Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead

Chai, Junyi; Ngai, Eric W.T.

doi:10.1016/j.eswa.2019.112903

Cited by 139 publications

(87 citation statements)

References 174 publications

(61 reference statements)

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“…After determining the criteria (risk types) and sub-criteria (risk factors), decisionmakers should choose an appropriate and systematic method to evaluate and select alternative suppliers. Many studies have reviewed the literature on supplier selection models [50][51][52][53]. Multi-criteria decision-making models (MCDM), mathematical programming (MP), and artificial intelligence (AI) techniques are some of the most popular approaches [50,53,54].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Many studies have reviewed the literature on supplier selection models [50][51][52][53]. Multi-criteria decision-making models (MCDM), mathematical programming (MP), and artificial intelligence (AI) techniques are some of the most popular approaches [50,53,54]. MCDM provides a methodological framework for decision support systems; MP is used to optimize or evaluate supplier selection; AI identifies approximate solutions to complex optimization problems [54].…”

Section: Literature Reviewmentioning

confidence: 99%

“…MCDM provides a methodological framework for decision support systems; MP is used to optimize or evaluate supplier selection; AI identifies approximate solutions to complex optimization problems [54]. MCDM approaches are the most popular and within MCDM the Analytical Hierarchy Process (AHP) is most often applied [53].…”

Section: Literature Reviewmentioning

confidence: 99%

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Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

2021

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Supplier risks have attracted significant attention in the supply chain risk management literature. In this article, we propose a new computational system based on the ‘Fuzzy Extended Analytic Hierarchy Process (FEAHP)’ method for supplier selection while considering the relevant risks. We sought to evaluate the opportunities and limitations of using the FEAHP method in supplier selection and analyzed the support of the system developed through the real case of a Brazilian oil and natural gas company. The computational approach based on FEAHP automates supplier selection by determining a hierarchy of criteria, sub-criteria, and alternatives. First, the criteria and sub-criteria specific to the selection problem were identified by the experts taking the relevant literature as a starting point. Next, the experts performed a pair-wise comparison of the predefined requirements using a linguistic scale. This evaluation was then quantified by calculating the priority weights of criteria, sub-criteria, and alternatives. The best decision alternative is the one with the highest final score. Sensitivity analysis was performed to verify the results of the proposed model. The FEAHP computer approach automated the supplier selection process in a rational, flexible, and agile way, as perceived by the focal company. From this, we hypothesized that using this system can provide helpful insights in choosing the best suppliers in an environment of risk and uncertainty, thereby maximizing supply chain performance.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

2021

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“…In addition, Brans and Mareschal [31] provides all versions of the PROMETHEE method, which has been applied to many fields [32,33], but only some articles to supply chain management [20,23,[34][35][36]. AHP is the discrete multiple criteria method most applied on this topic so far, to both elicit weights of criteria and select suppliers, with a fuzzy version also used to deal with uncertainty [4,5,8,37,38]. In contrast, MAUT barely appears in the literature, although it is appropriate for qualifying products and suppliers [3,23].…”

Section: A Multiple Criteria System For Sustainable Evaluation Of Foomentioning

confidence: 99%

Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies

2019

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Supplier evaluation is a relevant task of supply chain management where multicriteria methods make great contributions to manufacturing industries. This is not the case in food distribution companies, which have a key role in providing safe and affordable food to society. The purpose of this research is to measure the sustainability of products and suppliers in food distribution companies through a multiple criteria approach. Firstly, the system proposed provides indicators to qualify products and assess the food quality, using the compensatory Multi-Attribute Utility Theory (MAUT) model. Secondly, these indicators are included in supplier evaluation, which takes economic, environmental, and social criteria into account. MAUT and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE), a non-compensatory method, are used for supplier evaluation. This approach has been validated for fresh food in a supermarket chain, mainly using historical data. Partial indicators, such as food safety scores, together with global indicators of suppliers, inform the most appropriate decisions and the most appropriate relations between companies and providers. Poor performance in food safety can lead to the disqualification of some suppliers. MAUT is good for qualifying products and is easy to apply at the operational level in logistic platforms, while PROMETHEE is more suitable for supplier segmentation, as it helps to identify supplier strengths and weaknesses.

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“…In addition to these traditional management considerations, green issues should also be taken into account so that the importance of environment is elevated for business ventures. The importance of supplier selection and evaluation is well recognized in the literature (Chai, Liu, & Ngai, 2013; Govindan, Rajendran, Sarkis, & Murugesan, 2015; Soheilirad et al 2018, Chai & Ngai, 2020). In this paper, a new multilevel selection and capacity dedication method is proposed.…”

Section: Introductionmentioning

confidence: 99%

Green supplier selection using a common weights analysis of DEA and EOQ types of order allocation

Dobos

Vörösmarty

2020

Manage Decis Econ

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This paper offers a solution to the supplier selection problem and the problem of lot‐sizing decisions. Data Envelopment Analysis (DEA) is seldom applied to help solve multilevel supplier selection problems. The order allocation problem is reformulated as a linear programming problem in a novel way. First, a Data Envelopment Analysis/common weights model (DEA/CWA) is introduced to help define the supplier pool of capable suppliers. Selection criteria include management and green criteria. In a second phase, a nonlinear mathematical programing model is offered to determine capacity distribution among selected suppliers. A numerical example is provided to support the theoretical model.

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Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead

Cited by 139 publications

References 174 publications

Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP

Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies

Green supplier selection using a common weights analysis of DEA and EOQ types of order allocation

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