A Pythagorean Fuzzy Approach to Identify and Prioritize Factors Affecting Import Decisions in Wood Supply Chain

Wood is a highly sought-after commodity traded internationally to meet the global demand for building materials, furniture, and paper products. The decision-making process for wood imports is intricate and influenced by various factors. Prioritizing these factors helps decision-makers allocate resources, time, and attention efficiently and make well-informed and strategically effective decisions. This study proposes an interval- valued Pythagorean fuzzy analytic hierarchy process (AHP)-based decision-making framework to identify and analyze factors influencing wood import decisions. With the aim in mind, four main factors are determined: “economic factors”, “political factors”, “material-related factors”, and “market factors”. Each main factor has four sub-factors. The interval-valued Pythagorean fuzzy AHP method reveals the weight of each factor based on experts’ perspectives. According to the results, the most important main factor is “economic factors”. The sub-factors with the highest local importance are: “supply chain and logistics management” in the “economic factors” group, “political stability” in the “political factors” group, “wood species” in the “material-related factors” group, and “demand and demand trends” in the “market factors” group. The global weights show that the most important sub-factors are “supply chain and logistics management”, “political stability”, and “wood species”. The model’s robustness is assessed through sensitivity, validity, and comparative analyses, and high stability is observed in the ranking of the factors.