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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Fernandes, E., Moro, S., Cortez, P., Batista, F. & Ribeiro, R. (2021). A data-driven approach to measure restaurant performance by combining online reviews with historical sales data. International Journal of Hospitality Management. 94
Exportar Referência (IEEE)
E. D. Fernandes et al.,  "A data-driven approach to measure restaurant performance by combining online reviews with historical sales data", in Int. Journal of Hospitality Management, vol. 94, 2021
Exportar BibTeX
@article{fernandes2021_1618114364388,
	author = "Fernandes, E. and Moro, S. and Cortez, P. and Batista, F. and Ribeiro, R.",
	title = "A data-driven approach to measure restaurant performance by combining online reviews with historical sales data",
	journal = "International Journal of Hospitality Management",
	year = "2021",
	volume = "94",
	number = "",
	doi = "10.1016/j.ijhm.2020.102830",
	url = "https://www.sciencedirect.com/journal/international-journal-of-hospitality-management"
}
Exportar RIS
TY  - JOUR
TI  - A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
T2  - International Journal of Hospitality Management
VL  - 94
AU  - Fernandes, E.
AU  - Moro, S.
AU  - Cortez, P.
AU  - Batista, F.
AU  - Ribeiro, R.
PY  - 2021
SN  - 0278-4319
DO  - 10.1016/j.ijhm.2020.102830
UR  - https://www.sciencedirect.com/journal/international-journal-of-hospitality-management
AB  - Restaurant management requires customer responsiveness to deal with increasingly higher expectations and market competitiveness. This study proposes an approach to simplify the decision-making process of restaurant managers by combining both live social media customer feedback and historical sales data in a sales forecast model (based on TripAdvisor data and the Bass model).
Our approach was validated with internal and external (i.e., online reviews) data gathered from six restaurants. The collected data was processed using data analytics for developing a dashboard that provides value for restauranteurs by taking advantage of online reviews and sales forecast. Such dashboard was evaluated by restaurant management experts, which provided positive feedback, highlighting in particular the time saved in the decision-making process.
ER  -