Sustainability assessment framework for proactive supply chain management

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Almeida, A (Author) Other; Bastos, J (Author) Other; Francisco, RDP (Author) Other; Américo Azevedo (Author) FEUP; Ávila, P (Author) Other

Journal

Title: International Journal of Industrial and Systems Engineering

Vol. 24

Pages: 198-222

ISSN: 1748-5037

Publisher: Inderscience Publishers

Indexing

Scopus - 10 Citations

Other information

Authenticus ID: P-00K-WCR

DOI: 10.1504/ijise.2016.078900

Abstract (EN): 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. © 2016 Inderscience Enterprises Ltd.

Language: English

Type (Professor's evaluation): Scientific