Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review

Dutta, Pankaj; Jaikumar, Bharath; Arora, Manpreet Singh

doi:10.1007/s10479-021-03931-6

Cited by 61 publications

(24 citation statements)

References 171 publications

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“…La gran cantidad de literatura identificada se puede observar La metodología DEA se ha utilizado en diferentes estudios a nivel mundial, aplicado a la agroindustria, por ejemplo: López-González et al, 2015;Ajayi & Oluntumise, 2018;Saiyut et al, 2018;Rashidghalam & Heshmati, 2019;Machmud et al, 2019;Adanguidi, 2019;Danso-Abbeam & Baiyegunhi, 2020;Ferdushi & Kamil, 2020;Yang & Shang, 2020;Dutta et al, 2021. Dutta et al (2021 realizaron una revisión de la literatura entre 2000 y 2020 sobre las aplicaciones del análisis envolvente de datos en la selección de proveedores en las organizaciones justificado por la alta relación entre el costo de compra y los ingresos, las decisiones sobre la evaluación, selección y gestión del desempeño de los proveedores en las empresas.…”

Section: Estado Del Arte: Metodología Dea Aplicada a La Agroindustriaunclassified

Estrategia para el fortalecimiento de la competitividad empresarial en el sector de grasas y aceites, mediante la medición de la eficiencia y la productividad

Duque¹,

Contreras²,

García³

et al. 2021

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Section: Estado Del Arte: Metodología Dea Aplicada a La Agroindustriaunclassified

Estrategia para el fortalecimiento de la competitividad empresarial en el sector de grasas y aceites, mediante la medición de la eficiencia y la productividad

Duque¹,

Contreras²,

García³

et al. 2021

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“…This mainly involves basic models such as simple Weighted Sum Method from model (WSM) to more complex models such as Analytic Hierarchy Process (AHP) and data wrapping Analysis (DEA), Analytical Network Process (ANP), ELECTRE (Elimination and choice Expressing the Reality), Fuzzy Approach, PROMETHEE (Prioritizing organization method for enrichment evaluation), Artificial Neural Network based approach (ANN) and Simple multiattribute evaluation method (SMART). Several researchers have conducted literature reviews on this subject [2,[8][9][10][11][12][13][14][15][16]. However, the purpose of this study is to provide a thorough analysis of 10 literature reviews on green supplier evaluation and selection models.…”

Section: Introductionmentioning

confidence: 99%

A Review of Green Supplier Evaluation and Selection Issues Using MCDM, MP and AI Models

2022

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For any industry to improve and expand, the proper evaluation and selection of suppliers is essential. In order to establish whether a supplier is appropriate for working with a company, a system for selecting green suppliers is required. A variety of Decision-Making (DM) models have been created by researchers to address the problems associated with evaluating and choosing green suppliers. In order to address the Green Supplier Evaluation and Selection (GSES) challenge, we did a thorough investigation of ten works of literature, in order to find out which approach is the most widely used and which is more efficient. This study primarily focuses on the findings of ten reviews that examined 1098 research publications from academic journals between 1990 and 2020. 271 DM models examined that were broken down into 170 individual models and 101 combination models, our analysis only looked at the single models. The method of Analytic Hierarchy Process (AHP) is the dominant model used by 160 articles, 122 studies used Data Envelopment Analysis (DEA), and finally 101 research works that utilized the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model. In addition, we found that the biggest percentage “62%” of studied articles used multi-criteria decision-making (MCDM) models. As a result, the most widely utilized Decision Making models to address the evaluation and selection of green supplier were found to be AHP, DEA, and TOPSIS.

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“…The main contribution of this method is in operations research and management science. Dutta et al provided a literature review of DEA applications in supplier evaluation and selection [5]. Among the various application fields, DEA is extensively applied in various energy sectors like renewable energy and wastewater treatment plants e.g.…”

Section: Introductionmentioning

confidence: 99%

Second-order conic programming for data envelopment analysis models

Mourad¹

2022

PEN

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Data envelopment analysis (DEA) is a widely used benchmarking technique. Its strength stems from the fact that it can include several inputs and outputs of not necessarily the same type to evaluate efficiency scores. Indeed, the aforesaid method is based on mathematical optimization. This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. As far as known, no MATLAB function solves DEA models. Among different types of DEA, this function can handle deterministic, Malmquist index, and stochastic models. In fact, DEA is involved in various practical applications, thus, this work will provide some possible future extensions, not only for MATLAB but also for any programming software in applications of decision science and efficiency analysis.

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Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review

Cited by 61 publications

References 171 publications

Estrategia para el fortalecimiento de la competitividad empresarial en el sector de grasas y aceites, mediante la medición de la eficiencia y la productividad

Estrategia para el fortalecimiento de la competitividad empresarial en el sector de grasas y aceites, mediante la medición de la eficiencia y la productividad

A Review of Green Supplier Evaluation and Selection Issues Using MCDM, MP and AI Models

Second-order conic programming for data envelopment analysis models

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