%0 Journal Article %1 Mondaca-Marino201987 %A Mondaca-Marino, C.M. %A Guala, C. %A Montecinos-Astorga, A.L. %A Concha, C.S. %D 2019 %I Centro de Informacion Tecnologica %J Informacion Tecnologica %K , Booking.com, Chile, Chile; Corrective Costs; Hotels Information Lodging Multivariate Positive Regression Santiago actions; analysis, asymmetry; correlations; de linear model; prices; regression tourism; %N 1 %P 87-96 %R 10.4067/S0718-07642019000100087 %T Factors affecting in the hotel price at Booking.com. The case of Santiago, Chile Factores que influyen en el precio de hoteles en booking.com. El Caso de Santiago de Chile %U https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062341733&doi=10.4067%2fS0718-07642019000100087&partnerID=40&md5=72bc00d401775adc4c359c644e7e9da9 %V 30 %X This research discusses the effect of different variables on the price of hotel services in Chile and establishes whether there is a correlation between prices and user ratings. In doing so, a multivariate linear regression model was used to analyse a set of 145 hotels available in Booking.com in Santiago de Chile during three seasons. The findings suggest that social media are an effective tool in addressing information asymmetry issues in the hotel industry. There is a positive correlation between the price of hotels and the score assigned by users. Other variables that have some impact on prices were also found, including location and number of comments. The findings suggest that the hotel industry should pay greater attention to comments management in order to improve its price position in the market. This means relying on a post sales policy that can monitor guest experience and take the relevant corrective actions to improve user experiences. © 2019 Centro de Informacion Tecnologica. All Rights Reserved.

@article{Mondaca-Marino201987, abbrev_source_title = {Inf Tecnol}, abstract = {This research discusses the effect of different variables on the price of hotel services in Chile and establishes whether there is a correlation between prices and user ratings. In doing so, a multivariate linear regression model was used to analyse a set of 145 hotels available in Booking.com in Santiago de Chile during three seasons. The findings suggest that social media are an effective tool in addressing information asymmetry issues in the hotel industry. There is a positive correlation between the price of hotels and the score assigned by users. Other variables that have some impact on prices were also found, including location and number of comments. The findings suggest that the hotel industry should pay greater attention to comments management in order to improve its price position in the market. This means relying on a post sales policy that can monitor guest experience and take the relevant corrective actions to improve user experiences. © 2019 Centro de Informacion Tecnologica. All Rights Reserved.}, added-at = {2021-08-28T19:41:18.000+0200}, affiliation = {Universidad Austral de Chile, Campus Isla Teja, Valdivia, Chile}, author = {Mondaca-Marino, C.M. and Guala, C. and Montecinos-Astorga, A.L. and Concha, C.S.}, author_keywords = {Booking.com, tourism; Hotels; Lodging prices}, biburl = {https://www.bibsonomy.org/bibtex/2c70aedfe51de3e494e2aed557472fe3e/cristiansalazar}, coden = {ITECF}, correspondence_address1 = {Mondaca-Marino, C.M.; Universidad Austral de Chile, Chile; email: cristianmondaca@uach.cl}, document_type = {Article}, doi = {10.4067/S0718-07642019000100087}, interhash = {5f9bd1e5271ffd7bca9514a05e231e89}, intrahash = {c70aedfe51de3e494e2aed557472fe3e}, issn = {07168756}, journal = {Informacion Tecnologica}, keywords = {, Booking.com, Chile, Chile; Corrective Costs; Hotels Information Lodging Multivariate Positive Regression Santiago actions; analysis, asymmetry; correlations; de linear model; prices; regression tourism;}, language = {Spanish}, note = {cited By 1}, number = 1, pages = {87-96}, publisher = {Centro de Informacion Tecnologica}, references = {Abrate, G., Viglia, G., Strategic and tactical price decisions in hotel revenue management (2016) Tourism Management, 55, pp. 123-132; Andrews, L., Bianchi, C., America, C.L., Consumer internet purchasing behavior in Chile (2013) Journal of Business Research, 66, pp. 1791-1799; Bhatiasevi, V., Yoopetch, C., The determinants of intention to use electronic booking among young users in Thailand (2014) Journal of Hospitality and Tourism Management, 23, pp. 1-11; Buhalis, D., Licata, M.C., The future eTourism intermediaries (2002) Tourism Management, 23 (3), pp. 207-220; Campos, S., Yague, M.J., Los precios de referencia en la evaluación online del servicio hotelero (2011) Estudios De Economía Aplicada, 29 (3), pp. 825-843; Cao, K., Yang, Z., A study of e-commerce adoption by tourism websites in China (2016) Journal of Destination Marketing & Management, 5 (3), pp. 282-289; Deutch, D., Milo, T., A structural/temporal query language for Business Processes (2012) Journal of Computer and System Sciences, 78 (2), pp. 583-609; Diana-Jens, P., Rodríguez, A., La reputación online y su impacto en la política de precios de los hoteles (2015) Cuadernos De Turismo, 36, pp. 129-155; Garrigos-Simon, F.J., Galdon, J.L., Sanz-Blas, S., Effects of crowdvoting on hotels: The Booking.com case (2017) International Journal of Contemporary Hospitality Management, 29 (1), pp. 419-437; Jolivet, G., Jullien, B., Postel-Vinay, F., Reputation and prices on the e-market: Evidence from a major French platform (2016) International Journal of Industrial Organization, 45, pp. 59-75; Levy, S.E., Duan, W., Boo, S., An analysis of one-star online reviews and responses in the Washington, D.C. 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The case of Santiago, Chile [Factores que influyen en el precio de hoteles en booking.com. El Caso de Santiago de Chile]}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062341733&doi=10.4067%2fS0718-07642019000100087&partnerID=40&md5=72bc00d401775adc4c359c644e7e9da9}, volume = 30, year = 2019 }