TY  - CONF
TI  - Behavioral Safety Performance Assessment in Construction: a Data-driven Approach in Virtual Reality
C1  - Osaka and Kyoto, Japan
C3  - Proceedings of the 33rd Annual Conference of the International Group for Lean Construction (IGLC 33)
SP  - 1114
EP  - 1125
PY  - 2025
DO  - 10.24928/2025/0169
AU  - Speiser, Kilian
AU  - Golovina, Olga
AU  - Teizer, Jochen
AD  - Ph.D. Candidate, Department for Civil and Mechanical Engineering, Technical University of Denmark (DTU), Kongens Lyngby, Denmark, kilsp@dtu.dk, https://orcid.org/0000-0001-8428-8053
AD  - Ph.D., Consultant, Kongens Lyngby, Denmark, kj7_i@web.de, https://orcid.org/0009-0009-5021-3139
AD  - Professor, Department for Civil and Mechanical Engineering, Technical University of Denmark (DTU), Kongens Lyngby, Denmark, teizerj@dtu.dk, https://orcid.org/0000-0001-8071-895X
ED  - Seppänen, Olli 
ED  - Koskela, Lauri 
ED  - Murata , Koichi 
AB  - The construction industry suffers from high incidence rates compared to other sectors. Lean and safety training is one effort to increase work productivity while preventing accidents, but the effectiveness of various existing training methods relies on intention-based evaluations. These can fail to capture behavioral lean and safety performance. This paper presents a novel Virtual Reality (VR)-based assessment method for quantifying (lean and) safety performance in construction, addressing the critical gap between intention and behavior. By simulating real-world hazards, a simplified VR learning environment allows for objective, data-driven assessment of workers’ behavior using metrics that capture, for example, the interaction with poor construction site layout and hazards. This study created a virtual environment and tested the capabilities of objectively assessing aspects of lean and safety performance in an experiment with 60 subjects. Splitting them into groups of experts and novices and exposing them to different training methods allowed a qualitative discussion on the implications of such an assessment method. The results demonstrate its applicability for a data-driven metric to assess lean and safety behavior, given that the environment includes relevant hazards and represents lifelike tasks. Construct validity requires further considerations when using this concept for virtual performance assessment. A more nuanced metric could further strengthen the study design. This study provides an explorative framework for further research to investigate the effectiveness of training methods based on behavior and overcoming the intention-behavior gap.
KW  - Active learning
KW  - behavioral assessment
KW  - education and training
KW  - lean and safe construction
KW  - safety performance
KW  - virtual reality
KW  - lean and safety indicators.
PB  - 
T2  - Proceedings of the 33rd Annual Conference of the International Group for Lean Construction (IGLC 33)
DA  - 2025/06/02
CY  - Osaka and Kyoto, Japan
L1  - http://iglc.net/Papers/Details/2352/pdf
L2  - http://iglc.net/Papers/Details/2352
N1  - Export Date: 02 June 2025
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -