Is smart tourism technology important in predicting visiting tourism destination? Lessons from West Java, Indonesia
DOI:
https://doi.org/10.35313/jtos.v1i2.20Keywords:
smart tourism technology, perceived ease of use, perceived usefulness, travel intention, visiting tourism destinationAbstract
This study analyzes tourist behavior in visiting tourism destinations influenced by smart tourism technology and uses the technology acceptance model (TAM) as a model for acceptance of smart tourism technology. This study used a sample of 324 tourists in West Java Province, Indonesia. Partial least square is applied to assess the relationship between smart tourism technology, perceived usefulness, perceived ease-of-use, travel intention, and visiting tourism destinations. The results of this study have revealed that the integration of TAM and smart tourism technology provides a complete explanation of the adoption of smart tourism technology. The results showed that smart tourism technology had a significant effect on perceived ease of use and perceived usefulness, and then had an effect on attitude. Travel intention was found to be directly influenced by attitude. Then, visiting tourism destinations is influenced by travel intention. By identifying smart tourism technology, various stakeholders such as the Government, tourism service providers and tourists can optimize a more comprehensive travel experience through the use of smart tourism technology. This research has developed TAM and integrated it with smart tourism technology to assess the attitudes and behavior of tourists in visiting tourism destinations.
References
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Buhalis, D. (1997). Information technology as a strategic tool for economic, social, cultural and environmental benefits enhancement of tourism at destination regions. Progress in Tourism and Hospitality Research, 3(1), 71–93.
Buhalis, D., & Amaranggana, A. (2015). Smart tourism destinations enhancing tourism experience through personalisation of services. Information and Communication Technologies in Tourism, 377–389. https://doi.org/10.1007/978-3-319-14343-9
Chen, H., Rong, W., Ma, X., Qu, Y., & Xiong, Z. (2017). An extended technology acceptance model for mobile social gaming service popularity analysis. Mobile Information Systems, 1–12. https://doi.org/https://doi.org/10.1155/2017/3906953
Chin, W. W. (1998). The partial least squares approach to structural modeling. In Modern Method for Business Research (pp. 295–336). Lawrence Erlbaum Associates, Inc.
Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
Chuttur, M. (2009). Overview of the technology acceptance model: origins, developments and future directions. Sprouts: Working Papers on Information Systems, 9(37), 1–23. https://doi.org/10.1021/jf001443p
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/https://doi.org/10.2307/249008
Filimonau, V., & Perez, L. (2019). National culture and tourist destination choice in the UK and Venezuela: an exploratory and preliminary study. Tourism Geographies, 21(2), 235– 260. https://doi.org/10.1080/14616688.2018.1490342
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to the- oryand research. Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/https://doi.org/10.1177/002224378101800104
French, A. M., Luo, X. (Robert), & Bose, R. (2017). Toward a holistic understanding of continued use of social networking tourism: A mixed-methods approach. Information and Management, 54(6), 802–813. https://doi.org/10.1016/j.im.2016.10.006
Ghaderi, Z., Hatamifar, P., & Henderson, J. C. (2018). Destination selection by smart tourists: the case of Isfahan, Iran. Asia Pacific Journal of Tourism Research, 23(4), 385–394. https://doi.org/10.1080/10941665.2018.1444650
Gretzel, U., Werthner, H., Koo, C., & Lamsfus, C. (2015). Conceptual foundations for understanding smart tourism ecosystems. Computers in Human Behavior, 50, 558–563.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage publications.
Halpenny, E., Kono, S., & Moghimehfar, F. (2018). Predicting world heritage site visitation intentions of North American park visitors. Journal of Hospitality and Tourism Technology, 9(3), 417–437. https://doi.org/10.1108/JHTT-10-2017-0109
Hua, L. Y., Ramayah, T., Ping, T. A., & Jun-Hwa, C. (2017). Social media as a tool to help select tourism destinations: The case of Malaysia. Information Systems Management, 34(3), 265–279. https://doi.org/https://doi.org/10.1080/10580530.2017.1330004
Huang, Y., Hsu, M. K., Basu, C., & Huang, F. (2009). Toward developing a social network site-based model for knowledge sharing in the travel industry. Issues in Innovation, 3(1).
