Predicting and Evaluating Construction Trades Foremen Performance: Fuzzy Logic Approach
Publication: Journal of Construction Engineering and Management
Volume 135, Issue 9
Abstract
This paper illustrates a fuzzy logic model for use in predicting and evaluating the performance of construction trades foremen. The model assists in measuring the effectiveness of a foreman, monitoring improvements in effectiveness over time, and identifying areas where a foreman requires training or mentoring to improve his/her performance. This paper also discusses the factors that affect the performance of a foreman in each area of responsibility. The structure of the model and the use of fuzzy logic are described. The model is validated using data collected from an actual construction company, illustrating its high level of linguistic accuracy. This model is relevant to researchers and makes a contribution to performance evaluation by developing a methodology for evaluating and predicting the performance of construction trades foremen. The model provides a complete approach for handling uncertainty inherent in performance evaluation by using fuzzy logic. The use of fuzzy logic in the model allows users to express themselves linguistically and to make assessments that are subjective in nature. It is relevant to construction industry practitioners since it provides them with a useful technique for evaluating the performance of foremen and identifying the factors that affect their performance on a daily basis. Last, the model offers the advantage of benchmarking foreman performance, allowing organizations to develop plans to improve the performance of their foremen over time.
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Acknowledgments
The writers would like to express their sincere appreciation for the contributions to this research made by the pilot study participants at Ledcor Industrial. The COAA Workforce Development Supervisory Training and Qualifications Subcommittee, members provided guidance throughout the study. In addition, the writers would like to thank Dr. Yasser Mohamed and Dr. Peter Flynn for their valuable and helpful comments. This research was made possible by the financial support of the NSERC Associate Industrial Research Chair in Construction Engineering and Management at the University of Alberta under a Natural Sciences and Engineering Industrial Research Chair Grant No. NSERCNSERC IRCPJ 349527–05.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 135 • Issue 9 • September 2009
Pages: 920 - 929
Copyright
© 2009 ASCE.
History
Received: Aug 28, 2008
Accepted: Feb 26, 2009
Published online: Apr 30, 2009
Published in print: Sep 2009
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