Destination Brand Equity for Australia

Abstract

The study of destination brand performance measurement has only emerged in earnest as a field in the tourism literature since 2007. The concept of consumer-based brand equity (CBBE) is gaining favor from services marketing researchers as an alternative to the traditional “net-present-value of future earnings”’ method of measuring brand equity. The perceptions-based CBBE model also appears suitable for examining destination brand performance, where a financial brand equity valuation on a destination marketing organization’s balance sheet is largely irrelevant. This is the first study to test and compare the model in both short- and long-haul markets. The article reports the results of tests of a CBBE model for Australia in a traditional short-haul market (New Zealand) and an emerging long-haul market (Chile). The data from both samples indicated destination brand salience, brand image, and brand value are positively related to purchase intent for Australia in these two disparate markets.

Keywords

destination branding consumer-based brand equity destination loyalty destination image Australia New Zealand

Introduction

The notion of branding began during the 1700s as a means to identify the maker of the product. Despite its early roots, the discussion and study of the concept of branding did not emerge as a central part of the marketing discipline until well into the 20th century (Bastos & Levy, 2012). Stern (2006) suggested that the term brand entered marketing discourse in 1922, as an expression of a trade or proprietary name. The Second World War had a great impact on the competitive situation in the marketplace, which led to intensive competition and proliferation of brands. Since the 1950s, the study of brands and branding grew gradually, and in the second half of the 20th century the branding concept expanded in terms of both application and thinking. Gardner and Levy (1955) pointed out that consumers were confronted with making choices among brands, often in instances when they could not discern differences among the products.

The first published research related to tourism destination branding did not appear until the late 1990s (see, e.g., Dosen, Vranesevic, & Prebezac, 1998). A literature review of the first decade of destination branding publications, from 1998 to 2007 identified 74 publications (see, Pike, 2009). Of these, only four were concerned with the measurement of brand performance. This is a major gap in the literature, given the increasing investment in branding initiatives by destination marketing organizations (DMOs). Traditional financial accounting means of measuring brand effectiveness, such as the net-present-value of future earnings on corporate balance sheets, are largely irrelevant for DMOs, with the possible exception of brand/merchandise licensing revenue. There is a need for measures of brand performance that are more appropriate for DMOs and their stakeholders, and in particular indicators that capture effectiveness of past marketing communications as well as pointers to future performance such as consumers’ purchase intent.

Branding emerged as a means to gain differentiation in markets crowded with competitors offering similar products or services. In the evolution of marketing, branding explicitly recognizes the competitive requirement to adapt from a sales orientation to a marketing orientation. A marketing orientation recognizes consumers are spoilt for choice and thus all company decisions should be made with consumer’s needs in mind. The most common definition of branding, by Aaker (1991) focuses on the concept of differentiation:

A brand is a distinguishing name and/or symbol (such as a logo, trademark, or package design) intended to identify the goods or services of either one seller or a group of sellers, and to differentiate those goods from those of competitors. (p. 7)

However, destination branding is more complex than merely the design of product names and symbols (see Pike, 2005). Destination branding should (a) feature DMO marketing communications that consistently reinforce brand identity elements to differentiate the destination, (b) be based on a small set of determinant attributes that appeal to the needs of the target segment, (c) be supported and delivered by stakeholders. The aim of destination branding should be to stimulate intent to visit and revisit, which are indicators of brand loyalty.

In terms of visitation intent, consumers from short-haul destinations might consider different factors when deciding about a destination preference compared with long-haul travelers which consider mostly airfare costs and travel time (McKercher, 2008; McKercher, Chan, & Lam, 2008). This implies that short-haul travelers may visit a preferred destination several times compared with long-haul visitors. In addition, a few recent studies suggest that short haul tourists may be a fundamentally different group of people from long haul tourists in terms of income level, sensitivity of demand, and tourism consumer behavior (Bao & McKercher, 2008; Ho & McKercher, 2012). According to these studies, short-haul travelers tend to be younger people and more likely females, with lower income and education, and are more price sensitive compared with long-haul travelers (Bao & McKercher, 2008; Crouch, 1994; Ho & McKercher, 2012).

Overall, the literature suggests differences between short-haul and long-haul travelers, yet these studies tend to focus predominantly on demographic and differences of tourists using secondary travel data. Little or no emphasis has been placed on the short and long haul tourist’s perceptions of the elements and factors of destination brand identity that might lead to destination brand loyalty. Additionally, to date, little has been published outside the destination image literature about destination brand performance measures over time (Pike, 2009). This is essential for destination marketers to reinforce salient brand attributes that can stimulate on a permanent basis potential tourists to visit and revisit the destination.

It is proposed in the branding literature that the model of consumer-based brand equity (CBBE), developed by Aaker (1991, 1996) and Keller (1993, 2003), offers destination marketers a performance instrument with which to evaluate and measure consumer perceptions of a destination brand. The proposed CBBE model integrates five related dimensions to obtain a measure of brand equity: brand salience, brand image, brand quality, brand value, and brand loyalty (Aaker, 1991, 1996; Keller, 1993, 2003). Developing and testing such measures will offer practical value to DMOs who have been increasing investment in brand identity development.

Thus, the purpose of this study is to test the suitability of the CBBE model for benchmarking brand performance of Australia. It was conducted at the time of the launch of a new brand campaign, and thus provides an opportunity to benchmark future performance over time. To test the model we used samples from a traditional short-haul market (New Zealand) and an emerging long-haul market (Chile). These two countries were chosen for this study because they are both located in the southern hemisphere within the Pacific Rim region, and both have direct flights to Australia, although they are located 9,000 kilometers apart. New Zealand has traditionally been Australia’s largest single source of visitors. The country is a 3-hour flight from Australia’s east coast destinations such as Sydney, Brisbane, and the Gold Coast, and shares a sporting rivalry, and similar language and culture. Australia is also home to the largest number of New Zealand expatriates. Chile, on the other hand, is more than 16 hours flying time, and the predominant language is Spanish. Tourism Research Australia (2011) acknowledges that although visitors from Latin America represent only 1% of total annual arrivals, Chile is one of the fastest growing. This market has recently emerged as a tourism market for Australia, with 2009 ushering in a free trade agreement and direct flights between Sydney and Santiago. The number of Chilean visitors to Australia grew 23% for the year 2011 and this market is considered important for Australia because of its high level of development and growth within the Latin American region and improved air connectivity (Tourism Research Australia, 2011). Some aspects of the first stage of the study, which involved only the Chilean sample, have previously been reported (Pike et al., 2010).

