An Integrated Framework for Modeling Construction Competencies and Performance Using Artificial Intelligence and Fuzzy Simulation

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Construction is one of Canada's largest industries, and it is a mainstay of the country's economy. Construction organizations function in a constantly changing environment, characterized by complex, interconnected events and processes involving a wide range of participants and interactions. The competenciesdefined as the skills, knowledge, technologies, resources, and practices of an organizationthat enable it to execute its work and fulfil its functions can be assessed and used to distinguish superior from average performance. Modeling construction competencies and their effects on performance is essential for forecasting performance, identifying those competencies that require improvement, and developing performance enhancement strategies. One of the most significant challenges associated with modeling competencies is that they are assessed using multiple criteria and consist of both objective and subjective measures, the latter of which are best evaluated using linguistic terms. Linguistic terms can be effectively modeled using fuzzy logic, a component of artificial intelligence; artificial intelligence has been identified as a priority in the Canadian government's innovation strategy. Fuzzy logic is a technique for modeling human reasoning and for computing with linguistic terms. It enables researchers to draw definite conclusions in the absence of precise numerical data and to represent uncertainty due to subjectivity. The overall goal of this research program is to develop a first-of-its-kind multilevel modeling framework to enable researchers and practitioners to model construction competencies and their interrelationships at multiple levels of assessment (individual, activity, project, and organizational) and relate them to performance at each level. This framework will be used to improve the performance of construction organizations. A secondary goal is to develop new fuzzy hybrid techniques to model aspects of construction that are dynamic and contain both random and subjective uncertainty. These hybrid methods will be based on the integration of artificial intelligence techniques (fuzzy logic and machine learning) with simulation techniques (agent-based modeling and system dynamics). By providing organizations with knowledge on competencies at multiple levels, the outcomes of this research will bring about transformational changes in construction organizational practices, leadership, and culture. The framework will provide a technological advantage to construction organizations by enabling them to identify and improve the competencies that have the most significant impact on performance. Thus this research will contribute to the overall level of innovation, profitability, and competitiveness of the Canadian construction industry, both nationally and internationally, making a significant contribution to the Canadian economy.