Document Type : Original Article
Authors
1 Assistant Professor, Department of Information Technology, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran
2 Assistant Professor, Information Technology Research Faculty, ICT Research Institute, Tehran, Iran
3 PhD of Electrical Engineering, Communication Technology Research Faculty, ICT Research Institute, Tehran, Iran
4 MSc. of Computer Engineering, Communication Technology Research Faculty, ICT Research Institute, Tehran, Iran
Abstract
The information and communication technology (ICT) industry is the driving force of the development of countries. Especially, the importance of this industry has been increased when, countries are moving towards economics and digital transformation. On the other hand, the ICT regulatory as a policy-making body in the field of ICT has a significant role in the ICT situation of that country. It would be very effective if a country's ICT regulator could adopt its policies in a way that would lead to the development of that country's ICT as well. In this article, we want to create a synergy between the ICT development and ICT regulatory policies of a country, we examined the relationship between the types of ICT development indicators of countries and their ICT regulatory improvement indicators. In this regard, by using analytical and statistical tools, 63 randomly selected countries are investigated and a meaningful correlation between sub-indices of these two domains is extracted. According to the results, the size, power and authority of a national regulatory body has no meaningful relation with the development status of the ICT industry in the country. On the contrary, the quality of regulatory services and establishment of a healthy competitive environment for cooperation and competition between actors (regulatory maturity) in a country are strongly linked to the development of its ICT industry. The results obtained in this paper are analyzed using Kolmogorov-Smirnoff and Shapiro-Wilk tests, Pearson correlation coefficient, t-student distribution test with n-2 degree of freedom, t-distribution table, covariance and linear regression. The results and conclusions can be applied to all countries with a confidence level of 95%.
Keywords