Investigation and Analysis of Human, Organizational, and Project Based Rework Indicators in Construction Projects

Elnaz Safapour, Sharareh Kermanshachi

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

11 Scopus citations

Abstract

Since construction project rework is one of the most important causes of cost overruns, the best strategy is to identify the causes of rework at the right time. Therefore, the aim of this study is to investigate and analyze the rework indicators (RIs) belonging three categories of organization, project, and people. To fulfill the objectives of this study, a structured survey was developed in order to collect data associated with various construction project characteristics, change orders, cost, and schedule performance. Appropriate statistical tests were applied to the 39 collected survey responses. The result reveals that the experience of the project management team PMT in the design and/or construction phase, and number of PMTs who work in a construction project are the most important indicators in deriving rework. The findings of this study would assist project managers (PMs) in planning proactively to prevent construction project rework.

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)
Pages505-512
Number of pages8
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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