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Tesi etd-09192017-231847


Tipo di tesi
Tesi di laurea magistrale
Autore
BORGHI, MATTEO
URN
etd-09192017-231847
Titolo
ONLINE REVIEWS' FINANCIAL LESSON: BOOKING.COM CASE
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA PER L'ECONOMIA E PER L'AZIENDA (BUSINESS INFORMATICS)
Relatori
relatore Prof. Pedreschi, Dino
relatore Prof. Buhalis, Dimitrios
relatore Prof. Mariani, Marcello Maria
controrelatore Prof. Mazzei, Daniele
Parole chiave
  • Hotels
  • Financial performance
  • Data analytics
  • Booking.com
  • Online reputation
  • Online reviews
Data inizio appello
06/10/2017
Consultabilità
Completa
Riassunto
Nowadays online product reviews are becoming a useful tool for customers to reduce their information gaps in their purchase decision-making process. This is particularly highlighted in the hotel industry where electronic word of mouth (e-WOM) plays a crucial role in travellers’ choice of hotel. The main goal of this study is to investigate whether there is a relationship between measures of financial
performance of London hotels and customer satisfaction measured through online hotel reviews. Part of the novelty is related to the online review platform chosen for the project, Booking.com, an online travel agency whose contents have not been studied in depth for the above mentioned kind of analysis. Based on a large unique dataset of 1’181’919 online consumer reviews on Booking.com over 23 months, matched with monthly hotel financial performance (ADR and RevPAR), this study finds that an increase in the score enhances future financial performance, whereas the overall volume of reviews is negatively correlated with the financial performance. The quality expressed during the evaluation of the service is more important than the mere quantity of user-generated content. Moreover, the number of helpful reviews and the volume of management response are found to influence in a positive and significant way the financial metrics. It is important for the hotel management to answer the online reviews and stimulate customers to write exhaustive contents that could be useful to guide the decision-making process of future travellers. Nevertheless, the hotel star rating plays a crucial role in the predictive models, dividing in different performance levels the analysed population of hotels. The study findings highlight the peculiarity of the user-generated content in Booking.com and generate a set of metrics to be taken into account by the hotel management during their interaction with the studied online travel agency.
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