An interregional extension of destination brand equity

Abstract

Since the 1990s, the Asia-Pacific region’s world market share of international travelers has increased, as America’s and Europe’s shares have fallen. China (People’s Republic of China) has become the world’s biggest tourism source market with an overseas spend of US$292 billion in 2015, fueling opportunities for the region and beyond. Now, Asia Pacific outbound travel is extending past short-haul interregional travel to long-haul destinations, specifically Europe. To realize this potential, European destinations need a better understanding of the Chinese traveler; their perceptions of destinations, awareness, and loyalty. This study measures the brand equity of Switzerland and Austria as perceived by Hong Kong Chinese tourists. Structural equation modeling results indicate that destination brand image and associations significantly impact brand loyalty, whereas destination awareness does not, contrary to past interregional research findings. Understanding the influence of brand components on overall brand equity supports the efficacy of the brand equity model for interregional destinations.

Keywords

Brand loyalty China outbound destination marketing destination management long haul secondary destinations

For decades now, outbound Chinese tourists have attracted the attention of destinations looking to new source markets for growth, first from within the Asia-Pacific region, then increasingly from longer-haul markets, notably, Europe. In this East-West interregional travel context, relatively little is known about the differential effect of European destination brands on the Chinese consumer’s response to those brands or the destination brand equity effect. As the economic situation of Hong Kong and China continues to improve the income and living standards for most Chinese, increased wealth and disposable income for international travel present a market opportunity and a research challenge.

Outbound tourism from Mainland China and the special administrative regions of Hong Kong and Macau took off during the 1990s (China Outbound Tourism Research Institute, 2015). The growth was so significant that by 2012, China overtook Germany and the United States as the largest outbound tourism source market in the world. In 2015, 120 million Chinese traveled from the mainland spending US$292 billion (UNWTO, 2016). As growth from other source markets such as Europe, Russia, and North America slows, it is not surprising that China’s outbound tourism market is gaining attention. While China remains the most important source market for intraregional travel within Asia, interregionally, Europe has grown most significantly in popularity for Chinese long-haul trips (The Wall Street Journal, 2015).

Destinations like the UK, France, and Italy were early hot spots for Chinese tourists, and now the Alpine destinations of Switzerland and Austria are attracting more Chinese and are increasing their market share of Chinese outbound tourists. It took almost a decade of concentrating specifically on the Chinese market for Austria and Switzerland to see overnight stays start to grow. With a memorandum of understanding between European countries and the National Tourism Administration of the People’s Republic of China, Switzerland and Austria received approved destination status in March 2004 and in the following months, Switzerland Tourism and the Swiss Hotel Association Hotelleriesuisse launched their initiative “Hello China” (Switzerland Tourism, 2004). Tourism Austria and the Austrian Hotel Association introduced a comparable campaign named “China Meets Austria” in 2005 (/ÖHV, 2005).

For Switzerland, China (including Hong Kong) is now the biggest Asian source market.¹ From 2008 to 2014, the overnight stays jumped by double digits, resulting in growth of 285%: from 214,000 in 2008 to 1,142,000 in 2012 (BFS, 2015). The Swiss tourism board (Schweiz Tourismus) projects 2 million overnight stays from China by 2020. Incredibly, China will overtake the neighboring country Italy as a key source market for Switzerland (Schmid, 2012).

The development for Austria shows a similar pattern, though slightly less dynamic than for Switzerland. From 2008 to 2014, the number of overnight stays from China to Austria grew by 127% from 217,000 in 2008 to 683,000 in 2014 (Statistik Austria, 2008–2016). Like Switzerland, China is the biggest Asian source market and ranks among Austria’s top 20 origin markets.

Switzerland and Austria are both Alpine countries in the heart of Europe. The mainstream of their tourism products is more or less similar and mainly based on nature, landscape, and culture: both offer outdoor-, nature-, and/or activity-based tourism products consisting of hiking and/or mountain biking during summer season and snow sports during winter season. In addition, both countries offer special interest tourism with a leisure focus on cities, wine, and wellness. In terms of differentiation, Switzerland offers unique shopping based on its luxury goods (e.g. watches and jewelry), niche railway-based products such as the Glacier Express, and UNESCO world heritage sites.

In contrast, Austria offers tourism products based on its rich cultural heritage such as classical music, concerts, operas, and movies (e.g. The Sound of Music) as well as their imperial heritage from the days of the Austrian-Hungarian Empire (Peters et al., 2011). Historically, both countries have depended heavily on neighboring markets like Germany, the Netherlands, Great Britain, Italy, and Eastern Europe including Russia. In terms of currency and buying power, the countries are unique. Austria, as part of the European Union (EU), is under the Euro currency system. Switzerland is not a member of the EU and kept its Swiss franc currency, which gained in value in recent years, pushing export industries into competitive disadvantage, including tourism and hospitality.

From a European perspective, the differences in culture and national identity between Austria and Switzerland are likely quite clear. However, whether these differences are perceived from afar, particularly from markets outside Europe, is less clear. Despite their differences, long-haul Chinese tourists may very well perceive the brand images of these two destinations to be similar.

The research objectives of this study are twofold. First, it is to propose and test a destination brand equity model and investigate the characteristics of destination brand. Second, it is to understand destination brand equity from the perspective of an interregional traveler, Hong Kong Chinese tourists, concerning long-haul destinations in Europe, specifically Switzerland and Austria. This extension of destination brand equity research explores interregional traveler perceptions of long-haul destinations to better understand the components of overall brand equity (OBE) in a new context.

Literature and hypotheses

The marketing concept of brand equity has evolved from its product roots, to services and corporate brands, and has most recently been expanded to measure city and nation brands (Elliot et al., 2011; Kotler and Gertner, 2002). Among the resulting diversity of brand equity constructs, customer-based brand equity (CBBE) has been recognized for its applicability in the service industry. Keller (1993: 8) defined it as “the differential effect that brand knowledge has on consumer response to the marketing of that brand.” The CBBE model advocated by Aaker (1996a, 1996b) has been applied across academic disciplines. In the hospitality and tourism literature, the concept of CBBE has been used to assess the brand equity of several tourism destinations (e.g. Bianchi et al., 2014; Boo et al., 2009; Gomez et al., 2015; Horng et al., 2012; Im et al., 2012; Kladou and Kehagias, 2014; Konecnik and Gartner, 2007; Pike et al., 2010).

The CBBE model has also been applied to hotels (e.g. Dioko and So, 2012; Kayaman and Arasli, 2007; Kim and Kim, 2005; Oh and Hsu, 2014; Prasad and Dev, 2000; Xu and Chan, 2010), restaurants (Hyun, 2009; Kimpakorn and Tocquer, 2010; Lu et al., 2015; Namkung and Jang, 2013), conferences and exhibitions (Camarero et al., 2010; Lee and Back, 2008), and festivals (Manthiou et al., 2014). Specific to the application of CBBE in the context of a tourism destination, the concept of customer-based destination brand equity (CBDBE) has developed.

Understandably, there are disparities in the various conceptualizations of brand equity and its composition. A four-dimensional structure incorporating brand awareness, perceived quality, brand image, and brand loyalty has been most popular in specifying the dimensions of CBDBE (Horng et al., 2012; Lu et al., 2015; Malik and Naeem, 2011). Yet, some researchers exclude brand awareness (e.g. Camarero et al., 2010; Horng et al., 2012; Nam et al., 2011; Šerić et al., 2014), while others rule out brand image (Hsu et al., 2012; Kimpakorn and Tocquer, 2010; Nam et al., 2011; Prasad and Dev, 2000). Some studies include new dimensions such as trust (Kimpakorn and Tocquer, 2010; Oh and Hsu, 2014), performance (Dioko and So, 2012; Prasad and Dev, 2000), self and lifestyle congruence (Nam et al., 2011), quality of experience (Xu and Chan, 2010), or perceived value (Camarero et al., 2010; Manthiou et al., 2014).

In addition, some studies include OBE as a dimension along with the four common dimensions (Im et al., 2012; Manthiou et al., 2014; Washburn and Plank, 2002; Yoo et al., 2000; Yoo and Donthu, 2001) to identify a cause–effect relationship between the dimensions. In these studies, OBE is considered as a measure of the sum of destination brand equity, which manifests strong willingness to revisit one specific place despite the existence of alternative destinations. Comparatively, brand loyalty captures a more passive intention to revisit or recommend to others.

