How do online travel reviews facilitate informed purchase decisions?

References

• Adamış, E., & Pınarbaşı, F. (2022). Unfolding visual characteristics of social media communication: Reflections of smart tourism destinations. Journal of Hospitality and Tourism Technology, 13(1), 34–61. https://doi.org/10.1108/JHTT-09-2020-0246
   Web of Science ®Google Scholar
• Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Amaro, S., & Duarte, P. (2015). An integrative model of consumers’ intentions to purchase travel online. Tourism Management, 46, 64–79. https://doi.org/10.1016/j.tourman.2014.06.006
   Web of Science ®Google Scholar
• Andoy, A. D. G., Beriña, J. A. C., Querubin, J. E. S., & Grimaldo, J. R. (2022). The effects of online reviews on purchase intention in the Shopee fashion industry. Journal of Business and Management Studies, 4(2), 150–162. https://doi.org/10.32996/jefas.2022.4.2.12
   Google Scholar
• Artursson, E. (2015). Online Ratings–who decides what games you buy [Doctoral dissertation. Master Thesis in Economics]. Lunds Universitet.
   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/10.1080/19368623.2019.1653807
   Web of Science ®Google Scholar
• Baka, V. (2016). The becoming of user-generated reviews: Looking at the past to understand the future of managing reputation in the travel sector. Tourism Management, 53, 148–162. https://doi.org/10.1016/j.tourman.2015.09.004
   Web of Science ®Google Scholar
• Baker, M. A., & Kim, K. (2019). Value destruction in exaggerated online reviews: The effects of emotion, language, and trustworthiness. International Journal of Contemporary Hospitality Management, 31(4), 1956–1976. https://doi.org/10.1108/IJCHM-03-2018-0247
   Web of Science ®Google Scholar
• Book, L. A., & Tanford, S. (2020). Measuring social influence from online traveler reviews. Journal of Hospitality and Tourism Insights, 3(1), 54–72. https://doi.org/10.1108/JHTI-06-2019-0080
   Web of Science ®Google Scholar
• Branstad, A., & Solem, B. A. (2020). Emerging theories of consumer-driven market innovation, adoption, and diffusion: A selective review of consumer-oriented studies. Journal of Business Research, 116, 561–571. https://doi.org/10.1016/j.jbusres.2020.01.028
   Web of Science ®Google Scholar
• Brinol, P., & Petty, R. E. (2009). Persuasion: Insights from the self-validation hypothesis. In M. P. Zanna (Ed.), Advances in experimental social psychology, (Vol. 41, pp. 69–118). Academic Press.
   Google Scholar
• Chatterjee, S. (2020). Drivers of helpfulness of online hotel reviews: A sentiment and emotion mining approach. International Journal of Hospitality Management, 85, Article 102356. https://doi.org/10.1016/j.ijhm.2019.102356
   Web of Science ®Google Scholar
• Chetioui, Y., Lebdaoui, H., & Chetioui, H. (2021). Factors influencing consumer attitudes toward online shopping: The mediating effect of trust. EuroMed Journal of Business, 16(4), 544–563. https://doi.org/10.1108/EMJB-05-2020-0046
   Web of Science ®Google Scholar
• Cheung, C. M., Lee, M. K., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247. https://doi.org/10.1108/10662240810883290
   Web of Science ®Google Scholar
• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 1295–1336). Lawrence Erlbaum Associates.
   Google Scholar
• Cho, J. (2004). Likelihood to abort an online transaction: Influences from cognitive evaluations, attitudes, and behavioral variables. Information & Management, 41(7), 827–838. https://doi.org/10.1016/j.im.2003.08.013
   Web of Science ®Google Scholar
• Colistra, R., Buchman, E., & Duvall, K. (2017). User-generated content and television news stations. Electronic News, 11(3), 123–144. https://doi.org/10.1177/1931243116672261
   Google Scholar
• Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58(6), 737–758. https://doi.org/10.1016/S1071-5819(03)00041-7
   Web of Science ®Google Scholar
• Coves-Martínez, A. L., Sabiote-Ortiz, C. M., & Frías-Jamilena, D. M. (2021). Cultural intelligence as an antecedent of satisfaction with the travel app and with the tourism experience. Computers in Human Behavior, 127, Article 107049. https://doi.org/10.1016/j.chb.2021.107049
   Web of Science ®Google Scholar
• Cui, F., Lin, D., & Qu, H. (2018). The impact of perceived security and consumer innovativeness on e-loyalty in online travel shopping. Journal of Travel & Tourism Marketing, 35(6), 819–834. https://doi.org/10.1080/10548408.2017.1422452
   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/10.2307/249008
   Web of Science ®Google Scholar
• DeVellis, R. F. (2012). Scale development: Theory and applications (3rd ed.). Sage Publications.
