An interview survey of Alberta-based construction contractors was conducted in July and August 1998. The purpose of this survey was to elicit information on the factors that cause unanticipated project cost escalation during construction, from the contractor's perspective. This paper presents the findings of this survey and a proposed method of modeling the factors identified. The majority of factors identified impact labour productivity, which is a major source of cost overruns. A combination of subjective, objective, and secondary indicators are used to measure these factors and to assess their impact on project performance. The main conclusion of this survey is that many of the factors affecting the cost of construction are evaluated in subjective and imprecise terms and are difficult to quantify. This paper presents a method of modeling these factors using fuzzy membership functions, which capture the imprecision and subjectivity associated with the measurement of these factors. It discusses a basis for the definition of these membership functions and a method of calibrating these functions to make them more widely applicable to suit different contexts. These membership functions are being incorporated in a set of expert rules, which reason about the factors affecting costs, their impact on the project, and the appropriate corrective actions. These expert rules are being developed as part of a fuzzy expert system for construction project monitoring and control. A method of calibrating membership functions to suit individual contexts is currently being developed, which would be a significant advancement in the area of fuzzy logic.Key words: construction, costs, expert systems, fuzzy logic, project control, survey.