Im, J., & Hancer, M. (2016). What fosters favorable attitudes toward using travel mobile applications? Journal of Hospitality Marketing and Management, 26(4), 361–377. https://doi.org/10.1080/19368623.2017.1248805
Jamshidi, D., & Hussin, N. (2016). Forecasting patronage factors of Islamic credit card as a new e-commerce banking service. Journal of Islamic Marketing, 7(4), 378–404. https://doi.org/https://doi.org/10.1108/JIMA-07-2014-0050
Jeong, M., & Shin, H. H. (2019). Tourists’ experiences with smart tourism technology at smart destinations and their behavior intentions. Journal of Travel Research, 59(8), 1464–1477. https://doi.org/10.1177/0047287519883034
Kah, J. A., Lee, C.-K., & Lee, S.-H. (2016). Spatial–temporal distances in travel intention– behavior. Annals of Tourism Research, 57, 160–175. https://doi.org/https://doi.org/10.1016/j.annals.2015.12.017
Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, D. Y., Park, J., & Morrison, A. M. (2008). A model of traveller acceptance of mobile technology. International Journal of Tourism Research, 10(5), 393–407. https://doi.org/10.1002/jtr.669
Kim, J. Y., Chung, N., & Ahn, K. M. (2019). The impact of mobile tour information services on destination travel intention. Information Development, 35(1), 107–120. https://doi.org/https://doi.org/10.1177/0266666917730437
Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/IJCHM-09-2012-0165
Koo, C., Shin, S., Gretzel, U., Hunter, W. C., & Chung, N. (2016). Conceptualization of smart tourism destination competitiveness. Asia Pacific Journal of Information Systems, 26(4), 367–384. https://doi.org/10.14329/apjis.2016.26.4.561
Lee, H., Lee, J., Chung, N., & Koo, C. (2018). Tourists’ happiness: are there smart tourism technology effects? Asia Pacific Journal of Tourism Research, 23(5), 486–501. https://doi.org/10.1080/10941665.2018.1468344
Lee, H. W., Ramayah, T., & Zakaria, N. (2012). External factors in hospital information system (HIS) adoption model: a case on malaysia. Journal of Medical Systems, 36, 2129–2140. https://doi.org/https://doi.org/10.1007/s10916-011-9675-4
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/https://doi.org/10.1016/S0378-7206(01)00143-4
Lin, W. B., Wang, M. K., & Hwang, K. P. (2010). The combined model of influencing on-line consumer behavior. Expert Systems with Applications, 37(4), 3236–3247. https://doi.org/10.1016/j.eswa.2009.09.056
Liu, D., Du, H., Southworth, F., & Ma, S. (2017). The influence of social-psychological factors on the intention to choose low-carbon travel modes in Tianjin, China. Transportation Research Part A: Policy and Practice, 105(November), 42–53. https://doi.org/10.1016/j.tra.2017.08.004
Nunkoo, R., Ramkissoon, H., & Juwaheer, T. D. (2016). Travelers’ intent to purchase tourism products and services online. Travel and Tourism Research Association: Advancing Tourism Research Globally, 66.
