2019 CSCE Annual Conference - Laval (Greater Montreal) Conference
Dr. Farnaz Sadeghpour, University of Calgary
Dr. George Jergeas , University of Calgary
Forming 46% of Canada’s goods-producing GDP and employing over two-hundred fifty thousand people, the heavy industrial sector is a major driver of the economy. Construction projects in this sector, however, tend to experience significant delays during project delivery. These delays prevent the start of production, which impacts profitability, and in turn impacts the economy. Best practices have been proposed as one of the measures that can be taken to reduce delays and schedule growth. The objective of this study is to investigate which best practices impact schedule growth. As the impact of best practices can vary between project phases, the impact will be determined for each of the five phases of a construction project – front-end planning, detailed engineering, procurement, construction, and commissioning. Data from 747 heavy industrial construction projects from Canada and the United States will be analyzed. Descriptive statistics will be used to summarize schedule characteristics such as phase schedule growth and delay. Inferential statistics (t-test and Pearson’s correlation) will be used to determine which phase a practice impacts and the magnitude of the impact. Identifying practices that can reduce the duration of projects is especially useful for practitioners working on schedule-driven projects. Determining which phase a practice impacts and the magnitude of that impact allows for further selection of practices based on the priority phases of each project.