Prioritizing Matcha Green Tea Production Criteria by Logarithmic Fuzzy FUCOM with Z-Numbers
Received: 31 December 2025 | Revised: 30 January 2026 and 19 February 2026 | Accepted: 4 March 2026 | Online: 4 April 2026
Corresponding author: Busaba Phruksaphanrat
Abstract
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.
Keywords:
LF-Z-FUCOM, Multi-Criteria Decision-Making (MCDM), Z-numbers, matcha production, fuzzy evaluationDownloads
References
J. Wu et al., "Physicochemical indicators coupled with multivariate analysis for comprehensive evaluation of matcha sensory quality," Food Chemistry, vol. 371, Mar. 2022, Art. no. 131100. DOI: https://doi.org/10.1016/j.foodchem.2021.131100
J. H. Ye et al., "A comprehensive review of matcha: production, food application, potential health benefits, and gastrointestinal fate of main phenolics," Critical Reviews in Food Science and Nutrition, vol. 64, no. 22, pp. 7959–7980, Aug. 2024. DOI: https://doi.org/10.1080/10408398.2023.2194419
Y. Q. Phuah, S. K. Chang, W. J. Ng, M. Q. Lam, and K. Y. Ee, "A review on matcha: Chemical composition, health benefits, with insights on its quality control by applying chemometrics and multi-omics," Food Research International, vol. 170, Aug. 2023, Art. no. 113007. DOI: https://doi.org/10.1016/j.foodres.2023.113007
S. Ahmed and J. R. Stepp, "Green Tea," in Tea in Health and Disease Prevention, Elsevier, 2013, pp. 19–31. DOI: https://doi.org/10.1016/B978-0-12-384937-3.00002-1
S. Yao, Z. Jiang, N. Li, H. Zhang, and N. Geng, "A multi-objective dynamic scheduling approach using multiple attribute decision making in semiconductor manufacturing," International Journal of Production Economics, vol. 130, no. 1, pp. 125–133, Mar. 2011. DOI: https://doi.org/10.1016/j.ijpe.2010.12.014
Ž. Stević, E. K. Zavadskas, F. M. O. Tawfiq, F. Tchier, and T. Davidov, "Fuzzy Multicriteria Decision-Making Model Based on Z Numbers for the Evaluation of Information Technology for Order Picking in Warehouses," Applied Sciences, vol. 12, no. 24, Dec. 2022, Art. no. 12533. DOI: https://doi.org/10.3390/app122412533
A. Mao et al., "Effects of roasting treatment on non‐volatile compounds and taste of green tea," International Journal of Food Science & Technology, vol. 53, no. 11, pp. 2586–2594, Nov. 2018. DOI: https://doi.org/10.1111/ijfs.13853
B. Ozturk et al., "Change of enzyme activity and quality during the processing of Turkish green tea," LWT, vol. 65, pp. 318–324, Jan. 2016. DOI: https://doi.org/10.1016/j.lwt.2015.07.068
Q. Xu et al., "Economic, environmental, and emergy analysis of China’s green tea production," Sustainable Production and Consumption, vol. 28, pp. 269–280, Oct. 2021. DOI: https://doi.org/10.1016/j.spc.2021.04.019
Y. Huang et al., "Effect of three milling processes (cyclone-, bead- and stone-millings) on the quality of matcha: Physical properties, taste and aroma," Food Chemistry, vol. 372, Mar. 2022, Art. no. 131202. DOI: https://doi.org/10.1016/j.foodchem.2021.131202
H. Wang, M. Tao, H. Zhang, S. Cheng, L. Zhang, and Z. Liu, "The mechanism on decreasing the microbiological contamination of superfine green tea powder by ball milling," LWT, vol. 134, Dec. 2020, Art. no. 109966. DOI: https://doi.org/10.1016/j.lwt.2020.109966
H. Nobari, S. Saedmocheshi, L. H. Chung, K. Suzuki, M. Maynar-Mariño, and J. Pérez-Gómez, "An Overview on How Exercise with Green Tea Consumption Can Prevent the Production of Reactive Oxygen Species and Improve Sports Performance," International Journal of Environmental Research and Public Health, vol. 19, no. 1, Dec. 2021, Art. no. 218. DOI: https://doi.org/10.3390/ijerph19010218
Z. Guo et al., "Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy," Food Chemistry, vol. 353, Aug. 2021, Art. no. 129372. DOI: https://doi.org/10.1016/j.foodchem.2021.129372