Consumer-Based Brand Equity

Consumer-Based Brand Equity Model Development

There have been relatively few applications testing the CBBE model in relation to destination branding. Modeling of CBBE in the wider tourism and hospitality literature has included: conferences (Lee & Back, 2008), hotels (Cobb-Walgren, Beal, & Donthu, 1995; Kayaman & Arasli, 2007; H. Kim, Kim, & An, 2003; W. G. Kim, Jin-Sun, & Kim, 2008), restaurants (H. Kim & Kim, 2005), wineries (Lockshin & Spawton, 2001), and airlines (C.-F. Chen & Tseng, 2010). The first published journal article related to the measurement of destination brand equity appears to be that by Kim (2001, cited in S. H. Kim, Han, Holland, & Byon, 2009). Since then there have been at least eight published articles: Croatian-based brand equity for Slovenia (Konecnik & Gartner, 2007); short-break destination brand equity for an emerging destination (Pike 2007); CBBE for Las Vegas and Atlantic City, in the context of gambling destinations (Boo, Busser, & Baloglu, 2009); host community brand equity (Pike & Scott, 2009); international visitors to Korea (S. H. Kim et al., 2009); international visitors to Mongolia (C.-F. Chen & Myagmarsuren, 2010); and short-haul international travelers to Slovenia (Ruzzier, 2010). This shows that the application and testing of the CBBE model is in its infancy and needs further work. The CBBE conceptual model is shown in Figure 1, and features five latent variables: destination brand loyalty, brand salience, brand image, brand quality and brand value. These variables are consistent with previous destination studies.

Figure 1

Proposed Model

Dependent Variable: Attitudinal Loyalty

There is a compelling argument for using attitudinal loyalty as the dependent variable in modeling destination brand equity. Destination loyalty is vital for achieving repeat visitation and positive word of mouth among visitors (Gartner & Hunt, 1987, X. Li & Petrick, 2008b). Although attracting new customers is essential, it is more desirable and much less expensive to retain current customers (Reichheld, Markey, & Hopton, 2000). Research shows that in the short run, loyal customers are more profitable because they spend more and are less price sensitive (Reichheld et al., 2000). Loyal customers can also lead to increased positive word of mouth for the service provider (Jones & Taylor, 2007). Nevertheless, despite these advantages, few studies attempt to identify the key determinants of destination brand loyalty for travelers from long-haul markets (X. Li & Petrick, 2008a).

Although brand loyalty was first reported in the literature during the early 1900s (Bastos & Levy, 2012; Guest, 1942), only a few studies of destination brand loyalty are found in the tourism literature before the millennium (Oppermann, 2000). The topic of repeat visitors to destinations has started to attract increased interest from researchers only in the past decade (Alegre & Cladera, 2006; J. S. Chen & Gursoy, 2001; Chi & Qu, 1998; Chitty, Ward, & Chua, 2007; X. Li & Petrick, 2008b; McKercher & Guillet, 2011; Mechinda, Serirat, & Guild, 2009; Niininen, Szivas, & Riley, 2004; Oppermann, 2000; Yoona & Uysalb, 2005). These studies assert that the measurement of destination loyalty, especially in a long-haul travel context, is difficult since the purchase of a tourism product is often infrequent, or even once in a lifetime, and/or part of a multidestination travel experience (Martin & Woodside, 2008; Oppermann, 1999). However, following the conceptual work of Aaker (1991, 1996) and Keller (1993, 2003), the loyalty construct in CBBE is suitable for application with prospective visitors as well as previous visitors. Therefore, the aim of this study was to test the appropriateness of this dependent variable in both long-haul and short-haul markets.

Previous research suggests that the loyalty construct is composed of two dimensions; behavioral loyalty and attitudinal loyalty (Jones & Taylor, 2007; X. Li & Petrick, 2008b). Hence, loyalty implies a commitment to the specific brand and goes beyond repetitive behavior (Jacoby & Kyner, 1973). Behavioral loyalty refers to the frequency of repeat purchase or relative volume of same brand purchase. Attitudinal loyalty refers to the dispositional commitment or attitude a consumer-traveler has toward a destination, measured by intent to visit and positive word-of-mouth recommendations. Both items are relevant to prospective visitors as well as previous visitors. This study uses attitudinal loyalty as the dependent variable since it is a measure of future travel preference or intent to visit.

Brand Salience

Brand salience is the foundation of the CBBE model (Keller, 2003), with the aim being to be remembered for the reasons intended rather than just achieve general awareness per se (Aaker, 1996). Since most consumers will be aware of a multitude of destinations, we conceptualize destination brand salience as the strength of awareness of the destination in the mind of an individual when a given travel situation is considered. Previous studies demonstrate that consumers will usually only actively consider between two to four brands in their decision set (Howard, 1963; Howard & Sheth, 1969; Pike, 2006; Thompson & Cooper, 1979; Woodside & Sherrell, 1977). Brand salience is commonly measured by unaided awareness or aided brand recall. It is proposed that membership in a consumer’s decision set for a given travel context, elicited through unaided awareness, represents a source of competitive advantage. Previous research suggests an indirect relationship between destination brand salience and destination brand loyalty for short-haul destinations (Boo et al., 2009). Thus, we propose that destination brand salience will positively influence destination brand loyalty for short- and long-haul visitors. Yet we predict that destination brand salience will be stronger for short-haul travelers because of the geographical proximity:

Hypothesis 1: Destination brand salience will positively influence destination brand loyalty.

