The Effect of Message Consistency and Destination-Positioning Brand Strategy Type on Consumer-Based Destination Brand Equity

Abstract

Today, communication is a key factor of destination competitiveness. The aim of the present study is to examine the effect of message consistency between different online communication tools on the formation of consumer-based destination brand equity (CBDBE), within two distinct brand positioning strategies (single-destination brand vs. multiple-destination brands). An experimental design is applied to manipulate message consistency (high vs. low) and the type of brand positioning strategy implemented by the destination (single vs. multiple brands). The results demonstrate that when the messages received by the tourist are highly consistent across different channels, branding strategy type exerts no differential effect on CBDBE. By contrast, when the messages present low consistency, a single destination branding strategy generates higher CBDBE than a multiple destination branding strategy. The study makes an original contribution to the literature, showing the interaction between destination branding strategy type and degree of consistency in the messages received by the tourist.

Keywords

message consistency integrated marketing communications destination branding strategy consumer-based destination brand equity destination positioning destination competitiveness

Introduction

Heavy competition between tourist destinations demands that those organizations charged with promoting destinations focus on those factors that create competitive advantage (Pike and Page 2014). One of the principal resources that destinations can employ to create a sustainable competitive advantage is a strong brand. Although brand equity was initially approached from a marketing-based perspective, Keller (1993) defines brand equity from the perspective of the individual consumer and provides a conceptual framework of what consumers know about brands and what such knowledge implies for marketing strategies. Customer-based brand equity (CBBE) is defined as the differential effect of brand knowledge on consumer response to the marketing of the brand. Conceptualizing brand equity from this perspective is useful because it suggests both specific guidelines for marketing strategies and also tactics and areas where research can be useful in assisting managerial decision-making. The concept of customer-based brand equity (CBBE) (Aaker 1991; Keller 1993) offers destination marketers a performance instrument with which to evaluate and measure customer perceptions of a destination brand (Pike and Bianchi 2013).

Communication is also unquestionably a key feature in the quest for competitiveness among today’s tourism firms and destinations and, therefore, in the development of strong destination brands. In this respect, an integrated marketing communication (IMC) strategy is especially relevant for those services that have few physical components with which to differentiate themselves from the competition (Elliott and Boshoff 2008), as is the case with tourism. An IMC strategy can help ensure that all external messages are well coordinated and consistent with the desired positioning of the brand. In the academic literature, message consistency is considered the foundational level in the process of achieving the aim of integrated communications (Schultz and Schultz 1998). It is defined as the degree of coherence achieved across all the messages the consumer receives via different communication tools and media (Caywood, Schultz, and Wang 1991). Duncan and Moriarty (1998) highlighted the importance of ensuring that all messages conveyed by a firm are strategically consistent and thus deliver positive results, in terms of business performance and, ultimately, brand equity. On this point, various authors propose that message consistency across communication channels is a precondition for brand equity to be generated (Delgado-Ballester, Navarro, and Sicilia 2012; Šerić, Gil-Saura, and Ruiz Molina 2014; Šerić 2017). As noted by Šerić (2017) and Madhavaram, Badrinarayanan and McDonald (2005), the benefits of an effective message-consistency strategy will translate into a positive effect on some of the component dimensions of brand equity. To date, the majority of studies on this question have focused on some of the dimensions of brand equity, but not on overall brand equity measured in holistic terms. Furthermore, many of the published studies have taken an organizational approach, while there is very little literature that has measured message consistency (and its positive effects on brand equity) from a consumer perspective (Šerić 2017).

Together with a suitable integrated communication strategy based on message consistency, the right positioning strategy that will deliver the greatest brand equity is essential; indeed, positioning can provide a source of competitive advantage for any organization (Hooley, Saunders, and Piercy 2004; Porter 1980). There is considerable literature dealing with the relevance of positioning for tourist destinations, some of which study their image (Gallarza, Gil, and Garcı́a 2002; Gartner 1989) and some of which provide an empirical comparison of destination positioning (Botha, Crompton, and Kim 1999; Chen and Uysal 2002; Gartner 1989; Melián-González and García-Falcón 2003; Uysal, Chen, and Williams 2000). These studies identify several attributes related to tourist preferences, destination characteristics, and the benefits that tourists seek from destinations. They find that a destination’s location and attributes can help shape its status relative to other destinations (Seongseop Kim, Chun, and Petrick 2005).

Other studies endeavor to discern possible typologies of positioning (Blankson and Kalafakis 2004) and to identify the attributes that should be employed in that positioning (Nickerson and Moisey 1999). There are also studies addressing the very concept of destination positioning (Grabler 1997; Uysal, Chen, and Williams 2000) and the range of decisions that tourists make at a destination (Botha, Crompton, and Kim 1999; Crompton 1992; Pike 2006, 2012; Woodside and Sherrell 1977) as indicators of competitiveness, alongside destination appeal (Pike 2006). Other papers deal with the effectiveness of positioning and its impact on the firm (Fisher 1991; McAlexander, Becker, and Kaldenberg 1993) and on the consumer (Chen and Uysal 2002; Mayo and Jarvis 1981; Mykletun, Crotts, and Mykletun 2001). However, a number of topics related to destination positioning remain under-investigated (Pike 2006, 2012). Among these is the issue of how to differentiate destinations that operate at the same competitive level and offer the same features (Pike 2012). The present study aims to examine how different branding strategies may generate different consumer perceptions of a tourist destination. There is growing territorial competition at all levels—country, region, and city (Anholt 2007), leading territories to have to position themselves competitively and favorably in the minds of potential decision makers (Peralba 2009). In competitive positioning strategies of this kind, the functional attributes of the offer (such as price or quality) play an extremely limited role in achieving this much-needed differentiation (Villafañe 2005). Price competition offers no sustainable advantages, while quality has little bearing on appeal, as it is largely taken as a given (Peralba 2009). Hence, it is the more intangible factors that prove essential in the creation of value (Daum 2003), to build perceptions that evoke certain benefits, qualities, and emotions around the territory in question and its offer (López and Benlloch 2005). In this regard, the destination brand is a fundamental intangible in a territory’s promise of value (Paz 2005). When managing their brands, destinations should consider which of two primary options is likely to generate greater brand equity for potential tourists: (1) to build a single brand for the entire country (a single-destination branding strategy) or (2) build different brands, positioning each territory of the country a destination in its own right (a multiple-destination branding strategy).

To address the aforementioned gaps in the literature, the present research contributes to the study of tourist destinations by examining the role of (a) message consistency across different communication tools and (b) the particular brand-positioning strategy adopted by a destination country (single-destination branding vs. multiple-destination branding) on the formation of consumer-based destination brand equity (CBDBE). In other words, message consistency is contrasted along with, on the one hand, a branding strategy for a whole country as one single destination and, on the other, a branding strategy for a country based on different regions having their own individual brands.

