Reinvestigating repurchase intentions for travel apps: a comparison of China's various tiers of cities

References

• Aguirre-Urreta, M. I., & Hu, J. (2019). Detecting common method bias: Performance of the Harman’s single-factor test. Data Base for Advances in Information Systems, 50(2), 45–70. https://doi.org/10.1145/3330472.3330477
   Web of Science ®Google Scholar
• Ahmad, W., Kim, W. G., Choi, H. M., & Haq, J. U. (2021). Modeling behavioral intention to use travel reservation apps: A cross-cultural examination between US and China. Journal of Retailing and Consumer Services, 63, 102689. https://doi.org/10.1016/j.jretconser.2021.102689
   Web of Science ®Google Scholar
• Ali, F., Terrah, A., Wu, C., Ali, L., & Wu, H. (2021). Antecedents and consequences of user engagement in smartphone travel apps. Journal of Hospitality and Tourism Technology, 12(2), 355–371. https://doi.org/10.1108/JHTT-09-2020-0221
   Web of Science ®Google Scholar
• Atwal, G., & Bryson, D. (2017). Luxury brands in China and India. In Luxury brands in China and India. Palgrave Macmillan. https://doi.org/10.1057/978-1-137-54715-6/COVER
   Google Scholar
• Badu-Baiden, F., Kim, S., & Wong, I. A. (2023). A cross-cultural multilevel investigation on memorable destination local food consumption experience and food personality traits. Journal of Travel & Tourism Marketing, 40(4), 275–293. https://doi.org/10.1080/10548408.2023.2245423
   Web of Science ®Google Scholar
• Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421–458. https://doi.org/10.2307/2393203
   Web of Science ®Google Scholar
• Becker, J. M., Cheah, J. H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321–346. https://doi.org/10.1108/IJCHM-04-2022-0474
   Web of Science ®Google Scholar
• Becker, J. M., Ringle, C. M., Sarstedt, M., & Völckner, F. (2015). How collinearity affects mixture regression results. Marketing Letters, 26(4), 643–659. https://doi.org/10.1007/s11002-014-9299-9
   Web of Science ®Google Scholar
• Benítez-Aurioles, B. (2018). Why are flexible booking policies priced negatively? Tourism Management, 67, 312–325. https://doi.org/10.1016/j.tourman.2018.02.008
   Web of Science ®Google Scholar
• Bento, M., Martinez, L. M., & Martinez, L. F. (2018). Brand engagement and search for brands on social media: Comparing Generations X and Y in Portugal. Journal of Retailing and Consumer Services, 43(January), 234–241. https://doi.org/10.1016/j.jretconser.2018.04.003
   Google Scholar
• Bilby, J., Reid, M., & Brennan, L. (2016). The future of advertising in China: Practitioner insights into the evolution of Chinese advertising creativity. Journal of Advertising Research, 56(3), 245–258. https://doi.org/10.2501/JAR-2016-018
   Web of Science ®Google Scholar
• Bilby, J., Reid, M., Brennan, L., & Chen, J. (2020). Tiers and fears: An investigation of the impact of city tiers and uncertainty avoidance on Chinese consumer response to creative advertising. Australasian Marketing Journal, 28(4), 332–348. https://doi.org/10.1016/j.ausmj.2020.07.005
   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/10.1108/IJQSS-07-2015-0054
   Web of Science ®Google Scholar
• Bravo, R., Catalán, S., & Pina, J. M. (2021). Understanding how customers engage with social tourism websites. Journal of Hospitality and Tourism Technology, 12(1), 141–154. https://doi.org/10.1108/JHTT-02-2019-0040
   Web of Science ®Google Scholar
• CEIC. (2022). China Gross Domestic Product: Prefecture Level City.
