Analysis of Factors Influencing the Prices of Tourist Offers
Source abstract
Abstract
Tourism is a significant branch of many world economies. Many factors influence the volume of tourist traffic and the prices of trips. There are factors that clearly affect tourism, such as COVID-19. The paper describes the methods of machine learning and process mining that allow for assessing the impact of various factors (micro, mezzo and macro) on the prices of tourist offers. The methods were used on large sets of real data from two tour operators, and the results of these studies are discussed in this paper. The research presented is part of a larger project aiming at predicting trip prices. It answers the question of which factors have the greatest impact on the price and which can be omitted in further work. Nevertheless, the dynamic world situation suggests that the ranking of factors may change and the presented universal methods may provide different results in the coming years.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Wine Industry and Tourism · Business Strategy and Innovation · Statistical and Computational Modeling
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Intelligent Interactive Systems, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, Poland
Funding
National Centre for Research and Development · ETI Faculty, Gdansk University of Technology
References (39)
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