlying dimensions, including tangible destination resources (two factors emerged, labeled Skiing and Service), intangible destination resources (one factor), social destination resources (one factor), and destination awareness (one factor). Three destination awareness items with factor loadings below 0.5 were dropped from the analysis, namely, “Åre has a good reputation,” “I have heard about Åre from friends and relatives,” and “I often find information about Åre on the internet” (Hair et al. 2010).
As discussed by Hair et al. (2010, 712), the removal of 20% of measurement items represents an acceptable level of measurement model adjustment and, thus, allows further model testing with remaining data. Therefore, in addition to model testing with data collected during the pilot study, the study has been replicated to collect new data and retest the model.
Pilot Study Results and Model Development
In a first methodological step, confirmatory factor analysis (CFA) was employed using the AMOS (v.21) software package to test the constitutive measurement constructs of the proposed CBDBE model. Unidimensionality of the specified measurement model was examined (Hair et al. 2010). All loadings (regression weights) were statistically different from zero and all t values higher than 1.96. However, overall model fit revealed that most fit statistics were slightly below the recommended thresholds (Brown 2006). Thus, the measurement model was slightly adjusted. Examination of standardized loadings (<0.50), standardized residuals (>2.58), and modification indices suggested the removal of three items (“Åre is a luxury winter resort,” “Åre is a famous site for international winter sports competitions,” and “Åre is known as one of the world’s top ski resorts”). Additionally, discriminant validity analysis suggested the need to increase the extracted variance for the “Skiing” factor, which was achieved by removing the items “Safety in the ski area” and “Transportation at the mountain area.” As a result, model fit improved substantially (Table 3). Although the goodness-of-fit index (GFI = 0.878) is still slightly below the recommended threshold, all indexes satisfy cut-off requirements (Steenkamp and Baumgartner 2000). Moreover, the model shows satisfactory measurement results (Table 4).
CBDBE Measurement Model: CFA Goodness-of-Fit Statistics.
Note: CBDBE = customer-based destination brand equity.
CBDBE Measurement Model: Test Statistics.
Note: CBDBE = customer-based destination brand equity; SMC = squared multiple correlation; AVE = average variance extracted.
Paths fixed to one to estimate parameters.
More precisely, composite reliability (CR) supports the model as all CR values rank above the threshold value of 0.7 (Hair et al. 2010). All estimates are significant (t values > 1.96) and show high values (standardized loadings > 0.50). Squared multiple correlation (SMC) demonstrates respectable portions while average variance extracted (AVE) amounting at values of 0.5 (or higher) indicates convergent validity (Hair et al. 2010; Nunkoo, Ramkissoon, and Gursoy 2013). Finally, results confirm convergent validity, as indicators of the latent constructs share high proportions of common variance. Overall, CFA results are satisfactory: convergent validity is confirmed, whereas discriminant validity is attested for most model dimensions (Table 5).
Discriminant Validity of the CBDBE Model Measurement Scale.
Note: The bold diagonal elements show average variance extracted values; off-diagonal elements show squared correlations between model constructs. CBDBE = customer-based destination brand equity.
As a next step, the measurement model is transformed into a structural model to test the hypothesized relationships between validated CBDBE model constructs (Reisinger and Turner 1999). A linear structural equation model (SEM) using maximum likelihood (ML) estimation is applied (Hair et al. 2010). GFI statistics for the path model, however, do not fully satisfy recommended thresholds (GFI = 0.773; RMSEA = 0.084 [lower limit (LL) 0.078, upper limit (UL) 0.091]; SRMR = 0.21; normed chi-square [χ2/df] = 2.76 [1002.94/363]; TLI = 0.83; CFI = 0.85; AGFI = 0.73). Furthermore, not all hypothesized paths are statistically significant. Particularly, relationships between awareness and intangible attributes, the influence of intangible attributes on both value in use and value for money perception, as well as the influence of social destination resources on value for money turned out to be nonsignificant.
However, examination of modification indices revealed that the model fit is substantially improved by allowing theoretically plausible correlations between the four destination resource dimensions. Thus, in the revised model (Figure 3) “Skiing” (SKI), “Service” (SER), “Intangible destination resources” (INT), and “Social destination resources” (SOC) constitute the subdimensions of the second-order construct “Destination resources” (DRES). As a result of this model revision, the GFI statistics reach a satisfactory level: GFI = 0.83; RMSEA = 0.065 (LL 0.058, UL 0.072); normed chi-square (χ2/df) = 2.04 (750.65/368); SRMR = 0.077; TLI = 0.90; CFI = 0.91; AGFI = 0.80.