   Google Scholar
• Cham, T. H., Lim, Y. M., & Sigala, M. (2022). Marketing and social influences, hospital branding, and medical tourists’ behavioural intention: Before- and after-service consumption perspective. International Journal of Tourism Research, 24(1), 140–157. https://doi.org/10.1002/jtr.2489
   Web of Science ®Google Scholar
• Cheah, J. H., Amaro, S., & Roldán, J. L. (2023). Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations. Journal of Business Research, 156, 113539. https://doi.org/10.1016/j.jbusres.2022.113539
   Web of Science ®Google Scholar
• Cheah, J. H., Lim, X. J., Ting, H., Liu, Y., & Quach, S. (2022). Are privacy concerns still relevant? Revisiting consumer behaviour in omnichannel retailing. Journal of Retailing and Consumer Services, 65, 102242. https://doi.org/10.1016/j.jretconser.2020.102242
   Web of Science ®Google Scholar
• Cheah, J. H., Nitzl, C., Roldán, J. L., Cepeda-Carrion, G., & Gudergan, S. P. (2021). A primer on the conditional mediation analysis in PLS-SEM. Data Base for Advances in Information Systems, 52(SI), 43–100. https://doi.org/10.1145/3505639.3505645
   Google Scholar
• Cheung, M. L., Leung, W. K. S., Cheah, J. H., & Ting, H. (2022). Exploring the effectiveness of emotional and rational user-generated contents in digital tourism platforms. Journal of Vacation Marketing, 28(2), 152–170. https://doi.org/10.1177/13567667211030675
   Web of Science ®Google Scholar
• Chin, W., Cheah, J. H., Liu, Y., Ting, H., Lim, X. J., & Cham, T. H. (2020). Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research. Industrial Management and Data Systems, 120(12), 2161–2209. https://doi.org/10.1108/IMDS-10-2019-0529
   Web of Science ®Google Scholar
• Choi, K., Wang, Y., & Sparks, B. (2019). Travel app users’ continued use intentions: It’s a matter of value and trust. Journal of Travel and Tourism Marketing, 36(1), 131–143. https://doi.org/10.1080/10548408.2018.1505580
   Web of Science ®Google Scholar
• Choi, K., Wang, Y., Sparks, B. A., & Choi, S. M. (2021). Privacy or security: Does it matter for continued use intention of travel applications? Cornell Hospitality Quarterly, 64, 267–282. https://doi.org/10.1177/19389655211066834
   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/10.1080/13683500.2019.1631266
   Web of Science ®Google Scholar
• Ciavolino, E., Aria, M., Cheah, J. H., & Roldán, J. L. (2022). A tale of PLS structural equation modelling: Episode I— A bibliometrix citation analysis. Social Indicators Research, 164(3), 1323–1348. https://doi.org/10.1007/s11205-022-02994-7
   Web of Science ®Google Scholar
• Claffey, E., & Brady, M. (2015). A model of consumer engagement in a virtual customer environment. Journal of Customer Behaviour, 13(4), 325–346. https://doi.org/10.1362/147539214X14185702584405
   Google Scholar
• Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd edition). Routledge.
   Google Scholar
• Coursaris, C. K., & Van Osch, W. (2016). A cognitive-affective model of perceived user satisfaction (CAMPUS): The complementary effects and interdependence of usability and aesthetics in IS design. Information and Management, 53(2), 252–264. https://doi.org/10.1016/j.im.2015.10.003
   Web of Science ®Google Scholar
• Crane, B., Albrecht, C., Duffin, K. M., & Albrecht, C. (2018). China’s special economic zones: An analysis of policy to reduce regional disparities. Regional Studies, Regional Science, 5(1), 98–107. https://doi.org/10.1080/21681376.2018.1430612
   Web of Science ®Google Scholar
• Dabbous, A., & Barakat, K. A. (2020). Bridging the online offline gap: Assessing the impact of brands’ social network content quality on brand awareness and purchase intention. Journal of Retailing and Consumer Services, 53, 101966. https://doi.org/10.1016/j.jretconser.2019.101966
   Web of Science ®Google Scholar
• Dacko, S. G. (2017). Enabling smart retail settings via mobile augmented reality shopping apps. Technological Forecasting and Social Change, 124, 243–256. https://doi.org/10.1016/j.techfore.2016.09.032
   Web of Science ®Google Scholar
• Dastjerdi, A. M., Kaplan, S., de Abreu e Silva, J., Nielsen, O. A., & & Pereira, F. C. (2019a). Participating in environmental loyalty program with a real-time multimodal travel app: User needs, environmental and privacy motivators. Transportation Research Part D: Transport and Environment, 67, 223–243. https://doi.org/10.1016/j.trd.2018.11.013
   Web of Science ®Google Scholar
• Dastjerdi, A. M., Kaplan, S., de Abreu e Silva, J., Nielsen, O. A., & & Pereira, F. C. (2019b). Use intention of mobility-management travel apps: The role of users goals, technophile attitude and community trust. Transportation Research Part A: Policy and Practice, 126, 114–135. https://doi.org/10.1016/j.tra.2019.06.001
   Web of Science ®Google Scholar
• Dewan, N., Hossain, M. B., Kim, G. G., Dunay, A., & Illés, C. B. (2022). Transportation mobile applications adoption behavior does affect overseas residents’ life satisfaction: Involvement as a moderator. Cogent Business and Management, 9(1), 1. https://doi.org/10.1080/23311975.2022.2096998
   Web of Science ®Google Scholar
• Dickinson, J. E., Hibbert, J. F., Filimonau, V., Cherrett, T., Davies, N., Norgate, S., Speed, C., & Winstanley, C. (2017). Implementing smartphone enabled collaborative travel: Routes to success in the tourism domain. Journal of Transport Geography, 59, 100–110. https://doi.org/10.1016/j.jtrangeo.2017.01.011
   Web of Science ®Google Scholar
• Ding, G., Guo, J., Pueppke, S. G., Ou, M., Ou, W., & Tao, Y. (2022). Has urban form become homogenizing? Evidence from cities in China. Ecological Indicators, 144, 109494. https://doi.org/10.1016/j.ecolind.2022.109494
