Article
Measuring Circular Supply Chain Risk: A Bayesian
Network Methodology
Madhukar Chhimwal
1,
* , Saurabh Agrawal
2
and Girish Kumar
1
Citation: Chhimwal, M.; Agrawal, S.;
Kumar, G. Measuring Circular Supply
Chain Risk: A Bayesian Network
Methodology. Sustainability 2021, 13,
8448. https://doi.org/10.3390/
su13158448
Academic Editors: Maurizio
Bevilacqua and João Carlos de
Oliveira Matias
Received: 26 May 2021
Accepted: 16 July 2021
Published: 28 July 2021
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4.0/).
1
Department of Mechanical Engineering, Delhi Technological University, Delhi 110042, India;
girish.kumar154@gmail.com
2
Delhi School of Management, Delhi Technological University, Delhi 110042, India; agrawals.iit@gmail.com
* Correspondence: madhukar.chhimwal@gmail.com
Abstract:
The world is facing economic, as well as social, crisis due to the COVID-19 pandemic.
Implementing sustainable practices is one of the possible ways to address these issues. Adopting
circular oriented techniques throughout the supply chain not only guarantees economic profitability,
but also provides an edge to the organization in the market of fierce global competition. The concept
of implementing circularity in the supply chain is novel and dynamic in nature, and it involves
certain risk. In this study, a Bayesian Network methodology is adopted to analyze how the risk
propagation takes place in a circular supply chain network of an automobile organization. The
circular supply chain network consists of a group of manufacturers, retailers and recyclers, located in
the Delhi–NCR region. Economic, environmental, social, technological, waste management, agile
vulnerability, and risk of cannibalization are the major risk categories that were identified through
an extensive literature review. Further, the impact of risk on the performance of the circular supply
chain is analyzed by considering performance parameters such as lost sales, impact on supply chain
revenue, and inventory holding cost. Risk exposure index is incorporated into the study to analyze
the vulnerability of each node. The findings of the study reveal that the reverse side of the circular
supply chain can be a source of risk propagation during the implementation of the circularity concept.
This work is carried out under a single industry domain. In the future, risk propagation analysis
can be examined in the supply chain of other sectors. The findings of the study can assist the supply
chain managers and the risk experts to focus on the areas that are more vulnerable to risk.
Keywords: circular supply chain; Bayesian network; risk management; risk modeling; COVID-19
1. Introduction
The world is moving towards digitization in this pandemic era [
1
]. Digitization is
good in many senses, but whether it is sufficient to meet the needs of the customer is
unknown [
2
]. Customers require resources. This pandemic has majorly hit the logistics
services all over the globe [
3
]. Logistic services are not only affected at a major global level,
but at the domestic level too. Due to this, there is an imbalance created between the supply
and demand of resources [
4
]. This imbalance has led to the evolvement of several risks
occurring throughout the complete supply chain cycle [
5
]. One of the major risk occurring
is the shortage of resources, thereby leading toahigh selling price [
6
]. In some situations,
production and consumption is normal, but the finished product inventory still has a rising
graph, due to missing logistics [
7
]. Disruptions in the supply of the right quantity of raw
material, at the right time, having the right quality may lead to a delay in production,
which may affect the entire supply chain cycle [
8
]. The global crisis of COVID-19 has
ravaged the world economy, and has created an atmosphere of fear and panic buying
among customers [3].
A pandemic is a period of uncertainty [
9
]. It is difficult to predict the occurrence and
severity of the disruption in the supply chain during the pandemic phase [
10
]. Looking
Sustainability 2021, 13, 8448. https://doi.org/10.3390/su13158448 https://www.mdpi.com/journal/sustainability
