| description abstract | The so-called digital transformation of the construction industry is essential to overcoming long-standing global productivity stagnation. This transformation aims to adopt the latest technological developments and methodologies to improve construction productivity while supporting data-informed decision-making. However, the construction sector has fallen short of meeting the fast-growing population’s demands for sustainable quality infrastructure at the required pace as it has not yet taken full advantage of these advancements. Despite broad experience in managing projects, when it comes to modeling, monitoring, and re-engineering processes, the construction industry has fallen behind several other industries. To overcome these challenges, efficient construction processes and operational strategies are essential to keeping organizations competitive and meeting market demands. In this regard, even though several studies on process modeling and management in construction exist, research on construction process improvement and automation through data-driven process mining remains understudied. Moreover, the literature lacks a comprehensive review of process-oriented studies with practical industry insights. To fill these gaps, this paper aims to provide an exhaustive analysis of process mining, modeling, and management as reported by the most current state of the literature in the architecture, engineering, construction/facility management (AEC/FM) domain coupled with a current industry perspective. As a result, the authors: (1) propose a conceptual process classification framework that considers the broad spectrum of process-oriented studies in the existing literature; (2) identify construction processes commonly present across a project’s life cycle; (3) design and conduct structured interviews with subject matter experts to validate identified processes and get industry insights about them; (4) spot major literature gaps describing future research opportunities; and (5) develop a business process model canvas template that supports construction organizations in improving their corporate memory and pursuing construction productivity growth by better managing, monitoring, and automating construction processes. | |