   Web of Science ®Google Scholar
• Douglas, A. (2019). Mobile business travel application usage: Are South African men really from Mars and women from Venus? Journal of Hospitality and Tourism Technology, 10(3), 300–316. https://doi.org/10.1108/JHTT-01-2018-0002
   Web of Science ®Google Scholar
• Douglas, A., Lubbe, B., & van Rooyen, A. (2018). Business travellers’ use of mobile travel applications: A generational analysis. Information Technology and Tourism, 18(1–4), 113–132. https://doi.org/10.1007/s40558-017-0103-6
   Web of Science ®Google Scholar
• Fakfare, P., & Manosuthi, N. (2022). Examining the influential components of tourists’ intention to use travel apps: The importance–performance map analysis. Journal of Hospitality and Tourism Insights, 6, 1144–1168. https://doi.org/10.1108/JHTI-02-2022-0079
   Web of Science ®Google Scholar
• Fakfare, P., Promsivapallop, P., & Manosuthi, N. (2023). Applying integrated generalized structured component analysis to explore tourists' benefit consideration and choice confidence toward travel appscape. Technological Forecasting and Social Change, 188, 122321. http://doi.org/10.1016/j.techfore.2023.122321
   Web of Science ®Google Scholar
• Fakfare, P., Talawanich, S., & Wattanacharoensil, W. (2020). A scale development and validation on domestic tourists’ motivation: the case of second-tier tourism destinations. Asia Pacific Journal of Tourism Research, 25(5), 489–504. http://doi.org/10.1080/10941665.2020.1745855
   Web of Science ®Google Scholar
• Fang, J., Zhao, Z., Wen, C., & Wang, R. (2017). Design and performance attributes driving mobile travel application engagement. International Journal of Information Management, 37(4), 269–283. https://doi.org/10.1016/j.ijinfomgt.2017.03.003
   Web of Science ®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/10.3758/BRM.41.4.1149
   PubMed Web of Science ®Google Scholar
• Florida, R. (2017). The new urban crisis: How our cities are increasing inequality, deepening segregation, and failing the middle class-and what we can do about it. Basic Books.
   Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
   Web of Science ®Google Scholar
• Fu, Y., Liu, X., Wang, Y., & Chao, R. F. (2018). How experiential consumption moderates the effects of souvenir authenticity on behavioral intention through perceived value. Tourism Management, 69(January), 356–367. https://doi.org/10.1016/j.tourman.2018.06.023
   Google Scholar
• Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. https://doi.org/10.1016/j.jbusres.2015.12.008
   Web of Science ®Google Scholar
• Gao, Z., Cheah, J. H., Lim, X. J., Ng, S. I., Cham, T. H., & Yee, C. L. (2023). Can travel apps improve tourists’ intentions? Investigating the drivers of Chinese gen Y users’. Journal of Vacation Marketing, 30, 505–534. https://doi.org/10.1177/13567667231152938
   Web of Science ®Google Scholar
• Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American Statistical Association, 70(350), 320–328. https://doi.org/10.1080/01621459.1975.10479865
   Web of Science ®Google Scholar
• Gretzel, U., Koo, C., Sigala, M., & Xiang, Z. (2015). Special issue on smart tourism: Convergence of information technologies, experiences, and theories. Electronic Markets, 25(3), 175–177. https://doi.org/10.1007/s12525-015-0194-x
   Web of Science ®Google Scholar
• Gretzel, U., Zarezadeh, Z., Li, Y., & Xiang, Z. (2020). The evolution of travel information search research: A perspective article. Tourism Review, 75(1), 319–323. https://doi.org/10.1108/TR-06-2019-0279
   Web of Science ®Google Scholar
• Guo, X., Pesonen, J., & Komppula, R. (2021). Comparing online travel review platforms as destination image information agents. Information Technology and Tourism, 23(2), 159–187. https://doi.org/10.1007/s40558-021-00201-w
   Web of Science ®Google Scholar
• Gupta, A., & Dogra, N. (2017). Tourist adoption of mapping apps: A UTAUT2 perspective of smart travellers. Tourism and Hospitality Management, 23(2), 145–161. https://doi.org/10.20867/thm.23.2.6
   Google Scholar
• Gupta, A., Dogra, N., & George, B. (2018). What determines tourist adoption of smartphone apps? Journal of Hospitality and Tourism Technology, 9(1), 50–64. https://doi.org/10.1108/JHTT-02-2017-0013
   Web of Science ®Google Scholar
• Gupta, S., Pansari, A., & Kumar, V. (2018). Global customer engagement. Journal of International Marketing, 26(1), 4–29. https://doi.org/10.1509/jim.17.0091
   Web of Science ®Google Scholar
• Gursoy, D. (2019). A critical review of determinants of information search behavior and utilization of online reviews in decision making process (invited paper for ‘luminaries’ special issue of International Journal of Hospitality Management). International Journal of Hospitality Management, 76, 53–60. https://doi.org/10.1016/j.ijhm.2018.06.003
   Web of Science ®Google Scholar
• Hair, J. F., Hult, G. T. M., Ringle, C., Sarstedt, M., Danks, N., & Ray, S. (2023). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Structural Equation Modeling: A Multidisciplinary Journal, 30(1), 165–167. https://doi.org/10.1080/10705511.2022.2108813
   Web of Science ®Google Scholar
• 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. https://doi.org/10.1108/EBR-11-2018-0203
   Web of Science ®Google Scholar
• Hair, J. F., & Sarstedt, M. (2019). Factors versus composites: Guidelines for choosing the right structural equation modeling method. Project Management Journal, 50(6), 619–624. https://doi.org/10.1177/8756972819882132
   Web of Science ®Google Scholar
• Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced issues in partial least squares structural equation modeling (PLS-SEM). Thousand Oaks.