   Google Scholar
• Dickinger, A. (2011). The trustworthiness of online channels for experience- and goal-directed search tasks. Journal of Travel Research, 50(4), 378–391. https://doi.org/10.1177/0047287510371694
   Web of Science ®Google Scholar
• Dou, X., Walden, J. A., Lee, S., & Lee, J. Y. (2012). Does source matter? Examining source effects in online product reviews. Computers in Human Behavior, 28(5), 1555–1563. https://doi.org/10.1016/j.chb.2012.03.015
   Web of Science ®Google Scholar
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley.
   Google Scholar
• Flanagin, A. J., & Metzger, M. J. (2013). Trusting expert- versus user-generated ratings online: The role of information volume, valence, and consumer characteristics. Computers in Human Behavior, 29(4), 1626–1634. https://doi.org/10.1016/j.chb.2013.02.001
   Web of Science ®Google Scholar
• Gensler, S., Völckner, F., Egger, M., Fischbach, K., & Schoder, D. (2016). Listen to your customers: Insights into brand image using online consumer-generated product reviews. International Journal of Electronic Commerce, 20(1), 112–141. https://doi.org/10.1080/10864415.2016.1061792
   Web of Science ®Google Scholar
• Ghose, A., & Ipeirotis, P. G. (2011). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512. https://doi.org/10.1109/TKDE.2010.188
   Web of Science ®Google Scholar
• Goes, P. B., Lin, M., & Yeung, C.-M. A. (2014). “Popularity effect” in user-generated content: Evidence from online product reviews. Information Systems Research, 25(2), 222–238. https://doi.org/10.1287/isre.2013.0512
   Web of Science ®Google Scholar
• Gunasekar, S., & Sudhakar, S. (2019). How user-generated judgments of hotel attributes indicate guest satisfaction. Journal of Global Scholars of Marketing Science, 29(2), 180–195. https://doi.org/10.1080/21639159.2019.1577155
   Web of Science ®Google Scholar
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson.
   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
• Halliday, S. V. (2016). User-generated content about brands: Understanding its creators and consumers. Journal of Business Research, 69(1), 137–144. https://doi.org/10.1016/j.jbusres.2015.07.027
   Web of Science ®Google Scholar
• Hansen, T. (2005). Consumer adoption of online grocery buying: A discriminant analysis. International Journal of Retail & Distribution Management, 33(2), 101–121. https://doi.org/10.1108/09590550510581449
   Google Scholar
• Hazari, S., Bergiel, B., & Sethna, B. (2016). Hedonic and utilitarian use of user-generated content on online shopping websites. Journal of Marketing Communications, 23(6), 572–591. https://doi.org/10.1080/13527266.2016.1143383
   Google Scholar
• Heung, V. C. (2003). Internet usage by international travellers: Reasons and barriers. International Journal of Contemporary Hospitality Management, 15(7), 370–378. https://doi.org/10.1108/09596110310496015
   Google Scholar
• Hou, Z., Cui, F., Meng, Y., Lian, T., & Yu, C. (2019). Opinion mining from online travel reviews: A comparative analysis of Chinese major OTAs using semantic association analysis. Tourism Management, 74, 276–289. https://doi.org/10.1016/j.tourman.2019.03.009
   Web of Science ®Google Scholar
• Huang, N., Burtch, G., Gu, B., Hong, Y., Liang, C., Wang, K., Fu, D., & Yang, B. (2019). Motivating user-generated content with performance feedback: Evidence from randomized field experiments. Management Science, 65(1), 327–345. https://doi.org/10.1287/mnsc.2017.2944
   Web of Science ®Google Scholar
• Huang, Z., & Mou, J. (2021). Gender differences in user perception of usability and performance of online travel agency websites. Technology in Society, 66, Article 101671. https://doi.org/10.1016/j.techsoc.2021.101671
   Web of Science ®Google Scholar
• Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G., Tatsuta, R., & Mieno, H. (1993). The max-min Delphi method and fuzzy Delphi method via fuzzy integration. Fuzzy Sets and Systems, 55(3), 241–253. https://doi.org/10.1016/0165-0114(93)90251-C
   Web of Science ®Google Scholar
• Jensen, J. M. (2009). Travellers’ intentions to purchase travel products online: The role of shopping orientation. In A. Matias, P. Nijkamp, & M. Sarmento (Eds.), Advances in tourism economics: New developments (pp. 203–215). Physica Verlag.