Brand Image

Brand image, in accordance with the associative network memory model (J. R. Anderson, 1983), is anything linked to a brand in the consumer’s memory (Aaker, 1991), which consists of nodes and links. A node contains information about a concept, and is part of a network of links to other nodes. When a given node concept is recalled, strength of association determines what other nodes will be activated from memory. A destination can therefore be conceptualized as a node to which a number of other node concepts are linked. Although destination image research is well established in the tourism literature, there is no universally accepted measurement scale index. Following Boo et al. (2009), this study limits destination image to social and self-image. Using this approach, Boo et al. (2009) found a positive relationship between brand image and brand destination loyalty. This was supported by Chitty et al. (2007), who examined the antecedents of backpacker loyalty to Australia and found brand image to be an important predictor. Thus, we propose that destination brand image will positively influence destination brand loyalty for short and long haul travelers:

Hypothesis 2: Destination brand image will positively influence destination brand loyalty.

Perceptions of Quality

Brand quality is a key dimension of brand equity for product manufacturers and service providers (Aaker, 1996; Keller, 2003). Perceived quality is defined as the “perception of the overall quality or superiority of a product or service relative to relevant alternatives and with respect to its intended purpose” (Keller, 2003, p. 238). Destination brand quality, therefore, refers to perceptions of quality of the facilities and nonphysical aspects of the destinations. Previous research reports that elements of perceived quality, such as destination infrastructure, affect brand performance (Buhalis, 2000) and have a positive effect on brand loyalty (Boo et al., 2009). Thus, we propose that destination brand infrastructure elements of quality will positively influence destination brand loyalty for short- and long-haul travelers:

Hypothesis 3: Destination brand quality is positively related to destination brand loyalty.

Perceptions of Value

The perceived value of a service pertains to the benefits customers believe they receive relative to the costs associated with its consumption (McDougall & Levesque, 2000). Zeithaml and Bitner (2000) suggest that perceived value is an overall evaluation of a service’s utility, based on customers’ perceptions of what is received at what price. Heskett, Sasser, and Schlesinger (1997) argue that high perceived value is positively associated with satisfaction and loyalty. In a tourism context, Mechinda et al. (2009) examined the antecedents of consumer loyalty toward a destination in Thailand and found that destination attitudinal loyalty was driven mainly by perceived value. This finding was supported by Boo et al. (2009) and Chitty et al. (2007), who also found a positive relationship between perceived value and destination loyalty. Thus, we propose that destination brand value will positively influence destination brand loyalty for short- and long-haul visitors, yet we predict that destination brand value will have a stronger effect for short haul travelers:

Hypothesis 4: Destination brand value will positively influence destination brand loyalty.

Method

This section discusses the second stage of the study, which tested the proposed model with a sample of New Zealand residents, to examine CBBE for Australia in a traditional short-haul market. As indicated, the model was previously tested in a similar way with a Spanish version of the questionnaire and a sample of 341 Chilean travelers to examine CBBE for Australia as a long-haul destination in an emerging market (Pike et al., 2010).

The New Zealand sample consisted of members of a panel from a locally based marketing research company. Panel members were sent an e-mail invitation to participate in an online survey. As well as the usual benefits that panel members are offered as an incentive to participate in surveys by the marketing research firm, an additional $500 travel voucher prize was offered.

No mention of Australia was made on the opening page of the online survey. Two filter questions were first used to identify: (a) if participants had visited another country during the previous 5 years and (b) the likelihood of taking an international holiday during the following 12 months. Next, two open-ended questions were used to identify unaided destination salience, top of mind awareness (ToMA) preferred destination, and the other destinations in their decision set.

The next page asked participants to indicate if they had previously visited Australia and to evaluate the destination on the five dimensions of the CBBE model using a 7-point scale anchored at 1 = very strongly disagree to 7 = very strongly agree. Brand salience was measured with five items derived from Boo et al. (2009) and Konecnik and Gartner (2007). Brand quality was measured with four items based on Konecnik and Gartner (2007). Brand value was measured by four items adapted from Boo et al. (2009). Brand image and brand loyalty were both measured using four items each from Boo et al. (2009), Konecnik and Gartner (2007), and Chi and Qu (1998).

Results

Data Analysis

The characteristics of the New Zealand and Chilean participants are shown in Table 1. The New Zealand sample (N = 858) comprised 24% males and 76% females. Although these characteristics possibly affect the generalizability of the data, a purposeful sample of residents with international travel experience was achieved. That is, it is argued that the sample is suitable for assessing the destination brand equity model given that 764 respondents (89%) had taken a holiday in another country during the previous 5 years. The mean likelihood of participants taking a holiday in another country during the following 12 months was 5.8 on a 7-point scale anchored at 1 = definitely not and 7 = definitely. The majority of participants (84%) were aged between 25 and 64 years.

Table 1

Characteristics of Participants

	New Zealand (N = 858)		Chile (N = 845)
	n	Valid (%)	n	Valid (%)
Gender
Male	206	24.0	643	76.5
Female	652	76.0	197	23.5
Age (years)
18-24	86	10.0	6	0.07
25-44	339	39.5	514	60.8
45-64	384	44.8	301	35.6
65+	49	5.7	24	3.59
Marital status
Single	196	22.8	124	14.7
Married/live in partner	558	65.0	644	76.2
Divorced/separated/widowed	104	12.1	77	9.1
Number of dependent children
0	477	55.6	246	29.1
1-2	299	34.8	329	38.9
3+	82	9.6	270	32.0
Household income (US$)
<25,000	72	8.4	86	10.2
25,000-50,000	286	33.3	233	27.6
50,001-99,999	210	24.5	313	37.0
100,000+	290	33.8	213	25.2
Education
High school	300	34.9	3	0.00
University	243	28.3	450	53.3
Other	315	36.7	392	46.7

The Chile sample (N = 845) comprised 76% males and 24% females. Although the characteristics do not enable the data to be generalized to the wider Chilean population, the aim was to achieve a purposeful sample of residents with recent international travel experience. It is suggested that the sample is suitable for destination brand equity model testing, given that 758 participants (90%) had taken a holiday in another country during the previous 5 years. The mean likelihood of participants taking a holiday in another country during the following 12 months was 5.2 on a 7-point scale anchored at 1 = definitely not and 7 = definitely. The majority of participants (87%) were aged between 25 and 64 years.

