Analyzing big data capabilities, absorptive capacity and competitive performance in Jordanian commercial banks

Purpose This study aims to examine how absorptive capacity (AC) mediates the relationship between big data capabilities (BDCs) and competitive performance (CP). It also tests how BDCs affect AC and CP in the case of Jordanian commercial banks. Design/methodology/approach Drawing on a conceptual model and cross-sectional research design, self-administered questionnaires were used to collect quantitative research data from 360 managers in the Jordanian banking sector. Path analysis was performed using structural equation modeling. Findings This empirical study provides evidence that AC substantially mediates the relationship between BDCs and CP and that potential absorptive capacity (PAC) significantly impacts realized AC. Research limitations/implications This study offers insights into BDCs. It adds value to how BDCs foster AC and enhance CP. The cross-sectional research design affects the generalization of the findings. Practical implications The findings guide bank managers in managing BDCs and offer policymakers perspectives on enhancing CP. Social implications BDCs and AC in Jordanian banks can improve financial inclusion by tailoring services to target customers and enhancing customer service through data analysis. Additionally, these capabilities contribute to the economic growth and stability of the country by optimizing risk assessment, creating new jobs and developing specialized skills within the workforce. Originality/value This study developed an empirical model to examine the relationship between BDCs, AC and CP. It offers a novel addition to the big data literature on the crucial interplay between BDCs, PAC, realized absorptive capacity and CP.