Factors affecting international tourists’ intention to use local mobile apps in online purchase

References

• Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97–111. https://doi.org/https://doi.org/10.1016/j.chb.2016.02.038
   Web of Science ®Google Scholar
• Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23. https://doi.org/https://doi.org/10.1016/j.jretconser.2014.09.003
   Web of Science ®Google Scholar
• Ahmed, K., Khan, M., Siddiqui, O., Iftikhar, S., Das, B., & Khurrum, M. (2018). Proposed efficient method for ticket booking (PEMTB). Journal of Fundamental and Applied Sciences, 10(6S), 321–338. https://doi.org/http://dx.doi.org/10.4314/jfas.v10i6s.125
   Google Scholar
• Akroush, M. N., & Al-Debei, M. M. (2015). An integrated model of factors affecting consumer attitudes towards online shopping. Business Process Management Journal, 21(6), 1353–1376. https://doi.org/https://doi.org/10.1108/BPMJ-02-2015-0022
   Web of Science ®Google Scholar
• Aluri, A. (2017). Mobile augmented reality (MAR) game as a travel guide: Insights from Pokémon GOG.O. Journal of Hospitality and Tourism Technology, 8(1), 55–72. https://doi.org/https://doi.org/10.1108/JHTT-12-2016-0087
   Web of Science ®Google Scholar
• Amaro, S., & Duarte, P. (2013). Factors that influence the purchase of travel online: A proposed model. Aspects of Tourist Behavior, 5, 63–76. http://hdl.handle.net/10400.19/2581
   Google Scholar
• Assaker, G. (2020). Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: Extending the technology acceptance model (TAM) with credibility theory. Journal of Hospitality Marketing & Management, 29(4), 428–449. https://doi.org/https://doi.org/10.1080/19368623.2019.1653807
   Web of Science ®Google Scholar
• Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of Family Business Strategy, 5(1), 116–128. https://doi.org/https://doi.org/10.1016/j.jfbs.2013.12.002
   Web of Science ®Google Scholar
• Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 69(4), 133–152. https://doi.org/https://doi.org/10.1509/jmkg.2005.69.4.133
   Web of Science ®Google Scholar
• Batkovic, I., & Batkovic, R. (2015). Understanding Consumer Acceptance of Mobile-Retail. An empirical analysis of the revised technology acceptance model. Master Degree Project.
   Google Scholar
• Benckendorff, P., Moscardo, G., & Pendergast, D. (2010). Tourism and generation Y. Cabi.
   Google Scholar
• Bicen, H., & Sadikoglu, S. (2016). Determination of the opinions of students on tourism impact using mobile applications. Procedia Economics and Finance, 39, 270–274. https://doi.org/https://doi.org/10.1016/S2212-5671(16)30354-9
   Google Scholar
• Bigné, E., Sanz, S., Ruiz, C., & Aldás, J. (2010). Why some Internet users don’t buy air tickets online. Information and Communication Technologies in Tourism, 209–221.
   Google Scholar
• Bilgihan, A. (2016). Gen Y customer loyalty in online shopping: An integrated model of trust, user experience and branding. Computers in Human Behavior, 61, 103–113. https://doi.org/https://doi.org/10.1016/j.chb.2016.03.014
   Web of Science ®Google Scholar
• Bilgihan, A., Kandampully, J., & Zhang, T. (2016). Towards a unified customer experience in online shopping environments: Antecedents and outcomes. International Journal of Quality and Service Sciences, 8(1), 102–119. https://doi.org/https://doi.org/10.1108/IJQSS-07-2015-0054
   Web of Science ®Google Scholar
• Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43(6), 706–717. https://doi.org/https://doi.org/10.1016/j.im.2006.03.007
   Web of Science ®Google Scholar
• Cacho, A., Mendes-Filho, L., Estaregue, D., Moura, B., Cacho, N., Lopes, F., & Alves, C. (2016). Mobile tourist guide supporting a smart city initiative: A Brazilian case study. International Journal of Tourism Cities, 2(2), 164–183. https://doi.org/https://doi.org/10.1108/IJTC-12-2015-0030
   Web of Science ®Google Scholar
• Calisir, F., Altin Gumussoy, C., & Bayram, A. (2009). Predicting the behavioral intention to use enterprise resource planning systems: An exploratory extension of the technology acceptance model. Management Research News, 32(7), 597–613. https://doi.org/https://doi.org/10.1108/01409170910965215
   Google Scholar
• Cameron, D., Gregory, C., & Battaglia, D. (2012). Nielsen personalizes the mobile shopping app: If you build the technology, they will come. Journal of Advertising Research, 52(3), 333–338. https://doi.org/https://doi.org/10.2501/JAR-52-3-333-338
   Web of Science ®Google Scholar
• Campón-Cerro, A. M., Hernández-Mogollón, J. M., & Alves, H. (2017). Sustainable improvement of competitiveness in rural tourism destinations: The quest for tourist loyalty in Spain. Journal of Destination Marketing & Management, 6(3), 252–266. https://doi.org/https://doi.org/10.1016/j.jdmm.2016.04.005
   Web of Science ®Google Scholar
• Castaneda, J. A., Frias, D. M., & Rodriguez, M. A. (2009). Antecedents of internet acceptance and use as an information source by tourists. Online Information Review, 3(3). https://doi.org/https://doi.org/10.1108/14684520910969952
   Google Scholar
• Chaffey, D. (2007). E-business and E-commerce management: Strategy, implementation and practice. Pearson Education.
