TY - GEN
T1 - The Least-distance DEA Based Efficiency Improvement under Multiple Perspectives
AU - Wang, Xu
AU - Hasuike, Takashi
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Data envelopment analysis (DEA) is widely used to evaluate and improve the relative efficiency of decision making units (DMUs), which have multiple inputs and outputs. However, traditional DEA models can only handle a single perspective. In this study, we propose a new approach for efficiency improvement under multiple perspectives based on the least-distance DEA. The Nash bargaining game (NBG) theory has been used in extant studies to avoid conflicts and obtain a rational direction of efficiency improvement under multiple perspectives. Because of the practicality of the closest efficient target, we first propose a least-distance DEA model incorporating NBG. A numerical experiment is conducted to compare the performance of our proposed approach with that of previous studies. The results reveal that our proposed approach can (1) evaluate the efficiency of DMUs under multiple perspectives, and (2) provide more easy-to-achieve efficiency improvement suggestions for the assessed DMUs. Thus, the proposed approach has remarkable potential applicability in decision making.
AB - Data envelopment analysis (DEA) is widely used to evaluate and improve the relative efficiency of decision making units (DMUs), which have multiple inputs and outputs. However, traditional DEA models can only handle a single perspective. In this study, we propose a new approach for efficiency improvement under multiple perspectives based on the least-distance DEA. The Nash bargaining game (NBG) theory has been used in extant studies to avoid conflicts and obtain a rational direction of efficiency improvement under multiple perspectives. Because of the practicality of the closest efficient target, we first propose a least-distance DEA model incorporating NBG. A numerical experiment is conducted to compare the performance of our proposed approach with that of previous studies. The results reveal that our proposed approach can (1) evaluate the efficiency of DMUs under multiple perspectives, and (2) provide more easy-to-achieve efficiency improvement suggestions for the assessed DMUs. Thus, the proposed approach has remarkable potential applicability in decision making.
KW - DEA
KW - Efficiency Improvement
KW - Least Distance
KW - Multiple Perspectives
KW - NBG
UR - http://www.scopus.com/inward/record.url?scp=85125406461&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125406461&partnerID=8YFLogxK
U2 - 10.1109/IEEM50564.2021.9672865
DO - 10.1109/IEEM50564.2021.9672865
M3 - Conference contribution
AN - SCOPUS:85125406461
T3 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
SP - 818
EP - 823
BT - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Y2 - 13 December 2021 through 16 December 2021
ER -