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Comparison of Diffusion Models for Forecasting the Growth of Broadband Markets in Thailand

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  • Sudtasan, Tatcha
  • Mitomo, Hitoshi

Abstract

The aim of this paper is to investigate the most accurate S-curve model, the Logistic, Gompertz, and Bass models, in forecasting the diffusion of telecommunication markets Thailand. The analyses apply the data of mobile telecommunication market and fixed-broadband market separately without the interaction between both services. The originality of this study is at the diffusion path segmentation intervened by technological change that accelerates or decelerates each market. Parameters of each model are estimated by nonlinear model estimation methodology. By applying those parameters, the accuracy of each model can be identified compared to the actual data. Following the evaluation of the goodness-of-fit and forecasting ability, the Gompertz model shows the best performance in forecasting the diffusion of mobile telecommunication and fixed broadband markets. With the more suitable forecasting model to the markets, the ultimate total number of users in the future period could be more accurately predicted.

Suggested Citation

  • 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).
  • Handle: RePEc:zbw:itsp17:168541
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    References listed on IDEAS

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    1. Orakanya Kanjanatarakul & Komsan Suriya, 2012. "Comparison of sales forecasting models for an innovative agro-industrial product: Bass model versus logistic function," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(4), pages 89-106, December.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. 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.
    4. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
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    Cited by:

    1. Eleni Laitsou & Antonios Kargas & Dimitris Varoutas, 2020. "Digital Competitiveness in the European Union Era: The Greek Case," Economies, MDPI, vol. 8(4), pages 1-33, October.
    2. Kumar, Rajeev Ranjan & Guha, Pritha & Chakraborty, Abhishek, 2022. "Comparative assessment and selection of electric vehicle diffusion models: A global outlook," Energy, Elsevier, vol. 238(PC).
    3. 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.
    4. Franklin M. Lartey, 2020. "Predicting Product Uptake Using Bass, Gompertz, and Logistic Diffusion Models: Application to a Broadband Product," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 9(2), pages 1-5, October.

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    More about this item

    Keywords

    Broadband diffusion; Empirical comparison; Logistic model; Gompertz model; Bass model;
    All these keywords.

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