A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach

Shi, Ping; Yan, Bo; Shi, Song; Ke, Chang-Bo

doi:10.1007/s10799-014-0193-1

Cited by 70 publications

(25 citation statements)

References 26 publications

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“…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%

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: 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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“…For this reason, the output must be easily read and digested by the user. Based on the results of this study, the most frequently occurring forms of output are data and documents (Shi et al, 2015;Scott et al, 2015;Park et al, 2013;Attadjei et al, 2018;Dev et al, 2017;Silva et al, 2017). This result can be understood because the output is in the form of data and documents are very easy to read and use, compared with other outcomes such as information and guidelines that are universal and less specific.…”

Section: Discussionmentioning

confidence: 68%

Decision support system in supply chain: A systematic literature review

Teniwut¹,

Hasyim²

2020

10.5267/j.uscm

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Systematic literature review in supply chain and decision support system, in general, have been rapidly performed during the last decade. However, the studies on the epistemological progress of decision support system related to the supply chain are still lacking. This study intended to provide comprehensive information on the trends, methodologies and the applications on different sectors and platforms used by scientists for building their decision support systems in supply chain. We used different keywords to collect the raw data based on articles published in well-known journals in the world to select the eligible studies which furthermore assembled. The data were processed by using bibliometric tool in VOSviewer and Microsoft Excel. The results of this systematic review give some key learning of the trends on the use of decision support system on smoothing the flow of supply chain and the logistic performance in the last decade and also provide a background for future research related to the fields.

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“…The multi-criteria decision-making methods, such as the analytic hierarchy process (AHP) [22], analytical network process (ANP) [25,26], data envelopment analysis (DEA) [27], the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) [25,28], VIKOR [29] and the Decision Making Trial and Evaluation Laboratory (DEMATEL) [30] methods, are usually adopted to evaluate the alternatives in sustainability and green practices. MCDM methods would be used in recycling practices to select the best ELV recycling merchant.…”

Section: Hybrid Multi-criteria Decision-making (Mcdm) Methodsmentioning

confidence: 99%

ELV Recycling Service Provider Selection Using the Hybrid MCDM Method: A Case Application in China

et al. 2016

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Abstract:With the rapid depletion of natural resources and undesired environmental changes globally, more interest has been shown in the research of green supply chain practices, including end-of-life vehicle (ELV) recycling. The ELV recycling is mandatory for auto-manufacturers by legislation for the purpose of minimizing potential environmental damages. The purpose of the present research is to determine the best choice of ELV recycling service provider by employing an integrating hybrid multi-criteria decision making (MCDM) method. In this research, economic, environmental and social factors are taken into consideration. The linguistic variables and trapezoidal fuzzy numbers (TFNs) are applied into this evaluation to deal with the vague and qualitative information. With the combined weight calculation of criteria based on fuzzy aggregation and Shannon Entropy techniques, the normative multi-criteria optimization technique (FVIKOR method) is applied to explore the best solution. An application was performed based on the proposed hybrid MCDM method, and sensitivity analysis was conducted on different decision making scenarios. The present study provides a decision-making approach on ELV recycling business selection under sustainability and green philosophy with high robustness and easy implementation.

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A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach

Cited by 70 publications

References 26 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

Decision support system in supply chain: A systematic literature review

ELV Recycling Service Provider Selection Using the Hybrid MCDM Method: A Case Application in China

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