   Google Scholar
• Heine, K., Atwal, G., & He, J. (2019). Managing country-of-origin affiliations for luxury brand-building in China. Australasian Marketing Journal, 27(1), 14–23. https://doi.org/10.1016/j.ausmj.2018.09.001
   Web of Science ®Google Scholar
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
   Web of Science ®Google Scholar
• Ho, R. C., Amin, M., Ryu, K., & Ali, F. (2021). Integrative model for the adoption of tour itineraries from smart travel apps. Journal of Hospitality and Tourism Technology, 12(2), 372–388. https://doi.org/10.1108/JHTT-09-2019-0112
   Web of Science ®Google Scholar
• Hsu, C. L., & Lin, J. C. C. (2016). Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change, 108, 42–53. https://doi.org/10.1016/j.techfore.2016.04.012
   Web of Science ®Google Scholar
• Huang, Y., & Qian, L. (2018). Consumer preferences for electric vehicles in lower tier cities of China: Evidences from south Jiangsu region. Transportation Research Part D: Transport and Environment, 63, 482–497. https://doi.org/10.1016/j.trd.2018.06.017
   Web of Science ®Google Scholar
• Huang, Y., Qian, L., Tyfield, D., & Soopramanien, D. (2021). On the heterogeneity in consumer preferences for electric vehicles across generations and cities in China. Technological Forecasting and Social Change, 167, 120687. https://doi.org/10.1016/j.techfore.2021.120687
   Web of Science ®Google Scholar
• Huang, S. S., & Wei, X. (2018). Chinese outbound travel: Understanding the socioeconomic drivers. International Journal of Tourism Research, 20(1), 25–37. https://doi.org/10.1002/jtr.2150
   Web of Science ®Google Scholar
• Hung, N. T., Anh, L. H., Hien, D. T. T., & Hang, V. T. T. (2020). A studying on factors affecting decision to use smart tourism applications using extended TAM. WSEAS Transactions on Business and Economics, 17(May), 288–299. https://doi.org/10.37394/23207.2020.17.30
   Google Scholar
• Itani, O. S., Kassar, A. N., & Loureiro, S. M. C. (2019). Value get, value give: The relationships among perceived value, relationship quality, customer engagement, and value consciousness. International Journal of Hospitality Management, 80, 78–90. https://doi.org/10.1016/j.ijhm.2019.01.014
   Web of Science ®Google Scholar
• İlkan, Ş. P., Öztüren, A., Avcı, T., & Irani, F. (2023). Mobile application features effects on the application’s engagement and intention for continuing use in tourism. Asia Pacific Journal of Tourism Research, 28(4), 386–400. https://doi.org/10.1080/10941665.2023.2230328
   Web of Science ®Google Scholar
• Jahn, B., & Kunz, W. (2012). How to transform consumers into fans of your brand. Journal of Service Management, 23(3), 344–361. https://doi.org/10.1108/09564231211248444
   Web of Science ®Google Scholar
• Jang, S., Kitchen, P. J., & Kim, J. (2018). The effects of gamified customer benefits and characteristics on behavioral engagement and purchase: Evidence from mobile exercise application uses. Journal of Business Research, 92, 250–259. https://doi.org/10.1016/j.jbusres.2018.07.056
   Web of Science ®Google Scholar
• Jensen, Ø, Chen, J. S., & Korneliussen, T. (2015). Cultural-geographic influences of destination images: A case of Northern Norway. Advances in Hospitality and Leisure, 11, 3–19. https://doi.org/10.1108/S1745-354220150000011001
   Google Scholar
• 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
   Web of Science ®Google Scholar
• Julien, H., Pecoskie, J. J. L., & Reed, K. (2011). Trends in information behavior research, 1999–2008: A content analysis. Library & Information Science Research, 33(1), 19–24. https://doi.org/10.1016/J.LISR.2010.07.014
   Web of Science ®Google Scholar
• Jung, H., & Hwang, J. (2023). The information characteristics of YouTube tourism content and their impacts on user satisfaction and intention to visit and share information: The moderating role of word-of-mouth information acceptance. Asia Pacific Journal of Tourism Research, 28(2), 143–156. https://doi.org/10.1080/10941665.2023.2207692
   Web of Science ®Google Scholar
• Kang, J. W., & Namkung, Y. (2019). The role of personalization on continuance intention in food service mobile apps: A privacy calculus perspective. International Journal of Contemporary Hospitality Management, 31(2), 734–752. https://doi.org/10.1108/IJCHM-12-2017-0783
   Web of Science ®Google Scholar
• Kim, S. E., Lee, K. Y., Shin, S., & Yang, S. B. (2017). Effects of tourism information quality in social media on destination image formation: The case of Sina Weibo. Information and Management, 54(6), 687–702. https://doi.org/10.1016/j.im.2017.02.009
   Web of Science ®Google Scholar
• Klimczuk, A., & Klimczuk-Kochańska, M. (2015). Technology transfer. In M. Odekon (Ed.), The SAGE Encyclopedia of World Poverty (2nd ed (pp. 1529–1531). SAGE Publications.
