How Smart Are You at Traveling? Adoption of Smart Tourism Technology in Influencing Visiting Tourism Destinations

  • Lusianus KUSDIBYO Politeknik Negeri Bandung, Indonesia
  • Wahyu RAFDINAL Politeknik Negeri Bandung, Indonesia
  • Eko SUSANTO Politeknik Negeri Bandung, Indonesia
  • Rina SUPRINA Trisakti School of Tourism, Indonesia
  • Ikhsan NENDI Politeknik Siber Cerdika Internasional, Indonesia
  • Abdurokhim ABDUROKHIM Politeknik Siber Cerdika Internasional, Indonesia

Abstract

This study analyses smart tourism technology adoption's role in influencing visiting destinations by providing unity to the technology acceptance model (TAM) mechanism and the model theory of planned behaviour (TPB), using 324 samples of tourists from Indonesia. This study uncovers eight dimensions of innovative tourism technology by applying exploratory factor analysis. A variance-based structural equation model is used to evaluate the model and test hypotheses. This study reveals that the integrated TAM and TPB model can better explain smart tourism technology adoption and visiting tourism destinations. The integrated model is suitable for adopting smart tourism technology, which is the basis for tourist behaviour in tourist destinations. From its finding, this study offers a foundation for formulating an implementation strategy for using appropriate smart tourism technology to attract tourists. By originality, this study describes empirical evidence to promote the values of the smart tourism technology dimensions in enhancing tourist intention to use smart tourism technology and visit tourism destinations. 

References

[1] Agag, G. M., Khashan, M. A., & ElGayaar, M. H. 2019. Understanding online gamers’ intentions to play games online and effects on their loyalty: An integration of IDT, TAM and TPB. Journal of Customer Behaviour, 18(2): 101–130.
[2] Ajzen, I. 1991. The Theory of Planned Behavior Organizational Behavior and Human Decision Processes. Organizational Behavior and Human Decision Processes.
[3] Astor, Y., Suhartanto, D., Brien, A., Wibisono, N., & Novianti, S. 2022. Tourist Experience , Satisfaction , and Behavioural Intention during COVID-19 Outbreak A Lesson from Indonesian Creative Tourist Attractions. Journal of Quality Assurance in Hospitality & Tourism, 00(00): 1–20. DOI:https://doi.org/10.1080/1528008X.2022.2141415
[4] Azis, N., Amin, M., Chan, S., and Aprilia, C. 2020. How smart tourism technologies affect tourist destination loyalty. Journal of Hospitality and Tourism Technology, 11(4): 603–625. DOI: https://doi.org/10.1108/JHTT-01-2020-0005
[5] 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. DOI: https://doi.org/10.1108/IJTC-11-2018-0088
[6] 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.
[7] BPS. 2022. Number of International Tourist Arrivals to Indonesia by Entrance (Persons), 2019-2021. Available at: https://www.bps.go.id/indicator/16/1017/1/jumlah-kedatangan-wisatawan-mancanegara-ke-indonesia-menurut-pintu-masuk.html
[8] Cai, W., Richter, S., and McKenna, B. 2019. Progress on technology use in tourism. Journal of Hospitality and Tourism Technology, 10(4): 651–672. DOI: https://doi.org/10.1108/JHTT-07-2018-0068
[9] Cao, J., Zhang, J., Wang, C., Hu, H., & Yu, P. 2019. How far is the ideal destination? distance desire, ways to explore the antinomy of distance effects in tourist destination choice. Journal of Travel Research. DOI:https://doi.org/10.1177/0047287519844832

