The Income Groups of Countries: An Approach of Management Information Systems via Networked Readiness Index

Abstract

The main aim of this study is to utilize discriminant analysis to explain the relationship between the income groups, which was determined by the World Bank for 148 countries, and the Networked Readiness Index (NRI) values calculated for the same 148 countries given in the "Global Information Technology" report 2014, which is published by the World Economic Forum since 2001. In addition, it is aimed to put forward the administrative uses necessary to increase the income levels of countries through utilization of the NRI, which is a performance analysis on the use of information technologies in a country and hence is an index that comparatively measures the level of readiness of countries to use Information and Communication Technologies (ICTs), according to the findings obtained by comparing the NRI 2013 and NRI 2014 values of these countries. In this study, July 2014 World Bank Income groups (low income, lower middle income, upper middle income, high income:Non-OECD and high income:OECD) were used as the dependent variables, and 4 main Indicators of the NRI 2014 values, and 54 sub-index values were used as independent variables. The hypothesis of this study investigates whether the income groups of each country can be predicted by the components of the NRI index correctly. For this purpose, five different Fischer discriminant analyses were carried out by using the sub-indexes of the NRI both individually and in combination to calculate the extent which these components explain the income groups, and the results were presented in tables and graphs. In addition, the data analysis was supported with ANOVA, MANOVA and Post Hoc Tukey's test. The accuracy rate was found to be 94.0% in explaining the income groups of the countries when all sub-index values of the NRI were taken into account with the help of the discriminant functions which can be formed in accordance with the findings of the study. Among these groups, it explained the most of the variance in the High income:Non-OECD - High income:OECD - Low income group (100%), and the least of the variance in the Upper middle income group (88.2%). Considering the differences between the NRI 2014 and NRI 2013, the differences in the High income:OECD, high income:Non-OECD and upper middle income groups were statistically significant. The Territorial map created by the NRI 2014 values revealed that the Upper middle income group is located at the center. Besides other few methods, the NRI is a completely effective criterion for a country in this group to rise into the high income:OECD and high income:Non-OECD groups, which are the next upper economic groups. This map also helps to determine which income group rises or falls to which income groups when they increase or decrease their NRI values. And, the NRI values that converge or diverge the countries or the NRI values common among the countries in the income groups are determined with the help of a network graph created.

Keywords: Global Information Technology Report, management, Networked Readiness Index (NRI), income group, Information and Communication Technologies (ICTs), discriminant analysis, big data