Energy Efficiency Behavior in Mechanical Engineering Operations: The Roles of Machine Performance Literacy, Operational Discipline, and Maintenance Culture - Aris Tri Ika Rakhmadi; Pompy Pratisna; Ayip Rivai Prabowo (Information Technology Education Journal, 2026)
Purpose –Improving energy efficiency in industrial operations requires not only technological advancement but also supportive employee behavior. This study investigates how machine performance literacy contributes to energy efficiency behavior, both directly and through operational discipline, while examining whether maintenance culture strengthens this relationship in mechanical engineering operations. Design/methods/approach – A quantitative survey was conducted with 200 respondents, including machine operators, maintenance technicians, engineers, and production supervisors from several industrial sectors. The proposed research model was analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to evaluate direct, indirect, and moderating effects among the study variables. Findings – The results indicate that machine performance literacy significantly enhances operational discipline and energy efficiency behavior. Operational discipline was also found to positively influence energy efficiency behavior and partially mediate the effect of machine performance literacy. In contrast, maintenance culture did not significantly strengthen the relationship between operational discipline and energy efficiency behavior. The structural model accounted for 55.4% of the variance in energy efficiency behavior, demonstrating satisfactory explanatory power. Research implications/limitations – Because the study employed a cross-sectional design, the findings should be interpreted with caution regarding causal relationships and may not fully represent all industrial settings. Originality/value – This study offers a behavioral perspective on industrial energy efficiency by integrating machine performance literacy and operational discipline within a single analytical framework. The findings broaden existing knowledge by highlighting human-related factors that complement technology-based approaches to energy efficiency improvement.