Participants’ ToMA-preferred destinations are listed in Table 2. This table includes the data from the Chilean study as well. Australia was listed as the top of mind destination by 40% of participants from the New Zealand sample (short haul). Although it might be expected that Australia would receive a high level of ToMA elicitation from such a contiguous market, it is important to note that the majority of participants (60%) identified other preferred destinations. This differs when looking at the Chilean sample (long haul), where Australia was listed as the top of mind destination by only 2.8% of participants. The mean number of destinations in both participants’ decision sets is 3.4, which is consistent with previous studies reported in the tourism and marketing literature (Woodside & Sherrell, 1977).

Table 2

Top of Mind Awareness Preferred Destination

Rank	New Zealand Sample	n	%	Chile Sample	n	%
1	Australia	340	39.8	USA	138	16.3
2	United Kingdom	71	8.3	Brazil	114	13.5
3	United States	67	7.8	Mexico	71	8.4
4	Rarotonga	30	3.5	Italy	54	6.4
5	Fiji	28	3.3	Spain	53	6.3
6	Samoa	22	2.6	Argentina	49	5.8
7	Italy	21	2.5	Caribbean	38	4.5
8	Canada	19	2.2	France	27	3.2
9	France	18	2.1	Greece	25	3.0
10	Greece	12	1.4	Australia	24	2.8

Table 3 presents the destination performance means, standard deviation, and Cronbach’s alpha scores for each construct for both the New Zealand and Chile sample. This table also includes the data from the Chilean study for comparative purposes. The Cronbach alpha coefficients for both samples, which ranged from .81 to .93, indicate good internal consistency and reliability (Kline, 2005). This is despite differences in the destination performance means. Brand salience means for the Chilean sample are lower than the New Zealand sample except for the item “This destination has a good name and reputation,” which is higher. Interestingly, the means for brand image and perceived quality were all higher in the Chilean data, except for the item “Accommodation,” which had a higher mean in the New Zealand data. Finally, as would be expected, the means for brand value were lower for the long-haul sample compared with the short-haul sample.

Table 3

Destination Performance Means

	New Zealand			Chile
	M	SD	α	M	SD	α
Brand salience			.82			.81
• This destination has a good name and reputation (Boo, Busser, & Baloglu, 2009)	5.6	1.1		6.1	1.1
• The characteristics of this destination come to my mind quickly (Boo et al., 2009; Konecnik & Gartner, 2007)	5.6	1.2		4.8	1.8
• This destination is very famous (Boo et al., 2009)	5.3	1.3		4.7	1.6
• When I am thinking of an international holiday, this destination comes to my mind immediately (Boo et al., 2009)	4.8	1.7		2.7	1.6
• I have seen a lot of advertising promoting Australian holidays (Konecnik & Gartner, 2007)	5.6	1.3		3.1	1.6
Perceived quality			.93			.93
• High-quality accommodation (Konecnik & Gartner, 2007)	5.8	1.1		5.6	1.3
• High levels of cleanliness (Konecnik & Gartner, 2007)	5.7	1.1		5.8	1.2
• High level of personal safety (Konecnik & Gartner, 2007)	5.5	1.1		5.8	1.2
• High-quality infrastructure (Konecnik & Gartner, 2007)	5.6	1.1		5.9	1.1
Brand image			.92			.92
• This destination fits my personality (Boo et al., 2009)	3.8	1.7		4.0	1.7
• My friends would think highly of me if I visited this destination (Boo et al., 2009)	3.6	1.6		4.3	1.8
• The image of this destination is consistent with my own self image (Boo et al., 2009).	3.7	1.6		4.3	1.7
• Visiting this destination reflects who I am (Boo et al., 2009)	3.4	1.7		3.6	1.6
Brand loyalty			.88			.88
• This destination would be my preferred choice for a vacation (Boo et al., 2009)	4.4	1.7		3.2	1.6
• I would advise other people to visit this destination (Boo et al., 2009; Chi & Qu 1998; Konecnik & Gartner, 2007)	5.0	1.4		4.0	1.8
• I intend visiting this destination in the future (Chi & Qu, 1998; Konecnik & Gartner, 2007)	4.6	1.5		4.6	1.9
• This destination provides more benefits than other destinations (Konecnik & Gartner, 2007)	4.4	1.4		3.5	1.5
Brand value			.92			.85
• This destination has reasonable prices	5.2	1.29		3.0	1.3
• Considering what I would pay for a trip, I will get much more than my money’s worth by visiting this destination (Boo et al., 2009)	4.9	1.35		3.7	1.5
• The costs of visiting this destination are a bargain relative to the benefits I receive (Boo et al., 2009)	4.6	1.38		2.8	1.3
• Visiting this destination is good value for money (Boo et al., 2009)	4.9	1.30		3.4	1.4

Item-to-total correlations, standardized Cronbach’s alpha, exploratory factor analysis (all in SPSS), single measurement models, and confirmatory factor analysis (using AMOS 16) were used for construct purification. Based on these analyses, eight measurement indicators from the five constructs were dropped. The authors tested the proposed model with the refined measures using structural equation modeling techniques (J. C. Anderson & Gerbing, 1991). Tables 4 and 5 show the correlations, means, and standard deviations for the construct measures of the New Zealand and Chile samples, respectively. The standardized regression weights for both the New Zealand and Chile samples are shown in Table 6. The estimates are similar in both countries and greater than .6, which demonstrates convergent validity for the constructs (except for one item of brand salience which is less than .6 in both countries).

Table 4

Means, Standard Deviations, and Correlations: New Zealand Sample

	M	SD	DBS	DBQ	DBI	DBV	DBL
DBS	5.54	0.97	1.00	0.27*	0.36*	0.56*	0.56*
DBQ	5.46	1.15	0.27*	1.00	0.10*	0.28*	.027*
DBI	3.62	1.47	0.36*	0.10*	1.00	0.44*	0.52*
DBV	4.89	1.19	0.56*	0.28*	0.44*	1.00	0.70*
DBL	5.00	1.31	0.56*	0.27*	0.52*	0.70*	1.00*

Note: DBS = destination brand salience; DBQ = destination brand quality; DBI = destination brand image; DBV = destination brand value; DBL = destination brand loyalty.

