scholarly journals Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry

2018 ◽  
Vol 21 (7) ◽  
pp. 847-864 ◽  
Author(s):  
Gholamreza Soltani-Fesaghandis ◽  
Alireza Pooya

Predicting the performance of the new product development and selecting the strategy in the case of new product development failure is an issue that has drawn the attention of the many managers. Therefore, the goal of this study is to design an integrated system of prediction of product development success and selection of a proper market-product strategy by the method of artificial intelligence in companies working in the food industry. The population of this study was 250 companies of the food industries in Iran. The inputs and outputs of the success of the new product development were obtained from the research literature. Moreover, Ansoff matrix was applied to select the market-product strategy. A questionnaire was used to collect the data in this study. The adaptive neural-fuzzy network method and the fuzzy inference system are used to analyze the data. The results show that the Chief Executive Officers of companies working in the food industry may take action to predict a new product development success before developing the new product and use alternative strategies if needed.

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.


1998 ◽  
Vol 1 (2-3) ◽  
pp. 11-15
Author(s):  
Prisana Suwannaporn ◽  
Mark Speece

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