Online ratings provide valuable information to operators. However, the use of this information for revenue maximization purposes remains at a moot point. This article proposes a new method to decompose ratings based on their relevance to hotel performance. From a methodological standpoint, we propose a multi-criteria decision analysis approach. The empirical validation includes two independent data sources, online ratings from Booking.com and RevPAR data from STR. By means of pairwise comparisons in PROMETHEE, the findings reveal the different weights of individual ratings, helping operators to understand the weight of each rating attribute in terms of revenue maximization. In particular, apart from the importance of the location, the role of staff and facilities emerge as central in terms of revenue maximization. The proposed model offers new theoretical insights on the relevant dimensions, helping hoteliers to prioritize when making trade-off decisions.
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.ijhm.2018.09.002|
|Codice identificativo ISI:||WOS:000457510800060|
|Codice identificativo Scopus:||2-s2.0-85053674820|
|Titolo:||The dimensions of hotel customer ratings that boost RevPAR|
|Appare nelle tipologie:||1.1 Articolo in rivista|