BibTex RIS Kaynak Göster

Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case

Yıl 2015, Cilt 3, Sayı 2, 2015, 35 - 40, 30.12.2015
https://doi.org/10.17093/aj.2015.3.2.5000140094

Öz

This paper aims to analyze relationship between Mobile penetration and various indicators of communication infrastructure throughout OECD countries. Panel data is utilized for the purpose of this study. In order to control network effects as well as the endogeneity of variables, the Arellano–Bond dynamic panel estimation is adopted. In particular, this paper attempts to identify what are the factors to promote the 3G mobile phone by using dynamic panel data analysis. In constructing an estimation model, Cellular mobile penetration is taken as a dependent variable, while various technical and economic variables are selected as independent variables. The obtained results can be used to forecast adoption of New Broadband Penetration technology. 

Kaynakça

  • Abu, S.T. 2010. Technological innovations and 3G mobile phone diffusion: Lessons learned from Japan. Telematics and Informatics. 27 (2010) 418–432.
  • Akematsu, Y. , Shinohara, S.,& Tsuji, M., Empirical analysis of factors promoting the Japanese 3G mobile phone, Telecommunications Policy. 36 (2012) 175–186
  • Andres, L., Cuberes,D., Diouf,M., & Serebrisky,T. (2010). The diffusion of the Internet: A cross-country analysis. Telecommunications Policy, 34(5–6), 323–340.
  • Arellano, M., & O. Bover. 1995. Another look at the instrumental variables estimation of error components models. Journal of Econometrics. 68: 29(51).
  • Arellano, M. & S. Bond. (April 1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58. pp. 277 – 297.
  • Bouckaert, J.,VanDijk,T., & Verboven,F.(2010).Access regulation, competition, and broadband penetration: An international study. Telecommunications Policy, 34(11), 661–671.
  • Cava-Ferreruela, I.,&Alabau-Muˇ noz, A.(2006).Broadband policy assessment:Across-national empirical analysis. Telecommunications Policy, 30(8-9), 445–463.
  • Chen, L.-Y. 2014. Application of SVR with chaotic GASA algorithm to forecast Taiwanese 3G mobile phone demand. Neuro computing 127 (2014) 206–213.
  • Church, J. & Gandal, N. (2005). Platform competition in telecommunications. In: S.Mujumdar, I. Vogelsang, and M.Cave (Eds.), The handbook of telecommunications (pp. 119–150). Amsterdam:North-Holland.
  • Distaso, W., Lupi,P., & Maneti, F.M. (2006). Platform competition and broadband uptake:Theory and empirical evidence from the European Union. Information Economics and Policy, 18(1), 87–106.
  • Estache, A.,Manacorda,M., & Valletti, T. M. (2002). Telecommunications, reform, Access regulation, and Internet adoption in Latin America. Economia Pubblica, 2, 153–217.
  • Garcia-Murillo, M.(2005).International broadband deployment: The impact of unbundling. Communications and Strategies, 57, 83–108.
  • Gruber, H., & Verboven,F. (2001). The evolution of markets under entry and standards regulation: The case of global mobile telecommunications. International Journal of Industrial Organisation, 19, 1189–1212.
  • Kang F. , Hauge J. A. ,& Lu T. . (2012) Competition and mobile network investment in China’s telecommunications industry. Telecommunications Policy. 36 901–913
  • Kwon. 2011. An Empirical Analysis of the State of Competition in OECD Mobile Wireless Markets. 22nd European Regional ITS Conference Budapest, 18-21 September, 2011.
  • Kiiski, S., & Pohjola,M.(2002).Cross-country diffusion of the Internet. Information Economics and Policy, 14, 297–310.
  • Lee, S., & Brown,J.S. (2008). Examining broadband adoption factors: An empirical analysis between countries. The Journal of Policy,Regulation,and Strategy for Telecommunication, Information, and Media, 10(1), 25–39.
  • Lee, S., & Lee,S. (2010). An empirical study of broadband diffusion and bandwidth capacity in OECD countries. Communications and Convergence Review, 2(1). KISDI.
  • Lin M., & Wu F. Identifying the determinants of broadband adoption by diffusion stage in OECD countries, Telecommunications Policy. 37 (2013) 241–251.
  • OECD. (2013). Communications outlook. Paris:Head of Publications Service, OECD. Retrieved from /http://www.oecd.org/S.
  • Pagani, M. 2006. Determinants of adoption of High Speed Data Services in the business market: Evidence for a combined technology acceptance model with task technology fit model. Information & Management 43 (2006) 847–860.
  • Suki, N.M. 2011. Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. Journal of Information Technology Management. Volume XXII, Number 1, 2011.
  • Rogers, E.M.(2003). The diffusion of innovations (5th edition).New York: The Free Press. ).
  • Roodman, D. (December 2006). How to do xtabond2: an introduction to “Difference” and “System” GMM in Stata. Center for Global Development. Working Paper Number 103
  • Singh, S.K.(2008).The diffusion of mobile phone in India. Telecommunications Policy. 32, 642–651.
  • Stoneman, P. (1983). The economic analysis of technological change. Oxford: Oxford University Press.
  • Trappey, C.V., & Wu, H. (2008). An evaluation of the time –varying extended logistic,simple logistic, and Gompertz models for forecasting short product life cycles. Advanced Engineering Informatics, 22, 421–430.
  • Xia, J. (2011). The third-generation-mobile (3G) policy and deployment in China: Current status, challenges, and prospects. Telecommunications Policy. 35 (2011) 51–63.