   Google Scholar
• Jiang, Y., Wang, X., & Yuen, K. F. (2021). Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation. Journal of Retailing and Consumer Services, 63, Article 102720. https://doi.org/10.1016/j.jretconser.2021.102720
   Web of Science ®Google Scholar
• Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
   Web of Science ®Google Scholar
• Kardes, F. R., Posavac, S. S., Cronley, M. L., & Herr, P. (2008). Consumer inference. In C. P. Haugtvedt, P. M. Herr, & F. R. Kardes (Eds.), Handbook of Consumer Psychology (pp. 165–191). LEA/Psychology Press.
   Google Scholar
• Khwaja, M. G., Mahmood, S., & Zaman, U. (2020). Examining the effects of eWOM, trust inclination, and information adoption on purchase intentions in an accelerated digital marketing context. Information, 11(10), 478. https://doi.org/10.3390/info11100478
   Web of Science ®Google Scholar
• Kim, L. H., Qu, H., & Kim, D. J. (2009). A study of perceived risk and risk reduction of purchasing air-tickets online. Journal of Travel & Tourism Marketing, 26(3), 203–224. https://doi.org/10.1080/10548400902925031
   Web of Science ®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/10.1016/j.tourman.2010.01.011
   Web of Science ®Google Scholar
• Kollmuss, A., & Agyeman, J. (2002). Mind the gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research, 8(3), 239–260. https://doi.org/10.1080/13504620220145401
   Google Scholar
• Lee, H. Y., Qu, H., & Kim, Y. S. (2007). A study of the impact of personal innovativeness on online travel shopping behavior – A case study of Korean travelers. Tourism Management, 28(3), 886–897. https://doi.org/10.1016/j.tourman.2006.04.013
   Web of Science ®Google Scholar
• Li, K., Chen, Y., & Zhang, L. (2020). Exploring the influence of online reviews and motivating factors on sales: A meta-analytic study and the moderating role of product category. Journal of Retailing and Consumer Services, 55, 102107. https://doi.org/10.1016/j.jretconser.2020.102107
   Web of Science ®Google Scholar
• Li, L., & Buhalis, D. (2006). E-Commerce in China: The case of travel. International Journal of Information Management, 26(2), 153–166. https://doi.org/10.1016/j.ijinfomgt.2005.11.007
   Web of Science ®Google Scholar
• Li, X., Wu, C., & Mai, F. (2019). The effect of online reviews on product sales: A joint sentiment-topic analysis. Information & Management, 56(2), 172–184. https://doi.org/10.1016/j.im.2018.04.007
   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
• Limayem, M., Khalifa, M., & Frini, A. (2000). What makes consumers buy from internet? A longitudinal study of online shopping. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 30(4), 421–432. https://doi.org/10.1109/3468.852436
   Web of Science ®Google Scholar
• Lin, P. J., Jones, E., & Westwood, S. (2009). Perceived risk and risk-relievers in online travel purchase intentions. Journal of Hospitality Marketing & Management, 18(8), 782–810. https://doi.org/10.1080/19368620903235803
   Google Scholar
• Ling, H. C., Chen, H. R., Ho, K. K., & Hsiao, K. L. (2021). Exploring the factors affecting customers’ intention to purchase a smart speaker. Journal of Retailing and Consumer Services, 59, 102331. https://doi.org/10.1016/j.jretconser.2020.102331
   Web of Science ®Google Scholar
• McClure, C., & Seock, Y.-K. (2020). The role of involvement: Investigating the effect of brand’s social media pages on consumer purchase intention. Journal of Retailing and Consumer Services, 53, Article 101975. https://doi.org/10.1016/j.jretconser.2019.101975
   Web of Science ®Google Scholar
• Mehraliyev, F., Choi, Y., & King, B. (2021). Expert online review platforms: Interactions between specialization, experience, and user power. Journal of Travel Research, 60(2), 384–400. https://doi.org/10.1177/0047287520901595
   Web of Science ®Google Scholar
• Min, S., So, K. K. F., & Jeong, M. (2019). Consumer adoption of the uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. Journal of Travel & Tourism Marketing, 36(7), 770–783. https://doi.org/10.1080/10548408.2018.1507866
   Web of Science ®Google Scholar
• Mishra, A., & Satish, S. M. (2016). eWOM: Extant research review and future research avenues. Vikalpa: The Journal for Decision Makers, 41(3), 222–233. https://doi.org/10.1177/0256090916650952
   Google Scholar
• Moe, W. (2009). How much does a good product rating help a Bad product? Modeling the role of product quality in the relationship between online consumer ratings and sales, working paper. University Of Maryland College Park.
