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Determinant Factors of Electricity Consumption for a Malaysian Household Based on a Field Survey

Author

Listed:
  • Boni Sena

    (Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, Malaysia)

  • Sheikh Ahmad Zaki

    (Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, Malaysia)

  • Hom Bahadur Rijal

    (Faculty of Environmental Studies, Tokyo City University, Yokohama 224-8551, Japan)

  • Jorge Alfredo Ardila-Rey

    (Department of Electrical Engineering, Universidad Técnica Federico Santa María, Santiago de Chile 8940000, Chile)

  • Nelidya Md Yusoff

    (Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Kuala Lumpur 54100, Malaysia)

  • Fitri Yakub

    (Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, Malaysia)

  • Mohammad Kholid Ridwan

    (Faculty of Engineering, Gadjah Mada University, Yogyakarta 55281, Indonesia)

  • Firdaus Muhammad-Sukki

    (School of Engineering & the Built Environment, Edinburgh Napier University, Merchiston Campus, 10 Colinton Road, Edinburgh EH10 5DT, UK)

Abstract

Electricity-saving strategies are an essential solution to overcoming increasing global CO 2 emission and electricity consumption problems; therefore, the determinant factors of electricity consumption in households need to be assessed. Most previous studies were conducted in developed countries of subtropical regions that had different household characteristic factors from those in developing countries of tropical regions. A field survey was conducted on electricity consumption for Malaysian households to investigate the factors affecting electricity consumption that focused on technology perspective (building and appliance characteristics) and socio-economic perspective (socio-demographics and occupant behaviour). To analyse the determinant factors of electricity consumption, direct and indirect questionnaire surveys were conducted from November 2017 to January 2018 among 214 university students. Direct questionnaire surveys were performed in order to obtain general information that is easily answered by respondents. On the other hand, some questions such as electricity consumption and detailed information of appliances must be confirmed by the respondents’ parents or other household members through an indirect questionnaire survey. The results from multiple linear regression analyses of the survey responses showed that appliance characteristic factors were the main variables influencing electricity consumption and house characteristics were the least significant. Specifically, air conditioners, fluorescent lamps, and flat-screen TVs emerged as appliances with the most significant effect on electricity consumption. Occupant behaviour factors had a more significant influence than socio-demographic factors. The findings in this study can be used by policymakers to develop electricity-saving strategies in Malaysia.

Suggested Citation

  • Boni Sena & Sheikh Ahmad Zaki & Hom Bahadur Rijal & Jorge Alfredo Ardila-Rey & Nelidya Md Yusoff & Fitri Yakub & Mohammad Kholid Ridwan & Firdaus Muhammad-Sukki, 2021. "Determinant Factors of Electricity Consumption for a Malaysian Household Based on a Field Survey," Sustainability, MDPI, vol. 13(2), pages 1-31, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:818-:d:481031
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    References listed on IDEAS

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    1. Kavousian, Amir & Rajagopal, Ram & Fischer, Martin, 2013. "Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior," Energy, Elsevier, vol. 55(C), pages 184-194.
    2. Hara, Keishiro & Uwasu, Michinori & Kishita, Yusuke & Takeda, Hiroyuki, 2015. "Determinant factors of residential consumption and perception of energy conservation: Time-series analysis by large-scale questionnaire in Suita, Japan," Energy Policy, Elsevier, vol. 87(C), pages 240-249.
    3. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    4. Tso, Geoffrey K.F & Yau, Kelvin K.W, 2003. "A study of domestic energy usage patterns in Hong Kong," Energy, Elsevier, vol. 28(15), pages 1671-1682.
    5. Huebner, Gesche M. & Hamilton, Ian & Chalabi, Zaid & Shipworth, David & Oreszczyn, Tadj, 2015. "Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes," Applied Energy, Elsevier, vol. 159(C), pages 589-600.
    6. Jones, Rory V. & Fuertes, Alba & Lomas, Kevin J., 2015. "The socio-economic, dwelling and appliance related factors affecting electricity consumption in domestic buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 901-917.
    7. Huebner, Gesche & Shipworth, David & Hamilton, Ian & Chalabi, Zaid & Oreszczyn, Tadj, 2016. "Understanding electricity consumption: A comparative contribution of building factors, socio-demographics, appliances, behaviours and attitudes," Applied Energy, Elsevier, vol. 177(C), pages 692-702.
    8. Pal, Monalisa & Alyafi, Amr Alzouhri & Ploix, Stéphane & Reignier, Patrick & Bandyopadhyay, Sanghamitra, 2019. "Unmasking the causal relationships latent in the interplay between occupant’s actions and indoor ambience: A building energy management outlook," Applied Energy, Elsevier, vol. 238(C), pages 1452-1470.
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    Cited by:

    1. Nsangou, Jean Calvin & Kenfack, Joseph & Nzotcha, Urbain & Ngohe Ekam, Paul Salomon & Voufo, Joseph & Tamo, Thomas T., 2022. "Explaining household electricity consumption using quantile regression, decision tree and artificial neural network," Energy, Elsevier, vol. 250(C).
    2. Boni Sena & Sheikh Ahmad Zaki & Hom Bahadur Rijal & Jorge Alfredo Ardila-Rey & Nelidya Md Yusoff & Fitri Yakub & Farah Liana & Mohamad Zaki Hassan, 2021. "Development of an Electrical Energy Consumption Model for Malaysian Households, Based on Techno-Socioeconomic Determinant Factors," Sustainability, MDPI, vol. 13(23), pages 1-22, November.
    3. Chee Keong Khoo & Xin Li & Jianxiang Huang, 2022. "Green Behaviors and Green Buildings: A Post-Occupancy Evaluation of Public Housing Estates in Hong Kong," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    4. Mithila Seva Bala Sundaram & ChiaKwang Tan & Jeyraj Selvaraj & Ab. Halim Abu Bakar, 2023. "Energy Savings for Various Residential Appliances and Distribution Networks in a Malaysian Scenario," Energies, MDPI, vol. 16(13), pages 1-18, June.
    5. Fikru, Mahelet G. & Kisswani, Khalid M., 2023. "Environmental impacts of household energy use in ASEAN-5 countries: Are there asymmetric effects?," Energy Policy, Elsevier, vol. 182(C).

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