Rong Quan Low Universiti Sains Malaysia, Pulau Pinang, Malaysia

International Journal of Accounting & Business Management Vol. 1 (No.1), April, 2013 Page: 99-106 ISSN: 2289-4519 This work is licensed under a Creative Commons Attribution 4.0 International License. www.ftms.edu.my/journals/index.php/journals/ijabm Investigating Determinants of Tourist Intention and Associationsof PerceivedUsefulness, Ease of Use and Mobility in the Context of Mobile Tourism Guide Abstract Numtip Trakulmaykee Universiti Sains Malaysia, Pulau Pinang, Malaysia maykee_n@yahoo.com Ahman SuhaimiBaharudin Universiti Sains Malaysia, Pulau Pinang, Malaysia suhaimi@cs.usm.my This study investigates the determinants of tourist intention and associations of perceived usefulness, perceived ease-ofuse, and perceived mobility in the context of mobile tourism guide. As a result of a few previous research studies the association of these constructs, especially in the context of mobile tourism guide. The research model is developed based on technology acceptance model 2 and extended model with perceived mobility constructs. The study employs convenience sampling technique to collect data from international tourists at Suvarnabhumi Airport in Thailand. The study employed WarpPLS 3.0 to analyze the proposed model in terms of validity, reliability, and path coefficients. The results evidence perceived usefulness, mobility are the determinants of tourists intention to use mobile tourism guide in all traveller types. Even thought, 99 Rong Quan Low Universiti Sains Malaysia, Pulau Pinang, Malaysia lowrongquan@gmail.com Muhammad Rafie Mohd. Arshad Universiti Sains Malaysia, Pulau Pinang, Malaysia rafie@cs.usm.my perceived ease-of-use is not the determinant of intention for both selfmanaged tour and package tour. In addition, the study supports the technology acceptance model 2 in terms of association of perceived ease-of-use and perceived usefulness. Furthermore, the findings also reveal the association of perceived mobility and perceived ease-of-use, and evidence the association of perceived mobility and perceived usefulness in intention model. The findings of study extend the body of knowledge in the context of mobile application and contribute the tourism industries to understand the tourists perception on mobile application. Keywords: Intention, mobile tourism guide, mobility, technology acceptance model, tourist. I. Introduction With the popularity of ubiquitous mobile applications that enable users to access

information on the move, many researchers have been interested in determinants of users intention to use mobile application. In particular, the determinants of tourists intention to use mobile tourism guide (MTG) has been studied in tourism domain. Tourists usually need much more tour information for their travel, especially for tour planning before travel and getting information during their trip. Nowadays, there have been also studies that examined the determinant of users intention of mobile information services, in terms of perceived usefulness, mobility(xue et al., 2012, Wu et al., 2011, Schierz et al., 2010, Kaba and Osei- Bryson, 2009).However, few studies have in depth investigated the association of perceived usefulness, mobility in the context of mobile information services. In addition, there is a lack of research which studies the associations of these three variables on international tourists intention to use MTG; and compare the associations in three different tour-managed types: selfmanaged tour, package tour, and others. Therefore, this study aims to investigate the determinants of intention and associations of perceived usefulness, mobility among international tourists in the context of MTG. Furthermore, the study compares these associations in three types of tour-managed: selfmanaged tour, package tour, and others. In this study, the MTG refers to a mobile application for international tourist to get the tour information of Thailand. For instance, attractive places, maps, do & don t in Thailand, climate & seasons, culture, transportation, accommodation, Thai food & Thai fruit, easy Thai dialogues for international tourist, and currency exchange rate. Findings from the study can evidence the association of three perceptions in the context of MTG, and can refer to the other contexts in mobile information services domain. II. Research Model And Hypotheses In order to study the association of perceived