Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case
Journal Title: Alphanumeric Journal - Year 2015, Vol 3, Issue 2
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.
Authors and Affiliations
Lutfu Sagbansua, Osman Şahin, Muhterem Çöl
Keywords
Related Articles
- EP ID EP196124
- DOI 10.17093/aj.2015.3.2.5000140094
- Views 143
- Downloads 0
Productivity Change: An Empirical Study on Turkish State Universities
As it is known universities are public institutions providing educational and training services. They are also engaged with research activities. The services provided by these institutions concerns very closely both the...
Energy Saving In Continuous Annealing Line Using Heating Optimization
Energy consumption of Iron and Steel Industry sector in Turkey has the highest share in final energy consumption. In the globalized world, day by day, worsening of the conditions of competition and negative environmental...
Determining The Relationship Between Happiness And Human Development: Multivariate Statistical Approach
It has been understood that it is not enough to consider just certain macro-economic indicators to determine the development level of countries. Human Development Index (HDI), which is a part of the Human Development Rep...
Determining Strategy Based Supplier Pre-Qualification Criteria With Fuzzy Relational Maps
Supplier Selection is one of the most studied areas in management and decision sciences. However, it is still a highly problematic subject since decision-makers take an educated guess after a certain stage in real life p...
A Comparison Of Artificial Neural Networks And Multiple Linear Regression Models As Predictors Of Discard Rates In Plastic Injection Molding
In today’s global competitive environment, it is important to be able to evaluate the efficient use of a firms’ resources. The aim of this study is to predict the discard rate for headlight frames before the project of a...