Choosing between hotels: impact of bimodal rating summary statistics and maximizing behavioral tendency
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Choosing between hotels: impact of bimodal rating summary statistics and maximizing behavioral tendency Ludovik Coba1 · Laurens Rook2 · Markus Zanker1 Received: 28 June 2019 / Revised: 7 October 2019 / Accepted: 21 October 2019 © The Author(s) 2019
Abstract Rating summary statistics are basic aggregations that reflect users’ assessments of experienced products and services in numerical form. Thus far, scholars primarily investigated textual reviews, but dedicated considerably less time and effort exploring the potential impact of plain rating summary statistics on people’s choice behavior. Notwithstanding their fundamental nature, however, rating summary statistics also are relevant to electronic commerce in general, and to e-tourism in particular. In this work, we attempted to fill this void, by exploring the effects of different types of rating attributes (the mean rating value, the overall number of ratings, and the bimodality of rating distributions) on hotel choice behavior. We also investigated whether individual differences in the cause of people’s maximizing behavioral tendency moderated the effect of rating summary statistics on hotel choice behavior. Results of an eye-tracked conjoint experiment show that people’s high or low on decision difficulty as the cause of maximization determined whether and how rating summary statistics have an impact on the choice between hotels. Implications for the tourism and hospitality domain are addressed. Keywords e-Tourism · Rating summaries · Maximization · Conjoint analysis · Eye-tracking · Recommender systems · eWOM
* Markus Zanker [email protected] Ludovik Coba [email protected] Laurens Rook [email protected] 1
Free University of Bozen-Bolzano, Piazza Domenicani 3, 39100 Bolzano, Italy
2
Delft University of Technology, Jaffalaan 5, Delft, The Netherlands
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1 Introduction Online customer ratings and reviews were coined ’novel components of the marketing communication mix’ about a decade ago (Chen and Xie 2008). Nowadays, due to the omnipresence of Web 2.0-based information technologies and applications in everyday life, user-produced and customer-shared evaluations of products and services have, indeed, become an essential ingredient of electronic commerce. Considerable evidence has been generated for their impact on sales and customer’s purchase behavior for a wide range of products and services (De Maeyer 2012; Zhu and Zhang 2010). Customer ratings and reviews also are important factors in today’s tourism and hospitality landscape—especially on the web platforms of online travel agencies (OTAs), cf. Gavilan et al. (2018). Competition on such web platforms is severe, due to the saturation of the market (Xiang et al. 2015). Moreover, tourism products are so-called ’experience goods’ that are simultaneously delivered and experienced. This unique feature renders them highly variable in terms of experienced quality, and complicated to assess for the interested traveller prior to purchase (Chevalier et al. 2018). This has le
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