   Google Scholar
• Chang, I.-C., Chou, P.-C., Yeh, R. K.-J., & Tseng, H.-T. (2016). Factors influencing Chinese tourists’ intentions to use the Taiwan medical travel App. Telematics and Informatics, 33(2), 401–409. https://doi.org/https://doi.org/10.1016/j.tele.2015.09.007
   Web of Science ®Google Scholar
• Choi, H., Kim, Y., & Kim, J. (2011). Driving factors of post adoption behavior in mobile data services. Journal of Business Research, 64(11), 1212–1217. https://doi.org/https://doi.org/10.1016/j.jbusres.2011.06.025
   Web of Science ®Google Scholar
• Choi, K., Wang, Y., & Sparks, B. (2018). Travel app users’ continued use intentions: It’sa matter of value and trust. Journal of Travel & Tourism Marketing, 36(1) 1–13. https://doi.org/https://doi.org/10.1080/10548408.2018.1505580
   Web of Science ®Google Scholar
• Chua, B.-L., Lee, S., Goh, B., & Han, H. (2015). Impacts of cruise service quality and price on vacationers’ cruise experience: Moderating role of price sensitivity. International Journal of Hospitality Management, 44, 131–145. https://doi.org/https://doi.org/10.1016/j.ijhm.2014.10.012
   Web of Science ®Google Scholar
• Chuang, C.-M. (2020). A current travel model: Smart tour on mobile guide application services. Current Issues in Tourism, 23(18), 2333–2352. https://doi.org/https://doi.org/10.1080/13683500.2019.1631266
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Dedeoglu, B. B., Bilgihan, A., Ye, B. H., Buonincontri, P., & Okumus, F. (2018). The impact of servicescape on hedonic value and behavioral intentions: The importance of previous experience. International Journal of Hospitality Management, 72, 10–20. https://doi.org/https://doi.org/10.1016/j.ijhm.2017.12.007
   Web of Science ®Google Scholar
• Dong, X., Dong, X., Chang, Y., Chang, Y., Wang, Y., Wang, Y., … Yan, J. (2017). Understanding usage of Internet of things (IOT) systems in China: Cognitive experience and affect experience as moderator. Information Technology & People, 30(1), 117–138. https://doi.org/https://doi.org/10.1108/ITP-11-2015-0272
   Web of Science ®Google Scholar
• Eagly, A. H., & Carli, L. L. (2003). The female leadership advantage: An evaluation of the evidence. The Leadership Quarterly, 14(6), 807–834. https://doi.org/https://doi.org/10.1016/j.leaqua.2003.09.004
   Web of Science ®Google Scholar
• Enache, M. C., & Man, O. R. (2017). Mobile Applications for Promoting Romanian Tourism. Annals of the University Dunarea de Jos of Galati: Fascicle: XVII, Medicine(2).
