Improving organizational performance through Big Data analytics and information management capability

The Big Data phenomenon has gained increasing attention in the digital age, thus representing a strategic opportunity for managerial decision-making and organizational performance. Scholars are interpreting Big Data Analytics (BDA) as one of the most innovative technologies able to collect and analyze relevant information resources from companies’ stakeholders and markets. As a result, the use of BDA in strategic planning and decision-making is becoming crucial for managers to address rapidly changing environments and gain sustainable competitive advantage. Despite this growing attention, the literature is still limited in exploring the underlying mechanisms between the implementation of BDA and organizations’ performance. Moreover, the individual and organizational dimensions involved in such value creation processes have been largely neglected. To address these gaps, the present study builds on the process- oriented dynamic capabilities view to propose a conceptual model that aims to unpack the BDA-performance linkage. First, BDA capabilities – the micro dimension – and Big Data organizational diffusion process – the meso dimension – are hypothesized as antecedents of organizational performance. Next, information management capability is hypothesized as the mediating variable of such a relationship. The model is empirically tested on a sample of 311 respondents – data analysts, data scientists, data managers, and chief data officers – working in Italian Big Data organizations. Confirmatory factor analysis (CFA) and bootstrapped mediation analysis are used to validate the model and test the hypotheses. The results show the important role of BDA in enhancing organizations’ performance. Interestingly, information management capability resulted as a significant mediating variable of the BDA-performance relationship. Theoretical and practical implications to Big Data academics and practitioners are provided, along with suggestions for future research.