  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
