Formation of Tourist Behavioral Intention and Actual Behavior

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1 Formation of Tourist Behavioral Intention and Actual Behavior Cathy H.C. Hsu 1, Songshan (Sam) Huang 2 1 School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Kowloon, Hong Kong (hmhsu@polyu.edu.hk) 2 School of Management, University of South Australia, Adelaide, Australia (Sam.Huang@unsa.edu.au) ABSTRACT The theory of planned behavior (TPB) has been used to examine behavior formation in a wide range of activities. Based on a comprehensive literature review, an extended TPB model of tourists was proposed to investigate the relations amongst constructs of the model with the addition of motivation and actual behavior. An instrument was developed based on previous tourism and marketing studies as well as focus groups. A two-wave data collection was implemented. Data were collected from 1,524 Beijing, Shanghai, and Guangzhou residents in stage one and 311 respondents from the same cohort in stage two. Results of the study demonstrated that the proposed model with tourist motivation fit the data very well. However, the model integrated with both tourist motivation and actual behaviour was not tenable, which suggests that while TPB constructs predict behavioral intention, behavioral intention may not necessarily lead to actual tourist behavior. Keywords: Theory of planned behavior; behavior formation; behavioral model; Chinese outbound tourism; travel motivation 1. INTRODUCTION To take adequate actions in tourism marketing or planning, one must understand which motivational factors influence individuals travel decisions, how attitudes are formed, and how various reference groups affect travel behaviors (e.g., Moutinho, 1987). Some behavioral theories investigated how motivational factors help develop travelers attitudes and how these attitudes lead to behavioral intentions in choosing a travel destination (Lam & Hsu, 2004, 2006; March & Woodside, 2005a). One of the often-researched consumer behavior formation models is the theory of planned behavior (TPB) (Ajzen, 1988, 1991). TPB considers both social (i.e., subjective norm) and psychological (i.e., attitudes) factors in the consumers behavioral formation process, and has been accepted and employed to predict individuals behaviors in hotel selection (Buttle & Bok, 1996), destination choice (Lam & Hsu, 2006), and social psychology studies (Conner, Kirk, Cade, & Barrett, 2001). These previous studies paid particular attention to the relationship between travelers attitudes and behavior intentions, which could only predict a person s attempt to perform a particular behavior but not the actual performance of the behavior (March & Woodside, 2005b). Little research could be found investigating how travelers motivation influences their attitudes and behavioral intentions and subsequently determines their actual behaviors in choosing an international travel destination. The current study attempted to investigate the travelers behavioral formation process in choosing a destination and to test an extended model of the TPB. Specifically, travel motivation and actual behavior were added to the TPB model, which enriches the connotation of TPB, thus the travel behavioral formation process can be more thoroughly examined. A two-wave data collection process was adopted to collect data from a sample of potential mainland Chinese travelers to Hong Kong, which enabled the empirical testing of the extended TPB model. As Chinese outbound tourism is playing an unprecedented important role in the global tourism industry (Cai, Li, & Knutson, 2007) and China s outbound market continues to grow in size and sophistication, Chinese travelers behavioral formation process in choosing a destination demands a deeper level of investigation. The study makes a contribution to the theoretical development of travel behavior formation by enhancing the sufficiency of a commomnly accepted consumer behavior model. Results of the study also provide practical implications for the tourism industry in terms of marketing, operations, and planning. 2. MODEL PROPOSITION Studies aiming to understand the tourist behavior formation process are seriously lacking in the literature. Although TPB model was adopted by some researchers in social psychology studies, few researchers have simultaneously examined the nature of the motivation-attitude-behavior relationship and the role of behavioral facilitators in tourism research or in consumer research in general. The current study attempted to test the applicability of the TPB with the addition of the motivation and actual behavior in the tourism context. The conceptual model of the current study is illustrated in Figure 1. Motivation contributes to the understanding of the formation and change of attitude (Katz, 1960). Theoretically, motivation is cognitive in nature in that it /10/$ IEEE