   Google Scholar
• Mou, J., Shin, D. H., & Cohen, J. (2017). Understanding trust and perceived usefulness in the consumer acceptance of an e-service: A longitudinal investigation. Behaviour & Information Technology, 36(2), 125–139. https://doi.org/10.1080/0144929X.2016.1203024
   Web of Science ®Google Scholar
• Nowacki, M., & Niezgoda, A. (2020). Identifying unique features of the image of selected cities based on reviews by TripAdvisor portal users. Scandinavian Journal of Hospitality and Tourism, 20(5), 503–519. https://doi.org/10.1080/15022250.2020.1833362
   Web of Science ®Google Scholar
• Oheix, J. (2018). Detecting bad customer reviews with NLP: Sentiment analysis and text classification with Python. https://towardsdatascience.com/detecting-bad-customer-reviews-with-nlp-d8b36134dc7e/.
   Google Scholar
• Papathanassis, A., & Knolle, F. (2011). Exploring the adoption and processing of online holiday reviews: A grounded theory approach. Tourism Management, 32(2), 215–224. https://doi.org/10.1016/j.tourman.2009.12.005
   Web of Science ®Google Scholar
• Park, C., & Lee, T. M. (2009). Antecedents of online reviews’ usage and purchase influence: An empirical comparison of U.S. And Korean consumers. Journal of Interactive Marketing, 23(4), 332–340. https://doi.org/10.1016/j.intmar.2009.07.001
   Web of Science ®Google Scholar
• Park, S., Chung, S. A., & Lee, S. (2019). The effects of online product reviews on sales performance: Focusing on number, extremity, and length. Journal of Distribution Science, 17(5), 85–94. https://doi.org/10.15722/jds.17.5.201905.85
   Google Scholar
• Phillips, P., Barnes, S., Zigan, K., & Schegg, R. (2017). Understanding the impact of online reviews on hotel performance. Journal of Travel Research, 56(2), 235–249. https://doi.org/10.1177/0047287516636481
   Web of Science ®Google Scholar
• Ray, A., Bala, P. K., & Rana, N. P. (2021). Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach. Journal of Business Research, 128, 235–249. https://doi.org/10.1177/0047287516636481
   Web of Science ®Google Scholar
• Ringle, C. M., Wende, S., & Will, S. (2005). SmartPLS 2.0 (M3) (version beta). [Software]. Hamburg. http://www.smartpls.de
   Google Scholar
• Rogers, E. M. (1995). Diffusion of innovations (4th ed.). The Free Press.
   Google Scholar
• Rogers, E. M., & Shoemaker, F. F. (1971). Communication of innovations: A cross-cultural approach. The Free Press.
   Google Scholar
• Roma, P., & Aloini, D. (2019). How does brand-related user-generated content differ across social media? Evidence reloaded. Journal of Business Research, 96, 322–339. https://doi.org/10.1016/j.jbusres.2018.11.055
   Web of Science ®Google Scholar
• Roy, G., Datta, B., & Mukherjee, S. (2019). Role of electronic word-of-mouth content and valence in influencing online purchase behavior. Journal of Marketing Communications, 25(6), 661–684. https://doi.org/10.1080/13527266.2018.1497681
   Google Scholar
• Ruiz-Mafe, C., Bigné-Alcañiz, E., & Currás-Pérez, R. (2020). The effect of emotions, eWOM quality and online review sequence on consumer intention to follow advice obtained from digital services. Journal of Service Management, 31(3), 465–487. https://doi.org/10.1108/JOSM-11-2018-0349
   Web of Science ®Google Scholar
• San Martín, H., & Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341–350. https://doi.org/10.1016/j.tourman.2011.04.003
   Web of Science ®Google Scholar
• Saparudin, M., Rahayu, A., Hurriyati, R., & Sultan, M. (2020). The influence of trust, perceived usefulness, and perceived ease upon customers’ attitude and intention toward the use of mobile banking in Jakarta. Journal of Theoretical and Applied Information Technology, 98(17), 3584–3594.
