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Diffusion of mobile telephony: An empirical study in Taiwan

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  • Chu, Wen-Lin
  • Wu, Feng-Shang
  • Kao, Kai-Sheng
  • Yen, David C.

Abstract

Mobile telephony penetration is a major indicator of mobile telephony diffusion. Taiwan had a mobile telephony penetration of 108% in 2002, ranking first in the world. This study analyzes this accelerated diffusion in terms of growth model and determinants of the diffusion rate. To eliminate the inherent uncertainty associated with choosing the optimal growth model, this study compares the performance of three conventional models, namely Gompertz, Logistic and Bass, to identify the most appropriate model, and to distinguish the forces driving the diffusion rate. Empirical results indicate that the most appropriate model is the Logistic model. Network externalities, which this study shows to be the same as the imitation effect in the Bass model, explain the superiority of the Logistic model. Moreover, market competition, which markedly reduces service prices, is identified as a primary driver of the diffusion rate of mobile telephony in Taiwan. Economic conditions, technological innovation and number of operators are insignificant factors. Finally, mobile telephony is a substitute for fixed-line telephony in Taiwan.

Suggested Citation

  • Chu, Wen-Lin & Wu, Feng-Shang & Kao, Kai-Sheng & Yen, David C., 2009. "Diffusion of mobile telephony: An empirical study in Taiwan," Telecommunications Policy, Elsevier, vol. 33(9), pages 506-520, October.
    • Handle: RePEc:eee:telpol:v:33:y:2009:i:9:p:506-520
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    Cited by:

    1. Baburin, Vyacheslav & Zemtsov, Stepan, 2014. "Diffussion of ICT-products and "five Russias"," MPRA Paper 68926, University Library of Munich, Germany, revised 10 May 2014.
    2. Riikonen, Antti & Smura, Timo & Kivi, Antero & Töyli, Juuso, 2013. "Diffusion of mobile handset features: Analysis of turning points and stages," Telecommunications Policy, Elsevier, vol. 37(6), pages 563-572.
    3. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    4. 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.
    5. Satoh, Daisuke, 2021. "Discrete Gompertz equation and model selection between Gompertz and logistic models," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1192-1211.
    6. Marinakis, Yorgos D., 2012. "Forecasting technology diffusion with the Richards model," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 172-179.
    7. Lin, Chiun-Sin, 2013. "Forecasting and analyzing the competitive diffusion of mobile cellular broadband and fixed broadband in Taiwan with limited historical data," Economic Modelling, Elsevier, vol. 35(C), pages 207-213.
    8. Oğuz, Fuat & Akkemik, K. Ali & Göksal, Koray, 2015. "Toward a wider market definition in broadband: The case of Turkey," Utilities Policy, Elsevier, vol. 37(C), pages 111-119.
    9. Zaber, Moinul & Sirbu, Marvin, 2012. "Impact of spectrum management policy on the penetration of 3G technology," Telecommunications Policy, Elsevier, vol. 36(9), pages 762-782.
    10. Tseng, Fang-Mei & Wang, Shenq-Yuan & Hsieh, Chih-Hung & Guo, Aifang, 2014. "An integrated model for analyzing the development of the 4G telecommunications market in Taiwan," Telecommunications Policy, Elsevier, vol. 38(1), pages 14-31.
    11. Sudtasan, Tatcha & Mitomo, Hitoshi, 2017. "Comparison of Diffusion Models for Forecasting the Growth of Broadband Markets in Thailand," 14th ITS Asia-Pacific Regional Conference, Kyoto 2017: Mapping ICT into Transformation for the Next Information Society 168541, International Telecommunications Society (ITS).
    12. 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.
    13. Dewenter, Ralf & Kruse, Jörn, 2011. "Calling party pays or receiving party pays? The diffusion of mobile telephony with endogenous regulation," Information Economics and Policy, Elsevier, vol. 23(1), pages 107-117, March.
    14. Ünver, Mehmet Bilal & Göktaylar, Yavuz & Tezel, Fatih, 2015. "Regulatory Implications of FMS for Voice Services in Turkey: Analysis of Recent Regulatory Acts on Deregulation and Margin Squeeze," 26th European Regional ITS Conference, Madrid 2015 127186, International Telecommunications Society (ITS).
    15. Yamakawa, Peter & Rees, Gareth H. & Manuel Salas, José & Alva, Nikolai, 2013. "The diffusion of mobile telephones: An empirical analysis for Peru," Telecommunications Policy, Elsevier, vol. 37(6), pages 594-606.
    16. Yuan, Xiaodong & Cai, Yuchen, 2021. "Forecasting the development trend of low emission vehicle technologies: Based on patent data," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    17. José F. C. Castro & Davidson C. Marques & Luciano Tavares & Nicolau K. L. Dantas & Amanda L. Fernandes & Ji Tuo & Luiz H. A. de Medeiros & Pedro Rosas, 2022. "Energy and Demand Forecasting Based on Logistic Growth Method for Electric Vehicle Fast Charging Station Planning with PV Solar System," Energies, MDPI, vol. 15(17), pages 1-21, August.
    18. Nguimkeu, Pierre, 2014. "A simple selection test between the Gompertz and Logistic growth models," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 98-105.
    19. 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).
    20. Xiaoxia Fu & Ping Zhang & Juzhi Zhang, 2017. "Forecasting and Analyzing Internet Users of China with Lotka–Volterra Model," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-18, February.
    21. Omamo, AmosO. & Rodrigues, Anthony J. & Muliaro, Wafula, 2019. "Kenya's vision 2030: Modelling technology usage and the economy," Technology in Society, Elsevier, vol. 59(C).
    22. Arunabha Mukhopadhyay & Kallol K. Bagchi & Godwin John Udo, 2024. "Exploring the Main Factors Affecting Mobile Phone Growth Rates in Indian States," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 5746-5768, June.
    23. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    24. Gupta, Ruchita & Jain, Karuna, 2015. "Adoption behavior of rural India for mobile telephony: A multigroup study," Telecommunications Policy, Elsevier, vol. 39(8), pages 691-704.
    25. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.

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