Spatial Analysis of the Global Digital Divide

The global pattern of social, economic, and political influences on technology utilization is analyzed through a combinationof linear regression and spatial analysis. The conceptual framework is based on prior research findings on the global digitaldivide, including non-spatial determinants and on geographic differences. The theory posits that higher levels oftechnological utilization are based on known factors and it further provides that significant geographic differences will bepresent in world regions. The paper tests the theory by first conducting ordinary least squares (OLS) regression. For theworld, the most significant determinants are tertiary education, innovation capacity, judicial independence, and foreign directinvestment. For each regression equation, the spatial autocorrelation of the residuals are tested for significant spatialautocorrelation. After determining that geographically weighted regression cannot be applied, based on residual spatialmapping, OLS regression is performed for three world UN-defined regions and two sub-regions. Findings reveal distinctivedeterminants for these regions and sub-regions. The paper contributes insights to the global digital divide literature stemmingfrom the geospatial analysis methods

Economic and Social influences on Technology Utilization and A vailability in China, 2006 - 2009: a Regression and Spatial Analysis

China’s technology levels have grown rapidly in the first decade of the 21st century. This study examines the economic and social influences on technology utilization and availability in China’s 31 administrative units. An exploratory conceptual model is established, based on prior research and including screening for spatial clustering of like-valued residuals. The empirical research goals are (1) to statistically analyze the determinants of technology usage in China at the provincial level using the most recent technology, economic, and social data, and (2) to statistically analyze the impact of spatial autocorrelation on Chinese provincial technology levels and on regression residuals. Findings indicate the most significant determinant of China’s provincial technology levels is export commodities value, followed by published books, tertiaryand non-state-owned employment, and to a lesser extent innovation. Spatial autocorrelation isonly slightly present following the regression analysis. The implications of the study for government policies in China are examined