Timing of hotel bookings: not monotonic

References

• Antonio, N., de Almeida, A., & Nunes, L. (2019). Big data in hotel revenue management: Exploring cancellation drivers to gain insights into booking cancellation behavior. Cornell Hospitality Quarterly, 60(4), 298–319. https://doi.org/10.1177/1938965519851466
   Web of Science ®Google Scholar
• Arenoe, B., & van der Rest, J. P. I. (2020). Does willingness to pay for rate conditions depend on the booking window? A novel time-dependent conjoint analysis approach. Cornell Hospitality Quarterly, 61(2), 213–222. https://doi.org/10.1177/1938965519864863
   Web of Science ®Google Scholar
• Barros, C. P., & Machado, L. P. (2010). The length of stay in tourism. Annals of Tourism Research, 37(3), 692–706. https://doi.org/10.1016/j.annals.2009.12.005
   Web of Science ®Google Scholar
• Bigne, E., Nicolau, J. L., & William, E. (2021). Advance booking across channels: The effects on dynamic pricing. Tourism Management, 86, 104341. https://doi.org/10.1016/j.tourman.2021.104341
   Web of Science ®Google Scholar
• Bruin, J. (2006). Newtest: Command to compute new test. Statistical Consulting Group. https://stats.oarc.ucla.edu/stata/ado/analysis/
   Google Scholar
• Cheng, L. L., & Monroe, K. B. (2013). An appraisal of behavioral price research (part 1): Price as a physical stimulus. AMS Review, 3(3), 103–129. https://doi.org/10.1007/s13162-013-0041-1
   Google Scholar
• Chen, C.-C., & Schwartz, Z. (2006). The importance of information asymmetry in customers’ booking decisions: A cautionary tale from the internet. Cornell Hotel and Restaurant Administration Quarterly, 47(3), 272–285. https://doi.org/10.1177/0010880406290966
   Google Scholar
• Chen, C. C., & Schwartz, Z. (2008). Timing matters: Travelers’ advanced-booking expectations and decisions. Journal of Travel Research, 47(1), 35–42. https://doi.org/10.1177/0047287507312413
   Web of Science ®Google Scholar
• Chen, C.-C., Schwartz, Z., & Vargas, P. (2011). The search for the best deal: How hotel cancellation policies affect the search and booking decisions of deal-seeking customers. International Journal of Hospitality Management, 30(1), 129–135. https://doi.org/10.1016/j.ijhm.2010.03.010
   Web of Science ®Google Scholar
• Chen, C. M., Tsai, Y. C., & Chiu, H. H. (2017). The decision-making process of and the decisive factors in accommodation choice. Current Issues in Tourism, 20(2), 111–119. https://doi.org/10.1080/13683500.2015.1087476
   Web of Science ®Google Scholar
• Chiang, C.-F., & Jang, S. S. (2007). The effects of perceived price and brand image on value and purchase intention: Leisure travelers’ attitudes toward online hotel booking. Journal of Hospitality & Leisure Marketing, 15(3), 49–69. https://doi.org/10.1300/J150v15n03_04
   Google Scholar
• Day, J., Chin, N., Sydnor, S., & Cherkauer, K. (2013). Weather, climate, and tourism performance: A quantitative analysis. Tourism Management Perspectives, 5, 51–56. https://doi.org/10.1016/j.tmp.2012.11.001
   Google Scholar
• Dogru, T., Sirakaya-Turk, E., & Crouch, G. I. (2017). Remodeling international tourism demand: Old theory and new evidence. Tourism Management, 60, 47–55.
