IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i22p12698-d680787.html
   My bibliography  Save this article

An Agent-Based Model for 5G Technology Diffusion in Urban Societies: Simulating Two Development Scenarios

Author

Listed:
  • Sahat Hutajulu

    (Institut Teknologi Bandung, School of Business Management, Bandung 40132, Indonesia)

  • Wawan Dhewanto

    (Institut Teknologi Bandung, School of Business Management, Bandung 40132, Indonesia)

  • Eko Agus Prasetio

    (Institut Teknologi Bandung, School of Business Management, Bandung 40132, Indonesia)

Abstract

Although 5G has been deployed in several countries, stakeholders are still hesitant to adopt the technology. Massive investment and collaboration become prerequisites for this technology to be successfully implemented and bring the most benefit. This research discusses the diffusion of 5G technology to personal end-users and industries and simulates the collaboration model. The simulation analyzes key essential indicators for stakeholders, such as the number of adopters, diffusion time, and total revenue. This study follows the pragmatism philosophy and abductive approach, integrating qualitative and quantitative research, resulting in the diffusion model. The qualitative data was obtained through focus groups and semi-structured interviews with key sources, while quantitative data from 437 people were gathered through a questionnaire. The simulation resulted in a 34% improvement in diffusion time, leading to faster investment return for industry players. This study offers an alternative paradigm compared to the diffusion of innovation theory, especially for new technology distribution. Finally, this research suggests that 5G stakeholders adopt the proposed collaboration strategy to achieve better business indicators.

Suggested Citation

  • Sahat Hutajulu & Wawan Dhewanto & Eko Agus Prasetio, 2021. "An Agent-Based Model for 5G Technology Diffusion in Urban Societies: Simulating Two Development Scenarios," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12698-:d:680787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/22/12698/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/22/12698/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    2. Hutajulu, Sahat & Dhewanto, Wawan & Prasetio, Eko Agus, 2020. "Two scenarios for 5G deployment in Indonesia," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    3. J. Gareth Polhill & Lee-Ann Sutherland & Nicholas M. Gotts, 2010. "Using Qualitative Evidence to Enhance an Agent-Based Modelling System for Studying Land Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(2), pages 1-10.
    4. Dania Marabissi & Lorenzo Mucchi & Romano Fantacci & Maria Rita Spada & Fabio Massimiani & Andrea Fratini & Giorgio Cau & Jia Yunpeng & Lucio Fedele, 2018. "A Real Case of Implementation of the Future 5G City," Future Internet, MDPI, vol. 11(1), pages 1-16, December.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Mart van der Kam & Annemijn Peters & Wilfried van Sark & Floor Alkemade, 2019. "Agent-Based Modelling of Charging Behaviour of Electric Vehicle Drivers," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 22(4), pages 1-7.
    7. Hossein Sabzian & Mohammad Ali Shafia & Mehdi Ghazanfari & Ali Bonyadi Naeini, 2020. "Modeling the Adoption and Diffusion of Mobile Telecommunications Technologies in Iran: A Computational Approach Based on Agent-Based Modeling and Social Network Theory," Sustainability, MDPI, vol. 12(7), pages 1-36, April.
    8. 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.
    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. Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
    2. Zhang, Cen & Schmöcker, Jan-Dirk & Kuwahara, Masahiro & Nakamura, Toshiyuki & Uno, Nobuhiro, 2020. "A diffusion model for estimating adoption patterns of a one-way carsharing system in its initial years," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 135-150.
    3. 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).
    4. Babutsidze, Zakaria, 2018. "The rise of electronic social networks and implications for advertisers," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 27-39.
    5. Sergei Sidorov & Alexey Faizliev & Vladimir Balash & Olga Balash & Maria Krylova & Aleksandr Fomenko, 2021. "Extended innovation diffusion models and their empirical performance on real propagation data," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 99-110, June.
    6. Arias-Gaviria, Jessica & Larsen, Erik R. & Arango-Aramburo, Santiago, 2018. "Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach," Utilities Policy, Elsevier, vol. 53(C), pages 73-83.
    7. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2018. "IRPsim: A techno-socio-economic energy system model vision for business strategy assessment at municipal level," Contributions of the Institute for Infrastructure and Resources Management 02/2018, University of Leipzig, Institute for Infrastructure and Resources Management.
    8. Arias-Gaviria, Jessica & Carvajal-Quintero, Sandra Ximena & Arango-Aramburo, Santiago, 2019. "Understanding dynamics and policy for renewable energy diffusion in Colombia," Renewable Energy, Elsevier, vol. 139(C), pages 1111-1119.
    9. Katarzyna Maciejowska & Arkadiusz Jedrzejewski & Anna Kowalska-Pyzalska & Katarzyna Sznajd-Weron & Rafal Weron, 2015. "Two faces of word-of-mouth: Understanding the impact of social interactions on demand curves for innovative products," HSC Research Reports HSC/15/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    10. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Modeling consumer opinions towards dynamic pricing: An agent-based approach," HSC Research Reports HSC/14/06, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    12. Li, Feng & Du, Timon C. & Wei, Ying, 2021. "With whom should I work? Ratings consideration for partner selection in a P2P supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    13. David Huckebrink & Valentin Bertsch, 2021. "Integrating Behavioural Aspects in Energy System Modelling—A Review," Energies, MDPI, vol. 14(15), pages 1-26, July.
    14. Oscar Gutiérrez & Francisco Ruiz-Aliseda, 2011. "Real options with unknown-date events," Annals of Finance, Springer, vol. 7(2), pages 171-198, May.
    15. Shari, Babajide Epe & Dioha, Michael O. & Abraham-Dukuma, Magnus C. & Sobanke, Victor O. & Emodi, Nnaemeka V., 2022. "Clean cooking energy transition in Nigeria: Policy implications for Developing countries," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 319-343.
    16. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    17. Tiruwork B. Tibebu & Eric Hittinger & Qing Miao & Eric Williams, 2024. "Adoption Model Choice Affects the Optimal Subsidy for Residential Solar," Energies, MDPI, vol. 17(3), pages 1-19, February.
    18. Simon P. Anderson & André de Palma, 2012. "Competition for attention in the Information (overload) Age," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 1-25, March.
    19. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    20. Van, Tien Linh Cao & Barthelmes, Lukas & Gnann, Till & Speth, Daniel & Kagerbauer, Martin, 2021. "Addressing the gaps in market diffusion modeling of electrical vehicles: A case study from Germany for the integration of environmental policy measures," Working Papers "Sustainability and Innovation" S05/2021, Fraunhofer Institute for Systems and Innovation Research (ISI).

    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:gam:jsusta:v:13:y:2021:i:22:p:12698-:d:680787. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.