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Average hotel price, cost in the U.S. 2015. (n.d.). Retrieved August 15, 2016, from http://www.statista.com/statistics/195704/average-hotel-room-rate-in-the-us-since-2005/
Ayeh, J. K., Au, N., & Law, R. (2013). “Do We Believe in TripAdvisor?” Examining Credibility Perceptions and Online Travelers’ Attitude toward Using User-Generated Content. Journal of Travel Research, 47287512475217. https://doi.org/10.1177/0047287512475217
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
Baker, A. M., Donthu, N., & Kumar, V. (2016). Investigating how word-of-mouth conversations about brands influence purchase and retransmission intentions. Journal of Marketing Research, 53(2), 225–239. https://doi.org/10.1509/jmr.14.0099
Berezina, K., Bilgihan, A., Cobanoglu, C., & Okumus, F. (2016). Understanding Satisfied and Dissatisfied Hotel Customers: Text Mining of Online Hotel Reviews. Journal of Hospitality Marketing & Management, 25(1), 1–24. https://doi.org/10.1080/19368623.2015.983631
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. https://doi.org/10.1177/1938965514533419
Book, L. A., Tanford, S., & Chen, Y.-S. (2015). Understanding the impact of negative and positive traveler reviews social influence and price anchoring effects. Journal of Travel Research, 47287515606810. https://doi.org/10.1177/0047287515606810
Book, L. A., Tanford, S., Montgomery, R., & Love, C. (2015). Online traveler reviews as social influence price is no longer king. Journal of Hospitality & Tourism Research, 42(3), 445 - 475. . https://doi.org/10.1177/1096348015597029
Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir.20082
Casaló, L. V., Flavián, C., & Guinalíu, M. (2011). Understanding the intention to follow the advice obtained in an online travel community. Computers in Human Behavior, 27(2), 622–633. https://doi.org/10.1016/j.chb.2010.04.013
Cheung, C. M. K., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461–470. https://doi.org/10.1016/j.dss.2012.06.008
Chevalier, J. A., Dover, Y., & Mayzlin, D. (2017). Channels of impact: User reviews when quality is dynamic and managers respond (No. w23299). National Bureau of Economic Research.
Chu, S. C., Lien, C. H., & Cao, Y. (2018). Electronic word-of-mouth (eWOM) on WeChat: Examining the influence of sense of belonging, need for self-enhancement, and consumer engagement on Chinese travellers’ eWOM. International Journal of Advertising 23(2), 1-24. doi.org/10.1080/02650487.2018.1470917
Cross, R. G., Higbie, J. A., & Cross, D. Q. (Dax). (2009). Revenue management’s renaissance a rebirth of the art and science of profitable revenue generation. Cornell Hospitality Quarterly, 50(1), 56–81. https://doi.org/10.1177/1938965508328716
De Pelsmacker, P., van Tilburg, S., & Holthof, C. (2018). Digital marketing strategies, online reviews and hotel performance. International Journal of Hospitality Management, 72, 47-55. doi.org/10.1016/j.ijhm.2018.01.003
Dewnarain, S., Ramkissoon, H., & Mavondo, F. (2018). Social customer relationship management: An integrated conceptual framework. Journal of Hospitality Marketing & Management, 1-17.
Duverger, P. (2013). Curvilinear effects of user-generated content on hotels’ market share a dynamic panel-data analysis. Journal of Travel Research, 52(4), 465–478. https://doi.org/10.1177/0047287513478498
Fader, P. S., & Winer, R. S. (2012). Introduction to the Special Issue on the Emergence and Impact of User-Generated Content. Marketing Science. https://doi.org/10.1287/mksc.1120.0715
Filieri, R., & McLeay, F. (2014). E-WOM and accommodation an analysis of the factors that influence travelers’ adoption of information from online reviews. Journal of Travel Research, 53(1), 44–57. https://doi.org/10.1177/0047287513481274
Fotis, J., Buhalis, D., & Rossides, N. (2012). Social Media Use and Impact during the Holiday Travel Planning Process. In P. M. Fuchs, P. F. Ricci, & P. L. Cantoni (Eds.), Information and Communication Technologies in Tourism 2012 (pp. 13–24). Springer Vienna. Retrieved from http://link.springer.com/chapter/10.1007/978-3-7091-1142-0_2
Gavilan, D., Avello, M., & Martinez-Navarro, G. (2018). The influence of online ratings and reviews on hotel booking consideration. Tourism Management, 66, 53-61. doi.org/10.1016/j.tourman.2017.10.018
Goodman, J. K., Cryder, C. E., & Cheema, A. (2013). Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. Journal of Behavioral Decision Making, 26(3), 213–224. https://doi.org/10.1002/bdm.1753
Gregory, A. M. (2011). Assessment of product and service attributes and consumers’ willingness to pay in the vacation ownership industry using the Kano Model and conjoint analysis (Doctoral dissertation). University of Central Florida.
