Abstract
The importance of multi-criteria group decision-making techniques in today’s complex decision-making environment is undeniable. In complex decision problems, the determination of criteria weights is often subject to both DM-related uncertainty and external event-related uncertainty. The Fuzzy Best-Worst Method (FBWM), as a widely applied MCDM technique based on pairwise comparisons under the fuzzy environment, has been recognized for its systematic expert data collection process, reduced pairwise comparison steps, and high result consistency. Considering the impact of future events on current decision criteria is also necessary in practice. The concept of stratification (CST) provides a fresh perspective on the stratified decision-making process in the MCDM domain. However, the integration of CST with MCDM methods is still in its infancy. Specifically, there is a lack of exploration in the implementation process of FBWM under CST in a group decision-making environment. To address this gap, this study proposes a stratified fuzzy best-worst group decision-making framework. This study aims to promote human-centric decision-making by incorporating advanced decision-making techniques to facilitate efficient decision implementation. An illustrative numerical example is provided in this paper to demonstrate the applicability of the proposed framework.
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The authors would like to thank the Research and Innovation Office of the Hong Kong Polytechnic University for supporting the project (Project Code: RKQY).
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Li, Y., Tsang, Y.P., Lee, C.K.M., Yao, Y. (2024). A Stratified Fuzzy Group Best Worst Decision-Making Framework. In: Campos Ferreira, M., Wachowicz, T., Zaraté, P., Maemura, Y. (eds) Human-Centric Decision and Negotiation Support for Societal Transitions. GDN 2024. Lecture Notes in Business Information Processing, vol 509. Springer, Cham. https://doi.org/10.1007/978-3-031-59373-4_6
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