Online hotel ratings and its influence on hotel room rates: the case of Lisbon, Portugal
Lisbon is one of the European Union cities that has one of the highest growth in the number of hotels. With the digital revolution travelers can easily not only compare prices but also get information about the experience of other guests which can influence prices. The aim of this paper is to analyze how prices for a hotel stay can be influenced by some quality signaling factors, as star rating and online consumer’s ratings (location, cleanliness, comfort, facilities, staff and value for money, available on Booking.com), the volume of consumer’s comments and the availability of rooms in Lisbon. For 151 hotels in Lisbon, from 3 to 5 stars, through a multiple regression model, the results suggest that hotel category, location and facilities ratings have a positive influence on hotel room rates, but higher trade-off between what clients pay and the guest hotel stay experience has a negative impact on the consumer’s willingness to pay, as well as the number of comments. Among different hotel categories, the influent factors are different. Our main findings provide signs to hoteliers to take corrective actions towards the attributes most valuable for consumers and that can provide a higher room rate premium.
Abrate, G., Capriello, A. & Fraquelli, G. (2011). When quality signals talk: Evidence from the Turin hotel industry. Tourism Management, 32(4), 912-921.
Abrate, G., Fraquelli, G. & Viglia, G. (2012). Dynamic pricing strategies: Evidence from European hotels. International Journal of Hospitality Management, 31, 160–168.
Anderson, C. K. (2012). The Impact of Social Media on Lodging Performance. Center for Hospitality Research Report, 12 (15).
Andersson, D.E. (2010). Hotel attributes and hedonic prices: an analysis of internet-based transactions in Singapore’s market for hotel rooms. The Annals of Regional Science, 44, 229-240.
Arbel, A. & Pizam, A. (1977) Some Determinants of Urban Hotel Location: The Tourists' Inclinations. Journal of Travel Research, 15(3): 18-22. DOI: 10.1177/004728757701500305
Badinelli, R. (2000). An optimal, dynamic policy for hotel yield management. European Journal of Operational Research, 121, 476–503.
Blal, I. & Sturman, M. C. (2014). The differential effects of the quality and quantity of online reviews on hotel room sales. Cornell Hospitality Quarterly, 55(4), 365-375.
Borges, I., Pereira, G., Matos, C. & Borchardt, M. (2015). Análise da relação entre a satisfação dos consumidores e os preços ofertados no sítio booking.com. Tourism & Management Studies, 11(2), 64-70.
Castro, C. & Ferreira, F. A. (2015). Effects of Hotel Characteristics on Room Rates in Porto: a Hedonic Price Approach, AIP Conference Proceedings 1648, 070002.
Castro, C., Ferreira, F. A. & Vasconcelos, L. (2016). Effects of Hotel Characteristics on Room Rates in Lisbon: a Hedonic Price Approach. Forthcoming.
Chaves, M., Gomes, R. & Pedron, C. (2011). Analysing reviews in the Web 2.0: Small and medium hotels in Portugal. Tourism Management, 33(5), 1286-1287.
Chen, C. & Rothschild, R. (2010). An application of hedonic pricing analysis to the case of hotel rooms in Taipei. Tourism Economics, 16(3), 685–694.
Cheung, C. & Thadani, D. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54 (1), 461-70.
Espinet, J. M., Saez, M., Coenders, G. & Fluvià, M. (2003). Effects on Prices of the Attributes of Holiday Hotels: A Hedonic Prices Approach. Tourism Economics, vol. 9(2), 165-177.
Eurostat (2016). Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation (NACE Rev. 2, I, 55.1) by NUTS 2 regions (from 2012 onwards) [Database]. Retrieved April 30, 2016, from http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do
INE (2016a). Guests (No.) in hotel establishments by Geographic localization (NUTS - 2013) and Type (hotel establishment); Annual [Statistical data]. Retrieved April, 30, from https://www.ine.pt/xportal/xmain?
INE (2016b). Lodging capacity (No.) in hotel establishments by Geographic localization (NUTS - 2013) and Type (hotel establishment; Annual [Statistical data]. Retrieved April, 30, from https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0008574&contexto=bd&selTab=tab2
Gallego, G. & Ryzin, G. (1994). Optimal dynamic pricing of inventories with stochastic demand over ?nite horizons. Management Science, 40, 999–1020.