Standardized path estimates for the revised CBDBE structural model.
Loadings pertaining to the four subdimensions of the second-order construct DRES are all statistically significant and vary from 0.675 for intangible destination resources to 0.812 for social destination resources. The AVE value for the DRES construct amounts at 0.59 (Hair et al. 2010). All proposed relationships between the model constructs are statistically significant (Table 6).
Structural Parameter Estimates for the Revised CBDBE Model.
To conclude, the hypothesized hierarchical structure of the proposed CBDBE model could be empirically confirmed. Thus, the test approach can be considered as plausible, reliable and valid (Hair et al. 2010). However, in order to retest the model, the survey instrument is improved before collection of new sample data. Particularly, customers’ perception of tangible, intangible, and social destination resources are consistently operationalized on the basis of similar measurement scales.
Replication Study Results
To retest the reliability and robustness of the proposed CBDBE model, new customer data were collected during July–August 2013. The survey instrument was slightly modified; thus, a satisfaction scale was employed to measure tourists’ satisfaction with intangible and social destination resources and value for money. To address the issue of missing values and to retest the model without missing value replacement, the guest-base was extended to both domestic and international visitors of the Swedish ski destination Åre in the winter season 2012/2013. In total, 23,243 e-mails from the CRM databases of four major accommodation providers, including Skistar Åre, Holiday Club Åre, Copperhill Mountain Lodge Åre, and Tott Hotell Åre, were disseminated. A reminder was sent out two weeks after the first invitation. While 3,013 respondents started the survey, resulting in a 13% response rate, 1,984 individuals completed the survey. Respondents who answered all the 29 measurement items of the CBDBE model made up the subsample for repeat model testing (n=752). The first effort to validate measurement constructs by CFA, again, produced fit statistics slightly below recommended thresholds (Brown 2006). Examination of standardized residuals (>2.58) revealed the need to remove the social resource item “Friendliness and professionalism of employees.” Additionally, results from discriminant validity analysis indicate the need to increase the extracted variance of the Service construct, which is achieved by removing the “Overall quality of accommodation” item with the lowest loading score. The performed adjustments resulted in a substantial improvement of the model fit (GFI = 0.896; RMSEA = 0.061 [LL 0.057, UL 0.065]; SRMR = 0.062; χ2/df = 3.781 [1119.302/296]; TLI = 0.93; CFI = 0.94; AGFI = 0.87). The normed chi-square statistic slightly above the threshold value (χ2/df = 3.781) may, however, be neglected because of the relatively large sample size (Hair et al. 2010).
Moreover, the measurement model shows satisfactory measurement results (Table 7). First, the values for CRs approve the model, and the values rank well above the recommended threshold amounting at 0.7. Estimated regression weights (factor loadings) are relatively high and significant. Particularly, all t values are above 1.96, varying from 14.177 to 48.278; all standardized loadings are greater than 0.50 (varying between 0.541 and 0.961), while most of the standardized loadings exceed 0.7. SMCs demonstrate respectable portions. Average variance extracted (AVE) ranks well above the recommended threshold value, amounting at 0.5. Convergent validity of construct measurement is confirmed, as indicators of latent constructs are sharing a relatively high proportion of common variance (Hair et al. 2010). Additionally, the standardized loadings for the DRES second-order construct are all statistically significant and vary from 0.70 to 0.91. SMC values vary from 0.49 to 0.82, construct reliability is at the level of 0.86, and the AVE value amounts at 0.62.
CBDBE Measurement Model: Replicated Test Statistics.
Paths fixed to one to estimate parameters.
Table 8 shows the result of discriminant validity evaluation that is fully confirmed for all proposed model constructs. Thus, the results of the CFA are satisfactory as both convergent and discriminant validity are confirmed (Hair et al. 2010). As the next step, the validated measurement model is transformed into a structural model (Figure 4).
Discriminant Validity of the CBDBE Model Measurement Scale (Replicated Study).
Note: the bold diagonal elements show AVE values; off-diagonal elements show squared correlations between model constructs.
Standardized path estimates for the revised CBDBE structural model (replicated study).
Goodness-of-fit statistics for the path model are all satisfactory (GFI = 0.874; RMSEA = 0.066 [LL 0.063, UL 0.070]; SRMR = 0.076; χ2/df = 4.291 [1351.587/315]; TLI = 0.92; CFI = 0.93; AGFI = 0.85). The AVE value for the DRES construct amounts at 0.60 (Hair et al. 2010). All hypothesized relationships between model constructs are statistically significant (Table 9). The hierarchical structure of the CBDBE model has been repeatedly confirmed, demonstrating high reliability and empirical robustness of the proposed destination brand equity modeling approach (Hair et al. 2010).