The proposed model in this study follows previous studies (Im et al., 2012; Manthiou et al., 2014; Washburn and Plank, 2002; Yoo et al., 2000; Yoo and Donthu, 2001) by conceptualizing the dimensions of destination brand equity to be brand awareness, brand image, brand associations (perceived quality and attitude), brand loyalty, and OBE. As Figure 1 shows, brand awareness, brand image, and brand associations influence brand loyalty, while all dimensions determine OBE. Hypotheses are developed to explore the casual relationships between the components of destination brand equity. Figure 1 exhibits the proposed destination brand equity model.

Figure 1.

Proposed destination brand equity model.

Influence of multidimensional destination brand equity on brand loyalty

Among components consisting of brand equity, brand awareness is considered an important component, reflecting the salience of the brand in the customer’s mind (Aaker, 1991). According to a study of Keller (1993), CBBE occurs when the consumer has a high level of awareness and familiarity with the brand and holds some strong, favorable, and unique brand associations in memory. In a tourism setting, awareness has been frequently employed in models of the destination choice process (Chon, 1992; Um and Crompton, 1990). In addition, a traveler’s awareness of a destination influences his/her destination preference that has been observed to be strongly associated with perceived likelihood of intention to visit (Woodside and Lysonskin, 1989). In line with this notion, various CBDBE studies have identified brand awareness as an essential component of destination brand equity (Chen and Myagmarsuren, 2010; Horng et al., 2012; Im et al., 2012; Yoo and Donthu, 2001).

Although some researchers express concern with the overridingly intense focus on image in the conceptualization of destination branding (Cai, 2002; Faullant et al., 2008; Hankinson, 2004), it is generally agreed that destination image is central to the formation of a CBDBE model (Ferns and Walls, 2012; Im et al., 2012; Konecnik and Gartner, 2007). In this study, both affective and cognitive components of destination brand image are combined in order to capture tangible and intangible features of a particular destination brand in the minds of customers.

Some researchers measure brand associations as perceived value, personality, and differentiation, while others classify brand associations into attributes, image, perceived quality, attitude, and benefits (Aaker, 1996b; Ekinci and Hosany, 2006; Pappu et al., 2005). Low and Lamb (2000) argue that these individual elements (i.e. brand image, perceived quality, and brand attitude) should be combined into one model in order to measure their interrelationships. They conclude that brand associations are multidimensional and that dimensionality of brand associations is influenced by brand familiarity. With a slight alteration of Low and Lamb’s (2000) model, the present study incorporates perceived quality and brand attitude within the brand associations construct to explore the multidimensional aspect of brand associations.

Brand recognition and brand recall are frequently adopted in consumer behavior studies (e.g. Atilgan et al., 2005; Pappu et al., 2005). In the context of an associative network memory model of brand knowledge, Keller (1993) defined brand image as the brand perceptions reflected by the brand associations held in consumer memory. He posits that the more favorable, strong, and unique the brand image, the greater the likelihood of decision choice. Destination image has been of great interest in the tourism context for more than three decades now. Research has investigated various aspects of destination image such as the components/dimensions of image (Echtner and Ritchie, 1993; Kim and Yoon, 2003), the destination image formation process (Chon, 1992; Gartner, 1993; Kim et al., 2009), the destination choice process (Um and Crompton, 1990), and the measurement of destination image, to name a few.

Past research of CBDBE tends to highlight the composite approach to destination brand loyalty that integrates both attitudinal and behavioral aspects (Boo et al., 2009; Konecnik and Gartner, 2007; Pike, 2009). The brand loyalty measures commonly used by CBDBE studies are likelihood of revisit, recommendation to others, and willingness to pay a premium (Bianchi et al., 2014; Ferns and Walls, 2012; Kladou and Kehagias, 2014; Yuan and Jang, 2008). Hence, we conceptualize brand loyalty on the basis of an attitudinal perspective and customer perceptions.

The aforementioned destination brand studies have investigated the interrelationship of these commonly used constructs of awareness, perceived quality, image, loyalty, and associations and brand loyalty (e.g. intention to visit and recommendation; Bianchi et al., 2014; Boo et al., 2009; Ferns and Walls, 2012; Horng et al., 2012; Pike et al., 2010). It is concluded that high destination brand equity indicates customers’ positive and strong associations and perceptions toward the destination brand, which results in customers’ high loyalty to the brand. In line with this conclusion, hypotheses were proposed as follows:

H1-1: Destination brand awareness is positively related to destination brand loyalty.

H1-2: Destination brand image is positively related to destination brand loyalty.

H1-3: Destination brand associations are positively related to destination brand loyalty.

Influence of multidimensional destination brand equity on OBE

OBE was not proposed by early scholars, but it has been employed to evaluate the sum of brand equity to confirm outcome of brand equity components (Im et al., 2012; Manthiou et al., 2014; Washburn and Plank, 2002; Yoo et al., 2000; Yoo and Donthu, 2001). For example, the OBE comprising four items was originally developed by Yoo and Donthu (2001) in relation to the validity of the multidimensional brand equity scale: brand awareness, brand associations, perceived quality, and brand loyalty. The results of their study suggest that these four brand equity dimensions are positively related to the OBE.

A follow-up study of Washburn and Plank (2002) was supportive of most of Yoo and Donthu’s (2001) findings in which the components influenced OBE. Likewise, Im et al.’s (2012) study conceptualized a model to identify the effects of four components of destination brand equity on the OBE. That is, a mediating role of brand loyalty between brand equity dimensions and the OBE was investigated on the grounds that brand equity dimensions such as brand awareness, perceived quality, and brand associations will directly influence the OBE. Results of Im’s (2012) study reported that brand awareness and brand associations significantly influenced the OBE, whereas brand image was not significant.

This study adopts the OBE scale to empirically examine the applicability of the measurement in the destination tourism context and to identify the significance of the OBE as a consequence of multidimensional brand equity. Thus, this study adds brand image to the conceptualization of CBDBE model. On this basis, we propose a positive relationship between the destination brand equity measures of awareness, image, and associations (perceived quality and attitude) and the OBE as follows:

H2-1: Destination brand awareness is positively related to overall destination brand equity.

H2-2: Destination brand image is positively related to overall destination brand equity.

H2-3: Destination brand associations are positively related to overall destination brand equity.

Influence of destination brand loyalty on OBE

In the brand equity literature, a definition of brand loyalty is arguably characterized by two different perspectives—attitudinal and behavioral (Chaudhuri and Holbrook, 2001). An attitudinal perspective focuses on a customer’s favorable attitude toward a brand that is expressed by the customer’s repurchase intentions and their commitment (Atilgan et al., 2005; Russell-Bennett et al., 2007). On the other hand, the behavioral perspective emphasizes the customer’s actual loyalty to the brand as reflected in purchase choices (Pappu et al., 2005; Yoo et al., 2000). To overcome the limited definitions of both aspects of loyalty, some researchers suggest that measurement of brand loyalty includes both attitudes and behavior (e.g. Javalgi and Moberg, 1997).

The importance of brand loyalty has been evidenced by its role as a determinant of measuring brand equity through most brand equity studies (e.g. Bianchi et al., 2014; Im et al., 2012; Oh and Hsu, 2014; Yuan and Jang, 2008). For example, Im et al.’s (2012) study conceptualizes brand loyalty between brand equity components (image, awareness, and associations) and OBE. Thus, this study adopted conceptualization of previous studies that OBE has been employed to evaluate the sum of brand equity as consequence of its components (Im et al., 2012; Manthiou et al., 2014; Washburn and Plank, 2002; Yoo et al., 2000; Yoo and Donthu, 2001). In this study, we propose destination brand loyalty as a mediating construct between the three destination brand equity dimensions and OBE.

H3: Destination brand loyalty is positively related to overall destination brand equity.

Study methods

To develop scales, the first stage was a thorough literature review of destination brand equity research. Second, a destination brand equity model was proposed based on this literature. Third, a sample of Hong Kong Chinese tourists who visited Switzerland and Austria as a package tour were surveyed. Data were collected by tour guides working for a travel agency specialized in Chinese inbound to these countries.

The English questionnaire was designed to measure the dimensions of destination brand equity and travel-related and demographic characteristics. To ascertain the clarity of the conceptualization of destination brand equity components, a series of in-depth interviews with 10 Hong Kong tourists in Switzerland as pretest survey was undertaken. A pilot test was then undertaken to confirm the measurement items of the destination brand equity model using 50 Hong Kong tourists visiting Switzerland. After confirming revisions based on the aforementioned procedures, the final version of the questionnaire was completed.

