ITcon Vol. 20, pg. 275-294, http://www.itcon.org/2015/18

Human computation enabled organizational learning in the face of deep uncertainty: example of conceptual estimating

revised:March 2015
published:April 2015
editor(s):Ruikar K
authors:Jing Du, Assistant Professor,
Department of Construction Science, The University of Texas at San Antonio;
email: jing.du@utsa.edu

Mohamed El-Gafy, Associate Professor,
School of Planning, Design and Construction, Michigan State University;
email: elgafy@msu.edu
summary:Parametric estimating has been widely used in conceptual estimating to tackle quality and efficiency related issues. Despite the merits obtained, human involvement is always missing from the decision process and organizational learning is difficult to realize because knowledge of experienced estimators is not well preserved. This paper proposes a paradigm and a corresponding information system that combine the intelligence of humans and computational power of computers, streamline the information flow in the mixture of human-computer-network, and solicit and preserve knowledge of estimators in proposal development. The Human Computation paradigm created by Von Ahn has been tailored to tackle the construction conceptual estimating problems. A Cloud computing infrastructure that supports the proposed paradigm is also proposed. In order to demonstrate the applicability and validity of the proposed paradigm and information system, a case study of the proposal development of a power plant project is introduced. The findings confirm that the proposed paradigm and information system can be used to advance knowledge transfer and organizational learning in construction problems where necessary information is not always available. Although designed for conceptual estimating problems, the proposed paradigm and information system can be applied in other construction engineering and management problems fraught with deep uncertainties.
keywords:conceptual estimating, human computation, organizational learning, information system
full text: (PDF file, 1.107 MB)
citation:Du J, El-Gafy M (2015). Human computation enabled organizational learning in the face of deep uncertainty: example of conceptual estimating, ITcon Vol. 20, pg. 275-294, https://www.itcon.org/2015/18