   Google Scholar
• Saumya, S., & Singh, J. P. (2022). Spam review detection using LSTM autoencoder: An unsupervised approach. Electronic Commerce Research, 22(1), 113–133. https://doi.org/10.1007/s10660-020-09413-4
   Web of Science ®Google Scholar
• Sethna, B. N., Hazari, S., & Bergiel, B. (2017). Influence of user generated content in online shopping: Impact of gender on purchase behaviour, trust, and intention to purchase. International Journal of Electronic Marketing and Retailing, 8(4), 344–371. https://doi.org/10.1504/IJEMR.2017.087719
   Google Scholar
• Sharma, S., Singh, G., & Pratt, S. (2020). Does consumers’ intention to purchase travel online differ across generations? Empirical evidence from Australia. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.2751
   Google Scholar
• Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102–113. https://doi.org/10.1016/j.intmar.2012.01.002
   Web of Science ®Google Scholar
• Sparks, B. A., & Browning, V. (2011). The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, 32(6), 1310–1323. https://doi.org/10.1016/j.tourman.2010.12.011
   Web of Science ®Google Scholar
• Sparks, B. A., So, K. K. F., & Bradley, G. L. (2016). Responding to negative online reviews: The effects of hotel responses on customer inferences of trust and concern. Tourism Management, 53, 74–85. https://doi.org/10.1016/j.tourman.2015.09.011
   Web of Science ®Google Scholar
• Sun, Q., Niu, J., Yao, Z., & Yan, H. (2019). Exploring eWOM in online customer reviews: sentiment analysis at a fine-grained level. Engineering Applications of Artificial Intelligence, 81, 68–78. https://doi.org/10.1016/j.engappai.2019.02.004
   Web of Science ®Google Scholar
• Tang, T., Fang, E., & Wang, F. (2014). Is neutral really neutral? The effects of neutral user-generated content on product sales. Journal of Marketing, 78(4), 41–58. https://doi.org/10.1509/jm.13.0301
   Web of Science ®Google Scholar
• Tao, S., & Kim, H. S. (2019). Cruising in Asia: What can we dig from online cruiser reviews to understand their experience and satisfaction. Asia Pacific Journal of Tourism Research, 24(6), 514–528. https://doi.org/10.1080/10941665.2019.1591473
   Web of Science ®Google Scholar
• Terho, H., Mero, J., Siutla, L., & Jaakkola, E. (2022). Digital content marketing in business markets: Activities, consequences, and contingencies along the customer journey. Industrial Marketing Management, 105, 294–310. https://doi.org/10.1016/j.indmarman.2022.06.006
   Web of Science ®Google Scholar
• Thomas, M.-J., Wirtz, B. W., & Weyerer, J. C. (2019). Determinants of online review credibility and its impact on consumers’ purchase intention. Journal of Electronic Commerce Research, 20(1), 1–20.
   Web of Science ®Google Scholar
• Ukpabi, D. C., & Karjaluoto, H. (2018). What drives travelers’ adoption of user-generated content? A literature review. Tourism Management Perspectives, 28, 251–273. https://doi.org/10.1016/j.tmp.2018.03.006
   Web of Science ®Google Scholar
• Ulker-Demirel, E., & Ciftci, G. (2020). A systematic literature review of the theory of planned behavior in tourism, leisure and hospitality management research. Journal of Hospitality and Tourism Management, 43, 209–219. https://doi.org/10.1016/j.jhtm.2020.04.003
   Web of Science ®Google Scholar
• Vargo, S. L., Wieland, H., & Akaka, M. A. (2015). Innovation through institutionalization: A service ecosystems perspective. Industrial Marketing Management, 36(3), 309–312. https://doi.org/10.1016/j.indmarman.2014.10.008
   Google Scholar
• Verhoef, P. C., & Langerak, F. (2001). Possible determinants of consumers’ adoption of electronic grocery shopping in The Netherlands. Journal of Retailing and Consumer Services, 8(5), 275–285. https://doi.org/10.1016/S0969-6989(00)00033-3
   Google Scholar
• Verma, S., Yadav, N., & Chikhalkar, R. (2023). An integrated measure of eWOM usefulness in the leisure travel: Conceptualisation, scale development, and validation. Journal of Marketing Communications, 29(3), 211–237. https://doi.org/10.1080/13527266.2021.2004442
   Google Scholar
• Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747–762. https://doi.org/10.1016/j.im.2003.08.011
   Web of Science ®Google Scholar
• Wang, L., Law, R., Guillet, B. D., Hung, K., & Fong, D. K. C. (2015). Impact of hotel website quality on online booking intentions: eTrust as a mediator. International Journal of Hospitality Management, 47, 108–115. https://doi.org/10.1016/j.ijhm.2015.03.012
   Web of Science ®Google Scholar
• Wani, T. A., & Ali, S. W. (2015). Innovation diffusion theory. Journal of General Management Research, 3(2), 101–118.
