Paper Info
Title
A fuzzy weighted average approach for selecting portfolio of new product development projects.
Abstract
New product portfolio selection is a multi-criteria decision making problem including both qualitative and quantitative criteria. Determining the exact values for these criteria is often difficult or even impossible taking into account uncertainty and complexity associated with new product development projects. To assist managers in making portfolio selection decisions, this study proposes a new project portfolio selection model that uses a fuzzy weighted average approach for ranking new product projects and artificial neural networks for estimating project performance. New product development projects are evaluated according to criteria related to marketing, project team, project performance, risk, and strategy. The use of neural networks enables more precise evaluation of project performance criteria and provides additional information in portfolio selection. A case study of the evaluation of new product projects illustrates the usefulness of the proposed approach.
Year
DOI
Venue
2017
10.1016/j.neucom.2016.05.104
Neurocomputing
Keywords
Field
DocType
Fuzzy logic,Neural networks,Fuzzy neural system,Multi-criteria decision making,New product screening
Project portfolio management,Portfolio,Project team,Artificial intelligence,Artificial neural network,Management science,New product development,Application portfolio management,Ranking,Fuzzy logic,Operations research,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
231
C
0925-2312
Citations 
PageRank 
References 
5
0.44
21
Authors
2
Name
Order
Citations
PageRank
Marcin Relich1295.70
Pawel Pawlewski26721.03