Open AccessHotels competition based on online ranking position
Author(s) -
Juan Pedro Aznar-Alarcón,
Bernat Palacín,
Josep Maspera
Publication year - 2020
Publication title -
european journal of tourism research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.467
H-Index - 16
eISSN - 1314-0817
pISSN - 1994-7658
DOI - 10.54055/ejtr.v26i.1940
Subject(s) - reputation , ranking (information retrieval) , competition (biology) , position (finance) , context (archaeology) , marketing , sample (material) , quality (philosophy) , business , value (mathematics) , variable (mathematics) , service quality , service (business) , economics , econometrics , microeconomics , statistics , computer science , mathematics , finance , social science , philosophy , ecology , mathematical analysis , chemistry , sociology , biology , paleontology , epistemology , chromatography , machine learning
Electronic word of mouth (eWOM) information has become extremely relevant for the reputation of hotels and is a key variable in terms of their capacity to set prices and improve their occupancy rate. However, overall ratings have a bias towards high values; luxury hotels concentrate on a few ranges of values in terms of their rating, making it more difficult for consumers to differentiate among these hotels. In this context, the ranking position that is unique for each hotel is an additional source of information for potential consumers, and it can have a direct impact on the hotel managers’ capacity for setting higher prices. This research proposes a theoretical model of vertical differentiation that adds the ranking position as a part of demand function and analyses the optimum strategy in terms of quality investment and prices for hotels in a given destination. The model is empirically tested using a sample of 102 hotels from the city of Barcelona. Our results suggest that the ranking position has a direct effect on higher prices and that this effect is more important and significant than the effects of rating value or the number of stars on prices.