Prioritizing Matcha Green Tea Production Criteria by Logarithmic Fuzzy FUCOM with Z-Numbers - Phruksaphanrat, Busaba; Panjavongroj, Saruntorn; Jarernsuk, Saran (Engineering, Technology & Applied Science Research, 2026)
The rapid growth of the global matcha market requires manufacturers to develop systematic tools for production planning under uncertainty. Matcha manufacturing involves multiple interdependent criteria, including cost, tea raw material quality, physicochemical properties, sensory attributes, and dissolvability, each contributing differently to overall product performance and consumer acceptance. Experts' opinions are not only vague but also differ in reliability, which limits the effectiveness of conventional Multi-Criteria Decision-Making (MADM) methods that treat all expert opinions equally. To address this limitation, this paper presents the Logarithmic Fuzzy Full Consistency Method with Z-numbers (LF-Z-FUCOM), which integrates fuzzy sets, logarithmic preference programming, and Z-numbers into a unified weighting framework. The proposed method allows both the importance of criteria and the confidence level of expert assessments to be incorporated directly into the weight estimation process. A real-world case study was conducted on matcha green tea production in Thailand. The results are compared with those obtained from the conventional FUCOM and Fuzzy FUCOM methods. The findings demonstrate that LF-Z-FUCOM provides more discriminative and reliability-consistent criterion weights, clearly identifying cost (0.3208) and tea raw material quality (0.2829) as the dominant factors, whereas FUCOM and Fuzzy FUCOM fail to sufficiently separate closely ranked criteria. The proposed method improves decision transparency, consistency, and managerial interpretability in uncertain multi-criteria environments.