The development of new and improved management methods for new product development is important. Existing methods suffer from a number of shortcomings, especially their inability to deal with a mixture of quantitative and qualitative data. The objective of this study is to apply decision support techniques (especially Bayesian networks) to the area of new product development management in order to address some of the shortcomings. The research approach is one of decision structuring and modeling. The literature shows the criteria that are important during the management of new product development. These criteria are used in a three-step decision structuring framework to develop a conceptual model based on a Bayesian network, in support of new product development management. The result is a Bayesian network that incorporates the knowledge of experts into a decision support model. The model is shown to be requisite because it contains all the essential elements of the problem on which decision-makers can base their action. The model can be used to perform 'what-if' analyses in various ways, thereby supporting the management of risk in new product development. This research not only contributes a model to support new product development management, but also provides insight into how decision support — especially Bayesian networks — can enhance technology management methods.
Managing supply chain knowledge in the new product development process: A social network analysis approach
