IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v153y2020ics0040162519316701.html
   My bibliography  Save this article

Forecasting the video data traffic of 5 G services in south korea

Author

Listed:
  • Shin, Hyungsup
  • Jung, Jiyeon
  • Koo, Yoonmo

Abstract

Along with the rapid evolution of mobile communication services, popularization of smartphones, and increase in traffic service usage, data traffic has also grown rapidly. Anticipating massive data traffic growth owing to the launch of the fifth-generation (5 G) mobile communication service in 2019, this study analyzes and forecasts: 1) the number of 5 G users using a logistic model, 2) consumer preference for 5 G services using a mixed logit model, and 3) 5 G data traffic increase using sensitivity analysis. The results indicate that data traffic would rapidly increase for 5 G services: the number of 5 G users is estimated to be 1.560 million by 2019, which will increase to 3.475 million by 2020 and 37.340 million by the end of 2025. Data traffic growth is predicted to reach 46 PB by the end of 2019, 129 PB by 2020, and 342 PB by 2021, after which it is projected to rapidly rise to 1,343 PB by 2022 and to 6,340 PB by 2025. The findings of this study provide a reference point for annual investment and marketing strategies of communication companies.

Suggested Citation

  • Shin, Hyungsup & Jung, Jiyeon & Koo, Yoonmo, 2020. "Forecasting the video data traffic of 5 G services in south korea," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    • Handle: RePEc:eee:tefoso:v:153:y:2020:i:c:s0040162519316701
    DOI: 10.1016/j.techfore.2020.119948
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162519316701
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2020.119948?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. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    2. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    4. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    5. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    6. Jongsu Lee & Minkyu Lee, 2009. "Analysis on the growth of telecommunication services: a global comparison of diffusion patterns," Applied Economics, Taylor & Francis Journals, vol. 41(24), pages 3143-3150.
    7. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    8. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    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. Brem, Alexander & Viardot, Eric & Nylund, Petra A., 2021. "Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    3. Hoeschele, Thomas & Dietzel, Christoph & Kopp, Daniel & Fitzek, Frank H.P. & Reisslein, Martin, 2021. "Importance of Internet Exchange Point (IXP) infrastructure for 5G: Estimating the impact of 5G use cases," Telecommunications Policy, Elsevier, vol. 45(3).

    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. Bi-Huei Tsai & Yiming Li, 2011. "Modelling competition in global LCD TV industry," Applied Economics, Taylor & Francis Journals, vol. 43(22), pages 2969-2981.
    2. Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.
    3. 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.
    4. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    5. Yogesh V. Joshi & David J. Reibstein & Z. John Zhang, 2009. "Optimal Entry Timing in Markets with Social Influence," Management Science, INFORMS, vol. 55(6), pages 926-939, June.
    6. Guo, Xuezhen, 2014. "A novel Bass-type model for product life cycle quantification using aggregate market data," International Journal of Production Economics, Elsevier, vol. 158(C), pages 208-216.
    7. Stone, Glenn Davis & Flachs, Andrew & Diepenbrock, Christine, 2014. "Rhythms of the herd: Long term dynamics in seed choice by Indian farmers," Technology in Society, Elsevier, vol. 36(C), pages 26-38.
    8. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    9. Hélène Dernis & Mariagrazia Squicciarini & Roberto Pinho, 2016. "Detecting the emergence of technologies and the evolution and co-development trajectories in science (DETECTS): a ‘burst’ analysis-based approach," The Journal of Technology Transfer, Springer, vol. 41(5), pages 930-960, October.
    10. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    11. Stefan Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    12. Jayasekara, Dinithi N. & Fredriksson, Per G., 2021. "Culture, intellectual property rights, and technology adoption," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 317-330.
    13. Mikael Sandberg, 2011. "Soft Power, World System Dynamics, and Democratization: A Bass Model of Democracy Diffusion 1800-2000," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(1), pages 1-4.
    14. Bernd Frick & Franziska Prockl, 2018. "Information Precision In Online Communities: Player Valuations On Www.Transfermarkt.De," Working Papers Dissertations 37, Paderborn University, Faculty of Business Administration and Economics.
    15. Lefeng, Shi & Shengnan, Lv & Chunxiu, Liu & Yue, Zhou & Cipcigan, Liana & Acker, Thomas L., 2020. "A framework for electric vehicle power supply chain development," Utilities Policy, Elsevier, vol. 64(C).
    16. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    17. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    18. Amini, Mehdi & Li, Haitao, 2011. "Supply chain configuration for diffusion of new products: An integrated optimization approach," Omega, Elsevier, vol. 39(3), pages 313-322, June.
    19. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    20. Massiani, Jérôme, 2015. "Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: Methods and results," Transport Policy, Elsevier, vol. 38(C), pages 19-26.

    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:tefoso:v:153:y:2020:i:c:s0040162519316701. 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.sciencedirect.com/science/journal/00401625 .

    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.