| Title |
Barriers to the Adoption of Computer Vision-based Object Recognition in Construction Sites |
| Authors |
Kyu-Hoi Kim ; Tae-Jin Kim ; Yo-Han Park ; Seong-Hwan Yoon ; Jung-Ho Jeon ; Jin-Woo Kim |
| DOI |
https://dx.doi.org/10.6106/KJCEM.2025.26.3.087 |
| Keywords |
Computer Vision; Object Recognition; Technology Acceptance Model; Construction Safety |
| Abstract |
This study investigates the factors hindering the adoption of computer vision object recognition technology in construction sites, focusing on user perception and technology acceptance. Using the Technology Acceptance Model (TAM) alongside factors such as price efficiency, social influence, and associated experience, the research reveals key reason. Price efficiency significantly enhances both perceived ease of use (PEOU) and PU, suggesting economic benefits make the technology more accessible and beneficial. Conversely, social influence negatively impacts PEOU, indicating that higher social pressure may make the technology seem more challenging to use. Associated experience positively affects PU, implying that prior experience makes the technology more valuable to users. Both PEOU and PU positively influence the intention to use the technology, with PEOU having a particularly strong effect. Emphasizing economic efficiency and ease of use is crucial for technology adoption, while addressing social influence through education and awareness can mitigate its negative impact. Survey results highlight the importance of cost support, showing users are sensitive to financial aspects. These findings offer valuable insights for promoting advanced safety technologies in the construction industry. |