Park, S. H., Hsieh, C. M., & Lee, C. K. (2017). Examining Chinese college students’ intention to travel to Japan using the extended theory of planned behavior: Testing destination image and the mediating role of travel constraints. Journal of Travel and Tourism Marketing, 34(1), 113–131. https://doi.org/10.1080/10548408.2016.1141154
Paul, H. S., Roy, D., & Mia, R. (2019). Influence of social media on tourists’ destination selection decision influence of social media on tourists’ destination selection decision. Scholars Bulletin, 5(11), 658–664. https://doi.org/10.36348/SB.2019.v05i11.009
Priya, R., Gandhi, A. V., & Shaikh, A. (2018). Mobile banking adoption in an emerging economy: An empirical analysis of young Indian consumers. Benchmarking: An International Journal, 25(2), 743–762. https://doi.org/https://doi.org/10.1108/BIJ-01-2016-0009
Sahli, A. B., & Legohérel, P. (2015). The tourism Web acceptance model: A study of intention to book tourism products online. Journal of Vacation Marketing, 22(2), 179–194. https://doi.org/10.1177/1356766715607589
Sevrani, K., & Elmazi, L. (2008). ICT and the changing landscape of tourism distribution- a new dimension of tourism in the global conditions. Revista de Turism, 6, 22–29.
Shafiee, S., Rajabzadeh Ghatari, A., Hasanzadeh, A., & Jahanyan, S. (2019). Developing a model for sustainable smart tourism destinations: A systematic review. Tourism Management Perspectives, 31, 287–300. https://doi.org/10.1016/j.tmp.2019.06.002
Sheeran, P. (2002). Intention—behavior relations: a conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/https://doi.org/10.1080/14792772143000003
Sigala, M. (2018). New technologies in tourism: From multi-disciplinary to anti-disciplinary advances and trajectories. Tourism Management Perspectives, 25, 151–155. https://doi.org/https://doi.org/10.1016/j.tmp.2017.12.003
Suhartanto, D. (2017). The role of store coopetition and attractiveness on the performance of tourism destination and its retail stores. International Journal of Tourism Policy, 7(2), 151–165. https://doi.org/10.1504/IJTP.2017.085327
Suhartanto, D., & Leo, G. (2018). Small business entrepreneur resistance of ICT adoption: a lesson from Indonesia. International Journal of Business and Globalisation, 21(1), 5. https://doi.org/10.1504/ijbg.2018.10015253
Susanto, E., Novianti, S., Rafdinal, W., Fitriani, M., & Prawira, A. (2020). Visiting tourism destination : Is it influenced by smart tourism technology ? Journal of Indonesian Tourism and Development Studies, 8(3), 145–155. https://doi.org/10.21776/ub.jitode.2020.008.03.04
Tussyadiah, I. P., Wang, D., & Jia, C. H. (2017). Virtual reality and attitudes toward tourism destinations. In Information and Communication Technologies in Tourism 2017 (pp. 229– 239). Springer, Cham. https://doi.org/10.1007/978-3-319-51168-9
Um, T., & Chung, N. (2019). Does smart tourism technology matter? Lessons from three smart tourism cities in South Korea. Asia Pacific Journal of Tourism Research. https://doi.org/10.1080/10941665.2019.1595691
UNWTO. (2020). Growth in international tourist arrivals continues to outpace the economy. World Tourism Baromoter, 18(1), 1–6.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 324–365. https://doi.org/1047-7047/00/1104/0342$05.00
Wang, D., Li, X., & Li, Y. (2013). China’s “smart tourism destination” initiative: A taste of the service-dominant logic. Journal of Destination Marketing and Management, 2(2), 59– 61. https://doi.org/10.1016/j.jdmm.2013.05.004
Wang, X., Li, X. R., Zhen, F., & Zhang, J. H. (2016). How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach. Tourism Management, 54, 309–320. https://doi.org/10.1016/j.tourman.2015.12.003
Xia, M., Zhang, Y., & Zhang, C. (2018). A TAM-based approach to explore the effect of online experience on destination image: A smartphone user’s perspective. Journal of Destination Marketing & Management, 8, 259–270. https://doi.org/https://doi.org/10.1016/j.jdmm.2017.05.002
Yoo, C. W., Goo, J., Huang, C. D., Nam, K., & Woo, M. (2017). Improving travel decision support satisfaction with smart tourism technologies: A framework of tourist elaboration likelihood and self-efficacy. Technological Forecasting and Social Change, 123, 330– 341. https://doi.org/10.1016/j.techfore.2016.10.071
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.4135/9781446249215.n22
Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior : Attitudes , intentions , and perceived behavioral control. Journal of Experimental Social Psychology, 22, 453– 474.