Correlation is significant at the .01 level (two-tailed).

Table 5

Means, Standard Deviations, and Correlations: Chile Sample

	M	SD	DBS	DBQ	DBI	DBV	DBL
DBS	4.32	1.16	1.00	0.45*	0.49*	0.48*	0.66*
DBQ	5.76	1.06	0.45*	1.00	0.38*	0.21*	0.43*
DBI	4.10	1.59	0.49*	0.38*	1.00	0.33*	0.60*
DBV	3.07	1.09	0.48*	0.21*	0.33*	1.00	0.52*
DBL	3.82	1.44	0.66*	0.43*	0.60*	0.52*	1.00

Note: DBS = destination brand salience; DBQ = destination brand quality; DBI = destination brand image; DBV = destination brand value; DBL = destination brand loyalty.

Correlation is significant at the .01 level (two-tailed).

Table 6

Standardized Regression Weights

	New Zealand	Chile
Brand salience
This destination has a good name and reputation	.80	.78
The characteristics of this destination come to my mind	.83	.79
This destination is very famous	.75	.79
I have seen a lot of advertising promoting Australian holidays	.57	.56
Perceptions of brand quality
High-quality accommodation	.87	.83
High levels of cleanliness	.94	.92
High level of personal safety	.84	.88
High-quality infrastructure	.95	.93
Brand image
This destination fits my personality	.86	.88
My friends would think highly of me if I visited this destination	.76	.77
The image of this destination is consistent with my own self-image	.92	.93
Visiting Australia would reflect who I am	.94	.92
Brand value
This destination has reasonable prices	.78	.77
Considering what I would pay for a trip, I will get much more than my money’s worth by visiting this destination	.88	.88
The costs of visiting this destination are a bargain relative to the benefits I receive	.88	.88
Visiting this destination is good value for money	.89	.89
Brand loyalty
This destination would be my preferred choice for a vacation	.77	.76
I would advise other people to visit this destination	.86	.84
I intend visiting this destination in the future	.70	.69

To examine the model structure, confirmatory factor analysis, using Amos 16.0, was undertaken. Results from the New Zealand data indicate a good model fit. The chi-square statistic was significant (χ²/df = 3.99, incremental fit index [IFI] = .966, Tucker–Lewis index [TLI] = .959, comparative fit index [CFI] = .966, and root mean square error of approximation [RMSEA] = .059). The RMSEA was greater than .05, which is considered a reasonably good fit (Bollen, 1989). Furthermore, IFI, TLI, and CFI exceeded the recommended level of .90 (Bollen, 1989). All items are significantly associated with their hypothesized factors, evidence of convergent validity. In addition, the potential for acquiescence bias was minimized by including both positively and negatively worded items in the questionnaire. Furthermore, a combination of semantic differential scales and 7-point Likert-type scales were used to reduce common method bias (Podsakoff, Mackenzie, Lee, & Podsakoff, 2003). Finally, no single factor accounted for most of the variance in the independent and dependent variables. This result provides support for the absence of common method bias variance (Podsakoff & Organ, 1986).

Hypotheses Testing

The results from the hypotheses testing on the New Zealand data indicate that destination brand salience is significantly and positively related to destination brand loyalty (β = .34, p < .001). Therefore, the data supports Hypothesis 1. This is consistent with the Chilean sample (long haul), which found a positive statistical relationship between destination brand salience and destination brand loyalty (β = .29, p < .001).

Regarding Hypothesis 2, the data indicate that destination brand quality is not significantly related to destination brand loyalty (β = .04, p = .60). Therefore, Hypothesis 2 is not supported in the New Zealand sample. This also matches the Chilean study, which finds a nonsignificant relationship between destination brand quality and destination brand loyalty (β = .16, p = .075).

Furthermore, the results indicate that destination brand image is significantly and positively related to destination brand loyalty (β = .20, p < .001). Therefore, the data supports Hypothesis 3 for the New Zealand sample. This is consistent with the Chilean sample, which also found a positive statistical relationship between destination brand salience and destination brand loyalty (β = .28, p < .001).

Finally, in reference to Hypothesis 4, the data indicate that destination brand value is significantly and positively related to destination brand loyalty (β = .56, p < .001). Therefore, Hypothesis 4 is supported for the New Zealand sample. This is also consistent with the Chilean sample which also found a positive statistical relationship between destination brand salience and destination brand loyalty (β = .23, p < .001).

Overall, three out of four hypotheses were supported by both the New Zealand (short haul) and Chilean (long haul) data. The final model is shown in Table 7. It is interesting to note that for Hypothesis 3, the relationship between destination brand image and destination brand loyalty is stronger for the Chilean sample than for the New Zealand sample. As predicted, when looking at destination brand value, the relationship with destination brand loyalty is much stronger for the New Zealand sample. In fact, destination brand value is the strongest driver of destination brand loyalty for the New Zealand data, yet destination brand salience is the strongest driver for the Chilean data.

Table 7

Model Goodness-of-Fit and Hypotheses Testing

New Zealand Data (n = 858)
	χ²	df	χ²/df	RMSEA	IFI	TLI	CFI
Total sample	486.8	142	3.43	.053	.967	.961	.967
**p < .001
Hypotheses	Path Directions	β	t	Significance	Result
H1	DBS → DBL	.34	6.22	***	Supported
H2	DBQ → DBL	.04	1.57	.598	Not Supported
H3	DBI → DBL	.20	7.53	***	Supported
H4	DBV → DBL	.56	12.72	***	Supported
Results significant at *p < .001, p < .005
Chile Data (n = 341) align="center"
	χ²	df	χ²/df	RMSEA	IFI	TLI	CFI
Total sample	181.4	80	2.27	.061	.964	.946	.964
**p < .001
Hypotheses	Path Directions	β	t	Significance	Result
H1	DBS → DBL	.29	4.71	***	Supported
H2	DBQ → DBL	.16	2.43	.075	Not Supported
H3	DBI → DBL	.28	5.61	***	Supported
H4	DBV → DBL	.23	3.88	***	Supported
Results significant at *p < .001, p < .005

Note: RMSEA = root mean square error of approximation; IFI = incremental fit index; TLI = Tucker-Lewis index; CFI = comparative fit index; DBS = destination brand salience; DBQ = destination brand quality; DBI = destination brand image; DBV = destination brand value; DBL = destination brand loyalty.

