Fuzzy AHP and Fuzzy TOPSIS Methods for Fruit Tree Selection: The Case of İzmir

The application of fuzzy multi-criteria decision-making (MCDM) methods has become increasingly relevant in addressing the complexities of agricultural decision-making, particularly when multiple conflicting criteria are involved. This study investigates the selection of the most suitable fruit tree species for orchards in the Tire District of İzmir Province, Türkiye, by utilizing Fuzzy AHP and Fuzzy TOPSIS methodologies. The aim is to provide a systematic and robust framework to support long-term investment decisions in fruit cultivation. Five main criteria—economic viability, production and operational factors, environmental and regional suitability, social and support mechanisms, and market demand—were evaluated, along with 21 sub-criteria. The Fuzzy AHP results indicated that economic factors were the most critical, reflecting their importance in farmers' decision-making processes, while market and demand factors had the least impact. Among sub-criteria, "Government Incentives and Grants" emerged as the most influential, underscoring the importance of supportive policies in sustainable agriculture. Using Fuzzy TOPSIS, 12 fruit tree alternatives were ranked based on their proximity to an ideal solution. Olive (A2) was identified as the most suitable option, followed by fig (A1) and grape (A4). Sensitivity analysis confirmed the robustness of the framework, as the rankings of the top three alternatives remained stable across varying criteria Weights.This study contributes to the Turkish agricultural literature by demonstrating the practical application of fuzzy MCDM methods. It provides valuable insights for farmers, policymakers, and agricultural planners, underscoring the need for economic and policy support to promote sustainable agricultural practices. Future studies should explore dynamic frameworks to enhance decision-making adaptability.