Quantifying uncertainty and equivocality in engineering projects

Andrew Chang and Chih-Chiang Tien

Construction Management and Economics, 2006, vol. 24, issue 2, 171-184

Abstract: Engineering work is intangible and difficult to measure and manage. Engineering project tasks entail various degrees of uncertainty and equivocality (U&E). Quantifying U&E of project tasks helps understand and manage engineering work. This study developed an assessing questionnaire from five sources of U&E and tested it on a large subway design project. Questions were answered by nine discipline managers of 58 tasks and the quantified U&E scores reflect reality. It was found that uncertainty is higher than equivocality for most tasks. The U&E reduction test shows that task U&E decrease over one year and different reduction patterns exist. Task-possessed information contributes the largest decrease. This means information from planning, past projects or experiences is very important to performing new projects. The developed questionnaire can be a useful tool to help managers better understand and plan project tasks.

Keywords: Case study; information processing; organizational theory; project management; uncertainty (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/01446190500310353 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:conmgt:v:24:y:2006:i:2:p:171-184

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCME20

DOI: 10.1080/01446190500310353

Access Statistics for this article

Construction Management and Economics is currently edited by Will Hughes

More articles in Construction Management and Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().