Discussion and Conclusion

There has been limited research addressing the drivers and modeling of destination brand performance. This study contributes to the tourism destination branding literature by testing a conceptual model of destination brand performance in two disparate markets. Key constructs from the CBBE model, championed by Aaker (1991, 1996) and Keller (1993, 2003), were trialed. The data from both the emerging long-haul market (Chile) and traditional short-haul market (New Zealand) found brand salience, brand image, and brand value to be positively related to brand loyalty. In addition, the results of this study supported our prediction that destination brand salience is higher and has a stronger effect on destination brand loyalty for short-haul travelers (New Zealand β = .34), than long-haul travelers (Chile β = .29, p < .001), mainly due to geographic proximity. The findings also support our prediction that destination brand value has a stronger effect for short-haul travelers (New Zealand β = .54) compared with long-haul travelers (Chile β = .23, p < .001), probably because short-haul travelers tend to be more price sensitive compared with long-haul travelers (Bao & McKercher, 2008; Crouch, 1994; Ho & McKercher, 2012).

We argued the case for attitudinal destination loyalty as the dependent variable in the proposed model. This construct measures stated intent to visit and likelihood of personal recommendations to others. One of the key aims of DMOs is to stimulate intent to visit and revisit. In this regard, whereas all the constructs provide performance measures in terms of the effectiveness of past marketing communications, the intent-to-visit data also provide a future orientation. For any individual business, strong levels of purchase intent represent a form of “goodwill” on the balance sheet. For DMOs, intent to visit represents an important barometer for future performance.

This is the first study to model and compare a destination’s CBBE in short-haul and long-haul markets. Most published research in this field has focused on destination brand initiatives aimed at travelers from geographically close markets (McKercher, 2008), particularly for Australia (Prosser, 2000), such as China and Taiwan (e.g., Huang & Gross, 2010; Kao, Patterson, Scott, & Li, 2008; J. W. Li & Carr, 2004; Pan & Laws, 2003). Attracting visitors from long-haul destinations entails distinctive challenges; including mitigating higher airfare costs, travel time, and consumer confidence or risk (McKercher, 2008; McKercher et al., 2008). Long travel distances have an influence on tourism demand due to higher levels of consumer involvement in planning and expenditure (McKercher & Lew, 2003). In fact, some studies suggest that many people may be precluded from long-haul travel because of the longer distances and higher costs (McKercher, 2008; McKercher et al., 2008). For example, McKercher et al. (2008) report that relatively few people are willing to travel more than 2,000 kilometers from their home country and as a result, most destinations’ ability to attract long-haul markets is limited. Indeed it has been suggested that 70% of international travelers visit only 10 countries, so more than 90 National Tourism Offices around the world compete for 30% of total international arrivals (Morgan, Pritchard, & Pride, 2002).

The negative relationship between distance and demand has been termed distance decay. This is apparent in the results of the brand value scale items, where the means for the Chile sample were all below the scale midpoint, whereas the means for the New Zealand sample were all above the scale midpoint.

On the other hand, Nicolau (2008) contends that the journey itself can lead to satisfaction and thus, longer distances can sometimes be preferred. This is consistent with Goh, Law, and Mok (2008), who found that the decision to traveling to a long-haul destination can also be affected by the consumer’s perceptions of a destination, its cultural background, and climatic conditions. As highlighted in Table 2, more than half the New Zealand sample (64%) and around half the Chilean sample (48%) elicited long-haul destinations as ToMA preferences for their next international holiday. On a positive note for the tourism industry, Australia was perceived well in both markets across many of the brand salience and brand quality items. The highest mean (6.1) for any scale item was Chileans’ respondent’s perception that Australia has a good name and reputation as a holiday destination. Clearly this image has been formed organically rather than induced by marketing (see, Gunn, 1988), since the mean for “I have seen a lot of advertising promoting Australian holidays” was 3.1 for the Chilean sample. This organic image provides a solid base for future brand building.

The study took place at the commencement of a new brand campaign by Tourism Australia. The Chilean data were also collected at the same time as the commencement of direct air services between Sydney and Santiago. The data therefore provides a performance benchmark, for future studies of Australia’s performance in this, and the New Zealand market.

Finally, it is important to reflect on the relevance of structural equation modeling for destination marketing practitioners. Although the model we have tested contributes toward our understanding of the complexities of brand performance measurement, we do not necessarily advocate this method for tracking performance over time. Although structural equation modeling helps identify antecedents of destination loyalty as the dependent variable, we suggest that future destination brand performance tracking include the following:

Unaided awareness questions to elicit ToMA position and decision set composition. These data identify the competitive set of brands for a travel segment, as well as provide an indicator of future competitiveness given the higher probability of travel to places listed in decision sets.

Brand salience, brand image, and brand value scale items should not be measured for the destination in isolation. Rather, perceptions of the other destinations in the competitive set are required to provide a relative measure of the brand’s competitive position in the market.

Limitations and Future Research

Several limitations might have affected the generalizability of the results of this study. First, this empirical investigation considers only the perceptions of Chilean and New Zealand consumers with regard to Australia as a holiday destination. Thus, the analysis was limited to two countries. More research needs to be undertaken with consumers in other markets of interest to Australia, such as the Asia-Pacific region. Second, both samples differ in their gender and educational characteristics; however, we argue that both data sets represent the typical traveler and holiday decision maker for New Zealand and Chile. Finally this study only considers attitudinal destination loyalty and not behavioral loyalty.

Our literature review found scant research on the travel motivations and preferences of Latin American consumers, other than the “purpose of visit” data published by Tourism Research Australia (e.g., Tourism Research Australia, 2012). Thus, more insights are required into the motivations of long-haul North and South American as well as European travelers. Replications of this study in such markets could deliver additional performance indicators for current branding efforts by Tourism Australia and its stakeholders.