An experimental design is used, manipulating (a) message consistency (high vs. low) between two different online communication tools (YouTube promotional video and WordPress blog) and (b) the destination’s brand positioning strategy (single-destination brand positioning vs. multiple-destination brand positioning).

The results of the present study are particularly valuable in contexts in which, as noted by Tasci (2011), destination branding is characterized by the coexistence of brands at different levels (local, regional, national, or supranational), which are being promoted via both controlled and uncontrolled sources (Banyai and Glover 2012; Xu and Pratt 2018), where messages about the destination are not always consistent. Analyzing the consequences of this reality in CBDBE terms will enable destination managers to assess the suitability of alternative strategies (single-brand; management of recommendations on the Internet).

Literature Review

IMC and Message Consistency

Since the late 1980s–early 1990s, there has been growing interest among scholars and professionals in the IMC concept (Taylor 2010; Kitchen 2017). Recent literature review studies affirm that academic research on this topic continues to flourish (Kliatchko 2008; Muñoz-Leiva, Porcu, and Del Barrio-García 2015; Šerić 2018; Schultz, Kim, and Kang 2014). Yet despite the extensive scientific literature on IMC, the debate over its definition remains open ended (Porcu, Del Barrio-García, and Kitchen 2017). In the classical vision of IMC, it can be defined as the message consistency communicated via different tools and media (Caywood, Schultz, and Wang 1991; Duncan and Everett 1993). Message consistency, accepted as the most fundamental level of communications integration, is allied to achieving strategic coherence between the messages conveyed via different tools and media, with the aim of securing clear brand positioning (one sight, one sound) (Caywood, Schultz, and Wang 1991). Schultz and Schultz (1998) consider the consistency of the message to be the first step toward integration.

Therefore, while the literature has examined consistency from many different perspectives and in numerous fields, the specific type of consistency with which we deal in the present study is the degree of message consistency across different communication tools and media. The principle of congruence/consistency and its effects on attitudinal change was proposed several decades ago by Osgood and Tannenbaum (1955). These authors asserted that incongruent information generates cognitive dissonance, and that congruent information is preferable for generating positive attitudinal change. In short, information is deemed to be more congruent, the greater the range of information sources that convey the same message. Studies in the marketing field have also addressed the topic of congruence from other perspectives. For instance, Chao (2001) and Josiassen, Lukas, and Whitwell (2008) found that product origin consistency has an effect on the manner in which consumers evaluate products.

In the marketing communications realm, message consistency is referred to in a number of ways by the IMC academic literature, with terms including one voice (Nowak and Phelps 1994; Phelps and Johnson 1996; Porcu, Del Barrio-García, and Kitchen 2012); common communication message (Low 2000); unified communications for consistent message (D. H. Lee and Park 2007); strategic consistency (Duncan and Moriarty 1997); tactical coordination (Schultz and Schultz 1998); communication mix integration (Pickton 2004); and message consistency itself (Moriarty and Schultz 2012; Porcu, Del Barrio-García, and Kitchen 2017).

As the range of communication channels expands, marketing managers are faced with the challenge of how to effectively integrate and coordinate all of the messages that are being transmitted (Schultz and Patti 2009), to ensure that the market hears one single voice. Ewing (2009) and Schultz, Kim, and Kang (2014) contend that greater efforts are required in the IMC research field to describe and explain the communication integration processes not only at organizational level (on which most of the extant literature focuses) but also at the consumer level. Both levels of analysis are important to understand how IMC functions and the benefits it presents for firms and consumers (Porcu, Del Barrio-García, and Kitchen 2017).

Most of the literature to date in this field has taken an organizational perspective by attempting to examine the main benefits of an IMC strategy based on message consistency in terms of business performance (Porcu, Del Barrio-García, and Kitchen 2012, 2017). Relevant examples include the work of Duncan and Moriarty (1998), Low (2000), Naik and Raman (2003), or Luxton, Reid, and Mavondo (2017). By contrast, there are much fewer studies examining this issue from the consumer perspective. Those that do, seek to analyze the extent to which perceptions of message consistency positively affect consumer response (Navarro-Bailón et al. 2009; Navarro-Bailón 2012). Just how consumers assimilate these messages from varying sources, in line with the IMC strategy behind the brand, is yet to be agreed among scholars (Phelan, Chen, and Haney 2013).

Scholarly research on tourism has also given rise to this dual analytical perspective, although in this case the number of studies is much lower. The majority of these studies have mainly focused on tourism service firms (Elliott and Boshoff 2008) and on hospitality (Šerić and Gil-Saura 2012; Šerić, Gil-Saura, and Ruiz Molina 2014; Šerić, Gil-Saura, and Ozretić-Došen 2015; Šerić 2017). To our knowledge, no previous study has centered on tourist destinations. Some of the extant works have taken the tourist perspective, by examining the extent to which tourist perceptions of message consistency determines brand loyalty (Šerić and Gil-Saura 2011; Šerić, Gil-Saura, and Ruiz Molina 2014), brand image and quality (Šerić, Gil-Saura, and Ruiz Molina 2014), tourist satisfaction (Šerić, Gil-Saura, and Ozretić-Došen 2015), and brand equity (Šerić 2017).

The present study responds to the call made by Phelan, Chen, and Haney (2013) for greater debate on how tourists respond to a destination strategy based on message consistency. Within this approach, our work is based on an experimental design that enables us to manipulate the level of message consistency.

The Impact of Message Consistency on CBDBE

The essential goal of all destination marketing organizations is sustained destination competitiveness, and to attain this requires the cultivation of resources that can create competitive advantage (Pike and Page 2014; Zehrer, Smeral, and Hallmann 2017). One of the most important resources is that of brand-building for the destination. The branding literature proposes that the CBBE model developed by Aaker (1991, 1996) and Keller (1993, 2003) offers destination marketers a performance instrument with which to evaluate and measure customer perceptions of a destination brand (Pike and Bianchi 2013). Most studies that have approached CBDBE for a tourist destination have identified the following dimensions: (a) brand image; (b) brand quality; (c) brand awareness; and (d) brand loyalty; and (in some studies) perceived value (Bianchi, Pike, and Lings 2014; Boo, Busser, and Baloglu 2009; Pike and Bianchi 2013). However, a number of studies take a more global perspective, approaching brand equity as an overall measure (OBE). The OBE scale was developed by Yoo, Donthu, and Lee (2000), primarily to evaluate the convergent validity of the multidimensional BE scale—including brand awareness, perceived quality, brand associations, and brand loyalty. Yoo and Donthu’s (2001) multidimensional BE and OBE scales were assessed by Washburn and Plank (2002) to examine their robustness. The results showed consistent correlation between the scales. Frías-Jamilena, Polo-Peña, and Rodríguez Molina (2017) adapted these scales for Spain, and Im et al. (2012) for Korea as a tourist destination. In the work of Šerić (2017), the OBE scale was adopted for the hotel sector in Croatia. The present study adopts this more holistic approach. As noted earlier, marketing communication is unquestionably a key factor in the development of strong destination brands. Keller (2003) outlined the importance of marketing communication in the formation of brand equity, mainly via the brand awareness and brand image dimensions. The shared view in the marketing literature appears to be that strategic message consistency across all communication channels is an essential precondition for the creation of CBBE (Delgado-Ballester, Navarro, and Sicilia 2012), as it makes a positive impact on the various dimensions of the concept (Šerić and Gil-Saura 2012; Šerić 2017). As noted by Keller (2009), a well-implemented integrated communications strategy can encourage CBBE by facilitating a strong connection between customers and the brand. Similarly, Madhavaram, Badrinarayanan, and McDonald (2005) posited that achieving synergies through the implementation of strategies based on image consistency would exert a positive effect on the “awareness” and “image” dimensions of brand equity. Anantachart (2004) proposed that IMC based on the systematic consistency of messages and media can influence CBBE by stimulating positive evaluations and attitudes among consumers. In short, given that the concept of CBBE is closely related to the brand associations held in the mind of the consumer, a message-consistency strategy will have a positive impact on brand equity, in two regards (Anantachart 2004). First, this strategy will exert an immediate effect on the consumer’s recall of the association between message and brand. Second, message consistency will create a beneficial effect in terms of brand attitudes.

