The role of authenticity in forming slow tourists' intentions: Developing an extended model of goal-directed behavior

Tourism Management 57 (2016) 397e410

Contents lists available at ScienceDirect

Tourism Management journal homepage: www.elsevier.com/locate/tourman

The role of authenticity in forming slow tourists' intentions: Developing an extended model of goal-directed behavior Bo Meng a, Kyuhwan Choi b, * a b

Department of Tourism Management at Shanxi University, No. 92, Wucheng Road, Taiyuan 030006, Shanxi Province, PR China Department of International Tourism at Dong-A University, 255, Gudeok-ro, Seo-gu, Busan 602-760, South Korea

h i g h l i g h t s
This study incorporates authenticity-related constructs into the model of goal-directed behavior.
The results implied that the extended MGB is an improvement over the MGB.
All antecedents of intention were found to be important constructs in our extended model.
This study provides an insightful understanding of the slow tourist decision-making process.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 October 2013 Received in revised form 22 February 2016 Accepted 5 July 2016

Despite the rapid growth in the slow tourism industry, research on slow tourists' behavior is rare. This study develops an extended model of goal-directed behavior to more comprehensively explain the formation of tourists' intentions to visit a slow tourism destination. Specifically, the extended model incorporates the critical constructs (i.e., perception of authenticity, knowledge, and information search behavior) into the original model of goal-directed behavior (MGB). The results of an on-site survey (N ¼ 387) revealed that the model provides a satisfactory fit with the data and explains greater amounts of variance in behavioral intention. Three authenticity-related variables formed positive and significant causal relationships with the constructs in the extended model of goal-directed behavior. All the constructs in the original MGB were significant predictors of both desire and intention. The theoretical and practical implications of the findings are discussed. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Slow tourism Perception of authenticity Model of goal-directed behavior (MGB)

1. Introduction The problems of global warming, environmental pollution and significant socio-economic inequalities are forcing tourism companies and tourists to evaluate the impact from the tourism industry (Frey & George, 2010). As responses to these threats, tourism researchers have made efforts to develop new alternative tourism paradigms to make the tourism industry sustainable (e.g., responsible tourism, justice tourism, ethical tourism, eco-tourism, propoor tourism, volunteer tourism, peace tourism) (CeballosLascurain, 1991; Goodwin & Francis, 2003; Middleton, 1998; Weeden, 2001). As such, one of the tourism industry's responses to the future

* Corresponding author. E-mail addresses: [email protected] (B. Meng), [email protected] (K. Choi). http://dx.doi.org/10.1016/j.tourman.2016.07.003 0261-5177/© 2016 Elsevier Ltd. All rights reserved.

sustainability directions was the slow tourism, which applies the “slow philosophy” from the slow food and slow city movements (Dickinson & Lumsdon, 2010; Heitmann, Robinson, & Povey, 2011). Slow tourism refers to the form of tourism in which the tourists take their time on their journey and engage with people and places (Dickinson & Lumsdon, 2010; Gardner, 2009; Slow Travel.com, 2013). This tourism form shares common ideas with the sustainable tourism paradigms (e.g., alternative tourism, eco-tourism, and responsible tourism). For instance, alternative tourism is considered “developed from a reaction to the negative impacts of mass tourism” (Smith & Eadington, 1992, p.3). More specifically, responsible tourism is about “treating local people as people” “understanding the culture you are visiting” “respecting the people who are hosting your visit” and “treading softly on the environment of your hosts” (Lea, 1993, p.708). Consistent with these forms of tourism, the slow idea achieves sustainable development

398

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

through authentic experiences (e.g., deep engagement with unspoiled nature and places; slow activities in the form of training/ education and community participation). As such, slow tourism and its related slow destinations focus on authentic experiences as well as the benefits that accrue to the localities (Timms & Conway, 2012). Despite of the importance of slow tourism, little is known about how slow tourists behave. From the practical respective, comprehending and predicting slow tourists' behavior is important to developing proper marketing strategies and increasing tourism market shares. To reach this goal, the factors influencing tourists' decision-making processes can provide some clues. Among sociopsychological theories, the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) are considered as a representative theories used in previous studies. The TRA suggests that an individual can make a rational decision and reasoned choice depending upon the relationship between attitudes toward behavior, subjective norms, and actual behavior (Ajzen, 1985). This theory assumed that individuals' decisions are derived from the intensity of volitional efforts for the specific decisions (Fishbein & Ajzen, 1975). Unlike TRA which are solely dependent on volitional aspects of one's decision/behaviors, the TPB provides a welldefined structure which explains human behaviors by adding the concept of perceived behavior control (PBC) to the original antecedents in the TRA (i.e., attitude and subjective norms) (Ajzen, 1991). Although these theories, the TRA and the TPB, are often used to understand tourists' intentions, the limitations of these theories have also been noted. That is, they do not consider the influence of past behavior, affective factors and motivational processes (Conner & Armitage, 1998; Leone, Perugini, & Ercolani, 1999). Thus, based on the conceptualization of the TRA and TPB, Perugini and Bagozzi (2001) proposed the Model of Goal-directed Behavior (MGB) to enhance the capacity and address the limitations of the TPB. They claimed that motivational, affective, and habitual processes should be considered during the decisionmaking process. In terms of the motivational process, desire was suggested as an important variable in forming behavioral intention. In terms of the affective factors, anticipated affective reaction to a specific behavior is a significant determination that can reflect individuals' emotions. Since anticipated emotion constructs represent the motive of promoting a positive situation and avoiding a negative situation of affairs, two types of emotions, positive and negative anticipated emotion, are believed to be the predictors of desire. In terms of the habitual process, past behavior or behavior is considered as a critical variable influencing the decision-making process (Perugini & Bagozzi, 2001). Therefore, the MGB incorporates desire, positive and negative anticipated emotions, and past behaviors along with the original factors in the TPB. Moreover, researchers have emphasized the necessity for a revision of existing socio-psychological theories to include new constructs that are considered critical in a certain context or that alter existing paths among latent variables (Ajzen, 1991; Conner & Abraham, 2001; Oh & Hsu, 2001). Slow tourism activities provide more detailed and authentic experiences (Dickinson & Lumsdon, 2010). Hence, slow tourists are in essence those who have a strong orientation towards a sense of authenticity and an intention to participate in authentic activities (e.g., Ramkissoon & Uysal, 2011; Shen, Guo, & Wu, 2012). In other words, individuals whose perceptions of authentic activities are especially sensitive are potential customers of slow tourism. Thus, tourists who seek out authentic touristic experiences provide important clues for understanding slow tourist decision-making processes. Furthermore, the formation of perceptions mainly

depends on an individual's knowledge of certain fields and information about specific products/services (Baloglu, 2001). Thus, both knowledge of authentic activities and behavior associated with searching for authenticity-related information are believed to be effective variables in the formation of authenticity perception. Thus, this study extended the MGB by incorporating three constructs (i.e., perception of authenticity, knowledge and information search behavior), which are expected to improve understanding of tourists' intentions. The specific purposes of this study are the following: 1) to develop a model by inserting perceptions of authenticity, knowledge and information search behavior into the original MGB (attitude, subjective norm, perceived behavior control, positive anticipated emotion, negative anticipated emotion, frequency of past behavior, desire and behavioral intention) in the context of slow tourism and 2) to provide practical suggestions and strategies for tourism marketers and government agencies. This study helps verify the context of slow tourism and provides an insightful understanding of the slow tourist decision-making process. 2. Literature review 2.1. Slow tourism and its authentic characteristics Although there is no clear definition of slow tourism, slow tourism is believed by researchers as a new form of tourism (Dickinson & Lumsdon, 2010; Oh, Assaf, & Baloglu, 2016). Generally, slow tourism is defined as traveling more slowly, taking in the sights, and immersing oneself in the local landscape. Further, “slowing” the pace of a holiday provides more opportunities to interact and connect with local people and places on a deeper level (Dickinson & Lumsdon, 2010; Dickinson, Lumsdon, & Robbins, 2011). Actually, slow tourism is a concept modeled after the slow food and slow city movements (Heitmann et al., 2011). Thus, slow tourism shares the “slow” concept with these movements: addressing the issue of time poverty by encouraging more thorough connections to local people, places and life (Gardner, 2009; Heitmann et al., 2011; Slow Travel, 2013). The idea of “slow” derives from slow food in Italy in the 1970s. Local organizations taught visitors how to best enjoy their products and, having created a market for their products, set up a worldwide mail-order business (Perini & Watson, 2001). From then on, this new business has begun to establish itself in the food industry, as mass-produced food gives way to a growing preference for seasonal, local and traditional products (Nosi & Zanni, 2004). By extending the slow food movement's philosophy to all aspects of urban living, the slow city appeared and differentiated itself from other cities by broadcasting an anti-globalization message, promoting local food and cultural differences, and fostering networks and transnational cooperation (Heitmann et al., 2011). Slow City Movement, a nongovernmental organization established in 1999 in Italy, has spread across 25 countries and has certified more than 100 cities worldwide (Cittaslow, 2013). These slow ideas reflected a social phenomenon caused by a modern society characterized by fast living and people who are often over-scheduled, task-orientated, and stressed (Dickinson & Lumsdon, 2010). By traveling slow, authentic experiences usually result in the sustainable development. For instance, slow food requires the standards of eco-friendly products/services and slow modes of transportations are often lowcarbon means of travel (Cohen, 2002; Dickinson et al., 2011). However, as Scott (2011) and Weaver (2011) have criticized the validity of sustainable tourism, slow tourism's contributions to the environment remain in doubt by scholars. For instance, in a slow

