Pregled bibliografske jedinice broj: 252191
Predicting customer satisfaction in hotel industry using neural networks
Predicting customer satisfaction in hotel industry using neural networks // Economic Development, 1, 2 i 3 (2005), 93-106 (podatak o recenziji nije dostupan, članak, znanstveni)
CROSBI ID: 252191 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Predicting customer satisfaction in hotel industry using neural networks
Autori
Horvat, Jasna ; Hristovska, Ljubica ; Zekić-Sušac, Marijana ; Marković, Suzana
Izvornik
Economic Development (1409-7893) 1, 2 i 3
(2005);
93-106
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
customer statisfaction; neural networks; predicting; hotel industry; service quality
Sažetak
Customer satisfaction with the service quality is one of the key factors of the hotel industry successfulness. The paper investigates the ability of neural networks in predicting customer satisfaction in five Croatian hotels using neural networks. The accuracy of neural network models regarding different customer satisfaction measurements is also examined. The first model uses a seven-point Lickert scale, while the second model is based on a binary output variable. The backpropagation multi-layer perceptron is used as a neural network algorithm. The results show that the neural networks produce better accuracy on the second model, and therefore can be suggested as an effective tool for classifying the customers into satisfied and unsatisfied ones. The analysis of type I and type II errors show that the model classifies satisfied customers with better accuracy that unsatisfied customers. The results should be useful to researchers as well as hotel managers in improving the quality of their services.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
POVEZANOST RADA
Projekti:
0010016
Ustanove:
Ekonomski fakultet, Osijek,
Fakultet za menadžment u turizmu i ugostiteljstvu, Opatija