   Google Scholar
• Wen, J., Lin, Z., Liu, X., Xiao, S. H., & Li, Y. (2021). The interaction effects of online reviews, brand, and price on consumer hotel booking decision making. Journal of Travel Research, 60(4), 846–859.
   Web of Science ®Google Scholar
• Xie, K. L., Zhang, Z., & Zhang, Z. (2014). The business value of online consumer reviews and management response to hotel performance. International Journal of Hospitality Management, 43, 1–12. https://doi.org/10.1016/j.ijhm.2014.07.007
   Web of Science ®Google Scholar
• Xiong, W., Huang, M., Okumus, B., Chen, S., & Fan, F. (2022). The predictive role of tourist-generated content on travel intentions: Emotional mechanisms as mediators. Asia Pacific Journal of Tourism Research, 27(5), 443–456. https://doi.org/10.1080/10941665.2022.2075778
   Web of Science ®Google Scholar
• Xu, H., Lovett, J., Cheung, L. T., Duan, X., Pei, Q., & Liang, D. (2021). Adapting to social media: The influence of online reviews on tourist behaviour at a world heritage site in China. Asia Pacific Journal of Tourism Research, 26(10), 1125–1138. https://doi.org/10.1080/10941665.2021.1952460
   Web of Science ®Google Scholar
• Yang, M., Ren, Y., & Adomavicius, G. (2019). Understanding user-generated content and customer engagement on Facebook business pages. Information Systems Research, 30(3), 839–855. https://doi.org/10.1287/isre.2019.0834
   Web of Science ®Google Scholar
• Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human Behavior, 27(2), 634–639. https://doi.org/10.1016/j.chb.2010.04.014
   Web of Science ®Google Scholar
• Zablocki, A., Schlegelmilch, B., & Houston, M. J. (2019). How valence, volume and variance of online reviews influence brand attitudes. AMS Review, 9(1-2), 61–77. https://doi.org/10.1007/s13162-018-0123-1
   Google Scholar
• Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302
   Web of Science ®Google Scholar
• Zhang, K. Z., Zhao, S. J., Cheung, C. M., & Lee, M. K. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic–systematic model. Decision Support Systems, 67, 78–89. https://doi.org/10.1016/j.dss.2014.08.005
   Web of Science ®Google Scholar
• Zhang, Z., Li, H., Meng, F., & Qiao, S. (2018). Gender difference in restaurant online booking timing and the moderating effects of sell-out risk and information type. Journal of Electronic Commerce Research, 19(3), 266–279.
   Web of Science ®Google Scholar
• Zhang, Z., Zhang, Z., & Yang, Y. (2016). The power of expert identity: How website-recognized expert reviews influence travelers’ online rating behavior. Tourism Management, 55, 15–24. https://doi.org/10.1016/j.tourman.2016.01.004
   Web of Science ®Google Scholar
• Zhao, X., Wang, L., Guo, X., & Law, R. (2015). The influence of online reviews to online hotel booking intentions. International Journal of Contemporary Hospitality Management, 27(6), 1343–1364. https://doi.org/10.1108/IJCHM-12-2013-0542
   Web of Science ®Google Scholar
• Zheng, L. (2021). The classification of online consumer reviews: A systematic literature review and integrative framework. Journal of Business Research, 135, 226–251. https://doi.org/10.1016/j.jbusres.2021.06.038
   Web of Science ®Google Scholar
• Zhu, W., Mou, J., & Benyoucef, M. (2019). Exploring purchase intention in cross-border E-commerce: A three stage model. Journal of Retailing and Consumer Services, 51, 320–330. doi:10.1016/j.jretconser.2019.07.004
   Web of Science ®Google Scholar