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

situation, tourists' personal benefit of travel may outweigh the nebulous societal costs of climate change. If a large number of slow tourists fly to a destination and then rely on local public transport, in the destination context, their holiday meets the low-carbon criteria, but overall the carbon footprint remains high (Dickinson & Lumsdon, 2010). Tourists would naturally like to choose a convenient way (traveling by air) rather than a slow way. Additionally, the slow tourism rejects homogenization and is usually small-scaled. Yet this label of slow can attract people's attention, which may paradoxically ruin the slow atmosphere by overcrowding with tourists (Heitmann et al., 2011; Knox, 2005). Still, although there are potent criticisms, this new tourism paradigm is believed to be a growing market in the tourism industry (Dickinson & Lumsdon, 2010; Heitmann et al., 2011). According to evidence from several sources, essential elements in slow tourism include slow food (e.g., local food) (Hjalager & Richards, 2002; Long, 2013; Parasecoli & Lima, 2012; Smith & Costello, 2009), slow transportation (e.g., local buses and trains) (Dickinson & Lumsdon, 2010) and slow places/cities (slow cities are those smaller areas which highlight the succession of seasons, are respectful of citizens' health, offer authenticity of products and food, have a rich of fascinating craft traditions and valuable works, and are characterized by spontaneity of religious rites. Such slow cities, respect traditions through the joy of a slow and quiet living, such as one can observe in Orvieto in Italy and Damyang in Korea) (Cittaslow, 2013; Mayer & Knox, 2006; Timms & Conway, 2012). Specifically, food-related slow experiences are achieved through a connection to cultural heritage by sharing aspects of production, preparation and consumption with slow tourists. In this manner, the food is an expression of a specific community, and culinary heritage is composed not only of ingredients and dishes but also bodily practices and living performances that define individuals and communities (Hall, Sharples, Mitchell, Macionis, & Cambourne, 2003). Some modes of transportation, such as local trains, local buses, cycling, and walking, also enhance slow experiences. Tourists who use these modes experience a greater connection to the outdoors and nature, and by removing them from their hectic schedule, tourists are able to rediscover a sense of self (Fallon, 2012; Watts, 2008). In addition, slow tourism activities are connected to specific slow places (e.g., slow cities). There, slow tourists are encouraged to relax and refresh their mind and body and interact with the local community (Dickinson et al., 2011; Timms & Conway, 2012). Due to the particular characteristics of slow tourism, slow tourists can perceive high-authenticity experiences that are enjoyable in ways that “fast tourism” is not (Dickinson & Lumsdon, 2010). Thus, the perception of authenticity in slow activities is the critical factor in tourists' decision-making process. Tourism authenticity was described as follows: tourist settings can be viewed as a continuum, with the fast and frontmost region being the one most purposed for show and the backmost region being the one that is most authentic (MacCannell, 1976). From this definition, slow tourism, which requires more time and deeper engagement, apparently shows more of the “backmost region” to tourists. In the tourism-related literature, a considerable amount of attention has been given to measures of authenticity (e.g., Brown, 1996; Cohen, 1988; Wang, 1999). Generally, three approaches are exemplified: the objectivist approach, the constructivist approach and the postmodernized approach (Wang, 1999). The three approaches reflect the transition from the modern tourist's concern with the “cool” authenticity which is associated with the originality of an object (i.e., the objectivist approach), then to the authenticity projected onto toured objects by tourists or tourism producers in terms of

399

imagery, expectations, beliefs, etc. (i.e., the constructivist approach), and finally to the post-tourist's requirement for the experience of “hot” authenticity, which resides in a tourist's feelings of being true to oneself (i.e., post-modernized approach) (Cohen, 2002; Wang, 1999). As such, the objectivist approach assumes that authenticity comes from the originality of a toured object, such as a site or tourism attraction; the constructivist approach refers to objects linked to identity and meaning (Cohen, 1988). The post-modernized approach is associated with the concept of existential authenticity, which is defined as “an existential state of being that is to be activated by tourism” (Wang, 1999, p.359). It resides in the subject (i.e., the tourist) rather than in the toured object. Of these three approaches, the existential approach to authenticity is most appropriate for understanding contemporary tourists' experiences because in empirical studies, this construct has more explanatory power (Kim & Jamal, 2007; Wang, 1999). Thus, this study employed the approach of existential authenticity to measure slow tourism.

2.2. Model of goal-directed behavior (MGB) and its extended model The MGB proposed by Perugini and Bagozzi (2001) has been recognized by many researchers as a useful framework for understanding human intentions. The MGB is an extended model based on the Theory of Planned Behavior (TPB) and the Theory Reasoned Action (TRA). However, the MGB differs from previous models in three respects: 1) the intention to perform a behavior is primarily motivated by the desire to perform the behavior, and this desire is assumed to reflect the effects of attitude, subjective norms, perceived behavioral control, and anticipated emotions; 2) anticipated emotions for a specific behavior can be imperative variables in a decision-making process; and 3) past behavior or habits are assumed to be a significant determinant of desire, intention and human behaviors (Perugini & Bagozzi, 2001). Specifically, the MGB identified antecedents toward a certain behavior in the original TPB (i.e., attitude, subjective norm, and perceived behavioral control) that affect intention indirectly through desire (Leone, Perugini, & Ercolani, 2004; Perugini & Bagozzi, 2001). The role of desire as the major predictor of intention mediates the attitude, the subjective norm, perceived behavioral control and anticipated emotions in the MGB (Bagozzi, 1992; Hunter, 2006; Leone et al., 1999). In the TPB, if positive attitudes are strong enough, they will influence intentions. However because motivational content has been described as “someone intends to do something only if he is motivated to do it” (Davis, 1986, p74), researchers have believed that attitudes cannot activate intention without desire (Perugini & Bagozzi, 2001; Taylor, Ishida, & Wallace, 2009). Second, anticipated affective reactions to the performance or non-performance of a behavior are also important determinants of intention (e.g., Conner & Armitage, 1998; Triandis, 1977). In an uncertain situation, people may have forward-looking emotions toward future behaviors (Gleicher et al., 1995). With other original variables of the TPB, both positive and negative emotions are assumed to predict desire in that these emotions lead to the dynamic self-regulatory process implied by the appraisal of success or failure (Carver & Scheier, 1990). Finally, the influence of past behavior was found to have an effect on individual desire and intention (e.g., Bagozzi & Warshaw, 1992; Bentler & Speckart, 1981; Fredricks & Dossett, 1983). Past behavior is regarded as a proxy of habits and is expected to influence both desire and intention (Conner & Armitage, 1998). It was theorized and empirically shown that past behavior influences desire and intention (Ouellette & Wood, 1998; Perugini & Bagozzi, 2001).

400

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

Researchers have emphasized the necessity for a revision of the existing socio-psychological theories to include new constructs that are considered critical in a certain context or that alter existing paths among latent variables (Ajzen, 1991; Conner & Abraham, 2001; Oh & Hsu, 2001). New variables introduced to the original model should be imperative factors that affect decision-making behaviors. This process was described by Bagozzi (1992) as the broadening and deepening of a theory. In tourism-related contexts, researchers have modified the MGB by incorporating some new constructs (Han & Ryu, 2012; Lee, Song, Bendle, Kim, & Han, 2012; Song, Lee, Norman, & Han, 2012). For instance, Han and Ryu (2012) extended the MGB by incorporating important factors relating to re-buying intentions and tested the new model in a full-service restaurant setting. Lee et al. (2012) developed an extended MGB to explore potential travelers' decision-making processes by introducing constructs of perception of influenza A H1N1 and nonpharmaceutical interventions when the risk during the 2009 H1N1 infection discouraged international travel. Song et al. (2012) extended the MGB by incorporating the perception of gambling strategy with respect to the behavioral intentions of casino visitors. In this regard, this study extended the original MGB by including the perception of authenticity, knowledge, and information search behavior into the slow tourists' intention-formation process. 2.3. Slow tourism and MGB In order to explore slow tourist behavior, our study chooses MGB as a framework for the following reasons. First, as stated above, the MGB is an excellent model in explaining tourist behavior compared to previous models. Although some socio-psychological theories such as TRA and TPB were employed to examine tourist behavior, the MGB was empirically demonstrated to have more explanatory power in predicting tourists' behaviors in various tourism and hospitality contexts including restaurants (e.g., Han & Ryu, 2012) and tourism destination marketing (Lee et al., 2012; Song, You, Reisinger, Lee, & Lee, 2014). In particular, the MGB was also used to understand tourist behaviors in eco/sustainable tourism. These forms of tourism usually have elements in common with slow tourism (e.g., environmentally friendly activities and green hotels) (Han & Yoon, 2015; Song et al., 2012). Thus, the MGB can be employed in our study as a useful model in examining slow tourist behaviors. Second, our study chose the MGB as the theoretical background after considering the features of slow tourism. Slow tourism is an emerging concept with various sustainable/ green elements (e.g., interaction with local people, culture, and food; use of low-carbon modes of transportation, etc.) (Fallon, 2012; Timms & Conway, 2012). Since slow tourism is much different from mass tourism, slow tourists would experience some inconvenience. In this sense, slow tourists should have a certain goal to achieve while traveling (Oh et al., 2016). Therefore, the MGB, which is used to predict a goal behavior, is the optimal framework for examining slow tourists' behaviors. Third, as a new phenomenon, slow tourism is inconvenient to the tourists who have already gotten used to mass tourism. In other words, it is necessary for a slow tourist to overcome some difficulties to achieve such a trip. In addition, since the green benefits are also found in slow tourism, keeping the rapid growth of slow tourism also helps the sustainable development of tourist destinations. As somewhat of a hard and green trip, prompting a continuous trip is important for the future development of slow tourism. Thus, tourists' past habits should be considered as a critical construct inducing tourists' continuous behavior. Therefore, the MGB, which indeed reflects frequency of past behavior, is considered to be an ideal model for slow tourism.

