Analyzing risk factors affecting project cost overrun

Masateru Tsunoda, Akito Monden, Kenichi Matsumoto, Ryosuke Hatano, Toshihiko Nakano, Yutaka Fukuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To prevent cost overrun of software projects, it is effective to predict the project which has high risk of cost overrun in the early phase of the project. In this paper, we clarify the risk factors which affect cost overrun. The risk factors are denoted by the questions such as Are the customer's project goals clear? The risk factors can be used as independent variables of the cost overrun prediction model. In the analysis, we used 290 projects' data collected in a software development company. The dataset was stratified by the project start time and the project size to eliminate their influence, and relationships between risk factors and cost overrun were analyzed with the correlation ratio. In addition, we focused risk factors which have strong and stable relationships to cost overrun, and analyzed them using the Sharpe ratio based index. As a result, we identified some risk factors which have relatively strong and stable relationships to cost overrun. After the analysis, we experimentally predicted cost overrun projects by collaborative filtering, using the risk factors as independent variables. The result suggested that cost overrun projects can be predicted by the risk factors.

Original languageEnglish
Title of host publicationSoftware Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012
PublisherSpringer Verlag
Pages171-184
Number of pages14
ISBN (Print)9783642321719
DOIs
Publication statusPublished - Jan 1 2013
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume443
ISSN (Print)1860-949X

Keywords

  • Sharpe ratio
  • collaborative filtering
  • correlation ratio
  • risk management
  • stratification

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Tsunoda, M., Monden, A., Matsumoto, K., Hatano, R., Nakano, T., & Fukuchi, Y. (2013). Analyzing risk factors affecting project cost overrun. In Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012 (pp. 171-184). (Studies in Computational Intelligence; Vol. 443). Springer Verlag. https://doi.org/10.1007/978-3-642-32172-6_14