As proposed, destination brand equity consisted of brand awareness, brand image, brand associations, brand loyalty, and OBE. The brand awareness items were designed to measure both knowledge and recognition of a destination (Horng et al., 2012; Kim and Kim, 2005; Lu et al., 2015; Malik and Naeem, 2011; Nel et al., 2009). Items to measure brand image were manifested to elucidate features of Switzerland and Austria as tourism destinations (Echtner and Ritchie, 1993; Ferns and Walls, 2012; Im et al., 2012; Kim and Yoon, 2003; Konecnik and Gartner, 2007; Manthiou et al., 2014; Pike et al., 2010). Items to explain brand associations comprised brand quality and brand attitude as proposed by previous studies (Im et al., 2012; Low and Lamb, 2000; Yoo and Donthu, 2001). Items to measure brand loyalty were also similar to previous studies (Bianchi et al., 2014; Boo et al., 2009; Horng et al., 2012; Im et al., 2012). Finally, OBE was operationalized to capture the strength of intentions to travel (Im et al., 2012; Manthiou et al., 2014; Washburn and Plank, 2002; Yoo et al., 2000; Yoo and Donthu, 2001). All items were measured as five-point Likert-type scales where “1” = “Strongly disagree” and “5” = “Strongly agree.”

A pilot test was conducted in March 2014 with a sample of 50 respondents. The surveys took place in Switzerland at selected tourism hotspot areas where tourists had time to fill in the four-page questionnaire. The locations were in Zürich and around the Lake Zürich area, Lucerne and around Lake Lucerne, Berne and the Bernese Oberland, including the Top of Europe Jungfraujoch attraction, as well as Western Switzerland near Zermatt (Matterhorn), Montreux and Lausanne (by Lake Geneva).

Since this study uses diverse constructs or dimensions to represent the destination brand equity concept, it is necessary to consider validity or the extent to which the concept was accurately measured. To ascertain accuracy of measurement, there are three major types of validity: content, construct, and concurrent (Hair et al., 2009). Content validity was sought through a thorough literature review, pretest, and pilot test. In particular, face validity was checked using a pool of judges (teaching faculty and graduate students) to guarantee comprehensiveness and understanding of the constructs.

To identify concurrent validity, correlation analysis was conducted among the constructs used in this study. If a high level of correlation is observed between similar constructs, concern for a lack of concurrent validity is lessened (Hair et al., 2009). Results of the correlation analysis between the five destination brand equity dimensions revealed that all construct items in both Switzerland and Austria data sets were significant at the 0.001 level, confirming concurrent validity. Later, confirmatory factor analyses of the main survey data set will assess construct validity and discriminant validity.

The main survey was based on a distribution of 500 questionnaires to Hong Kong Chinese tourists who had traveled to Austria and then to Switzerland. Data collection was administered in June and July 2014 by a group travel agency specialized in tours packaging Switzerland and Austria for Chinese tourists. A total of 464 completed questionnaires were used for further analysis (36 questionnaires were incomplete). After conducting factor analysis, structural equation modeling (SEM) was used to assess whether the hypothesized theoretical model was consistent with the collected data for the two country destinations.

Findings

Demographic profile of respondents

Respondents of this study are closely balanced in terms of gender (51.5% female), and most often are married (62.6%). The highest categories for average monthly household income are Hong Kong dollar (HKD) 40,000 to 49,999 (29.9%) and HKD 50,000 to 59,999 (21.3%). About 90% of respondents reside in Hong Kong, while 9.7% reside in Mainland China (with Hong Kong citizenship). The highest level of education is typically college (74.0%). Concerning age, they are primarily in their 30s (28.1%), 40s (27.0%), and 20s (23.2%). With regard to occupation, they are company workers (26.5%), students (18.1%), and retired (9.3%). The most preferred information sources in planning their overseas trip include travel agent/tour operator/airline (30.4%), word of mouth from acquaintances (24.9%), and the Internet (23.9%). The information is reported in Table 1.

Table 1.

Demographic profile (N = 464).

Variable	Category	Percentage	Variable	Category	Percentage
Gender	Male	48.5	Marital status	Married	62.6
	Female	51.5		Single	32.5
	Female	51.5		Others	4.9
Average monthly household income	HKD 9999 or less	3.4	Occupation	Company worker	26.5
	HKD 9999 or less	3.4		Self-employed	7.1
	HKD 10,000–19,999	1.5		Professional	8.0
	HKD 10,000–19,999	1.5		Housewife	4.3
	HKD 20,000–29,999	13.0		Student	18.1
	HKD 20,000–29,999	13.0		Retired	9.3
	HKD 30,000–39,999	20.4		Agricultural/fishery	2.2
	HKD 30,000–39,999	20.4		Government/military	3.2
	HKD 40,000–49,999	29.9		Management/executive	6.7
	HKD 40,000–49,999	29.9		Sales/service employees	7.3
	HKD 50,000–59,999	21.3		Education	6.5
	HKD 60,000–69,999	5.6		Others	0.8
	HKD 70,000 or above	4.9		Others	0.8
Age (years)	20	23.2	The most preferred information source in planning overseas trip	Word of mouth from acquaintances	24.9
	30	28.1		Word of mouth from acquaintances	24.9
	40	27.0		Internet	23.9
	50	12.4		Internet	23.9
	50	12.4		Advertisement (TV/radio/magazine)	7.3
	≥60	9.2		Advertisement (TV/radio/magazine)	7.3
	≥60	9.2		Travel agency/tour operator/airlines	30.4
Education	Middle school or below	1.1		Travel agency/tour operator/airlines	30.4
	High school	17.1		Media (movie/TV drama/music)	7.3
	College	74.0		Books/magazine	6.4
	Graduate school	7.8
Residence	Hong Kong	90.1
Residence	Mainland China	9.7

HKD: Hong Kong dollar.

Factor analyses and reliability tests

Table 2 shows the results of exploratory factor analyses for brand image, brand awareness, brand associations, brand loyalty, and OBE. The principal components method using varimax rotation was adopted to extract the underlying factors. Results of the analysis using the 17 brand image items reveal a four-factor solution where eigenvalues (6.86, 1.79, 1.51, and 1.05) are greater than 1.0 on the scree plot. The factor model explains 65.93% of the variance. Bartlett’s test of sphericity confirms that one or more factors exist (p = 0.000), and the KMO measure of sampling adequacy (0.84) validates the factor structure. Factor loadings are mostly greater than 0.60, except for a few items that fall as low as 0.365. The reliability αs within the four domains exceed 0.70, meeting the criterion recommended by Nunnally (1978) for internal consistency. The mean values on the 17 items range from 3.64 to 4.60, while the grand means on the four domains are 4.48, 3.68, 4.22, and 4.01, respectively. The domain factors are labeled “quality tourism facilities,” “cultural resources,” “hospitality and amusement,” and “opportunities and accessibility.”

Table 2.

Results of factor analyses and reliability tests.

Constructs	Items	Factor loading	Mean
Brand awareness (2.84^a, 94.1%^b, α = 0.79^c)	I recognize ______ as a travel destination among other countries.	0.970	4.30
	I know what ______ looks like.	0.942	4.27
	I am aware of ______.	0.940	4.31
Brand image	Domain 1: Quality tourism facilities (6.86, 44.22%, α = 0.76)
	High quality of infrastructure	0.941	4.57
	Availability outdoor recreation activities (camping, hiking, canoeing, technology)	0.879	4.44
	Advanced technology and economy	0.814	4.58
	Good shopping facilities	0.625	4.44
	Well known for luxury hotels and hospitality facilities	0.592	4.27
	Standard hygiene and cleanliness	0.522	4.60
	Domain 2: Cultural resources (1.79, 12.06%, α = 0.70)
	Interesting classic music events, opera and theatre	0.900	3.64
	Rich in cultural/historical heritage	0.853	3.67
	Availability to visit featured destination of movies or TV dramas	0.476	3.74
	Domain 3: Hospitality and amusement (1.51, 8.71%, α = 0.71)
	Friendly local people	0.755	4.41
	Interesting cultural events/festivals	0.583	4.11
	Interesting cultural historical attraction	0.577	4.59
	A wide choice of accommodations	0.573	4.07
	Availability of water sports	0.419	3.90
	Domain 4: Opportunities and accessibility (1.05, 6.03%, α = 0.72)
	Interesting sightseeing opportunities	0.737	4.10
	Acceptable cost of accommodations	0.697	4.12
	Less communication (language) barrier	0.365	3.80
Brand associations (2.83, 94.48%, α = 0.97)	______ provides tourism attractions with high quality.	0.978	4.26
Brand associations (2.83, 94.48%, α = 0.97)	Service quality provided by ______ is high.	0.966	4.22
	The overall quality of ______ as a travel destination is high.	0.930	4.23
Brand loyalty (4.35, 87.05%, α = 0.69)	I am loyal to ______.	0.968	4.02
Brand loyalty (4.35, 87.05%, α = 0.69)	______ would be my first choice if I had an opportunity to travel overseas.	0.944	3.97
	I would strongly recommend ______ to someone who seeks my advice.	0.937	4.01
	I would intend to travel ______ in the next 5 years.	0.870	3.98
	I still consider a trip to ______ even though the travel cost was increased.	0.833	3.97
Overall brand equity (2.85, 94.85%, α = 0.69)	It makes sense to travel ______ instead of any other countries, even if they are the same.	0.964	3.95
	Even if another country has the same features as ______, I would prefer to travel ______.	0.964	3.93
	Even though there is another country as good as ______, I prefer to travel ______.	0.953	3.92

