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Occupants’ Decision-Making of Their Energy Behaviours in Office Environments: A Case of New Zealand

Author

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  • Achini Shanika Weerasinghe

    (School of Built Environment, Massey University, Auckland 0745, New Zealand)

  • Eziaku Onyeizu Rasheed

    (School of Built Environment, Massey University, Auckland 0745, New Zealand)

  • James Olabode Bamidele Rotimi

    (School of Built Environment, Massey University, Auckland 0745, New Zealand)

Abstract

Understanding how occupants behave and interact with building systems is vital to energy efficiency in buildings. The building occupants’ behaviours are complex and influenced by diverse factors. A deep understanding of the underlying environmental, contextual, social, and psychological factors is the first step of many in establishing the relationship between the indoor environment and occupants’ behaviours. The current study investigates the influence of occupants’ perceived indoor environmental comfort, the availability of control, and the social-psychological impacts on occupant behaviours in a New Zealand context. The data were collected through online surveys, and 99 office occupants responded. A machine learning technique was applied to identify the critical factors influencing the decision-making of occupant behaviours. Of the occupant behaviours considered in the study, adjusting windows, doors, shades and blinds, and drinking beverages were mostly practised (>70%) while adjusting lighting, personal fans, thermostats/heaters, and computers (40–70%) was moderately practised by occupants. The availability of specific user controls was the main predictor of most occupant behaviours, followed by social-psychological factors such as actual knowledge, perceived knowledge, behavioural interventions, subjective norms, organisational support, personal norms, attitudes, and perceived behavioural control. The indoor environmental parameters such as indoor temperature, indoor air quality, natural light, and inside noise were highlighted as most influential in decision-making for occupant behaviours. Additionally, the demographic factors: gender, work duration, days at work, and permanence/temporariness of workspace, were also impactful. Knowing the complexity of occupants’ decision-making with respect to their behaviours helps building managers use this sensitive information to enhance building energy performance and enable more energy feedback to the occupants to raise their awareness. Such information is helpful for creating an intelligent environmental control system loop with eco-feedback and establishing occupant-centric buildings or features.

Suggested Citation

  • Achini Shanika Weerasinghe & Eziaku Onyeizu Rasheed & James Olabode Bamidele Rotimi, 2023. "Occupants’ Decision-Making of Their Energy Behaviours in Office Environments: A Case of New Zealand," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2305-:d:1047814
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    References listed on IDEAS

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    1. Xie, Chengyang & Ding, Hongxing & Zhang, Huan & Yuan, Jingfeng & Su, Shu & Tang, Meiling, 2021. "Exploring the psychological mechanism underlying the relationship between organizational interventions and employees’ energy-saving behaviors," Energy Policy, Elsevier, vol. 156(C).
    2. Jia, Mengda & Srinivasan, Ravi S. & Raheem, Adeeba A., 2017. "From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 525-540.
    3. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    4. Zhang, Yixiang & Wang, Zhaohua & Zhou, Guanghui, 2013. "Antecedents of employee electricity saving behavior in organizations: An empirical study based on norm activation model," Energy Policy, Elsevier, vol. 62(C), pages 1120-1127.
    5. Yao, Jian, 2014. "Determining the energy performance of manually controlled solar shades: A stochastic model based co-simulation analysis," Applied Energy, Elsevier, vol. 127(C), pages 64-80.
    6. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
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