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An Evaluation of the environmental factors for supply chain strategy decisions using grey systems and composite indicators

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An Evaluation of the environmental factors for supply chain strategy decisions using grey systems and composite indicators

dc.contributor.author	Alfaro Saiz, Juan José
dc.contributor.author	Bas Cerdá, María del Carmen
dc.contributor.author	Giner Bosch, Vicent
dc.contributor.author	Rodríguez Rodríguez, Raúl
dc.contributor.author	Verdecho, María José
dc.date.accessioned	2021-03-24T07:39:37Z
dc.date.available	2021-03-24T07:39:37Z
dc.date.issued	2020
dc.identifier.citation	Alfaro Saiz, Juan José Bas Cerdá, María del Carmen Giner Bosch, Vicent Rodríguez Rodríguez, Raúl Verdecho, María José 2020 An Evaluation of the environmental factors for supply chain strategy decisions using grey systems and composite indicators Applied Mathematical Modelling
dc.identifier.uri	https://hdl.handle.net/10550/78338
dc.description.abstract	The purpose of this work is to assess the importance of environmental factors in a supply chain with four partners as a preliminary step to select the competitive strategies and objectives. To achieve this purpose, a real case study was carried out in a footwear supply chain, in which two approaches were used: the grey system theory and uncertainty analysis tools for composite indicators. In order to validate both approaches, a seven-phase research methodology was developed and applied to our case study. In addition, the priorization of environmental factors was calculated individually for each partner. The results allow managers to establish the competitive strategy that best suits the prioritization of the most relevant factors and to define the most appropriate objectives where the supply chain should invest its efforts and resources.
dc.language.iso	eng
dc.relation.ispartof	Applied Mathematical Modelling, 2020
dc.subject	Matemàtica aplicada
dc.subject	Economia matemàtica
dc.title	An Evaluation of the environmental factors for supply chain strategy decisions using grey systems and composite indicators
dc.type	journal article	es_ES
dc.date.updated	2021-03-24T07:39:38Z
dc.identifier.doi	10.1016/j.apm.2019.10.048
dc.identifier.idgrec	143666
dc.rights.accessRights	open access	es_ES