TY - JOUR
T1 - Innovative value-based price assessment in data-rich environments
T2 - Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs
AU - Boccali, Filippo
AU - Mariani, Marcello M.
AU - Visani, Franco
AU - Mora-Cruz, Alexandra
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/9
Y1 - 2022/9
N2 - This work introduces, develops, and empirically applies an innovative approach aimed at assessing selling prices based on the value perceived by the customers, as measured by electronic word-of-mouth (eWOM) in the guise of online reviews. To achieve this aim, it applies a constant return to scale Data Envelopment Analysis (DEA) approach where the price is the input, and the value attributes are the outputs measured through eWOM in the form of online reviews. We empirically apply the model to the hotel sector by considering both the prices and the service attributes (i.e., staff, location, cleanliness, comfort, facilities and free wi-fi) of 364 hotels based in two leading Italian tourism destinations: Milan and Rome. Our findings suggest that online review analytics can be suitably embedded into analytical models to assess prices. The index developed innovatively supports value-based pricing by means of online review analytics and it is easy-to-perform, and parsimonious as it is based on widely available information on the Internet.
AB - This work introduces, develops, and empirically applies an innovative approach aimed at assessing selling prices based on the value perceived by the customers, as measured by electronic word-of-mouth (eWOM) in the guise of online reviews. To achieve this aim, it applies a constant return to scale Data Envelopment Analysis (DEA) approach where the price is the input, and the value attributes are the outputs measured through eWOM in the form of online reviews. We empirically apply the model to the hotel sector by considering both the prices and the service attributes (i.e., staff, location, cleanliness, comfort, facilities and free wi-fi) of 364 hotels based in two leading Italian tourism destinations: Milan and Rome. Our findings suggest that online review analytics can be suitably embedded into analytical models to assess prices. The index developed innovatively supports value-based pricing by means of online review analytics and it is easy-to-perform, and parsimonious as it is based on widely available information on the Internet.
KW - Big data
KW - Data Envelopment Analysis
KW - Electronic word of mouth (eWOM)
KW - Innovation
KW - Online reviews analytics
KW - Price assessment
UR - http://www.scopus.com/inward/record.url?scp=85132536266&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2022.121807
DO - 10.1016/j.techfore.2022.121807
M3 - Artículo
AN - SCOPUS:85132536266
SN - 0040-1625
VL - 182
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 121807
ER -