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Abudayyeh, O, Federicks, T, Palmquist, M and Torres, H N (2003) Analysis of Occupational Injuries and Fatalities in Electrical Contracting Industry. Journal of Construction Engineering and Management, 129(02), 152–8.

Ammar, A, Hanna, A S, Nordheim, E V and Russell, J S (2003) Indicator Variables Model of Firm’s Size-Profitability Relationship of Electrical Contractors Using Financial and Economic Data. Journal of Construction Engineering and Management, 129(02), 192–7.

Brown, D C (2003) Novel Method of Excavation. Journal of Construction Engineering and Management, 129(02), 222–5.

Brunso, T P and Siddiqi, K M (2003) Using Benchmarks and Metrics to Evaluate Project Delivery of Environmental Restoration Programs. Journal of Construction Engineering and Management, 129(02), 119–30.

Chua, D K H, Wang, Y and Tan, W T (2003) Impacts of Obstacles in East Asian Cross-Border Construction. Journal of Construction Engineering and Management, 129(02), 131–41.

Cox, R F, Issa, R R A and Ahrens, D (2003) Management’s Perception of Key Performance Indicators for Construction. Journal of Construction Engineering and Management, 129(02), 142–51.

Elliott, M E and Heymsfield, E (2003) Inspection of Luling Bridge Cable Stays: Case Study. Journal of Construction Engineering and Management, 129(02), 226–30.

Hinze, J and Gambatese, J (2003) Factors That Influence Safety Performance of Specialty Contractors. Journal of Construction Engineering and Management, 129(02), 159–64.

Maloney, W F (2003) Labor-Management Cooperation and Customer Satisfaction. Journal of Construction Engineering and Management, 129(02), 165–72.

Marzouk, M and Moselhi, O (2003) Object-oriented Simulation Model for Earthmoving Operations. Journal of Construction Engineering and Management, 129(02), 173–81.

Palaneeswaran, E and Kumaraswamy, M M (2003) Knowledge Mining of Information Sources for Research in Construction Management. Journal of Construction Engineering and Management, 129(02), 182–91.

  • Type: Journal Article
  • Keywords: Construction management; Research; Information management; construction industry; research and development management; optimisation; information technology; Internet;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2003)129:2(182)
  • Abstract:
    Extracting the right information at the right time is vital in any research project. Moreover, researchers generally seek innovative “knowledge mining” techniques for optimizing their research efforts within constrained time frames and with scarce resources. Meanwhile, rapid developments in the fields of computing and information technology drive the accelerated globalization process in both industry and academia. This paper explores some of the emerging technologies and associated research methodologies from an information supply chain perspective. An application in a recent Internet based two-phase questionnaire survey for design/build contractor selection provides a useful case study in the structuring of an innovative knowledge mining strategy. This experience feeds into the formulation of a “high-velocity” knowledge mining framework and a set of guidelines—to facilitate and enhance such innovative construction management research, while dealing with some initial issues/problems in the Internet based research environment. Furthermore, some critical success factors, key performance indicators, and mining strategies are consolidated for marshalling both vivid and tacit knowledge sources, such as by “exploiting” Internet resources for more creative and efficient construction management research.

Schaufelberger, J E and Wipadapisut, I (2003) Alternate Financing Strategies for Build-Operate-Transfer Projects. Journal of Construction Engineering and Management, 129(02), 205–13.

Shi, J J and Halpin, D W (2003) Enterprise Resource Planning for Construction Business Management. Journal of Construction Engineering and Management, 129(02), 214–21.

Trost, S M and Oberlender, G D (2003) Predicting Accuracy of Early Cost Estimates Using Factor Analysis and Multivariate Regression. Journal of Construction Engineering and Management, 129(02), 198–204.