Structural Parameter Estimates for the Revised CBDBE Model (Replicated Study).
Discussion and Conclusion
This research contributes to the development of knowledge on transferring the concept of customer-based brand equity to a tourism destination context (Konecnik and Gartner 2007; Boo, Busser, and Baloglu 2009; Pike et al. 2010). The proposed CBDBE model was repeatedly tested for the leading Swedish ski destination Åre with data from international tourists visiting Åre (winter season 2009/2010) and a second sample consisting of domestic and international tourists (winter season 2012/2013). Results from a repeated test confirmed the hierarchical structure and demonstrated reliability and empirical robustness of the proposed CBDBE model. The explanation power of the CBDBE model is high and squared multiple correlations (SMC) for destination value in use and loyalty exceed the value of 0.50 for both tourist samples. Similarly, the chain of causal relationships between customers’ perception of destination resources, value in use, and destination loyalty is strong and significant across both samples.
Findings are in line with previous research (Konecnik and Gartner 2007; Boo, Busser, and Baloglu 2009; Pike et al. 2010) and confirm the multidimensional nature of the tourism destination brand equity model, which integrates the concepts of destination brand awareness, attribute-based perception of image and quality of tourism destinations, value for money, and destination loyalty as isolated CBDBE model constructs.
Examination of the hypothesized relational structure within the CBDBE model confirmed previous findings regarding relationships between destination awareness and tourists’ perception of tangible, intangible, and social destination resources (Pike et al. 2010; Chen and Myagmarsuren 2010; Kladou and Kehagias 2014). However, this relationship is consistently weak and its contribution toward explaining tourists’ perception of destination resources is only minor. Moreover, this study repeatedly confirms the significant, strong and positive relationship between tourists’ perception of destination resources and destination value in use. This finding is in line with prior studies’ results demonstrating the positive influence of attribute-based destination image and quality on tourists’ perception of desired destination benefits (Chi and Qu 2008; Chen and Tsai 2007; Klenosky 2002; Pike et al. 2010; Yoon and Uysal 2005; Zabkar, Brencic, and Dmitrovic 2010). Similarly, the relationship between customers’ perception of destination resources and value for money is significant, strong and in line with the traditional conceptualization of consumer value, defined as the interplay between consumers’ benefits and sacrifices (Zeithaml 1988).
The confirmation of the hypothesis that destination value in use is a direct antecedent of destination loyalty is, indeed, an important finding that has not been previously discussed in the literature. Nevertheless, the result is in line with studies demonstrating that overall judgments of destination performance and the consistency of destination image with the tourist’s own image positively influence destination brand loyalty (Boo, Busser, and Baloglu 2009; Im et al. 2012; Kladou and Kehagias 2014; Pike et al. 2010).
Finally, the study confirms the relationship between value for money and destination loyalty (Chen and Tsai 2007). However, the relationship is comparatively weak, thereby indicating that under certain circumstances, the evaluation of sacrifice is only a minor factor in the process of destination loyalty formation.
Theoretical Implications
This study corroborates the assumption that the integration of the value cocreation perspective into the destination brand equity framework provides an adequate extension to better understand the relationship-building process between tourists and destination brands by taking into consideration the complex and multidimensional nature of destinations as well as the heterogeneous consumption patterns of tourist segments (Moeller 2010). As the main theoretical contribution of this study, the inner core of the CBDBE model has been conceptualized as the “perceived destination promise” depicting customers’ evaluation of the service process comprising the resources offered by the destination and the transformation of these resources into customers’ value in use (Vargo and Lusch 2008). Hence, this study introduced value in use as a new isolated CBDBE dimension.
This study emphasizes the need to understand the destination-specific and customer (i.e., segment)–specific benefits of destination visitation by considering the unique, experiential, and contextually dependent nature of value in use (Vargo and Lusch 2008). Most importantly, the findings support the co-creation logic behind the destination value promise to provide destination resources and to transform them into emotional values for tourists (Moeller 2010; Sheth, Newman, and Gross 1991). Therefore, findings also corroborate the conceptual distinction between value in use and value in exchange (Vargo and Lusch 2004, 2008).
