This study investigates the gap between construction workers’ acceptance willingness (AW) and participation behavior (PB) in metaverse safety training (MST), a critical barrier to the effective implementation of digital safety innovations. Although MST offers clear advantages over traditional methods, its success relies on both workers’ willingness and actual engagement. This study quantifies the critical gap between AW and PB and explores key behavioral factors limiting MST adoption in the Chinese construction context.
A large-scale survey was conducted involving 1,329 workers across nine highway construction projects in China. Based on an expanded theory of planned behavior (TPB) model, binary logistic regression was used to examine the AW–PB gap and identify influencing factors.
The analysis reveals a substantial 51.32% discrepancy between AW and PB. Through the expanded TPB model, four distinct influence patterns emerge: (1) Personal characteristics and subjective norms primarily influence AW, with minimal impact on PB; (2) Facilitating conditions powerfully drive PB, while showing limited effect on AW; (3) Attitudinal factors like skill enhancement affect both dimensions, whereas regulatory oversight suppresses AW but promotes PB and (4) Education level, professional status and training perception show no significant influence. These findings highlight differentiated mechanisms underlying the translation from intention to action.
This study introduces the acceptance-participation gap (APG) framework to explain intention-behavior misalignment in MST adoption. By quantifying the AW–PB gap and identifying bridging mechanisms, it offers both theoretical advancement and practical strategies. The findings support a three-phase implementation framework prioritizing technical foundations and balanced rewards, offering guidance for MST adoption in the Chinese construction industry and similar institutional contexts.
