The influence of the practices of big data analytics applications on bank performance: filed study

Abstract

Purpose This paper aims to examine factors influencing the practices of big data analytics applications by commercial banks operating in Jordan and their bank performance. Design/methodology/approach A conceptual framework was developed in this regard based on a comprehensive literature review and the Technology–Environment–Organization (TOE) model. A quantitative approach was used, and the data was collected from 235 commercial banks’ senior and middle managers (IT, financial and marketers) using both online and paper-based questionnaires. Findings The results showed that the extent of the practices of big data analytics applications by commercial banks operating in Jordan is considered to be moderate (i.e. 60%). The results indicated that 61% of the variation on the practices of big data analytics applications by commercial banks could be predicated by TOE model. The organizational factors were found the most important predictors. The results also provide empirical evidence that the extent of practices of big data analytics applications has a positive influence on the bank performance. In the final section, research implications and future directions are presented. Originality/value This paper contributes to theory by filling a gap in the literature regarding the extent of the practices of big data analytics applications by commercial banks operating in developing countries, such as Jordan. It empirically examines the impact of the practices of big data analytics applications on bank performance.