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The purpose of this paper is to present findings from a study of factors that affect continuous improvement (CI) project success in hospitals.

Quantitative regression analysis was performed on Likert scale survey responses. Qualitative thematic analysis was performed on open-ended survey responses and written reports on CI projects.

The paper identifies managerial and employee factors that affect project success. These factors include managerial support, communication, and affective commitment. Affective commitment is the extent to which employees perceive the change as being needed or necessary.

The results highlight how managerial decisions, approaches to communication – including communication before, during and after CI projects affect project success. The results also show that success depends on the way employees perceive proposed changes. This suggests the need for a more individualized approach to CI, lean, and broader change initiatives.

This research is the first to fuse project success and sustainability theory to CI projects, beyond Kaizen events, in healthcare environments. The research is particularly important at a time when healthcare organizations are required to make rapid changes with limited resources as they work toward outcome-based assessment and reimbursement rules.

Existing literature suggests that construction worker safety could be optimized using emerging technologies. However, the application of safety technologies in the construction industry is limited. One reason for the constrained adoption of safety technologies is the lack of empirical information for mitigating the risk of a failed adoption. The purpose of this paper is to fill the research gap through identifying key factors that predict successful adoption of safety technologies.

In total, 26 key technology adoption predictors were identified and classified using a combination of literature review and an expert panel. The level of influence for each identified safety technology adoption predictor was assessed and ranked using the Relative Importance Index. Analysis of variance was performed as well to assess the potential difference in perceived level of importance for the predictors when the study participants were clustered according to work experience and company size.

Statistical analysis indicates that 12 out of the 26 predictors identified are highly influential regarding technology adoption decision-making in construction. Technology reliability, effectiveness and durability were ranked as the most influential predictors. The participants who work for small companies and who had less than ten years of experience rated individual- and technology-related predictors significantly lower than the experienced participants working for medium and large companies.

The present study provides construction researchers and practitioners with valuable information regarding safety technology predictors and their magnitude, both of which are essential elements of a successful safety technology adoption process. Improved technology adoption can enhance workplace safety and minimize worker injuries, providing substantial benefits to the construction industry.

This study contributes to technology adoption knowledge by identifying and quantifying the influential predictors of safety technologies in relation to different organizational contexts. The study informs the need to develop an integrated conceptual model for safety technology adoption.