Predicting effectiveness of construction project management: decision-support tool for competitive bidding

Predicting effectiveness of construction project management: decision-support tool for competitive bidding

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Article ID: iaor20073602
Country: Greece
Volume: 6
Issue: 3
Publication Date: Sep 2006
Journal: Operational Research - An International Journal
Authors: ,
Keywords: bidding, neural networks
Abstract:

This article presents construction project management effectiveness modelling from the construction management organization perspective. The paper reports on construction project performance data collected from construction management companies in Lithuania and the United States of America. Construction project management effectiveness model (CPMEM) was established by applying artificial neural networks (ANN) methodology. The discussions of project management effectiveness (success) factors identified in the literature were presented. Twelve key determinant factors that influence project management effectiveness in terms of construction cost variation were identified covering areas related to the project manager, project team, project planning, organization and control. The application algorithm of the CPMEM was developed. The CPMEM can be used during the competitive bidding process to evaluate management risk of a construction project and predict construction cost variation.

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