Supply chain risk network management : a Bayesian belief network and expected utility based approach for managing supply chain risks

TLDR: A supply chain risk network management process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting is developed and operationalised.

About: This article is published in International Journal of Production Economics.The article was published on 2018-02-28 and is currently open access. It has received 144 citations till now. The article focuses on the topics: Supply chain risk management & Risk management.

Frequently asked questions

Q1. What have the authors stated for future works in "Supply chain risk network management: a bayesian belief network and expected utility based approach for managing supply chain risks" ?

This lower bound can further drop in the event of unfavorable correlations within the network. 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 6. 3. Limitations and Future Research Directions Studies focussing on the cost and benefit analysis of implementing these sophisticated frameworks would incentivise practitioners towards adopting interdependency modelling in managing risks. As the risk network developed does not cover all aspects of the supply chain including engineering facets mainly because of the main intention of demonstrating the proposed process and not developing a comprehensive risk network, future research may be directed to developing such risk networks specific to different industries. The upper bound of the expected utility is determined by the efficacy of potential strategies, however, there is another constraint of the budget and the need for an important consideration as to the significance of the relative improvement in expected utility with respect to the marginal cost of implementing these strategies. 

Q2. What contributions have the authors mentioned in the paper "Supply chain risk network management: a bayesian belief network and expected utility based approach for managing supply chain risks" ?

The paper develops and operationalises a supply chain risk network management ( SCRNM ) process that captures interdependencies between risks, multiple ( potentially conflicting ) performance measures and risk mitigation strategies within a ( risk ) network setting. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. The merits and challenges associated with the implementation of interdependency based frameworks are discussed. 

Q3. What is the importance of risk appetite in the decision making framework?

The risk appetite of a decision maker drives the tolerance level with respect to the acceptance of risks and therefore, it is extremely important to integrate risk appetite within the decision making framework. 

Q4. What is the purpose of risk mitigation strategies?

Risk mitigation strategies are implemented in order to reduce the likelihood of occurrence and/or negative impact of risks (Tang & Tomlin, 2008). 

Q5. What is the main limitation of these studies?

There are many studies in the literature with exclusive focus on the impact of supply chain risks on performance measures (Jüttner et al., 2003; Zhao et al., 2013), however, the main limitation of these studies is modelling risks in silo whereas the authors focus on modelling a risk network and evaluating its holistic impact on performance measures. 

Q6. What is the definition of a supply chain risk management process?

2.1. Supply Chain Risk Management Process/FrameworkSCRM is “the identification and management of risks for the supply chain, through a co-ordinated approach amongst supply chain members, to reduce supply chain vulnerability as a whole” (Jüttner et al., 2003, p. 201). 

Q7. What was the quantitative part of the model validated?

The quantitative part was validated through conducting the sensitivity analysis during which some conditional probability values had to be revised as the participants were not satisfied with some of the sensitivity results. 

Q8. What is the probability of each performance measure being realised in a network?

Decision makers are then assumed to evaluate the expected utility of the network:EU = ∑ i∈I piu(si). (3)As the state of risks influences performance measures, the authors introduce the notion of risk propagation measure (RPM) to capture the relative impact of each risk on the set of performance measures modelled within a risk network. 

Q9. how to capture risk in a framework?

Once the framework gets established in its simplified form of risks and strategies with binary states, more general characterisation of risks can be captured. 

Q10. What are the graphs representing the efficacy of potential risk mitigation strategies?

The graphs representing the efficacy of potential risk mitigation strategies were highly appreciated as these helped the decision makers realise the significance of adopting the proposed process without which it would not be possible to segregate optimal strategies from the dominated ones. 

Q11. Why is it not always optimal to mitigate the critical risk identified?

This is because the optimal set comprises two costeffective mitigation strategies applied to relatively less critical risks (R4 and R12) yielding maximum expected utility to the decision maker whereas exclusively mitigating R20 is the most expensive option (costing 100 units) among the set of potential strategies (see Table A.5). 

Q12. What can be done to establish the efficacy of such integrated tools?

Algorithms can be developed to establish the efficacy of such integrated tools considering the effort involved and the precision of results obtained. 

Q13. What are the main reasons why practitioners adhere to using conventional tools to assess risks?

The practitioners adhere to using conventional tools treating risks as independent factors because of various reasons: sophisticated interdependency based tools introduced in theory are rarely applied in industry; practitioners are unable to appreciate the significance of capturing correlations until they acknowledge the extent of damage relevant to adopting risk matrix based tools; use of risk matrix is governed by established risk management standards; and there is not always a commitment from the top management as the implementation of a robust process necessitates time and investment in terms of training staff and enhancing their knowledge to assimilate the underlying mechanism of the process. 

Q14. What were the updated probabilities of the quality (low), timeliness (delayed?

The updated probabilities of the quality (low), timeliness (delayed), market share (low), profit (low) and sustainability (low) were calculated as 0.35, 0.08, 0.68, 0.60 and 0.33, respectively. 

Q15. What was the main merit of the proposed process?

The main merit of the proposed process was acknowledged as the ability to visualise the interconnectedness between the risks and how exactly a risk or a set of risks influences multiple objectives.