Robustness Analysis of Design Phase Performance Predictors Using Extreme Bounds Analysis (EBA)

Sharareh Kermanshachi, Behzad Rouhanizadeh

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

3 Scopus citations

Abstract

The design phase is one of the important phases in any construction project. Leading cost and schedule performance indicators of design phase have been studied by some of the researchers, however, these variables' robustness has been studied rarely. The goal of this research is to discern between the robust and fragile cost overrun and schedule delay indicators of the design phase. Both extreme bounds analysis (EBA) methods including Leamer's and Sala-i-Martin were implemented in this research. The Leamer's method only considers the extreme bounds of the indicator's distribution while Sala-i-Martin focuses on the whole indicator's distribution. Results of this study revealed robust cost overrun and schedule delay indicators in the design phase. Project managers can use the findings of this research to prioritize the more robust indicators as higher priority and reduce required design modifications within the project process.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2019
Subtitle of host publicationData, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019
EditorsYong K. Cho, Fernanda Leite, Amir Behzadan, Chao Wang
PublisherAmerican Society of Civil Engineers (ASCE)
Pages563-571
Number of pages9
ISBN (Electronic)9780784482438
StatePublished - 2019
EventASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019 - Atlanta, United States
Duration: Jun 17 2019Jun 19 2019

Publication series

NameComputing in Civil Engineering 2019: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019

Conference

ConferenceASCE International Conference on Computing in Civil Engineering 2019: Data, Sensing, and Analytics, i3CE 2019
Country/TerritoryUnited States
CityAtlanta
Period6/17/196/19/19

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Civil and Structural Engineering

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