Abstract

Organisations have been increasingly adopting decision support and business intelligence (BI). However, there is still considerable academic interest in comprehending the factors that influence the decisions to embrace such technologies. Moreover, the use of BI in developing countries, like Jordan, is remain at an early stage. This study examines the factors that impact the adoption of BI in the banking sector. This research also examines at the impact of BI adoption on decision-making performance in Jordan commerce banks. A conceptual framework was formulated as an extension of the Technology-Organization-Environment (TOE) framework to determine how technological, organizational and environmental factors influence the adoption of business intelligence (BI) in the banking sector. An empirical analysis was conducted with a sample of employees working for Jordanian commercial banks. Hypotheses were analysed through partial least squares structural equation modeling (PLS-SEM) using 251 responses that were obtained from respondents using an administered a questionnaire. The outcomes display a significant positive relationship between the TOE factors and the adoption of BI, which emphasizes their criticality as far as shaping BI adoption in commercial banks is concerned. However, it could be noted that organisational readiness related to one of the organisation’s factors has not been found to affect BI adoption. This suggests that further scrutiny is required on specific organisational aspects that can impact on BI adoption in banking environments. Moreover, the study revealed that the adoption of BI greatly improves decision-making performance. These findings highlight the importance of the Jordanian banking sector embracing a complete approach that incorporates cutting-edge technology solutions, a conducive organisational culture, and adaptability in order to maximise the adoption and use of BI. This report provides significant insights for banks aiming to improve their adoption of BI and perform informed and data based decisions in the continually evolving banking sector. The study provides numerous theoretical and practical contributions, acknowledges its limitations, and offers possibilities for future research.

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