Ballina, F. J., Valdes, L., & Del Valle, E. (2019). The Phygital experience in the smart tourism destination. International Journal of Tourism Cities, 5(4), 656–671. https://doi.org/10.1108/IJTC-11-2018-0088
Başer, G., Doğan, O., & Al-Turjman, F. (2019). Smart tourism destination in smart cities paradigm: a model for Antalya. In Artificial Intelligence in IoT (pp. 63–83). Springer.
BPS-Statistics Indonesia. (2019). Statistik wisatawan nusantara 2018. BPS RI.
Buhalis, D. (1997). Information technology as a strategic tool for economic, social, cultural and environmental benefits enhancement of tourism at destination regions. Progress in Tourism and Hospitality Research, 3(1), 71–93.
Buhalis, D., & Amaranggana, A. (2015). Smart tourism destinations enhancing tourism experience through personalisation of services. Information and Communication Technologies in Tourism, 377–389. https://doi.org/10.1007/978-3-319-14343-9
Chen, H., Rong, W., Ma, X., Qu, Y., & Xiong, Z. (2017). An extended technology acceptance model for mobile social gaming service popularity analysis. Mobile Information Systems, 1–12. https://doi.org/https://doi.org/10.1155/2017/3906953
Chin, W. W. (1998). The partial least squares approach to structural modeling. In Modern Method for Business Research (pp. 295–336). Lawrence Erlbaum Associates, Inc.
Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
Chuttur, M. (2009). Overview of the technology acceptance model: origins, developments and future directions. Sprouts: Working Papers on Information Systems, 9(37), 1–23. https://doi.org/10.1021/jf001443p
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/https://doi.org/10.2307/249008
Filimonau, V., & Perez, L. (2019). National culture and tourist destination choice in the UK and Venezuela: an exploratory and preliminary study. Tourism Geographies, 21(2), 235– 260. https://doi.org/10.1080/14616688.2018.1490342
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to the- oryand research. Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/https://doi.org/10.1177/002224378101800104
French, A. M., Luo, X. (Robert), & Bose, R. (2017). Toward a holistic understanding of continued use of social networking tourism: A mixed-methods approach. Information and Management, 54(6), 802–813. https://doi.org/10.1016/j.im.2016.10.006
Ghaderi, Z., Hatamifar, P., & Henderson, J. C. (2018). Destination selection by smart tourists: the case of Isfahan, Iran. Asia Pacific Journal of Tourism Research, 23(4), 385–394. https://doi.org/10.1080/10941665.2018.1444650
Gretzel, U., Werthner, H., Koo, C., & Lamsfus, C. (2015). Conceptual foundations for understanding smart tourism ecosystems. Computers in Human Behavior, 50, 558–563.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage publications.
Halpenny, E., Kono, S., & Moghimehfar, F. (2018). Predicting world heritage site visitation intentions of North American park visitors. Journal of Hospitality and Tourism Technology, 9(3), 417–437. https://doi.org/10.1108/JHTT-10-2017-0109
Hua, L. Y., Ramayah, T., Ping, T. A., & Jun-Hwa, C. (2017). Social media as a tool to help select tourism destinations: The case of Malaysia. Information Systems Management, 34(3), 265–279. https://doi.org/https://doi.org/10.1080/10580530.2017.1330004
Huang, Y., Hsu, M. K., Basu, C., & Huang, F. (2009). Toward developing a social network site-based model for knowledge sharing in the travel industry. Issues in Innovation, 3(1).