   Google Scholar
• Klimczuk, A., & Klimczuk-Kochańska, M. (2019). Core-periphery model. In S. Romaniuk, M. Thapa, & P. Marton (Eds.), The Palgrave Encyclopaedia of Global Security Studies (pp. 1–8). Springer International Publishing. https://doi.org/10.1007/978-3-319-74336-3_320-1.
   Google Scholar
• Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546–580. https://doi.org/10.17705/1jais.00302
   Web of Science ®Google Scholar
• Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–499. https://doi.org/10.1086/261763
   Web of Science ®Google Scholar
• Krugman, P. (1998). What’s new about the new economic geography? Oxford Review of Economic Policy, 14(2), 7–17. https://doi.org/10.1093/oxrep/14.2.7
   Web of Science ®Google Scholar
• Krugman, P. (2011). The New Economic Geography, now middle-aged. Regional Studies, 45(1), 1–7. https://doi.org/10.1080/00343404.2011.537127
   Web of Science ®Google Scholar
• Kullada, P., & Kurniadjie, M. C. R. (2021). Examining the influence of digital information quality on tourists’ experience. Journal of Quality Assurance in Hospitality and Tourism, 22(2), 191–217. https://doi.org/10.1080/1528008X.2020.1769522
   Web of Science ®Google Scholar
• Kunming Government. (2021a). The cumulative disposable income per capita of all residents increased by 46.1%. https://www.km.gov.cn/c/2021-07-15/4002975.shtml
   Google Scholar
• Kunming Government. (2021b). The main data of the seventh national census of Kunming. https://www.km.gov.cn/c/2021-06-07/3968656.shtml
   Google Scholar
• Lai, I. K. W. (2015). Traveler acceptance of an app-based mobile tour guide. Journal of Hospitality and Tourism Research, 39(3), 401–432. https://doi.org/10.1177/1096348013491596
   Web of Science ®Google Scholar
• Ledikwe, A. (2021). Determinants of behavioural intention towards travel applications in an emerging African economy: A perspective on the hospitality industry. African Journal of Hospitality, Tourism and Leisure, 10(6), 1882–1895. https://doi.org/10.46222/AJHTL.19770720.198
   Google Scholar
• Lee, Z. W. Y., Chan, T. K. H., Chong, A. Y. L., & Thadani, D. R. (2019). Customer engagement through omnichannel retailing: The effects of channel integration quality. Industrial Marketing Management, 77, 90–101. https://doi.org/10.1016/j.indmarman.2018.12.004
   Web of Science ®Google Scholar
• Li, R., Luo, Z., Bilgihan, A., & Okumus, F. (2021). Marketing China to U.S. travelers through electronic word-of-mouth and destination image: Taking Beijing as an example. Journal of Vacation Marketing, 27, 267–286. https://doi.org/10.1177/1356766720987869
   Web of Science ®Google Scholar
• Lim, X. J., Cheah, J. H., Morrison, A. M., Ng, S. I., & Wang, S. (2022). Travel app shopping on smartphones: Understanding the success factors influencing in-app travel purchase intentions. Tourism Review, 77(4), 1166–1185. https://doi.org/10.1108/TR-11-2021-0497
   Web of Science ®Google Scholar
• Lim, X. J., Cheah, J. H., Ng, S. I., Basha, N. K., & Liu, Y. (2021). Are men from Mars, women from Venus? Examining gender differences towards continuous use intention of branded apps Journal of Retailing and Consumer Services, 60, 102422. https://doi.org/10.1016/j.jretconser.2020.102422
   Web of Science ®Google Scholar
• Lin, S. Y., Juan, P. J., & Lin, S. W. (2020). A tam framework to evaluate the effect of smartphone application on tourism information search behavior of foreign independent travelers. Sustainability, 12(22), 9366. https://doi.org/10.3390/su12229366
   Web of Science ®Google Scholar
• Lin, F., & Ryu, K. (2023). How product design affects repurchase intention, eWOM, and museum visit intention: Museum mystery boxes in China. Journal of Travel & Tourism Marketing, 40(5), 434–451. https://doi.org/10.1080/10548408.2023.2258154
   Web of Science ®Google Scholar
• Liu, Y., Li, Q., Edu, T., & Negricea, I. C. (2023). Exploring the continuance usage intention of travel applications in the case of Chinese tourists. Journal of Hospitality and Tourism Research, 47(1), 6–32. https://doi.org/10.1177/1096348020962553
   Google Scholar
• Lu, J., Mao, Z., Wang, M., & Hu, L. (2015). Goodbye maps, hello apps? Exploring the influential determinants of travel app adoption Current Issues in Tourism, 18(11), 1059–1079. https://doi.org/10.1080/13683500.2015.1043248
   Web of Science ®Google Scholar
• Lv, X., Zhang, R., Su, Y., & Yang, Y. (2022). Exploring how live streaming affects immediate buying behavior and continuous watching intention: A multigroup analysis. Journal of Travel & Tourism Marketing, 39(1), 109–135. https://doi.org/10.1080/10548408.2022.2052227
   Web of Science ®Google Scholar
• Marafa, L. M., Chan, C. S., & Li, K. (2022). Market potential and obstacles for film-induced tourism development in Yunnan province in China. Journal of China Tourism Research, 18(2), 245–267. https://doi.org/10.1080/19388160.2020.1819498
   Web of Science ®Google Scholar
• Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.
