Closed Loop Supply Chain (CLSC) networks are an attractive topic in both industry and academic research due to their positive environmental effects and waste reduction. Performance evaluation of CLSC networks is challenging due to the variety of facility types and complex relationships among them. In this study, a framework based on Social Network Analysis (SNA) is proposed to evaluate the individual components of a network and identify the critical facilities whose disruptions can affect the entire network. The proposed SNA metrics are applied to a CLSC network case study based on real data and the results and their interpretation are presented. Practical recommendations and actionable guidelines are provided are provided based on the results to mitigate the identified risks and improve the flexibility and resilience of the network. The SNAinSCM R package is developed and shared on GitHub to facilitate the computation and visualization of the discussed metrics
@article{arxiv.2110.00652,
title = {Application of Social Network Analysis in Evaluating Risk and network resilience of Closed-Loop-Supply-Chain},
author = {Sara Akbar Ghanadian and Saeed Ghanbartehrani},
journal= {arXiv preprint arXiv:2110.00652},
year = {2021}
}