Sustainable supplier selection: A ranking model based on fuzzy inference system

Amindoust, Atefeh; Ahmed, Shamsuddin; Saghafinia, Ali; Bahreininejad, Ardeshir

doi:10.1016/j.asoc.2012.01.023

Cited by 505 publications

(310 citation statements)

References 27 publications

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“…Yu & Wong, 2014). Besides, a few studies have also considered social aspects of the TBL in the supplier selection either combined with environmental and economic dimensions or in a separate manner (Amindoust et al, 2012;Baskaran et al, 2012;Buyukozkan & Cifci, 2011;Govindan, Khodaverdi, et al, 2013). However, based on a recent empirical study by and Meixell and Luoma (2015), it was highlighted that incorporating TBL attributes into traditional operations strategies are still at its early stages and more comprehensive treatments should be made to address all three TBL dimensions.…”

Section: Methodsmentioning

confidence: 99%

“…Some of these applied techniques include fuzzy analytical hierarchy process (FANP) (Buyukozkan & Cifci, 2011), decision-making trial and evaluation laboratory (DEMATEL) (Chiou et al, 2011), fuzzy analytical hierarchy process (FAHP) (Chiouy et al, 2011), fuzzy inference system (FIS) (Amindoust et al, 2012), fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) (Govindan (Govindan, Kannan, et al, 2013) and data envelopment analysis (DEA) (Shi et al, 2015). There are also few research activities that tried to combine two or more techniques in order to form a hybrid approach that could perform better than its constituting techniques individually.…”

Section: Introductionmentioning

confidence: 99%

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Sustainable supplier performance scoring using audition check-list based fuzzy inference system: A case application in automotive spare part industry

Ghadimi

Dargi

Heavey

2017

Computers & Industrial Engineering

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With the global awareness of sustainability issues, sustainable development is being increasingly recognized by governments and industries. In addressing these issues, organizations worldwide have taken initiatives in adopting sustainability practices in their supply chain transferring it to sustainable supply chain management. In order to establish a responsible sustainable supply chain management, an effective way would be to make sure that the potential suppliers for procuring required components are precisely assessed and evaluated based on sustainable criteria. Therefore, this paper proposes a practical decision making approach to evaluate and select the most sustainable suppliers for an automotive spare part manufacturer licensed under a France-based automotive organization. Firstly, a requirement gathering approach, the audition check-list approach, is designed to facilitate the process of data gathering for supplier evaluation based on three pillars of sustainability. Next, the gathered data are processed using a proposed fuzzy inference system to remove impreciseness and vagueness in the gathered sustainability related data. The strength of this model falls into its applicability in data gathering phase which helps decision makers in manufacturing company to perform a fast audition of a typical supplier. Secondly, the final sustainable ranking of suppliers using the proposed fuzzy inference system provide a precise and less uncertain sustainability performance scoring which makes the developed approach a reliable system for making sustainable sourcing decisions. Comparison and sensitivity analysis are performed to evaluate the proficiency of the developed approach. Finally, theoretical and managerial implications together with conclusions of the study are presented.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sustainable supplier performance scoring using audition check-list based fuzzy inference system: A case application in automotive spare part industry

Ghadimi

Dargi

Heavey

2017

Computers & Industrial Engineering

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“…Several MADM techniques have been proposed for the SSE problem: analytic hierarchy process (AHP) [34][35][36], analytic network process (ANP) [34], complex proportional assessment (COPRAS) [36][37][38], data envelopment analysis (DEA) [36,[39][40][41], elimination et choix traduisant la realité (ELECTRE) [42,43], preference ranking organization method for enrichment of evaluations (PROMETHEE) [44], technique for order of preference by similarity to ideal solution (TOPSIS) [45][46][47][48][49], visekriterijumska optimizacija i kompromisno resenje (VIKOR) [50,51], decision-making trial and evaluation laboratory (DEMATEL) [52,53], multi-objective optimisation by ratio analysis (MOORA) [54], case based reasoning (CBR) [55], fuzzy inference systems [56,57], genetic algorithm (GA) [58], mathematical and goal programming (MP) [59], simple multi-attribute rating technique (SMART) [60], and their hybrids, among others. In those MADM techniques, the supplier qualification is set according to the valuation given to different relevant factors (qualitative and quantitative) in the evaluation process.…”

Section: Main Methodologies and Factors Used In Sse Modelsmentioning

confidence: 99%

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

et al. 2018

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This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method's superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process.

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“…Sustainability is a topic not originally handled by the model, but a concern that affects many business today. When social and environmental concerns are important drivers for procurement decisions, the categorization of suppliers, which originally emphasized the economic aspects, becomes inadequate (Amindoust et al, 2012).…”

Section: Portfolio Model With a Sustainability Dimensionmentioning

confidence: 99%

Sustainable procurement portfolio management: a case study in a mining company

Mello

Eckhardt

Leiras

2017

Prod.

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Sustainable procurement is a solution to integrate environmental and social considerations in all steps of procurement process, in order to reduce impacts on human health, environment, and human rights. Despite the existence of important works in this area, more studies for determining how the principles related to sustainable development can be integrated to procurement strategies are needed. This study presents a case study in a mining company to evaluate the elements that should be considered for the implementation of sustainability concept in the contracting of services through the application of a sustainability portfolio model. Results show that the contracts of the internal movement's category of the studied company fit as Strategic Commodity, which means that the items in this category have a risk in the strategic supply, because they need investments made by the buyer in the relationship with the supplier.

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Sustainable supplier selection: A ranking model based on fuzzy inference system

Cited by 505 publications

References 27 publications

Sustainable supplier performance scoring using audition check-list based fuzzy inference system: A case application in automotive spare part industry

Sustainable supplier performance scoring using audition check-list based fuzzy inference system: A case application in automotive spare part industry

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

Sustainable procurement portfolio management: a case study in a mining company

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