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Relative performance of judgmental methods for forecasting the success of megaprojects

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  • Litsiou, Konstantia
  • Polychronakis, Yiannis
  • Karami, Azhdar
  • Nikolopoulos, Konstantinos

Abstract

Forecasting the success of megaprojects, such as the Olympic Games or space exploration missions, is a very difficult but important task, due to their complexity and the large capital investment they require. Typically, megaproject stakeholders do not employ formal forecasting methods, but instead rely on impact assessments and/or cost–benefit analysis; however, as these tools do not necessarily include forecasts, there is no accountability. This study evaluates the effectiveness of judgmental methods for successfully forecasting the accomplishment of specific megaproject objectives, where the measure of success is the collective accomplishment of such objectives. We compare the performances of three judgmental methods used by a group of 69 semi-experts: unaided judgement (UJ), semi-structured analogies (s-SA), and interaction groups (IG). The empirical evidence reveals that the use of s-SA leads to accuracy improvements relative to UJ. These improvements are amplified further when we introduce the pooling of analogies through teamwork in IG.

Suggested Citation

  • Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
  • Handle: RePEc:eee:intfor:v:38:y:2022:i:3:p:1185-1196
    DOI: 10.1016/j.ijforecast.2019.05.018
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

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