   Web of Science ®Google Scholar
• Falk, M., & Vieru, M. (2018). Modelling the cancellation behaviour of hotel guests. International Journal of Contemporary Hospitality Management, 30(10), 3100–3116. https://doi.org/10.1108/IJCHM-08-2017-0509
   Web of Science ®Google Scholar
• Falk, M., & Vieru, M. (2019). Myth of early booking gains. Journal of Revenue and Pricing Management, 18(1), 52–64. https://doi.org/10.1057/s41272-017-0134-9
   Web of Science ®Google Scholar
• Guillet, B. D., Mattila, A., & Gao, L. (2020). The effects of choice set size and information filtering mechanisms on online hotel booking. International Journal of Hospitality Management, 87, 102379. https://doi.org/10.1016/j.ijhm.2019.102379
   Web of Science ®Google Scholar
• Han, W., Bai, B., Raab, C., Shum, C., & Krishen, A. S. (2024). Will you choose a low-rating hotel that offers promotions?–Insights from the prospect theory. Journal of Travel & Tourism Marketing, 41(3), 418–432. https://doi.org/10.1080/10548408.2024.2323960
   Web of Science ®Google Scholar
• Hoch, S. J., & Loewenstein, G. F. (1991). Time-inconsistent preferences and consumer self-control. Journal of Consumer Research, 17(4), 492–507. https://doi.org/10.1086/208573
   Web of Science ®Google Scholar
• Jang, Y., Chen, C. C., & Miao, L. (2019). Last-minute hotel-booking behavior: The impact of time on decision-making. Journal of Hospitality & Tourism Management, 38, 49–57. https://doi.org/10.1016/j.jhtm.2018.11.006
   Web of Science ®Google Scholar
• Kim, K., Zhang, M., & Li, X. (2008). Effects of temporal and social distance on consumer evaluations. Journal of Consumer Research, 35(4), 706–713. https://doi.org/10.1086/592131
   Web of Science ®Google Scholar
• Lacetera, N., Piga, C. A., & Zirulia, L. (2021). Sticky price for declining risk? The case of cancellation premia in the hotel industry (No. w28456). National Bureau of Economic Research.
   Google Scholar
• Leclerc, F., Schmitt, B. H., & Dube, L. (1995). Waiting time and decision making: Is time like money? Journal of Consumer Research, 22(1), 110–119. https://doi.org/10.1086/209439
   Web of Science ®Google Scholar
• Liu, J., Park, J., Xie, K., Song, H., & Chen, W. (2020). Effect of commercial neighbors on the online popularity of peer-to-peer accommodation-sharing properties. Journal of Hospitality & Tourism Research, 44(5), 780–805. https://doi.org/10.1177/1096348020909855
   Web of Science ®Google Scholar
• Liu, Q., & Van Ryzin, G. J. (2008). Strategic capacity rationing to induce early purchases. Management Science, 54(6), 1115–1131. https://doi.org/10.1287/mnsc.1070.0832
   Web of Science ®Google Scholar
• Loosschilder, G., van der Rest, J. P. I., Schwartz, Z., Cordella, P., & Sierag, D. (2017). From OTA interface design to hotels’ revenues: The impact of sorting and filtering functionalities on consumer choices. Journal of Revenue and Pricing Management, 16(2), 125–138. https://doi.org/10.1057/s41272-016-0074-9
   Google Scholar
• Ma, J., & Li, F. (2022). Effects of psychological distance and social influence on tourists’ hotel booking preferences. Journal of Travel & Tourism Marketing, 39(4), 394–411. https://doi.org/10.1080/10548408.2022.2116628
   Web of Science ®Google Scholar
• Manthiou, A., Luong, V. H., & Klaus, P. (2023). Solo tourism: Exploration and conceptualization–a semi-supervised machine learning approach. Journal of Travel & Tourism Marketing, 40(6), 453–474. https://doi.org/10.1080/10548408.2023.2255891
   Web of Science ®Google Scholar
• Masiero, L., Viglia, G., & Nieto-Garcia, M. (2020). Strategic consumer behavior in online hotel booking. Annals of Tourism Research, 83, 102947. https://doi.org/10.1016/j.annals.2020.102947
   Web of Science ®Google Scholar
• Masiero, L., Yang, Y., & Qiu, R. T. (2019). Understanding hotel location preference of customers: Comparing random utility and random regret decision rules. Tourism Management, 73, 83–89.
   Web of Science ®Google Scholar
• McCullagh, P., & Nelder, J. A. (2019). Generalized linear models. Routledge.
   Google Scholar
• McGuire, K. A. (2016). Hotel pricing in a social world: Driving value in the digital economy. John Wiley.
