IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v505y2018icp591-600.html
   My bibliography  Save this article

The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach

Author

Listed:
  • Weron, Tomasz
  • Kowalska-Pyzalska, Anna
  • Weron, Rafał

Abstract

Using an agent-based modeling approach we examine the impact of educational programs and trainings on the diffusion of smart metering platforms (SMPs). We also investigate how social responses, like conformity or independence, mass-media advertising as well as opinion stability impact the transition from predecisional and preactional behavioral stages (opinion formation) to actional and postactional stages (decision-making) of individual electricity consumers. We find that mass-media advertising (i.e., a global external field) and educational trainings (i.e., a local external field) lead to similar, though not identical adoption rates. Secondly, that spatially concentrated ‘group’ trainings are never worse than randomly scattered ones, and for a certain range of parameters are significantly better. Finally, that by manipulating the time required by an agent to make a decision, e.g., through promotions, we can speed up or slow down the diffusion of SMPs.

Suggested Citation

  • Weron, Tomasz & Kowalska-Pyzalska, Anna & Weron, Rafał, 2018. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 591-600.
    • Handle: RePEc:eee:phsmap:v:505:y:2018:i:c:p:591-600
    DOI: 10.1016/j.physa.2018.03.086
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118304072
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2018.03.086?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Gangale, Flavia & Mengolini, Anna & Onyeji, Ijeoma, 2013. "Consumer engagement: An insight from smart grid projects in Europe," Energy Policy, Elsevier, vol. 60(C), pages 621-628.
    2. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    3. Zhang, T. & Nuttall, W.J., 2008. "Evaluating Government’s Policies on Promoting Smart Metering in Retail Electricity Markets via Agent Based Simulation," Cambridge Working Papers in Economics 0842, Faculty of Economics, University of Cambridge.
    4. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    5. Galam, Serge & Jacobs, Frans, 2007. "The role of inflexible minorities in the breaking of democratic opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 366-376.
    6. Papachristos, George, 2017. "Diversity in technology competition: The link between platforms and sociotechnical transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 291-306.
    7. Anna Kowalska-Pyzalska, 2015. "Social acceptance of green energy and dynamic electricity tariffs - a short review," HSC Research Reports HSC/15/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. Diaz-Rainey, Ivan & Tzavara, Dionisia, 2012. "Financing the decarbonized energy system through green electricity tariffs: A diffusion model of an induced consumer environmental market," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1693-1704.
    9. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    10. Piotr Przybyła & Katarzyna Sznajd-Weron & Rafał Weron, 2014. "Diffusion Of Innovation Within An Agent-Based Model: Spinsons, Independence And Advertising," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-22.
    11. Katarzyna Sznajd-Weron & Janusz Szwabinski & Rafal Weron & Tomasz Weron, 2013. "Rewiring the network. What helps an innovation to diffuse?," HSC Research Reports HSC/13/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    12. Anna Kowalska-Pyzalska & Karolina Cwik & Arkadiusz Jedrzejewski & Katarzyna Sznajd-Weron, 2016. "Linking consumer opinions with reservation prices in an agent-based model of innovation diffusion," HSC Research Reports HSC/16/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    13. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    14. Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Szwabiński, Janusz, 2016. "Mapping the q-voter model: From a single chain to complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 110-119.
    15. Gerpott, Torsten J. & Paukert, Mathias, 2013. "Determinants of willingness to pay for smart meters: An empirical analysis of household customers in Germany," Energy Policy, Elsevier, vol. 61(C), pages 483-495.
    16. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    17. Gadenne, David & Sharma, Bishnu & Kerr, Don & Smith, Tim, 2011. "The influence of consumers' environmental beliefs and attitudes on energy saving behaviours," Energy Policy, Elsevier, vol. 39(12), pages 7684-7694.
    18. D. Stauffer & A. O. Sousa & S. Moss De Oliveira, 2000. "Generalization To Square Lattice Of Sznajd Sociophysics Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1239-1245.
    19. Sobkowicz, Pawel, 2016. "Agent based model of effects of task allocation strategies in flat organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 17-30.
    20. Martins, André C.R. & Pereira, Carlos de B. & Vicente, Renato, 2009. "An opinion dynamics model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3225-3232.
    21. Claudy, Marius C. & Michelsen, Claus & O'Driscoll, Aidan & Mullen, Michael R., 2010. "Consumer awareness in the adoption of microgeneration technologies: An empirical investigation in the Republic of Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2154-2160, September.
    22. Katarzyna Sznajd-Weron & Janusz Szwabiński & Rafał Weron, 2014. "Is the Person-Situation Debate Important for Agent-Based Modeling and Vice-Versa?," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-7, November.
    23. Galam, Serge, 2004. "Contrarian deterministic effects on opinion dynamics: “the hung elections scenario”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 453-460.
    24. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
    25. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    26. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    27. Alexandra-Gwyn Paetz & Elisabeth Dütschke & Wolf Fichtner, 2012. "Smart Homes as a Means to Sustainable Energy Consumption: A Study of Consumer Perceptions," Journal of Consumer Policy, Springer, vol. 35(1), pages 23-41, March.
    28. Paul R. Nail & Katarzyna Sznajd-Weron, 2016. "The diamond model of social response within an agent-based approach," HSC Research Reports HSC/16/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    29. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.
    30. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anna Kowalska-Pyzalska & Katarzyna Byrka, 2019. "Determinants of the Willingness to Energy Monitoring by Residential Consumers: A Case Study in the City of Wroclaw in Poland," Energies, MDPI, vol. 12(5), pages 1-20, March.
    2. Yash Chawla & Anna Kowalska-Pyzalska & Burcu Oralhan, 2020. "Attitudes and Opinions of Social Media Users Towards Smart Meters’ Rollout in Turkey," Energies, MDPI, vol. 13(3), pages 1-27, February.
    3. Bartłomiej Nowak & Katarzyna Sznajd-Weron, 2019. "Homogeneous Symmetrical Threshold Model with Nonconformity: Independence versus Anticonformity," Complexity, Hindawi, vol. 2019, pages 1-14, April.
    4. Yash Chawla & Anna Kowalska-Pyzalska, 2019. "Public Awareness and Consumer Acceptance of Smart Meters among Polish Social Media Users," Energies, MDPI, vol. 12(14), pages 1-27, July.
    5. Liu, Xueying & Madlener, Reinhard, 2021. "The sky is the limit: Assessing aircraft market diffusion with agent-based modeling," Journal of Air Transport Management, Elsevier, vol. 96(C).

