Paper Info
Title
Assessing new product development project risk by Bayesian network with a systematic probability generation methodology
Abstract
New product development (NPD) is a crucial process to keep a company being competitive. However, because of its inherent features, NPD is a process with high risk as well as high uncertainty. To ensure a smooth operation of NPD, the risk involved in the process need to be assessed and the uncertainty should also be addressed properly. Facing these two tasks, in this paper, the critical risk factors in NPD are first analyzed. Since Bayesian network is specialized in dealing with uncertainties, those risk factors are then modeled into a Bayesian network to facilitate the assessing of the risk involved in an NPD process. To generate the probabilities of different kinds of nodes in a Bayesian network, a systematic probability generation approach is proposed with emphasis on generating the conditional probabilities of the nodes with multi-parents. A case study is also given in the paper to test and validate the critical risk factors as well as the probability generation approach.
Year
DOI
Venue
2009
10.1016/j.eswa.2009.02.019
Expert Syst. Appl.
Keywords
Field
DocType
systematic probability generation approach,crucial process,new product development,npd process,bayesian network,critical risk factor,conditional probability,systematic probability generation methodology,risk factor,probability generation,probability generation approach,high uncertainty,high risk,new product development project,risk factors
Data mining,Project risk management,Conditional probability,Computer science,Bayesian network,Artificial intelligence,Machine learning,New product development
Journal
Volume
Issue
ISSN
36
6
Expert Systems With Applications
Citations 
PageRank 
References 
23
1.20
16
Authors
5
Name
Order
Citations
PageRank
Kwai-Sang Chin1103354.69
Dawei Tang21566.95
Jian-Bo Yang33832203.05
Shui Yee Wong4384.57
Hongwei Wang552830.86