2.4. Hypothetical relationships 2.4.1. Perception of authenticity, desire, knowledge and information search behavior Perceptions, formed by the individuals' attitudes, interests, and opinions acquired during their lives, are responses to the cognition of objects, behavior and events (Oliver, 1997). Some empirical studies supported the possible relationship between perception of authenticity and desire (e.g., Lin & Wang, 2012; Ramkissoon & Uysal, 2011; Shen et al., 2012). Ramkissoon and Uysal (2011) found that perceptions of authenticity play a critical role in altering tourists' cultural behavioral intentions. Lin and Wang (2012) claimed that the authenticity perceived by tourists affects their souvenir-repurchasing intention. These studies demonstrated that people who had a stronger orientation towards the sense of authenticity and who perceived more authenticity in tourism activities have a greater intention to participate in authentic activities. Because the role of desires in predicting intention can be justified by the strong motivational content and explains how intentions become energized (Perugini & Bagozzi, 2001), those with a more authenticity-conscious mind are more likely to choose slow tourism with a strong desire. In addition, previous literature assumes that the formation of certain perceptions or cognitions primarily depends on variables such as an individual's knowledge about certain fields and the extent to which the individual seeks out information about a specific product or service (Baloglu, 1999; Oliver, 1997). Knowledge can be considered as the search for prior knowledge, which is formed when the tourists acquire information and store it in their longterm memory (Bettman, 1979; Ratchford, 2001). Meanwhile, information search behavior occurs when the internal search cannot provide sufficient and adequate information and the consumers need to collect information from the external world (Bettman, 1979). Knowledge and information search behavior are highly related constructs that apply to different consumers' situations (Engel, Blackwell, & Miniard, 1995; Hawkins, Best, & Coney, 2000). Therefore, both prior knowledge of internal memory and information from the external world can enable consumers to focus on particular product attributes (Brucks, 1985; Fodness & Murray, 1997). In this sense, the slow tourists who had prior knowledge of authentic activities and who are actively searching for information about authentic tourism activities are more sensitive to the perceptions of authentic activities. Based on the literature, the following hypotheses are proposed: H1. Knowledge has a positive influence on the perception of authenticity. H2. Information search behavior has a positive influence on the perception of authenticity. H3. Perceptions of authenticity have a positive influence on desire.

2.4.2. Attitude, subjective norm, perceived behavioral control, and desire An attitude toward a behavior refers to the degree to which an individual has a favorable/unfavorable evaluation of performing a specific behavior (Ajzen, 1991). Individuals tend to have a positive attitude when the outcomes of a specific behavior are positively evaluated; thus, one is likely to have a strong attitude to perform such a behavior (Ajzen, 1991). The desire to perform the act was added to strengthen the predictive power in explaining intention, as it was the main motivational source to perform an action (Malle,

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

1999; Malle & Knobe, 1997). A subjective norm is defined as a perceived social pressure to perform or not to perform a particular behavior (Ajzen, 1991). An individual is likely to consider and comply with the opinions of other people when performing a specific behavior. The influences are usually from friends, family, and colleagues (Bearden & Etzel, 1982; Cheng, Lam, & Hsu, 2005). Similar to attitude, a subjective norm would not directly influence an individual's behavioral intention. It indirectly affects the behavioral intention through desire (Perugini & Bagozzi, 2001). Perceived behavior control is a non-volitional dimension that refers to an individual confidence or ability to carry out a behavior. Many studies have verified it as an important factor forming intention, which affects the decision-making formation in the TPB (Ajzen, 1991; Ajzen & Madden, 1986; Conner & Abraham, 2001; Taylor & Todd, 1995M). In general, the strength of an individual's intention to undertake a specific behavior is decided by whether the person has sufficient resources or opportunities to perform that behavior (Ajzen & Madden, 1986; Ajzen, 1991). However, Lokhorst and Staats (2006) discovered that there might be some intention to perform the behavior even if attitudes and subjective norms are entirely neutral. As a result, it is assumed that perceived behavior control reinforces an individual's desire and actual behavior in the MGB (Carrus, Passafaro, & Bonnes, 2008; Perugini & Bagozzi, 2001; Prestwich, Perugini, & Hurling, 2008). By applying the MGB to tourism-related domains, growing empirical evidence has revealed that attitudes, subjective norms and perceived behavioral control were significant variables in the formation of desire (Han & Ryu, 2012; Kim, Lee, Lee, & Song, 2012; Lee et al., 2012; Song et al., 2012). For instance, Lee et al. (2012) proposed an extended MGB to understand tourist's decisionmaking processes under the condition of the 2009 H1N1 influenza crisis and identified that attitudes and subjective norms affect behavioral intention indirectly through desire. Han and Ryu (2012) extended MGB in the context of repurchase decision-making and proved that attitudes, subjective norms and perceived behavior control played a critical role in the formation of intention through desire. Moreover, studies relating to slow elements also revealed the possible influential relationships existing between these factors (i.e., attitude, subjective norms, and perceived behavior control) and slow tourist behavior. Kuo and Dai (2012) investigated the lowcarbon tourism (i.e., the use of ecofriendly means of transport, choosing environmentally certified hotels, preferring local food and/or organic food), finding that tourists' attitude, subjective norms, perceived behavior control significantly influenced tourists behaviors. Jeoushyan, Su, and So (2013) examined behaviors of food festival visitors (similar to slow food). Their study results indicated that visitors' attitude, subjective norms, and perceived behavior control behavioral intentions. In the study on green lodging, which is very similar to slow accommodation, Han, Hsu, and Sheu (2011) suggested that attitude, subjective norms, and perceived behavior control positively affected the intention to stay in a green hotel. Therefore, based on the literature review, this study posits the following hypotheses in the context of slow tourism: H4. Attitudes have a positive influence on desire. H5. Subjective norms have a positive influence on desire. H6. Perceived behavior control has a positive influence on desire.

2.4.3. Anticipated emotions and desire Individuals usually consider the emotional consequence of both achieving a goal and failing to achieve a goal (Bagozzi & Pieters,

401

1998; Carver & Scheier, 1990). Leone et al. (2004) stated that anticipated emotions affect behavioral desire because the emotional constructs represent the hedonic motive of promoting a positive situation of affairs and avoiding a negative situation of affairs. Therefore, two types of emotions, positive and negative anticipated emotions, are believed to be the predictors of desire and intention. In empirical studies, Perugini and Bagozzi (2001) showed that two anticipated emotions have a critical role in forming desire. Kim et al. (2012) identified that both positive anticipated emotions and negative emotions significantly influence the international tourists' desires. A recent study by Chen (2013) investigated the airline passengers who participated in carbon offset plans, revealing that positive anticipated emotions have a positive effect on desire. In the studies about slow customers' behaviors, the study results demonstrated that slow tourists' anticipated emotions influence their behaviors. For instance, in the study of green activities, Han Hwang, and Woods (2014) found that green golfers' positive or negative emotions significantly influence their desire. Additionally, Han and Yoon (2015) studied green consumerism in hotel customers (i.e., slow lodging) and revealed that both positive and negative anticipated emotions significantly influence the desire toward the behavior. Thus, based on the literature review, two anticipated emotions for a target behavior are hypothesized to significantly influence the individuals' desire-related target behavior in slow tourism. H7. Positive anticipated emotion has a positive influence on desire. H8. Negative anticipated emotion has a positive influence on desire.

2.4.4. Frequency of past behavior, desire, and intention Frequency of past behavior is usually considered to be a proxy of habit, and studies agree that if an individual performs a particular behavior frequently and habitually, this behavior will enhance the individual's desire and behavioral intentions (Bagozzi & Warshaw, 1992; Bentler & Speckart, 1981). Studies have demonstrated that desire is a strong predictor of intention (Bagozzi, 1992; Perugini & Bagozzi, 2001). According to Bagozzi (1992), desire is a proximal cause of intention, while other variables in the MGB are distal causes in which influence is mediated by desire. In the tourism and leisure contexts, a relationship among these three variables can be found in many empirical studies (Chen, 2013; Han et al., 2014; Song et al., 2012). For instance, Chen (2013) confirmed that desire is the most important determinant of passengers' intention in carbon offset schemes. Han et al. (2014) investigated players' favorable/unfavorable attitudes toward screen golf. The results showed that their past behavior was a powerful predictor of their intention to play screen golf. Moreover, some studies further suggested the relationships among three variables in the context of tourism with slow elements. When Song et al. (2012) examined the tourists' intention to participate in environmental activities, which are a kind of slow activities, the study results indicated that there are positive and causal relationships among past behavior, desire, and intention. As a kind of slow food tourism, Lee, Bruwerb, and Song (2015) investigated wine tourists' decision-making processes using the MGB framework. Their results revealed that desire had a positive influence on behavioral intention. In addition, based on the literature review, this study posits the following hypotheses: H9. Past behavior has a positive influence on desire.

402

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

Fig. 1. Conceptual model.