Yeni Geniş Bant Adaptasyonunu Tahminlemede Mobil Penetrasyonun Belirleyicileri: OECD Örneği

Yıl 2015, Cilt 3, Sayı 2, 2015, 35 - 40, 30.12.2015
https://doi.org/10.17093/aj.2015.3.2.5000140094

Öz

Bu makalede mobil penetrasyon ile iletişim altyapısının çeşitli göstergeleri arasındaki ilişki OECD ülkeleri genelinde analiz edilmektedir. Bu amaçla panel data yöntemi kullanılmıştır. Değişkenlerin içsellik sorunu ve ağ etkilerini kontrol edebilmek için Arellano-Bond dinamik panel tahmini uygulanmıştır. Özel olarak bu makale, ilerideki çalışmalarda 4G kullanımını tahminleyebilmek için dinamik panel data analizini kullanarak 3G kullanımı etkileyen faktörleri belirlemeye çalışmaktadır. Bu amaçla bir tahmin modeli oluştururken cep telefonu penetrasyonu bağımlı değişken olarak, çeşitli teknik ve ekonomik değişkenler de bağımsız değişkenler olarak alınmıştır. Elde edilen sonuçlar yeni geniş bant penetrasyon teknolojisinin adaptasyonunu tahmin etmek için kullanılabilecektir.

