Securing the upstream supply chain: a risk management approach

Giunipero, Larry C.; Eltantawy, Reham A.

doi:10.1108/09600030410567478

Cited by 364 publications

(269 citation statements)

References 16 publications

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“…The proposed approach to supply chain risk modelling accentuates the complex nature of risk behavioural interactions. Giunipero and Eltantawy (2004) identified the need for investing in extensive risk management systems for holistic supply chain management. The fundamental objective of the research reported in this paper was to develop a holistic risk management approach to measure overall risk behavioural performance.…”

Section: Resultsmentioning

confidence: 99%

A systems approach for modelling supply chain risks

Ghadge

Dani

Chester

et al. 2013

Supply Chain Management: An International Journal

178

131

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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.

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Section: Resultsmentioning

confidence: 99%

A systems approach for modelling supply chain risks

Ghadge

Dani

Chester

et al. 2013

Supply Chain Management: An International Journal

178

131

View full text Add to dashboard Cite

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“…The only significant exception is reported in [30], who claimed that e-procurement reduced TCs by approximately 99.7%. However, it is likely that such a figure disregards various costs connected to e-procurement.…”

Section: Research Objectivesmentioning

confidence: 98%

Estimating the Benefits and Risks of Implementing E-Procurement

Trkman

McCormack

2010

IEEE Trans. Eng. Manage.

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Abstract-In recent years, organizations have invested heavily in e-procurement technology solutions. However, an estimation of the value of the technology-enabled procurement process is often lacking. Our paper presents a rigorous methodological approach to the analysis of e-procurement benefits. Business process simulations are used to analyze the benefits of both technological and organizational changes related to e-procurement. The approach enables an estimation of both the average and variability of procurement costs and benefits, workload, and lead times. In addition, the approach enables optimization of a procurement strategy (e.g., approval levels). Finally, an innovative approach to estimation of value at risk is shown.Index Terms-Business process modeling, e-procurement, methodological approach, procure-to-pay (P2P) process, simulations, value at risk (VaR).

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“…In order to overcome the limitation of the existing research methods, the research proposed an identification model based on PSO-a population-based random optimization method. Through a comparison of performance with a FCMM, the findings indicated PSO can predict the logistic risk more accurately [4]. From the test results, it is shown that model of risk analysis and identification of logistic risk based on PSO algorithm is superior to FCMM model.…”

Section: Introductionmentioning

confidence: 95%

Predict the logistic risk: fuzzy comprehensive measurement method or particle swarm optimization algorithm?

Pretorius

Jiang

2018

J Wireless Com Network

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Risk analysis is an important fundamental basis of the decision-making process, and it has been applied in many fields. In order to improve the risk management of logistic, a new model based on particle swarm optimization (PSO) is proposed, which is a stochastic optimization method based on population. Through a comparison of performance with a Fuzzy Comprehensive Measurement Method (FCMM), the findings indicated that PSO can predict the logistic risk more accurately. The experimental results show that the model of logistic risk analysis and identification based on PSO algorithm is superior to FCMM model.

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Securing the upstream supply chain: a risk management approach

Cited by 364 publications

References 16 publications

A systems approach for modelling supply chain risks

A systems approach for modelling supply chain risks

Estimating the Benefits and Risks of Implementing E-Procurement

Predict the logistic risk: fuzzy comprehensive measurement method or particle swarm optimization algorithm?

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