H10. Past behavior has a positive influence on intention. H11. Desire has a positive influence on intention. The proposed model is presented in Fig. 1. The model includes the original variables in the MGB and new constructs (i.e., perception of authenticity, knowledge, and information search behavior). 3. Method 3.1. Measures for study variables A list of measurement items was generated after an extensive review of research on human behavior, tourist behavior theories, and tourism authenticity (Ajzen & Madden, 1986; Ajzen, 1985, 1991; Bentler & Speckart, 1981; Lam & Hsu, 2004; Oh & Hsu, 2001; Perugini & Bagozzi, 2001; Ramkissoon & Uysal, 2011; Shen et al., 2012; Wang, 1999). The survey measurement items for each construct are shown in Table 1. To ensure the face validity of the constructs, four tourism scholars were invited to review and refine the items to reflect the contents of slow tourism. Three newly added constructs, knowledge, information search behavior, and perception of authenticity, were selected from the literature. Four items were used to assess knowledge as suggested by previous research (Bettman & Park, 1980; Park & Lessig, 1981; Smith & Park, 1992) (e.g., “I feel very knowledgeable about authentic tourism activities”), and three items were used to assess information search behavior as suggested by previous research (Moorthy, Ratchford, & Talukdar, 1997) (e.g., “Before going a trip, I

normally scan the information about authentic tourism activities”). To assess the perception of authenticity, four items were developed, as suggested by previous research (Cho, 2012; Shen et al., 2012; Wang, 1999) (e.g., “I like to be connected with local ways of life”). The original MGB was also modified to fit the context of slow tourism. Specifically, tourists' attitudes related to slow tourism were measured with seven items, as suggested by previous research (Ajzen, 1985, 1991; Perugini & Bagozzi, 2001) (e.g., “I think that going for slow tourism is a positive”). By the same context, the subjective norm was measured with five items, as suggested by previous research (Ajzen, 1985, 1991; Perugini & Bagozzi, 2001) (e.g., “Most people who are important to me think it is okay for me to go for slow tourism”). Perceived behavior control was evaluated with five items, as suggested by previous research (Ajzen, 1985, 1991; Perugini & Bagozzi, 2001) (e.g., “Whether or not I travel for slow tourism is completely up to me”). Anticipated emotions were operationalized with ten items (five items on positive emotion and five items on negative emotion) (e.g., “If I succeed in achieving my goal (going for slow tourism), I will feel excited”; “If I fail in achieving my goal (going for slow tourism), I will feel unsatisfied”), as suggested by previous research (Lee et al., 2012; Perugini & Bagozzi, 2001, 2004). Lastly, desire was measured with four items (e.g., “I want to travel by slow tourism in the near future”), and intention was measured by five items (e.g., I intend to travel by slow tourism in the near future), as suggested by previous research (Lee et al., 2012; Perugini & Bagozzi, 2001, 2004). All items were measured on a 7-point Likert-type scale (from 1 ¼ not at all, 7 ¼ very much) except frequency of past behavior. The frequency of past behavior was assessed as a continuous variable, ranging from

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

403

Table 1 Measurement items, standardized loadings, Cronbach alpha and composite reliability. Variables and measurement items Knowledge (KL) I feel very knowledgeable about authentic tourism activities If a friend asked me about authentic tourism activities, I could give them advice about different activities related to authenticity in tourism If I have to find authentic tourism activities, I would need to gather very little information in order to make a wise decision I feel very confident about my ability to tell the difference among different authentic activities Information Search Behavior (ISB) Before going a trip, I normally scan the information about authentic tourism activities When choosing a trip, I normally use the information concerning its authenticity I spend time seeking information about the authentic tourism activities Perception of Authenticity (PA) I like to be connected with local ways of life I want to experience the unique life style and customs experience I like the calm and peaceful atmosphere during the visit I like the feeling of being myself meaningful during traveling Attitude (AT) I think that slow tourism is positive I think that slow tourism is useful I think that slow tourism is valuable I think that slow tourism is benefit I think that slow tourism is attractive I think that slow tourism is enjoyable I think that slow tourism is necessary Subject Norm (SN) Most people who are important to me think it is okay for me to go for slow tourism Most people who are important to me support that I go for slow tourism Most people who are important to me understand that I go for slow tourism Most people who are important to me agree with me about going for slow tourism Most people who are important to me recommend going for slow tourism Perceived Behavioral Control (PBC) Whether or not I travel for slow tourism is completely up to me I am capable of going for slow tourism I am confidence that if I want, I can go for slow tourism I have enough resource, time and opportunities to go for slow tourism Positive Anticipated Emotion (PAE) If I succeed in achieving my goal (going for slow tourism), I will feel excited If I succeed in achieving my goal (going for slow tourism), I will feel glad If I succeed in achieving my goal (going for slow tourism), I will feel satisfied If I succeed in achieving my goal (going for slow tourism), I will feel happy If I succeed in achieving my goal (going for slow tourism), I will feel proud Negative Anticipated Emotion (NAE) If I failed in achieving my goal (going for slow tourism), I will feel unsatisfied If I failed in achieving my goal (going for slow tourism), I will feel angry If I failed in achieving my goal (going for slow tourism), I will feel disappointed If I failed in achieving my goal (going for slow tourism), I will feel worried If I failed in achieving my goal (going for slow tourism), I will feel sad Desires (DE) I want to travel by slow tourism in the near future I wish to travel by slow tourism in the near future I am eager to travel by slow tourism in the near future My wish to travel by slow tourism in the near future can be described desirably Behavioral Intention (BI) I intend to travel by slow tourism in the near future I am planning to travel by slow tourism in the near future I will make an effort to travel by slow tourism in the near future I will certainly invest time and money to travel by slow tourism in the near future I am willing to travel by slow tourism in the near future

Standardized loadings

Cronbach's alpha

Composite reliability

0.914 0.941

0.964

0.930

0.929 0.981 0.885

0.951

0.903

0.924 0.926 0.846 0.857

0.939

0.898

0.932 0.930 0.896 0.883 0.907 0.902 0.920

0.971

0.965

0.907 0.924 0.939 0.971 0.962

0.974

0.966

0.902 0.887 0.898 0.924

0.843

0.924

0.912 0.940 0.949 0.950 0.903

0.970

0.962

0.904 0.929 0.953 0.978 0.969

0.977

0.960

0.957 0.969 0.895 0.884

0.958

0.940

0.938 0.960 0.883 0.860 0.906

0.959

0.937

0.942 0.940

Note 1. Goodness-of-fit statistics: c2 ¼ 2552.144 (df ¼ 944, p < 0.001), RESEA ¼ 0.066, CFI ¼ 0.937; NFI ¼ 0.903.

1 ¼ never, 5 ¼ occasionally, 7 ¼ very many times (Perugini & Bagozzi, 2001). 3.2. Data collections and demographic profile The survey was conducted using a nonprobability convenience sampling technique. This type of survey approach has been widely employed in consumer behavior and marketing, especially, when the entire population is too large (using an independent random

sampling that perfectly represents the entire population is almost impossible) (e.g., Han, 2013; Song et al., 2012). A brief description of slow tourism was first presented to the respondents before they started. Moreover, the definition of slow tourism was also included in the questionnaire. Survey participants traveling on Galmaet-gil (Seagull Road) in Busan were considered potential respondents. Seagull Road is a typical slow tourism destination in South Korea where tourists can experience the uniqueness of oceanic culture. To achieve the goal of understanding

404

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

slow tourists' decision making process, respondents with slow tourism experiences were targeted. An on-site survey was conducted for Korean domestic visitors since they almost presented the total visitors (Yonhap News, 2012). Only respondents who had experiences with at least three slow activities or programs on Seagull Road (e.g., slow-walking-related activities; oceanic culture exhibitions; seafood experiential programs; and bird-watching programs) were invited to participate in the survey. The questionnaires were completed in the presence of the field surveyors. Four well-trained surveyors randomly distributed 500 questionnaires to tourists at three main entrances/exits on Seagull Road. To obtain a representative sample, field surveyors distributed questionnaires on both weekdays and weekends from July 10 to July 20, 2013. Additionally, to ensure higher response and usable rates, completeness was checked on site. Finally, 412 questionnaires were collected (a response rate of 82.4%). After excluding unusable responses and extreme multivariate outliers, 387 were used for analysis. SPSS 12 and AMOS 5 were used to analyze the data. According to the two-step approach by Anderson and Gerbing (1988), first, Confirmatory Factor Analysis (CFA) with the maximum likelihood estimation method was used to estimate a measurement model, and Structural Equation Modeling (SEM) was then used to test the causal relationships. Descriptive information on the sample revealed that 47.5% of the tourists were male and 52.5% were female. The most frequently reported age groups of the respondents were 20e29 (35.7%) and 30e39 years (33.9%). Among respondents, approximately 51% reported that they were single and 49% stated that they were married. With a regard to education, most of the respondents held a bachelor's or higher degree (77.5%).

4. Results 4.1. Measurement model To confirm if the data assumed multivariate normality, Mardia's standardized coefficient was used. Since Mardia's standardized coefficient for the measurement model was 42.92, which is higher than the criterion of 5, the data in the current study was deemed non-normally distributed (Byrne, 2006). Thus, bootstrapping was used to estimate structural equation modeling (Nevitt & Hancock, 2001). Meanwhile, as in Table 2, the

correlations between the study constructs proposed in the model were generally equal to or less than 0.75, indicating no high multicollinearity (Green, 1978). Then, a confirmatory factor analysis (CFA) was used to assess the measurement model and test data quality involving construct reliability and validity. Table 1 shows that the Cronbach's alpha values were above the cut-off point of 0.7, indicating an acceptable level of reliability for each construct (Nunnally & Bernstein, 1994). The fit statistics of the measurement model indicated that the model fits the data well (c2 ¼ 2552.144, df ¼ 944, p < 0.001; RESEA ¼ 0.066, CFI ¼ 0.937; NFI ¼ 0.903). As shown in Table 1, the composite reliability values, which evaluate the multi-item scales used in this study, were between 0.898 and 0.966, exceeding the minimum requirement of 0.600 (Bagozzi & Yi, 1988). This finding indicated that the multi-item measures used in the present study are highly reliable. A construct validity test was conducted using factor loadings for each construct to determine the average variance extracted (AVE) and the correlation between constructs. As shown in Table 2, convergent validity exists because all AVE values exceeded the suggested cut-off of 0.50 (Hair, Black, Babin, Anderson & Tatham, 2006). Discriminant validity was also tested. Fornell and Larcker (1981) indicated that discriminant validity exists when the proportion of variance extracted in each construct exceeds the square of the coefficient representing its correlation with other constructs. As show in Table 2, all AVE values were greater than the squared correlations between constructs, indicating an adequate level of discriminant validity. When comparing MGB and EMGB (Table 3), Chi-square tests indicated that there was a significant difference between the two models, D c2 (450) ¼ 706.978, p < 0.001. The R2 for behavioral intention in the MGB improved from 0.575 to 0.617 by including perception of authenticity, knowledge and information search behavior. Therefore, the EMGB performed better than the MGB at explaining slow tourists' behavioral intentions.

