Modeling of Risk Management Strategies for SMEs Using ANN under Various Levels of Operational Risks

Abstract:

In competitive world, it becomes essential for the firms to consider the risks and uncertainties as the core concerns. To control the risks, various strategies like multiple sourcing, horizontal/ vertical integrations, buffer stocks etc are employed. But, out of many available risk mitigation strategies, SMEs usually prefer to keep excess safety stocks to manage the operational risks as they have feeble control and position in supply chain as well as limited means to employ other strategies, which requires skills and resources. Keeping appropriate safety stocks becomes a very complex and crucial problem for SMEs as excess stocks reduces the efficiency and shortage of it may make their position vulnerable in supply chains. Concerning to this issue, this paper focuses on operational risks with SME perspectives and explores the appropriate safety inventory levels using artificial neural network models and the results are further simulated with various settings of risk scenarios.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 1683-1691
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.1683
• Online since: January 2012
• Authors: Piyush Singhal, Gopal Agarwal, M L Mittal
• Keywords: Artificial Neural Network (ANN), Operational Risks, SME

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