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