4.2. Structural model results As presented in Fig. 2, the results of SEM confirmed that the proposed structural model fits the data well: c2 ¼ 2234.186, df ¼ 990, NFI ¼ 0.916, RMSEA ¼ 0.057. In terms of hypothesis testing, hypotheses 1 and 2 posited that knowledge and information search behavior have a positive effect on the perception of

Table 2 Correlations among latent constructs (Squared correlation). KL KL ISB PA AT SN PBC PAE NAE DE BI AVE Mean SD

1.000 0.621 0.525 0.194 0.168 0.072 0.162 0.212 0.274 0.334 0.769 3.347 1.386

ISB (0.385) (0.275) (0.037) (0.028) (0.005) (0.026) (0.045) (0.075) (0.112)

1.000 0.516 0.192 0.147 0.042 0.210 0.141 0.267 0.304 0.757 3.803 1.382

PA

(0.266) (0.036) (0.021) (0.002) (0.044) (0.019) (0.071) (0.092)

1.000 0.546 0.383 0.363 0.473 0.034 0.535 0.475 0.688 4.958 1.206

AT

(0.298) (0.146) (0.131) (0.223) (0.001) (0.286) (0.225)

1.000 0.636 0.553 0.656 0.112 0.667 0.553 0.797 5.471 1.021

SN

(0.404) (0.305) (0.430) (0.012) (0.444) (0.305)

1.000 0.534 0.613 0.611 0.616 0.525 0.853 5.353 1.095

PBC

(0.285) (0.375) (0.373) (0.379) (0.275)

1.000 0.522 0.043 0.594 0.595 0.752 5.175 1.112

(0.272) (0.002) (0.352) (0.354)

PAE

NAE

DE

BI

1.000 0.179 (0.032) 0.682 (0.465) 0.582 (0.338) 0.837 5.252 1.061

1.000 0.248 (0.061) 0.240 (0.057) 0.827 3.479 1.297

1.000 0.751 (0.564) 0.798 5.086 1.155

1.000 0.748 4.611 1.172

Note 1. The numbers in the parenthesis indicate squared correlation among latent constructs; all correlations are significant at p < 0.01. Note 2. ISB ¼ Information Search Behavior; KL ¼ Knowledge; PA ¼ Perception of Authenticity; AT ¼ Attitude; SN ¼ Subjective Norm; PBC ¼ Perceived Behavioral Control; PAE ¼ Positive Anticipated Emotion; NAE ¼ Negative Anticipated Emotion; DE ¼ Desire; BI¼ Behavioral Intention. Note 3. AVE ¼ Average Variance Extracted. Note 4. Frequency of Past Behavior (FPB) was not included in the measurement model since it was a single indicator. Mean and SD values for frequency of past behavior were 2.144 and 0.798.

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

405

Table 3 Comparison of MGB and EMGB.

MGB EMGB Suggested value

c2

df

CMIN/df

NFI

CFI

RMSEA

R2 for DE

R2 for BI

1527.208 2234.186

540 990

2.828 2.257 <3.0

0.926 0.916 >0.90

0.946 0.951 >0.90

0.069 0.057 <0.08

0.626 0.634

0.575 0.617

Note1: DE ¼ desires; BI ¼ behavioral intention.

Fig. 2. Findings from structural equation model (N ¼ 387).

authenticity. Both predictor variables (bKL/ PA ¼ 0.271, t ¼ 4.631, p < 0.01; bISB/ PA ¼ 0.294, t ¼ 5.109, p < 0.01) exerted a positive influence on the perception of authenticity. Thus, H1 and H2 were supported.

Furthermore, all predictor variables were statistically significant in predicting desire (DE) as follows: perception of authenticity (bPA/ DE ¼ 0.087, t ¼ 2.015, p < 0.05), attitude (bAT/ DE ¼ 0.180, t ¼ 2.535, p < 0.05), subject norm (bSN/ DE ¼ 0.160, t ¼ 2.606,

Table 4 Results of the structural model. Direct effect PA KL ISB PA AT NB PBC PAE NAE FPB DE

0.271** 0.294** e e e e e e e e

*p < .05, **p < .01, ***p < .001.

Indirect effect

Total effect

DE

BI

PA

DE

BI

PA

DE

BI

e e 0.987* 0.180* 0.160* 0.217** 0.195* 0.121* 0.531*

e e e e e e e e 0.953** 0.577*

e e e e e e e e e e

0.024* 0.026* e e e e e e e e

0.014* 0.015* 0.050* 0.104* 0.092* 0.125* 0.112* 0.070* 0.307* e

0.271** 0.294** e e e e e e e e

0.024* 0.026* 0.087* 0.180* 0.160* 0.217** 0.195* 0.121* 0.531* e

0.014* 0.015* 0.050* 0.104* 0.092* 0.125* 0.112* 0.070* 1.260** 0.577*

406

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

p < 0.05), perceived behavioral control (bPBC/ DE ¼ 0.217, t ¼ 3.807, p < 0.01), positive anticipated emotion (bPAE/ DE ¼ 0.195, t ¼ 2.805, p < 0.05), negative anticipated emotion (bNAE/ DE ¼ 0.121, t ¼ 2.688, p < 0.05), and frequency of past behavior (bFPB/ DE ¼ 0.531, t ¼ 2.007, p < 0.05); thus, H3, H4, H5, H6, H7, H8, and H9 were supported. Overall, seven constructs (i.e., PA, AT, SN. PBC, PAE, NAE, and FPB) played an essential role in explaining the formation of the tourists' desire for slow tourism. In addition, desire (bDE/ BI ¼ 0.577, t ¼ 3.135, p < 0.05) and frequency of past behavior (bFPB / BI ¼ 0.953, t ¼ 3.373, p < 0.01) served as important antecedents in predicting the tourists' behavioral intention for slow tourism. Moreover, perception of authenticity was a significant and direct predictor of desire, which in turn indirectly influenced behavioral intention. This finding reveals that tourists' perception of authenticity can influence their desire along with the antecedents that have been tested in the MGB. To show all changes in dependent variables as one-unit changes in an independent variable, the total effect on each dependent variable was examined in this study. As shown in Table 4, FPB, with the largest total impact (1.260), is the most powerful antecedent in predicting BI, followed by desire (0.577), perceived behavioral control (0.125), positive anticipated emotion (0.112), attitude (0.104), subjective norm (0.092), negative anticipated emotion (0.070), perception of authenticity (0.050), information search behavior (0.015), and knowledge (0.014). 5. Discussion Little research has focused on slow tourists' decision-making processes. The current study aims to provide a deeper understanding of slow tourists' behavioral intention by incorporating three critical constructs, knowledge, information search behavior, and perception of authenticity, into the original MGB. The effects of knowledge, information search behavior, and perception of authenticity in the EMGB were supported by the model's increased power in predicting slow tourists' intention. In terms of hypothesis testing, the study results revealed a satisfactory fit for the data, and all 11 hypotheses in the study model were supported. Specifically, the findings indicated that FPB and DE were found to be the most important constructs for the intention formation. It is noteworthy that the relative importance of DE and FPB was not consistent with previous studies, which reported that desire was the most significant construct in predicting behavioral intention (e.g., Bagozzi & Dholakia, 2006; Taylor, 2007). However, it is possible that antecedent variables in the model differed based on the context (Song et al., 2011). Perceived behavior control, negative anticipated emotion and subjective norms were found to be more important determinants to desire, while other constructs, such as attitude and positive anticipated emotion, are less critical variables to desire. Overall, the study achieved all its objectives. 5.1. Theoretical implications The current study has some theoretical implications. First, the prediction of slow tourists' behavioral intention towards slow tourism in the extended MGB is well supported. The results of the comparison between the two models implied that the original MGB is insufficient for understanding tourists' behavioral intention in the slow tourism context, while the EMGB is an improvement over the MGB. This process was described by Bagozzi (1992) as the broadening and deepening of a theory. Researchers emphasized that for a revision of the existing socio-physiological