usefulness, perceived ease-ofuse, and perceived mobility in intention model, the research model is conducted as presented in Figure 1. Due to perceived usefulness and perceived ease-of-use are the determinants of users intention to use technology in the technology acceptance model 2 (TAM2) of Venkatesh and Davis (2000). Furthermore, mobility is a foundation feature of mobile phone and mobile application, hence perceived mobility is possibly a determinant of tourists intention to use MTG. Consequently, the research model consists of intention to use MTG as dependent variable and three possible determinants of tourists intention to use MTG: perceived usefulness, perceived ease-of-use, and perceived mobility. In the following sections, the study defined the definition of variables, discussed relationship between variables, and proposed relevant hypotheses. 100

Figure 1. Research model Based on TAM2 (Venkatesh and Davis, 2000), perceived usefulness and perceived ease-of-use directly influenced on users intention. Perceived usefulness refers to the prospective users subjective assessment of the probability that using a specific application system will increase his or her exist context(venkatesh and Davis, 2000).Perceived ease-of-use refers to the degree to which the prospective user expects the target system to be free of effort in use (Venkatesh and Davis, 2000). Moreover, according to the TAM2 structure, perceived ease-of-use has a direct impact on perceived usefulness. In addition, most previous mobile studies also found the positive influence of perceived usefulness on users intention(xue et al., 2012, Kim et al., 2010, Wu et al., 2011, Chen et al., 2009).Likewise, most prior mobile studies found the positive relationship between perceived ease-of-use and perceived usefulness(kim et al., 2010, Wu et al., 2011, Xue et al., 2012).Even though, Hernandez and Mazzon (2007) found ease-of-use did not influence on intention to use internet banking in Brazil, the findings of most previous mobile researches reported that 101 perceived ease-of-use positively impacted on users intention. Thus, three hypotheses are proposed as the following: H1: Perceived usefulness has a positive impact on intention to use MTG. H2: Perceived ease-of-use has a positive impact on intention to use MTG. H3: Perceived ease-of-use has a positive impact on perceived usefulness. Perceived mobility refers to the degree of prospective benefits which are provided by mobile technologies. Benefits are about the information access, communication, and services anytime and anywhere (Kim et al., 2010).Most studies found mobility was a key of user to adopt mobile service and influenced on users intention (Schierz et al., 2010, Kaba and Osei-Bryson, 2009). For example, (Schierz et al., 2010) reported that individual mobility positively influenced on intention to use mobile payment services, and Kaba and Osei-Bryson (2009) found mobility was a external factor which influenced on mobile phones use in Quebec. Therefore, perceived mobility of using MTG maybe positively influence on tourists intention to use MTG, the following hypothesis is: H4: Perceived mobility has a positive impact on intention to use MTG. In addition, several previous mobile researches also investigated the relationship between perceived mobility and perceived usefulness and found various results. For instance, Kim et al. (2010)presented mobility had a positive effect on the perceived usefulness of

mobile payment, whileschierz et al. (2010) found there is not a positive relationship between individual mobility and perceived usefulness in the context of mobile payment services. Even though Kim et al. (2010) found mobility did not influence on perceived usefulness of mobile payment, we believed that perceived mobility positively associated to perceived usefulness and perceived ease-of-use in the context of MTG. Thus, in order to evidence this relationship, the study proposes hypothesis as the following: H5: Perceived mobility has a positive impact on perceived usefulness. H6: Perceived mobility has a positive impact on perceived ease-of-use. III. Methodology The study employed self-administered questionnaire for data collection. All measures were adapted from good reliable items, which Cronbach s alpha value exceed value of 0.70 (Nunnally, 1978). The items for measuring perceived usefulness, perceived ease-ofuse, and perceived mobility were adapted from Kim