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The US construction industry has been relatively slow to employ digital information technologies. The lack of adoption by project owners is a result of them not having a solid understanding of probable factors (PFs) that could influence the implementation of such systems and potential benefits (PBs) that can serve as key motivators and an assessment instrument. Thus, this article aims to study PBs of digital construction-phase information management (DCIM) systems for project owners and PFs that could influence the implementation of such systems by project owners.

Qualitative data collection and analysis methods were followed to conduct the research. The qualitative data (information) regarding PBs and PFs were collected using a survey to subject matter experts and the content analysis method was used to analyze the data.

Findings show that almost all the qualitative data regarding PBs of DCIM systems are positive, and these data support 10 of 18 PBs with which they were compared. The qualitative data that is negative does not support one PB. Findings also show that all the qualitative data regarding the PFs are confirmatory, and these data support 14 of 28 PFs with which they were compared. The most supported PB is improvement in the efficiency of documentation within the organization and the most supported PF is upper management support.

The primary contribution of this research is in increasing project owners’ understanding of PBs of DCIM systems and PFs that could influence the implementation of such systems.

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.