SavedAdd your journal

Journals / Advances in Hospitality and Tourism Research (AHTR) / 2026 / Volume: 8 Issue: 1

Winning the Battle: The Importance of Price and Online Reviews for Hotel Selection

Olena Cıftcı(The University of Mississippi)0000-0003-2867-5897
Katerina Berezına(The University of Mississippi)0000-0002-1309-9930
Muhittin Cavusoglu(Northern Arizona University)0000-0003-2272-1004
Cihan Cobanoglu(University of South Florida)0000-0001-9556-6223
Pages
—
Publication Date
2020-06-10
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results revealed that the overall online rating was the most influential factor with regard to customer decision making about booking a hotel.

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
📊
Key Findings & Data: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.
💡
Conclusion & Impact:The results revealed that the overall online rating was the most influential factor with regard to customer decision making about booking a hotel.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:revenue management · conjoint analysis · user generated content

Abstract

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.

🔖

Cite This Article

Cıftcı, O., Berezına, K., Cavusoglu, M., Cobanoglu, C. (2020). Winning the Battle: The Importance of Price and Online Reviews for Hotel Selection. Advances in Hospitality and Tourism Research (AHTR), Volume: 8 Issue: 1. https://doi.org/10.30519/ahtr.528150

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (69)

  1. Anderson, C. (2012). The impact of social media on lodging performance. Cornell Hospitality Report, 12(15), 6–11. Retrieved from http://scholarship.sha.cornell.edu/chrpubs/5
  2. Anonymous. (2013, February 26). Revenue management and reviews: the perfect match for pricing it right. Retrieved July 3, 2016, from http://www.eyefortravel.com/social-media-and-marketing/revenue-management-and-reviews-perfect-match-pricing-it-right
  3. 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/
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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.
  15. 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
  16. 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
  17. 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
  18. Dewnarain, S., Ramkissoon, H., & Mavondo, F. (2018). Social customer relationship management: An integrated conceptual framework. Journal of Hospitality Marketing & Management, 1-17.
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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.
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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.
  31. 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.
  32. 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.
  33. 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
  34. 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
  35. 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.
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. 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
  43. Moro, S., Rita, P., & Oliveira, C. (2018). Factors influencing hotels’ online prices. Journal of Hospitality Marketing & Management, 27(4), 443-464.
  44. 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
  45. Netzer, O., Toubia, O., Bradlow, E. T., Dahan, E., Evgeniou, T., Feinberg, F. M., … Rao, V. R. (2008). Beyond conjoint analysis: Advances in preference measurement. Marketing Letters, 19(3–4), 337–354. https://doi.org/10.1007/s11002-008-9046-1
  46. Nieto-García, M., Muñoz-Gallego, P. A., & González-Benito, Ó. (2017). Tourists’ willingness to pay for an accommodation: The effect of eWOM and internal reference price. International Journal of Hospitality Management, 62, 67-77. https://doi.org/10.1016/j.ijhm.2016.12.006
  47. Noone, B. M., & McGuire, K. A. (2013a). Effects of price and user-generated content on consumers’ prepurchase evaluations of variably priced services. Journal of Hospitality & Tourism Research, 1096348012461551. https://doi.org/10.1177/1096348012461551
  48. Noone, B. M., & McGuire, K. A. (2013b). Pricing in a social world: The influence of non-price information on hotel choice. Journal of Revenue & Pricing Management, 12(5), 385–401. https://doi.org/10.1057/rpm.2013.13
  49. Noone, B. M., McGuire, K. A., & Rohlfs, K. V. (2011). Social media meets hotel revenue management: Opportunities, issues and unanswered questions. Journal of Revenue and Pricing Management, 10(4), 293–305. https://doi.org/10.1057/rpm.2011.12
  50. Öğüt, H., & Taş, B. K. O. (2012). The influence of internet customer reviews on the online sales and prices in hotel industry. The Service Industries Journal, 32(2), 197–214. https://doi.org/10.1080/02642069.2010.529436
  51. Orme, B. (2010). Getting started with conjoint analysis: strategies for product design and pricing research (Second Edition). Madison, Wis.: Research Publishers LLC.
  52. Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67. https://doi.org/10.1016/j.jbusres.2007.11.017
  53. PhoCusWright. (2014, February 11). 24 insights to shape your TripAdvisor strategy. Retrieved April 16, 2016, from http://t4binsights-cache.tripadvisor.com/TripAdvisorInsights/sites/default/files/pdf_links/26309_pcw_infographic_en_us.pdf
  54. Repetti, T., Roe, S., & Gregory, A. (2015). Pricing strategies for resort fees: consumer preferences favor simplicity. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-06-2013-0237
  55. Schuckert, M., Liu, X., & Law, R. (2015). Stars, Votes, and Badges: How Online Badges Affect Hotel Reviewers. Journal of Travel & Tourism Marketing. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/10548408.2015.1064056
  56. 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. https://doi.org/10.1016/j.ijhm.2013.08.007
  57. 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
  58. Tanford, S., & Montgomery, R. (2015). The effects of social influence and cognitive dissonance on travel purchase decisions. Journal of Travel Research, 54(5), 596–610. https://doi.org/10.1177/0047287514528287
  59. Torres, E. N., Adler, H., Lehto, X., Behnke, C., & Li, M. (2013). One experience and multiple reviews: the case of upscale US hotels. Tourism Review of AIEST - International Association of Scientific Experts in Tourism, 68(3), 3–20. https://doi.org/http://dx.doi.org/10.1108/TR-03-2013-0012
  60. Torres, E. N., Singh, D., & Robertson-Ring, A. (2015). Consumer reviews and the creation of booking transaction value: Lessons from the hotel industry. International Journal of Hospitality Management, 50, 77–83. https://doi.org/10.1016/j.ijhm.2015.07.012
  61. Van der Rest, J. I., Cordella, P., Loosschilder, G., & Schwartz, Z. (2016). Connecting search marketing to revenue management: conjoint analysis as a methodology to evaluate the optimal OTA commission fee. Service Science, 8(2), 1–15. https://doi.org/http://dx.doi.org/10.1287/serv.2016.0137
  62. Viglia, G., Minazzi, R., & Buhalis, D. (2016) The influence of e-word-of-mouth on hotel occupancy rate. International Journal of Contemporary Hospitality Management, 28 (9), 2035-2051. https://doi.org/10.1108/IJCHM-05-2015-0238
  63. Wilson, A., Murphy, H., & Fierro, J. C. (2012). Hospitality and Travel The Nature and Implications of User-Generated Content. Cornell Hospitality Quarterly, 53(3), 220–228. https://doi.org/10.1177/1938965512449317
  64. Wong, D. K. K. F., & Chi-Yung, L. (2002). Predicting Hotel Choice Decisions and Segmenting Hotel Consumers: A Comparative Assessment of a Recent Consumer Based Approach. Journal of Travel & Tourism Marketing, 11(1), 17–33. https://doi.org/10.1300/J073v11n01_02
  65. Ye, Q., Law, R., & Gu, B. (2009). The impact of online user reviews on hotel room sales. International Journal of Hospitality Management, 28(1), 180–182. https://doi.org/10.1016/j.ijhm.2008.06.011
  66. 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
  67. Zhang, X., Yu, Y., Li, H., & Lin, Z. (2016). Sentimental interplay between structured and unstructured user-generated contents. Online Information Review, 40(1), 119-145. https://doi.org/10.1108/OIR-04-2015-0101
  68. Zhao, X. (Roy), 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
  69. 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