Moreover, study findings bring up the discussion about the role destination awareness plays in the brand equity formation process, particularly in situations where tourists have already visited the destination (Milman and Pizam 1995). As Gartner and Konecnik Ruzzier (2011) reveal, the awareness dimension is more important for the renewal market compared with the repeat market. Therefore, the focus on customers who had already visited the destination clarifies the rather low explanation power of the awareness construct in our study.
Similarly, the significant but weak relationship between value for money and destination loyalty is in line with the concept of the zone of tolerance (Zeithaml, Berry, and Parasuraman 1996). This implies the existence of critical levels of sacrifices that may influence tourists’ behavior in case of a negative or positive service perception.
This study solely integrates monetary sacrifices (value for money). However, as emphasized by Fuchs (2004) and Moeller (2010), there exist additional types of tourists’ sacrifices, such as time required for traveling to the destination and physical efforts, which should be integrated in future CBDBE models following the logic of value co-creation as highlighted in this study.
To conclude, although the presented study empirically confirms the overall hierarchical structure of the proposed CBDBE model, the inner composition of the core model dimension “perceived destination promise” and its measurement remains a challenging task for future research, as it requires a better understanding of destination-specific consumption patterns across various tourism segments. Therefore, further empirical examination is required to validate the complex nature of CBDBE constructs as well as theoretically grounded relationships between these constructs.
Managerial Implications
The proposed CBDBE model rests upon a resource-based view of marketing strategy (Fuchs 2004; Palmer 2010; Zabkar, Brencic, and Dmitrovic 2010; Moeller 2010). This implies that for the most effective destination management, knowledge on the co-creative nature of unique destination experiences made by various customer segments is of utmost importance (Ek et al. 2008; Moeller 2010). By tracking awareness, tourists’ perceptions of tangible, intangible, and social destination resources for various customer segments, value in use of destination stay, value for money, and attitude-based loyalty, the brand equity model can be successfully used as a tool for brand monitoring, diagnostics, and the implementation of effective brand development strategies.
As a managerial tool, the brand equity model proposed and validated in this article clearly separates between value in use and value for money as drivers behind customer loyalty. This study finds that value in use affects loyalty to a larger extent than value for money. Managers cannot directly control value in use and value for money, which represent the customer’s perception of the benefits and sacrifices of a destination stay. However, the study exemplifies the complexity of destination consumption by tourists and shows the transformation process of tangible, intangible, and social resources into value in use and value for money, which now can be better understood and controlled. It enables destination managers to effectively implement brand development strategies by formulating segment-specific value propositions, which include respective destination resources relevant for customers’ expected value outcomes of a destination stay (Vargo and Lusch 2008). By doing so, managers can effectively build customer loyalty. For instance, for winter tourists of the Swedish mountain destination Åre, skiing, service quality, and intangible destination resources, such as family-friendliness, tidiness, and safety and interaction with other tourists, serve as the main resource inputs to the generation of emotional value for a destination stay. The study also showed the importance of key emotional value dimensions, such as fun, thrill, and variety. Thus, the amplifying relationship between resources and value in use will be communicated through the destination brand.
Managerial relevance of the proposed customer-based brand equity goes beyond brand communication development, as it also provides opportunities for discovering promising innovation potentials. Insights obtained by applying the CBDBE model in an empirical context translate into a valuable source of customer-based knowledge and, therefore, represent an important element of organizational learning and innovation in tourism destinations (Fuchs, Höpken, and Lexhagen 2014).
The proposed CBDBE model enables destination managers to measure customers’ brand perceptions on different stages of the brand value co-creation process and, ultimately, the measurement of the value of the destination brand. In particular, the model integrates customers’ evaluation of various brand messages associated with the destination brand. However, beyond brand messages controlled by the destination management (e.g., promotion campaigns, online and offline destination information provided by the destination management organization, tourism firms operating at the destination, as well as travel agencies), there are uncontrolled and unplanned brand messages, such as information in various media channels (TV, magazines and newspapers), social media (e.g., online communities and customers’ review websites, such as TripAdvisor), and word of mouth from family members, friends, and acquaintances.
Furthermore, destination managers and marketers can evaluate the brand’s ability to promise value to customers and to facilitate this value by guiding tourists on how to assemble (configure), use, and interpret destination resources during their destination stay. Hence, the model provides managers with a tool to evaluate the individual contribution of destination stakeholders (e.g., hotels, restaurants, and activity providers) in creating the total destination experience of tourists’ visitation.
