Knowledge management in tourism: Leveraging Fuzzy modelling to understand and predict tourist behaviour in the V4 countries

Abstract

Research background: Although knowledge management has become one of the most discussed concepts in management, its application in tourism—both at the organizational and destination levels—remains limited. Existing literature highlights potential benefits of knowledge management for improving tourist experiences, yet empirical evidence in the tourism sector is scarce compared to other industries.

Purpose of the article: The main goal of this study is to develop a fuzzy assessment model and derive the level of the possibility of repeated visits to the region by participants of the tourist movement in the Visegrad Group countries (the Czech Republic, Hungary, Poland, Slovakia).

Methods: A fuzzy sets and fuzzy logic-based model was applied to evaluate tourist satisfaction, regional infrastructure, and digital popularity, which allowed deriving quantitative and linguistic predictions of repeated visits.

Findings & value added: The research provides a novel, data-driven method for evaluating tourism performance from the perspective of tourist satisfaction and regional attractiveness. It highlights the interplay between infrastructure, accessibility, and digital visibility in shaping repeated visit behaviour. This approach offers actionable insights for policymakers, destination managers, and tourism organizations seeking to optimize strategies for sustainable tourism growth. The study contributes to the broader knowledge management discourse by demonstrating how fuzzy logic models can capture complex human perceptions and decision-making processes in tourism.

Keywords

knowledge management, consumer behavior, tourism industry, fuzzy modeling, decision-making

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