A Two Phase Integrated Fuzzy Decision-Making Framework for Green Supplier Selection in the Coffee Bean Supply Chain

Abstract

In Vietnam, as more and more organizations are moving toward globalization, green supplier selection (GSS) has emerged as a strategic approach in supply chain management that requires supplier practices in lessening the environmental risks to society. Based on both conventional and environmental criteria, this paper aims to evaluate a set of suppliers by establishing a multi-criteria decision-making (MCDM)-based framework using an integrated fuzzy analytical hierarchy process (FAHP) with the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Initially, five GSS criteria of the environmental aspect (wastewater treatment, solid waste generation, energy consumption, air pollution, corporate social responsibility) and conventional criteria (quality, cost, delivery, and technology) are identified from the literature and consulting field experts to employ the MCDM approach. The trustworthiness of the proposed integrated framework is presented by discussing a case study in the coffee bean supply chain in Vietnam. The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts, and VIKOR is used to rank the alternatives against the selected criteria. From FAHP findings, the most important criteria are quantity discount, solid waste generation, order fulfillment rate, logistics cost, and purchasing cost. A consistency test is performed to ensure the uniformity of the expert’s input. The best suppliers are determined through the final ranking of the VIKOR model for the case study. The work presented provides insight to decision-makers of supplier selection that helps determine significant GSS criteria and aids in the minimization of environmental risks to society arising from the supply chain on corporate sustainability standards.

Strategic Environmental Assessment of Land Transportation: An Application of DEA with Undesirable Output Approach

“…Future studies should investigate other transport modes such as pipeline, inland waterway, or air transport. In terms of methodologies approach, future studies should combine DEA with multi-criteria decision-making (MCDM) models, such as (fuzzy) WASPAS, VIKOR, EDAS, and ELECTRE, to name a few, [43] and analyze the results with sensitivity of criteria, or comparative analysis of methods [44], to enhance the results' robustness.…”

A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

“…The usefulness of fuzzy AHP approaches has been shown, and researchers and practitioners are becoming more interested. Such approaches have been used on many extensions of fuzzy set theory that are dependent on the determination of linguistic assertions, such as traditional fuzzy sets [3,[27][28][29]47,49], type-2 fuzzy sets [50][51][52], interval-valued fuzzy sets [53], intuitionistic fuzzy sets [30], neutrosophic sets [54], Pythagorean fuzzy sets (PSF) [46], and spherical fuzzy sets [55][56][57]. The spherical fuzzy set (SFS) is the novel set introduced in 2018 by Kutlu Gündo gdu and Kahraman [58][59][60][61].…”

“…Luthra et al [26] AHP and VIKOR SSS for the Indian automobile industry Azimifard et al [43] AHP and TOPSIS SSS for Iran's Steel Industry Awasthi et al [27] Fuzzy AHP and Fuzzy VIKOR Multi-tier SSS for electronic goods manufacturing Jain et al [28] AHP and TOPSIS SSS in the Indian automotive industry Abdel-Basset et al [34] Neutrosophic Group ANP and TOPSIS SSS in a dairy company in Egypt Mohammed et al [44] MCDM-FMOO SSS in a metal factory in Saudi Arabia Gupta et al [29] Fuzzy AHP, TOPSIS, MABAC and WASPAS Green supplier selection in the automotive industry in India Memari et al [30] Intuitionistic fuzzy TOPSIS SSS for the manufacturer of catalytic converters Wong [45] Fuzzy goal programming Green supplier selection with risk management Hendiani et al [11] Fuzzy BWM SSS for refineries in Iran Zhang et al [36] DEMATEL and fuzzy VIKOR Numerical analysis Thanh and Lan [37] Fuzzy AHP and CoCoSo SSS in the food processing industry Çalık [46] Pythagorean fuzzy AHP and fuzzy TOPSIS Green supplier selection in the industry 4.0 era Orji and Ojadi [3] AHP and MULTIMOORA SSS in the Nigerian manufacturing sector with COVID-19 impacts Wang and Chen [31] AHP-MINLP-GA SSS with COVID-19 impacts Nguyen et al [47] Fuzzy AHP and VIKOR Supplier selection in coffee bean supply chain with COVID-19 impacts Petrudi et al [32] BWM and GRA SSS with COVID-19 impacts in Iran Salimian et al [40] VIKOR and MARCOS SSS in the healthcare sector…”

A Decision Support System for Supporting Strategic Production Allocation in the Automotive Industry

“…Once all data are inserted, the system adds two other scenarios: one between the positive and the average and one between the average and the negative. Thus, 5 4 problems are solved in parallel to provide the initial set of solutions. Since having more solutions for the same instance can provide more alternatives for the users, we use the Solution Pool method provided by Gurobi.…”

“…This problem becomes even more impactful in stochastic problems, since the risk aversion of the decision maker must be taken into account, and several exogenous factors may impact the solution. It is worth noting that one possibility is to use multi-objective optimization ( [3][4][5]). Nevertheless, its usage might be affected by the computational time needed and the tuning of different parameters, which is particularly needed when the number of objectives increase.…”