More specifically, in the hospitality field, Šerić and Gil-Saura (2012) and Šerić, Gil-Saura, and Ruiz Molina (2014) identified a significant relationship between perceived message consistency—according to tourist hotel guests—and some of the dimensions of brand equity, hotel brand image, perceived quality, and loyalty. Similarly, Šerić, Gil-Saura, and Ozretić-Došen (2015) found that tourists’ perceptions of message consistency had a significant influence on their satisfaction. More recently, Šerić (2017) found there to be a significant relationship between message consistency and, on the one hand, brand consistency (as perceived by tourists) and, on the other hand, brand equity.

In light of the findings of the literature review, the following hypothesis is proposed:

Hypothesis 1: For a tourist destination, a communication strategy based on message consistency will generate significantly higher CBDBE than one that is not based on message consistency.

The Effect of Destination-Positioning Brand-Strategy Type on CBDBE

The most comprehensive definition of destination branding to date is that proposed by Blain, Levy, and Ritchie (2005), which embraces both the offer- and the demand-side. The authors describe the concept as “the set of marketing activities that (1) support the creation of a name, symbol, logo, word mark, or other graphic that readily identifies and differentiates a destination; that (2) consistently convey the expectation of a memorable travel experience that is uniquely associated with the destination; that (3) serve to consolidate and reinforce the emotional connection between the visitor and the destination; and that (4) reduce consumer search costs and perceived risk. Collectively, these activities serve to create a destination image that positively influences consumer destination choice” (Blain, Levy, and Ritchie 2005; Pike et al. 2010).

Destinations must therefore select the right combination of brand components to attract tourists by helping them to make their decision to visit—and later, revisit. The process begins in the tourist’s country of origin and is reinforced on arrival at the destination and during their stay; subsequently, it is managed during their departure and in the postvisit phase. Both the brand image and the tourist experience in itself should trigger emotions associated with the destination (Balakrishnan 2009).

There is only limited literature addressing destination branding strategies (Pike et al. 2010). Among the exceptions, Balakrishnan (2009) develops a framework for this concept. Her study goes beyond the conventional brand elements of design, by integrating the brand at the strategic level. Other studies on the alternative strategies for managing the portfolio of brands for a territory (Dooley and Bowie 2005) or destination (García, Gómez, and Molina 2013; Serra 2002; Solá 2007) have a more theoretical focus or deal with case studies. For example, Dooley and Bowie (2005) classify management strategies for territory brands into four groups, according to the extent of strength/weakness of the main brand relative to the sub-brands, with a particular focus on the case of South Africa. The work of Solá (2007) is based on a more specialized classification in the tourism realm by Serra (2002), which distinguishes between types of destination brand management strategies: (1) single-destination brand; (2) umbrella-destination brand; and (3) multiple-destination brands. Solá (2007) consider each of these strategies to present advantages and disadvantages. According to this study, a single-destination brand strategy may face difficulties when attempting to secure positioning among visitors, whereas a multiple-destination brand strategy facilitates visitor segmentation and can better address the particular requirements of each niche, this being a source of strength (Dooley and Bowie 2005; Serra 2002; Solá 2007). Single-destination and umbrella-destination branding strategies may be suitable or not in terms of positioning brands as the preferred choice in the minds of visitors, depending on the homogeneity of the tourism products and the degree of coordination between the core brand and sub-brands. In a similar vein, García, Gómez, and Molina (2013) conducted an empirical study to evaluate the positioning of regional destination brands using different management strategies (single-territory brand, single-destination brand, umbrella-destination brand, and multiple-destination brands), finding that the most successful approach was the single-destination brand strategy.

A strong, unique image forms the essence of destination positioning, thanks to its capacity to differentiate the destination from alternatives and embed itself in the mind of consumers, who often simplify the information they receive (Botha, Crompton, and Kim 1999; Crompton 1992; Fan 2006; Mihalic 2000; Mykletun, Crotts, and Mykletun 2001; Uysal, Chen, and Williams 2000). A destination seeks to create an authentic visual identity that should honor the intangible concepts of the social identity, the integrity, and the authenticity that have evolved over time (Gertner 1996). It is advantageous for destinations to create a brand that reflects the distinctive characteristics of the place, in terms of implementing coherent strategies with which to manage their resources, reputation, and image (Pike 2004) and to create an umbrella of trust and a guarantee of quality (Anholt 2003, 2004). But it is essential that destinations understand which brand associations have an advantage over competitors, by identifying the aspects that make them distinct or unique. Associations between the brand and points of difference help consumers evaluate the brand positively and form a bond with it (Keller 2008). Indeed, the key to brand-building is to ensure that consumers perceive a difference between brands in a given product category—which corresponds to brand positioning—as those brands that consumers perceive to be uniquely distinctive are difficult for others to substitute.

Although the literature on destination branding strategy is limited, and the majority of the extant literature is conceptual in nature, there does seem to be consensus among scholars regarding the importance of achieving one unique, overall country image as a differentiation strategy and the fact that this unique image can help the consumer to make the decision to visit the destination country and can even contribute to loyalty-generation (Balakrishnan 2009).

