IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v333y2023ics0306261923000259.html
   My bibliography  Save this article

Influence of advertisement control to residential energy savings in large networks

Author

Listed:
  • Du, Feng
  • Yue, Hong
  • Zhang, Jiangfeng

Abstract

User awareness and behaviour have a strong impact on energy savings especially through large-scale mass rollout programmes for new energy products. Such energy programmes are mostly funded by government with specific energy saving targets. In this work, we aim to investigate the influence of advertisement control to residential energy savings in large population networks. A mathematical model is established to predict the expected energy savings (EES) in a network where advertisement is used to influence user adoption rate of energy efficient product. The proposed dynamic network model consists of information diffusion, EES calculation, and advertisement control. It can be applied to mass rollout programmes to forecast the EES and the adoption rate of new energy products, based on which the advertising investment required to accelerate energy savings can be determined by optimisation design. The proposed approach is tested first with a small population network involving 40 participants, then applied to a large population network with one million internet users. Case studies for different scenarios consider various optimisation targets including adoption rate, time cost, advertisement cost, and total energy savings subject to programme budget and time constraints. The optimisation results show that 32.21 % and 18.15 % of EES are achieved for the small- and large-scale networks, respectively, suggesting the potential benefits of taking advertisement as a means to promote energy efficient product through social networks.

