Research Summary: Beyond Demographics: BIM Engagement and Job Satisfaction Among AEC Professionals, A Machine Learning Pilot Study

A pilot study utilizing machine learning techniques to analyze survey responses from 104 Architecture, Engineering, and Construction (AEC) professionals indicates that Building Information Modeling (BIM) engagement is a more significant predictor of job satisfaction than demographic characteristics. This finding challenges previous assumptions and suggests a stronger linkage between technological engagement and employee satisfaction within this sector.

Why it matters

Understanding the drivers of job satisfaction is crucial for talent retention and productivity within technologically evolving sectors. This study highlights the strategic importance of employee engagement with core technological tools, rather than solely focusing on demographic profiles, for optimizing workforce satisfaction and operational effectiveness.

Key insights

• BIM engagement is a stronger predictor of job satisfaction among AEC professionals compared to demographic factors.
• The study analyzed survey responses from 104 participants using Spearman rank correlations, logistic regression, and Classification and Regression Tree (CART) modeling.
• A 27-item Job Satisfaction Index demonstrated excellent internal reliability in the study.
• The research specifically focused on the relationship between BIM engagement, demographic characteristics, and job satisfaction in the AEC industry.
• The study was conducted as a pilot, suggesting initial findings that warrant further investigation.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.05181