A. Bakhshipour, H. Zareiforoush, and I. Bagheri, "Application of decision trees and fuzzy inference system for quality classification and modeling of black and green tea based on visual features," Journal of Food Measurement and Characterization, vol. 14, no. 3, pp. 1402–1416, June 2020. DOI: https://doi.org/10.1007/s11694-020-00390-8
H. D. Arora and A. Naithani, "Significance of TOPSIS approach to MADM in computing exponential divergence measures for pythagorean fuzzy sets," Decision Making: Applications in Management and Engineering, vol. 5, no. 1, pp. 146–263, Mar. 2022. DOI: https://doi.org/10.31181/dmame211221090a
C. Bai and J. Sarkis, "A critical review of formal analytical modeling for blockchain technology in production, operations, and supply chains: Harnessing progress for future potential," International Journal of Production Economics, vol. 250, Aug. 2022, Art. no. 108636. DOI: https://doi.org/10.1016/j.ijpe.2022.108636
E. Ilbahar, S. Cebi, and C. Kahraman, "A state-of-the-art review on multi-attribute renewable energy decision making," Energy Strategy Reviews, vol. 25, pp. 18–33, Aug. 2019. DOI: https://doi.org/10.1016/j.esr.2019.04.014
S. Biswas, D. Pamucar, S. Kar, and S. S. Sana, "A New Integrated FUCOM–CODAS Framework with Fermatean Fuzzy Information for Multi-Criteria Group Decision-Making," Symmetry, vol. 13, no. 12, Dec. 2021, Art. no. 2430. DOI: https://doi.org/10.3390/sym13122430
N. M. F. H. N. B. Alam, K. M. N. Ku Khalif, N. I. Jaini, and A. Gegov, "The Application of Z-Numbers in Fuzzy Decision Making: The State of the Art," Information, vol. 14, no. 7, July 2023, Art. no. 400. DOI: https://doi.org/10.3390/info14070400
S. Ashraf, M. Naeem, C. Jana, M. Akram, and G. W. Weber, "Multi-criteria group decision-making method using Spherical Fuzzy Z-Numbers for smart technology revolution in municipal waste management," Engineering Applications of Artificial Intelligence, vol. 161, Dec. 2025, Art. no. 111928. DOI: https://doi.org/10.1016/j.engappai.2025.111928
H. J. Shyur, "Combination weighting method using Z-numbers for multi-criteria decision-making," Applied Soft Computing, vol. 174, Apr. 2025, Art. no. 112992. DOI: https://doi.org/10.1016/j.asoc.2025.112992
A. Shahid, S. Ashraf, and M. S. Chohan, "Complex Fuzzy MARCOS and WASPAS Approaches with Z-Numbers for Augmented Reality Decision Making," Spectrum of Operational Research, vol. 3, no. 1, pp. 40–62, Jan. 2026. DOI: https://doi.org/10.31181/sor31202637
C. Musial, A. Kuban-Jankowska, and M. Gorska-Ponikowska, "Beneficial Properties of Green Tea Catechins," International Journal of Molecular Sciences, vol. 21, no. 5, Mar. 2020, Art. no. 1744. DOI: https://doi.org/10.3390/ijms21051744
S. Zhang et al., "Development and Validation of Near-Infrared Methods for the Quantitation of Caffeine, Epigallocatechin-3-gallate, and Moisture in Green Tea Production," Journal of Analytical Methods in Chemistry, vol. 2021, pp. 1–12, Nov. 2021. DOI: https://doi.org/10.1155/2021/9563162
M. Z. Islam, Y. Kitamura, M. Kokawa, and S. Fujii, "Processing of green tea pastes by micro wet milling system: Influences on physicochemical and functional properties," Innovative Food Science & Emerging Technologies, vol. 64, Aug. 2020, Art. no. 102408. DOI: https://doi.org/10.1016/j.ifset.2020.102408
C. Someswararao and P. P. Srivastav, "A novel technology for production of instant tea powder from the existing black tea manufacturing process," Innovative Food Science & Emerging Technologies, vol. 16, pp. 143–147, Oct. 2012. DOI: https://doi.org/10.1016/j.ifset.2012.05.005
D. Pamucar and F. Ecer, "Prioritizing the Weights of the Evaluation Criteria Under Fuzziness: The Fuzzy Consistency Method - FUCOM-F," Facta Universitatis, Series: Mechanical Engineering, vol. 18, no. 3, Oct. 2020, Art. no. 419. DOI: https://doi.org/10.22190/FUME200602034P
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