Note: Items were measured as five-point Likert-type scales (1 = Strongly disagree, 3 = Neutral, 5 = Strongly agree).

^aEigenvalue.

^bVariance explained.

^cReliability α.

Results of the factor analysis using three brand awareness items generate a single underlying domain with an eigenvalue of 2.83 on the scree plot. The factor explains 94.16% of the variance. The reliability α is 0.79, showing high internal consistency of items. The mean values of the three items are 4.30, 4.27, and 4.31, while the grand mean is 4.29.

Similarly, the factor analysis for the three items of brand associations results in a one-factor solution. The factor’s eigenvalue is 2.83 and the factor explains 94.48% of the variance. Factor loadings on the three items are greater than 0.93. Since the reliability α is 0.97, the one-factor model is considered to have internal consistency of items on the one factor. The mean scores on the three items are 4.22, 4.23, and 4.26, respectively, and the grand mean is 4.24.

Factor analysis for the five items of brand loyalty produces a one-factor structure. The eigenvalue of the factor is 4.35 and the factor model explains 87.05% of the variance. Factor loadings on all three items range from 0.83 to 0.94. Since the reliability α is 0.69, the one-factor structure is regarded as having internal consistency. The mean scores of the three items span from 3.97 to 4.02, and the grand mean is 3.99.

Results of the factor analysis for the three items of OBE also reveal a single factor. The eigenvalue of the factor is 2.85 and the factor solution accounts for 94.85% of the variance. Factor loadings on all three items are greater than 0.95. Since the reliability α is 0.69, the one-factor structure proves high internal consistency. The mean scores of the three items are 3.95, 3.93, and 3.92, respectively, and the grand mean is 3.93.

Results of confirmatory factor analyses

Prior to the SEM procedures, a confirmatory factor analysis (CFA) was conducted to produce the proposed measurement model that was in turn used to certify if a latent variable influences an observed variable (Hair et al., 2009). A correlation matrix employed for CFA for the Switzerland data set is exhibited in Table 3. As Table 4 presents, results of CFA analysis are acceptable because fit indices are satisfactory with the exception of the χ ² value (χ ²(86.8), p = 0.000). However, since the χ ² is sensitive to the sample size, interpretation of other fit indices is substantially more meaningful (Kline, 1998). Other goodness-of-fit (GFI) indices support the fit: GFI = 0.96, adjusted goodness-of-fit index (AGFI) = 0.89, comparative fix index (CFI) = 0.95, Tucker–Lewis index (TLI) = 0.90, root mean residual (RMR) = 0.01, and root mean square of approximation (RMSEA) = 0.11.

Table 3.

Correlation matrix (Switzerland).

	1	2	3	4	5
1	1.000	–	–	–	–
2	0.128	1.000	–	–	–
3	0.727	0.158	1.000	–	–
4	0.302	0.153	0.457	1.000	–
5	0.184	0.177	0.368	0.785	1.000
Mean	4.29	4.10	4.23	3.99	3.93
Standard deviation	0.56	0.45	0.50	0.47	0.52

Construct 1: brand awareness; construct 2: brand image; construct 3: brand association; construct 4: brand loyalty; construct 5: overall brand equity.

Note: All correlation coefficients were significant at the 0.001 level.

Table 4.

Results of confirmatory factor analyses (Switzerland).

Constructs	Unstandardized coefficient	t-value	p-value	Factor loading	SMC	AVE^a	CCR^b
Brand awareness	1.000			N/A
Quality tourism facilities (domain 1)	1.027	12.337*	0.000	0.717	0.514
Cultural resources (domain 2)	1.249	11.822*	0.000	0.675	0.456	0.760	0.926
Hospitality and amusement (domain 3)	1.017	12.969*	0.000	0.790	0.625
Opportunities and accessibility (domain 4)	1.000	–^c		0.666	0.443
Brand associations	1.000			N/A
Brand loyalty	1.000			N/A
Overall brand equity	1.000			N/A
χ ² = 86.825 (df = 14, p = 0.000), GFI = 0.957, AGFI = 0.889, CFI = 0.953, TLI = 0.900, RMR = 0.013, RMSEA = 0.106

AVE: average variance extracted; CCR: composite construct reliability; N/A: not available; GFI: goodness-of-fit; AGFI: adjusted goodness-of-fit index; CFI: comparative fix index; TLI: Tucker–Lewis index; RMR: root mean residual; RMSEA: root mean square of approximation.

Note: In the measurement model, the estimated parameter was fixed at 1.0.

^aAVE = ∑standardized loadings²/∑standardized loadings² + ∑∊_j , where ∊_j is the measurement error.

^bCCR = (∑standardized loadings)²/(∑standardized loadings)² + ∑∊_j . −^c indicates that the estimated parameter was fixed at 1.0.

*p < 0.001.

Similarly, the correlation matrix employed to conduct CFA for the Austria data set is shown in Table 5. The GFI indices for the “Austria” data set, shown in Table 6, support the measurement model except for the χ ² value (χ ²(14) = 84.8, p = 0.000). Like the interpretation of the Switzerland data set, other acceptable GFI indices are GFI = 0.96, AGFI = 0.90, CFI = 0.96, TLI = 0.93, RMR = 0.11, and RMSEA = 0.11.

Table 5.

Correlation matrix (Austria).

	1	2	3	4	5
1	1.000	–	–	–	–
2	0.29	1.000	–	–	–
3	0.71	0.33	1.000	–	–
4	0.31	0.38	0.52	1.000	–
5	0.23	0.37	0.47	0.85	1.000
Mean	4.26	4.25	4.18	3.92	3.88
Standard deviation	0.57	0.43	0.53	0.53	0.57

Construct 1: brand awareness; construct 2: brand image; construct 3: brand association; construct 4: brand loyalty; construct 5: overall brand equity.

Note: All correlation coefficients were significant at the 0.001 level.

Table 6.

Results of confirmatory factor analyses (Austria).

Constructs	Unstandardized coefficient	t-Value	p-Value	Factor loading	SMC	AVE^a	CCR^b
Brand awareness	1.000			N/A
Quality tourism facilities (domain 1)	1.091	12.186*	0.000	0.601	0.569
Cultural resources (domain 2)	1.331	12.372*	0.000	0.773	0.598
Hospitality and amusement (domain 3)	1.096	12.970*	0.000	0.856	0.733	0.817	0.946
Opportunities and accessibility (domain 4)	1.000	-^c	-^c	0.601	0.361
Brand associations	1.000			N/A
Brand loyalty	1.000			N/A
Overall brand equity	1.000			N/A
χ ² = 84.752 (df = 14, p = 0.000), GFI = 0.961, AGFI = 0.901, CFI = 0.963, TLI = 0.928, RMR = 0.010, RMSEA = 0.105

Note: In the measurement model, the estimated parameter was fixed at 1.0.

^aAVE = ∑standardized loadings²/∑standardized loadings² + ∑∊_j , where ∊_j is the measurement error.

^bCCR = (∑standardized loadings)²/(∑standardized loadings)² + ∑∊_j .

-^cindicates that the estimated parameter was fixed at 1.0.

*p < 0.001.