et al. (2010).All items were anchored on a 7-point Likert scale which ranged from 1=strongly disagree to 7=strongly agree. Before data collection, the study conducted pilot test in order to ensure the effective questionnaires. In pilot test, the questionnaires were distributed to 30 convenient international tourists at Suvarnabhumi Airport in Thailand. Following the pilot test, the completed questionnaires were distributed to respondents with convenience sampling technique. Respondents were the international tourists and departed from the Suvarnabhumi Airports of Thailand in May, 2012. In this study, survey respondents participated voluntarily. Before filling out the questionnaire, participants were given the demonstration of MTG usage and MTG features; and then they had a chance to try out the MTG. According to Sekaran and Bougie (2010), the minimum sample size of 384 respondents is considered sufficient to test the hypothesis when the population above one million individual users. The population of study is more than 1 million and the total number of completed questionnaires is 593.Therefore, the data of this study is proper for analysis and testing in terms of reliability, validity, and research model. Table 1 presents the demographic data of respondents. Profile Frequency Percentage Gender Male Female 320 273 54.0 46.0 Age Below than 21 years 21-25 years 26-30 years 31-40 years 41-50 years Above than 50 years 26 127 142 140 66 92 4.4 21.4 23.9 23.6 11.2 15.5 Marital Status Annual Income (USD) Continent Table 1.The demographic data of respondents (N=593) IV. Single Married Divorced/Widowed Relationship Below than $20,001 $20,001-$30,000 $30,001-$40,000 $40,001-$50,000 Above than $50,000 Asia Europe America Oceania Africa Middle East 224 276 26 67 147 92 66 62 189 254 167 48 94 12 18 Data Analysis And Results 37.8 46.6 4.3 11.3 26.9 16.8 12.1 11.3 32.9 42.8 28.2 8.1 15.9 2.0 3.0 The reliability and validity of measurements instrument were evaluated with WarpPLS 3.0,which is the 102

powerful structural equation modeling (SEM) software. The results of measurement analysis consist of two parts: 1) assessment of convergent validity and reliability, and 2) examination of discriminant validity. Convergent validity and reliability were evaluated by factor loading, composite reliability (CR), average variance extracted (AVE), and Cronbach s alpha as shown in the Table 2.All factor loadings are significant and above 0.7, indicating excellent convergent validity (Fornell and Larcker, 1981). Furthermore, all CR values exceeds the 0.7 cut-off value and all AVE values are above the recommended value of 0.5 (Hair et al., 2010).Moreover, all Cronbach s alpha values were greater than 0.7(Cronbach, 1951). Hence, the convergent validity and reliability of this study were adequate. Construct Items Loading CR a AVE b Perceived usefulness Perceived ease-of-use Perceived mobility Intention to use MTG Cronbach's Alpha PU1 0.884 0.915 0.782 0.860 PU2 0.922 PU3 0.845 PEOU1 0.903 0.925 0.805 0.879 PEOU2 0.920 PEOU3 0.867 PM1 0.901 0.926 0.806 0.880 PM2 0.916 PM3 0.876 INT1 0.880 0.921 0.796 0.872 INT2 0.903 INT3 0.893 Note: a Composite Reliability (CR) = (square of the summation of the factor loading) / ((square of the summation of the factor loadings) + (square of the summation of the error variances)) b Average Variance Extracted (AVE) = (summation of the square of the factor loadings) / ((summation of the square of the factor loadings) + (summation of the error variances)) Table 2. Measurement analysis: convergent validity and reliability To test the discriminant validity, the diagonal elements were computed by the square root of AVE. According to Fornell and Larcker (1981) and Agarwal and Karahanna (2000), the diagonal elements of constructs should exceed its correlations with other constructs. As shown in Table 3, all diagonal elements were larger than their corresponding correlation coefficients, thus the findings indicated the acceptable discriminant validity. In addition, all variance inflation factors (VIFs) are less than the threshold value of 10.0 (Hair et al., 2010), indicating no multicollinearity problem in this study. 