Determinants of Energy Conservation Behaviour among University Staff: An Application of the Theory of Planned behaviour
Authors
Faculty of Business and Communication, Universiti Malaysia Perlis, S2-L1-20, Kampus Unicity Alam, 02100 Padang Besar, Perlis; Faculty of Electrical Engineering & Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis (Malaysia)
Faculty of Business and Communication, Universiti Malaysia Perlis, S2-L1-20, Kampus Unicity Alam, 02100 Padang Besar, Perlis (Malaysia)
Faculty of Electrical Engineering & Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100500592
Subject Category: Sustainability
Volume/Issue: 10/5 | Page No: 8794-8798
Publication Timeline
Submitted: 2026-05-12
Accepted: 2026-05-18
Published: 2026-06-08
Abstract
Energy consumption in university environments has become a concern due to increasing operational demands and the environmental impacts associated with excessive energy consumption. Promoting energy conservation behaviour within universities is essential for improving energy conservation in line with SDG 7 and SDG 13. Guided by the Theory of Planned Behaviour (TPB), data were collected from a sample of 251 academic staff. The results indicate attitude (ATT) is not significant, while subjective norms (SN) and perceived behaviour control (PBC) show a significant effect on intention energy conservation. The findings indicate that intention toward energy conservation is significantly affected by SN and PBC, highlighting the importance of normative norms and institutional support in promoting sustainable intention energy conservation in the university. The study contributes to a better understanding of the psychological and behavioural determinants of energy conservation among academic staff, thereby supporting the formulation of targeted behavioural intervention programmes, institutional policies, and awareness initiatives.
Keywords
Energy conservation behaviour, sustainable development goal
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References
1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. [Google Scholar] [Crossref]
2. Chaer, I., Ozarisoy, B., Ismail, M. A. E., Salari, S., & Zhihui, Y. (2025). Energy efficiency in educational buildings: A systematic review of smart technology integration and occupant behaviour. Building and Environment, 280, 113132. [Google Scholar] [Crossref]
3. Cibinskiene, A., Dumciuviene, D., & Andrijauskiene, M. (2020). Energy Consumption in Public Buildings: The Determinants of Occupants’ Behavior. Energies, 13(14), 3586–3586. [Google Scholar] [Crossref]
4. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. [Google Scholar] [Crossref]
5. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd Edition ed.). Sage. [Google Scholar] [Crossref]
6. Hnin, S. W., Javed, A., Karnjana, J., Jeenanunta, C., & Kohda, Y. (2025). Workplace sustainability: energy-saving behaviors in office environments of Thailand. Frontiers in Psychology, 16, 1400410. [Google Scholar] [Crossref]
7. Katun, M. M., & Popoola, O. M. (2025). Occupant behavior and energy efficiency in higher education buildings: A systematic review. International Journal of Development and Sustainability. [Google Scholar] [Crossref]
8. Nations, U. (2025). Global Status Report for Buildings and Construction 2024/2025. U. N. E. Programme. [Google Scholar] [Crossref]
9. Puiu, S., Yilmaz, S. E., Udriștioiu, M. T., Raganova, J., Raykova, Z., Yildizhan, H., & Ameen, A. (2025). The expanded theory of planned behavior for energy saving among academics in Romania, Bulgaria, Turkey, and Slovakia. Scientific Reports, 15(1), 2772. [Google Scholar] [Crossref]
10. Rawat, A., Kumar, D., & Khati, B. S. (2024). A review on climate change impacts, models, and its consequences on different sectors: a systematic approach. Journal of Water and Climate Change, 15(1), 104–126. https://doi.org/10.2166/wcc.2023.536 [Google Scholar] [Crossref]
11. Shafaay, M., Alqahtani, F. K., Alsharef, A., & Chen, G. (2025). Modeling construction cost overrun risks at the FEED stage for mining projects using PLS-SEM. Journal of Asian Architecture and Building Engineering, 1–17. [Google Scholar] [Crossref]
12. Yan, D., Hong, T., Dong, B., Mahdavi, A., D’Oca, S., Gaetani, I., & Feng, X. (2017). IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings. Energy and Buildings, 156, 258–270. [Google Scholar] [Crossref]
13. Zhang, S., Su, H., Wu, M., & Yang, B. (2025). An empirical study on energy usage and occupant comfort of occupant-centric control systems in offices. Building and Environment, 278, 112954. [Google Scholar] [Crossref]
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