An estimation of the pattern of diffusion of mobile phones: The case of Colombia

Gamboa, Luis Fernando; Otero, Jesús

doi:10.1016/j.telpol.2009.08.004

Cited by 41 publications

(15 citation statements)

References 23 publications

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“…Logistic model is found appropriate to describe the process of mobile diffusion in Portugal ( [10], [12]), in Korea ( [13]), Taiwan ( [17]), Colombia ( [16]) and Cameroon ( [23]). The Gompertz model is found to fit best to the data and to give accurate forecasts for the mobile diffusion process in Turkey ( [21]).…”

Section: Resultsmentioning

confidence: 99%

“…Singh [15] found that the Gompertz model adequately described the path of mobile phone diffusion from 1995-1996 to 2005-2006 in India and the number of mobile phones will exceed the number of people by 2022-2023. The findings of Gamboa and Otero [16] indicate that the diffusion pattern of mobile telephony in Colombia can be best characterised as following a Logistic specification. The estimated saturation level of 103.7 was expected to be reached in five years' time.…”

Section: Introductionmentioning

confidence: 92%

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Modeling and Forecasting the Diffusion of Mobile Telephony in Albania and Turkey

Spaho

Kraja

2019

Journal of Engineering Technology and Applied Sciences

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Mobile telephony has become a main factor driving the social and economic development of a country. This study examines the diffusion process of mobile telephony in Albania and Turkey. The aim of this research is to model and to forecast the diffusion rate of mobile telephony using Logistic and Gompertz models, and World Bank data. The results of estimated models indicated that the Gompertz model fits best with the actual data of mobile telephony in Albania, and the Logistic model fits best with the actual data of mobile telephony in Turkey. According to the results of the Logistic model, the best model for predicting the diffusion rate of mobile telephony in Albania, the maximum level of the mobile diffusion rate of 131.89% will be achieved in the year 2025. The results of the Gompertz model, the best model for predicting the mobile telephony in Turkey indicate that the maximum diffusion rate of 97.98% is predicted to be achieved after the year 2025. These findings are useful to telecommunication operators, policymakers, and customers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Modeling and Forecasting the Diffusion of Mobile Telephony in Albania and Turkey

Spaho

Kraja

2019

Journal of Engineering Technology and Applied Sciences

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“…Specifically p indicates the rate of change of adoption by innovators per unit fraction of population while q indicates the rate of change of adoption by imitators per unit fraction of potential adopters population per unit of existing adopters. In other words, p reflects the fraction of adopters who are innovators and q reflects the pressure operating on imitators 1 Logistic curve is derived from a differential equation where the relative growth rate of a product decreases monotonically with time, while in the case of the Gompertz curve the relative growth rate decreases in an exponential fashion (Gamboa and Otero, 2009).…”

Section: -4mentioning

confidence: 99%

Modelling Diffusion of Wind Power Across Countries

Panse

Kathuria

2015

Int. J. Innov. Mgt.

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In this paper, we analyse the diffusion mechanism of wind power over the last two decades in the leading countries, namely China, the United States, Germany, India and Spain. For each country, three prominent models of technology diffusion (Logistic, Bass and Gompertz) were fitted and the best model is identified based on AIC, BIC and adjusted R 2 criteria. The selected diffusion model in each case is then characterised with respect to the policy mechanisms. Often, research follows the "one size fits all" approach and tends to propose one model to define diffusion for all. Here we find that it is not necessarily true. The study then proposes the causal relationship between parameters of the selected model and corresponding policies along with the socioeconomic structure for a country to corroborate our findings. Further, forecasts were generated to predict the saturation point of the diffusion path and solutions are proposed to expand the diffusion curve.

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“…See Griliches (1957), Mansfield (1968), and Stoneman (2002) for a survey of technological diffusion. In addition, the S-shaped interhousehold diffusion is treated as a stylized fact in the marketing literature and found in color televisions (Karshenas and Stoneman, 1992), fax machines (Economides and Himmelberg, 1995), clothes dryers (Krishnan, Bass, and Jain, 1999), and mobile phones (Gamboa and Otero, 2009).…”

Section: Introductionmentioning

confidence: 99%

Free entry, market diffusion, and social inefficiency with endogenously growing demand

Kitamura

Miyaoka

Sato

2013

Journal of the Japanese and International Economies

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This paper analyzes market diffusion in the presence of oligopolistic interaction among firms. Market demand is positively related to past market size because of consumer learning, networks, and bandwagon effects. Firms enter the market freely in each period with fixed costs and compete in quantities. We demonstrate that the nature of the inefficiency under free entry can change as the market grows, and more importantly, that S-shaped diffusion can be a signal that the number of firms under free entry is initially insufficient, but eventually excessive.

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An estimation of the pattern of diffusion of mobile phones: The case of Colombia

Cited by 41 publications

References 23 publications

Modeling and Forecasting the Diffusion of Mobile Telephony in Albania and Turkey

Modeling and Forecasting the Diffusion of Mobile Telephony in Albania and Turkey

Modelling Diffusion of Wind Power Across Countries

Free entry, market diffusion, and social inefficiency with endogenously growing demand

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