[10] Chen, S. Y. 2016. Using the sustainable modified TAM and TPB to analyze the effects of perceived green value on loyalty to a public bike system. Transportation Research Part A: Policy and Practice, 88: 58–72. DOI: https://doi.org/10.1016/j.tra.2016.03.008
[11] Davis, F. D. 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3): 319–340. DOI: https://doi.org/https://doi.org/10.2307/249008
[12] Dean, D., & Suhartanto, D. 2019. The formation of visitor behavioral intention to creative tourism: the role of push–Pull motivation. Asia Pacific Journal of Tourism Research, 24(5): 393–403. DOI:https://doi.org/10.1080/10941665.2019.1572631
[13] Fornell, C., & Larcker, D. F. 1981. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1): 39–50. DOI:https://doi.org/https://doi.org/10.1177/002224378101800104
[14] 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. DOI:https://doi.org/10.1080/10941665.2018.1444650
[15] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. 2019. When to Use and How to Report The Results of PLS-SEM. European Business Review, 31(1): 2–24. DOI: https://doi.org/10.1108/EBR-11-2018-0203
[16] 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. DOI: https://doi.org/10.1108/JHTT-10-2017-0109
[17] Hu, H., Zhang, J., Wang, C., Yu, P., & Chu, G. 2019. What influences tourists’ intention to participate in the Zero Litter Initiative in mountainous tourism areas: A case study of Huangshan National Park, China. Science of the Total Environment, 657: 1127–1137. DOI: https://doi.org/10.1016/j.scitotenv.2018.12.114
[18] 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. DOI:https://doi.org/10.1080/10580530.2017.1330004
[19] Hunter, W. C., Chung, N., Gretzel, U., & Koo, C. 2015. Constructivist research in smart tourism. Asia Pacific Journal of Information Systems, 25(1): 105–120.
[20] Im, J., & Hancer, M. 2017. What fosters favorable attitudes toward using travel mobile applications? Journal of Hospitality Marketing and Management, 26(4): 361–377. DOI:https://doi.org/10.1080/19368623.2017.1248805
[21] 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. DOI:https://doi.org/https://doi.org/10.1108/JIMA-07-2014-0050
[22] Jeong, M., & Shin, H. H. 2020. 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
[23] Kim, M., & Qu, H. 2014. Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2): 225–245. DOI: https://doi.org/10.1108/IJCHM-09-2012-0165
[24] 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. DOI:https://doi.org/10.14329/apjis.2016.26.4.561
[25] Kusdibyo, L. 2022. Tourist loyalty to hot springs destination: the role of tourist motivation, destination image, and tourist satisfaction. Leisure/Loisir, 46(3): 381–408. DOI:https://doi.org/https://doi.org/10.1080/14927713.2021.1986420
[26] Lamsfus, C., Martin, D., Alzua-Sorzabal, A., & Torres-Manzanera, E. 2015. Smart tourism destinations: An extended conception of smart cities focusing on human mobility. Information and Communication Technologies in Tourism, 363–375. DOI: https://doi.org/10.1007/978-3-319-14343-9
[27] Lin, W. B., Wang, M. K., & Hwang, K. P. 2010. The combined model of influencing online consumer behavior. Expert Systems with Applications, 37(4): 3236–3247. DOI:https://doi.org/10.1016/j.eswa.2009.09.056
[28] Mulyawan, I., & Rafdinal, W. 2021. Mobile games adoption : An extension of technology acceptance model and theory of reasoned action. IOP Conf. Series: Materials Science and Engineering. DOI:https://doi.org/10.1088/1757-899X/1098/3/032022
[29] Pantano, E., Priporas, C. V., & Stylos, N. 2017. ‘You will like it!’ using open data to predict tourists’ response to a tourist attraction. Tourism Management, 60: 430–438. https://doi.org/10.1016/j.tourman.2016.12.020
[30] 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. DOI:https://doi.org/10.36348/SB.2019.v05i11.009
[31] Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. 2017. Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis and Prevention, 108: 361–373. DOI:https://doi.org/10.1016/j.aap.2017.09.011
[32] 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. DOI:https://doi.org/10.1177/1356766715607589
[33] 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
[34] 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. DOI: https://doi.org/10.21776/ub.jitode.2020.008.03.04
[35] Um, T., & Chung, N. 2021. Does smart tourism technology matter? Lessons from three smart tourism cities in South Korea. Asia Pacific Journal of Tourism Research, 26(4): 396–414. DOI:https://doi.org/10.1080/10941665.2019.1595691
[36] 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. DOI: https://doi.org/1047-7047/00/1104/0342$05.00
[37] 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. DOI: https://doi.org/10.1016/j.tourman.2015.12.003
[38] Wibisono, N., Arrasy, B. F., & Rafdinal, W. 2022. Predicting Consumer Behaviour toward Digital K-Pop Albums : An Extended Model of the Theory of Planned Behaviour. Journal of Cultural Marketing Strategy, 7(1): 19–33.
[39] Wibisono, N., Rafdinal, W., Setiawati, L., & Senalasari, W. 2023. Predicting the adoption of virtual reality tourism in the post COVID-19 pandemic era. African Journal of Hospitality, Tourism and Leisure, 12(1): 239–256. DOI: https://doi.org/10.46222/ajhtl.19770720.365
[40] 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. DOI: https://doi.org/https://doi.org/10.1016/j.jdmm.2017.05.002
[41] Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: Integrating TAM, TPB, trust and perceived risk. Electronic Library, 35(1), 2–20. DOI: https://doi.org/10.1108/EL-08-2015-0141
Published
2023-06-30
How to Cite
KUSDIBYO, Lusianus et al. How Smart Are You at Traveling? Adoption of Smart Tourism Technology in Influencing Visiting Tourism Destinations. Journal of Environmental Management and Tourism, [S.l.], v. 14, n. 4, p. 2015 - 2028, june 2023. ISSN 2068-7729. Available at: <https://journals.aserspublishing.eu/jemt/article/view/7898>. Date accessed: 17 june 2024. doi: https://doi.org/10.14505/jemt.14.4(68).13.