We investigate the empirical phenomenon of rating bubbles, that is, the presence of a disproportionate number of extremely positive ratings in user-generated content websites. We test whether customers are influenced by prior ratings when evaluating their stay at a hotel through a field experiment that exogenously manipulates information disclosure. Results show the presence of (asymmetric) social influence bias (SIB): access to information on prior ratings that are above the average positively influences the consumers’ rating of the hotel. In contrast, information on ratings that are below the average does not affect reviewers. Furthermore, customers who have never been to the hotel before the intervention are more susceptible to prior ratings than customers who have repeatedly been to the hotel before. Finally, customers who are not used to writing online reviews are more prone to SIB than customers who frequently write online reviews. Our findings suggest that online rating systems should be adjusted to mitigate this bias, especially as these platforms become more relevant and widespread in the hospitality sector.

Cicognani, S., Figini, P., Magnani, M. (2022). Social influence bias in ratings: A field experiment in the hospitality sector. TOURISM ECONOMICS, 28(8), 2197-2218 [10.1177/13548166211034645].

Social influence bias in ratings: A field experiment in the hospitality sector

Figini, Paolo
;
2022

Abstract

We investigate the empirical phenomenon of rating bubbles, that is, the presence of a disproportionate number of extremely positive ratings in user-generated content websites. We test whether customers are influenced by prior ratings when evaluating their stay at a hotel through a field experiment that exogenously manipulates information disclosure. Results show the presence of (asymmetric) social influence bias (SIB): access to information on prior ratings that are above the average positively influences the consumers’ rating of the hotel. In contrast, information on ratings that are below the average does not affect reviewers. Furthermore, customers who have never been to the hotel before the intervention are more susceptible to prior ratings than customers who have repeatedly been to the hotel before. Finally, customers who are not used to writing online reviews are more prone to SIB than customers who frequently write online reviews. Our findings suggest that online rating systems should be adjusted to mitigate this bias, especially as these platforms become more relevant and widespread in the hospitality sector.
2022
Cicognani, S., Figini, P., Magnani, M. (2022). Social influence bias in ratings: A field experiment in the hospitality sector. TOURISM ECONOMICS, 28(8), 2197-2218 [10.1177/13548166211034645].
Cicognani, Simona; Figini, Paolo; Magnani, Marco
File in questo prodotto:
File Dimensione Formato  
Figini23a+TE+21+postprint.pdf

accesso aperto

Tipo: Postprint
Licenza: Licenza per accesso libero gratuito
Dimensione 912.67 kB
Formato Adobe PDF
912.67 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/865004
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 5
social impact