   Google Scholar
• Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G* power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/https://doi.org/10.3758/BRM.41.4.1149
   PubMed Web of Science ®Google Scholar
• Fong, L. H. N., Lam, L. W., & Law, R. (2017). How locus of control shapes intention to reuse mobile apps for making hotel reservations: Evidence from Chinese consumers. Tourism Management, 61, 331–342. https://doi.org/https://doi.org/10.1016/j.tourman.2017.03.002
   Web of Science ®Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
   Google Scholar
• Ghaderi, Z., Hatamifar, P., & Henderson, J. C. (2018a). Destination selection by smart tourists: The case of isfahan, Iran. Asia Pacific Journal of Tourism Research, 23(4), 1–10. https://doi.org/https://doi.org/10.1080/10941665.2018.1444650
   Web of Science ®Google Scholar
• Ghaderi, Z., Soltani, S., Henderson, J., & Zareei, A. (2018b). Sanctions, the 2015 agreement and Iran’s tourism industry. In S. H. Seyfi (Ed.), Tourism in Iran: Challenges, development and issues (pp. 55–66). Routledge.
   Google Scholar
• Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information & Management, 39(8), 705–719. https://doi.org/https://doi.org/10.1016/S0378-7206(01)00127-6
   Web of Science ®Google Scholar
• Gong, W., Stump, R. L., & Maddox, L. M. (2013). Factors influencing consumers’ online shopping in China. Journal of Asia Business Studies, 7(3), 214–230. https://doi.org/https://doi.org/10.1108/JABS-02-2013-0006
   Google Scholar
• Goodhue, D., Lewis, W., & Thompson, R. (2006, January). PLS, small sample size, and statistical power in MIS research. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06) (Vol. 8, pp. 202b-202b). IEEE.
   Google Scholar
• Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In Esposito Vinzi, V., Chin, W.W., Henseler, J., & Wang, H. (Eds.), Handbook of partial least squares (pp. 691–711). Springer.
   Google Scholar
• Guo, X. (2016). A study on the international tourism of Jiangxi province under the guidance of one belt, one road strategy. Economic and Social Changes: Facts, Trends, Forecast, 3(45), 221–230. https://doi.org/https://doi.org/10.15838/esc.2016.3.45.13
   Google Scholar
• Gupta, D. K., & Khincha, P. K. (2015). Factors influencing online shopping behavior of customers: An empirical study. Common wealth. Journal of Commerce & Management Research, 2(7), 39–50. https://doi.org/https://doi.org/10.4067/S071818762019000200102
   Google Scholar
• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/https://doi.org/10.2753/MTP1069-6679190202
   Google Scholar
• Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
   Google Scholar
• Henseler, J. (2012). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In Wolfgang A. Gaul & Andreas Geyer-Schulz (Eds.), Challenges at the interface of data analysis, computer science, and optimization (pp. 495–501). Springer.
   Google Scholar
• Höpken, W., Fuchs, M., Zanker, M., & Beer, T. (2010). Context-based adaptation of mobile applications in tourism. Information Technology & Tourism, 12(2), 175–195. https://doi.org/https://doi.org/10.3727/109830510X12887971002783
   Google Scholar
• Hsu, C.-L., Chuan-Chuan Lin, J., & Chiang, H.-S. (2013). The effects of blogger recommendations on customers’ online shopping intentions. Internet Research, 23(1), 69–88. https://doi.org/https://doi.org/10.1108/10662241311295782
   Web of Science ®Google Scholar
• Hsu, C.-L., & Lin, J. C.-C. (2015). What drives purchase intention for paid mobile apps?–An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, 14(1), 46–57. https://doi.org/https://doi.org/10.1016/j.elerap.2014.11.003
   Web of Science ®Google Scholar
• Hsu, C.-P., Chiang, Y.-F., & Huang, H.-C. (2012). How experience-driven community identification generates trust and engagement. Online Information Review, 36(1), 72–88. https://doi.org/https://doi.org/10.1108/14684521211206971
   Web of Science ®Google Scholar
• Huang, C. D., Goo, J., Nam, K., & Yoo, C. W. (2017). Smart tourism technologies in travel planning: The role of exploration and exploitation. Information & Management, 54(6), 757–770. https://doi.org/https://doi.org/10.1016/j.im.2016.11.010
   Web of Science ®Google Scholar
• Huang, Y.-C., Chang, L. L., Yu, C.-P., & Chen, J. (2019). Examining an extended technology acceptance model with experience construct on hotel consumers’ adoption of mobile applications. Journal of Hospitality Marketing & Management, 28(8), 957–980. https://doi.org/https://doi.org/10.1080/19368623.2019.1580172
   Web of Science ®Google Scholar
• Hung, S.-Y., Ku, C.-Y., & Chang, C.-M. (2003). Critical factors of WAP services adoption: An empirical study. Electronic Commerce Research and Applications, 2(1), 42–60. https://doi.org/https://doi.org/10.1016/S1567-4223(03)00008-5
   Google Scholar
• Ilie, V., Van Slyke, C., Green, G., & Lou, H. J. I. R. M. J. (2005). Gender differences in perceptions and use of communication technologies: A diffusion of innovation approach. 18(3), 13–31. https://doi.org/https://doi.org/10.4018/irmj.2005070102
   Google Scholar
• Islam, Z., Kim Cheng Low, P., & Hasan, I. (2013). Intention to use advanced mobile phone services (AMPS). Management Decision, 51(4), 824–838. https://doi.org/https://doi.org/10.1108/00251741311326590
   Web of Science ®Google Scholar
• Jeon, H.-M., Ali, F., & Lee, S.-W. (2018). Determinants of consumers’ intentions to use smartphones apps for flight ticket bookings. The Service Industries Journal, 39(5-6), 1–18. https://doi.org/https://doi.org/10.1080/02642069.2018.1437908
   Web of Science ®Google Scholar
• Kennedy-Eden, H., & Gretzel, U. (2012). A taxonomy of mobile applications in tourism.
