Track

Business Intelligence and Knowledge Management

Abstract

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.

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