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Supply Chain Risk Management: Identification, Evaluation and Mitigation Techniques
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Supply chains have expanded rapidly over the decades, with the aim to increase productivity, lower costs and fulfil demands in emerging markets. The increasing complexity in a supply chain hinders visibility and consequently reduces one’s control over the process. Cases of disruption such as the ones faced by Ericsson and Enron, have shown that a risk event occurring at one point of the supply chain can greatly affect other members, when the disruption is not properly controlled. Supply chain management thus faces a pressing need to maintain the expected yields of the system in risk situations. To achieve that, we need to both identify potential risks and evaluate their impacts, and at the same time design risk mitigation policies to locate and relocate resources to deal with risk events.

This dissertation aims to analyse how supply chain risks could be effectively managed. This is done firstly by positioning the research agenda in supply chain risk management (SCRM). Then, methods for effective management of supply chain risk are identified and analysed. In order to find these, we develop a research framework in which the supply chain system is divided into subsystems based on the operations of make, source and deliver; as well as on material, financial and information flows. Furthermore, research questions are raised in order to understand the impact of risks on supply chains, to identify the performance measures for monitoring supply chains, and to determine risk mitigation strategies for improving system performances.

This dissertation includes a bibliometric analysis of relevant literature of SCRM published in recent years. Based on the co-citation analysis, we identify the changing interest in SCRM, from performance-focused individual issues in the early years to integrated system issues with management perspective in recent years. We also identify the growing importance of information issues in SCRM. However, there is a relative lack of research into risk mitigation focusing on information flows in the literature.

This dissertation also develops a conceptual model for analysing supply chain risk. The adoption of tools from the established field of reliability engineering provides a systematic yet robust process for risk analysis in supply chains. We have found that the potential use of a stand-alone tool of Failure Modes and Effect Analysis (FMEA) or a hybrid application of Fault Tree Analysis (FTA) and Analytical Hierarchy Process (AHP), will be most appropriate in SCRM.

Apart from above mentioned studies, this dissertation then includes three manuscripts respectively investigating the risk mitigation policies in SCRM. First, we suggest a dynamic pricing policy when facing supply yield risk, such as price postponement, where price is determined only after receiving the delivery information. This postponed pricing, can improve the balance between supply and demand, especially when the delivery quantity is small, demand has a low uncertainty and there is a wide range when demand is sensible to price change. In another paper, a system dynamics model is developed to investigate the dispersion of disruption on the supply chain operation as well as along the network. Based on this simulation model, policies are tested to observe their influence to the performance of the supply chain. The study results support the benefit of a dual-sourcing strategy. Furthermore, information sharing, appropriate order splitting and time to react would further improve the supply chain performance when disruption strikes. In the last paper, we study how capacity should be expanded when a new product is introduced into the market. The major risk here is due to a quick capacity expansion with large investments which could be difficult to recover. Using the Bass diffusion model to describe demand development, we study how capacity expansion, together with sales plan could affect the economics of the system. Using sales information for the forecast, delaying the sales and adding initial inventories, should create a better scheme of cash flows.

This dissertation contributes in several ways to the research field of SCRM. It plots research advancements which provide further directions of research in SCRM. In conjunction with the conceptual model, simulations and mathematical modelling, we have also provided suggestions for how a better and more robust supply chain could be designed and managed. The diversified modelling approaches and risk issues should also enrich the literature and stimulate future study in SCRM.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. , 57 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1459
Keyword [en]
Supply chain risk management, risk analysis, risk control, co-citation, system dynamics, modelling
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-78763ISBN: 978-91-7519-866-8 (print)OAI: oai:DiVA.org:liu-78763DiVA: diva2:535627
Public defence
2012-06-15, ACAS, Hus A, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved
List of papers
1. Identifying risk issues and research advancements in supply chain risk management
Open this publication in new window or tab >>Identifying risk issues and research advancements in supply chain risk management
2011 (English)In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 133, no 1, 25-34 p.Article in journal (Refereed) Published
Abstract [en]

The purpose of this paper is to investigate the research development in supply chain risk management (SCRM), which has shown an increasing global attention in recent years. Literature survey and citation/co-citation analysis are used to fulfil the research task. Literature survey has undertaken a thorough search of articles on selected journals relevant to supply chain operations management. Meanwhile, citation/co-citation analysis uses Web of Sciences database to disclose SCRM development between 1995 and 2009. Both the approaches show similar trends of rising publications over the past 15 years. This review has piloted us to identify and classify the potential risk associated with different flows, namely material, cash and information flows. Consequently, we identify some research gaps. Even though there is a pressing need and awareness of SCRM from industrial aspect, quantitative models in the field are relatively lacking and information flow risk has received less attention. It is also interesting to observe the evolutions and advancements of SCRM discipline. One finding is that the intellectual structure of the field made statistically significant increase during 2000-2005 and evolved from passively reacting to vague general issues of disruptions towards more proactively managing supply chain risk from system perspectives.

Place, publisher, year, edition, pages
Elsevier, 2011
Keyword
Supply chain; Risk management; Citation/co-citation analysis
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-69766 (URN)10.1016/j.ijpe.2010.06.013 (DOI)000292942100004 ()
Available from: 2011-08-10 Created: 2011-08-08 Last updated: 2017-12-08Bibliographically approved
2. Assessing Supply Chain Risk Adopting Reliability Tools
Open this publication in new window or tab >>Assessing Supply Chain Risk Adopting Reliability Tools
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The gradual expansion of supply chains has developed its own risk. A single disruption at any element or flow will eventually affect the whole system. It can be observed now that there has been an increase in awareness of the risks involved with supply chain disruption. Many have shown concern over the significance of reliable systems which can identify risk prior to the event, assess the consequences of risk events, and, at the same time, be capable of controlling and managing the events that lead to disruption risk throughout supply chain.

