A systems approach for modelling supply chain risks

Abstract

Purpose -With increasing exposure to disruptions, it is vital for supply chains to manage risks proactively. Prediction of potential failure points and overall impact of these risks is challenging. In this paper, systems thinking concepts are applied for modelling supply chain risks. The purpose of this paper is to develop a holistic, systematic and quantitative risk assessment process for measuring the overall risk behaviour. Design/methodology/approach -A framework for supply chain risk management (SCRM) is developed and tested using an industrial case study. A systematically developed research design is employed to capture the dynamic behaviour of risks. Additionally, a system-based supply chain risk model is conceptualized for risk modelling. Sensitivity modelling results are combined for validating the supply chain risk model. Findings -The systems approach for modelling supply chain risks predicts the failure points along with their overall risk impact in the supply chain network. System-based risk modelling provides a holistic picture of risk behavioural performance, which is difficult to realise through other research methodologies commonly preferred in SCRM research. Practical implications -The developed framework for SCRM is tested in an industry setting for its viability. The framework for SCRM along with the supply chain risk model is expected to benefit practitioners in understanding the intricacies of supply chain risks. The system model for risk assessment is a working tool which could provide a perspective of future disruptive events. Originality/value -A holistic, systematic and quantitative risk modelling mechanism for capturing overall behaviour of risks is a valuable contribution of this research. The paper presents a new perspective towards using systems thinking for modelling supply chain risks.

Humanitarian supply chain strategies – a review of how actors mitigate supply chain risks

“…Chopra and Sodhi (2004) suggested that flexible supply base and strategic stocks are the two strategies that can mitigate disruptions. Ghadge et al (2013) found flexible supply base as a way to cope with geopolitical risks. Ritchie and Brindley (2007) differentiate risks by 'high' vs. 'low' only.…”

“…SCRM frameworks suggest categorising strategies by different dimensions, including redundancy vs. flexibility (Chang et al 2015;Kleindorfer and Saad, 2005;); reducing vs. coping (Ghadge et al 2012;Knemeyer et al 2009;Simangunsong et al 2012), such as sharing and transferring (Ghadge et al 2013); monitoring vs. collaboration (Hajmohammad and Vachon 2016); and depending on what risks they are to handle (Chopra and Sodhi, 2004;Ghadge et al 2013;Ho et. al 2015;Lavastre et.…”

The Relationship Between Green Building and Regional Economy: A Case Study in Guangdong, China

“…contribute to the development of the interaction between the two variables, and the analysis of its process structure is clear and definite [33]. The system dynamics can simulate the function of the two variables with the help of the computer, and observe d.…”

An Empirical Risk Analysis of the Brazilian Shipbuilding Industry

“…In the literature, the SCRM process is described in similar ways, which can vary from risk identification and/or measurement, risk assessment and/or risk evaluation to mitigation plans and control and/or monitoring (Hallikas et al, 2002;Neiger et al, 2003;Jüttner et al 2005;Kleindorfer and Saad 2005;Tse et al, 2005;Cucchiella and Gastaldi, 2006;Ritchie and Brindley, 2007;Adhitya et al, 2008;Knemeyer et al, 2009;Giannakis and Louis, 2011;Tummala and Schoenherr, 2011;Kern et al, 2012;Ghadge et al, 2013;Ceryno et al, 2014;Elleuch et al, 2014). Different systems have been put forward but most approaches for SCRM process tend to follow the generic process shown in Figure 4.…”

“…This involves a comprehensive and structured determination of potential SC risks associated with the given problem. The main focus of supply chain risk identification is to recognize SC uncertainties in order to enable an efficient risk management (Hallikas et al, 2000;Norrman and Jansson, 2004;Kleindorfer and Saad, 2005;Cucchiella and Gastaldi, 2006;Ritchie and Brindley, 2007;Pujawan and Geraldin, 2009;Blome and Schoenherr, 2011;Kern et al, 2012;Ghadge et al, 2013;Ceryno et al, 2014).…”