Beyond Technical Barriers: A Soft Systems-Regression Framework for Scaling Industrial Energy Efficiency Adoption - Herlan Herlan; Eka Sudarmaji; Widyaningsih Azizah (goodwood publishing, 2026)
Purpose: This study examines how stakeholder engagement, financial support, policy frameworks, and technology awareness shape sustainable energy efficiency adoption among Indonesian SMEs and corporations, where only 30% of conservation potential is realized despite existing incentives. Research Methodology: This study used a two-phase hybrid design. Phase one applied SSM with focus group discussions, interviews, and CATWOE analysis to map policy fragmentation. In Phase two, 303 firms in Jakarta, Tangerang, and Bekasi completed structured questionnaires with a 42-item Likert scale, and three-tier regression models examined adoption, viability, and alignment pathways. Results: The SSM identified SEE adoption as a wicked problem due to stakeholder conflicts and institutional misalignment. Three-tier regression showed policy support as the strongest predictor, explaining 60.9% of the adoption variance. Performance impact and market readiness explained 57% of the viability variance, while staff capacity accounted for 52.9% of the alignment variance. Conclusions: Scaling SEE adoption requires institutional coherence, stakeholder alignment, and organizational readiness. Coherent policy frameworks, performance- based financing, and collaborative governance that integrate sociocultural and technical realities are essential for making meaningful progress. Limitations: The study was limited to Greater Jakarta, which limits generalizability, and the cross-sectional design cannot confirm causal direction. SSM was applied only through stage six; future research should extend the framework longitudinally across diverse regions and industries. Contributions: This is the first study to integrate SSM with three-tier regression for energy conservation in Indonesia. It introduces a performance-based blended finance model that links microcredit repayments to verified energy savings tracked in real time via smart meters.