The proposed CBDBE model enables the evaluation of the destination brand’s ability to encourage existing and potential customers to establish and maintain stable and mutually beneficial relationships with the destination brand and to identify the nature, strength, and stability of these relationships. However, a current brand equity evaluation reflects both the past and the future of the brand and is, thus, only the first step in the long-term process of (destination) brand value creation (Keller and Lehmann 2009). Hence, a longitudinal measurement of destination brand performance should be considered in a managerial context.
Limitations and Future Research
For the study at hand, the following limitations were identified. Notably, alternative aspects of customers’ benefits, such as social value, remained outside the model. Another limitation arises from testing the model only for actual visitors. Moreover, operationalization of destination brand awareness needs improvement, as there is a need to properly conceptualize the construct of destination awareness relevant to repeat, new, and potential customers, respectively. Although not yet intensively discussed in the literature (Konecnik and Gartner 2007), but supported by the findings of this study, the CBDBE dimension “awareness” can be assumed to be relatively more important for a destination at the national level (i.e., country’s tourism brand). By contrast, for local or regional destination brands, functional characteristics become more critical.
Analysis of discriminant validity suggests the need to further strengthen the destination loyalty construct operationalization. For future research, thus, we propose to further develop the theoretical conceptualization of destination brand loyalty as the endogenous CBDBE model construct. In particular, the construct should combine items reflecting both the degree of cognitive and affective attachment to the brand, future purchase intentions, and the extent of using the brand when communicating to other customers, searching for information and responding to promotion activities (Back and Parks 2003; Oliver 1999; Keller 2008).
Further limitations refer to the issues of study design and data collection and, specifically, a relatively high number of missing values. The high share of missing values, however, is not merely a measurement problem but rather illustrates the complexity of the consumption process across different tourism segments. Interestingly, only few resources are commonly utilized and, thus, experienced by customers. This observation is in line with the nature of both value in use (Vargo and Lusch 2004; Grönroos 2008) and the service co-creation process (Moeller 2010). Nevertheless, additional exploration of survey data is necessary to identify valuable customer segments based on consumption patterns during destination stay (Park and Almeida Santos 2016).
To increase the generalizability of the findings for (mountain) destinations, we propose to retest the model for different seasonal products and validate the model for different markets (a priori segments) in terms of country of origin, age groups, and travel group composition as well as for customer segments based on homogeneous destination activity patterns (a posteriori segments). Furthermore, we recommend to test the CBDBE model for other destinations, including destinations at higher geographical aggregate levels (e.g., provinces or countries).
Future research should also consider the time dimension in CBDBE modeling, as the hierarchy of the CBDBE model dimensions inherently reflects stages of relationship development between tourists and destination brands (Keller 2009; Park and Almeida Santos 2016). Finally, ethical aspects of brand relationship building were left beyond the scope of this study. However, ethical aspects are embedded within the value co-creation paradigm (Vargo and Lusch 2008). As discussed by Williams and Aitken (2011), value cocreation implies mutual dependency and reciprocal exchange; thus, it is the result of differences in goals and desires of economic actors. Goals and desires vary because actors have different access to resources and different values and judgments about what is “good” and “bad.” In contemporary digital societies characterized by a heavy use of social media, failure to make ethically sound decisions spread globally in near real time and have immediate impact on brand value. Thus, global connectedness implies that target audiences for marketing communications have expanded far beyond the traditional set of potential customers. Indeed, everyone has the power to amplify or weaken the value of a (destination) brand in accordance to the coherence of brand-related messages.
Footnotes
Acknowledgements
We would like to thank the members of the CBIT and “Knowledge destination” project teams in Åre and, in particular, Åre Destination AB, Skistar AB Åre, Holiday Club Åre, Copperhill Mountain Lodge Åre, and Tott Hotel. We would like to especially acknowledge Niclas Sjögren Berg and Anna Wersén (Skistar AB Åre), Lars-Börje Eriksson (Åre Destination AB), Hans Ericson (Holiday Club Åre), Pernilla Gravenfors (Copperhill Mountain Lodge), Peter Nilsson (Tott Hotel), Elisabeth Hallbäck (Skistar AB Åre), Helena Lindahl (Åre Destination AB), and Ulrika Eriksson (Copperhill Mountain Lodge) for their excellent cooperation, help with data collection and essential feedback during the long hours of project meetings.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work reported in this study was partly financed by the CBIT research project (EU Structural Fund objective 2 project no. 39736). Furthermore, the research work continued in close collaboration with the project “Engineering the Knowledge Destination through Customer-based Competence Development” (no. 20100260; Stockholm, Sweden) financed by the Knowledge Foundation (KK-stiftelsen).