Title: Sustainability assessment framework for proactive supply chain management

Authors: António Almeida; João Bastos; Roberto Da Piedade Francisco; Américo Azevedo; Paulo Ávila

Addresses: INESC Porto, Rua Doutor Roberto Frias 378, 4200-465 Porto, Portugal ' INESC Porto, Rua Doutor Roberto Frias 378, 4200-465 Porto, Portugal ' INESC Porto, Rua Doutor Roberto Frias 378, 4200-465 Porto, Portugal ' INESC Porto, Rua Doutor Roberto Frias 378, 4200-465 Porto, Portugal ' ISEP, Rua Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal

Abstract: Nowadays, it has been observed an increasing awareness and understanding on the subject of sustainable companies and business models, addressing multi-disciplinary approaches that cover not only economical problems, but also social and environmental challenges. Supply chains and especially collaborative networks managers are increasingly aware of these sustainability issues, continuously seeking to meet current human needs while preserving environmental safety. Only this way, focusing on its sustainable growing, it is possible to preserve companies' steadiness. In order to achieve this goal, sustainable networks must ensure that each partner is fully aligned and committed with economic, environmental and social axes that rule the network operational behaviour. Nevertheless, in order to achieve this level of maturity within such complex and turbulent environments, organisations need to improve the quality of their performance assessment approaches, integrating the different sustainability perspectives. To accomplish this, it is critical to establish specific indicators responsible to formalise and evaluate partners' behaviour, according to well-identified objectives, as well as fuse this information in a comprehensive and user-friendly way. This paper presents a new approach, based on a fuzzy logic-based algorithm, for sustainable network performance and risk assessment.

Keywords: sustainability assessment; supply chain management; SCM; collaborative networks; performance management; key performance indicators; KPIs; fuzzy logic; risk management; complex systems; supply chain performance; sustainable development; risk assessment.

DOI: 10.1504/IJISE.2016.078900

International Journal of Industrial and Systems Engineering, 2016 Vol.24 No.2, pp.198 - 222

Available online: 04 Aug 2016 *

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