theories to include new constructs, some criteria should be met first: the proposed variables are behavior-specific and comply with the principle of compatibility; the factors are conceptually independent of existing constructs of the original model; and the newly added constructs are considered casual factors that determine decisions (Ajzen, 1991; Conner & Abraham, 2001; Oh & Hsu, 2001). In this study, added constructs (i.e., perception of authenticity; knowledge; information search behavior) apparently met these criteria and theoretically contribute to improve the understanding of the complicated process of slow tourist decisionmaking. Second, according to previous research on the possible relationships among perception of authenticity, desire and intention, the perception of authenticity in slow tourism was proven to be a significant predictor in determining desire and behavioral intention. This finding suggests that a tourist's awareness and understanding of authenticity in tourism can prompt him or her to participate in various forms of slow activities. Thus, tourists who preferred authentic activities can be targeted as potential slow tourism customers. Furthermore, the results also demonstrated that both knowledge and information search behavior have significant influence on the perception of authenticity. This result provided us with clues regarding how to increase an individual's perception of authenticity. Third, as the results indicated, all antecedents of desire in the original MGB were found to be important constructs in our extended model. Many previous studies have emphasized the significance of these variables (e.g., Han & Ryu, 2012; Han et al., 2014; Kim et al., 2012; Lee et al., 2012). This study agrees with other studies in the literature. Hence, slow destination operators should actively develop and execute various marketing strategies to increase attitudes, subjective norms, perceived behavior control, and positive and negative emotions. Fourth, our results indicated that the frequency of past behavior had the greatest total impact on behavioral intention. In previous studies employing the MGB (e.g., Perugini & Bagozzi, 2001; Song et al., 2012; Taylor et al., 2009), desire was one of the predominant variables explaining tourists' decision-making processes. However, in a slow tourism context, FPB plays a major role in explaining intention formation. In other words, slow tourists' decision-making processes differ from decision-making in other tourism-related settings. This finding is consistent with Han and Ryu (2012) study concerning restaurant customers' re-buying decision-making behavior. In their study, the frequency of past behavior had a greater role in intention than the original key variables in MGB. 5.2. Managerial implications From a practical perspective, the marketing focus of businesses should create and strengthen their reputations of offering an authentic tourism experience, through building various management strategies. A strong reputation of providing an authentic and detailed tourism experience can be used as a precious treasure for every slow tourism destination. Therefore, advertising the detailed, leisurely features of slow tourism products to the public will increase slow-orientated behaviors in tourists' day-to-day lives, and eventually enhance their decisions to purchase slow tourism products. In addition, improving, in general, tourists' authentic awareness and perceptions is one of the critical approaches to encouraging more slow-tourism purchasing decisions. By doing so, the segment of customers attracted to the slow tourism market is expected to increase to a larger share hold.

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

Second, since both knowledge and information search behavior contribute to the formation of authenticity, an emphasis should be place upon how to increase the knowledge of authentic activities (e.g., how to eat slow food; and how to participate in slow walking). Thus, using various resources, supporting the tourists as they learn new approaches about enjoying slow products, by providing them with educational materials, for instance, will contribute to helping them increase their knowledge. In addition, the establishment of a membership system could be introduced to increase the level of individuals' knowledge. Through the membership system, regular educational courses, as well as slow events (e.g., a slow walking competition) should be carried out to spread awareness of slow activities. Moreover, making slow destination information available on the map application in a smartphone would also alert tourists that slow products exist around them. Because information search behavior is also very important to the perception of authenticity, information should be provided through some important channels (e.g., internet; word-of-mouth). Therefore, effective ways to improve the slow reputation would be carried out through: managing social media: tracking and monitoring the reputation of slow tourism products; being an active social media participant; and advertising the characteristics of slow practices to raise awareness. In addition, positive word-of-mouth is a critical factor in forming the perception of authenticity, and thus, favorable slow tourists can be used as message senders to the people around them. A reward system could be built up to stimulate these tourists to bring more newcomers. Third, the significant influence from attitude revealed that an excellent slow experience should be offered by enhancing significant slow tourism attributes (the good feeling of rest; deep engagement in local culture and nature; and enjoying highquality, unique slow food). By surveying the slow tourists' experiences (e.g., their favorite slow food items; favorite slow activities; length of staying in slow destinations; number of companions, etc.), clues can be unearthed to develop new, slow activities for slow destination managers. Consequently, a more appropriate slow program can be developed to the corresponding tourism market. More importantly, quality improvement programs should be introduced to keep “continuous excellence” in slow experiences. Quality strategies, such as benchmarking by learning from other excellent slow destinations and establishing quality standards (e.g., ISO9000 standard), can prompt the achievement of excellent quality in the slow experience. This will ultimately garner positive attitudes in individuals who will participate in slow activities again. Fourth, the study result of the significant influence by subjective norm implied that salient referents (i.e., family, relatives, friends, colleagues, and co-workers) should be located to develop favorable perceptions towards slow tourism. Presenting the benefits of slow tourism (e.g., places of interest, the enjoyment of discovery, learning, and sharing, and a calm and peaceful atmosphere) to the public may improve such referents' favorable perceptions of slow tourism. As the Internet continues to grow as an effective marketing tool, positive outcome beliefs by communicating with these referents through various SNS (social networking service) websites would contribute to enhancing the positive perception of the slow tourism movement. By doing so, these referents would generate supportive actions towards slow tourism. In addition, inviting important referents for a free trip to tourism destinations may also increase their perception of slow benefits. Fifth, because perceived behavior control has a stronger direct effect among antecedents of desire, it is essential to reduce the possible effect of barriers (e.g., the distance of a slow destination for a one-day trip or unclear guidance that fails to explain a destination or how to get there). Destination managers could also run free shuttle buses to reduce the barriers in transportation. Investigating

407

reasonable prices of slow tourism products would reduce monetary barriers. Slow products were generally labeled as a high-quality, however, high-price image. Showing a clear and reasonable price to tourists would make them estimate the costs, and clear out the psychological pressure of the expenditure. In addition, managers could help tourists stimulate their emotional experiences with proper marketing strategies, such as sending free photos to reinforce their happy memories of slow trips. In general, transforming intangible emotions into tangible things would be an effective approach. For example, the souvenir with travelers' names on it can be presented to recall their “slow” memories. A refrigerator magnet made with 100% recycled materials that remind the visitor of their trip and other slow characteristics can be also developed as a decent marketing strategy that supports authenticity without being gimmicky. Finally, the study result from FPB indicated that tourists who have had favorable experiences at a specific slow tourism destination on a number of visits are more willing to go to other slow tourism destinations. For those marketing slow tourism, the development of effective strategies for slow activities is necessary to improve tourists' favorable experiences. 5.3. Limitations and suggestions for future research This study has some limitations. First, the data were collected at slow destinations in a single metropolitan city. Therefore, the findings may not be generalized to all types of slow tourism activities. Future research is needed to test the applicability of the theoretical framework in other slow tourism segments. Additionally, as various elements (e.g., food, accommodation and transportation etc.) exist in slow tourism, unique research on different slow sectors should be carried out. Identifying the attributes of slow tourism and examining the variables, such as attitude and satisfaction, of these slow attributes will help us understand the roles of slow sectors in the choosing of slow tourism. Second, cultural differences should be examined. Future studies should use a sample population that more adequately represents other cultural backgrounds. Third, future research should also ask non - visitors why they do not visit slow destinations or do not prefer the way of slow tourism. Looking at consumer behavior in comparison helps turning non-visitors into visitors. Finally, future research may include some other constructs not considered in the current model when explaining slow tourists' intention-formation process. For example, environmentally friendly tourism behaviors may help in the understanding of the decision-making processes involved when slow tourists participate in nature-based slow activities. In addition, the gap between tourists' awareness and actual behaviors should be examined. The current study contributes to the line of research on the extension of the MGB. Although the MGB and its extended versions have been used widely in the tourism literature, (e.g., Han & Ryu, 2012; Song et al., 2012), little is know about its implication to slow tourism. Taking the perception of authenticity, knowledge and information-search behaviors together with the MGB, the current research indicated that added constructs along with the original MGB are apparently useful in explaining slow tourists' decision-making processes. Therefore, our research adds to a growing body of research examining the extended MGB and significantly improves our understanding of intention formation in the slow tourism context. Acknowledgements This work was supported by the Dong-A University research fund.

408

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

Appendix

Knowledge (KL)

Mean S.D.

Skew

Kurtosis

I feel very knowledgeable about authentic tourism activities If a friend asked me about authentic tourism activities, I could give them advice about different activities related to authenticity in tourism If I have to find authentic tourism activities, I would need to gather very little information in order to make a wise decision I feel very confident about my ability to tell the difference among different authentic activities Information Search Behavior (ISB) Before going a trip, I normally scan the information about authentic tourism activities When choosing a trip, I normally use the information concerning its authenticity I spend time seeking information about the authentic tourism activities Perception of Authenticity (PA) I like to be connected with local ways of life I want to experience the unique life style and customs experience I like the calm and peaceful atmosphere during the visit I like the feeling of being myself meaningful during traveling Attitude (AT) I think that slow tourism is positive I think that slow tourism is useful I think that slow tourism is valuable I think that slow tourism is benefit I think that slow tourism is attractive I think that slow tourism is enjoyable I think that slow tourism is necessary Subject Norm (SN) Most people who are important to me think it is okay for me to go for slow tourism Most people who are important to me support that I go for slow tourism Most people who are important to me understand that I go for slow tourism Most people who are important to me agree with me about going for slow tourism Most people who are important to me recommend going for slow tourism Perceived Behavioral Control (PBC) Whether or not I travel for slow tourism is completely up to me I am capable of going for slow tourism I am confidence that if I want, I can go for slow tourism I have enough resource, time and opportunities to go for slow tourism Positive Anticipated Emotion (PAE) If I succeed in achieving my goal (going for slow tourism), I will feel excited If I succeed in achieving my goal (going for slow tourism), I will feel glad If I succeed in achieving my goal (going for slow tourism), I will feel satisfied If I succeed in achieving my goal (going for slow tourism), I will feel happy If I succeed in achieving my goal (going for slow tourism), I will feel proud Negative Anticipated Emotion (NAE) If I failed in achieving my goal (going for slow tourism), I will feel unsatisfied If I failed in achieving my goal (going for slow tourism), I will feel angry If I failed in achieving my goal (going for slow tourism), I will feel disappointed If I failed in achieving my goal (going for slow tourism), I will feel worried If I failed in achieving my goal (going for slow tourism), I will feel sad Desires (DE) I want to travel by slow tourism in the near future I wish to travel by slow tourism in the near future I am eager to travel by slow tourism in the near future My wish to travel by slow tourism in the near future can be described desirably Behavioral Intention (BI) I intend to travel by slow tourism in the near future I am planning to travel by slow tourism in the near future I will make an effort to travel by slow tourism in the near future I will certainly invest time and money to travel by slow tourism in the near future I am willing to travel by slow tourism in the near future Frequency of Past Behavior (FPB) How many times have you traveled for a slow tourism in the past 12 months