We take a “single-brand strategy” to refer to that which employs the same brand for an entire country as a tourist destination; and a “multiple-brand strategy” is that which uses various different brands to represent the distinct territorial areas of a given country (i.e., within one country, several tourist destinations are differentiated). It is anticipated that the adoption of a strategy based on single-destination brand positioning will also be more successful than a multiple-destination brand strategy in cases where the destinations offer homogeneous tourism products that tend to emphasize very similar points of comparison, such as high-quality accommodation, good restaurants, and/or well-designed public spaces (Baker 2007). This is all the more likely when the destination in question seeks to create an authentic brand by connecting it with elements of its cultural and historical identity to form a visual identity (Walker 2010). The implementation of a multiple-destination brand positioning strategy can dilute a destination’s identity and differentiation, compared to competing destinations, as the existence of several brands with similar characteristics—each brand representing a territory within the country—may generate confusion among consumers. This confusion may then be reflected in CBDBE evaluations. On this premise, the following hypothesis is proposed:

Hypothesis 2: A positioning strategy based on one single-destination brand will generate a higher level of CBDBE than a strategy based on multiple-destination brands.

The Moderating Effect of Message Consistency on the Relationship between Destination Branding Strategy and CBDBE

We saw earlier that the coherent strategic management of all brand messages contributes to the creation of strong brands and the creation of brand equity (Anantachart 2004; Duncan and Moriarty 1998; Duncan and Mulhern 2004). Yet despite the consensus in the literature that efforts to achieve message consistency make a significant contribution to achieving the desired positioning and brand equity, no study to date has analyzed the extent to which a communication strategy based on message consistency may moderate the effect of destination positioning type (single-destination brand vs. multiple-destination brands) on CBDBE.

Schema theory (Bobrow and Norman 1975) may be useful in this context. This theory plays an important role in explaining how individuals process the new (noncongruent) stimuli they receive and how they integrate the new information alongside their previous mental schema. Schemas are higher-order cognitive structures composed of simpler units that represent generic concepts in the memory (Fiske and Taylor 1991). When an individual receives new information, they compare it to their previous mental schemas and respond in terms of memory and cognitive elaboration (M. Lee and Faber 2007). Unlike congruent information, incongruent information is that which contradicts the knowledge stored in the memory in the form of cognitive schemas (Schmidt and Hitchon 1999). The literature finds that, while a low level of cognitive elaboration is required to process congruent information, a markedly higher level of elaboration is activated when an individual receives messages that are incongruent with the previous schema (Mandler 1982). This has a major effect on how the incoming information is processed, the cognitive responses that are triggered (in the form of counter-argumentation), attention levels (Heckler and Childers 1992), and ultimately the individual’s attitudes and perceptions of value. By contrast, messages that are congruent with the previous schema do not activate the counterargumentation mechanisms, and it is more likely that positive affect will be generated (d’Astous and Chartier 2000).

Following a similar vein, the Associative Network model (Srull 1981) holds that information that is not entirely congruent with expectations will be intensively processed, in a manner that makes it particularly likely to be remembered. As a result of this highly elaborated processing, the subject forms numerous cognitive associations between the incongruent information and the other information they have in their minds (Stangor and McMillan 1992). In the terminology of the Elaboration Likelihood Model (ELM) (Petty and Cacioppo 1986), this process is known as high message elaboration, or processing via the central route. In contrast, when the information received by the subject is congruent with what they are expecting (i.e., with their existing schema), this reduces the level of cognitive complexity (Stangor and McMillan 1992). In turn, the individual will elaborate the message much less, and will process it via the peripheral route, in ELM terms.

In view of these previous findings, it is to be expected that, when a tourist perceives a lack of consistency in the messages they receive via the different communication tools, their cognitive elaboration will be greater (in ELM terms) and conducted via the central processing route. This means they will perform a more elaborate analysis of the information, which will trigger a counterargumentation process; and they will compare the new information with that which preexists in their expected schema. Elsewhere, the branding literature has demonstrated that those brands whose positioning offers a mix of symbols, functions, and experiential benefits (in the present case, multiple-destination brand positioning) are more difficult to manage in terms of brand associations (brand image) than those whose approach is simpler (in the present case, single-destination brand positioning) (Park, Jaworski, and Maclnnis 1986).

In view of these findings, it may be the case that, when tourists receive information about a destination via different media, and they perceive that information to be inconsistent, they will perform a greater degree of elaboration (via the central processing route), which will enable them to create much clearer associations with the destination. This, in turn, will lead to a clearer brand image and greater CBDBE than in the case of a multiple-destination brand positioning strategy, under the same conditions of low message consistency across different media. This latter strategy, as noted by Park, Jaworski, and Maclnnis (1986), will generate certain confusion in the subject and a destination image that is not as clear.

By contrast, when the messages are congruent and in line with a consistent communication strategy, there will be less cognitive elaboration. This will lead to more peripheral processing, which will hinder the individual’s appreciation of the benefits that a single-destination brand strategy presents in terms of destination image and CBDBE, compared to a multiple-destination brand strategy.

On the basis of these theoretical considerations, the following hypothesis is proposed:

Hypothesis 3: Message consistency moderates the effect of destination-positioning brand strategy type on CBDBE.

Hypothesis 3a: Under conditions of low message consistency across different media, compared to high consistency, a single-destination brand positioning strategy will generate significantly higher CBDBE than multiple-destination brand positioning.

Hypothesis 3b: Under conditions of high message consistency across different media, compared to low consistency, a single-destination brand positioning strategy will not generate any significant differences in CBDBE, compared to multiple-destination brand positioning.

Methodology

To fulfill the research aims and test the proposed hypotheses, a 2 × 2 full factorial experimental design between-subjects was applied, in which two variables were manipulated, each of which had two levels: brand positioning (single brand vs. multiple brands) and message consistency (low vs. high). The dependent variable was CBDBE.

Sample and Procedure

To participate in the experiment, individuals were required to fulfill two conditions: they had to be of legal age (18 years or older), and they had to never have been to Spain (so as to avoid the potential for any past experience to contaminate the CBDBE scores). Spain was chosen as the tourist destination for the study, because in recent years it has consistently featured among the top five destinations in the world by number of visitors (Word Tourism Barometer 2016; Lascu et al. 2018). The United States was chosen as the target population for two reasons. First, the possibility of identifying individuals with no previous experience of the destination was high, given that the percentage of US tourists visiting Spain is fairly low (in 2016, the country represented just 2.9% of tourist arrivals to Spain) (ITE 2017). Second, the United States represents a potential market of great interest to Spain, not only in terms of tourist volumes but also because it generates higher-quality tourism: the primary interests of the US tourist are cultural visits (67%), visits to cities (62%), and shopping (59%) (Tourspain 2018).

Participants were selected by means of an Internet user panel managed by Survey Sampling Spain S.L. (part of Survey Sampling International, or SSI). The rationale for this choice was twofold. First, SSI has won several awards for its results and rigor in the market research field. The firm has more than 30 offices in more than 20 countries; it has 17 million panelists from 90 countries on its books; and, in 2016 alone, it successfully completed 40 million surveys across 60,000 projects. By controlling the characteristics of individuals within the sample, SSI has created an online sample blend that is consistent when measured by comparison with external benchmarks, including telephone sample studies. Second, the panel comprises more than 7 million users in the United States, aged 18 years or older, with information on the panelists. Hence, the target population can be selected with great accuracy, ensuring sample representativeness, which is reflected in the population defined for the present study (Table 1). Data were collected in September 2016, and the final sample comprised 804 cases. This sample size presented a random sampling error of 3.5% and a statistical power of 81% considering a small effect size (0.10) and a significance level equal to 5%. The sociodemographic characteristics of the final sample largely matched the general profile of US tourists, according to the US National Travel and Tourism Office (2014). The number of cases for each of the four treatments was between 199 and 203.