1. Perceived usefulness 2. Perceived ease-of-use 3. Perceived mobility 4. Intention to use MTG Mean Std. Dev. 6.35 0.706 1.89 0.884 VIFs 1 2 3 4 6.56 0.604 1.66 0.568** 0.897 6.32 0.723 2.00 0.612** 0.531** 0.898 6.46 0.641 1.70 0.513** 0.489** 0.594** 0.892 Note: ** Correlation significant at p < 0.01 Table 3.Measurement analysis: discriminant validity To test structural relationships, the study also employed WarpPLS 3.0 to analyze path coefficients. For all types of managed-tour, the overall fit of the model is acceptable, due to the goodness-of-fit statistics are adequate and acceptable as presented in Figure 2. The results show all relationships are significant at significant level 0.001, thus all proposed hypotheses are supported. The results of study evidence that perceived usefulness (β=0.246, p<0.001), perceived ease-of-use (β=0.167, p<0.001), and perceived mobility (β=0.362, p<0.001) are the determinants of tourists intention to use MTG. These 103

three constructs, perceived usefulness, mobility, jointly explain 43.5% of the variance in intention to use MTG (R 2 =0.435). Furthermore, perceived mobility is the most important determinant of tourist intention in the context of MTG. In addition, there are the associations of perceived usefulness, mobility. Perceived ease-of-use (β=0.344, p<0.001) and perceived mobility (β=0.426, p<0.001) plays the critical role in determining perceived usefulness. Both perceived ease-of-use and perceived mobility, jointly explain 45.9% of the variance in perceived usefulness (R 2 =0.459). While perceived mobility singly explains 28.5% of the variance in perceived ease-of-use (R 2 =0.285). The construct of perceived mobility indicates as an important antecedent of perceived ease-of-use (β=0.534, p<0.001). Figure 2.Path results of all type of managed-tour (n=593) In order to clearly understand the association of three constructs and determinants of intention in the context of MTG, the study examined the research model for each type of managed-tour. In this study, international travelers were classified by managed-tour method to 104 three types: self-managed tour, package tour, and others. Self-managed tour refers to the tourist who manages his/her travel with himself/herself such as travel planning, reserving hotel, booking flight. Package tour refers to the tourist who travelsby arrangement of tour agencies; such as vehicle, tour guide, admission fee, meal, hotel, and activities. Others refers to the traveler who visited Thailand with other purposes (not for visiting attractive places in Thailand); such as seeing doctor, transit flight, visiting family, convention, business meeting, and conference. Table 4 presents the comparison results of three types of managed-tour: selfmanaged tour, package tour, and others. All variance inflation factors (VIFs) of each β in intention model of each tourist type are less than 5 (Hair et al., 2010). The largest value is 1.94, indicating that this intention model avoids the problem of multicollinearity. The findings of this study reveal many interested issue in terms of associations of constructs and determinants of intention. First, there are the similar associations of perceived usefulness, perceived ease-of-use, and perceived mobility in all types of managed-tour. These relationships are: perceived usefulness and perceived ease-of-use, perceived mobility and perceived usefulness, and perceived mobility and perceived ease-of-use. Apparently, types of managed-tour do not play a role on these associations; indicating the associations of perceived usefulness, perceived ease-of-use, and perceived mobility are significant in the context of MTG. Second, perceive mobility and perceived ease-of-use play the role on perceived usefulness in all types of managed-tour. Perceived ease-

of-use and perceived mobility, jointly explain 57.2%, 38.1%, and 46.9% of the variance in perceived usefulness in selfmanage tour, package tour, and others, respectively. It implies that increasing mobility and ease-of-use will significantly increase perceived usefulness of tourists in the context of MTG. Third, perceived usefulness and perceived mobility are the determinants of three types of traveler, while perceived ease-of-use is not a determinant of intention to use MTG in both type of self-managed tour and package tour. Finally, perceived mobility is the most important determinant of intention to use MTG in both package tour and others, while self-managed tour focus on usefulness than mobility and ease-of-use. Relationship Self-managed tour (n=219) Package Tour (n=198) Others (n=176) β S.E. β S.E. β S.E. PU INT 0362** 0.122 0.185* 0.098 0.186* 0.079 PEOU INT 0.147 0.097 0.079 0.066 0.359*** 0.083 MOB