   Google Scholar
• Khodadadi, M. (2016). A new dawn? The Iran nuclear deal and the future of the Iranian tourism industry. Tourism Management Perspectives, 18, 6–9. https://doi.org/https://doi.org/10.1016/j.tmp.2015.12.019
   Web of Science ®Google Scholar
• Kothari, C. R. (2004). Research methodology: Methods and techniques. New Age International.
   Google Scholar
• Kibe, J., Ogutu, H., & Ojwach, S. (2019). Efficacy of the use of mobile applications on front office operations; A case study Hilton Hotel Nairobi. Journal of Hospitality and Tourism Management, 2(1), 1–16.
   Google Scholar
• 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/https://doi.org/10.1002/jtr.669
   Web of Science ®Google Scholar
• Kim, E., Lin, J.-S., & Sung, Y. (2013). To app or not to app: Engaging consumers via branded mobile apps. Journal of Interactive Advertising, 13(1), 53–65. https://doi.org/https://doi.org/10.1080/15252019.2013.782780
   Google Scholar
• Kim, M.-J., Chung, N., & Lee, C.-K. (2011). The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea. Tourism Management, 32(2), 256–265. https://doi.org/https://doi.org/10.1016/j.tourman.2010.01.011
   Web of Science ®Google Scholar
• Kim, M. J., Chung, N., Lee, C. K., & Preis, M. W. (2015). Motivations and use context in mobile tourism shopping: Applying contingency and task–technology fit theories. International Journal of Tourism Research, 17(1), 13–24. https://doi.org/https://doi.org/10.1002/jtr.1957
   Web of Science ®Google Scholar
• Kim, Y. G., & Woo, E. (2016). Consumer acceptance of a quick response (QR)Q.R.) code for the food traceability system: Application of an extended technology acceptance model (TAM). Food Research International, 85, 266–272. https://doi.org/https://doi.org/10.1016/j.foodres.2016.05.002
   PubMed Web of Science ®Google Scholar
• Lai, I. K. (2015). Traveler acceptance of an app-based mobile tour guide. Journal of Hospitality & Tourism Research, 39(3), 401–432. https://doi.org/https://doi.org/10.1177/1096348013491596
   Web of Science ®Google Scholar
• Law, R., Leung, R., & Buhalis, D. (2009). Information technology applications in hospitality and tourism: A review of publications from 2005 to 2007. Journal of Travel & Tourism Marketing, 26(5-6), 599–623. https://doi.org/https://doi.org/10.1080/10548400903163160
   Web of Science ®Google Scholar
• Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91. Pew Internet & American Life Project. https://doi.org/https://doi.org/10.1080/10864415.2001.11044227
   Web of Science ®Google Scholar
• Lee, S. M., Tan, X., & Trimi, S. (2006). M-government, from rhetoric to reality: Learning from leading countries. Electronic Government, an International Journal, 3(2), 113–126. https://doi.org/https://doi.org/10.1504/EG.2006.009213
   Google Scholar
• Liu, C., Lu, J., & Yu, C.-S. (2018). Examining wechat social commerce continuance intention and use incorporating personality traits. Paper presented at the Proceedings of 2018 International Conference on Big Data Technologies.