2 is an interaction of motives and situation. Comparatively, attitude is more predisposed to be affective. According to the TPB, an individual s attitude is determined by behavioral belief, implying that cognitive motivation may influence affective attitude (Ajzen, 1991). Building upon previous studies on motivation and attitude, Gnoth (1997) proposed a conceptual framework to delineate the relationship between motivation and attitude. According to Gnoth, an individual s attitude towards an object is determined by both the tourist s felt needs and value system. However, very few studies have investigated the relationship between travel motivation and attitude (e.g., Beard & Ragheb, 1983; Lam & Hsu, 2004, 2006); and the relationship between motivation and travel intention to a destination has not been well documented. Ajzen (1991) argued, however, intentions capture the motivational factors that influence a behavior and indicate how hard people are willing to try or how much effort they would exert to perform the behavior. This implies that motivation is related to behavioral intention. Adding a separate motivational component to the TPB will provide an alternative model that allows an in-depth understanding of travelers motivation and its influence on the travel behavior formation process. Therefore, the following two hypotheses were proposed: H1: Tourists motivation of visiting a destination has a direct effect on their attitude towards choosing the destination. H2: Tourists motivation of visiting a destination has a direct effect on their behavioral intention of visiting the destination. Motivation of Visiting a H1 Attitude towards Visiting a Subjective Norm towards Visiting a Perceived Behavioral Control towards Visiting a H3 H4 H6 H5 H2 Behavior Intention of Visiting the Actual Behavior of Visiting the Figure 1. Proposed model based on TPB H7 Most of the work on destination choice intention (e.g., Lam & Hsu, 2004, 2006) has been conducted based on the TPB model, which proclaims that behavioral intention is a consequence of attitude, subjective norm, and perceived behavioral control (Ajzen, 1991). For instance, Lam and Hsu (2004; 2006) conducted two empirical studies with 328 Mainland Chinese travelers (2004) and 390 Taiwanese tourists (2006) to predict travel behavior and intention of destination selection. In these studies, attitude and perceived behavioral control were found to be related to mainland Chinese s behavioral intention of visiting Hong Kong; while for Taiwanese, subjective norm and perceived behavioral control were found to be related to their behavioral intention of choosing a destination. Although an individual s subjective norm and perceived behavioral control affect the target future behavior, they do so only indirectly through behavioral intention (Ajzen, 1991; Fishbein & Ajzen, 1975). Therefore, the following three hypotheses were proposed: H3, H4, H5: Tourists attitude (H3), subjective norm (H4), and perceived behavioral control (H5) of visiting a destination has a direct effect on their behavioral intention of visiting the destination. Fishbein and Ajzen s (1975) original conceptualization asserts that the effect of attitude on future behavior is completely mediated by intention, and they did not establish the relationship between attitude and actual behavior (Conner & Armitage, 1998). Nevertheless, researchers still discovered that, in addition to an indirect influence through intention, attitude can influence future behavior directly (Bagozzi & Yi, 1989; Golob, 2003). Thus, the following hypothesis was formed. H6: Tourists attitude towards visiting a destination has a direct effect on their actual behavior of visiting the destination. The TPB seems to deal adequately with the relationship among attitude, subjective norm, perceived behavioral control and intention, but the question of how an intention is implemented in actual behavior has largely been ignored (Gärling, Gillholm, & Gärling, 1998). According to Fishbein and Ajzen (1975), the behavioral intention is considered as the immediate determinant and best predictor of behavior among all the antecedents of behavior. The TPB theorized that intention results in behavior when there is an opportunity to act (Ajzen, 1985). Thus, a construct of actual behavior was added in the proposed model and a hypothesis was proposed: H7: Tourists behavioral intention of visiting a destination has a direct effect on their actual behavior of visiting the destination. 3, METHODS 2.1 Instrument Development The instrument was developed based on focus group interviews and literature review. Five focus groups were conducted in Guangzhou and Beijing to identify

