TY - GEN
T1 - A Stratified Fuzzy Group Best Worst Decision-Making Framework
AU - Li, Yanlin
AU - Tsang, Y. P.
AU - Lee, C. K.M.
AU - Yao, Yipu
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
KW - Concept of Stratification
KW - Group Decision Making
KW - Human-centric Decision-Making
KW - Stratified Fuzzy Best-Worst Group Method
UR - http://www.scopus.com/inward/record.url?scp=85194076005&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-59373-4_6
DO - 10.1007/978-3-031-59373-4_6
M3 - Conference article published in proceeding or book
AN - SCOPUS:85194076005
SN - 9783031593727
T3 - Lecture Notes in Business Information Processing
SP - 65
EP - 76
BT - Human-Centric Decision and Negotiation Support for Societal Transitions - 24th International Conference on Group Decision and Negotiation, GDN 2024, Proceedings
A2 - Campos Ferreira, Marta
A2 - Wachowicz, Thomasz
A2 - Zaraté, Pascale
A2 - Maemura, Yu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th International Conference on Group Decision and Negotiation, GDN 2024
Y2 - 2 June 2024 through 5 June 2024
ER -