Im, J., & Hancer, M. (2016). What fosters favorable attitudes toward using travel mobile applications? Journal of Hospitality Marketing and Management, 26(4), 361–377. https://doi.org/10.1080/19368623.2017.1248805
Jamshidi, D., & Hussin, N. (2016). Forecasting patronage factors of Islamic credit card as a new e-commerce banking service. Journal of Islamic Marketing, 7(4), 378–404. https://doi.org/https://doi.org/10.1108/JIMA-07-2014-0050
Jeong, M., & Shin, H. H. (2019). Tourists’ experiences with smart tourism technology at smart destinations and their behavior intentions. Journal of Travel Research, 59(8), 1464–1477. https://doi.org/10.1177/0047287519883034
Kah, J. A., Lee, C.-K., & Lee, S.-H. (2016). Spatial–temporal distances in travel intention– behavior. Annals of Tourism Research, 57, 160–175. https://doi.org/https://doi.org/10.1016/j.annals.2015.12.017
Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, D. Y., Park, J., & Morrison, A. M. (2008). A model of traveller acceptance of mobile technology. International Journal of Tourism Research, 10(5), 393–407. https://doi.org/10.1002/jtr.669
Kim, J. Y., Chung, N., & Ahn, K. M. (2019). The impact of mobile tour information services on destination travel intention. Information Development, 35(1), 107–120. https://doi.org/https://doi.org/10.1177/0266666917730437
Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/IJCHM-09-2012-0165
Koo, C., Shin, S., Gretzel, U., Hunter, W. C., & Chung, N. (2016). Conceptualization of smart tourism destination competitiveness. Asia Pacific Journal of Information Systems, 26(4), 367–384. https://doi.org/10.14329/apjis.2016.26.4.561
Lee, H., Lee, J., Chung, N., & Koo, C. (2018). Tourists’ happiness: are there smart tourism technology effects? Asia Pacific Journal of Tourism Research, 23(5), 486–501. https://doi.org/10.1080/10941665.2018.1468344
Lee, H. W., Ramayah, T., & Zakaria, N. (2012). External factors in hospital information system (HIS) adoption model: a case on malaysia. Journal of Medical Systems, 36, 2129–2140. https://doi.org/https://doi.org/10.1007/s10916-011-9675-4
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/https://doi.org/10.1016/S0378-7206(01)00143-4
Lin, W. B., Wang, M. K., & Hwang, K. P. (2010). The combined model of influencing on-line consumer behavior. Expert Systems with Applications, 37(4), 3236–3247. https://doi.org/10.1016/j.eswa.2009.09.056
Liu, D., Du, H., Southworth, F., & Ma, S. (2017). The influence of social-psychological factors on the intention to choose low-carbon travel modes in Tianjin, China. Transportation Research Part A: Policy and Practice, 105(November), 42–53. https://doi.org/10.1016/j.tra.2017.08.004
Nunkoo, R., Ramkissoon, H., & Juwaheer, T. D. (2016). Travelers’ intent to purchase tourism products and services online. Travel and Tourism Research Association: Advancing Tourism Research Globally, 66.
Park, S. H., Hsieh, C. M., & Lee, C. K. (2017). Examining Chinese college students’ intention to travel to Japan using the extended theory of planned behavior: Testing destination image and the mediating role of travel constraints. Journal of Travel and Tourism Marketing, 34(1), 113–131. https://doi.org/10.1080/10548408.2016.1141154
Paul, H. S., Roy, D., & Mia, R. (2019). Influence of social media on tourists’ destination selection decision influence of social media on tourists’ destination selection decision. Scholars Bulletin, 5(11), 658–664. https://doi.org/10.36348/SB.2019.v05i11.009
Priya, R., Gandhi, A. V., & Shaikh, A. (2018). Mobile banking adoption in an emerging economy: An empirical analysis of young Indian consumers. Benchmarking: An International Journal, 25(2), 743–762. https://doi.org/https://doi.org/10.1108/BIJ-01-2016-0009
Sahli, A. B., & Legohérel, P. (2015). The tourism Web acceptance model: A study of intention to book tourism products online. Journal of Vacation Marketing, 22(2), 179–194. https://doi.org/10.1177/1356766715607589
Sevrani, K., & Elmazi, L. (2008). ICT and the changing landscape of tourism distribution- a new dimension of tourism in the global conditions. Revista de Turism, 6, 22–29.