   Google Scholar
• Mitra, S. K., Chattopadhyay, M., & Ali, S. (2022). Transforming tourism into a successful intervention strategy to decrease income inequality. Asia Pacific Journal of Tourism Research, 27(11), 1167–1178. https://doi.org/10.1080/10941665.2023.2166421
   Web of Science ®Google Scholar
• Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ, 339(7716), 332–336. https://doi.org/10.1136/BMJ.B2535
   Google Scholar
• Moon, M. A., Javaid, B., Kiran, M., Awan, H. M., & Farooq, A. (2018). Consumer perceptions of counterfeit clothing and apparel products attributes. Marketing Intelligence and Planning, 36(7), 794–808. https://doi.org/10.1108/MIP-11-2017-0272
   Web of Science ®Google Scholar
• Morosan, C. (2021). An affective approach to modelling intentions to use technologies for social distancing in hotels. Information Technology and Tourism, 23(4), 549–573. https://doi.org/10.1007/s40558-021-00216-3
   Web of Science ®Google Scholar
• National Bureau of Statistics. (2021). Communiqué of the Seventh National Population Census. http://www.stats.gov.cn/english/PressRelease/202105/t20210510_1817188.html
   Google Scholar
• National Bureau of Statistics of China. (2016). China statistical yearbook: 2016. http://www.stats.gov.cn/tjsj/ndsj/2016/indexeh.htm
   Google Scholar
• Oriade, A., & Schofield, P. (2019). An examination of the role of service quality and perceived value in visitor attraction experience. Journal of Destination Marketing and Management, 11, 1–9. https://doi.org/10.1016/j.jdmm.2018.10.002
   Web of Science ®Google Scholar
• Pandža Bajs, I. (2015). Tourist perceived value, relationship to satisfaction, and behavioral intentions: The example of the Croatian tourist destination Dubrovnik. Journal of Travel Research, 54(1), 122–134. https://doi.org/10.1177/0047287513513158
   Web of Science ®Google Scholar
• Pansari, A., & Kumar, V. (2017). Customer engagement: The construct, antecedents, and consequences. Journal of the Academy of Marketing Science, 45(3), 294–311. https://doi.org/10.1007/s11747-016-0485-6
   Web of Science ®Google Scholar
• Petticrew, M., & Roberts, H. (2006). Systematic Reviews in the Social Sciences: A Practical Guide. Blackwell Publishing.
   Google Scholar
• Piccoli, G., Lui, T. W., & Grün, B. (2017). The impact of IT-enabled customer service systems on service personalization, customer service perceptions, and hotel performance. Tourism Management, 59, 349–362. https://doi.org/10.1016/j.tourman.2016.08.015
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
   PubMed Web of Science ®Google Scholar
• Rather, R. A. (2020). Customer experience and engagement in tourism destinations: The experiential marketing perspective. Journal of Travel and Tourism Marketing, 37(1), 15–32. https://doi.org/10.1080/10548408.2019.1686101
   Web of Science ®Google Scholar
• Rauschnabel, P. A., He, J., & Ro, Y. K. (2018). Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research, 92, 374–384. https://doi.org/10.1016/j.jbusres.2018.08.008
   Web of Science ®Google Scholar
• Reis, J., Melão, N., Salvadorinho, J., Soares, B., & Rosete, A. (2020). Service robots in the hospitality industry: The case of Henn-na hotel, Japan. Technology in Society, 63, 101423. https://doi.org/10.1016/j.techsoc.2020.101423
   Web of Science ®Google Scholar
• Rianto, M. R., Sari, R. K., Sulistyowati, A., Handayani, M., & Woestho, C. (2020). Indonesian demographic bonus: Determinants of intention to use the cellular applications of tourism in Indonesia’s millennial generation. African Journal of Hospitality, Tourism and Leisure, 9(2), 1–13.