3 participants motivation to visit Hong Kong. Each group consisted of 6-9 participants and lasted for an average of 45 minutes. Twenty-seven motivational items were generated from focus group results. These 27 motivational items were then combined with measurements from previous research (eg., Crompton, 1979; Dann, 1981; Fodness, 1994; Hsu & Lam, 2003; Jang & Cai, 2002; Zhang & Lam, 1999) with a total of 38 items generated for pilot studies. Two pilot studies were conducted in mainland China with 204 and 186 respondents, respectively, to reduce and refine the motivation items with factor analyses and reliability tests. Items on attitude, subjective norm, and perceived behavior control were adapted from Lam and Hsu (2004). The survey instrument was designed in English and translated into Chinese using a blind translation-back-translation method (Brislin, 1976). The translated version was reviewed by several tourism researchers with competencies in both languages to ensure accuracy of translation. All motivation items shared an umbrella question stem: If you were to visit Hong Kong in the near future, you would visit it because you d like to The attitude construct was measured by six statements began with From all your knowledge about Hong Kong, you think the visit would be The six statements were enjoyable, pleasant, worthwhile, satisfying, fascinating, and rewarding. Three statements were asked to measure subjective norm: Most people who are important to you think you should visit Hong Kong in the near future ; The people in your life whose opinions you value would approve your visiting to Hong Kong in the near future ; Most people who are important to you would visit Hong Kong in the near future. Five statements were used to measure perceived behavioral control. A sample statement was: Whether or not to visit Hong Kong in the near future in completely up to you. Behavior intention and actual behavior were measured in two different surveys. Behavior intention of visiting Hong Kong in the first wave questionnaire included four statements mainly adapted from Lam and Hsu (2004), which were You intend to visit Hong Kong in the next 6 month, You plan to visit Hong Kong in the next 6 months, You want to visit Hong Kong in the next 6 months, and You probably will visit Hong Kong in the next 6 month. While the actual behavior in the second wave questionnaire was measured with one statement: How many times did you visit Hong Kong in the past 6 months? Except for actual behavior, all the above items employed the same seven-point Likert scale, ranging from strongly agree (7) to strongly disagree (1). 2.2 Two-wave Data Collection The sampling frame consisted of mainland Chinese individuals who have shown interest in travel. The data used in this study were collected in three major cities of Beijing, Shanghai, and Guangzhou, China. These three cities were selected for their residents trend-setting status in lifestyles and higher income and therefore higher propensities to travel (Hsu & Crotts, 2006). The three cities also have a broad geographic representation of China and include both long- and short-haul potential mainland Chinese travelers to Hong Kong. The first stage aimed to collect data on reasons of visiting Hong Kong (motivation), attitude towards visiting Hong Kong, groups or individuals whose views might influence respondents visit to Hong Kong (subjective norm), the degree of control over a future visit (perceived behavioral control), and likelihood of visiting Hong Kong in the next six months (behavioral intention), and demographic characteristics. In the second stage data collection, in addition to motivation, subjective norm, and perceived behavioral control, frequency of visit to Hong Kong in the past 6 months was added to collect information on actual behavior. For the first stage of data collection, respondents were chosen based on a convenience sampling method. A group of trained interviewers were stationed at airport terminals, train stations, shopping malls, and outside of travel agencies. Once respondents agreed to participate in the survey, the purpose of the study was explained and a self-administered questionnaire was distributed to them for completion on site. As a result 1,514 completed surveys were retained as the sample of the study. Respondents were asked to provide name, phone number, mailing address, and address for a follow-up survey in 6 months. The second wave of data collection was conducted 6 months after the initial survey. Respondents of the first data collection were contacted by postal and/or to be invited to complete the follow up questionnaire. A total of 995 questionnaires were successfully sent (i.e., were not returned) by postal mail, and 528 by . Follow up phone calls were made to remind participants of the questionnaire sent. Unique coding was used to make sure that each respondent can only return the second questionnaire once. No participant was found to return both the postal and survey. A total of 311 questionnaires were returned, for an overall response rate of 21.4%. 2.3 Data Analysis Data were analyzed using SPSS and LISREL. The first wave sample was randomly split into two halves, one as calibration sample (n=784) and the other as validation sample (n=730). Exploratory factor analyses (EFA) were run with the calibration sample on each of the research constructs in the proposed model except actual behavior. Subsequently, confirmatory factor analyses (CFA) were run with the validation sample to see whether the underlying factorial structures

