<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer’s comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.</p></abstract>

The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer’s comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.

Estimating New Product Success with the Use of Intelligent Systems

Faculty of Economics and Management, University of Zielona Góra, Zielona Góra, Poland

Faculty of Electronic and Computer Engineering, Koszalin University of Technology, Koszalin, Poland

Foundations of Management

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Estimating New Product Success with the Use of Intelligent Systems"}

The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on...

Estimating New Product Success with the Use of Intelligent Systems

Data publikacji: 11 mar 2015

Zakres stron: 7 - 20

DOI: https://doi.org/10.1515/fman-2015-0007

© Faculty of Management, Warsaw University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.