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

建筑业是加拿大最大的产业之一，也是该国经济的支柱。建筑组织在一个不断变化的环境中运作，其特点是复杂的、相互关联的事件和过程，涉及广泛的参与者和互动。能力被定义为组织的技能、知识、技术、资源和实践，使其能够执行其工作并履行其职能，这些能力可以被评估并用于区分卓越和一般绩效。建模构建能力及其对性能的影响对于预测性能、识别那些需要改进的能力以及开发性能增强策略是必不可少的。与建模能力相关的最重要的挑战之一是，它们使用多个标准进行评估，并由客观和主观度量组成，后者最好使用语言术语进行评估。语言术语可以使用模糊逻辑有效地建模，这是人工智能的一个组成部分；人工智能已被确定为加拿大政府创新战略的优先事项。模糊逻辑是一种模拟人类推理和用语言术语进行计算的技术。它使研究人员能够在没有精确的数值数据的情况下得出明确的结论，并表示由于主观性而产生的不确定性。该研究计划的总体目标是开发一个首创的多层次建模框架，使研究人员和实践者能够在多个评估层面（个人、活动、项目和组织）对建筑能力及其相互关系进行建模，并将它们与每个层面的绩效联系起来。该框架将用于提高施工组织的绩效。第二个目标是开发新的模糊混合技术来模拟动态的、包含随机和主观不确定性的建筑方面。这些混合方法将基于人工智能技术（模糊逻辑和机器学习）与仿真技术（基于代理的建模和系统动力学）的集成。通过为组织提供多层次的能力知识，本研究的结果将带来组织实践、领导和文化建设方面的转型变化。该框架将为建筑组织提供技术优势，使他们能够识别和改进对性能有最重要影响的能力。因此，这项研究将有助于整体水平的创新，盈利能力，以及加拿大建筑业的竞争力，在国内和国际上，对加拿大经济做出重大贡献。

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.