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The effectiveness of the IpOp model decision tree to calibrate projects at the pre-project stage

Author

Listed:
  • Nadina Müller
  • Mark Moses
  • Raphaël H. Cohen

Abstract

Literature supports the idea that projects delivering the target objective on time and within the anticipated budget represent less than 30% of all projects. Even though failure advances the learning curve, this low success rate equals a vast waste of resources. Based on practical experience, the authors hypothesise that: 1) low project success rates are linked to inadequate project selection methodologies or their inconsistent application; 2) the IpOp model decision tree could improve the selection of worthy projects. An online survey was carried out to determine: 1) project success rate; 2) links between project performance and selection parameters. Results show the importance of rigour in project selection in order to reduce waste of resources, while no clear correlation between the number of selection criteria could be proven. Further, the results indicate that practitioners consider the IpOp model decision tree to evaluate projects at pre-project stage an improvement over current practice.

Suggested Citation

  • Nadina Müller & Mark Moses & Raphaël H. Cohen, 2024. "The effectiveness of the IpOp model decision tree to calibrate projects at the pre-project stage," International Journal of Business and Globalisation, Inderscience Enterprises Ltd, vol. 37(3), pages 404-423.
    • Handle: RePEc:ids:ijbglo:v:37:y:2024:i:3:p:404-423
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