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Journals / Alphanumeric Journal / 2015 / Cilt 3, Sayı 2, 2015

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

Yeni Geniş Bant Adaptasyonunu Tahminlemede Mobil Penetrasyonun Belirleyicileri: OECD Örneği

Lutfu SAGBANSUA
Osman ŞAHİN
Muhterem ÇÖL
Pages
35–40
Publication Date
2015-12-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The obtained results can be used to forecast adoption of New Broadband Penetration technology.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper aims to analyze relationship between Mobile penetration and various indicators of communication infrastructure throughout OECD countries.
📊
Key Findings & Data:In particular, this paper attempts to identify what are the factors to promote the 3G mobile phone by using dynamic panel data analysis.
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Conclusion & Impact:The obtained results can be used to forecast adoption of New Broadband Penetration technology.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

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.

Özet

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.

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Cite This Article

SAGBANSUA, L., ŞAHİN, O., ÇÖL, M. (2015). Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case. Alphanumeric Journal, Cilt 3, Sayı 2, 2015, 35–40. https://ajindex.com/articles/63608

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