Model for Construction Budget Performance—Neural Network Approach

Abstract

A neural network approach is used to identify the key management factors that affect budget performance in a project. Field data of project performance has been used to build the budget performance model. This approach allows the model to be built even if the functional interrelationships between input factors and output performance cannot be clearly defined. Altogether eight key determining factors were identified covering areas related to the project manager, project team, and planning and control efforts, namely: number of organizational levels between project manager and craftsmen, project manager experience on similar technical scope, detailed design complete at start of construction, constructability program, project team turnover rate, frequency of control meetings during construction, frequency of budget updates, and control system budget. The model is able to give good predictions even with previously unseen data and incomplete information on the key factors. The model can be used to evaluate various management strategies and thus resources can be effectively deployed to strengthen these aspects of project management.

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