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Influencing turnover intention among building information modeling (BIM) Workers in China

A structural equation modeling approach

Bibliographic Data

ID9406719
AuthorsWei Wei (0000-0003-1852-2811, Mapúa University), Yogi Tri Prasetyo (0000-0003-3535-9657, Yuan Ze University, corresponding author), Omar Paolo Benito (Yuan Ze University), Maela Madel L Cahigas (0000-0002-6368-3393, Mapúa University), Reny Nadlifatin (0000-0003-1265-8515, Sepuluh Nopember Institute of Technology), Ma Janice J Gumasing (0000-0003-0627-5040, De La Salle University)
Year2025
Volume257
Pages105121-105121
Publication date2025-06-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueActa Psychologica (JOURNAL)
Journal identifiersISSN: 0001-6918 • E-ISSN: 1873-6297
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.actpsy.2025.105121
PMID40479852
OpenAlexW4411054378
LanguageEN
References cited123

Building Information Modeling (BIM) has become integral to modern construction management in China, yet its successful implementation has been hindered by a shortage of skilled BIM personnel and high turnover rates. This study investigates the key factors influencing turnover intention among BIM workers in China through a structural equation modeling (SEM) approach. Survey data were collected from 558 BIM practitioners and researchers across various regions in China. The SEM results revealed that three work-related factors-management and staff cooperation, working hours, and satisfaction with salary and incentives-significantly affected BIM workers' turnover intentions. Notably, the influence of these factors on turnover intention was fully mediated by two pivotal attitudinal variables: job satisfaction and organizational commitment. Among the predictors, excessive working hours emerged as the most salient driver heightening turnover intention, whereas strong team cooperation and competitive, fair rewards reduce the propensity to leave by enhancing worker satisfaction and commitment. The integrated model developed in this research advances understanding of BIM workforce retention and can be generalized to similar project-based contexts. The findings provide an evidence-based foundation for policymakers and industry leaders to devise strategies (e.g., improving working conditions, strengthening organizational support) aimed at increasing job satisfaction and commitment, thereby mitigating turnover intention among BIM workers

Building Information Modeling · Business · China · Job satisfaction · Knowledge management · Operations management · Political science · Structural equation modeling · Turnover intention · Computer Science · Construction Project Management and Performance · Engineering · Occupational Health and Safety Research · Psychology · Social Psychology · Urban Transport Systems Analysis

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