Table 1.

Sociodemographic Characteristics of the Sample.

Characteristics	Categories	Percentage	Categories	Population^a
Gender	Male	47.26	Male	50
Gender	Female	52.74	Female	51
Age, years	18–29	20.52	18 to 29	21.9
	30–44	37.44	30 to 44	27.9
	45–65	40.80	45 to 64	38.4
	>65	1.24	Over 65	11.8
Activity	Employed	56.59	Employed	58.9
Activity	Not in work	43.41	Not in work	41.1

Percentage of tourists, according to the US National Travel and Tourism Office (2014). Available online at: http://travel.trade.gov/outreachpages/download_data_table/2014_Outbound_Profile.pdf.

The data collection procedure started with an email invitation to take part in a research project to discover the perceptions of international tourists regarding Spain as a tourist destination. Those users who agreed to take part were directed to an intranet, where they had to complete three steps. First, prior to exposing participants to the stimuli, data were collected on the preconceived image they had of Spain and their (self-perceived) level of knowledge about the country. In this first stage of the experiment, the tourists’ opinions of the two media where the experimental stimuli would be placed, namely YouTube and WordPress, were also measured. Following this initial questionnaire, in the second stage the participants were randomly assigned one of the four treatments: (1) high message consistency–single-destination brand positioning; (2) high message consistency–multiple-destination brand positioning; (3) low message consistency–single-destination brand positioning; and (4) low message consistency–multiple-destination brand positioning. In the third and final step, the respondents were once again directed to a questionnaire, this time covering responses regarding CBDBE (the dependent variable) and the remaining measurements for subsequent manipulation checks (Perdue and Summers 1986).

Experimental Stimuli

The experimental stimuli were professionally designed for the purpose of the study, which captured the appropriate combination of different levels for the independent variables. The materials can be downloaded via the following link: https://1drv.ms/b/s!AhgrRnWDjB9pgYZDuK3veQjM7IpI-w). A communications agency with significant experience in the tourism sector was charged with this task. Two different promotional videos about Spain as a tourist destination were created, simulating the YouTube platform (one single-destination brand; multiple-destination brands within the same country). And four versions of a WordPress blog were produced, featuring the posts of a blogger narrating her or his experiences during a week of tourism in Spain (one single-destination brand and highly consistent message; one single-destination brand and less consistent message; multiple-destination brands and highly consistent message; multiple-destination brands and less consistent message). Controls ensured that participants viewed the respective videos from start to finish and read the respective blogs for at least one minute.

Positioning according to brand strategy type was manipulated by using a map of Spain that appeared at the beginning of the video, coupled with a caption in the upper left-hand corner of the screen. Treatments on two levels were employed: one single-destination brand vs. multiple-destination brands within the same country. For the single-destination brand, the map was presented featuring only the word “Spain” in the upper caption. During the video, no references were made to any given geographical area of the country when showing the various sights and attractions (www.youtube.com/watch?v=TlnzVKonsAg). In the alternative video, for the multiple-destination brand treatment, again the map of Spain was displayed but this time the specific locations shown in the video were indicated. These were Andalusia, the Canary Islands, and Catalonia—the principal destinations for international tourism in Spain (INE 2017) (www.youtube.com/watch?v=TgA9BWl0bRo). Apart from these differences in the captions, the look and feel of the two videos were identical, in terms of the images and music (flamenco), and the attributes of the destination that were featured, namely, beautiful beaches, outstanding hotels, rich heritage and history, and wonderful natural resources, and leisure activities. This ensured that, in both cases, the subject was exposed to a homogeneous offer.

Message consistency was manipulated by means of an online blog, which participants were asked to read following the video. The attributes of the destination described by the blogger in the online post were identical to those that featured in the video viewed by each tourist, but, just as in the video, the different treatments referred to Spain as an overall destination or to different areas of Spain as a destination (Andalusia, Canary Islands, and Catalonia). Message consistency between the video and the blog was thus used to manipulate this latter factor. Presenting the same message via different media is an approach used previously in the literature to manipulate message consistency (Duncan and Everett 1993). The message communicated via both the video and the blog was positive. The difference centered on whether the argument remained the same across both media (highly consistent message) or varied from one to the other (less consistent message). To take beaches as an example, the video showed beaches in an idyllic light, and the blog could either present this same narrative in the form of text and images (highly consistent message), or it could use a different narrative, about the beaches having the capacity to attract a high volume of tourists, showing the vast numbers of visitors that go there (less consistent message).

Measurements

To measure overall CBDBE, a four-item, 7-point Likert-type scale was used (see Appendix 1), this having also been applied in earlier studies (Im et al. 2012; Frías-Jamilena, Polo-Peña, and Rodríguez Molina 2017). The previous literature has demonstrated that this approach to measuring CBDBE provides acceptable psychometric properties in terms of reliability, convergent validity, and discriminant validity (Yoo and Donthu 2001; Frías-Jamilena, Polo-Peña, and Rodríguez Molina 2017).

The questionnaire also included a series of measurement scales to conduct the necessary manipulation checks. To check that the destination branding strategy had been correctly manipulated, a single item with 7 positions was used, in which position 1 reflected that the tourist felt the message positioned Spain as a destination with no differentiation between areas, and 7 that they considered Spain to be positioned as differentiated into distinct areas. To check the manipulation of message consistency, a five-item, 7-point Likert-type scale for perceived consistency was used, adapted from previous studies (Speed and Thompson 2000).

To ensure that the factors manipulated in the experiment were correctly related with the dependent variable, the participants’ opinions about YouTube and WordPress (on which the experimental stimuli were presented) were used as control variables (Malhotra 2010). These variables were measured before the subjects were exposed to the treatment, as recommended by authors including Keppel (1991), Kirk (1995), and Perdue and Summers (1986). To measure these opinions, a four-item, 7-point semantic differential scale adapted from Drolet, Williams, and Lau-Gesk (2007) and Lam and Hsu (2006) was used.

An important issue to consider was the possibility that the messages may not have been perceived in the same way in each of the treatments. Attitude toward the message in the promotional video and attitude toward the message in the online blog were therefore measured. The scales used to measure these two variables were similar to one another: eight-item, 7-point semantic differential scales, adapted from Morimoto and Trimble (2012).

Finally, as noted earlier, participants’ pre-image of Spain and their level of knowledge about Spain were also measured on a two-item, 7-point Likert-type scale (García, Gómez, and Molina 2012; Muehling, Stoltman and Grossbart 1994). Furthermore, several sociodemographic characteristics were measured to check for possible selection bias.

