A Comprehensive Evaluation of Factors Influencing Acceptance of Robotic Assistants in Field Construction Work

Abstract

The adoption of human–robot collaboration (HRC) in various forms is widely expected to help improve productivity, reduce human physical workload, and alleviate the issues created by a skilled labor shortage in the construction industry. One potential deterrent to adoption of such collaborative work methods often cited by industry stakeholders is resistance by workers stemming from their fear of losing their jobs or having to learn new approaches and methods of performing construction work. Although significant prior studies have used path analyses to statistically evaluate hypotheses about technology adoption models by estimating the relationships in the models, no research has specifically investigated the intention to work in HRC through such an approach. This study addresses this knowledge gap and empirically investigates the factors affecting construction personnel’s behavioral intention to accept HRC. HRC in this study is envisioned as robotic assistants performing the physically demanding repetitive work while construction personnel focus on cognitive tasks necessary to plan and supervise the work. An HRC adoption model based on the technology acceptance model (TAM) and innovation diffusion theory (IDT) is presented. This study expands a TAM-IDT model with new constructs such as job satisfaction and openness to training to explore an improved model that increases the understanding of construction personnel’s intention to adopt HRC. Data collected from 156 construction personnel were analyzed to identify the key components based on exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The proposed model, consisting of eight external and four internal variables, was examined using structural equation modeling (SEM). Results indicated that variables such as perceived usefulness (PU) and perceived ease of use (PEU) had a positive and significant impact on behavioral intention (BI) to work in the described HRC system. Both theoretical and management implications emerging from the study are offered as insights to assist the construction industry in managing the introduction and adoption of HRC for on-site construction.