A Design Concept for a Tourism Recommender System for Regional Development

Author:

Gamidullaeva LeylaORCID,Finogeev Alexey,Kataev Mikhail,Bulysheva Larisa

Abstract

Despite of tourism infrastructure and software, the development of tourism is hampered due to the lack of information support, which encapsulates various aspects of travel implementation. This paper highlights a demand for integrating various approaches and methods to develop a universal tourism information recommender system when building individual tourist routes. The study objective is proposing a concept of a universal information recommender system for building a personalized tourist route. The developed design concept for such a system involves a procedure for data collection and preparation for tourism product synthesis; a methodology for tourism product formation according to user preferences; the main stages of this methodology implementation. To collect and store information from real travelers, this paper proposes to use elements of blockchain technology in order to ensure information security. A model that specifies the key elements of a tourist route planning process is presented. This article can serve as a reference and knowledge base for digital business system analysts, system designers, and digital tourism business implementers for better digital business system design and implementation in the tourism sector.

Funder

Russian Science Foundation (RSF) and Penza Oblast

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Reference79 articles.

1. (2022, August 27). Tourism Development Strategy of the Russian Federation until 2035, Available online: https://tourism.gov.ru/.

2. The impact of digital technologies on the development of the tourism market;Vishnevskaya;Res. Result. Bus. Serv. Technol.,2019

3. Intelligent tourism recommender systems: A survey;Moreno;Expert Syst. Appl.,2014

4. Mobile recommender systems in tourism;Gavalas;J. Netw. Comput. Appl.,2013

5. E-commerce and tourism;Werthner;Commun. ACM,2004

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