A confirmatory factor analysis (CFA) was performed with these measures, to evaluate their psychometric properties. The CFA presented an adequate fit ( $χ_{S B}^{2}$ = 1000.84, p<0.01; adjusted goodness of fit index [AGFI] = 0.95; comparative fit index [CFI] = 0.98; non-normed fit index [NNFI] = 0.98; root mean square error of approximation (RMSEA) = 0.03), bearing in mind that Satorra and Bentler’s chi-square is affected by sample size. Appendix 1 shows how the indicators for internal consistency (Cronbach’s alpha) and composite reliability (ρ) were, in all cases, over 0.7 and the average variance extracted was higher than 0.5. These results indicated that the scales used were reliable and valid. Hence, an indicator variable could be created in each case, as the mean of the items.

Pretest

Two pretests were conducted. The first of these was carried out on 114 native English speakers to analyze the extent to which the questionnaire items and the experimental stimuli were understood. This is particularly important in the case of the blog, as the video included very little text and no verbal messages. Once the necessary adjustments had been made, both stimuli were tested among a sample of 233 tourists that matched the target public: from the United States, of legal age, and had never visited Spain before. This sample was used to test the suitability of the treatments. The procedure described here was based on the premise that the stimuli applied to the final sample, the measurement scales for the dependent variable, and the manipulation checks were those used in the main study, as recommended in the literature (Perdue and Summers 1986).

The pretest on the experimental stimuli showed that the manipulation of the destination brand strategy was working correctly, as the individuals presented different perceptions of the stimulus, depending on whether the positioning was based on a single-destination brand strategy or a multiple-destination brand strategy (Brand_{single_pretest} = 5.34 vs. Brand_{multiple_pretest} = 5.73; t-test = −2.17; p = 0.03). Similarly, it was verified that the different levels of message consistency between video and blog were perceived by the sample. An average difference t-test on the measure used for the consistency check showed that when consistency was high, subjects perceived a greater connection between the messages received in both communication tools, whereas in the case of low consistency, the average was lower (Message_{low_consistency_pretest} = 5.18 vs. Message_{high_consistency_pretest} = 5.85; t-test = −3.85; p < 0.01). These results suggest that the treatments were manipulated correctly. Nevertheless, in the main study, a further check was made on the adequacy of the manipulation of the experimental factors.

Results

Prior to testing the proposed hypotheses, analyses were undertaken on the data to rule out the existence of the following: selection bias in the experimental groups; manipulation bias in the stimuli; a confounding bias in the effect of the stimuli on the dependent variable; and possible covariables in the experiment.

Sample Selection Bias

As we have seen, once the panelists had accepted the invitation to take part in the study, they were randomly assigned to one of the four experimental groups. To ensure that the distribution of respondents across the four groups was well balanced, the association was calculated using a chi-square between each assigned group, and the sociodemographic characteristics of the sample. Given that Spain is a destination about which the participants may have had prior knowledge and pre-formed opinions, this analysis also tested the distribution of individuals across the experimental groups according to these two variables (measured prior to the application of the stimuli). The results showed that the distribution of cases in terms of gender, age, and employment status was even across the four groups, as was the distribution in terms of prior knowledge and opinions on Spain as a tourist destination (Table 2).

Table 2.

Association between Experimental Group and Sample Characteristics.

Characteristic	Chi-square	d.f.	p Value
Gender	4.36	3	0.22
Age	11.18	9	0.26
Employment status	19.71	15	0.18
Knowledge of Spain	9.18	6	0.16
Opinion of Spain	5.12	6	0.53

Manipulation Check

Although the pretest helped ensure that the stimuli were operating as anticipated, it is always advisable to perform the check one more time for the final sample (Oppenheimer, Meyvis, and Davidenko 2009). As described in the Metho-dology section, for positioning according to brand strategy (single-destination brand vs. multiple-destination brands), an item was used that measured the degree to which the individual perceived the message to be referring to different geographical areas of the country, each having its own brand (i.e., using a multiple-brands strategy). By means of an average difference test, it was demonstrated that the individuals assigned to the multiple-destination brand positioning group presented higher average scores for this item than those assigned to the single-destination brand positioning group (Brand_single = 5.42 vs. Brand_multiple = 5.62; t-test = −2.11; p = 0.03). The measurements obtained were similar to those taken from the pretest.

As regards the manipulation of message consistency, the results showed that participants perceived significantly higher consistency and a more logical connection between the video and the blog when they were allocated to a high-consistency group than to a low-consistency group (Message_{low_consistency} = 5.35 vs. Message_{high_consistency} = 5.80; t-test = −5.63; p < 0.01). Despite the presence of significant differences, given the values obtained it is more accurate to speak in terms of low and high consistency rather than inconsistency versus consistency.

Confounding Check

Confounding bias arises when, in the manipulation of factors, variables other than the actual experimental factor are altered, which can, in turn, affect the dependent variable (Perdue and Summers 1986). In the present case, the message consistency was manipulated by changing the narrative between the video and the blog, so it is possible that the message conveyed via the blog could be perceived as more negative or positive, as well as less consistent. To check for this possible bias, the questionnaire includes two scales to measure the attitudes toward the video and the blog messages. Two analyses of variance (ANOVAs) were then undertaken (one for the video and one for the blog), using the factors manipulated in the experiment as the independent variables. The results demonstrated that there was no relationship between attitudes toward the video message and the treatments (F = 1.37; p = 0.24), and nor was there any between attitudes toward the blog message and the treatments (F = 0.81; p = 0.37). It could therefore be concluded that the manipulation of the independent variables did not affect perceptions of the message among respondents (Shadish, Cook, and Campbell 2002).

Concomitant Variables (Covariates)

Given that the factors “message consistency” and “brand strategy type” are linked to the promotion of the destination, and bearing in mind the hierarchy of effects of attitudes, examined in studies on advertising effectiveness (Belch and Belch 2004), one possible covariable to consider is that of the tourist’s opinion regarding the tools via which the experimental stimuli were hosted (YouTube and WordPress). According to Kirk (1995), the choice of a covariable is appropriate if it fulfills the following requirements: (1) it is related to the dependent variable; and (2) it is not related to the independent variables (which is generally the case when they are measured prior to exposure to the stimuli, as in the present study). To test the first of these criteria, the correlation between CBDBE and opinions about both tools was calculated. The results presented a significant correlation in both cases (r_{CBDBE-YouTube} = 0.32, p < 0.01; r_{CBDBE-WordPress} = 0.44, p < 0.01), showing that the first requirement was fulfilled. With regard to the second criterion, two ANOVAs were conducted (one for each covariable); the dependent variable was opinion regarding each tool, and the independent variables were the manipulated factors. The results showed that there was no significant relationship between the treatments and each of the covariables (F_YouTube = 2.00, p = 0.16; F_WordPress = 0.92, p = 0.34), verifying that the second criterion was also fulfilled. These results suggest that opinions about the tools used in the stimulus should be included as covariables.

