Research on the Influencing Factors, Mechanisms, and Optimization Pathways of Building Energy Management: A Structural Equation Modeling and Case Study Approach

Authors

Minglu Fang

Department of Quantity Surveying, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor (Malaysia)

Mohd Saidin Misnan

Department of Quantity Surveying, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor (Malaysia)

Tantish Kamaruddin

Department of Quantity Surveying, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor (Malaysia)

Chunming Feng

Faculty of Humanities and Management, Sichuan Aerospace Vocational College, Guanghan, Sichuan (China)

Article Information

DOI: 10.47772/IJRISS.2026.100800067

Subject Category: Management

Volume/Issue: 10/8 | Page No: 924-948

Publication Timeline

Submitted: 2026-08-15

Accepted: 2026-08-20

Published: 2026-08-25

Abstract

Building energy management is influenced by technological, managerial, and external environmental factors. Based on ISO 50001 and socio-technical systems theory, this study integrates SWOT-AHP and interview findings to develop an influencing-factor model. Using 208 valid questionnaires, structural equation modeling is applied to examine the relationships among internal strengths, internal weaknesses, external opportunities, external threats, and energy management performance. An industrial factory case is further used to validate the empirical findings and identify an optimization pathway for energy management. The results provide practical implications for improving energy management systems and supporting low-carbon development.

Keywords

Building Energy Management; Influencing Factors; Structural Equation Modeling; Energy Management Performance; Optimization Pathway

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References

1. Andolfi, L., Lima Baima, R., Burcheri, L. M., Pavić, I., & Fridgen, G. (2024). Sociotechnical design of building energy management systems in the public sector: Five design principles. Applied Energy, 377, 124628. https://doi.org/10.1016/j.apenergy.2024.124628. [Google Scholar] [Crossref]

2. Cagno, E., Moschetti, R., Trianni, A., & Pizzocri, M. (2022). How do we learn about drivers for industrial energy efficiency—Current state of knowledge. Energies, 15(7), 2642. https://doi.org/10.3390/en15072642. [Google Scholar] [Crossref]

3. Cagno, E., Trianni, A., Abeelen, C., Worrell, E., & Miggiano, F. (2022). A novel characterization based framework to incorporate industrial energy management services. Applied Energy, 306, 118891. https://doi.org/10.1016/j.apenergy.2022.118891 [Google Scholar] [Crossref]

4. Cavalcanti, G. O., & Pimenta, H. C. D. (2023). Electric energy management in buildings based on the Internet of Things: A systematic review. Energies, 16(15), 5753. https://doi.org/10.3390/en16155753 [Google Scholar] [Crossref]

5. Culot, G., Nassimbeni, G., Orzes, G., & Sartor, M. (2023). Industrial digitalization: A systematic literature review and research agenda. European Management Journal, 41(1), 47–78. https://doi.org/10.1016/j.emj.2022.01.001 [Google Scholar] [Crossref]

6. Fitzgerald, P., Therkelsen, P., Sheaffer, P., & Rao, P. (2023). Deeper and persistent energy savings and carbon dioxide reductions achieved through ISO 50001 in the manufacturing sector. Sustainable Energy Technologies and Assessments, 57, 103280. https://doi.org/10.1016/j.seta.2023.103280. [Google Scholar] [Crossref]

7. Fuchs, H., Aghajanzadeh, A., & Therkelsen, P. (2020). Identification of drivers, benefits, and challenges of ISO 50001 through case study content analysis. Energy Policy, 142, 111443. https://doi.org/10.1016/j.enpol.2020.111443 [Google Scholar] [Crossref]

8. International Organization for Standardization (ISO). (2018). ISO 50001:2018 Energy management systems—Requirements with guidance for use. Geneva: International Organization for Standardization. [Google Scholar] [Crossref]

9. International Organization for Standardization. (2018). ISO 50001:2018 Energy management systems—Requirements with guidance for use. Geneva: International Organization for Standardization. [Google Scholar] [Crossref]

10. International Telecommunication Union (ITU). (2024). Recommendation ITU-T L.1260: Reference model of a factory energy management system. Geneva: International Telecommunication Union. [Google Scholar] [Crossref]

11. Kaya, D., Kılıç, F. Ç., & Öztürk, H. H. (2021). Energy efficiency in compressed air systems. In Energy Management and Energy Efficiency in Industry (pp. 395–418). Cham: Springer. https://doi.org/10.1007/978-3-030-25995-2_13. [Google Scholar] [Crossref]