Shafiee, S., Rajabzadeh Ghatari, A., Hasanzadeh, A., & Jahanyan, S. (2019). Developing a model for sustainable smart tourism destinations: A systematic review. Tourism Management Perspectives, 31, 287–300. https://doi.org/10.1016/j.tmp.2019.06.002
Sheeran, P. (2002). Intention—behavior relations: a conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/https://doi.org/10.1080/14792772143000003
Sigala, M. (2018). New technologies in tourism: From multi-disciplinary to anti-disciplinary advances and trajectories. Tourism Management Perspectives, 25, 151–155. https://doi.org/https://doi.org/10.1016/j.tmp.2017.12.003
Suhartanto, D. (2017). The role of store coopetition and attractiveness on the performance of tourism destination and its retail stores. International Journal of Tourism Policy, 7(2), 151–165. https://doi.org/10.1504/IJTP.2017.085327
Suhartanto, D., & Leo, G. (2018). Small business entrepreneur resistance of ICT adoption: a lesson from Indonesia. International Journal of Business and Globalisation, 21(1), 5. https://doi.org/10.1504/ijbg.2018.10015253
Susanto, E., Novianti, S., Rafdinal, W., Fitriani, M., & Prawira, A. (2020). Visiting tourism destination : Is it influenced by smart tourism technology ? Journal of Indonesian Tourism and Development Studies, 8(3), 145–155. https://doi.org/10.21776/ub.jitode.2020.008.03.04
Tussyadiah, I. P., Wang, D., & Jia, C. H. (2017). Virtual reality and attitudes toward tourism destinations. In Information and Communication Technologies in Tourism 2017 (pp. 229– 239). Springer, Cham. https://doi.org/10.1007/978-3-319-51168-9
Um, T., & Chung, N. (2019). Does smart tourism technology matter? Lessons from three smart tourism cities in South Korea. Asia Pacific Journal of Tourism Research. https://doi.org/10.1080/10941665.2019.1595691
UNWTO. (2020). Growth in international tourist arrivals continues to outpace the economy. World Tourism Baromoter, 18(1), 1–6.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 324–365. https://doi.org/1047-7047/00/1104/0342$05.00
Wang, D., Li, X., & Li, Y. (2013). China’s “smart tourism destination” initiative: A taste of the service-dominant logic. Journal of Destination Marketing and Management, 2(2), 59– 61. https://doi.org/10.1016/j.jdmm.2013.05.004
Wang, X., Li, X. R., Zhen, F., & Zhang, J. H. (2016). How smart is your tourist attraction?: Measuring tourist preferences of smart tourism attractions via a FCEM-AHP and IPA approach. Tourism Management, 54, 309–320. https://doi.org/10.1016/j.tourman.2015.12.003
Xia, M., Zhang, Y., & Zhang, C. (2018). A TAM-based approach to explore the effect of online experience on destination image: A smartphone user’s perspective. Journal of Destination Marketing & Management, 8, 259–270. https://doi.org/https://doi.org/10.1016/j.jdmm.2017.05.002
Yoo, C. W., Goo, J., Huang, C. D., Nam, K., & Woo, M. (2017). Improving travel decision support satisfaction with smart tourism technologies: A framework of tourist elaboration likelihood and self-efficacy. Technological Forecasting and Social Change, 123, 330– 341. https://doi.org/10.1016/j.techfore.2016.10.071
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