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The diffusion of mobile telephony in Kazakhstan: An empirical analysis

Author

Listed:
  • Sultanov, Azamat
  • Lee, Deok-Joo
  • Kim, Kyung-Taek
  • Avila, Luz Angelica Pirir

Abstract

Recently, the mobile telephony market of Kazakhstan has experienced rapid growth to the extent that the number of subscriptions exceeded the total population since 2009. In order to understand this phenomenon, this paper analyzes the diffusion of mobile telephony in Kazakhstan. Estimating the penetration rate of mobile telephony with the three most popular diffusion models, Logistic, Gompertz and Bass, it was found that the best fit model of the diffusion process for mobile telephony in Kazakhstan is Gompertz. Furthermore, we performed an empirical analysis to determine the significant factors that affect the fast diffusion speed and found that population and fixed line subscriptions are significant factors. Finally, we attempted to predict the demand of mobile telephony in Kazakhstan over the next ten years using a modified Gompertz model in which affecting factors are incorporated.

Suggested Citation

  • Sultanov, Azamat & Lee, Deok-Joo & Kim, Kyung-Taek & Avila, Luz Angelica Pirir, 2016. "The diffusion of mobile telephony in Kazakhstan: An empirical analysis," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 45-52.
    • Handle: RePEc:eee:tefoso:v:106:y:2016:i:c:p:45-52
    DOI: 10.1016/j.techfore.2016.01.020
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    Citations

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    Cited by:

    1. Mjellma Carabregu Vokshi But Dedaj Adel Ben Youssef Valentin Toçi, 2019. "Mobile phone penetration and its impact on inequality in the Western Balkan countries," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 22(2), pages 111-130, November.
    2. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Thakur Dhakal & Dae-Eun Lim, 2020. "Understanding ICT adoption in SAARC member countries," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 67-80, April.
    4. Ashutosh Jha & Manisha Chakrabarty & Debashis Saha, 2023. "Network Investment as Drivers of Mobile Subscription – A Firm-level Analysis," Information Systems Frontiers, Springer, vol. 25(5), pages 1811-1828, October.
    5. Bacha, Radia & Gasmi, Farid, 2022. "The broadband diffusion process and its determinants in Algeria: A simultaneous estimation," TSE Working Papers 22-1309, Toulouse School of Economics (TSE).
    6. Avila, Luz Angelica Pirir & Lee, Deok-Joo & Kim, Taegu, 2018. "Diffusion and competitive relationship of mobile telephone service in Guatemala: An empirical analysis," Telecommunications Policy, Elsevier, vol. 42(2), pages 116-126.
    7. Saurabh Panwar & P. K. Kapur & Ompal Singh, 2021. "Predicting diffusion dynamics and launch time strategy for mobile telecommunication services: an empirical analysis," Information Technology and Management, Springer, vol. 22(1), pages 33-51, March.
    8. Ashutosh Jha & Debashis Saha, 2022. "Mobile Broadband for Inclusive Connectivity: What Deters the High-Capacity Deployment of 4G-LTE Innovation in India?," Information Systems Frontiers, Springer, vol. 24(4), pages 1305-1329, August.
    9. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    10. Zhukov, Dmitry & Khvatova, Tatiana & Millar, Carla & Zaltcman, Anastasia, 2020. "Modelling the stochastic dynamics of transitions between states in social systems incorporating self-organization and memory," Technological Forecasting and Social Change, Elsevier, vol. 158(C).

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