The CFA reliability, evaluated through assessing composite construct reliability (CCR), is deemed reliable when the CCR value exceeds 0.70 (Fornell and Larcker, 1981; Hair et al., 2009). The construct validity of the two data sets meets the criterion because the CCR values are 0.93 (Table 4) and 0.95 (Table 6), respectively. In addition, it is possible that validity can be evaluated by the magnitude of t-values between each construct and the average variance extracted (AVE) (Fornell and Larcker, 1981). Significant t-values on their latent constructs are observed for all items of the four domains in both data sets. These results evidenced that high convergent and construct validity guarantee the measurement scales for each construct. Additionally, the convergent validity is acceptable, with AVE values of 0.76 (Table 4) and 0.82 (Table 6) for the two data sets.

Discriminant validity refers to the extent to which a given construct differs from other constructs. As a method to identify the discriminant validity, the AVE for each construct should be greater than the squared correlations between the construct and all other constructs (Fornell and Larcker, 1981). In Tables 4 and 6, the lowest AVE value is 0.76 for the Switzerland data set, whereas the lowest AVE value is 0.82 for the Austria data set. The highest squared correlation between each pair of constructs is 0.62 for the Switzerland data set (Table 3), while the highest squared correlation between each pair of constructs is 0.72 for the Austrian data set (Table 5). Conclusively, this measurement model confirms discriminant validity because the lowest AVE values exceed the highest squared correlation for all data.

Structural equation modeling

Successful assessment of the proposed measurement model in multifacets of GFI, reliability, and validity is a prerequisite for conducting SEM analysis. After acceptable assessment of the tests, a SEM with the maximum likelihood method of estimation is adopted to assess whether the hypothesized theoretical model indicates consistency with the data. Table 7 reports an inputted covariance matrix. Results of testing SEM models show the GFI indices for the hypothesized structural model on two different data sets.

Table 7.

Correlation matrix.

Construct	Switzerland (N = 466)								Austria (N = 456)
Construct	1	2	3	4	5	6	7	8	1	2	3	4	5	6	7	8
1	1.00								1.00
2	0.48**	1.00							0.61**	1.00
3	0.59**	0.51**	1.00						0.63**	0.66**	1.00
4	0.43**	0.51**	0.52**	1.00					0.47**	0.38**	0.55**	1.00
5	0.20**	0.00	0.09	0.15**	1.00				0.28**	0.25**	0.25**	0.17**	1.00
6	0.15**	0.12*	0.05	0.17**	0.73**	1.00			0.29**	0.28**	0.24**	0.25**	0.71**	1.00
7	0.04	0.12**	0.14**	0.19**	0.30**	0.46**	1.00		0.20**	0.38**	0.34**	0.32**	0.31**	0.52**	1.00
8	0.09*	0.09*	0.19**	0.20**	0.18**	0.37**	0.79**	1.00	0.25**	0.34**	0.33**	0.27**	0.23**	0.47**	0.85**	1.00
Mean	4.48	3.69	4.22	4.01	4.30	4.23	3.99	3.93	4.46	4.21	4.27	4.05	4.26	4.18	3.92	3.88
Standard deviation	0.53	0.68	0.48	0.55	0.56	0.50	0.47	0.52	0.50	0.59	0.44	0.57	0.57	0.53	0.53	0.57

Construct 1: quality tourism facilities; construct 2: cultural resources; construct 3: hospitality and amusement; construct 4: opportunities and accessibility; construct 5: brand awareness; construct 6: brand associations; construct 7: brand loyalty; construct 8: overall brand equity.

*p < 0.01; ***p < 0.05.

First, the Switzerland model shows that because the χ ² value is statistically significant (χ ²(14) = 86.83, p = 0.000), the model is not adequate. However, the other overall fit indices are acceptable, demonstrating GFI = 0.96, AGFI = 0.89, CFI = 0.95, TLI = 0.93, RMR = 0.01, and RMSEA = 0.11. Among the seven estimated path coefficients, six are statistically significant at the 0.05, 0.01, or 0.001 level. The significant relationships are found for hypothesis 1-2 (γ ₁₂ = 0.10, t = 2.13, p < 0.05), hypothesis 1-3 (γ ₁₃ = 0.49, t = 8.23, p < 0.001), hypothesis 2-1 (γ ₂₁ = −0.13, t = −3.21, p < 0.01), hypothesis 2-2 (γ ₂₂ = 0.08, t = 2.55, p < 0.05), hypothesis 2-3 (γ ₂₃ = 0.10, t = 2.31, p < 0.05), and hypothesis 3 (β ₂₁ = 0.76, t = 23.83, p < 0.001). Hypothesis 1-1, that destination brand awareness is positively related to destination brand loyalty, is not supported because the path was not significant (p = 0.233). In addition, the path to test hypothesis 2-1 was significant at the 0.01 level, but the sign value was negative. Therefore, the hypothesis was not supported.

Second, the examination of the Austrian model indicates that except for the χ ² value (χ ²(14) = 84.75, p = 0.000), the overall fit indices are acceptable, showing GFI = 0.96, AGFI = 0.90, CFI = 0.96, TLI = 0.91, RMR = 0.01, and RMSEA = 0.11. All seven estimated path coefficients show statistical significance at the 0.05, 0.01, or 0.001 level. Significant relationships are found for hypothesis 1-1 (γ ₁₁ = −0.16, t = −2.82, p < 0.05), hypothesis 1-2 (γ ₁₂ = 0.27, t = 5.91, p < 0.001), hypothesis 1-3 (γ ₁₃ = 0.54, t = 9.64, p < 0.001), hypothesis 2-1 (γ ₂₁ = −0.13, t = −3.70, p < 0.001), hypothesis 2-2 (γ ₂₂ = 0.07, t = 2.36, p < 0.05), hypothesis 2-3 (γ ₂₃ = 0.13, t = 3.45, p < 0.001), and hypothesis 3 (β ₂₁ = 0.79, t = 26.13, p < 0.001). Although the path to identify hypothesis 1-1 was significant at the 0.01 level, but the sign was negative. Therefore, the hypothesis was not supported. The results are illustrated in Table 8.

Table 8.

SEM analysis.

Path	Unstandardized coefficient	Standard error	Standardized coefficient	t-value		Total effect	Indirect effect	Decision
Switzerland χ ²(14) = 86.825 (p = 0.000), GFI = 0.957, AGFI = 0.889, CFI = 0.953, TLI = 0.933, RMR = 0.013, RMSEA = 0.106
Hypothesis 1-1 (γ ₁₁)	−0.059	0.050	−0.071	−1.193	0.233	−0.071	0.000	Reject
Hypothesis 1-2 (γ ₁₂)	0.126	0.059	0.099	2.131*	0.033	0.099	0.000	Accept
Hypothesis 1-3 (γ ₁₃)	0.462	0.056	0.493	8.230**	0.000	0.493	0.000	Accept
Hypothesis 2-1 (γ ₂₁)	−0.123	0.038	−0.133	−3.212**	0.001	−0.187	−0.051	Reject (significant but negative sign)
Hypothesis 2-2 (γ ₂₂)	0.116	0.046	0.083	2.545*	0.011	0.158	0.107	Accept
Hypothesis 2-3 (γ ₂₃)	0.106	0.046	0.102	2.313*	0.021	0.479	0.392	Accept
Hypothesis 3 (β ₂₁)	0.849	0.036	0.764	23.827***	0.000	0.764	0.000	Accept
Austria χ ²(14) = 84.752 (p = 0.000), GFI = 0.961, AGFI = 0.901, CFI = 0.963, TLI = 0.913, RMR = 0.010, RMSEA = 0.105
Hypothesis 1-1 (γ ₁₁)	−0.143	0.051	−0.155	−2.815*	0.005	−0.155	0.000	Reject (significant but negative sign)
Hypothesis 1-2 (γ ₁₂)	0.384	0.065	0.273	5.908***	0.000	0.273	0.000	Accept
Hypothesis 1-3 (γ ₁₃)	0.526	0.055	0.535	9.636***	0.000	0.535	0.000	Accept
Hypothesis 2-1 (γ ₂₁)	−0.131	0.035	−0.131	−3.704***	0.000	−0.253	−0.123	Accept
Hypothesis 2-2 (γ ₂₂)	0.108	0.046	0.071	2.357*	0.018	0.287	0.216	Accept
Hypothesis 2-3 (γ ₂₃)	0.143	0.041	0.133	3.451***	0.000	0.556	0.423	Accept
Hypothesis 3 (β ₂₁)	0.861	0.033	0.791	26.131***	0.000	0.791	0.000	Accept

GFI: goodness-of-fit; AGFI: adjusted goodness-of-fit index; CFI: comparative fix index; TLI: Tucker–Lewis index; RMR: root mean residual; RMSEA: root mean square of approximation.