   Google Scholar
• Ringle, C. M., Wende, S., & Becker, J.-M. (2023). SmartPLS 4. Boenningstedt: SmartPLS. https://www.smartpls.com
   Google Scholar
• Sarstedt, M., & Cheah, J. H. (2019). Partial least squares structural equation modeling using SmartPLS: A software review. Journal of Marketing Analytics, 7(3), 196–202. https://doi.org/10.1057/s41270-019-00058-3
   Google Scholar
• Saunders, M., Lewis, P., & Thornhill, A. (2015). Research methods for business students (7th ed.). Pearson Education.
   Google Scholar
• Schiffman, L. G., & Wisenblit, J. (2019). Consumer behavior (12th ed.). Pearson Education.
   Google Scholar
• Seck, A. M., & Philippe, J. (2013). Service encounter in multi-channel distribution context: Virtual and face-to-face interactions and consumer satisfaction. Service Industries Journal, 33(6), 565–579. https://doi.org/10.1080/02642069.2011.622370
   Web of Science ®Google Scholar
• Sharma, M., Antony, R., Sehrawat, R., Contreras, A., & Daim, T. U. (2022). Technology in Society Exploring post-adoption behaviors of e-service users : Evidence from the hospitality sector / online travel services. Technology in Society, 68, 101781. https://doi.org/10.1016/j.techsoc.2021.101781
   Web of Science ®Google Scholar
• Shin, H. H., Jeong, M., & Cho, M. H. (2021). The impact of smart tourism technology and domestic travelers’ technology readiness on their satisfaction and behavioral intention: A cross-country comparison. International Journal of Tourism Research, 23(5), 726–742. https://doi.org/10.1002/jtr.2437
   Web of Science ®Google Scholar
• Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552–4564. https://doi.org/10.1016/j.jbusres.2016.03.049
   Web of Science ®Google Scholar
• Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189
   Web of Science ®Google Scholar
• Shukla, P., & Rosendo-Rios, V. (2021). Intra and inter-country comparative effects of symbolic motivations on luxury purchase intentions in emerging markets. International Business Review, 30(1), 101768. https://doi.org/10.1016/j.ibusrev.2020.101768
   Web of Science ®Google Scholar
• Singh, N., Yu, J., Ramkissoon, H., Amponsah, M., & Han, H. (2023). Nature-based solution for state park travelers’ self-rated mental health, emotional well-being, and life satisfaction: Impact of national culture. Journal of Travel & Tourism Marketing, 40(1), 55–74. https://doi.org/10.1080/10548408.2023.2215251
   Web of Science ®Google Scholar
• The Star. (2017). Single travel app with many handy features. https://www.thestar.com.my/lifestyle/travel/2017/09/16/traveloka-travel-app
   Google Scholar
• Starmass. (2022). China Tiered Cities. http://www.starmass.com/china-tiered-cities/
   Google Scholar
• The State Council. (2014). China to apply new city classification standards. http://english.gov.cn/policies/latest_releases/2014/11/25/content_281475015213546.htm
   Google Scholar
• Statista. (2021a). China: Per capita disposable income in urban areas by region. https://www.statista.com/statistics/278856/china-per-capita-annual-income-in-urban-areas-by-region/
   Google Scholar
• Statista. (2021b). Most popular travel apps among young travllers in China. https://www.statista.com/statistics/441307/china-most-popular-travel-apps-among-young-luxury-travelers/
   Google Scholar
• Statista. (2021c). Retention rate of travel apps worldwide. https://www-statista-com.ezproxy.gavilan.edu/statistics/1230130/retention-rate-travel-apps-globally/
   Google Scholar
• Statista. (2022a). App downloads in travel segment worldwide. https://www-statista-com.ezproxy.gavilan.edu/outlook/dmo/app/travel/worldwide#downloads
   Google Scholar
• Statista. (2022b). China: GDP of provincial capital cities 2021. https://www.statista.com/statistics/1099570/china-gross-domestic-product-gdp-of-provincial-capital-cities/
   Google Scholar
• Statista. (2022c). China: Per capita disposable income of urban households 2021. https://www.statista.com/statistics/278698/annual-per-capita-income-of-households-in-china/
   Google Scholar
• Statista. (2022d). Most popular business travel booking channels in China in 2022. https://www-statista-com.ezproxy.gavilan.edu/statistics/785469/china-sme-business-travel-booking-channels/
   Google Scholar
• Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111–133. https://doi.org/10.1111/j.2517-6161.1974.tb00994.x
   Web of Science ®Google Scholar
• Sun, P., Cárdenas, D. A., & Harrill, R. (2016). Chinese customers’ evaluation of travel website quality: A decision-tree analysis. Journal of Hospitality Marketing and Management, 25(4), 476–497. https://doi.org/10.1080/19368623.2015.1037977