4 (measurement models) still hold, with adjustments being made where necessary. Once the measurement models were identified, the overall measurement model was tested, following by the test of the proposed structure model, both using the validation sample. In order to test the extended TBP model including actual behavior, the two-wave data were merged together. The new dataset contains wave one data for motivation, attitude, subjective norm and perceived behavioral control, and wave two data for actual behavior with an effective sample size of RESULTS 3.1 Measurement of Motivation EFA was conducted to extract underlying dimensions of motivation with the calibration sample (n=784). A principal component method with varimax rotation was used. The factor analysis reached a solution of four factors without deleting any items. The four factors were labeled as knowledge, relaxation, novelty, and shopping. A Cronbach s alpha reliability test was run and all factors showed acceptable levels of reliability (>0.7). The motivation factorial structure was tested using CFA with the validation sample (n=730). The measurement model with all items did not seem to have a satisfactory fit with the data. Five measurement items were then removed from the model, as suggested by the modification indices and their lack of utility to serve as a highly reliable measurement indicator either due to low loading or double loading. 3.2 Measurements of Other Latent Variables The same procedure was applied to test the measurement models of attitude, subjective norm (SN), perceived behavioral control (PBC), and behavioral intention (BI). EFA was run with the calibration sample first to identify the underlying latent structure and then the structure was due to CFA and further adjustment to find a suitable measurement model for each latent variable. Two attitude items, with the semantic words of fascinating and rewarding were removed from the attitude measurement due to redundancy. Two PBC variables, with the reversed wording were found to lay on a different underlying dimension from the other three items in the EFA. The result was probably due to the reversed wording. With an acceptable reliability of the three statements loaded on the primary factor, the two reversed items were removed. Similarly, one behavioral intention item was removed in the CFA process. 3.3 Overall Measurement and Structural Models without Actual Behavior An overall measurement model was tested with all latent variables (4 motivation factors, attitude, PBC, SN, BI) except actual behavior using the validation sample (n=730). The overall measurement model was found to fit the data very well ( 2 /df = 2.81, RMSEA =.050, Standardized RMR =.048, GFI =.92, NFI =.94, CFI =.96). The proposed structural model without actual behavior was then tested. The model was also found to fit the data well ( 2 /df = 2.83, RMSEA =.050, Standardized RMR =.049, GFI =.92, NFI =.94, CFI =.96). As shown in Figure 2, all the motivation factors had a significant positive effect on attitude. The result thus supported H1. However, only shopping as a motivation factor posted a significant influence on behavioral intention; all other three motivation factors did not affect behavioral intention. Thus, H2 can only be partially supported. As expected, subjective norm had a very salient effect ( =.315) on behavioral intention; so did perceived behavioral control ( =.171), albeit in a lesser magnitude. On the other hand, attitude was found to have an effect on behavioral intention; however, judging from the path coefficient ( =.095), the effect appeared only marginal. These findings generally supported H3, H4, and H5. The proposed model explained 33% of the variable for attitude and 42% of that of behavioral intention, which indicated the explanatory power of the model was quite satisfactory. *p<05, **p<.01 Relaxation Subjective Norm Novelty Knowledge.29**.117* Shopping Attitude.235**.19**.247**.095* Perceived Behavior Control.315** Figure 2. Structural model without actual behavior 3.4 Testing the Structural Model with Actual Behavior Visit Intention.171** The two wave data were combined to enable testing the structural model with actual behavior (Figure 1). LSIREL outputs displayed a warning message that the covariance matrix to be analyzed was not positive definite; and the model was found not converged with the data. Although by regressing the actual behavior on behavioral intention and attitude demonstrated -

