Selecting the Optimal Green Agricultural Products Supplier: A Novel Approach Based on GBWM and PROMETHEE II

Zhengmin Liu, Lin Li, Xiaolan Zhao, Linbin Sha, Di Wang, Xinya Wang and Peide Liu
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Zhengmin Liu: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
Lin Li: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
Xiaolan Zhao: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
Linbin Sha: School of Literature and Journalism, Shandong University of Finance and Economics, Jinan 250014, China
Di Wang: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
Xinya Wang: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
Peide Liu: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China

Sustainability, 2020, vol. 12, issue 17, 1-23

Abstract: Due to the uncertainty of natural factors and a larger global population, the work of supplying sustainable agricultural materials, especially green agricultural products, faces enormous challenges. How to effectively evaluate and select the most desirable green agricultural material supplier is an urgent issue for both agribusiness and government. In this paper, an integrated q-rung orthopair fuzzy (q-ROF) group best–worst method (GBWM) and the PROMETHEE II was introduced to availably solve such issue. Firstly, by taking similarity degree into account to solve incomplete weight information, a novel technique was constructed to determine the experts’ weight reasonably under the q-ROF context. Secondly, to improve consistency for group decision making and obtain a highly reliable selection result, the GBWM was used to derive criteria weights. Then, based on the proposed generalized p-norm knowledge-based score function, the PROMETHEE II was further improved to rank the feasible alternatives. After that, a representative case under the background of green agricultural material supplier selection was investigated in depth. Finally, the detailed comparative technique was conducted to verify the validity and superiority of the improved method.

Keywords: green agricultural material supplier selection; q-rung orthopair fuzzy sets; knowledge-based score function; group best-worst method; PROMETHEE II (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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