Critical managerial factors affecting defense projects success: A comparison between neural network and regression analysis

Dov Dvir, Arie Ben-David, Arik Sadeh, Aaron J. Shenhar

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

A comparison between neural networks and linear regression analysis is used for identifying critical managerial factors affecting the success of high-tech defense projects. The study shows that neural networks have better explanatory and prediction power, and it enables the exploration of relationships among the data that are difficult to arrive at by traditional statistical methods. The study yielded some new results: The chances to success of a project that was acknowledged by its prospected customers as essential for improving their performance are much higher than other projects. Furthermore, organizational learning and social cohesion of the development team are of extreme importance for success.

Original languageEnglish
Pages (from-to)535-543
Number of pages9
JournalEngineering Applications of Artificial Intelligence
Volume19
Issue number5
DOIs
StatePublished - 1 Aug 2006

Keywords

  • Defense development projects
  • Managerial success factors
  • Neural networks

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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