Prioritising sustainable supply chain management practices by their impact on multiple interacting barriers

ABSTRACT

Sustainable development in supply chain management (SCM) is challenging to implement, so various studies have sought to identify appropriate practices that eliminate barriers and challenges’ effects on sustainable SCM (SSCM). To overcome previous investigations’ limitations, the present research developed a multi-attribute decision-making (MADM) framework for prioritising SSCM practices, which was applied to an Iranian case. A careful, systematic review of previous studies extracted a comprehensive list of SSCM barriers and practices. To shorten the long list of barriers identified, the fuzzy Delphi and fuzzy decision-making trial and evaluation methods were used to reduce the decision criteria list. These two approaches are particularly appropriate because of the criteria’s complex interactions. In addition, fuzzy sets are useful when dealing with uncertainties in decision-making processes and obtaining experts’ opinions. With the selected experts’ help, the extent of each practice’s impact on barriers was measured. The practices were then ranked by order of priority using six fuzzy MADM methods. The implemented methods’ weights were determined using the correlation coefficient and standard deviation (CCSD) approach in order to prioritise the practices for the final time. The proposed methodological framework combines different approaches’ results and increases the findings’ empirical robustness by applying the CCSD method, thereby eliminating previous studies’ limitations. Results show that ‘Lack of sustainable product and service promotion’ (B18) and ‘Weak social and society-related pressures’ (B34) are the top priority barriers and ‘Applying preventive and maintenance strategies to maximize equipment’s effectiveness’ (P5) and ‘Implementing reverse logistics’ (P3) have been identified as the most important SSCM practices.

KEYWORDS:

• Sustainable supply chain management
• aggregation method
• fuzzy multi-attribute decision making (FMADM)
• multiple criteria
• correlation coefficient and standard deviation (CCSD)

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partially supported by the Portuguese Foundation for Science and Technology under Grant [UID/GES/00315/2019.UID/GES/00315/2019].