*p < 0.05; **p < 0.01; ***p < 0.001.

Conclusion, implications, and future research

Conclusion and discussion

This study tests the applicability of the CBDBE framework presented by previous studies (e.g. Boo et al., 2009; Im et al., 2012; Konecnik and Gartner, 2007; Yoo and Donthu, 2001), by measuring the OBE scale and its relationship with four dimensions for two visited countries. The two countries, Austria and Switzerland, were chosen to validate the robustness of the destination brand equity model with the OBE scale. Several significant observations can be made about differences in findings between the present study and previous studies.

First, two constructs (brand image and brand associations) have significant impact on brand loyalty. The results correspond to those of previous studies (Boo et al., 2009; Faullant et al., 2008; Im et al., 2012; Pike et al., 2010; Qu et al., 2011; Yoo et al., 2000) in which the results show that a favorable and strong destination image is an important influencer of visitor loyalty in terms of intention to revisit, price premium, and willingness to recommend the destination. The importance of brand associations is its foundation for visitor loyalty, providing travelers with a specific reason to visit and encouraging positive word of mouth.

Second, and in contrast to the first finding, no significant relationship was found between brand awareness and brand loyalty for either destination. Abundant evidence indicates that brand awareness is considered a key element of brand equity in marketing and tourism disciplines (Boo et al., 2009; Chen and Myagmarsuren, 2010; Keller, 2003; Konecnik and Gartner, 2007; Yoo et al., 2000). However, given that the results of this study are the same as that of Im et al.’s (2012) research, more evidence is needed to support the notion that a visitor’s awareness of a destination is not necessarily linked to one’s behavioral loyalty in the destination brand equity model.

More specifically, the results are understandable because loyalty to a tourism destination can vary according to its distance to the origin of tourists (McKercher et al., 2008). Unlike readily available commodities, when travel is involved, tourists may build more loyalty for short-haul destinations because they can assess nearby places relatively easily, investing less time and budget to do so. However, long-haul travel is different, typically requiring greater investment than short-haul travel. From Hong Kong to Austria and Switzerland requires relatively more travel cost, travel time, and possibly overcoming other travel constraints such as language and cultural differences than is the case for intraregional travel. Hong Kong Chinese tourists may consider a trip to the Alps to be a once-in-lifetime event. In addition, long-haul travelers have stronger intention to seek novelty than short-haul tourists (Crouch, 1994; McKercher et al., 2008; Pike, 2009). Therefore, building awareness of long-haul destinations through actual travel may decrease loyalty, in the traditional sense, in that it may actually encourage visitors to choose other destinations for future travel.

Another interpretation of this finding is that unlike other brand components such as brand image or associations, the concept of awareness is not directly or obviously predictive of the traveler experience. For example, “I recognize ___ as a travel destination among other countries,” “I know what ___ looks like,” and “I am aware of ___,” in our information-flooded era when online social media and the Internet are prevalent, are not necessarily strong measures of brand loyalty to tourism destinations. Moreover, the power of awareness may change during travel. As a result, awareness needs more discussion to determine its role in the conceptualization of tourism destination brand equity.

Third, brand associations (brand quality and brand attitude) had a greater effect than brand image on brand loyalty for both Austria (brand image: γ ₁₂ = 0.27, t-value = 5.91; brand associations: γ ₁₃ = 0.54, t-value = 9.64) and Switzerland (brand image: γ ₁₂ = 0.10, t-value = 2.13; brand associations: γ ₁₃ = 0.49, t-value = 8.23). Given that the factor analyses produced the same labels for underlying dimensions of destination images for both countries, such a difference may be a result of some overlapping between images of the two as travel destinations perceived by Hong Kong Chinese travelers. Further research is needed to identify the efficacy of the effects of brand associations and brand image on brand loyalty.

Fourth, the results of the study show that brand image is positively related to OBE in both countries (Austria: γ ₂₂ = 0.07, t-value = 2.36; Switzerland: γ ₂₂ = 0.08, t-value = 2.55). The effect of the three dimensions on OBE is somewhat different from that of previous studies that show that the relationship is not significant (Im et al., 2012). Such a difference may be a result of destination image differences between the target samples. In this study, Hong Kong Chinese tourists perceive a favorable destination image for both Austria and Switzerland, which positively affects OBE. This confirms that destination image is a core dimension of brand equity, as suggested in previous studies.

Fifth, brand awareness negatively affects OBE for both Austria (γ ₂₁ = −0.13, t-value = −3.70) and Switzerland (γ ₂₁ = −0.13, t-value = -3.21). The results are different from previous studies that suggest brand awareness positively influences brand equity (Chen and Myagmarsuren, 2010; Im et al., 2012; Konecnik and Gartner, 2007; Washburn and Plank, 2002; Yoo and Donthu, 2001). For example, the relationship between brand awareness and brand equity is positive in the case of industrial business purchasing because of brand loyalty. That is, customers choose well-recognized brands and it strengthens future intention to repurchase those brands (e.g. Dioko and So, 2012; Hyun, 2009; Lu et al., 2015; Prasad and Dev, 2000). Likewise, short-haul travel facilitates return to the same place because it requires less effort, less information search, and fewer constraints (e.g. travel cost, time, schedule conflict, accompanied persons to travel together, poor health, and safety).

However, potential long-haul tourists appear to want to choose other destinations, perhaps, because of a desire for novelty seeking in untraveled interregional destinations. In the study context of a long-haul trip from Hong Kong to Europe, many constraints may exist from cost to safety concerns. Moreover, since long-haul overseas travel is still uncommon for most Chinese, potential tourists may prefer to choose new, untraveled destinations if there is opportunity to make a long-haul overseas trip.

Sixth, both studies show positive results in examining the impact of brand associations on OBE. As consistent with numerous studies that document brand associations as frequently cited dimensions of brand equity, this study also supports that tourists with strong brand associations related to the destination tend to act accordingly in destination choice.

Seventh, it is revealed that brand loyalty is the most important brand equity dimension for both countries (Austria: β ₂₁ = 0.79, t-value = 26.13; Switzerland: β ₂₁ = 0.76, t-value = 23.83) supporting past destination brand studies. The results indicate that except for brand awareness, brand loyalty has the greatest impact on OBE. In this study, a tourist with strong brand loyalty is more likely to showcase unconditional preference for both countries by indicating that they prefer to travel to Austria and Switzerland even if they are different countries. In addition, this study partially ascertained a much stronger relationship between brand loyalty and brand equity than that between brand awareness and brand equity or between brand associations and brand equity as suggested by previous studies (e.g. Boo et al., 2009; Im et al., 2012; Konecnik and Gartner, 2007; Yoo and Donthu, 2001; Yoo et al., 2000).

Implications

With tourism becoming a major source of income in most regions of the world, hundreds of destinations now compete with one another in a global marketplace. The importance of destination brand equity lies in its vital role to offer a unique selling proposition so that consumers can differentiate a brand from many other destination brands in the international travel market (Morgan and Pritchard, 2001). In order to differentiate a destination from competitors, destination marketers should know vital components of what makes up brand equity to develop effective destination marketing strategies.

Findings from this study suggest several practical implications for destination marketers in Austria and Switzerland. The results demonstrate vital components of what makes up brand equity, that is, brand image, brand associations, and brand loyalty. These are important brand assets of the Hong Kong Chinese traveler’s holistic perception of the extra value derived from the destination brand names, which indicates that increased destination branding efforts by a Destination Management Organization (DMO) have the potential to pay off in the long run. In particular, the mediating role of brand loyalty is confirmed in relation to brand equity for both countries. It implies that Hong Kong travelers have a lot of positive and strong brand images related to Austria and Switzerland as destination brands, perceive the brands as high quality, and hold positive attitudes (brand associations) toward the destinations, and are loyal to them.

