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Aibinu, A A and Odeyinka, H A (2006) Construction Delays and Their Causative Factors in Nigeria. Journal of Construction Engineering and Management, 132(07), 667–77.

Brilakis, I and Soibelman, L (2006) Multimodal Image Retrieval from Construction Databases and Model-Based Systems. Journal of Construction Engineering and Management, 132(07), 777–85.

Caldas, C H, Torrent, D G and Haas, C T (2006) Using Global Positioning System to Improve Materials-Locating Processes on Industrial Projects. Journal of Construction Engineering and Management, 132(07), 741–9.

Galloway, P D (2006) Comparative Study of University Courses on Critical-Path Method Scheduling. Journal of Construction Engineering and Management, 132(07), 712–22.

Galloway, P D (2006) Survey of the Construction Industry Relative to the Use of CPM Scheduling for Construction Projects. Journal of Construction Engineering and Management, 132(07), 697–711.

Ho, S P (2006) Model for Financial Renegotiation in Public-Private Partnership Projects and Its Policy Implications: Game Theoretic View. Journal of Construction Engineering and Management, 132(07), 678–88.

Lædre, O, Austeng, K, Haugen, T I and Klakegg, O J (2006) Procurement Routes in Public Building and Construction Projects. Journal of Construction Engineering and Management, 132(07), 689–96.

Lowe, D J, Emsley, M W and Harding, A (2006) Predicting Construction Cost Using Multiple Regression Techniques. Journal of Construction Engineering and Management, 132(07), 750–8.

Lucko, G, Anderson-Cook, C M and Vorster, M C (2006) Statistical Considerations for Predicting Residual Value of Heavy Equipment. Journal of Construction Engineering and Management, 132(07), 723–32.

  • Type: Journal Article
  • Keywords: Construction equipment; Cost management; Regression analysis; Data analysis; Economic factors; Confidence intervals; Validation;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:7(723)
  • Abstract:
    Residual value needs to be considered in owning cost calculations for used heavy construction equipment. Its dependency on factors such as manufacturer and model, equipment age, and condition rating can best be examined by analyzing real market data from equipment auctions. Macroeconomic indicators can also be included to examine any potential influence of the overall economy on auction prices. This paper discusses statistical considerations for performing such a residual value analysis. Considerations include the study type, data properties, identifying outlier observations, regression assumptions, and formulating and selecting an appropriate regression model using the adjusted coefficient of determination. A second-order polynomial of equipment age with additive factors appears promising as the final regression model. Adjusted confidence and prediction intervals are created to correctly display residual value. Cross-validation using randomly split halves of the dataset is performed. Actual data for medium track dozers are used to illustrate the validity of the methodology.

Mullens, M A and Arif, M (2006) Structural Insulated Panels: Impact on the Residential Construction Process. Journal of Construction Engineering and Management, 132(07), 786–94.

Navon, R and Kolton, O (2006) Model for Automated Monitoring of Fall Hazards in Building Construction. Journal of Construction Engineering and Management, 132(07), 733–40.

Reinschmidt, K and Trejo, D (2006) Economic Value of Building Faster. Journal of Construction Engineering and Management, 132(07), 759–66.

Rezgui, Y and Zarli, A (2006) Paving the Way to the Vision of Digital Construction: A Strategic Roadmap. Journal of Construction Engineering and Management, 132(07), 767–76.