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Eriksson, P E, Atkin, B and Nilsson, T (2009) Overcoming barriers to partnering through cooperative procurement procedures. Engineering, Construction and Architectural Management, 16(06), 598–611.

Laryea, S and Hughes, W (2009) Commercial reviews in the tender process of contractors. Engineering, Construction and Architectural Management, 16(06), 558–72.

Meldrum, A, Hare, B and Cameron, I (2009) Road testing a health and safety worker engagement tool-kit in the construction industry. Engineering, Construction and Architectural Management, 16(06), 612–32.

Ochieng, E G and Price, A D (2009) Framework for managing multicultural project teams. Engineering, Construction and Architectural Management, 16(06), 527–43.

Pellicer, T M, Pellicer, E and Eaton, D (2009) A macroeconomic regression analysis of the European construction industry. Engineering, Construction and Architectural Management, 16(06), 573–97.

Pewdum, W, Rujirayanyong, T and Sooksatra, V (2009) Forecasting final budget and duration of highway construction projects. Engineering, Construction and Architectural Management, 16(06), 544–57.

  • Type: Journal Article
  • Keywords: construction industry; forecasting; neural nets; roads; Thailand
  • ISBN/ISSN: 0969-9988
  • URL: http://www.emeraldinsight.com/10.1108/09699980911002566
  • Abstract:
    Purpose – The purpose of this paper is to develop models to forecast final budget and duration of a highway construction project during construction stage. Design/methodology/approach – Highway construction project data are collected and analyzed to find out factors affecting project final budget and duration before developing the forecasting models, research for which is based on the principle of Artificial Neural Network (ANN). The forecasting results obtained from the proposed method are compared with those obtained from the current method based on earned value.Findings – Factors affecting final budget and duration are presented. The forecasting results obtained from the proposed method based on ANN application are more accurate and stable than those obtained from the current method based on earned value. Research limitations/implications – Factors affecting final budget and duration may differ if applied in other countries, since the project data were collected in the Kingdom of Thailand. The forecasting models, therefore, must be reconsidered for better outcomes. Practical implications – The study presents a useful tool for the highway construction project manager to predict project final budget and duration. The results can potentially provide early warning of over-budget and schedule delay. Originality/value – The ANN models to forecast final budget and duration of highway construction projects during the construction stage, developed by using project data reflecting continual and seasonal cycle data, can provide better predicting results.