intangibles that cannot be easily measured (e.g. friendliness). Because of the relationship between the functional-psychological and attribute-holistic components, the attribute-holistic and holistic image of a destination can be either a functional image or a psychological image. The common-unique axis recognizes what is similar about a destination (common to any destination) and what is particularly unique to a destination. Thus, the destination image is separated into two different components, attribute and holistic. Each of these components can then include either functional characteristics (related to the tangible aspects of the destination) or psychological characteristics (related to the intangible aspects), which in turn can reflect the common or unique characteristics of a destination (Rezende-Parker et al., 2003). In the context of tourism, functional and truly unique characteristics are not difficult to provide, they exist in any special destination such as monuments, attractions, symbols or special landscapes. Tourists will use their thinking and emotions to evaluate destinations and form images of certain places.
There are many proposals for the components of destination image measurement. Gallarza et al. (2002) selected 25 empirical destination studies that measured attributes based on destination image, reviewed all the attributes used in the studies and organized the most common attributes into a functional-psychological axis and suggested that there is a balance between functional and psychological attributes. However, different destinations or types of tourism have their own characteristics so the components of cognitive image may vary.
Summarizing previous studies, Beerli and Martín (2004a) demonstrated the lack of uniformity in the attributes measuring an individual's perception of a destination. This issue was reaffirmed when, from the initial basic study of Beerli and Martín (2004a), destination image was assessed from 9 components (Table 2.3), while the same two authors, when measuring destination image for the case of Lanzarote (Spain) in Beerli and Martín (2004b), included only 5 components (Table 2.4). In addition, a number of other studies (Table 2.4) also contributed to proving the assertion of Beerli and Martín (2004a).
Table 2.3: Destination image components/attributes
Natural resources
Weather
Temperature Rainfall Humidity
Number of hours of sunshine
Beach
Sea water quality Sandy or rocky beach Length of beach Overcrowding of
the beaches
Rural diversity
Nature Reserve
protected
Lakes, mountains, deserts, etc.
The diversity and uniqueness of
flora and fauna Entertainment and recreation Amusement parks
Entertainment and sports activities
sports
Golf, fishing, hunting, skiing, scuba diving, etc.
Water park
Walking Zoo
Adventure activities
Casino
Nightlife Shopping
Natural environment
The beauty of the landscape
The appeal of cities and towns
Cleanliness
Overloaded condition
Air and noise pollution
Traffic congestion
Common infrastructure
Development and quality of roads, airports and ports
Private and public transport
Development of medical services
economy
Development of telecommunications
Commercial Infrastructure Development
Level of construction development
Culture, history and art
Museums, historical sites, monuments, etc.
Festivals, concerts,
...
Handicrafts
The Art of Good Cooking Etiquette
Religion
Customs and lifestyle
Social environment
The hospitality and friendliness of the local people
Unhappiness and poverty Quality of life Language barriers
Tourism infrastructure
Hotels and self-catering accommodations
service
Number of beds
Class
Quality
Restaurant
Quantity
Class
Quality
Bars, discos, clubs
Easy access to destination
Destination excursions
Travel center
Tourism Information Network Political and Economic Factors
Political stability
Political tendencies
Economic development
Safe
Crime rate
Terrorist attack
Price
Atmosphere of the destination
Luxury Trendy Famous Place
Family-Oriented Destination
Strange Mysterious
Relax Stress
Happy, fun
Happy Bored
Attract or interest
Source: Beerli and Martín (2004a, p. 659)
Table 2.4: Summary of components of destination image
Author
Destination | Ingredients | |
Choi and colleagues (1999) | Hong Kong | 1. Activities and atmosphere 2. Travel and shopping information 3. Cultural differences 4. Communication and language |
Leisen (2001) | New Mexico, USA | 1. Social culture 2. Natural 3. Activities 4. Climate |
Beerli and Martin (2004b) | Lanzarote, Spain | 1. Natural and cultural resources 2. Entertainment, tourism and general infrastructure 3. Atmosphere 4. Society and environment 5. Sun and sand |
Chi and Qu (2008) | Eureka Springs, Arkansas, USA | 1. Tourism environment 2. Natural factors 3. Entertainment and events 4. Historical attractions 5. Infrastructure 6. Accessibility 7. Relax 8. Outdoor activities 9. Price and value |
Qu and colleagues (2011) | Oklahoma, USA | 1. Quality of experience 2. Attraction factor 3. Environment and infrastructure 4. Entertainment and activities 5. Cultural traditions |
Aksoy and Kiyci (2011) | Turkey | 1. History and cultural heritage 2. Shopping and food 3. Quiet atmosphere 4. Fresh climate 5. Regional structure and architecture |
Artuğer et al. (2013) | Antalya, Turkey | 1. Natural resources 2. Infrastructure 3. Atmosphere 4. Social environment 5. The value of money |
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Source: Author compiled from previous studies
Studies over the past two decades have demonstrated that image is a complex and valuable concept in understanding travel behaviors as it influences the decision-making process of destination choice (Chon, 1990; Echtner and Ritchie, 1991; Jenkins, 1999; Baloglu and McCleary, 1999a, 1999b; Sirakaya and
et al., 2001; Gallarza et al., 2002; Pike, 2002; Chen and Tsai, 2007; Govers et al., 2007; Chi and Qu 2008; Dominique and Lopes, 2011; Stepchenkova and Eales, 2011) and have important impacts on post-decision behaviors including involvement (on-site experience), evaluation (satisfaction), and future behavioral intentions (revisit intention and willingness to recommend) (Mansfeld, 1992; Bigné et al., 2001; Lee and Tideswell, 2005; Chen and Tsai, 2007; Chi and Qu, 2008; Žabkar et al., 2010; Assaker et al., 2011).
