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1 – 10 of over 56000Pradeep Kumar Tarei, Jitesh J. Thakkar and Barnali Nag
The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk…
Abstract
Purpose
The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk index by considering the importance of each risk and sub-risk drivers and their mutual interactions.
Design/methodology/approach
A hybrid method based on decision-making trial and evaluation laboratory and analytical network process has been proposed to develop the risk quantification framework. A case study of Indian petroleum supply chain (PSC) has been illustrated to explain the proposed method.
Findings
The results of this study found that transportation/logistics (delivery system), quality of the petroleum products, crude supply, customer’s order and legal/political regulations are the most significant risk drivers of a typical PSC. It is also found that the Indian PSC possesses a risk score of 34 percent.
Research limitations/implications
The quantification of risk in operational measure provides an unblemished representation of the overall SC risk. Unlike the existing financial measure, it takes complex subjective operational effectiveness like product quality, customer satisfaction, etc., into consideration. Identifying the high-prioritized risks helps the decision and policy makers to merely focus on the most prominent risk drivers, and reduce the impact of overall SC risk. Planning a risk mitigation strategy at a given level of risk is however beyond the scope of this research.
Originality/value
The paper develops a risk quantification framework in the context of a PSC.
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Keywords
Atanu Chaudhuri, Samir K. Srivastava, Rajiv K. Srivastava and Zeenat Parveen
The purpose of this paper is to identify various risk drivers which affect a food processing supply chain and to create a map of how those risk drivers propagate risks through the…
Abstract
Purpose
The purpose of this paper is to identify various risk drivers which affect a food processing supply chain and to create a map of how those risk drivers propagate risks through the supply chain and impact important performance measures.
Design/methodology/approach
This study involves experts from food processing companies to elucidate the contextual relationships among the risk drivers and between risk drivers and performance measures. This is used to quantify the relationships and to determine the indirect and overall relationships applying Fuzzy Interpretive Structural Modeling.
Findings
Three categories of risk drivers which Indian food processing companies need to pay maximum attention to minimize risks are identified. These are supplier dependency and contracting, supplier variability, visibility and traceability and manufacturing disruptions. Analysis shows that collaborating with suppliers and logistics service providers, developing mutually beneficial contracts with them while ensuring that adequate technology investments are made can significantly mitigate risks and consequently improve margins and lead to revenue growth.
Research limitations/implications
This study has been carried out with experts from large food processing companies in India, and hence, the results cannot be generalized across other types of food processing companies.
Practical implications
The proposed methodology can help understand the interrelationships between supply chain risks and between those risks and performance measures. Thus, it can help a food processing company to create business cases for specific supply chain risk mitigation projects.
Originality/value
This study is one of the earliest to create a comprehensive risk propagation map for food processing companies which helps in quantifying the impact the risk drivers have on each other and on performance measures.
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