Abstract
Understanding the mechanism underlying the mobile telecommunications technologies (MTTs) diffusion in a country is crucial for telecom planners to know how to accelerate their diffusion by designing appropriate scenarios. Considering the technology diffusion as a bottom-up process, this study is aimed at exploring this mechanism, drawing on insights from diffusion of innovation theory and social network theory. Accordingly, an agent-based model is proposed to investigate how MTTs are diffused in Iran over time. The results of this study show, (1) social network of Iranian society seems more similar to a Watts–Strogatz small-world network than a Barabási–Albert preferential attachment network, where the clustering coefficient is high and average path length is low, (2) compared to the compatibility parameter, the advertisement parameter not only is less influential on diffusion of a targeted MTT (i.e., 4G) but also is not necessary for it, and (3) scenarios having the least number of steps and turning points are more appropriate for continuous diffusion of 4G. The proposed study is empirically validated against real-world data ranging from 7/1/2017 to 12/31/2017. We believe it provides telecom planners insights regarding MTTs diffusion mechanism in a social complex structure and the how of scenario designing for increasing their diffusion.
Highlights
High-speed access to mobile data has become one of the most significant demands of smartphone subscribers
Like other countries [3], in Iran, mobile broadband penetration rate has been much higher than that of fixed broadband, as the growth rate of fixed broadband subscribers has moved from 2.81% in the summer 2012 only to 12% in the spring 2017, while the growth rate of mobile broadband subscribers has shifted from 1.92% in summer 2012 to
In contrast to equation-based models (EBMs), such as statistical models and partial differential equations [45] that are rooted in deductive inference, Agent-based modeling (ABM) can work as an inductive inference technique where a conclusion is drawn from a series of observations, and as a pure form of abductive inference by which the best explanation for the phenomena under the study is captured by simulation
Summary
High-speed access to mobile data has become one of the most significant demands of smartphone subscribers. The increasing availability of intelligent equipment and the ever-growing demand for multi-media streaming services have drastically increased the volume of mobile data traffic [1]. In 2016, the total generated mobile data was 8.8 Exabyte, 50% of which belonged to video content. It is estimated that this amount will reach 71 Exabyte in 2020, 75% of which will belong to video content [2]. Statistics and figures indicate that the mobile broadband subscriber growth rate has been steadily higher than that of fixed broadband in the world. A fixed broadband penetration rate reached 11.9% in 2016, from 0.9% in 2012, while mobile broadband penetration rate reached 49.4% in 2016 from 21.7% in 2012 Figure 1. Like other countries [3], in Iran, mobile broadband penetration rate has been much higher than that of fixed broadband, as the growth rate of fixed broadband subscribers has moved from 2.81% in the summer 2012 only to 12% in the spring 2017, while the growth rate of mobile broadband subscribers has shifted from 1.92% in summer 2012 to
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