Big Data Analytics and Culture

Abstract

The existing big data analytics measures were developed without considering the cultural dimensions of developing countries. This research aims to develop and validate measures for big data Vs and cultural big data analytics and study their impacts on the developing countries' big data value proposition. Following MacKenzie's and Shiau and Huang's scale development procedures, data was collected twice from individuals in a developing country to refine the scale and reexamine its properties. PLS methods were used to study the impacts of big data Vs and cultural big data analytics on the value proposition. The findings revealed that big data analytics snobbism and conformism positively impact big data value proposition. Similarly, big data volume, velocity, and variety positively impact the value proposition. Paradoxically, big data veracity and variability do not significantly affect the value proposition. Surprisingly, big data analytics fatalism negatively impacts the value proposition. Theoretical and practical contributions were offered.