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An Innovative Method to Quantitatively Assess Social Sustainability of Multi-tier Supply Chains in the Textile Industry

Francesco Olivero

An Innovative Method to Quantitatively Assess Social Sustainability of Multi-tier Supply Chains in the Textile Industry.

Rel. Andrea Tuni, Paolo Claudio Priarone, Fabiana Morandi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2024


Nowadays, social sustainability represents an essential element within the broader framework of Sustainable Supply Chain Management (SSCM), especially in the textile industry. During the last 15 years, many disasters, some of which have also resulted in the loss of human lives, have occurred in garment factories often located in developing countries. Furthermore, the apparel supply chain presents itself as highly fragmented and globally dispersed due to short lead times and low costs driven by customers’ expectations. Thereby, critical working conditions within the textile supply chain, such as child labour, forced labour, low wages, safety issues and harmful chemical exposure, demand attention. In fact, fashion and textile companies must implement social risk management practices to achieve fair social conditions at each tier of the supply chain. Moreover, social sustainability practices have the potential to positively impact the financial performance of fashion brands by improving their brand value, reputation and consumer loyalty, thus becoming a source of competitive advantage. Part of social risk management strategies involves applying monitoring and auditing activities towards suppliers and sub-suppliers to increase transparency and awareness. Therefore, Sustainable Supplier Evaluation (SSE) and Sustainable Supplier Selection (SSS) practices play a critical role in managing social criticalities and many Multi-Criteria Decision Making (MCDM) models have been developed. However, no method able to allocate sub-supplier social performance until tier 1, nor no methodology for the evaluation of social sustainability based on the Higg Facility Social and Labor Module (Higg FSLM), a widely adopted social audit program, have been proposed yet in the literature. Therefore, a research gap has been identified and a new methodology has been developed to cover these topics as well as to stimulate new research papers in these directions. The proposed methodology develops a Multi-Criteria Decision-Making (MCDM) model and an Aggregation Methodology for Sustainable Supplier Selection and Sustainable Supplier Evaluation based on the Higg FSLM. It employs a risk-based approach, utilizing non-compensatory and compensatory techniques, as well as the AHP and the TOPSIS methods. The Aggregation Methodology allocates sub-supplier social performance to higher-tier suppliers until tier 1, aiming to hold focal firms accountable for the entire supply chain’s social practices. The presented method has been applied to the case study of Benetton Group, a very well-known Italian fashion company that operates globally. First, a large pool of Benetton Group tier 1 suppliers has been analyzed with the proposed methodology without applying the Aggregation Methodology. Second, the complete methodology (including the Aggregation Methodology) has been applied to a smaller set of tier 2 suppliers and to the corresponding tier 1 suppliers. Thus, a sensitivity analysis has been performed to understand how different input parameters of the method affect the final ranking and scores of suppliers. Finally, the main results, limitations and future research directions are examined.

Relators: Andrea Tuni, Paolo Claudio Priarone, Fabiana Morandi
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 92
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: Benetton Group S.R.L.
URI: http://webthesis.biblio.polito.it/id/eprint/31384
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