Hypothesis Testing

Bearing in mind the use of a full factorial design and the results for concomitant variables, an analysis of covariance (ANCOVA) was used to test the hypotheses. The overall measure of CBDBE was used as the dependent variable; message consistency and destination-positioning brand strategy type were the factors; and opinions regarding each of the two communication tools were the covariables. The results of the ANCOVA estimation are shown in Table 3. As regards the assumptions of the model, Levene’s test gave a significant result, suggesting that the variance of the errors under each experimental condition was not homogeneous (F = 7.03; p < 0.01). However, the fact that the sample size was similar in each of the two treatments (between 199 and 203 cases) and that the ratio between the group with the higher and lower variance was less than 3 confirmed the robustness of the F statistic and the non-violation of this assumption (Kirk 1995, p. 100). However, to ensure that the results were robust, in light of the heterogeneity in the error variance between groups, it was decided to correct the standard errors for the estimated means using a nonparametric method (bootstrap) (Davidson and MacKinnon 2006). Specifically, a wild bootstrap based on 2,000 samples was used (Wu 1986), as this offers better results than a direct resampling of the dependent variables in the analysis of heteroskedastic data (MacKinnon 2002). In all cases, the results were similar.

Table 3.

Analysis of Covariance Results for Overall Consumer-Based Destination Brand Equity.

	SS	d.f.	MS	F	p Value	Wild Bootstrap p Value
Intercept	411.87	1	411.87	402.70	<0.01	<0.01
Opinion about the YouTube video tool	7.68	1	7.68	7.51	0.01	0.02
Opinion about the WordPress blogging tool	89.79	1	89.79	87.79	<0.01	<0.01
Message consistency (MC)	70.17	1	70.17	68.61	<0.01	<0.01
Brand strategy (BS)	3.77	1	3.79	3.68	0.05	0.05
MC * BS	4.82	1	4.82	4.72	0.03	0.03
Error	816.16	798	1.02

Hypothesis 1 proposed that a communication strategy based on message consistency will generate significantly higher CBDBE than one that is not based on message consistency. The results are in line with this hypothesis, as CBDBE was found to be significantly higher among tourists exposed to highly consistent messages, compared to the average for individuals exposed to messages low in consistency (Message_{low_consistency} = 4.65 vs. Message_{high_consistency} = 5.25; p value < 0.01). Cohen’s d effect size index for message consistency was 0.20 (Cohen 1988). Hypothesis 1 therefore finds empirical support.

The second hypothesis held that a positioning strategy based on one single-destination brand will generate a higher level of CBDBE than one based on multiple-destination brands. Once again, the results are in line with this proposition. The mean CBDBE was significantly higher when a positioning strategy based on a single-destination brand strategy was used than when a multiple-destination brand strategy was used (Brand_single = 5.02 vs. Brand_multiple = 4.88; p value = 0.05). With regard to brand strategy, the effect size according to Cohen’s d index was slightly lower than that of message consistency (0.13), albeit higher than the level Sawilowsky (2009) considers to be a “very small effect.” Hypothesis 2 therefore also receives empirical support.

Finally, hypothesis 3 proposed that the effect of destination-positioning brand strategy type on CBDBE is moderated by the degree of message consistency between communication tools. Hypothesis 3a postulated that, in the case of a communications strategy that is not based on message consistency, positioning based on one single-destination brand will generate significantly higher CBDBE than positioning based on multiple-destination brands. The results confirm this hypothesis (Brand_{single_low_consistency} = 4.80 vs. Brand_{multiple_low_consistency} = 4.51; p value < 0.01). Hypothesis 3b, on the other hand, contends that, in the case of a communications strategy based on message consistency, single-destination brand positioning will not generate significant differences in the level of CBDBE, compared to multiple-destination brand positioning. The data from the study appear to confirm this hypothesis (Brand_{single_high_consistency} = 5.25 vs. Brand_{multiple_high_consistency} = 5.26; p value = 0.98) (see Figure 1). The maximum effect size of that interaction was 0.84—deemed “large” by Cohen (1988). Therefore, based on these results, it can be concluded that the degree of message consistency across communication tools moderates the effect of destination-positioning brand strategy type (single-destination brand vs. multiple-destination brands) on CBDBE, in the direction proposed in hypothesis 3.

Figure 1.

Estimated marginal means for interaction between destination-positioning brand strategy type (single vs. multiple) and message consistency.

Discussion of Results and Conclusions

For destination managers, ensuring that the destination is appealing to tourists and remains competitive is a primary objective. The type of communication strategy that managers select for their destinations can help contribute to that competitiveness. On this point, the marketing literature concurs that strategic consistency of the message across all communication tools is a precondition for generating CBDBE (Delgado-Ballester, Navarro, and Sicilia 2012). The present study aimed to understand the effect of (1) message consistency between communication tools and (2) destination-positioning brand strategy type on CBDBE. The published studies highlight the fact that achieving greater brand equity is the equivalent of building competitive advantage (Pike and Page 2014).

Several contributions to the academic literature derive from this investigation, in terms of helping to improve the brand equity of a tourist destination. First, it is found that communication based on highly consistent messages helps to increase CBDBE. This result reinforces those of previous tourism studies, which found that message consistency exerted a significant effect on brand equity in the hotel sector (Šerić, Gil-Saura, and Ozretić-Došen 2015; Šerić 2017). The present work also goes a step further by focusing on the destination itself and experimentally controlling the degree of message consistency across two communication tools that are highly popular in this sector—online video and travel blogging. Second, the present investigation has demonstrated that destination positioning based on a single-destination brand strategy generates higher CBDBE than a multiple-destination brand strategy. Again, this finding corroborates those of the published literature to date (García, Gómez, and Molina 2013), which demonstrate that a single-destination brand strategy is the most successful approach; it is also in line with those studies that emphasize the need to create a strong, unique image as the basis for effective destination positioning (Mihalic 2000; Mykletun, Crotts, and Mykletun 2001; Uysal, Chen, and Williams 2000). Once again, the original contribution made by the present study lies in the experimental manipulation of destination-positioning brand strategy type.

Third, the present work demonstrates that, when the positioning strategy is communicated via consistent messages, the effects of both a single-destination brand strategy and a multiple-destination brand strategy on CBDBE are similar. However, when the positioning strategy is communicated via messages low in consistency, higher CBDBE is achieved by using a single-destination brand strategy than when a multiple-destination brand strategy is applied. These findings are congruent with the propositions of schema theory (Bobrow and Norman 1975), which leads us to think that a tourist destination can select either of the destination-positioning brand strategy types (single-destination brand vs. multiple-destination brands), as they both exert a positive effect on CBDBE, providing the messages that are used across different media to promote awareness of the destination are consistent.