   Google Scholar
• Lu, J. (2014). Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research, 24(2), 134–159. https://doi.org/https://doi.org/10.1108/IntR-05-2012-0100
   Web of Science ®Google Scholar
• Maruping, L. M., Bala, H., Venkatesh, V., & Brown, S. A. (2017). Going beyond intention: Integrating behavioral expectation into the unified theory of acceptance and use of technology. Journal of the Association for Information Science and Technology, 68(3), 623–637. https://doi.org/https://doi.org/10.1002/asi.23699
   Web of Science ®Google Scholar
• Miyatake, K., Nemoto, T., Nakaharai, S., & Hayashi, K. (2016). Reduction in consumers’ purchasing cost by online shopping. Transportation Research Procedia, 12, 656–666. https://doi.org/https://doi.org/10.1016/j.trpro.2016.02.019
   Google Scholar
• Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer Affairs, 35(1), 27–44. https://doi.org/https://doi.org/10.1111/j.1745-6606.2001.tb00101.x
   Web of Science ®Google Scholar
• Mo Kwon, J., Bae, J.-i., & Blum, S. C. (2013). Mobile applications in the hospitality industry. Journal of Hospitality and Tourism Technology, 4(1), 81–92. https://doi.org/https://doi.org/10.1108/17579881311302365
   Google Scholar
• Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8–22. https://doi.org/https://doi.org/10.1016/j.jretconser.2017.02.010
   Web of Science ®Google Scholar
• No, E., & Kim, J. K. (2014). Determinants of the adoption for travel information on smartphone. International Journal of Tourism Research, 16(6), 534–545. https://doi.org/https://doi.org/10.1002/jtr.1945
   Web of Science ®Google Scholar
• Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005a). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346. https://doi.org/https://doi.org/10.1177/0092070305276149
   Web of Science ®Google Scholar
• Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. J. J. o. c. M. (2005b). Explaining intention to use mobile chat services: moderating effects of gender.
   Google Scholar
• Oh, S., Lehto, X. Y., & Park, J. (2009). Travelers’ intent to use mobile technologies as a function of effort and performance expectancy. Journal of Hospitality Marketing & Management, 18(8), 765–781. https://doi.org/https://doi.org/10.1080/19368620903235795
   Google Scholar
• Okazaki, S., Campo, S., Andreu, L., & Romero, J. (2015). A latent class analysis of Spanish travelers’ mobile internet usage in travel planning and execution. Cornell Hospitality Quarterly, 56(2), 191–201. https://doi.org/https://doi.org/10.1177/1938965514540206
   Web of Science ®Google Scholar
• Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. (2015). Mobile hotel booking technology in the hotel industry. Paper presented at the International Academic Conference on Social Sciences.
   Google Scholar
• Ozturk, A. B., Nusair, K., Okumus, F., & Hua, N. (2016). The role of utilitarian and hedonic values on users’ continued usage intention in a mobile hotel booking environment. International Journal of Hospitality Management, 57, 106–115. https://doi.org/https://doi.org/10.1016/j.ijhm.2016.06.007
   Web of Science ®Google Scholar
• Pappas, I. O., Pateli, A., Giannakos, M., & Chrissikopoulos, V. (2014). Moderating effects of online shopping experience on customer satisfaction and repurchase intentions. International Journal of Retail & Distribution Management, 42(3), 187–204. https://doi.org/https://doi.org/10.1108/IJRDM-03-2012-0034
   Google Scholar
• Pareek, M., & Pattison, H. M. (2000). The two-dose measles, mumps, and rubella (MMR) immunisation schedule: Factors affecting maternal intention to vaccinate. British Journal of General Practice, 50(461), 969–971.
   Google Scholar
• Peres, R., Correia, A., & Moital, M. (2011). The indicators of intention to adopt mobile electronic tourist guides. Journal of Hospitality and Tourism Technology, 2(2), 120–138. https://doi.org/https://doi.org/10.1108/17579881111154236
   Google Scholar
• Pratt, S., & Alizadeh, V. (2018). The economic impact of the lifting of sanctions on tourism in Iran: A computable general equilibrium analysis. Current Issues in Tourism, 21(11), 1221–1238. https://doi.org/https://doi.org/10.1080/13683500.2017.1307329
   Web of Science ®Google Scholar
• Purcell, K. (2011). Half of adult cell phone owners have apps on their phones (pp. 1-33). Washington, DC.
