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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
Ist Teil von
Technological forecasting & social change, 2020-03, Vol.152, p.119885, Article 119885
Ort / Verlag
New York: Elsevier Inc
Erscheinungsjahr
2020
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
•Bass model is suited for analyzing only 3G diffusion in India.•Gompertz and logistic are fit for forecasting of mobile broadband (3G+4G) in India.•The speed of 4G diffusion is 6.1 times that of 3G diffusion in India.•3G and 4G services in India will reach saturation by 2019 and 2023, respectively.•NTP 2012 positively influenced mobile broadband (3G+4G) diffusion in India.
An empirical understanding of countrywide diffusion of third (3G) or/and fourth (4G) generations of Mobile Broadband Services (MBSs) has proven implications for both business and policy of the country. However, extant literature lacks in explanation for the diffusion and forecast of these services in India. We address this gap by analyzing both individual and multigenerational diffusions of 3G and 4G services in India, using Bass, Gompertz, Logistic and Norton-Bass models that utilize a mix of linear and non-linear regression techniques. Additionally, we evaluate the influence of several exogenous variables on the diffusion of those MBSs in India. Our analyses reveal that, firstly in case of diffusion, Bass model estimates are quite sensitive to both 3G and 4G historical data, whereas Gompertz and Logistic models fit well with the same dataset. As expected, Norton-Bass model - encompassing all the successive generations of 2G, 3G and 4G - provides more reliable estimates of the diffusion parameters. Secondly, as far as 3G forecast is concerned, Bass model works better with fixed assumptions of ultimate market potential, whereas Gompertz and Logistic models seem to be more suited for ‘optimistic’ long-range forecasts and ‘conservative’ short-term forecasts, respectively. Our results also show that 4G is diffusing at 6.1 times the speed of 3G diffusion in India, when the total MBS subscription in India is likely to reach 410 million by 2026. Finally, we notice that, among the notable external sources of influence, National Telecom Policy 2012, average revenue per user, and aggregate income variables have significant positive impacts on the diffusion of MBSs in India.