In the case of a positioning strategy that is communicated via messages that are not consistent, it is shown that higher CBDBE is achieved when the strategy is based on single-destination branding than when it is based on multiple-destination branding. As the messages received by the consumer are not consistent, positioning that is based on the more effective strategy (single-destination branding) increases perceptions of CBDBE.

Finally, the present study helps advance the literature dealing with the effectiveness of positioning strategies implemented by destinations. To our knowledge, none of the literature published to date manipulates different brand positioning strategies to examine which one is the most effective, based on the consumer’s perception of the destination’s brand equity. Previous studies mainly focus on examining the positioning strategies already used by destinations, to assess which approach appears to be the most effective (García, Gómez, and Molina 2013). Furthermore, they do not employ message consistency between promotional media for the destination as a moderator. Other earlier works also analyze, via survey, the main effect of message consistency on brand equity, for example in the hotel sector (Šerić 2007).

The present study makes a two-fold contribution to furthering the extant literature: (a) it validates the main effect of consistency for tourist destinations by means of an experimental methodology in which the possible confounding effects are controlled; and (b) it analyzes the moderating role of this variable on the effect of branding strategy type. This is particularly relevant in the context of tourist destination management, as the Internet has become the main information channel for. It is also in this context that destination-management organizations (DMOs) typically combine channels in which they can control the message with channels in which they cannot—meaning that the tourist is often exposed to inconsistent messages deriving from different channels. Furthermore, it is typically the case that the political, historical, and/or cultural determinants at play lead to the coexistence of several brands associated with a given destination (Tasci 2011; Balakrishnan 2009). It is in this context that the present study highlights the drop in destinations’ CBDBE.

Managerial Implications

There are several important implications arising from this work for managers of tourist destinations. In such a competitive operating environment as tourism, where many destinations can offer the same type of tourism and very similar features, the tourist will select the destination they perceive to most closely match their needs, and on this basis will accord it greater brand equity.

Consumers attach higher brand equity to a destination when it is promoted using a single-destination brand strategy than when its different regions have their own individual brands (multiple-destination brand strategy). The single-destination branding approach provides information to the consumer that is clearer and less confusing, leading them to have a more positive perception of the destination’s brand equity. However, it is not uncommon for managers and marketers of whole-country destination images to face pressure from the different regions to enable them to promote their own territory brands. The solution would be to develop a communication strategy based on a high level of consistency between the messages delivered via different media and tools. The challenge of this approach is that achieving such consistency is a complex task, particularly in the case of those communication tools that cannot be controlled by destination managers, as they would be in the case of traditional media. Previously, the different media such as television, print, external advertising, and radio offered a one-directional showcase that was possible to manage. But nowadays, blogs, social networks, and word-of-mouth marketing are proving much more difficult to actively control in terms of the messages communicated directly by clients about tourist destinations (Winer 2009). There are now innumerable websites, blogs, and social networking sites offering information on destinations, from the direct perspective of travelers’ experiences. All of this information influences other tourists in their selection of holiday destinations and is beyond the control of destination managers.

Given this reality, the destination strategy should be based on ensuring the consistency of those messages that can be controlled, while at the same time making active efforts to be attentive to comments being freely exchanged between tourists online. Using active listening systems enables destinations to intervene directly in the conversations tourists are having. Any such interventions have to be respectful of the comments being shared, and must be made incrementally—and only to provide new information of value to the conversation taking place.

In addition, a strategy based on multiple-destination brands within a given country enables tourists to perceive the distinct destinations they can visit within that country. For those tourists who do not like to repeat their holiday location, this approach improves the likelihood that they will repeat their visit to the country itself.

Limitations and Future Research

The present study presents certain limitations, as all research does, that may point to potential areas of research for the future. First, the work only addresses perceptions of brand equity among US tourists inexperienced in Spain as a destination. Future studies should use samples of tourists from other countries and endeavor to introduce the moderating effect of national culture in their analysis. It should also be noted that the results relating to message consistency between external information sources are valid solely for tourists inexperienced in the destination, given that experienced tourists will focus more on internal information (Gursoy and McCleary 2004). Second, while the study tests the effectiveness of destination positioning based on different brand strategies on CBDBE, future studies could include different positioning strategies to test whether IMC continues to moderate the effect of positioning strategies on CBDBE. One such option would be to examine the effect of positioning based on tourism type (sun-and-sand, cultural, rural, gastronomical, and so on) on CBDBE. Finally, the present study measures CBDBE using an overall measure of the construct. It would be of value to better understand the effect of manipulated factors on each of its dimensions.

Supplemental Material

Appendix_1 – Supplemental material for The Effect of Message Consistency and Destination-Positioning Brand Strategy Type on Consumer-Based Destination Brand Equity

Supplemental material, Appendix_1 for The Effect of Message Consistency and Destination-Positioning Brand Strategy Type on Consumer-Based Destination Brand Equity by J. A. Castañeda-García, D. M. Frías-Jamilena, S. Del Barrio-García and M. A. Rodríguez-Molina in Journal of Travel Research

Footnotes

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: research project P11 SEJ-8104 by the Junta de Andalucía and Projects ECO2012-39217 and ECO2015-65306-R by the Ministerio de Economía y Competitividad.

ORCID iDs

J. A. Castañeda-García

D. M. Frías-Jamilena

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

J. A. Castañeda-García, Senior Lecturer in the Department of Marketing and Market Research at the University of Granada. His research interests encompass e-commerce, mobile commerce, tourism and cross-cultural research. He has written several academic articles published in reputed journals in such areas, ie. Internet Research, Information & Management, Online Information Review, Tourism Management, Journal of Travel Research, among others.

D. M. Frías-Jamilena, Professor in the Department of Marketing and Market Research at the University of Granada. His research interests are in the areas of online consumer behavioral, tourism and cross-cultural research. She has published in Tourism Management, Journal of Sustainable Tourism, Journal Small Business Management, Entrepreneurship and Regional Development, Internet Research, Online Information Review, The Services Industries Journal, International Journal of Hospitality Management, Cornell Hospitality Quarterly, Journal of Travel Research, and other scholarly journals.

S. Del Barrio-García, Associate Professor of Marketing at University of Granada (Spain). His areas of specialization are the Integrated Marketing Communication (IMC), Tourism Marketing, Marketing Online, and Cross-Cultural Marketing. He has published several books as author and co-author on these matters. He has also published various peer-reviewed papers in prestigious journals such as International Journal of Advertising, Journal of Advertising Research, Cornell Hospitality Quarterly, Journal of Destination Marketing & Management, European Journal of Marketing, Cross Cultural Management, Computers in Human Behavior, among others.

M. A. Rodríguez-Molina, Senior Lecturer in the Department of Marketing and Market Research at the University of Granada. His research interests encompass tourism, consumer behaviour, and mobile marketing. He has written several academic articles published in reputed journals in such areas, ie. Tourism Management, Journal of Travel Research, Internet Research, Journal of advertising Research, and Journal of Small Business Management, among others.

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