Goodman, A. C. (1998). Andrew Court and the Invention of Hedonic Price Analysis. Journal of Urban Economics, 44, 291–298.
Google/IPSOS OTX. MediaTraveler's Road to Decision 2011. Retrieved May 5, 2016, from http://www.gstatic.com/ads/research/en/2011_TravelersRoadtoDecision2011.pdf.
Herrmann, R. & Herrmann, O. (2014). Hotel room rates under the influence of a large event: The Oktoberfest in Munich 2012. International Journal of Hospitality Management, 39, 21–28.
Hung, W., Shang, J. & Wang, F. (2010). Pricing determinants in the hotel industry: Quantile regression analysis. International Journal of Hospitality Management, 29, 378–384.
Molinillo, S., Ximénez-de-Sandoval, J., Fernández-Morales, A. & Coca-Stefaniak, A. (2016). Hotel Assessment through Social Media: The case of TripAdvisor. Tourism & Management Studies, 12(1), 15-24. DOI: 10.18089/tms.2016.12102
O’Connor, P. (2010). Managing a hotel’s image on TripAdvisor. Journal of Hospitality Marketing & Management, 19(7), 754–772.
Ö?üt, H. & Ta?, B. (2012). The influence of internet customer reviews on the online sales and prices in hotel industry. The Service Industries Journal, 32 (2), 197–214.
Park, D. & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electronic Commerce Research and Applications,7 (4), 386-398.
Phillips, P., Barnes, S., Zigan, K. & Schegg, R. (2016). Understanding the Impact of Online Reviews on Hotel Performance: An Empirical Analysis. Journal of Travel Research. DOI: 10.1177/0047287516636481.
Riegner, C. (2007). Word of mouth on the web: the impact of Web 2.0 on consumer purchase decisions. Journal of Advertising Research, 47(4), 436-447.
Rigall-I-Torrent, R., Fluvià, M., Ballester, R., Saló, A., Ariza, E. & Espinet, J. M. (2011). The effects of beach characteristics and location with respect to hotel prices. Tourism Management, 32, 1150-1158.
Rosen, S. (1974). Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. Journal of Political Economy, 82(1), 34-55.
Schamel, G. (2012).Weekend vs. midweek stays: Modelling hotel room rates in a small market. International Journal of Hospitality Management, 31 (4), 1113–1118.
Serra Cantallops, A. & Salvi, F. (2014). New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management, 36, 41-51.
Smith, T. & Spencer, A. (2011). Predictors of Value for Money in Jamaican All-Inclusive Hotels. International Journal of Humanities and Social Science, 1(4), 93-102.
Thrane, C. (2007). Examining the determinants of room rates for hotels in capital cities: The Oslo experience. Journal of Revenue and Pricing Management, 5(4), 315-323.
Tsao, W-C., Hsieh, M-T., Shih, L-W. & Lin, T. (2015). Compliance with eWOM: The in?uence of hotel reviews on booking intention from the perspective of consumer conformity. International Journal of Hospitality Management, 46, 99–111.
White, P. & Mulligan, G. (2002). Hedonic Estimates of Lodging Rates in the Four Corners Region. The Professional Geographer, 54 (4), 533-543.
World Tourism Organization (UNWTO) (2014). Online Guest Reviews and Hotel Classification Systems – An Integrated Approach. Madrid: UNWTO.
Xie, K., 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.
Yang, Y., Mueller, N. & Croes, R. (2016). Market accessibility and hotel prices in the Caribbean: The moderating effect of quality-signaling factors. Tourism Management, 56, 40-51.
Zhang, H., Zhang, J., Lu, S., Cheng, S. & Zhang, J. (2011). Modeling hotel room price with geographically weighted regression. International Journal of Hospitality Management, 30, 1036-1043.
Zhang, Z., Ye, Q. & Law, R. (2011). Determinants of hotel room price: An exploration of travelers' hierarchy of accommodation needs". International Journal of Contemporary Hospitality Management, 23(7), 972-981.
Zhou, L., Ye, S., Pearce, P.L. & Wu, M.-Y. (2014). Refreshing hotel satisfaction studies by reconfiguring customer review data. International Journal of Hospitality Management, 38, 1-10.
Zhu, F. & Zhang, X. (2010). Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. Journal of Market, 74(2), 133-148.
Copyright (c) 2018 Tourism & Management Studies
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.