Combining the power of artificial intelligence and mathematical modelling: A hybrid technique for enhanced forecast of tourism receipts

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dc.contributor.authorSeker, Ferhat
dc.date.accessioned2025-01-06T17:36:26Z
dc.date.available2025-01-06T17:36:26Z
dc.date.issued2024
dc.description.abstractDespite being one of the most visited countries in the world, Turkiye's share of tourism revenue does not rank among the top ten. Therefore, it would be worth researching tourist expenditures and analysing this data could provide valuable insights. This research develops a novel approach to estimating and modelling tourism receipts by analysing expenditure types. Artificial intelligence-based methods, such as machine learning, have been increasingly used in the tourism literature to improve various aspects of the industry. However, little research has been conducted using a hybrid method to model and estimate tourist expenditure. This paper is the first to combine conventional mathematical analysis, specifically first-order two-variable polynomial equations, with artificial intelligence-based machine learning algorithms in a tourism setting. The research results indicate that expenditure types such as accommodation and food & beverage significantly impact Turkiye's tourism revenue and Turkiye's total tourism revenue will not exceed 45 billion dollars by 2027. This study provides a valuable and practical contribution to improving the accuracy and efficiency of methods for managing tourism economics, particularly in European countries where the economy heavily relies on income generated by tourism. Additionally, it fills a gap in studies focused on tourists' expenditure types by combining artificial intelligence and traditional analysis, making it a unique piece of research.
dc.identifier.doi10.54055/ejtr.v36i.3246
dc.identifier.issn1994-7658
dc.identifier.issn1314-0817
dc.identifier.scopus2-s2.0-85176234317
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.54055/ejtr.v36i.3246
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1882
dc.identifier.volume36
dc.identifier.wosWOS:001103018900008
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherVarna Univ Management-Vum
dc.relation.ispartofEuropean Journal of Tourism Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectArtificial Intelligence
dc.subjectMachine Learning
dc.subjectCorrelation-Based Feature Selection
dc.subjectRandom Forest Algorithm
dc.subjectTourist Expenditure Types
dc.titleCombining the power of artificial intelligence and mathematical modelling: A hybrid technique for enhanced forecast of tourism receipts
dc.typeArticle

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