Modelling Buying Demand in the Tourism Industry based on Machine Training Methods
Viktoriya Tkach1, Anatolii Pavlenchyk2, Оlena Sadchenko3, Svetlana Nikola4, Valeriia Drozdova5, Iryna Davydenko6 

1ViktoriyaTkach, Department of International Tourism, Hotel & Restaurant Business and Language Training Alfred Nobel University Dnipro, Ukraine
2AnatoliiPavlenchyk, Department of Economics and Management Lviv State University of Physical Culture Lviv, Ukraine
3ОlenaSadchenko, Department of Marketing and Business Administration Odessa I.I. Mechnikov National University Odessa, Ukraine
4Svetlana Nikola, Department of Finance, Banking and Insurance Odessa I.I. Mechnikov National University Odessa, Ukraine
5ValeriiaDrozdova, Department of Management and Logistics Odessa National Academy of Food Technologies Odessa, Ukraine
6Iryna Davydenko, Department of Tourism, Hotel and Restaurant Business Odessa National Economic University, Odessa, Ukraine

Manuscript received on 07 March 2019 | Revised Manuscript received on 15 March 2019 | Manuscript published on 30 July 2019 | PP: 744-747 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1800078219/19©BEIESP | DOI: 10.35940/ijrte.B1800.078219
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Abstract: The business processes of companies in the tourism industry lend themselves well to formalization and, consequently, computer automation. This study focuses on the process of creating a demand forecast model for a travel agent based on data mining algorithms. The program code was developed in the Anaconda development environment, which allows to process the initial data and to give the prediction results for two indicators of MAE and program accuracy. The program code is designed to improve the performance of the entire system by selecting the correct functions.
Index Terms: ARIMA, Box-Jenkins model, buying demand, machine training, tourism industry.

Scope of the Article: Machine Design