According to Echtner and Ritchie (1991), Tasci and Gartner (2007), different levels of types, components and aspects of destination image impact the customer purchase process differently. Therefore, the destination image at a specific time for a specific market must be investigated and described to use resources in marketing and other destination management decisions more effectively (Tasci, 2007).
2.5. Travel barriers
From the theoretical review of the relationship between the concepts of travel motivation, destination image and destination choice, it can be seen that in different studies, its structure, components as well as its antecedent variables are very different. In these studies, most of the studies focus on the demographic characteristics of tourists, and very few studies mention the role of the antecedent variable of travel barriers in the decision to choose a destination. However, studies in the field of marketing in general have also noted that the prominent conclusion to predict actual purchase can be enhanced by considering barrier situations (Belk, 1975; Tybout and Hauser, 1981). Therefore, this study will investigate the role of the antecedent variable of travel barriers in the relationship between travel motivation, destination image and destination choice applied to the case of Binh Dinh tourist destination.
The concept of travel barriers has its origins in the leisure barrier theory. Leisure barriers were proposed in the 1960s. These barriers can be viewed as factors that “limit the formation of leisure preferences, inhibit or prevent participation and enjoyment of leisure” (Jackson, 1991, p. 279). In the tourism sector, travel barriers have been recognized since the 1980s. Sönmez and Graefe (1998) have
define travel barriers as undesirable events that range from a frustrating travel experience (psychological risk) to serious threats to the health or life of tourists (physical, health or terrorist threats). Travel barriers can slow down, reduce or completely prevent the process of tourism participation and destination choice, which is reflected in the attractiveness and competitiveness of the destination compared to other destinations. According to Kerstetter et al. (2005), travel barriers are the main factors that prevent people from initiating or continuing to travel. Travel barriers refer to factors that hinder the continuation of a trip, causing an inability to initiate a trip, leading to an inability to maintain or increase the frequency of trips, and/or leading to negative impacts on the quality of tourism (Hung and Petrick, 2010).
Barrier analysis is to determine whether obstacles exist, and therefore whether and to what extent barriers to travel exist. Usually, in the case of barriers, it is necessary to determine how they affect the process of destination image formation and destination choice. Um and Crompton (1990) found that barrier factors influence alternative choices in both the late arousal and final decision stages. Chen et al. (2013) concluded that travel barriers affect the formation of destination image in the early decision-making stage. Hong et al. (2006) applied the concept of barriers as inhibitors to destination choice. Therefore, travel barriers are considered as antecedent variables of destination image and destination choice.
Crawford et al. (1991), and Srisutto (2010) argue that the hierarchy of barriers exists on three levels: (1) intrapersonal (personality, attitudes, mood), (2) interpersonal (relationships with friends, family, and others such as lack of companionship), and (3) structural (arising from conditions in the external environment such as cost, time, transportation). Crawford et al. (1991) propose a hierarchical model that links the intrapersonal (antecedent), interpersonal, and structural levels together. The authors propose that people experience the three types of barriers in a sequential order starting at the intrapersonal level, moving to the interpersonal level, and extending to the structural level.
While intrapersonal barriers influence leisure preferences, structural barriers influence leisure participation after preferences have been made.
