How to Increase E-Commerce Incomes: A Correlation and a Cluster Analysis

Abstract

Our objective in this study  to reveal the relations between  population size, e-commerce sales penetration, internet user, penetration of population with Internet, gross national income (Atlas Method), gross national income per capita, purchasing power parity gross national income, purchasing power parity gross national per income, networked readiness index and its environment,  readiness, usage, impacts indexes, global competitiveness index, logistic performance index factors and which factor(s) should be prioritized by countries in order for a country to increase its e-commerce.   In the study, e-commerce sales penetration was used as dependent variable and others were used as independent variables. Relations among variants were studied with pearson correlation analysis. According to the result of Pearson Correlation Analysis, positive strong relations were found between e-commerce sales penetration and usage, gross national income per capita, penetration of population with Internet and purchasing power parity gross national per income. Variants with effect on e-commerce were analysed by using multi linear regression analysis and e-commerce description amounts were examined in %. When these values are taken in multi linear regression model; gross national income per capita and purchasing power parity gross national income per capita were found significant in the model.  In addition, cluster analyses of 25 selected countries with different economic, social and geographic qualities with respect to these variants in order to reveal the similarity and differences of a country with other countries with respect to e-commerce structure. In cluster analyses, our analysis to differentiate one country from other countries demonstrated China and India with respect to population and e-commerce sales amounts, Norway with respect to e-trade sales penetration, Norway with respect to groups of national income per capita when divided into income groups using e-commerce sales penetration; and China and USA with respect to national income groups only. According to these results, it was found that logistic index has a lower effect than expected, that it is not sufficient merely to prepare the required infrastructure and increase number of internet users and that purchasing power should increase too and that the national income and therefore population of the country were effective. The most obvious example of that was revealed in this study as the similarities and differences between USA, China and Norway.

Keywords: E-commerce, Internet user, penetration of population with Internet, Gross National Income Atlas Method, Gross national income per capita, Purchasing power parity gross national income, Purchasing power parity gross national income per capita, Networked readiness index