Footnotes

Acknowledgements

We acknowledge the support of Conicyt for the Research Centre for International Competitiveness, project SOC 1105. This paper was prepared with the assistance of the Services Innovation Research Program, QUT Business School, Queensland University of Technology.

Authors’ Note:

This article was prepared with the assistance of the Services Innovation Research Program, QUT Business School, Queensland University of Technology.

Steven Pike, PhD (e-mail: sd.pike@qut.edu.au) is an associate professor in the School of Advertising, Marketing and Public Relations, QUT Business School at the Queensland University of Technology, Brisbane, Queensland, Australia. Constanza Bianchi, PhD (e-mail: constanza.bianchi@uai.cl) is a Professor of International Marketing in the school of business at Universidad Adolfo Ibáñez, Santiago, Chile, and Adjunct Professor in the School of Advertising, Marketing and Public Relations, QUT Business School at the Queensland University of Technology, Brisbane, Queensland, Australia.

References

Aaker

D. A.

(1991). Managing brand equity. New York, NY: Free Press.

Aaker

D. A.

(1996). Building strong brands. New York, NY: Free Press.

Alegre

Cladera

(2006). Repeat visitation in mature sun and sand holiday destinations. Journal of Travel Research, 44, 288-297.

Anderson

J. C.

Gerbing

D. W.

(1991). Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities. Journal of Applied Psychology, 76, 732-740.

Anderson

J. R.

(1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

Bao

Y. F.

Mckercher

(2008). The effect of distance on tourism in Hong Kong: A comparison of short haul and long haul visitors. Asia Pacific Journal of Tourism Research, 13, 101-111.

Bastos

Levy

S. J.

(2012). A history of the concept of branding: Practice and theory. Journal of Historical Research in Marketing, 4, 347-368.

Bollen

K. A.

(1989). Structural equations with latent variables. New York, NY: Wiley.

Boo

Busser

Baloglu

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

10.

Buhalis

(2000). Marketing the competitive destination of the future. Tourism Management, 21, 97-116.

11.

Chen

C.-F.

Myagmarsuren

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

12.

Chen

C.-F.

Tseng

W. S.

(2010). Exploring customer-based airline brand equity: Evidence from Taiwan. Transportation Journal, 49, 24-35.

13.

Chen

J. S.

Gursoy

(2001). An investigation of tourists’ destination loyalty and preferences. International Journal of Contemporary Hospitality Management, 13, 79-85.

14.

Chi

C. G.-Q.

(1998). Examining the structural relationship of destination image, tourist satisfaction and destination loyalty. Tourism Management, 29, 624-636.

15.

Chitty

Ward

Chua

(2007). An application of the ECSI model as a predictor of satisfaction and loyalty for backpacker hostels. Marketing Intelligence & Planning, 25, 563-580.

16.

Cobb-Walgren

C. J.

Beal

Donthu

(1995). Brand equity, brand preferences, and purchase intent. Journal of Advertising, 24, 25-40.

17.

Crouch

G. I.

(1994). Demand elasticities for short-haul versus long-haul yourism. Journal of Travel Research, 33, 2-7.

18.

Dosen

D. O.

Vranesevic

Prebezac

(1998). The importance of branding in the development of marketing strategy of Croatia as touristic destination. Acta Turistica, 10, 93-182.

19.

Gardner

B. B.

Levy

S. J.

(1955). The product and the brand. Harvard Business Review, March-April, 33-39.

20.

Gartner

W. C.

Hunt

J. D.

(1987). An analysis of state image change over a twelve-year period (1971-1983). Journal of Travel Research, 26, 15-19.

21.

Goh

Law

Mok

H. M. K.

(2008). Analyzing and forecasting tourism demand: A rough sets approach. Journal of Travel Research, 46, 327-338.

22.

Guest

L. P.

(1942). The genesis of brand awareness. Journal of Applied Psychology, 26, 800-808.

23.

Gunn

(1988). Vacationscape: Designing tourist regions (2nd ed.). Austin: Bureau of Business Research, University of Texas.

24.

Heskett

J. L.

Sasser

W. E.

Jr. Schlesinger

L. A.

(1997). The service profit chain: How leading companies link profit and growth to loyalty, satisfaction and value. New York, NY: Free Press.

25.

McKercher

(2012). A comparison of long-haul and short-haul business tourists of Hong Kong. Asia Pacific Journal of Tourism Research. Advance online publication. doi:10.1080/10941665.2012.746235

26.

Howard

J. A.

(1963). Marketing management: Analysis and planning. Homewood, IL: Irwin.

27.

Howard

J. A.

Sheth

J. N.

(1969). The theory of buyer behavior. New York, NY: Wiley.

28.

Huang

Gross

M. J.

(2010). Australia’s destination image among mainland Chinese travelers: An exploratory study. Journal of Travel & Tourism Marketing, 27, 63-81.

29.

Jacoby

Kyner

D. B.

(1973). Brand loyalty vs. repeat purchasing behavior. Journal of Marketing Research, 10, 1-9.

30.

Jones

Taylor

S. F.

(2007). The conceptual domain of service loyalty: How many dimensions? Journal of Services Marketing, 21, 36-51.

31.

Kao

M. P.

Patterson

Scott

(2008). Motivations and satisfactions of Taiwanese tourists who visit Australia: An exploratory study. Journal of Travel & Tourism Marketing, 24, 17-33.

32.

Kayaman

Arasli

(2007). Customer based brand equity: Evidence from the hotel industry. Managing Service Quality, 17, 92-109.

33.

Keller

K. L.

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

34.

Keller

K. L.

(2003). Strategic brand management. Upper Saddle River, NJ: Prentice Hall.

35.

Kim

W. G.

(2005). The relationship between brand equity and firms’ performance in luxury hotels and chain restaurants. Tourism Management, 26, 549-560.

36.

Kim

W. G.

J. A.

(2003). The effect of customer-based brand equity on firm’s financial performance. Journal of Consumer Marketing, 20, 335-351.

37.