5 correlations between them (as proposed in H6 and H7), the researchers did not pursue the simple regressions because the current study intended to test the simultaneously holding causal relationship among all the research constructs involved in the model. Because the data did not support the extended model with the inclusion of the actual behavior, this study did not provide evidence to support H6 and H7. 4, DISCUSSION AND CONCLUSION Results of this study demonstrated the utility of TPB as a conceptual framework in analyzing the behavior of visiting a destination among potential visitors. Subjective norm, perceived behavioral control, and attitude all had direct and positive impact on behavioral intention. Important referents suggestions or evaluations of visiting a destination have a greater influence in choosing the destination than perceived behavior control does. Attitude does play a role in behavioral intention, but the effect can only be regarded as marginal. Results of this study mostly parallel that of Lam and Hsu (2006) who found that among Taiwanese respondents, subject norm (b =.37, p < 0.01) had the strongest influence on behavior intention, followed by perceived behavior control (b =.19 p < 0.05). This study also contributed to the extension of TPB. The theory of planned behavior seems to deal adequately with the relationship between attitude and intention; however, the question of how an intention is actualized as a behavior has largely been ignored (Eagly & Chaiken, 1993; Gärling et al., 1998). While behavior intention was to predict actual behavior, it is the actual behavior, not the likelihood of the behavior to be carried out, that makes a difference for practitioners. Thus, the establishment of relationships among motivation, attitude, subjective norm, perceived behavioral control, and behavior intention as well as actual behavior would make a significant contribution to both theory and practice. Thus, a two-wave data collection procedure was adopted to obtain the actual behavior data. Results showed that the extended TPB model with the addition of tourist motivation held with the study sample; however, no evidence could be generated to support the extended TPB model with both tourist motivation and actual behavior included. In addition, although motivation plays an important role in the formation and changing of attitude (Katz, 1960), very few studies have well examined the relationship between travel motivation and attitude or travel intention (e.g., Beard & Ragheb, 1983; Lam & Hsu, 2004, 2006). Adding a separate motivational component, with four motivation factors derived in this study context, to the TPB provided an alternative model that allows an in-depth understanding of travelers motivation of visiting a destination and its influence on the travel behavior formation process. For mainland Chinese travelers, the motivation of shopping as a significant predictor of their intention of visiting Hong Kong has been demonstrated. Another academic contribution of this study lies in its special study context. Unlike most of the prominent travel behavior models developed in Western societies or developed countries, this article reported the applicability of the TPB in a developing country and non-western society. China has achieved the most impressive development and become a new yet prosperous tourism outbound market in the past two decades. Due to the very different social, cultural, political, and economic background, the characteristics of Chinese outbound travelers are distinctive from those of western society. However, the exploration of Chinese outbound market seemed insufficient in the tourism literature (Cai et al., 2007). Based on findings of the study, some salient implications can be derived. As overseas travel becomes more common for the main stream consumer market, social influence from referent members of mainland Chinese residents becomes an important factor in making travel decisions. Thus, marketing and public relations campaigns should not only be directed towards potential travelers, but also the general public in forming a positive destination image among all members of the society so that positive influence can be exerted upon potential travelers through subjective norm. Image campaigns, rather than result specific promotions, could serve this purpose. Communication messages should also encourage positive word-of-mouth, whether based on actual visit experience in the past or general image formed through media exposure. Acknowledged as the shopping paradise by mainland Chinese residents, regardless of whether or not they had visited this city (Huang & Hsu, 2005), Hong Kong has an overall image of duty-free, world famous luxury goods, and abundant brand-name clothing and electronic products. Shopping is not only a motivation factor but also a signature attraction of Hong Kong. For the sake of Hong Kong tourism industry s sustainable development, Hong Kong s tourism and retail trades need to work together to enhance tourists shopping experience by offering the most attractive product mix, enjoyable shopping environment, and top notch service quality. Perceived behavior control was also found to be an important predictor of behavior intention. Marketing communication with potential visitors should stress the fact that visiting Hong Kong is easy, hassle free, and within their own control. The practical contribution to Hong Kong was at the same time the limitation of this present study. Similar research efforts are warranted to verify the validity of the model for other destinations. Future studies should further explore the relationship between behavior

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