   Google Scholar
• Rahimi, R., Hassan, A., & Tekin, O. (2017). Augmented reality apps for tourism destination promotion. In Sajad Rezaei (Ed.), Apps Management and E-commerce transactions in real-time (pp. 236–251). IGI Global.
   Google Scholar
• Rajput, M. (2015). Tracing the History and Evolution of Mobile Apps. https://tech.co/mobile-app-history-evolution-2015-11
   Google Scholar
• Riebeck, M., Stark, A., Modsching, M., & Kawalek, J. (2008). Studying the user acceptance of a mobile information system for tourists in the field. Information Technology & Tourism, 10(3), 189–199. https://doi.org/https://doi.org/10.3727/109830508787157308
   Google Scholar
• Schreurs, K., Quan-Haase, A., & Martin, K. J. C. J. o. C. (2017). Problematizing the digital literacy paradox in the context of older adults’ ICT use: Aging, media discourse, and self-determination. Canadian Journal of Communication, 42(2), 359–367. https://doi.org/https://doi.org/10.22230/cjc.2017v42n2a3130
   Google Scholar
• Schubring, S., Lorscheid, I., Meyer, M., & Ringle, C. M. (2016). The PLS agent: Predictive modeling with PLS-SEM and agent-based simulation. Journal of Business Research, 69(10). https://doi.org/https://doi.org/10.1016/j.jbusres.2016.03.052
   Google Scholar
• Selvi, M. S. (2016). Mobile marketing applications of travel agencies. International Journal of Research in Business and Social Science, 3(4), 68–84. https://doi.org/https://doi.org/10.20525/ijrbs.v3i4.118
   Google Scholar
• Seyfi, S., & Hall, C. M. (2019). International sanctions, tourism destinations and resistive economy. Journal of Policy Research in Tourism, Leisure and Events, 11(1), 159–169. https://doi.org/https://doi.org/10.1080/19407963.2018.1482305
   Web of Science ®Google Scholar
• Seyfi, S., Hall, C. M., & Vo-Thanh, T. (2020). Tourism, peace and sustainability in sanctions-ridden destinations. Journal of Sustainable Tourism, 1–20. https://doi.org/https://doi.org/10.1080/09669582.2020.1818764
   Web of Science ®Google Scholar
• Shemesh, T., Barnoy, S. J. T., & e-Health. (2020). Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population.
   Google Scholar
• Shi, S., & Chow, W. S. (2015). Trust development and transfer in social commerce: Prior experience as moderator. Industrial Management & Data Systems, 115(7), 1182–1203. https://doi.org/https://doi.org/10.1108/IMDS-01-2015-0019
   Web of Science ®Google Scholar
• Shih, Y.-Y., & Chen, C.-Y. (2013). The study of behavioral intention for mobile commerce: Via integrated model of TAM and TTF. Quality & Quantity, 1–12.
   Google Scholar
• Smirnov, A., Kashevnik, A., Ponomarev, A., Shchekotov, M., & Kulakov, K. (2015). Application for e-tourism: intelligent mobile tourist guide. Paper presented at the Advanced Applied Informatics (IIAI-AAI), 2015 IIAI 4th International Congress on.
   Google Scholar
• Suhartanto, D. J. J. o. I. M. (2019). Predicting behavioural intention toward Islamic bank: a multi-group analysis approach.
   Google Scholar
• Sun, S., Lee, P. C., Law, R., & Zhong, L. (2020). The impact of cultural values on the acceptance of hotel technology adoption from the perspective of hotel employees. Journal of Hospitality and Tourism Management, 44, 61–69. https://doi.org/https://doi.org/10.1016/j.jhtm.2020.04.012
   Web of Science ®Google Scholar
• Tan, G. W.-H., Lee, V. H., Lin, B., & Ooi, K.-B. (2017). Mobile applications in tourism: The future of the tourism industry? Industrial Management & Data Systems, 117(3), 560–581. https://doi.org/https://doi.org/10.1108/IMDS-12-2015-0490
   Web of Science ®Google Scholar
• Tan, G. W.-H., & Ooi, K.-B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 47(2). https://doi.org/https://doi.org/10.1016/j.tele.2018.04.009
   Google Scholar
• Teo, T., & Noyes, J. J. I. L. E. (2014). Explaining the intention to use technology among pre-service teachers: A multi-group analysis of the unified theory of acceptance and use of technology. Interactive Learning Environments, 22(1), 51–66. https://doi.org/https://doi.org/10.1080/10494820.2011.641674
   Google Scholar
• Thakur, R., & Srivastava, M. (2013). Customer usage intention of mobile commerce in India: An empirical study. Journal of Indian Business Research, 5(1), 52–72. https://doi.org/https://doi.org/10.1108/17554191311303385
   Google Scholar
• Ting, H., Fam, K.-S., Hwa, J. C. J., Richard, J. E., & Xing, N. J. T. M. (2019). Ethnic food consumption intention at the touring destination: The national and regional perspectives using multi-group analysis. Tourism Management, 71, 518–529.