Gregory, A. M. (2013). Examining the Impact of Negative Attributes On Consumer Preference and Willingness to Pay in the Vacation Ownership Industry: A Conjoint Analysis. Journal of Tourism Research & Hospitality, 2(3), 1–5. https://doi.org/10.4172/2324-8807.1000120
Guillet, B. D., Guo, Y., & Law, R. (2015). Segmenting Hotel Customers Based on Rate Fences Through Conjoint and Cluster Analysis. Journal of Travel & Tourism Marketing, 32(7), 835–851. https://doi.org/10.1080/10548408.2015.1063825
Guillet, B. D., Law, R., & Xiao, Q. (2013). Rate Fences in Hotel Revenue Management and Their Applications to Chinese Leisure Travelers A Fractional Factorial Design Approach. Cornell Hospitality Quarterly, 1938965513507497. https://doi.org/10.1177/1938965513507497
Guillet, B. D., Liu, W., & Law, R. (2014). Can setting hotel rate restrictions help balance the interest of hotels and customers? International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-01-2013-0020
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.
Gursoy, D., Del Chiappa, G., & Zhang, Y. (2017). Preferences regarding external information sources: A conjoint analysis of visitors to Sardinia, Italy. Journal of Travel & Tourism Marketing, 34(6), 806-820.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th edition). Upper Saddle River, NJ: Pearson Prentice Hall.
Hu, N., Koh, N. S., & Reddy, S. K. (2014). Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales. Decision Support Systems, 57, 42–53. https://doi.org/10.1016/j.dss.2013.07.009
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Jeong, M., & Jeon, M. M. (2008). Customer reviews of hotel experiences through consumer generated media (CGM). Journal of Hospitality & Leisure Marketing, 17(1-2), 121-138.
Lee, J., Park, D.-H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341–352. https://doi.org/10.1016/j.elerap.2007.05.004
Lee, S. H. (2016). How hotel managers decide to discount room rates: A conjoint analysis. International Journal of Hospitality Management, 52, 68–77. https://doi.org/10.1016/j.ijhm.2015.09.014
Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2017). Do electronic word-of-mouth and elaboration likelihood model influence hotel booking?. Journal of Computer Information Systems 28(3), 1-15. doi.org/10.1080/08874417.2017.1320953
Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458–468. https://doi.org/10.1016/j.tourman.2007.05.011
Lu, W., & Stepchenkova, S. (2014). User-Generated Content as a Research Mode in Tourism and Hospitality Applications: Topics, Methods, and Software. Journal of Hospitality Marketing & Management. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/19368623.2014.907758
Mauri, A. G. & Minazzi, R. (2013). Web reviews influence on expectations and purchasing intentions of hotel potential customers. International Journal of Hospitality Management, 34, 99–107. https://doi.org/10.1016/j.ijhm.2013.02.012
Millar, M., & Baloglu, S. (2011). Hotel Guests’ Preferences for Green Guest Room Attributes. Cornell Hospitality Quarterly, 52(3), 302–311. https://doi.org/10.1177/1938965511409031
Neirotti, P., Raguseo, E., & Paolucci, E. (2016). Are customers’ reviews creating value in the hospitality industry? Exploring the moderating effects of market positioning. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2016.02.010
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Winning the Battle: The Importance of Price and Online Reviews for Hotel Selection
Year 2020,
Volume: 8 Issue: 1, 177 - 202, 10.06.2020
Traditionally, price has been one of the main revenue management levers that allow hotels to sell the right product to the right customer at the right time. Recent research in the area of electronic word-of-mouth has found that travelers’ online reviews may also be an influential factor affecting other customers’ booking decisions. However, it is challenging to determine the value of online reviews for customer decision making and to compare this value to hotel room prices. Therefore, the main goal of this study is to investigate which factors (room rate, online reviews’ rating score, or the number of reviews by other travelers) are more important for customers’ booking decisions and the optimal combination of these factors for booking a hotel. Conjoint analysis was applied to measure the relative importance of the aforementioned factors for travelers’ booking decisions. The results revealed that the overall online rating was the most influential factor with regard to customer decision making about booking a hotel. In addition, the following combination of factors was discovered to be optimal for attracting customer reservations: more than 107 reviews with an average rating of at least 3.3 (on a 5-point scale), and a price level of $130 or below.
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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
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Dewnarain, S., Ramkissoon, H., & Mavondo, F. (2018). Social customer relationship management: An integrated conceptual framework. Journal of Hospitality Marketing & Management, 1-17.