INT 0.295*** 0.075 0.406*** 0.075 0.371*** 0.074 PEOU PU 0.518*** 0.069 0.254*** 0.070 0.319*** 0.085 MOB PU 0.321*** 0.063 0.464*** 0.066 0.453*** 0.074 MOB PEOU 0.656*** 0.052 0.420*** 0.074 0.549*** 0.067 R 2 of INT 0.491 0.318 0.611 R 2 of PU 0.572 0.381 0.469 R 2 of PEOU 0.430 0.176 0.301 Q 2 of INT 0.490 0.325 0.611 Notes: *p<0.05, **p<0.01, ***p<0.001 PU-Perceived usefulness, PEOU-Perceived ease-of-use, MOB-Mobility, INT- Intention to use MTG Table 4. Comparison of self-managed tour, package tour, and others V. Discussions and Conclusions The results of this study contain several implications for researchers as well as for mobile application in tourism industry. The empirical findings demonstrate that employing perceived mobility would be a worthwhile extension of the TAM2 in the mobile application context, as was found to be influential in predicting intention to use MTG. The finding increasingly clear that users do not use mobile application based only on criteria of usefulness and ease-of-use; mobility also has a key role on user intention, especially in the context of MTG. In addition, the findings reveal the association of perceived usefulness, perceived ease-of use, and perceived mobility. First, the study confirmstam2(venkatesh and Davis, 2000) and most previous mobile studies (Kim et al., 2010, Wu et al., 2011, Xue et al., 2012) in terms of the relationship between perceived usefulness and perceived ease-of-use. Second, the findings of this study found the association of perceived mobility and perceived ease-of-use, although Kim et al. (2010) found mobility did not influence on perceived usefulness of mobile payment. Due to most tourists usually learn MTG on their move, thus they possibly perceived that increasing mobility can help them perceive ease-ofuse in the context of MTG. In contrast, users possibly learn how to use m- payment before their need to use m- payment on their move, because they concern the risk of their money. Finally, the finding addresses the arguments of previous studies findings (Kim et al., 2010, Schierz et al., 2010), due to this study found the association of perceived mobility and perceived usefulness. Even though the study conducts intention model within the specific domain of the MTG. the future studies can employ this intention model in the other mobile contexts. In order to make more confidence, the future studies should reexamined the model in terms of reliability, validity, correlation, and path analysis. 105

References AGARWAL, R. & KARAHANNA, E. 2000. Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. Management Information Systems Quarterly, 24, 5. CHEN, J., YEN, D. & CHEN, K. 2009. The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Information and Management, 46, 241-248. CRONBACH, L. J. 1951. Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334. FORNELL, C. & LARCKER, D. F. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39-50. HAIR, J. F., BLACK, W. C., BABIN, B. J. & ANDERSON, R. E. 2010. Multivariate data analysis Upper Saddle River, New jersey, Pearson Prentice Hall. HERNANDEZ, J. & MAZZON, J. 2007. Adoption of internet banking: proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25, 72-88. KABA, B. & OSEI-BRYSON, K. M. External factors influencing mobile phones use in Quebec: An exploratory study. Proceedings of the 15th Americas Conference on Information Systems, AMCIS 2009, August 6-9, 2009 2009 San Francisco, California, USA. Americas Conference on Information Systems, 1-14. KIM, C., MIRUSMONOV, M. & LEE, I. 2010. An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26, 310-322. NUNNALLY, J. C. 1978. Psychometric theory, New York, McGraw-Hill. SCHIERZ, P., SCHILKE, O. & WIRTZ, B. 2010. Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9, 209-216. SEKARAN, U. & BOUGIE, R. 2010. Research methods for business: A skill building approach, United Kingdom, John Wiley & Sons Ltd. VENKATESH, V. & DAVIS, F. D. 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186-204. WU, I. L., LI, J. Y. & FU, C. Y. 2011. The adoption of mobile healthcare by hospital's professionals: An integrative perspective. Decision Support Systems. XUE, L., YEN, C. C., CHANG, L., CHAN, H. C., TAI, B. C., TAN, S. B., DUH, H. B. L. & CHOOLANI, M. 2012. An exploratory study of ageing women's perception on access to health informatics via a mobile phone-based intervention. International Journal of Medical Informatics, 81, 637-648. 106