A study on the relationship between technology diffusion and new product diffusion

Lee, Misuk; Kim, Kwangduk; Cho, Youngsang

doi:10.1016/j.techfore.2010.01.003

Cited by 49 publications

(23 citation statements)

References 11 publications

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“…In addition to easing the doing of business (Kumar & Zahn, 2003;Kuoa & Yub, 2006;Jin & von Zedtwitz, 2008;Lee et al, 2010), the mobile revolution has generated a plethora of inclusive development benefits to developing countries. According to recent African development literature (Asongu & De Moor, 2015), the revolution of the mobile phone has touched almost every societal fabric in Africa.…”

Section: Mobile Phones Penetration and Inclusive Developmentmentioning

confidence: 99%

The role of governance in mobile phones for inclusive human development in Sub-Saharan Africa

2016

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Section: Mobile Phones Penetration and Inclusive Developmentmentioning

confidence: 99%

The role of governance in mobile phones for inclusive human development in Sub-Saharan Africa

2016

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“…Stoneman (1983), Markus (1987), Geroski (2000) or Peres et al (2010) emphasize that emerging network externalities are the principal phenomenon that characterize technology diffusion and determine its dynamics. The network externalities are analogous to 'imitation effect' in the Bass model (see -Bass (1969-Bass ( , 1980, or the 'word-of-mouth' effect (or the 'domino effect') (see -Geroski, 2000, Lee et al, 2010. In other words, the value of new technological solution for an individual depends on how many people has already adopted it and use it, especially in communication technologies.…”

Section: Introductionmentioning

confidence: 99%

Networks Externalities as Social Phenomenon in the Process ICT Diffusion

Lechman¹

2018

Economics &Amp; Sociology

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ABSTRACT. This paper is designed to fill the gap in knowledge that we have identified regarding the process of diffusion of information and communication technologies and emerging network effects that significantly enhance spread of these technologies. We contribute to the present state of the art by examining the process of ICT diffusion in 50 countries, which in 2015 achieved highest ICT penetration rates. With this aim we consider 2 core ICT indicators -mobile cellular telephony and Internet penetration rates; all statistical data are entirely extracted from World Telecommunications / ICT Indicators database 2016. In the research part we demonstrate ICT diffusion curves and examine elementary descriptive statistics to show how fast and pervasively information and communication technologies have evaded telecommunication markets. Next, relying on panel and dynamic panel models we verify the hypothesis on the existence of network effects that enhance rate of ICT diffusion. Our major findings confirm that across countries being in scope of our analysis, the process of ICT diffusion has been significantly attributed to strong network externalities. JEL Classification: O33, A14, D80

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“…According to an analysis of 213 applications of Bass diffusion model done by Sultan et al, the average external influence parameter was estimated to be 0.03 (Sultan et al 1990;Lee et al 2010). With external influence, more AB are generated as the consequence of increased interactions between the two opposing factions A and B. AB survived beyond the critical value of zealot population (A c ).…”

Section: Population Sizementioning

confidence: 99%

On the role of evangelism in consensus formation: a simulation approach

Sharma

Chourasia

Bhatia

et al. 2016

Complex Adapt Syst Model

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Purpose Opinions continuously evolve in society. While conservative ideas may get replaced by a new one, some views remain immutable. Opinion formation and innovation diffusion have witnessed lots of attention in the last decade due to its widespread applicability in the diverse domain of science and technology. We analyse these scenarios in which interactions at the micro level results in the changes in opinions at the macro level in a population of predefined ideological groups. Methods We use the Bass model, otherwise well known for understanding innovation diffusion phenomena, to compute adoption probabilities of three opinion states-zealot, extremists and moderates. Thereafter, we employ cellular automata to explore the emergence of opinions through local and overlapped interactions between agents (people). NetLogo environment has been used to develop an agent-based model, simulating different ideological scenarios. Results Simulation results validate a critical proportion of committed individuals as a plausible basis for ideological shifts in societies. The analysis elucidates upon the role of moderates in the population and emergence of varying opinions. The results further delineate the role of evangelism through social and non-social methods in propagating views. Conclusion The results obtained from these simulations endorse the conclusions reported in previous studies regarding the role of a critical zealot population, and the preponderance of non-social influence. We, however, use two-phase opinion model with different experimental settings. Additionally, we examine global observable, such as entropy of the system to reveal common patterns of adoption in the views and evenness of population after reaching a consensus.

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A study on the relationship between technology diffusion and new product diffusion

Cited by 49 publications

References 11 publications

The role of governance in mobile phones for inclusive human development in Sub-Saharan Africa

The role of governance in mobile phones for inclusive human development in Sub-Saharan Africa

Networks Externalities as Social Phenomenon in the Process ICT Diffusion

On the role of evangelism in consensus formation: a simulation approach

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