2012
DOI: 10.1016/j.tele.2011.10.003
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An analysis of mobile Internet access in Thailand: Implications for bridging the digital divide

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Cited by 72 publications
(28 citation statements)
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“…For example, China has sought to increase Internet access in remote rural areas (Harwit 2004;Lai 2010) and has promoted the mobile Internet there (Loo and Ngan 2012). Similar programs exist in South Korea (Moon et al 2012), Thailand (Srinuan, Srinuan, and Bohlin 2012), and Malaysia (Nair et al 2010). The Indian government has initiated several commissions to bridge the country's digital divide, with limited success, such as Gyandoot, a series of digital information kiosks in Madhya Pradesh launched in 2000 (Rao 2005;Monga 2008).…”
Section: E-government and Digital Dividesmentioning
confidence: 99%
“…For example, China has sought to increase Internet access in remote rural areas (Harwit 2004;Lai 2010) and has promoted the mobile Internet there (Loo and Ngan 2012). Similar programs exist in South Korea (Moon et al 2012), Thailand (Srinuan, Srinuan, and Bohlin 2012), and Malaysia (Nair et al 2010). The Indian government has initiated several commissions to bridge the country's digital divide, with limited success, such as Gyandoot, a series of digital information kiosks in Madhya Pradesh launched in 2000 (Rao 2005;Monga 2008).…”
Section: E-government and Digital Dividesmentioning
confidence: 99%
“…Several studies, on the other hand, suggest mobile Internet access is associated with income. For example, Srinuan et al (2012) considers price as one of the strongest factors of mobile Internet adoption in Thailand. Even in the context of the OECD countries, Lee et al (2011) suggest income as a factor of mobile broadband adoption.…”
Section: Affordability and Other Prerequisitesmentioning
confidence: 99%
“…They find that standardization policies and population density are essential factors for the initial diffusion of the service, and that fixed and mobile broadband services are complementary in OECD countries. Srinuan et al (2012a) use a binomial logit regression model and find that in Thailand the age, region of residence and availability of fixed telephony are significant drivers of mobile internet access. Finally, Srinuan et al (2012b) consider a panel dataset of Finnish households in 2009, and use a multinomial logit model to examine which household characteristics explain Internet adoption.…”
Section: Literature Reviewmentioning
confidence: 99%