Nnaji, C; Gambatese, J; Karakhan, A and Eseonu, C (2019) Influential safety technology adoption predictors in construction. Engineering, Construction and Architectural Management, 26(11), pp. 2655-2681. ISSN 0969-9988
Abstract
Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: 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. Originality/value: 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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | mixed method; safety management; success predictors; technology adoption |
| Index terms: | relative importance index, literature review, workplace safety, injury, safety management, decision-making, methodology, practitioner, durability, statistical analysis, variance, integrated conceptual model, mixed method, construction industry, construction worker, technology adoption, emerging technology, effectiveness |
| Subjects: | professional development, performance management, research methods, industry analysis, occupational health, decision analysis, measurement and scaling, health conditions and diseases, occupational health and safety management, practitioner, risk assessment, data collection methods, material degradation and durability, data analysis and analytics, data science, innovation and technology management |
| Topics: | Health and Safety, Research Practice, Engineering Principles, Information Management, Construction Materials, Risk Management, Roles and Professions, Digital Applications, Quality Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here