Abstract
The current state of sustainability is promoting the status of the supply chain from traditional economic objectives related to the cost, quality, and time to the multidimensional opportunities in terms of economic, social and environmental fronts. The paper deals with the development of a decision support framework for the prioritization of suppliers on sustainability factors. The framework is based on the combined approach of the analytical hierarchical process (AHP) and the fuzzy inference system (FIS) to evaluate the supplier for the benefit of the manufacturer. The role of AHP is to select the significant factors as criteria, while the FIS mechanism works to measure the sustainability index of each supplier for prioritization from the combined effect of the selected factors. In the ranking process, experts’ opinions on the importance of deciding the criteria (developed by the AHP) are considered in linguistic terms. To handle the subjectivity of decision makers assessments, fuzzy logic has been applied using FIS. In addition, uncertainties in the decision making support system are overcome by considering the fuzzy set theory for the selected sustainable factors. A numerical experiment is carried out to consider seven suppliers working with the goalkeeping gloves manufacturing firm for the pragmatic application of the proposed framework. The methodology of the integrated AHP–FIS approach is utilized to rank the suppliers by calculating the sustainability index value. The proposed approach provides a platform for the manufacturer to better understand the capability, sustainable suppliers must possess to continue working with them for the sustainable supply chain management.
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Appendices
Appendix A: Selection and Effect of Economic Factors on Sustainability
The possible economic factors considered by the managers for the SSS are further processed through AHP. That is the reason, the pairwise comparison matrix among economic factors are given as in Table 8.
The output of the AHP is the formation of the eigen vector, which is the representation of the significance values of the factors as given in Table 9. Pareto principal is used to find the 80% of the economic factors necessary for the SSS, from which the three factors are selected i.e., unit cost, delivery cost, and inspection cost.
The selected economic factors are further converted into linguistic variables i.e., low, medium, and high to remove the uncertainties for fuzzy inference system. The combine effect of each factors among these linguistic variables are affecting the overall economics priority index as given in Table 10.
Appendix B: Selection and Effect of Social Factors on Sustainability
Similarly, the selection of the social factors is done through AHP, where the pairwise comparison matrix of each of 8 possible social factors is represented as in Table 11.
The output of AHP in the form of eigen vector representing the significance values of social factors is given in Table 12. Again Pareto principle is applied to select the social factors having combine significance value of 80% and the results are on-time delivery, relationship, and health and safety.
The requirement of the triangular fuzzy numbers required the selected social factors into three linguistic variable and their combine effect on social sustainability is given in Table 13. These rules are made as an input to FIS for the selection of the suppliers on the basis of social sustainability.
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Omair, M., Noor, S., Tayyab, M. et al. The Selection of the Sustainable Suppliers by the Development of a Decision Support Framework Based on Analytical Hierarchical Process and Fuzzy Inference System. Int. J. Fuzzy Syst. 23, 1986–2003 (2021). https://doi.org/10.1007/s40815-021-01073-2
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DOI: https://doi.org/10.1007/s40815-021-01073-2