Economic Growth Assessment through Tourism Development Using the Type-2 Fuzzy Multi-Criteria Decision-Making Method

Abstract

Tourism development plays a significant role in stimulating economic growth by promoting investment, job creation, and regional development. Assessing the impact of tourism on economic growth involves complex decision-making processes characterized by uncertainty, subjectivity, and imprecise expert judgments. To address these challenges, this study proposes a framework for evaluating the economic growth of tourism development using a Type-2 fuzzy set method. The proposed approach utilizes linguistic expert judgments and models the associated uncertainty using Type 2 fuzzy sets. This allows for a more realistic representation of ambiguities compared to traditional Type-1 fuzzy methods. Key tourism-related criteria, including infrastructure development, service quality, accessibility, investment intensity, and socioeconomic impacts, are systematically analyzed and weighed within the framework. The aggregation and defuzzification processes enable the prioritization of tourism development factors according to their contribution to economic growth. A case study serves to validate the applicability and effectiveness of the methodology. The results demonstrate that the Type-2 fuzzy logic approach yields more robust and reliable estimates, thereby supporting policymakers and stakeholders in developing effective tourism development strategies that promote sustainable economic growth in the face of uncertainty.