Suggested Citation

  • Du, Feng & Yue, Hong & Zhang, Jiangfeng, 2023. "Influence of advertisement control to residential energy savings in large networks," Applied Energy, Elsevier, vol. 333(C).
  • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261923000259
    DOI: 10.1016/j.apenergy.2023.120661
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923000259
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.120661?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Al-Shemmeri, Tarik & Naylor, Lucy, 2017. "Energy saving in UK FE colleges: The relative importance of the socio-economic groups and environmental attitudes of employees," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1130-1143.
    2. Belaïd, Fateh & Garcia, Thomas, 2016. "Understanding the spectrum of residential energy-saving behaviours: French evidence using disaggregated data," Energy Economics, Elsevier, vol. 57(C), pages 204-214.
    3. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    4. Cheng, Xiu & Long, Ruyin & Chen, Hong & Yang, Jiahui, 2019. "Does social interaction have an impact on residents’ sustainable lifestyle decisions? A multi-agent stimulation based on regret and game theory," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    5. Jiang, Peng & Fan, Yee Van & Klemeš, Jiří Jaromír, 2021. "Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities," Applied Energy, Elsevier, vol. 285(C).
    6. Wang, Richard & Ye, Zhongnan & Lu, Miaojia & Hsu, Shu-Chien, 2022. "Understanding post-pandemic work-from-home behaviours and community level energy reduction via agent-based modelling," Applied Energy, Elsevier, vol. 322(C).
    7. Neves, Catarina & Oliveira, Tiago, 2021. "Drivers of consumers’ change to an energy-efficient heating appliance (EEHA) in households: Evidence from five European countries," Applied Energy, Elsevier, vol. 298(C).
    8. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    9. Mitra, Debrudra & Chu, Yiyi & Cetin, Kristen, 2022. "COVID-19 impacts on residential occupancy schedules and activities in U.S. Homes in 2020 using ATUS," Applied Energy, Elsevier, vol. 324(C).
    10. Wan, Bingyue & Tian, Lixin & Zhu, Naiping & Gu, Liqin & Zhang, Guangyong, 2018. "A new endogenous growth model for green low-carbon behavior and its comprehensive effects," Applied Energy, Elsevier, vol. 230(C), pages 1332-1346.
    11. Carl Shapiro, 1983. "Premiums for High Quality Products as Returns to Reputations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(4), pages 659-679.
    12. Amasyali, Kadir & El-Gohary, Nora M., 2021. "Real data-driven occupant-behavior optimization for reduced energy consumption and improved comfort," Applied Energy, Elsevier, vol. 302(C).
    13. Stankovic, L. & Stankovic, V. & Liao, J. & Wilson, C., 2016. "Measuring the energy intensity of domestic activities from smart meter data," Applied Energy, Elsevier, vol. 183(C), pages 1565-1580.
    14. Murray, D.M. & Liao, J. & Stankovic, L. & Stankovic, V., 2016. "Understanding usage patterns of electric kettle and energy saving potential," Applied Energy, Elsevier, vol. 171(C), pages 231-242.
    15. Zhou, Xin & Tian, Shuai & An, Jingjing & Yan, Da & Zhang, Lun & Yang, Junyan, 2022. "Modeling occupant behavior’s influence on the energy efficiency of solar domestic hot water systems," Applied Energy, Elsevier, vol. 309(C).
    16. Du, Feng & Zhang, Jiangfeng & Li, Hailong & Yan, Jinyue & Galloway, Stuart & Lo, Kwok L., 2016. "Modelling the impact of social network on energy savings," Applied Energy, Elsevier, vol. 178(C), pages 56-65.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fang, Xingming & Wang, Lu & Sun, Chuanwang & Zheng, Xuemei & Wei, Jing, 2021. "Gap between words and actions: Empirical study on consistency of residents supporting renewable energy development in China," Energy Policy, Elsevier, vol. 148(PA).
    2. Sylwia Słupik & Joanna Kos-Łabędowicz & Joanna Trzęsiok, 2021. "Energy-Related Behaviour of Consumers from the Silesia Province (Poland)—Towards a Low-Carbon Economy," Energies, MDPI, vol. 14(8), pages 1-23, April.
    3. Liu, Bo & Luan, Wenpeng & Yu, Yixin, 2017. "Dynamic time warping based non-intrusive load transient identification," Applied Energy, Elsevier, vol. 195(C), pages 634-645.
    4. Cheng, Xiu & Long, Ruyin & Wu, Fan & Geng, Jichao & Yang, Jiameng, 2023. "How social interaction shapes habitual and occasional low-carbon consumption behaviors: Evidence from ten cities in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    5. Kabeya Clement Mulamba, 2020. "Relationship between education and households? electricity-saving behaviour in South Africa: A multilevel logistic analysis," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2020(2), pages 51-74.
    6. Ahmadi-Karvigh, Simin & Ghahramani, Ali & Becerik-Gerber, Burcin & Soibelman, Lucio, 2018. "Real-time activity recognition for energy efficiency in buildings," Applied Energy, Elsevier, vol. 211(C), pages 146-160.
    7. Ranran Yang & Chunxiao Yue & Jingjing Li & Junhong Zhu & Hongshu Chen & Jia Wei, 2020. "The Influence of Information Intervention Cognition on College Students’ Energy-Saving Behavior Intentions," IJERPH, MDPI, vol. 17(5), pages 1-17, March.
    8. Zhao, Bochao & Ye, Minxiang & Stankovic, Lina & Stankovic, Vladimir, 2020. "Non-intrusive load disaggregation solutions for very low-rate smart meter data," Applied Energy, Elsevier, vol. 268(C).
    9. Sylwia Słupik & Joanna Kos-Łabędowicz & Joanna Trzęsiok, 2021. "Are You a Typical Energy Consumer? Socioeconomic Characteristics of Behavioural Segmentation Representatives of 8 European Countries," Energies, MDPI, vol. 14(19), pages 1-28, September.
    10. Rashid, Haroon & Singh, Pushpendra & Stankovic, Vladimir & Stankovic, Lina, 2019. "Can non-intrusive load monitoring be used for identifying an appliance’s anomalous behaviour?," Applied Energy, Elsevier, vol. 238(C), pages 796-805.
    11. Liu, Chao & Akintayo, Adedotun & Jiang, Zhanhong & Henze, Gregor P. & Sarkar, Soumik, 2018. "Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network," Applied Energy, Elsevier, vol. 211(C), pages 1106-1122.
    12. Xu, Xiaoxiao & Yu, Hao & Sun, Qiuwen & Tam, Vivian W.Y., 2023. "A critical review of occupant energy consumption behavior in buildings: How we got here, where we are, and where we are headed," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    13. Janez Dolšak & Nevenka Hrovatin & Jelena Zorić, 2020. "Analysing Consumer Preferences, Characteristics, and Behaviour to Identify Energy-Efficient Consumers," Sustainability, MDPI, vol. 12(23), pages 1-19, November.
    14. Lin, Boqiang & Wang, Xia, 2021. "Does low-carbon travel intention really lead to actual low-carbon travel? Evidence from urban residents in China," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 743-756.
    15. Shigeru Matsumoto & Viet-Ngu Hoang & Clevo Wilson, 2024. "Covid-19 lockdown, gender and income dynamics in household energy consumption: evidence from Japan," Empirical Economics, Springer, vol. 67(4), pages 1473-1496, October.
    16. Yoseph, Nir Shlomo, 2018. "The Impact of Environmental Fraud on the Used Car Market: Evidence from Dieselgate," CEPR Discussion Papers 12899, C.E.P.R. Discussion Papers.
    17. Xingwei Li & Jianguo Du & Hongyu Long, 2019. "Green Development Behavior and Performance of Industrial Enterprises Based on Grounded Theory Study: Evidence from China," Sustainability, MDPI, vol. 11(15), pages 1-19, July.
    18. Villas-Boas, Sofia B, 2020. "Reduced Form Evidence on Belief Updating Under Asymmetric Information," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt08c456vk, Department of Agricultural & Resource Economics, UC Berkeley.
    19. Claire Chambolle & Eric Giraud‐Héraud, 2005. "Certification of Origin as a Non‐Tariff Barrier," Review of International Economics, Wiley Blackwell, vol. 13(3), pages 461-471, August.
    20. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja, 2017. "Report Cards: The Impact of Providing School and Child Test Scores on Educational Markets," American Economic Review, American Economic Association, vol. 107(6), pages 1535-1563, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261923000259. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.