However, risk issue has not been thoroughly evaluated from the perspective of supply chain performance measures. This is possibly due to the lack of detailed and specific measurement tools for systematically identifying and evaluating supply chain risks. In this study, reviews conducted on relevant journals have guided our search to identify significant components in developing supply chain risk analysis models i.e., risk identification, estimation and evaluation. We explore each component and highlight the respective requirements.

Acknowledging the well-developed risk analysis methods in the Reliability Engineering field, we consider the possibility of adopting the same approaches in the field of Supply Chain Risk Management. Thus we evaluate the advantages and disadvantages of several risk analysis methods applied in Reliability Engineering field, for example, Failure Modes and Effect Analysis (FMEA), Fault Tree Analysis (FTA), Event Tree Analysis (ETA), Hazards and Operability Analysis (HAZOP), Cause and Effect Diagram (CAED) and Analytical Hierarchy Process (AHP).

We analyse the similarities and gaps between the two fields with the aim to propose a tool that is suitable for supply chain risk analysis. We find that the use of a stand-alone tool of FMEA or a hybrid application of FTA and AHP is potentially most appropriate in Supply Chain Risk Management.

Keyword
Supply Chain, Risk Management, Risk Analysis, Risk Assessment, Reliability
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78757 (URN)
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved
3. Dynamic pricing in the newsvendor problem with yield risks
Open this publication in new window or tab >>Dynamic pricing in the newsvendor problem with yield risks
2012 (English)In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 139, no 1, 127-134 p.Article in journal (Refereed) Published
Abstract [en]

Nowadays supply chains are facing challenges in managing risk issues. Supply of raw materials may exhibit a random yield due to technical failure of production resources or supply disruption after a natural disaster. In case supply has a random yield, one way to reduce supply chain loss is by introducing a dynamic pricing policy, with the aim of manipulating demand in the market while inducing the customer to buy substitute products temporarily. This paper investigates newsvendor problem with random demand and random yields, in which the price decision will be postponed and determined upon recognition of random yield and prior to realising demand uncertainties. With the objective of maximising expected profits, we develop the optimal price and ordering decisions in the system, while comparing the system's performances with dynamic and fixed pricing policies. Further, we investigate the conditions of adapting dynamic pricing policy. An interesting finding shows that such a policy brings increase in benefit when demand uncertainty is small. The outcome of this research provides alternative solutions in designing a robust supply chain.

Place, publisher, year, edition, pages
Elsevier, 2012
Keyword
Yield risk; Dynamic pricing; Supply chain risk management; Newsvendor problem
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78759 (URN)10.1016/j.ijpe.2011.01.018 (DOI)000306877300016 ()
Note

funding agencies|National Natural Science Foundation of China|70832005|

Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2017-12-07Bibliographically approved
4. Information Flow and Mitigation Strategy in a Supply Chain under Disruption
Open this publication in new window or tab >>Information Flow and Mitigation Strategy in a Supply Chain under Disruption
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Current supply chain systems are structurally and behaviourally complex. The aim of this paper is to investigate the consequences of a supply chain in the case of disruption risk by exploiting the information flow. When studying supply chain disruption, there are two important aspects to be considered; the dynamics of supply chain information flow and the behaviour of supply chain entities towards disruption. Our simulation model proposes a system dynamics approach to cater for the dynamic properties of supply chain information flow when disruption occurs at one of its entities. In particular, we focus on the operational reaction of a supply chain which employs a dualsouring principle with a back-up supplier.

According to our observation, information flow is often transmitted throughout the network, resulting in a continuous influence on individual entities after any change occurs. In addition, each entity reacts differently when it identifies disruption in information flow. This variety of reactions further influences the information flow and may also contribute to the disturbance of information. Severe disruption shows signs of impacts on the supply chain earlier and longer. The implementation of dual-sourcing helps to reduce disruption impacts. An appropriate order shifting and a quick reaction time could further reduce disruption impacts. However, entirely shifting orders to a backup supplier is not always recommended. Furthermore, in most cases, the earlier the revised order splitting is executed, the lower the impact that is observed. We also identify that extensive information sharing applied within a supply chain brings agility, which further results in a better system reaction towards disruption.

Keyword
Supply chain risk management, simulation modelling, system dynamics, dual-sourcing
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78760 (URN)
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved
5. Capacity Expansion Policy and Its Risk in New Product Diffusion
Open this publication in new window or tab >>Capacity Expansion Policy and Its Risk in New Product Diffusion
(English)Manuscript (preprint) (Other academic)
Abstract [en]

It is difficult to know how much one should invest in expanding capacity when a new product is introduced to market, because there is often a lack of data for sales history. Based on the Bass diffusion model, we analyze the principles of capacity augmentation using progressive expansion and lumping expansion policies. In addition, decisions for capacity expansion also rely on four scenarios for collecting forecast information, either one or a combination of market demand, backlogs and sales information. For both progressive and lumping policies, this paper suggests the use of sales information for capacity forecasting. This should restrict the sales by limiting the speed of capacity expansion, and thus creates a drift of diffusion curve and avoids the over-investment of capacity. It is also important to define the initial capacity level, which is preferably at a value near the initial demand in a market. In the worst case of having too low initial capacity, delay of sales and adding initial inventory can significantly improve the system performance, in particular when capacity expansion is based on sales forecast. The result of this study is strategically important for defining the capacity position in a new product diffusion process.

Keyword
Bass diffusion, capacity expansion, system dynamics, information, risk management
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78761 (URN)
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved

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