12. Mischos, S., Dalagdi, E., & Vrakas, D. (2023). Intelligent energy management systems: A review. Artificial Intelligence Review, 56, 11635–11674. https://doi.org/10.1007/s10462-023-10441-3 [Google Scholar] [Crossref]

13. Mischos, S., Dalagdi, E., & Vrakas, D. (2023). Intelligent energy management systems: A review. Artificial Intelligence Review, 56, 11635–11674. https://doi.org/10.1007/s10462-023-10441-3. [Google Scholar] [Crossref]

14. Mustaffa, N. K., & Kudus, S. A. (2022). Challenges and way forward towards best practices of energy efficient building in Malaysia. Energy, 259, 124839. https://doi.org/10.1016/j.energy.2022.124839 [Google Scholar] [Crossref]

15. Pandin, M., Sumaedi, S., Yaman, A., & Ayundyahrini, M. (2024). ISO 50001 based energy management system: A bibliometric perspective. International Journal of Energy Sector Management, 18(6), 1938–1960. https://doi.org/10.1108/IJESM-08-2023-0001. [Google Scholar] [Crossref]

16. Sheaffer, P., et al. (2023). ISO 50001-based energy management systems as a practical path for decarbonization: Initial findings from a survey of technical assistance cohort participants. Energies, 16(14), 5441. https://doi.org/10.3390/en16145441 [Google Scholar] [Crossref]

17. Sievers, J., & Blank, T. (2023). A systematic literature review on data-driven residential and industrial energy management systems. Energies, 16(4), 1688. https://doi.org/10.3390/en16041688 [Google Scholar] [Crossref]

18. Sievers, J., & Blank, T. (2023). A systematic literature review on data-driven residential and industrial energy management systems. Energies, 16(4), 1688. https://doi.org/10.3390/en16041688. [Google Scholar] [Crossref]

19. Smith, K. M., Wilson, S., & Hassall, M. E. (2022). Barriers and drivers for industrial energy management: The frontline perspective. Journal of Cleaner Production, 335, 130320. https://doi.org/10.1016/j.jclepro.2021.130320. [Google Scholar] [Crossref]

20. Smith, K. M., Wilson, S., & Hassall, M. E. (2022). Barriers and drivers for industrial energy management: The frontline perspective. Journal of Cleaner Production, 335, 130320. https://doi.org/10.1016/j.jclepro.2021.130320 [Google Scholar] [Crossref]

21. Thollander, P., Backlund, S., Trianni, A., & Cagno, E. (2021). Overcoming the efficiency gap: Energy management as a means for overcoming barriers to energy efficiency—Empirical support in the case of Austrian large firms. Energy Efficiency, 14. https://doi.org/10.1007/s12053-021-09954-z [Google Scholar] [Crossref]

22. U.S. Department of Energy / Lawrence Berkeley National Laboratory. (2022). Organizational Behavior Insights from 50001 Ready Technical Assistance Cohorts. Lawrence Berkeley National Laboratory. [Google Scholar] [Crossref]

23. Wang, W. B., Wen, Y. S., Xiao, X. D., Guo, G. Q., Wu, Y. J., & Du, Y. (2024). Application and exploration of digital energy management technology in large scale energy equipment manufacturing enterprises. Dongfang Electric Review, 38(6), 80 84. [Google Scholar] [Crossref]

24. Wittmann, M., et al. (2022). Obstacles to demand response: Why industrial companies do not adapt their power consumption to volatile power generation. Energy Policy, 165, 112876. https://doi.org/10.1016/j.enpol.2022.112876 [Google Scholar] [Crossref]

25. Yu, W., Patros, P., Young, B. R., Klinac, E., & Walmsley, T. G. (2022). Energy digital twin technology for industrial energy management: Classification, challenges and future. Renewable and Sustainable Energy Reviews, 161, 112407. https://doi.org/10.1016/j.rser.2022.112407. [Google Scholar] [Crossref]

26. Yue, H., Worrell, E., Crijns-Graus, W., Liu, W., & Zhang, S. (2021). Saving energy in China’s industry with a focus on electricity: A review of opportunities, potentials and environmental benefits. Energy Efficiency, 14, 60. https://doi.org/10.1007/s12053-021-09979-4. [Google Scholar] [Crossref]

27. Zhou, J., Fennell, P., Korolija, I., Fang, Z., Tang, R., & Ruyssevelt, P. (2024). Review of non-domestic building stock modelling studies under socio-technical system framework. Journal of Building Engineering, 97, 110873. https://doi.org/10.1016/j.jobe.2024.110873. [Google Scholar] [Crossref]

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