   Google Scholar
• Tong, X. (2010). A cross-national investigation of an extended technology acceptance model in the online shopping context. International Journal of Retail & Distribution Management, 38(10), 742–759. https://doi.org/https://doi.org/10.1108/09590551011076524
   Google Scholar
• Toor, A. (2017). Apple removes popular apps in Iran due to USU.S. sanctions. https://www.theverge.com/2017/8/25/16201434/apple-iran-app-store-removal-sanctions-trump
   Google Scholar
• Vahdat, A., Alizadeh, A., Quach, S., & Hamelin, N. (2020). Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention. Australasian Marketing Journal (AMJ) 29(2). https://doi.org/https://doi.org/10.1016/j.ausmj.2020.01.002
   Google Scholar
• Vallespín, M., Molinillo, S., & Muñoz-Leiva, F. (2017). Segmentation and explanation of smartphone use for travel planning based on socio-demographic and behavioral variables. Industrial Management & Data Systems, 117(3), 605–619. https://doi.org/https://doi.org/10.1108/IMDS-03-2016-0089
   Web of Science ®Google Scholar
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/https://doi.org/10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Perspectives on partial least squares. In V. E. Vinzi, W. W. Chin, J. Henseler & H. Wang (Eds.), Handbook of partial least squares (pp. 1–20). Springer.
   Google Scholar
• Wang, D., Xiang, Z., & Fesenmaier, D. R. (2016). Smartphone use in everyday life and travel. Journal of Travel Research, 55(1), 52–63. https://doi.org/https://doi.org/10.1177/0047287514535847
   Web of Science ®Google Scholar
• Wang, H.-Y., & Wang, S.-H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598–608. https://doi.org/https://doi.org/10.1016/j.ijhm.2009.11.001
   Web of Science ®Google Scholar
• Xia, M., Zhang, Y., & Zhang, C. (2017). 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. https://doi.org/https://doi.org/10.1016/j.jdmm.2017.05.002
   Google Scholar
• Xiang, Z., Magnini, V. P., & Fesenmaier, D. R. (2015). Information technology and consumer behavior in travel and tourism: Insights from travel planning using the internetInternet. Journal of Retailing and Consumer Services, 22, 244–249. https://doi.org/https://doi.org/10.1016/j.jretconser.2014.08.005
   Web of Science ®Google Scholar
• Yang, H. C. (2013). Bon appétit for apps: Young American consumers’ acceptance of mobile applications. Journal of Computer Information Systems, 53(3), 85–96. https://doi.org/https://doi.org/10.1080/08874417.2013.11645635
   Web of Science ®Google Scholar
• Yenisey, M. M., Ozok, A. A., & Salvendy, G. (2005). Perceived security determinants in e-commerce among Turkish university students. Behaviour & Information Technology, 24(4), 259–274. https://doi.org/https://doi.org/10.1080/0144929042000320992
   Web of Science ®Google Scholar
• Yoon, S.-J. (2002). The antecedents and consequences of trust in online-purchase decisions. Journal of Interactive Marketing, 16(2), 47–63. https://doi.org/https://doi.org/10.1002/dir.10008
   Google Scholar
• Zhang, H., Wu, Y., & Buhalis, D. (2017). A model of perceived image, memorable tourism experiences and revisit intention. Journal of Destination Marketing & Management, 8. https://doi.org/https://doi.org/10.1016/j.jdmm.2017.06.004
   Google Scholar
• Zhou, T. (2012). Examining mobile banking user adoption from the perspectives of trust and flow experience. Information Technology and Management, 13(1), 27–37. https://doi.org/https://doi.org/10.1007/s10799-011-0111-8
   Web of Science ®Google Scholar