Integrating Knowledge Management Process inside New Product Development Phase: The Network Model

Author(s):  
Raed Hanandeh ◽  
Angelo Corallo ◽  
Antonio Zilli
Author(s):  
Bak Aun Teoh ◽  
Wei Hong Ling ◽  
Amlus Ibrahim

The growth in new knowledge and technology has substantially increased the complexity of the projects that is strongly influencing the time, cost, and quality of the project management. Due to the volatility of the current market, the effectiveness of knowledge management (KM) could reduce the project uncertainties, project life cycle costs, and risks of new product development (NPD). Since NPD is regarded as the key to innovation due to its strong connection between the knowledge and core competence, the ways how the knowledge will be captured, created, and shared among the project teams is important to remain competitive in today's business and market competition. Hence, the modes of how they are created and shared between the project team members as well as the impact of KM towards NPD will be discussed in this paper. KM are normally created and transferred through the conversion between explicit and tacit knowledge, which can be further applied into the project management. Furthermore, the existing knowledge of the organisation can be evaluated by the actions of decision makers, hence, it is undoubted that a better knowledge can lead to measurable efficiencies in production and product development. The key success factors of KM that have been implemented will be discussed in this paper as well, which help to increase the probability of project success. Keywords: New Product Development; Project Management; Knowledge Management; Globalisation


Author(s):  
Maria Manuel Mendes ◽  
Jorge F.S. Gomes ◽  
Bernardo Batiz-Lazo

This chapter uses key concepts in the knowledge management literature to analyse the procedures and practices used by a team during a new product development project. More precisely, the knowledge process or knowledge cycle is used as a means to examine issues relating to knowledge identification, creation, storage, dissemination, and application in new product development. Results from the case study also suggest that the knowledge process may be valuable in assessing the structural elements of knowledge management, but fails to provide a more comprehensive explanation of the dynamics and complexities involved. This suggests that more elaborate models are needed to explain how knowledge is created, shared and used in knowledge-intensive processes.


Author(s):  
Nassim Belbaly ◽  
Hind Benbya

The objective of this chapter is to provide an analytical tool to assist organizations in their implementations of Intelligent Knowledge Management Systems (IKMS) along the new product development (NPD) process. Indeed, organizations rely on a variety of systems using Artificial Intelligence to support the NPD process that depends on the maturity stage of both the process and type of knowledge managed. Our framework outlines the technological and organizational path that organizations have to follow to integrate and manage knowledge effectively along their new product development process. In doing so, we also address the main limitations of the systems used to date and suggest the evolution towards a new category of KMS based on artificial intelligence that we refer to as Intelligent Knowledge Management Systems. We illustrate our framework with an analysis of several case studies.


Author(s):  
Nassim Belbaly ◽  
Hind Benbya

The objective of this chapter is to provide an analytical tool to assist organizations in their implementations of Intelligent Knowledge Management Systems (IKMS) along the new product development (NPD) process. Indeed, organizations rely on a variety of systems using Artificial Intelligence to support the NPD process that depends on the maturity stage of both the process and type of knowledge managed. Our framework outlines the technological and organizational path that organizations have to follow to integrate and manage knowledge effectively along their new product development process. In doing so, we also address the main limitations of the systems used to date and suggest the evolution towards a new category of KMS based on artificial intelligence that we refer to as Intelligent Knowledge Management Systems. We illustrate our framework with an analysis of several case studies.


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