Therefore, in order to attract more Hong Kong travelers to their countries, destination marketers should capitalize on the current strength of the dimensions with an emphasis on enhancement of brand loyalty. Since there is a positive effect of the brand image on OBE and the image seems to overlap for long-haul markets such as China, destinations with overlapping images may think of joining market forces and budgets instead of costly competition against each other (e.g. Bieger et al., 2009; Blain et al., 2005; Buhalis, 2000; Jamal and Getz, 1995; Ness et al., 2014). Here, Switzerland and Austria could maintain separate marketing strategies in short-haul markets and combine marketing activities in far markets. From a theoretical point of view, this is understandable, and practiced in other sectors (e.g. aviation and hospitality), but requires a difficult change of the thinking and structures of National tourism Organizations (NTOs) and related government bodies to implement (Garnes and Mathisen, 2014).

In comparing the OBE of the two countries perceived by Hong Kong Chinese tourists as long-distance travel destinations, Austria was found to be better evaluated by Hong Kong travelers than Switzerland. It may require caution for immediate marketing implications due to possible substitutability of the two destinations from the perspective of Hong Kong Chinese travelers. As shown by results of data analyses, it was confirmed that the travelers perceived similar destination images of Austria and Switzerland as neighboring countries in terms of various tourism facilities, cleanliness, cultural resources, hospitality, amusement, and sightseeing opportunities. Further research, however, is called for to clarify whether the difference in perception of brand equity, through its dimensions, really exists in the minds of Hong Kong Chinese travelers. An interesting result of this study is that a negative impact of brand awareness on OBE has been observed in both countries, in contrast to previous studies in intraregional contexts. Again, it is closely related to a long-haul tourist’s motivation to travel to unexperienced destinations.

According to Aaker’s (1991) definition, brand awareness is the ability of the potential buyer to recognize and recall a brand. In an early consumer choice stage, brand awareness may have strong impact on brand preferences, which is strongly associated with brand equity. When the consumer in the travel industry has a fairly high degree of awareness and familiarity with the brand, however, the linkage between brand awareness and brand equity becomes weak. It implies a concern when the concept of brand equity is introduced from consumer behavior to the tourism destination setting because of existence of differences in characteristics of products between general consumer commodities and travel.

In this regard, destination marketers should understand the brand equity creation process in the target market to capitalize their marketing resources on brand awareness to generate brand equity. In addition, a cross-cultural validation of the brand equity formation process may be taken into account to formulate a marketing plan in international tourism markets. This leads again to the conclusion presented earlier that a partial or marketwise collaboration of the competing destinations, Austria and Switzerland, could be an effective strategy, or both destinations need to work on sharpening and clarifying their image against each other to remain differentiated (Garnes and Mathisen, 2014; Ness et al., 2014).

Study limitations and suggestions for future research

Although this study provides theoretical and practical insights, several limitations should be noted. First, there may be other dimensions that influence brand equity formation. The antecedent variables used in the study were limited to those repeatedly mentioned and partially supported by empirical results in past research. Therefore, the results of this study may have excluded additional dimensions of brand equity that might have helped better explain tourist destination choice behavior. Future research should investigate additional destination brand dimensions that may influence OBE. Second, the population of this study was limited to Hong Kong Chinese tourists who visited Switzerland and Austria. Thus, the results may not be generalizable to visitors with different cultural backgrounds or to other far markets. More research dealing with cross-cultural elements may reveal different processes of brand equity formation in different cultures and/or other long-haul markets with similar cultures.

The findings of the study offer thought for future research in several aspects. First, additional research needs to further investigate the role of brand awareness in the brand equity creation process as the present study identified a negative impact of brand awareness on brand equity in contrast to previous studies. More insights are required to determine whether the negative relationship between these variables is related to distance (geographically and/or culturally), that is, the further the destination, the weaker the relationship between brand awareness and brand equity. Such a negative relationship can be revealed by comparing the model among groups of different brand awareness levels of short-haul/intraregional versus long-haul/interregional destinations.

Second, replications of the CBDBE model in this study are strongly encouraged to improve validity and reliability of the model by reevaluating the items selected here, selecting more discriminating indicators for brand equity, and extending those dimensions to subdimensions. For example, a brand image can be further divided into cognitive, affective, and conative as suggested by Konecnik and Gartner (2007). In particular, a cross-cultural approach is recommended for more generalizable measurement of brand equity. A cross-cultural validation of the brand equity formation process is important to formulate a marketing strategy in international markets (e.g. Bianchi et al., 2014; Im et al., 2012; Yoo, 2002). Thus, it is hoped that the CBDBE model developed and tested here helps to advance our understanding of destination brand equity in an ever-expanding travel marketplace.

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: This project was funded by The Hong Kong Polytechnic University (G-UC91).

Note

References

Aaker

(1991) Managing Brand Equity. New York: The Free Press.

Aaker

(1996a) Building Strong Brands. New York: The Free Press.

Aaker

(1996b) Measuring brand equity across products and markets. California Management Review 38(3): 102–130.

Atilgan

Aksoy

Akinci

(2005) Determinants of the brand equity: a verification approach in the beverage industry in Turkey. Marketing Intelligence and Planning 23(3): 237–248.

BFS (2015) Schweizer Tourismusstatistik 2008-2014. Bern/Neuenburg: BFS indicates Swiss National Bureau of Statistics.

Bianchi

Pike

Lings

(2014) Investigating attitudes towards three South American destinations in an emerging long haul market using a model of consumer-based brand equity (CBBE). Tourism Management 42: 215–223.

Bieger

Beritelli

Laesser

(2009) Size matters!-Increasing DMO effectiveness and extending tourist destination boundaries. Turizam: znanstveno-stručni časopis 57(3): 309–327.

Blain

Levy

Ritchie

JRB

(2005) Destination branding: insights and practices from destination management organizations. Journal of Travel Research 43: 328–338.

Boo

Busser

Baloglu

(2009) A model of customer-based brand equity and its application to multiple destinations. Tourism Management 30(2): 219–231.

10.

Buhalis

(2000) Marketing the competitive destination of the future. Tourism Management 21(1): 97–116.

11.

Cai

(2002) Cooperative branding for rural destinations. Annals of Tourism Research 29(3): 720–742.

12.

Camarero

Garrido

Vicente

(2010) Components of art exhibition equity for internal and external visitors. Tourism Management 31: 495–504.

13.

Chaudhuri

Holbrook

(2001) The chain of effects from brand trust and brand affect to brand performance: the role of brand loyalty. Journal of Marketing 65(2): 81–93.

14.

Chen

Myagmarsuren

(2010) Exploring relationships between Mongolian destination brand equity, satisfaction and destination loyalty. Tourism Economics 16(4): 981–994.

15.

China Outbound Tourism Research Institute (2015) China’s “second wave” of outbound tourists: new destinations and new consumption patterns. Available at: www.china-outbound.com (accessed 10 May 2016).

16.

Chon

(1992) The role of destination image in tourism: an extension. The Tourist Review 47(1): 2–8.

17.

Crouch

(1994) Demand elasticities for short-haul versus Long-haul tourism. Journal of Travel Research 33(2): 2–7.

18.

Dioko

LDA

SIA

(2012) Branding destinations versus branding hotels in a gaming destination—examining the nature and significance of co-branding effects in the case study of Macao. International Journal of Hospitality Management 31(2): 554–563.

19.

Echtner

Ritchie

JRB

(1993) The measurement of destination image: an empirical assessment. Journal of Travel Research 31: 3–13.

20.

Ekinci

Hosany

(2006) Destination personality: an application of brand personality to tourism destination. Journal of Travel Research 45: 127–139.

21.

Elliot

Papadopoulos

Kim

(2011) An integrated model of place image: exploring relationship between destination, product, and country image. Journal of Travel Research 50(5): 520–534.

22.

Faullant

Matzler

Füller

(2008) The impact of satisfaction and image on loyalty: the case of Alpine ski resorts. Managing Service Quality 18(2): 163–178.

23.

Ferns

Walls

(2012) Enduring travel involvement, destination brand equity, and travelers’ visit intentions: a structural model analysis. Journal of Destination Marketing & Management 1: 27–35.

24.

Fornell

Larcker

(1981) Structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18(1): 39–50.

25.

Garnes

Mathisen

(2014) Organizational commitment of directors in collaborative tourist organizations: mediating effects of boardroom behavior. Journal of Travel Research 53(4): 448–461.

26.

Gartner

(1993) Image formation process. Journal of Travel and Tourism Marketing 2(2/3): 191–215.

27.

Gomez

Lopez

Molina

(2015) A model of tourism destination brand equity: the case of wine tourism destinations in Spain. Tourism Management 51: 210–222.

28.

Hair

Anderson

Tatham

. (2009) Multivariate Data Analysis, 7th ed. Upper Saddle River: Prentice Hall.