   Web of Science ®Google Scholar
• Tak, P., & Gupta, M. (2021). Examining travel mobile app attributes and its impact on consumer engagement: An application of S-O-R framework. Journal of Internet Commerce, 20(3), 293–318. https://doi.org/10.1080/15332861.2021.1891517
   Web of Science ®Google Scholar
• Tseng, L. Y., Chang, J. H., & Zhu, Y. L. (2021). What drives the travel switching behavior of Chinese Generation Z consumers. Journal of Tourism Futures, 10, 131–146. https://doi.org/10.1108/JTF-07-2020-0110
   Google Scholar
• Turulja, L., & Činjarević, M. (2021). How customer-driven and vendor-driven information cues shape a travel app user behaviour? Journal of Hospitality and Tourism Technology, 12(4), 745–761. https://doi.org/10.1108/JHTT-02-2020-0044
   Web of Science ®Google Scholar
• Vahdat, A., Alizadeh, A., Quach, S., & Hamelin, N. (2021). Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention Australasian Marketing Journal, 29(2), 187–197. https://doi.org/10.1016/j.ausmj.2020.01.002
   Web of Science ®Google Scholar
• Vinod, B. (2020). The age of intelligent retailing: Personalized offers in travel for a segment of ONE. Journal of Revenue and Pricing Management, 20, 473–479. https://doi.org/10.1057/s41272-020-00265-z
   Web of Science ®Google Scholar
• Wu, S., Ma, E., Wang, J., & Li, D. (2022). Experience with travel mobile apps and travel intentions—The case of university students in China. Sustainability, 14(19), 12603. https://doi.org/10.3390/su141912603
   Web of Science ®Google Scholar
• Wu, S., Wong, I. K. A., & Lin, Z. (2021). Understanding the role of atmospheric cues of travel apps: A synthesis between media richness and stimulus–organism–response theory. Journal of Hospitality and Tourism Management, 49, 226–234. https://doi.org/10.1016/j.jhtm.2021.09.014
   Web of Science ®Google Scholar
• Xiong, Z., Luo, L., & Lu, X. (2023). Understanding the effect of smart tourism technologies on behavioral intention with the stimulus-organism-response model: A study in Guilin, China. Asia Pacific Journal of Tourism Research, 28(5), 449–466. https://doi.org/10.1080/10941665.2023.2246598
   Web of Science ®Google Scholar
• Yicai. (2022). Ranking of Cities 2022. https://www.yicai.com/news/101430366.html
   Google Scholar
• Yin, J., Qu, X., & Ni, Y. (2023). The power of culture: How it shapes tourists’ online engagement with destinations. Journal of Travel & Tourism Marketing, 40(3), 242–259. https://doi.org/10.1080/10548408.2023.2239854
   Web of Science ®Google Scholar
• Zeljković, M. (2022). Urban-rural disparities in travel during the COVID-19 pandemic: The case study of Serbia. Erdkunde, 76(2), 111–125. https://doi.org/10.3112/erdkunde.2022.02.04
   Web of Science ®Google Scholar
• Zhang, S. N., Li, Y. Q., Liu, C. H., & Ruan, W. Q. (2019). Critical factors in the identification of word-of-mouth enhanced with travel apps: The moderating roles of Confucian culture and the switching cost view. Asia Pacific Journal of Tourism Research, 24(5), 422–442. https://doi.org/10.1080/10941665.2019.1572630
   Web of Science ®Google Scholar
• Zhang, S., Li, F., & Xiao, J. J. (2020). Internet penetration and consumption inequality in China. International Journal of Consumer Studies, 44(5), 407–422. https://doi.org/10.1111/ijcs.12575
   Web of Science ®Google Scholar
• Zhao, S., & Liu, Y. (2023). Revenge tourism after the lockdown: Based on the SOR framework and extended TPB model. Journal of Travel & Tourism Marketing, 40(5), 416–433. https://doi.org/10.1080/10548408.2023.2256777
   Web of Science ®Google Scholar
• Zhao, P., & Wan, J. (2021). Land use and travel burden of residents in urban fringe and rural areas: An evaluation of urban-rural integration initiatives in Beijing. Land Use Policy, 103, 105309. https://doi.org/10.1016/j.landusepol.2021.105309
   Web of Science ®Google Scholar
• Zheng, D., Huang, C., & Oraltay, B. (2023). Digital cultural tourism: Progress and a proposed framework for future research. Asia Pacific Journal of Tourism Research, 28(3), 234–253. https://doi.org/10.1080/10941665.2023.2217958
   Web of Science ®Google Scholar
• Zhou, T., Song, Y., & Zhou, P. (2022). Continued use intention of travel apps: From the perspective of control and motivation. Technology Analysis and Strategic Management, 34(6), 703–716. https://doi.org/10.1080/09537325.2021.1916457
   Web of Science ®Google Scholar