   Google Scholar
• Morales, D. R., & Wang, J. (2010). Forecasting cancellation rates for services booking revenue management using data mining. European Journal of Operational Research, 202(2), 554–562. https://doi.org/10.1016/j.ejor.2009.06.006
   Web of Science ®Google Scholar
• Nicolau, J. L., Zach, F. J., & Tussyadiah, I. P. (2018). Effects of distance and first-time visitation on tourists’ length of stay. Journal of Hospitality & Tourism Research, 42(7), 1023–1038. https://doi.org/10.1177/1096348016654972
   Web of Science ®Google Scholar
• O’Donoghue, T., & Rabin, M. (2000). The economics of immediate gratification. Journal of Behavioral Decision Making, 13(2), 233–250. https://doi.org/10.1002/(SICI)1099-0771(200004/06)13:2<233:AID-BDM325>3.0.CO;2-U
   Web of Science ®Google Scholar
• Park, J. Y., & Jang, S. (2018). The impact of sold-out information on tourist choice decisions. Journal of Travel & Tourism Marketing, 35(5), 622–632. https://doi.org/10.1080/10548408.2017.1401030
   Web of Science ®Google Scholar
• Park, J. Y., & Jang, S. S. (2014). Sunk costs and travel cancellation: Focusing on temporal cost. Tourism Management, 40, 425–435. https://doi.org/10.1016/j.tourman.2013.08.005
   Web of Science ®Google Scholar
• Park, S., & Tussyadiah, I. P. (2017). Multidimensional facets of perceived risk in mobile travel booking. Journal of Travel Research, 56(7), 854–867.
   Web of Science ®Google Scholar
• Payne, J., Bettman, J. R., & Johnson, E. J. (1991). Consumer decision making. Handbook of Consumer Behaviour, 50–84.
   Google Scholar
• Sánchez-Medina, A. J., & Eleazar, C. (2020). Using machine learning and big data for efficient forecasting of hotel booking cancellations. International Journal of Hospitality Management, 89, 102546. https://doi.org/10.1016/j.ijhm.2020.102546
   Web of Science ®Google Scholar
• Schwartz, Z. (2006). Advanced booking and revenue management: Room rates and the consumers’ strategic zones. International Journal of Hospitality Management, 25(3), 447–462. https://doi.org/10.1016/j.ijhm.2005.02.002
   Google Scholar
• Schwartz, Z. (2008). Time, price, and advanced booking of hotel rooms. International Journal of Hospitality & Tourism Administration, 9(2), 128–146. https://doi.org/10.1080/15256480801907885
   Google Scholar
• Schwartz, Z., & Chen, C. C. (2010). Advanced booking decisions of risk-averse, deal-oriented travelers. Journal of Hospitality Marketing & Management, 19(2), 188–197. https://doi.org/10.1080/19368620903455294
   Google Scholar
• Song, M., Noone, B. M., & Han, R. J. (2019). An examination of the role of booking lead time in consumers’ reactions to online scarcity messages. International Journal of Hospitality Management, 77, 483–491. https://doi.org/10.1016/j.ijhm.2018.08.012
   Web of Science ®Google Scholar
• Tian, X., Pan, B., Bai, L., & Mo, D. (2023). Md-pred: A multidimensional hybrid prediction model based on machine learning for hotel booking cancellation prediction. International Journal of Pattern Recognition and Artificial Intelligence, 37(5), 2351009. https://doi.org/10.1142/S0218001423510096
   Google Scholar
• Trope, Y., & Liberman, N. (2003). Temporal construal. Psychological Review, 110(3), 403. https://doi.org/10.1037/0033-295X.110.3.403
   PubMed Web of Science ®Google Scholar
• Vives, A., & Jacob, M. (2023). Sources of price elasticity of demand variability among Spanish resort hotels: A managerial insight. Journal of Hospitality & Tourism Technology, 14(2), 137–153. https://doi.org/10.1108/JHTT-11-2020-0298
   Web of Science ®Google Scholar
• Wang, W. (2020, August 1). Data visualization of hotel booking behavior. https://rstudio-pubsstatic.s3.amazonaws.com/643455_dd38c7aad1d14d389bdd3240c242a60b.html
   Google Scholar
• Wu, M. Y., Wall, G., Zu, Y., & Ying, T. (2019). Chinese children’s family tourism experiences. Tourism Management Perspectives, 29, 166–175. https://doi.org/10.1016/j.tmp.2018.11.003
   Web of Science ®Google Scholar
• Yordam Dağıstan, S., Sevim, B., Arici, H. E., Saydam, M. B., & Köseoglu, M. A. (2023). Perceived risk in hospitality and tourism scholarship: A systematic review and future research agenda. Journal of Travel & Tourism Marketing, 40(9), 863–877. https://doi.org/10.1080/10548408.2023.2296640
   Web of Science ®Google Scholar
• Yu, J., Moon, H., Chua, B. L., & Han, H. (2022). Hotel data privacy: Strategies to reduce customers’ emotional violations, privacy concerns, and switching intention. Journal of Travel & Tourism Marketing, 39(2), 215–227. https://doi.org/10.1080/10548408.2022.2061673
   Web of Science ®Google Scholar