Kim

S. H.

Han

H. S.

Holland

Byon

K. K.

(2009). Structural relationships among involvement, destination brand equity, satisfaction and destination visit intentions: The case of Japanese outbound travellers. Journal of Vacation Marketing, 15, 349-365.

38.

Kim

W. G.

Jin-Sun

Kim

H. J.

(2008). Multidimensional customer-based brand equity and its consequences in midpriced hotels. Journal of Hospitality & Tourism Research, 32, 235-254.

39.

Kline

R. B.

(2005). Principles and practise of structural equation modelling. New York, NY: Guilford.

40.

Konecnik

Gartner

W. C.

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

41.

Lee

J. S.

Back

K. J.

(2008). Attendee-based brand equity. Tourism Management, 29, 331-344.

42.

J. W.

Carr

(2004). Visitor satisfaction: An analysis of mainland Chinese tourists on the Australian Gold Coast. International Journal of Hospitality & Tourism Administration, 5, 31-48.

43.

Petrick

(2008a). Examining the antecedents of brand loyalty from an investment model perspective. Journal of Travel Research, 47, 25-34.

44.

Petrick

J. F.

(2008b). Reexamining the dimensionality of brand loyalty: A case of the cruise industry. Journal of Travel & Tourism Marketing, 25, 68-85.

45.

Lockshin

Spawton

(2001). Using involvement and brand equity to develop a wine tourism strategy. International Journal of Wine Marketing, 13, 72-81.

46.

Martin

Woodside

(2008). Grounded theory of international tourism behavior. Journal of Travel & Tourism Marketing, 24, 245-258.

47.

Mcdougall

G. H. G.

Levesque

(2000). Customer satisfaction with services: Putting perceived value into the equation. Journal of Services Marketing, 47, 9-20.

48.

McKercher

(2008). The implicit effect of distance on tourist behavior: A comparison of short and long haul pleasure tourists to Hong Kong. Journal of Travel & Tourism Marketing, 25, 367-381.

49.

McKercher

Chan

Lam

(2008). The impact of distance on international tourist movements. Journal of Travel Research, 47, 208-224.

50.

McKercher

Guillet

B. D.

(2011). Are tourists or markets destination loyal? Journal of Travel Research, 50, 121-132.

51.

McKercher

Lew

A. A.

(2003). Distance decay and the impact of effective tourism exclusion zones on international travel flows. Journal of Travel Research, 42, 159-165.

52.

Mechinda

Serirat

Guild

(2009). An examination of tourist’s attitudinal and behavioral loyalty: Comparison between domestic and international tourists. Journal of Vacation Marketing, 15, 129-148.

53.

Morgan

Pritchard

Pride

(2002). Destination branding–Creating the unique destination proposition. Oxford, England: Butterworth-Heinemann.

54.

Nicolau

(2008). Characterizing tourist sensitivity to distance. Journal of Travel Research, 47, 43-52.

55.

Niininen

Szivas

Riley

(2004). Destination loyalty and repeat behaviour: An application of optimum stimulation measurement. International Journal of Tourism Research, 6, 439-447.

56.

Oppermann

(1999). Predicting destination choice: A discussion of destination loyalty. Journal of Vacation Marketing, 5, 51-65.

57.

Oppermann

(2000). Tourism destination loyalty. Journal of Travel Research, 39, 78-84.

58.

Pan

G. W.

Laws

(2003). Tourism development of Australia as a sustained preferred destination for Chinese tourists. Asia Pacific Journal of Tourism Research, 8, 37-47.

59.

Pike

(2005). Tourism destination branding complexity. Journal of Product and Brand Management, 14, 258-259.

60.

Pike

(2006). Destination decision sets: A longitudinal comparison of stated destination preferences and actual travel. Journal of Vacation Marketing, 12, 319-328.

61.

Pike

(2007). Consumer-based brand equity for destinations: Practical DMO performance measures. Journal of Travel & Tourism Marketing, 22, 51-61.

62.

Pike

(2009). Destination brand positions of a competitive set of near-home destinations. Tourism Management, 30, 857-866.

63.

Pike

Bianchi

Kerr

Patti

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

64.

Pike

Scott

(2009). Destination brand equity among the host community—A potential source of competitive advantage for DMOs: The case of Brisbane, Australia. Acta Turistica, 21, 160-183.

65.

Podsakoff

P. M.

Mackenzie

S. B.

Lee

J.-Y.

Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879-903.

66.

Podsakoff

P. M.

Organ

(1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12, 531-543.

67.

Prosser

(2000). Regional tourism research: A scoping study. Lismore, New South Wales, Australia: Center for Regional Tourism Research.

68.

Reichheld

F. F.

Markey

R. G.

Jr. Hopton

(2000). The loyalty effect—The relationship between loyalty and profits. European Business Journal, 12, 134-139.

69.

Ruzzier

M. K.

(2010). Extending the tourism destination image concept into customer-based brand equity for a tourism destination. Ekonomska Istraživanja, 23, 24-42.

70.

Stern

B. B.

(2006). What does brand mean? Historical-analysis method and construct definition. Journal of the Academy of Marketing Science, 34, 216-223.

71.

Thompson

J. R.

Cooper

P. D.

(1979). Additional evidence on the limited size of evoked and inept sets of travel destination. Journal of Travel Research, 17, 23-25.

72.

Tourism Research Australia. (2011). The international visitor survey. Retrieved from http://www.tourism.australia.com/statistics/international.aspx

73.

Tourism Research Australia. (2012). Latin American short-term visitor arrivals: The trends and outlooks for Australia. Retrieved from http://www.ret.gov.au/tourism/Documents/tra/Forecasts/2012/LatinAmericaConsultancy22May.pdf

74.

Woodside

A. G.

Sherrell

(1977). Traveler evoked, inept, and inert sets of vacation destinations. Journal of Travel Research, 16, 14-18.

75.

Yoona

Uysalb

(2005). An examination of the effects of motivation and satisfaction on destination loyalty: A structural model. Tourism Management, 26, 45-56.

76.

Zeithaml

Bitner

M. J.

(2000). Service marketing: Integrating customer focus across the firm (2nd ed.). New York, NY: Irwin McGraw-Hill.