Good advice is rarer than rubies: A study on online Tripadvisor hotel reviews

User-generated content websites, such as review sites or travel communities, have become a major source of information for travelers with the advent of Web 2.0. A recent study [1] showed that more than 40% of travelers use the reviews and comments of other consumers as information sources when planning trips. While many studies have investigated the use and influence of online reviews on consumers, less is known about what motivates travelers to write online reviews. According to the results of the Yoo & Gretze's survey [2], based on a panel of TripAdvisor reviewers, the motivation to write online travel reviews is accounted for by four dimensions: Enjoyment/positive self- enhancement, Venting negative feelings, Concerns for other consumers, and Helping the company. As a consequence, the motivation to review should be high after extremely good outcomes (due to enjoyment in sharing a good experience, helping the company that provided a good travel service) and extremely bad experiences (owing to engagement in negative word-of-mouth to warn others, see also [3]), and low after intermediate/neutral experiences. In this study we adopted a data-driven approach in order to test the empirical robustness of such an expectation. Specifically, we investigated the motivation to write online travel reviews, by analyzing a publicly available world-wide dataset of 246,399 user generated hotel reviews posted on TripAdvisor [4]. Following on the expectation rising from the four dimension model of motivation proposed by [2], if reviewers are highly motivated to write after extremely good and extremely bad experiences, the distribution of overall hotel ratings (ranging from 1 “bubble”, labeled as “terrible”, to 5 “bubbles”, labeled as “excellent”) should be expected to be U-shaped, with central ratings being less represented than extreme values (1 “bubble” and 5 “bubbles”). The empirical distribution of ratings showed instead that the most represented ratings were 5 and 4 “bubbles” (accounting for 75% of all ratings), thus reflecting the fact that the majority of reviewers judged their experience in a monotonic continuum from very good to excellent. The same pattern of results emerged also in sub- ratings (business service – 63%, cleanliness – 81%, front desk – 75%, location – 84%, rooms – 73%, service – 75%, and value – 73%). The monotonic pattern of responses revealed by our study demonstrated that engaging in negative word-of-mouth to vent negative feelings and to warn others may not be an important motivation for writing online reviews. We speculate that monotonicity could results from a positivity bias in remembering and evaluating hedonic experiences [5]. Acknowledgment: This research was supported by the University of Trieste FRA 2013 grant to CF. TSPC2015 November, 13th – P42 1. Xiang Z, Wang D, O'Leary JT, Fesenmaier DR. (2015). Adapting to the internet. Trends in travelers’ use of the web for trip planning. Journal of Travel Research, 54:511-527. 2. Yoo KH, Gretzel U. (2008). What motivates consumers to write online travel reviews? Information Technology & Tourism, 10: 283-295. 3. Wetzer IM, Zeelenberg M, Pieters R. (2007). “Never eat in that restaurant, I did!”: Exploring why people engage in negative word‐of‐mouth communication. Psychology & Marketing, 24: 661-680. 4. Wang H, Lu Y, Zhai C. (2011). Latent aspect rating analysis without aspect keyword supervision. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 618-626). 5. Wirtz D, Kruger J, Scollon CN, Diener E. (2003). What to do on spring break? The role of predicted, on-line, and remembered experience in future choice. Psychological Science, 14: 520-524.