29.

Hankinson

(2004) Relational network brands: towards a conceptual model of place brands. Journal of Vacation Marketing 10(2): 109–121.

30.

Horng

J-S

Liu

C-H

Chou

H-Y

. (2012) Understanding the impact of culinary brand equity and destination familiarity on travel intentions. Tourism Management 33: 815–824.

31.

Hsu

Assaf

(2012) A customer-based brand equity model for upscale hotels. Journal of Travel Research 51(1): 81–93.

32.

Hyun

(2009) Creating a model of customer equity for chain restaurant brand formation. International Journal of Hospitality Management 28(4): 529–539.

33.

Kim

Elliot

. (2012) Conceptualizing the brand equity dimensions from a consumer-based brand equity perspective. Journal of Travel & Tourism Marketing 29(4): 385–403.

34.

Jamal

Getz

(1995) Collaboration theory and community tourism planning. Annals of Tourism Research 22(1): 186–204.

35.

Javalgi

Moberg

(1997) Service loyalty: implications for service providers. The Journal of Services Marketing 11(3): 165–179.

36.

Kayaman

Arasli

(2007) Customer based brand equity: evidence from the hotel industry. Managing Service Quality 17(1): 92–109.

37.

Keller

(1993) Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing 57: 1–22.

38.

Keller

(2003) Strategic Brand Management: Building, Measuring and Managing Brand Equity, 4th ed. New York: Pearson.

39.

Kim

(2005) The relationship between brand equity and firms’ performance in luxury hotels and chain restaurant. Tourism Management 26(4): 549–560.

40.

Kim

Mckercher

Lee

(2009) Tracking tourism destination image perception. Annals of Tourism Research 36(4): 715–718.

41.

Kim

Yoon

(2003) The hierarchical effects of affective and cognitive components on tourism destination image. Journal of Travel and Tourism Marketing 14(2): 1–22.

42.

Kimpakorn

Tocquer

(2010) Service brand equity and employee brand commitment. Journal of Services Marketing 24(5): 378–388.

43.

Kladou

Kehagias

(2014) Assessing destination brand equity: an integrated approach. Journal of Destination Marketing & Management 3: 2–10.

44.

Kline

(1998) Principles and Practice of Structural Equation Modeling, 2nd ed. New York: The Guilford Press.

45.

Konecnik

Gartner

(2007) Customer-based brand equity for a destination. Annals of Tourism Research 34(2): 400–421.

46.

Kotler

Gertner

(2002) Country as brand, product, and beyond: a place marketing and brand management perspective. Brand Management 9(4/5): 249–261.

47.

Lee

Back

(2008) Attendee-based brand equity. Tourism Management 29(2): 331–344.

48.

Low

Lamb

(2000) The measurement and dimensionality of brand associations. Journal of Product and Brand Management 9(6): 350–368.

49.

ACC

Gursoy

(2015) Authenticity perceptions, brand equity and brand choice intention: the case of ethnic restaurants. International Journal of Hospitality Management 50: 36–45.

50.

Malik

Naeem

(2011) Interrelationship between customer based brand equity constructs: empirical evidence from hotel industry of Pakistan. Interdisciplinary Journal of Contemporary Research in Business 3(4): 795.

51.

Manthiou

Kang

Schrier

(2014) A visitor-based brand equity perspective: the case of a public festival. Tourism Review 69(4): 264–283.

52.

McKercher

Chan

Lam

(2008) The impact of distance on international tourist movements. Journal of Travel Research 47(2): 208–224.

53.

Morgan

Pritchard

(2001) Contextualizing destination branding. In: Morgan

Pritchard

Pride

(eds) Destination Branding. Oxford: Butterworth-Heinemann, pp. 11–41.

54.

Nam

Ekinci

Whyatt

(2011) Brand equity, brand loyalty and consumer satisfaction. Annals of Tourism Research 38(3): 1009–1030.

55.

Namkung

Jang

(2013) Effects of restaurant green practices on brand equity formation: do green practices really matter? International Journal of Hospitality Management 33: 85–95.

56.

Nel

JDW

North

Myburg

. (2009) A comparative study of customer-based brand equity across selected South African hotels. International Retail and Marketing Review 5(1): 15–24.

57.

Ness

Aarstad

Haugland

. (2014) Destination development the role of interdestination bridge ties. Journal of Travel Research 53(2): 183–195.

58.

Nunnally

(1978) Psychometric Theory. New York: McGraw-Hill.

59.

Hsu

CHC

(2014) Assessing equivalence of hotel brand equity measures in cross-cultural contexts. International Journal of Hospitality Management 36: 156–166.

60.

ÖHV (2005) China meets Austria - Unsere Gäste aus China kennen- und verstehen lernen. Österreichische Hoteliervereinigung, ÖHV (ed). Wien.

61.

Pappu

Quester

Cooksey

(2005) Consumer-based brand equity: improving the measurement – empirical evidence. Journal of Product and Brand Management 14(3): 143–154.

62.

Peters

Schuckert

Chon

. (2011) Empire and romance: movie-induced tourism and the case of the Sissi movies. Tourism Recreation Research 36(2): 169–180.

63.

Pike

(2009) Destination brand positions of a competitive set of near-home destination. Tourism Management 30: 857–866.

64.

Pike

Bianchi

Kerr

. (2010) Consumer-based brand equity for Australia as a long-haul tourism destination in an emerging market. International Marketing Review 27(4): 434–449.

65.

Prasad

Dev

(2000) Managing hotel brand equity: a customer-centric framework for assessing performance. The Cornell Hotel and Restaurant Administration Quarterly 41(3): 22–24.

66.

Kim

(2011) A model of destination branding: integrating the concepts of the branding and destination image. Tourism Management 32(3): 465–476.

67.

Russell-Bennett

McColl-Kennedy

Coote

(2007) Involvement, satisfaction, and brand loyalty in a small business services setting. Journal of Business Research 60: 1253–1260.

68.

Schmid

(2012) Die neuen Entdecker: Wie Gäste aus Asien dem Schweizer tourismus neuen Schub verleihen. Die Volkswirtschaft 9: 36–37.

69.

Šerić

Gil-Saura

Ruiz-Molina

(2014) How can integrated marketing communications and advanced technology influence the creation of customer-based brand equity? Evidence from the hospitality industry. International Journal of Hospitality Management 39: 144–156.

70.

Statistik Austria (2008–2016). Tourismus in Österreich – Ergebnisse der Beherbergungsstatistik. Statistik

Austria

(ed.). Wien. ISBN 978-3-902791-84-9.

71.

Switzerland Tourism (2004) Hallo China. Bern/Zürich: Hotelleriesuisse & Schweiz Tourismus.

72.

The Wall Street Journal (2015) Chinese Tourists Will Spend $229 Billion Abroad in 2015. The Wall Street Journal. Available at: http://blogs.wsj.com/chinarealtime/2015/09/29/chinese-tourists-will-spend-229-billion-abroad-in-2015/ (accessed 31 December 2015).

73.

Crompton

(1990) Attitude determinants in tourism destination choice. Annals of Tourism Research 17(3): 432–448.

74.

UNWTO (2016) Exports from international tourism rise 4% In 2015. Available at: http://media.unwto.org/press-release/2016-05-03/exports-international-tourism-rise-4-2015 (accessed 14 July 2016).

75.

Washburn

Plank

(2002) Measuring brand equity: an evaluation of a consumer-based brand equity scale. Journal of Marketing Theory and Practice 17(6): 46–61.

76.

Woodside

Lysonski

(1989) A general model of travel destination choice. Journal of Travel Research 27(4): 8–14.

77.

Chan

(2010) A conceptual framework of hotel experience and customer-based brand equity: some research questions and implications. International Journal of Contemporary Hospitality Management 22(2): 174–193.

78.

Yoo

(2002) Cross-group comparisons: a cautionary note. Psychology and Marketing 19: 357–368.

79.

Yoo

Donthu

(2001) Developing and validating a multidimensional consumer-based brand equity scale. Journal of Business Research 52(1): 1–14.

80.

Yoo

Donthu

Lee

(2000) An examination of selected marketing mix elements and brand equity. Journal of the Academy of Marketing Science 28(2): 195–211.

81.

Yuan

Jang

S-H

(2008) The effects of quality and satisfaction on awareness and behavioral intentions: exploring the role of a wine festival. Journal of Travel Research 46: 279–288.