A Context Taxonomy for Construction Field Crew Members

The construction industry has encountered persistent stagnation in labor productivity spanning several decades. Although lean construction principles underscore the significance of information availability and transparency, advocating for bilateral communication with onsite personnel, it has come to light that the existing information levels fall short of satisfying the information requirements of field crew members. Timely and comprehensive information regarding context and context changes is crucial for construction field crew members when executing their tasks. Insufficiencies in this aspect could lead to increased variability and prolonged task cycle times for field crew members engaged in similar construction tasks. However, at present, there exists a dearth of a systematic understanding of context, rendering it challenging to promptly disseminate context-related information and its variations to field crew members. This research endeavor strives to bridge this knowledge gap by formulating a comprehensive construction context taxonomy encompassing 17 distinct context dimensions. This research contributes to the domain by (1) reviewing and amalgamating existing literature on context to delineate the potential structuring of context information, (2) developing a comprehensive context taxonomy comprising 17 diverse context dimensions, and (3) validating the taxonomy through semistructured interviews with industry experts and real-world field studies. The context taxonomy herein furnishes a structured representation of context specifically tailored to the requirements of construction field crew members. Consequently, it engenders a shared understanding of context and holds promise for catalyzing relevant research initiatives within the construction industry. For practical implementation, the context taxonomy may serve as a valuable tool for recognizing and conveying context and its fluctuations to construction field crew members, thereby enhancing their work processes and productivity.