3.392 3.276 3.397 3.323

0.142 0.345 0.230 0.264

0.260 0.365 0.286 0.360

References Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl, & J. Beckman (Eds.), Action control: From cognition to behavior (pp. 11e29). Heidelberg: Springer. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179e211. Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes,

1.425 1.509 1.418 1.477

3.845 1.425 0.070 0.390 3.829 1.427 0.170 0.498 3.736 1.493 0.048 0.597 4.821 4.857 5.090 5.062

1.298 1.316 1.299 1.308

0.315 0.345 0.546 0.443

0.134 0.058 0.329 0.047

5.503 5.447 5.459 5.219 5.608 5.527 5.534

1.113 1.079 1.119 1.117 1.119 1.089 1.101

0.355 0.415 0.511 0.196 0.533 0.462 0.533

0.030 0.364 0.244 0.158 0.014 0.319 0.247

5.361 5.382 5.444 5.224 5.299

1.144 1.147 1.116 1.135 1.203

0.364 0.390 0.185 0.223 0.459

0.030 0.364 0.244 0.158 0.014

5.299 5.049 5.258 5.064

1.177 1.219 1.242 1.146

0.389 0.292 0.378 0.355

0.075 0.203 0.101 0.225

5.054 5.235 5.377 5.359 5.235

1.098 1.116 1.111 1.139 1.151

0.034 0.194 0.274 0.431 0.223

0.077 0.069 0.109 0.263 0.068

3.775 3.333 3.509 3.379 3.400

1.328 1.340 1.347 1.372 1.385

0.103 0.146 0.019 0.029 0.045

0.103 0.146 0.019 0.029 0.045

5.191 5.173 5.111 4.870

1.158 1.210 1.273 1.253

0.177 0.248 0.270 0.142

0.021 0.149 0.136 0.124

4.684 4.563 4.726 4.418 4.664

1.254 1.229 1.214 1.349 1.236

0.255 0.188 0.204 0.031 0.170

0.158 0.143 0.273 0.214 0.140

2.144 0.798 0.020 0.941

intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453e474. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411e423. Bagozzi, R. P. (1992). The self-regulation of attitudes, intentions, and behavior. Social Psychology Quarterly, 178e204. Bagozzi, R. P., & Dholakia, U. M. (2006). Antecedents and purchase consequences of customer participation in small group brand communities. International Journal of Research in Marketing, 23(1), 45e61. Bagozzi, R. P., & Pieters, R. (1998). Goal-directed emotions. Cognition & Emotion,

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410 12(1), 1e26. Bagozzi, R. P., & Warshaw, P. R. (1992). An examination of the etiology of the attitude-behavior relation for goal-directed behaviors. Multivariate Behavioral Research, 27(4), 601e634. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74e94. Baloglu, S. (1999). A path analytic model of visitation information involving information sources, socio-psychological motivations, and destination image. Journal of Travel & Tourism Marketing, 8(3), 81e90. Baloglu, S. (2001). Image variations of Turkey by familiarity index: Information and experiential dimensions. Tourism Management, 22(2), 127e133. Bearden, W. O., & Etzel, M. J. (1982). Reference group influence on product and brand purchase decisions. Journal of Consumer Research, 92(2), 183e194. Bentler, P., & Speckart, G. (1981). Attitudes “cause” behaviors: A structural equation analysis. Journal of Personality and Social Psychology, 40(2), 226e238. Bettman, J. R. (1979). An information processing theory of consumer choice. Boston: Addison-wesley. Bettman, J. R., & Park, C. W. (1980). Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: A protocol analysis. Journal of Consumer Research, 234e248. Brown, D. (1996). Genuine fakes. In T. Selwyn (Ed.), The tourist image (pp. 33e47). New York: Wiley. Brucks, M. (1985). The effects of product class knowledge on information search behavior. Journal of Consumer Research, 1e16. Byrne, B. M. (2006). In B. Carmichael, & D. M. Peppard (Eds.), Structural equation modeling with EQS: Basic concepts, applications, and programming (2nd ed.). Mahwah, NJ: Lawrence Erlbaum. Carrus, G., Passafaro, P., & Bonnes, M. (2008). Emotions, habits and rational choices in ecological behaviours: The case of recycling and use of public transportation. Journal of Environmental Psychology, 28(1), 51e62. Carver, C. S., & Scheier, M. F. (1990). Origins and functions of positive and negative affect: A control-process view. Psychological Review, 97(1), 19e35. Ceballos-Lascurain, H. (1991). Tourism, ecotourism, and protected areas. Ecotourism and Resource Conservation, 1, 24e30. Chen, F. Y. (2013). The intention and determining factors for airline passengers' participation in carbon offset schemes. Journal of Air Transport Management, 29, 17e22. Cheng, S., Lam, T., & Hsu, C. H. (2005). Testing the sufficiency of the theory of planned behavior: A case of customer dissatisfaction responses in restaurants. International Journal of Hospitality Management, 24(4), 475e492. Cho, M. H. (2012). A study of authenticity in traditional Korean folk villages. International Journal of Hospitality & Tourism Administration, 13(2), 145e171. Cittaslow. (2013, July). Cittaslow international network. Retrieved from: http://www. cittaslow.org/index.php?method¼network&action¼country&id¼2. Cohen, E. (1988). Authenticity and commodification in tourism. Annals of Tourism Research, 15, 371e386. Cohen, E. (2002). Authenticity, equity and sustainability in tourism. Journal of Sustainable Tourism, 10(4), 267e276. Conner, M., & Abraham, C. (2001). Conscientiousness and the theory of planned behavior: Towards a more complete model of the antecedents of intentions and behavior. Personality and Social Psychology Bulletin, 27(11), 1547e1561. Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28(15), 1429e1464. Davis, W. A. (1986). The two senses of desire. In J. Marks (Ed.), The two ways of desire: New essays in philosophical on the concept of wanting (pp. 63e85). Piscataway, NJ: Thansaction Publishing. Dickinson, J. E., & Lumsdon, L. (2010). Slow travel and tourism. Washington, DC: Earthscan. Dickinson, J. E., Lumsdon, L. M., & Robbins, D. (2011). Slow travel: Issues for tourism and climate change. Journal of Sustainable Tourism, 19(3), 281e300. Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1995). Consumer behavior (8th ed.). Fort Worth, TX: Dryden. Fallon, J. (2012). If you're making waves then you have to slow down: Slow tourism and canals. In S. Fullagar, K. Markwell, & E. Wilson (Eds.), Slow tourism: Experiences and mobilities (pp. 143e156). NY: Channel View Publications. Fishbein, M. A., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory of and research. Reading. MA: Addison-Wesley. Fodness, D., & Murray, B. (1997). Tourist information search. Annals of Tourism Research, 24(3), 503e523. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 382e388. Fredricks, A. J., & Dossett, D. L. (1983). Attitudeebehavior relations: A comparison of the Fishbein-Ajzen and the Bentler-Speckart models. Journal of Personality and Social Psychology, 45(3), 501. Frey, N., & George, R. (2010). Responsible tourism management: The missing link between business owners' attitudes and behaviour in the Cape Town tourism industry. Tourism Management, 31(5), 621e628. Gardner, N. (2009). A manifesto for slow travel. Hidden Europe Magazine, 25, 10e14. Gleicher, F., Boninger, D. S., Strathman, A., Armor, D., Hetts, J., & Ahn, M. (1995). With an eye toward the future: The impact of counterfactual thinking on affect, attitudes, and behavior. In N. J. Roese, & J. M. Olsen (Eds.), What might have been: The social psychology of counterfactual thinking (pp. 283e304). Mahwah, NJ: Lawrence Erlbaum.

