A multi-level programming model for green supplier selection

PurposeIndustrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a compe...

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Veröffentlicht in:	Management decision Jg. 59; H. 10; S. 2496 - 2527
Hauptverfasser:	Gupta, Srikant, Chatterjee, Prasenjit, Yazdani, Morteza, Santibanez Gonzalez, Ernesto D.R
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Emerald Publishing Limited 06.09.2021 Emerald Group Publishing Limited
Schlagworte:	Climate change Efficiency Flexibility Manufacturing Order quantity Product design Product development Social responsibility Suppliers Supply chain management Sustainable development Green supplier selection Multi-level programming problem Forecasting Green supply chain Interval type-2 fuzzy numbers
ISSN:	0025-1747, 1758-6070
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Abstract	PurposeIndustrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.Design/methodology/approachIn this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.FindingsThis research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.Research limitations/implicationsThe proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.Practical implicationsThe proposed model is generic and can be applied for large-scale GSC environments with little modifications.Originality/valueNo prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.
AbstractList	PurposeIndustrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.Design/methodology/approachIn this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.FindingsThis research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.Research limitations/implicationsThe proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.Practical implicationsThe proposed model is generic and can be applied for large-scale GSC environments with little modifications.Originality/valueNo prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.
Author	Gupta, Srikant Chatterjee, Prasenjit Santibanez Gonzalez, Ernesto D.R Yazdani, Morteza
Author_xml	– sequence: 1 givenname: Srikant surname: Gupta fullname: Gupta, Srikant email: operation.srikant@hotmail.com – sequence: 2 givenname: Prasenjit surname: Chatterjee fullname: Chatterjee, Prasenjit email: prasenjit2007@gmail.com – sequence: 3 givenname: Morteza surname: Yazdani fullname: Yazdani, Morteza email: morteza_yazdani21@yahoo.com – sequence: 4 givenname: Ernesto D.R surname: Santibanez Gonzalez fullname: Santibanez Gonzalez, Ernesto D.R email: santibanez.ernesto@gmail.com
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Keywords	Green supplier selection Multi-level programming problem Forecasting Green supply chain Interval type-2 fuzzy numbers
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SubjectTerms	Climate change Efficiency Flexibility Manufacturing Order quantity Product design Product development Social responsibility Suppliers Supply chain management Sustainable development
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Title	A multi-level programming model for green supplier selection
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