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Capacity Expansion Policy and Its Risk in New Product Diffusion
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
(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 [en]
Bass diffusion, capacity expansion, system dynamics, information, risk management
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-78761OAI: oai:DiVA.org:liu-78761DiVA: diva2:535615
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2012-06-20Bibliographically approved
In thesis
1. Supply Chain Risk Management: Identification, Evaluation and Mitigation Techniques
Open this publication in new window or tab >>Supply Chain Risk Management: Identification, Evaluation and Mitigation Techniques
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
Supply chain risk management, risk analysis, risk control, co-citation, system dynamics, modelling
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-78763 (URN)978-91-7519-866-8 (ISBN)
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

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