Kaynakça

  • Abu, S.T. 2010. Technological innovations and 3G mobile phone diffusion: Lessons learned from Japan. Telematics and Informatics. 27 (2010) 418–432.
  • Akematsu, Y. , Shinohara, S.,& Tsuji, M., Empirical analysis of factors promoting the Japanese 3G mobile phone, Telecommunications Policy. 36 (2012) 175–186
  • Andres, L., Cuberes,D., Diouf,M., & Serebrisky,T. (2010). The diffusion of the Internet: A cross-country analysis. Telecommunications Policy, 34(5–6), 323–340.
  • Arellano, M., & O. Bover. 1995. Another look at the instrumental variables estimation of error components models. Journal of Econometrics. 68: 29(51).
  • Arellano, M. & S. Bond. (April 1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58. pp. 277 – 297.
  • Bouckaert, J.,VanDijk,T., & Verboven,F.(2010).Access regulation, competition, and broadband penetration: An international study. Telecommunications Policy, 34(11), 661–671.
  • Cava-Ferreruela, I.,&Alabau-Muˇ noz, A.(2006).Broadband policy assessment:Across-national empirical analysis. Telecommunications Policy, 30(8-9), 445–463.
  • Chen, L.-Y. 2014. Application of SVR with chaotic GASA algorithm to forecast Taiwanese 3G mobile phone demand. Neuro computing 127 (2014) 206–213.
  • Church, J. & Gandal, N. (2005). Platform competition in telecommunications. In: S.Mujumdar, I. Vogelsang, and M.Cave (Eds.), The handbook of telecommunications (pp. 119–150). Amsterdam:North-Holland.
  • Distaso, W., Lupi,P., & Maneti, F.M. (2006). Platform competition and broadband uptake:Theory and empirical evidence from the European Union. Information Economics and Policy, 18(1), 87–106.
  • Estache, A.,Manacorda,M., & Valletti, T. M. (2002). Telecommunications, reform, Access regulation, and Internet adoption in Latin America. Economia Pubblica, 2, 153–217.
  • Garcia-Murillo, M.(2005).International broadband deployment: The impact of unbundling. Communications and Strategies, 57, 83–108.
  • Gruber, H., & Verboven,F. (2001). The evolution of markets under entry and standards regulation: The case of global mobile telecommunications. International Journal of Industrial Organisation, 19, 1189–1212.
  • Kang F. , Hauge J. A. ,& Lu T. . (2012) Competition and mobile network investment in China’s telecommunications industry. Telecommunications Policy. 36 901–913
  • Kwon. 2011. An Empirical Analysis of the State of Competition in OECD Mobile Wireless Markets. 22nd European Regional ITS Conference Budapest, 18-21 September, 2011.
  • Kiiski, S., & Pohjola,M.(2002).Cross-country diffusion of the Internet. Information Economics and Policy, 14, 297–310.
  • Lee, S., & Brown,J.S. (2008). Examining broadband adoption factors: An empirical analysis between countries. The Journal of Policy,Regulation,and Strategy for Telecommunication, Information, and Media, 10(1), 25–39.
  • Lee, S., & Lee,S. (2010). An empirical study of broadband diffusion and bandwidth capacity in OECD countries. Communications and Convergence Review, 2(1). KISDI.
  • Lin M., & Wu F. Identifying the determinants of broadband adoption by diffusion stage in OECD countries, Telecommunications Policy. 37 (2013) 241–251.
  • OECD. (2013). Communications outlook. Paris:Head of Publications Service, OECD. Retrieved from /http://www.oecd.org/S.
  • Pagani, M. 2006. Determinants of adoption of High Speed Data Services in the business market: Evidence for a combined technology acceptance model with task technology fit model. Information & Management 43 (2006) 847–860.
  • Suki, N.M. 2011. Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. Journal of Information Technology Management. Volume XXII, Number 1, 2011.
  • Rogers, E.M.(2003). The diffusion of innovations (5th edition).New York: The Free Press. ).
  • Roodman, D. (December 2006). How to do xtabond2: an introduction to “Difference” and “System” GMM in Stata. Center for Global Development. Working Paper Number 103
  • Singh, S.K.(2008).The diffusion of mobile phone in India. Telecommunications Policy. 32, 642–651.
  • Stoneman, P. (1983). The economic analysis of technological change. Oxford: Oxford University Press.
  • Trappey, C.V., & Wu, H. (2008). An evaluation of the time –varying extended logistic,simple logistic, and Gompertz models for forecasting short product life cycles. Advanced Engineering Informatics, 22, 421–430.
  • Xia, J. (2011). The third-generation-mobile (3G) policy and deployment in China: Current status, challenges, and prospects. Telecommunications Policy. 35 (2011) 51–63.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Lutfu Sagbansua

Osman Şahin Bu kişi benim

Muhterem Çöl Bu kişi benim

Yayımlanma Tarihi 30 Aralık 2015
Gönderilme Tarihi 4 Eylül 2015
Yayımlandığı Sayı Yıl 2015 Cilt 3, Sayı 2, 2015

Kaynak Göster

APA Sagbansua, L., Şahin, O., & Çöl, M. (2015). Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case. Alphanumeric Journal, 3(2), 35-40. https://doi.org/10.17093/aj.2015.3.2.5000140094

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