Duverger, P. (2013). Curvilinear effects of user-generated content on hotels’ market share a dynamic panel-data analysis. Journal of Travel Research, 52(4), 465–478. https://doi.org/10.1177/0047287513478498
Fader, P. S., & Winer, R. S. (2012). Introduction to the Special Issue on the Emergence and Impact of User-Generated Content. Marketing Science. https://doi.org/10.1287/mksc.1120.0715
Filieri, R., & McLeay, F. (2014). E-WOM and accommodation an analysis of the factors that influence travelers’ adoption of information from online reviews. Journal of Travel Research, 53(1), 44–57. https://doi.org/10.1177/0047287513481274
Fotis, J., Buhalis, D., & Rossides, N. (2012). Social Media Use and Impact during the Holiday Travel Planning Process. In P. M. Fuchs, P. F. Ricci, & P. L. Cantoni (Eds.), Information and Communication Technologies in Tourism 2012 (pp. 13–24). Springer Vienna. Retrieved from http://link.springer.com/chapter/10.1007/978-3-7091-1142-0_2
Gavilan, D., Avello, M., & Martinez-Navarro, G. (2018). The influence of online ratings and reviews on hotel booking consideration. Tourism Management, 66, 53-61. doi.org/10.1016/j.tourman.2017.10.018
Goodman, J. K., Cryder, C. E., & Cheema, A. (2013). Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. Journal of Behavioral Decision Making, 26(3), 213–224. https://doi.org/10.1002/bdm.1753
Gregory, A. M. (2011). Assessment of product and service attributes and consumers’ willingness to pay in the vacation ownership industry using the Kano Model and conjoint analysis (Doctoral dissertation). University of Central Florida.
Gregory, A. M. (2013). Examining the Impact of Negative Attributes On Consumer Preference and Willingness to Pay in the Vacation Ownership Industry: A Conjoint Analysis. Journal of Tourism Research & Hospitality, 2(3), 1–5. https://doi.org/10.4172/2324-8807.1000120
Guillet, B. D., Guo, Y., & Law, R. (2015). Segmenting Hotel Customers Based on Rate Fences Through Conjoint and Cluster Analysis. Journal of Travel & Tourism Marketing, 32(7), 835–851. https://doi.org/10.1080/10548408.2015.1063825
Guillet, B. D., Law, R., & Xiao, Q. (2013). Rate Fences in Hotel Revenue Management and Their Applications to Chinese Leisure Travelers A Fractional Factorial Design Approach. Cornell Hospitality Quarterly, 1938965513507497. https://doi.org/10.1177/1938965513507497
Guillet, B. D., Liu, W., & Law, R. (2014). Can setting hotel rate restrictions help balance the interest of hotels and customers? International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-01-2013-0020
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.
Gursoy, D., Del Chiappa, G., & Zhang, Y. (2017). Preferences regarding external information sources: A conjoint analysis of visitors to Sardinia, Italy. Journal of Travel & Tourism Marketing, 34(6), 806-820.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th edition). Upper Saddle River, NJ: Pearson Prentice Hall.
Hu, N., Koh, N. S., & Reddy, S. K. (2014). Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales. Decision Support Systems, 57, 42–53. https://doi.org/10.1016/j.dss.2013.07.009
Jalilvand, M. R., Esfahani, S. S., & Samiei, N. (2011). Electronic word-of-mouth: Challenges and opportunities. Procedia Computer Science, 3, 42–46. https://doi.org/10.1016/j.procs.2010.12.008
Jeong, M., & Jeon, M. M. (2008). Customer reviews of hotel experiences through consumer generated media (CGM). Journal of Hospitality & Leisure Marketing, 17(1-2), 121-138.
Lee, J., Park, D.-H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341–352. https://doi.org/10.1016/j.elerap.2007.05.004
Lee, S. H. (2016). How hotel managers decide to discount room rates: A conjoint analysis. International Journal of Hospitality Management, 52, 68–77. https://doi.org/10.1016/j.ijhm.2015.09.014
Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2017). Do electronic word-of-mouth and elaboration likelihood model influence hotel booking?. Journal of Computer Information Systems 28(3), 1-15. doi.org/10.1080/08874417.2017.1320953
Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458–468. https://doi.org/10.1016/j.tourman.2007.05.011
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Mauri, A. G. & Minazzi, R. (2013). Web reviews influence on expectations and purchasing intentions of hotel potential customers. International Journal of Hospitality Management, 34, 99–107. https://doi.org/10.1016/j.ijhm.2013.02.012
Millar, M., & Baloglu, S. (2011). Hotel Guests’ Preferences for Green Guest Room Attributes. Cornell Hospitality Quarterly, 52(3), 302–311. https://doi.org/10.1177/1938965511409031
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