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Berg, R and Hinze, J (2005) Theft and Vandalism on Construction Sites. Journal of Construction Engineering and Management, 131(07), 826–33.

Castañeda, J A, Tucker, R L and Haas, C T (2005) Workers’ Skills and Receptiveness to Operate Under the Tier II Construction Management Strategy. Journal of Construction Engineering and Management, 131(07), 799–807.

Chua, D K and Shen, L J (2005) Key Constraints Analysis with Integrated Production Scheduler. Journal of Construction Engineering and Management, 131(07), 753–64.

Horman, M J and Thomas, H R (2005) Role of Inventory Buffers in Construction Labor Performance. Journal of Construction Engineering and Management, 131(07), 834–43.

Lee, S, Thomas, S R and Tucker, R L (2005) Web-Based Benchmarking System for the Construction Industry. Journal of Construction Engineering and Management, 131(07), 790–8.

  • Type: Journal Article
  • Keywords: Construction costs; Productivity; Performance characteristics; Project management; Bench marks; Internet;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:7(790)
  • Abstract:
    The construction industry has been slow to adopt competitive benchmarking as a tool for continuous improvement. The nature of the industry, its projects, participants, and methods of execution differ widely from the manufacturing sectors making traditional benchmarking models developed for manufacturing difficult to adapt. This paper presents a benchmarking system developed by the Construction Industry Institute (CII) for broad application in the construction industry. During the past couple of years, the CII Benchmarking and Metrics (BM&M) system has been ported to a web-based system of data collection, performance and practice use reporting, and industry analysis. CII serves as a third-party facilitator and data clearinghouse to permit the sharing of highly confidential project data in a competitive environment. Cost, schedule, safety, practice use, and productivity data are now collected on-line during project execution 24∕7 from the most remote project sites. Confidential reports are returned online showing metric scores, performance quartiles, and graphical comparisons of individual project performance to a database of similar projects. This paper addresses many of the issues that have served as barriers to benchmarking for the construction industry and provides an overview of how CII is confronting these issues. A background and a descriptive discussion of the database is provided and a few key findings from the data analyses are presented.

Mitropoulos, P, Abdelhamid, T S and Howell, G A (2005) Systems Model of Construction Accident Causation. Journal of Construction Engineering and Management, 131(07), 816–25.

Park, H, Thomas, S R and Tucker, R L (2005) Benchmarking of Construction Productivity. Journal of Construction Engineering and Management, 131(07), 772–8.

Thomas, H R, Riley, D R and Messner, J I (2005) Fundamental Principles of Site Material Management. Journal of Construction Engineering and Management, 131(07), 808–15.

Wilmot, C G and Mei, B (2005) Neural Network Modeling of Highway Construction Costs. Journal of Construction Engineering and Management, 131(07), 765–71.

Xu, T, Tiong, R L, Chew, D A and Smith, N J (2005) Development Model for Competitive Construction Industry in the People’s Republic of China. Journal of Construction Engineering and Management, 131(07), 844–53.

Zayed, T M and Halpin, D W (2005) Productivity and Cost Regression Models for Pile Construction. Journal of Construction Engineering and Management, 131(07), 779–89.