Naslov
Artificial neural networks implementation potentials - a literature review

Autori
Mamula, Maja ; Duvnjak, Kristina

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceeding of the 2nd International statistical conference in Croatia - ISCCRO'18 / Dumičić, Ksenija ; Erjavec, Nataša ; Pejić Bach, Mirjana ; Žmuk, Berislav - Zagreb : Hrvatsko statističko društvo, 2018, 86-93

Skup
2nd International Statistical Conference in Croatia (ISCCRO 2018)

Mjesto i datum
Opatija, Hrvatska, 10.05.2018. - 11.05.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
artificial neural networks ; modelling and forecasting ; tourism

Sažetak
The significant worldwide growth of the tourism sector in the two past decades resulted in an increased number of researches and studies of tourism industry determinants. In analysing and modelling core tourism components, mostly using secondary data, different methods and technique are applied ; different forecast models are constructed and compared using different forecast error measures. The aim of this research is to provide a detailed outline of different quantitative methods and techniques, both the traditional ones as well as some emerging most sophisticated methods used in modelling and forecasting tourism. Beside the various methods, there is a large variety of explanatory variables selection in constructing forecast models and explaining some core tourism industry components. This paper reviews the published researches and studies that use the Artificial Neural Networks in modelling and forecasting tourism industry. The most significant finding that resulted from the detailed desk research is that, beside their great implementation potentials, Artificial Neural Networks are underused in tourism analysing, although their forecast efficiency excel the usual traditional models.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija

Napomena
This paper has been financially supported by the
University of Rijeka, for the project ZP UNIRI 4/17.

POVEZANOST RADA