Risk Analysis of New Product Development Using Bayesian Networks

Document Type : Original Article

Authors

1 Assistant Professor, Department of Management, University of Guilan

2 M.A. of Industrial Management, University of Guilan

3 M.S. of Industrial Engineering, Hamedan Booali Sina University

Abstract

The process of presenting new product development (NPD) to market is of great importance due to variability of competitive rules in the business world. The product development teams face a lot of pressures due to rapid growth of technology, increased risk-taking of world markets and increasing variations in the customers` needs. However, the process of NPD is always associated with high uncertainties and complexities. To be successful in completing NPD project, existing risks should be identified and assessed. On the other hand, the Bayesian networks as a strong approach of decision making modeling of uncertain situations has attracted many researchers in various areas. These networks provide a decision supporting system for problems with uncertainties or probable reasoning. In this paper, the available risk factors in product development have been first identified in an electric company and then, the Bayesian network has been utilized and their interrelationships have been modeled to evaluate the available risk in the process. To determine the primary and conditional probabilities of the nodes, the viewpoints of experts in this area have been applied. The available risks in this process have been divided to High (H), Medium (M) and Low (L) groups and analyzed by the Agena Risk software. The findings derived from software output indicate that the production of the desired product has relatively high risk. In addition, Predictive support and Diagnostic support have been performed on the model with two different scenarios.

Keywords

References

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History

  • Receive Date: 14 June 2016
  • Revise Date: 20 July 2018
  • Accept Date: 14 June 2016

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