    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. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    2. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. Anna Kowalska-Pyzalska, 2015. "Social acceptance of green energy and dynamic electricity tariffs - a short review," HSC Research Reports HSC/15/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Anna Kowalska-Pyzalska & Katarzyna Byrka, 2019. "Determinants of the Willingness to Energy Monitoring by Residential Consumers: A Case Study in the City of Wroclaw in Poland," Energies, MDPI, vol. 12(5), pages 1-20, March.
    5. Byrka, Katarzyna & Jȩdrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna & Weron, Rafał, 2016. "Difficulty is critical: The importance of social factors in modeling diffusion of green products and practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 723-735.
    6. Jędrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna, 2018. "Impact of memory on opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 306-315.
    7. Yash Chawla & Anna Kowalska-Pyzalska, 2019. "Public Awareness and Consumer Acceptance of Smart Meters among Polish Social Media Users," Energies, MDPI, vol. 12(14), pages 1-27, July.
    8. Anna Kowalska-Pyzalska & Katarzyna Byrka & Jakub Serek, 2020. "How to Foster the Adoption of Electricity Smart Meters? A Longitudinal Field Study of Residential Consumers," Energies, MDPI, vol. 13(18), pages 1-19, September.
    9. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    10. Anna Kowalska-Pyzalska, 2018. "An Empirical Analysis of Green Electricity Adoption Among Residential Consumers in Poland," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    11. Anna Kowalska-Pyzalska, 2018. "An empirical analysis of green energy adoption among residential consumers in Poland," HSC Research Reports HSC/18/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    12. Yash Chawla & Anna Kowalska-Pyzalska & Burcu Oralhan, 2020. "Attitudes and Opinions of Social Media Users Towards Smart Meters’ Rollout in Turkey," Energies, MDPI, vol. 13(3), pages 1-27, February.
    13. Chawla, Yash & Kowalska-Pyzalska, Anna & Skowrońska-Szmer, Anna, 2020. "Perspectives of smart meters’ roll-out in India: An empirical analysis of consumers’ awareness and preferences," Energy Policy, Elsevier, vol. 146(C).
    14. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    15. Yash Chawla & Anna Kowalska-Pyzalska & Paulo Duarte Silveira, 2019. "Marketing and communications channels for diffusion of smart meters in Portugal," HSC Research Reports HSC/19/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    16. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    17. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    18. Agnieszka Kowalska-Styczeń & Krzysztof Malarz, 2020. "Noise induced unanimity and disorder in opinion formation," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-22, July.
    19. Walzberg, Julien & Dandres, Thomas & Merveille, Nicolas & Cheriet, Mohamed & Samson, Réjean, 2019. "Assessing behavioural change with agent-based life cycle assessment: Application to smart homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 365-376.
    20. Lopes, Marta A.R. & Henggeler Antunes, Carlos & Janda, Kathryn B. & Peixoto, Paulo & Martins, Nelson, 2016. "The potential of energy behaviours in a smart(er) grid: Policy implications from a Portuguese exploratory study," Energy Policy, Elsevier, vol. 90(C), pages 233-245.

    More about this item

    Keywords

    Smart meter; Smart metering platform (SMP); Behavioral strategy; Demand response; Diffusion of innovations; Agent-based model;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

    Statistics

    Access and download statistics

    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:phsmap:v:505:y:2018:i:c:p:591-600. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.