The development of leisure barriers as a multidimensional construct has allowed for a more systematic analysis of travel barriers. Tian et al. (1996) noted that the barriers that limit museum attendance in Texas include six factors: cost, time, difficult access, repetition, product failure, and lack of interest. Crawford and Godbey (1987) identified a barrier structure consisting of economic barriers, limited time, access, and opportunity. Hsu and Lam (2003) identified five important barriers that limit Chinese residents from visiting Hong Kong: high cost, lack of travel agents, short vacations, difficulty obtaining travel documents, and safety. Hong et al. (2006) found nine barriers when tourists choose to visit national parks in Korea: overcrowding; no one to accompany them; high physical demands; children; uncomfortable in social situations; inconvenient transportation; lack of suitable accommodation; time consuming; high travel costs. According to Mao (2008), there are four barriers for Chinese tourists to travel abroad including: physical, interpersonal, environmental and cultural. More specifically, the research results of Sparks and Pan (2009) show that the basic barriers for Chinese international tourists to Australia are external factors (exchange rate barriers, flight time, cost, language, visa regulations, China-Australia relationship) and safety factors (risk and safety).
Studies have shown that the most influential barriers to tourists participating in tourism are money and time. In contrast, the least influential barriers are friends, and internal difficulties such as safety, skills needed to participate, and information gathering skills. However, individuals can overcome (negotiate) some barriers, such as cost, if the desire to visit the destination is strong enough (Crawford et al., 1991; Chen et al., 2013).
2.6. Choose a destination
2.6.1. Concept
Tourist destination choice is one of the important topics studied by many scholars (Crompton, 1992; Crompton and Ankomah, 1993;
Ankomah et al., 1996; Corey, 1996; Awaritefe, 2004; Ahmed et al., 2010; Gill, 2011; Hasan and Mondal, 2013). In a broad sense, a destination can be viewed as a product or service. Destination choice, at the macro level, is conceptualized as the process of selecting a destination from competing alternatives (Woodside and Lysonski, 1989; Crompton, 1992; Tham et al., 2013). At the micro level, destination choice is understood as a function of the interaction between practical constraints such as time, money, skills and destination image (Woodside and Lysonski, 1989). Emphasizing the role of travel motivation in destination choice, Hsu et al. (2009, p. 289) argue that “destination choice can be conceptualized as a tourist’s choice of a destination from a set of alternatives; this choice is determined by various motivational factors”.
According to Sirakaya and Woodside (2005), most of the models developed for the tourism industry are based on the theoretical framework developed by the general consumer behavior theory. Similar to the consumer purchase decision process, the tourist destination choice process is very complex. Choosing a destination is a multi-step decision-making process that starts with a travel motive, then the potential tourist, with varying degrees of effort, depending on the level of involvement, will collect information about other destinations to assist in making a rational decision about the destination choice (Raaij, 1986; Crompton, 1992). Involvement as an antecedent to other purchase behavior-related variables including information search, learning, evaluation of alternatives, perception of brand image, and finally, decision-making based on brand preference (Goossens, 2000). According to Friedrichs and Opp (2002), there are three levels of customer involvement: low, medium and high. Choosing a destination is a high involvement decision associated with a high level of risk (Jang and Cai, 2002). This potential tourist puts considerable effort into making a destination decision to reduce the level of perceived risk (Zaichkowsky, 1985).
According to Huybers (2004), destination choice models can be used to analyze the choices that tourists make when choosing between different tourist destinations. Destination choice model analyses can provide information
valuable determinants of tourist destination choice. To date, there are many types of models that explain destination choice behavior. The models can be classified into four types: (1) choice set models; (2) decision grid models; (3) multi-destination models; and (4) general tourism models. Among them:
The choice set model (Um and Crompton, 1990; Crompton and Ankomah, 1993; Seddighi and Theocharous, 2002) focuses on the transition or selection process that an individual uses to select a single destination from a larger set of destinations. This model assumes that the list of destinations that a tourist chooses is a deterministic set, but in reality this is not possible.
The decision grid model (Fesenmaier and Jeng, 2000) examines travel decisions at a level of analysis that integrates different aspects of travel planning and the relationships between them. According to Fesenmaier and Jeng (2000), there are three basic levels of decisions: (1) core decisions, which are detailed pre-trip planning including main destination, date/length of trip, travel parties/members, accommodation, travel route, overall travel budget; (2) secondary decisions, which occur pre-trip but are also largely considered flexible to accommodate potential changes such as secondary destinations, activities, attractions, and (3) en route decisions, which are not considered until the traveler is actually on the road such as the amount of time spent stopping on the road, restaurant stops, shopping places, items to buy, budget for gifts and souvenirs, etc.
The multi-destination model (Lue et al., 1993; Yang et al., 2013) is used to explain the participation process where more than one destination is considered and visited in a single trip. This model is quite complex because there are many destinations that can be considered for subsequent visits.
The general tourism model (Woodside and Lysonski, 1989) is based on consumer theory and focuses on the process by which individuals choose their destinations. Woodside and Lysonski (1989) provide a model to explain the perception and choice of destinations by tourists (Figure 2.3). The authors suggest that all destinations perceived by tourists will fall into one of four clusters corresponding to different levels of attitude: considering, indifferent,