409

Goodwin, H., & Francis, J. (2003). Ethical and responsible tourism: Consumer trends in the UK. Journal of Vacation Marketing, 9(3), 271e284. Green, P. E. (1978). Analyzing multivariate data. Hinsdale. IL: Dryden Press. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. L. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson. Hall, C. M., Sharples, L., Mitchell, R., Macionis, N., & Cambourne, B. (2003). Food tourism around the world: Development, management and markets. Oxford: Butterworth-Heinemann. Han, S. (2013). The healthcare hotel: Distinctive attributes for international medical travelers. Tourism Management, 36(3), 257e268. Han, H., Hsu, L. T., & Sheu, C. (2011). Application of the theory of planned behavior to green hotel choice: Testing the effect of environmental friendly activities. Tourism Management, 30(3), 325e334. Han, H., Hwang, J., & Woods, D. P. (2014). Choosing virtualerather than realeleisure activities: An examination of the decision-making process in screen-golf participants. Asia Pacific Journal of Tourism Research, 19(4), 428e450. Han, H., & Ryu, K. (2012). The theory of repurchase decision-making (TRD): Identifying the critical factors in the post-purchase decision-making process. International Journal of Hospitality Management, 31(3), 786e797. Han, H., & Yoon, H. J. (2015). Hotel customers' environmentally responsible behavioral intention: Impact of key constructs on decision in green consumerism. International Journal of Hospitality Management, 45, 22e33. Hawkins, D. I., Best, R. J., & Coney, K. A. (2000). Consumer behavior: Building marketing strategy. Boston, MA: Irwin McGraw-Hill. Heitmann, S., Robinson, P., & Povey, G. (2011). Slow food, slow cities and slow tourism. In P. Robinson, S. Heitmann, & P. Dieke (Eds.), Research themes for tourism (pp. 115e127). Wallingford CAB International. Hjalager, A. M., & Richards, G. (2002). Tourism and gastronomy. New York: Routldege. Hunter, G. L. (2006). The role of anticipated emotion, desire, and intention in the relationship between image and shopping center visits. International Journal of Retail & Distribution Management, 34(10), 709e721. Jeoushyan, H., Su, C. S., & So, S. I. A. (2013). Segmenting food festival visitors: Applying the theory of planned behavior and lifestyle. Journal of Convention & Event Tourism, 14(3), 193e216. Kim, H., & Jamal, T. (2007). Touristic quest for existential authenticity. Annals of Tourism Research, 34(1), 181e201. Kim, M. J., Lee, M. J., Lee, C. K., & Song, H. J. (2012). Does gender affect Korean tourists' overseas travel? Applying the model of goal-directed behavior. Asia Pacific Journal of Tourism Research, 17(5), 509e533. Knox, P. (2005). Creating ordinary places: Slow cities in a fast world. Journal of Urban Design, 10, 1e11. Kuo, N. W., & Dai, Y. Y. (2012). Applying the theory of planned behavior to predict low-carbon tourism behavior: A modified model from Taiwan. International Journal of Technology & Human Interaction, 8(4), 45e62. Lam, T., & Hsu, C. H. (2004). Theory of planned behavior: Potential travelers from China. Journal of Hospitality & Tourism Research, 28(4), 463e482. Lea, J. P. (1993). Tourism development ethics in the third world. Annals of Tourism Research, 20(4), 701e715. Lee, S., Bruwerb, J., & Song, H. J. (2015). Experiential and involvement effects on the Korean wine tourist's decision-making process. http://dx.doi.org/10.1080/ 13683500.2015.1050362. Current Issues in Tourism. Lee, C. K., Song, H. J., Bendle, L. J., Kim, M. J., & Han, H. (2012). The impact of nonpharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior. Tourism Management, 33(1), 89e99. Leone, L., Perugini, M., & Ercolani, A. (1999). A comparison of three models attitudebehavior relations in the studying behavior domain. European Journal of Social Psychology, 29(2e3), 161e189. Leone, L., Perugini, M., & Ercolani, A. P. (2004). Studying, practicing, and mastering: A test of the model of goal-directed behavior (MGB) in the software learning domain. Journal of Applied Social Psychology, 34(9), 1945e1973. Lin, C. H., & Wang, W. C. (2012). Effects of authenticity perception, hedonics, and perceived value on ceramic souvenir-repurchasing intention. Journal of Travel & Tourism Marketing, 29(8), 779e795. Lokhorst, A. M., & Staats, H. (2006). Understanding farmers' intentions to carry out agricultural nature management: Using an adapted EMGB. Netherlands: Leiden University. Long, L. M. (2013). Culinary tourism. University Press of Kentucky. MacCannell, D. (1976). The tourist: A new theory of the leisure class. New York: Schocken Books. Malle, B. F. (1999). How people explain behavior: A new theoretical framework. Personality and Social Psychology Review, 3(1), 23e48. Malle, B. F., & Knobe, J. (1997). The folk concept of intentionality. Journal of Experimental Social Psychology, 33(2), 101e121. Mayer, H., & Knox, P. (2006). Slow cities: Sustainable places in a fast world. Journal of Urban Affairs, 28(4), 321e334. Middleton, V. (1998). Sustainable tourism-a marketing perspective. Oxford: butterworth-Heinemann. Moorthy, S., Ratchford, B. T., & Talukdar, D. (1997). Consumer information search revisited: Theory and empirical analysis. Journal of Consumer Research, 263e277. Nevitt, J., & Hancock, G. R. (2001). Performance of bootstrapping approaches to model test statistics and parameter standard error estimation in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 8(3), 353e377.

410

B. Meng, K. Choi / Tourism Management 57 (2016) 397e410

Nosi, C., & Zanni, L. (2004). Moving from “typical products” to “food-related services”: The slow food case as a new business paradigm. British Food Journal, 106(10/11), 779e792. Nunnally, J., & Bernstein, I. (1994). Psychometric theory. NY: McGraw-Hill. Oh, H., Assaf, A. G., & Baloglu, S. (2016). Motivations and goals of slow tourism. Journal of Travel Research, 55(2), 205e219. Oh, H., & Hsu, C. (2001). Volitional degrees of gambling behaviors. Annals of Tourism Research, 28(3), 618e637. Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the customer. New York: McGraw Hill. Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54e74. Parasecoli, F., & Lima, P. A. (2012). Eat your way through culture: Gastronomic tourism as performance and bodily experience. In F. Simone, M. Kevin, & Wilson (Eds.), Slow tourism aspects of tourism: Experiences and mobilities (aspects of tourism) (pp. 69e83). NY: Channel View Publications. Park, C. W., & Lessig, V. P. (1981). Familiarity and its impact on consumer decision biases and heuristics. Journal of Consumer Research, 223e231. Perini, C., & Watson, B. (2001). Slow food: Collected thoughts on taste, tradition, and the honest pleasures of food. Chelsea Green Publishing. Perugini, M., & Bagozzi, R. P. (2001). The role of desires and anticipated emotions in goal-directed behaviours: Broadening and deepening the theory of planned behaviour. British Journal of Social Psychology, 40(1), 79e98. Perugini, M., & Bagozzi, R. P. (2004). The distinction between desires and emotions. European Journal of Social Psychology, 34(1), 69e84. Prestwich, A., Perugini, M., & Hurling, R. (2008). Goal desires moderate intentionbehaviour relations. British Journal of Social Psychology, 47(1), 49e71. Ramkissoon, H., & Uysal, M. S. (2011). The effects of perceived authenticity, information search behaviour, motivation and destination imagery on cultural behavioural intentions of tourists. Current Issues in Tourism, 14(6), 537e562. Ratchford, B. T. (2001). The economics of consumer knowledge. Journal of Consumer Research, 27(4), 397e411. Scott, D. (2011). Why sustainable tourism must address climate change. Journal of Sustainable Tourism, 19(1), 17e34. Shen, S., Guo, J., & Wu, Y. (2012). Investigating the structural relationships among authenticity, loyalty, involvement, and attitude toward world cultural heritage sites: An empirical study of Nanjing Xiaoling Tomb, China. Asia Pacific Journal of Tourism Research, 19(1), 103e121. Slow Travel (2013). Available on www.slowtrav.com. Smith, S., & Costello, C. (2009). Segmenting visitors to a culinary event: Motivations, travel behavior, and expenditures. Journal of Hospitality Marketing & Management, 18(1), 44e67. Smith, V. L., & Eadington, W. R. (1992). Tourism alternatives: Potentials and problems in the development of tourism. Philadelphia: University of Pennsylvania Press. Smith, D. C., & Park, C. W. (1992). The effects of brand extensions on market share and advertising efficiency. Journal of Marketing Research, 296e313. Song, H. J., Lee, C. K., Norman, W. C., & Han, H. (2012). The role of responsible gambling strategy in forming behavioral intention: An application of a model of goal-directed behavior. Journal of Travel Research, 51(4), 512e523. Song, H., You, G. J., Reisinger, Y., Lee, C. K., & Lee, S. K. (2014). Behavioral intention of visitors to an Oriental medicine festival: An extended model of goal directed behavior. Tourism Management, 42, 101e113.

Taylor, S. A. (2007). The addition of anticipated regret to attitudinally based, goaldirected models of information search behaviours under conditions of uncertainty and risk. British Journal of Social Psychology, 46(4), 739e768. Taylor, S. A., Ishida, C., & Wallace, D. W. (2009). Intention to engage in digital piracy: A conceptual model and empirical test. Journal of Service Research, 11(3), 246e262. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144e176. Timms, B. F., & Conway, D. (2012). Slow tourism at the Caribbean's geographical margins. Tourism Geographies, 14(3), 396e418. Triandis, H. C. (1977). Interpersonal behavior. Monterey, CA: Brooks/Cole Publishing Company. Wang, N. (1999). Rethinking authenticity in tourism experience. Annals of Tourism Research, 26(2), 349e370. Watts, L. (2008). The art and craft of train travel. Social and Cultural Geography, 9(6), 711e726. Weaver, D. (2011). Can sustainable tourism survive climate change? Journal of Sustainable Tourism, 19(1), 5e15. Weeden, C. (2001). Ethical tourism: An opportunity for competitive advantage. Journal of Vacation Marketing, 8(8), 141e153. Yonhap News (2012). http://news.naver.com/main/read.nhn? mode¼LSD&mid¼sec&sid1¼102&oid¼001&aid¼0005974153.

Bo Meng, Ph. D. is a Lecturer in the Department of Tourism Management at Shanxi University, P. R. China. His primary research interests lie in tourists' behavior and sustainable tourism. Dr. Meng has published in various professional journals in the field of hospitality and tourism.

Kyuhwan Choi, Ph. D. is a Professor in the Department of International Tourism at Dong-A University in Busan, South Korea. He is the Dean of Office of Student Affairs & Career Development in Dong-A University. He got his PhD from Rikkyo University, Japan. His research interests include hospitality education, tourists' behavior and tourism marketing.