Adoption of Big Data Analytics and Banks’ Performance: The Moderating Role of Analytics Capability
Abstract/Description
Purpose: Big Data Analytics emerged as a tool for revolutionizing data-driven decision-making in the financial industry. This study aims to investigate the factors that influence the implementation of big data analytics. The mediating role of adoption of big data analytics and its effect on bank performance in the context of Pakistani banks. The study fills the gap by taking into consideration analytics capability and bank strategy alignment as the moderator.
Design/methodology/approach: The study uses a quantitative research approach by collecting primary data from managers of both public and private sector banks of Pakistan through a structured questionnaire. The study uses SPSS software for the data analysis. The hypotheses are tested through regression analysis, and mediation and moderation results are determined through Model 14 of Preacher and Hayes PROCESS macro.
Findings: The results reveal that all three factors i.e. technological, organizational, and environmental influence the adoption of big data analytics which in turn positively influences the performance of the banks. Moreover, the adoption of big data analytics mediates the relationship between all three factors and bank performance. However, analytics capability and bank strategy alignment do not act as a moderator.
Practical implications: This research helps policy-makers of the banks in better understanding the need to align the banks’ analytics capability and strategy, which is currently lacking in the system of the banks.
Originality/value: The study is the first empirical study to investigate the moderating role of analytics capability and bank strategy alignment.
Keywords
Big data, Bank performance, Big data analytics, TOE model, Organizational factors, Technological factors, Environmental factors, Analytics capability-bank strategy alignment
Track
Management
Session Number/Theme
4B: Management
Session Chair
Dr. Usman Nazir ; Mrs. Kanza Sohail
Start Date/Time
31-5-2024 9:00 AM
End Date/Time
31-5-2024 10:30 AM
Location
MCS – 4 AMAN CED Building
Recommended Citation
Fatima, M., & Ayub, H. (2024). Adoption of Big Data Analytics and Banks’ Performance: The Moderating Role of Analytics Capability. 3rd IBA SBS International Conference 2024. Retrieved from https://ir.iba.edu.pk/sbsic/2024/program/49
COinS
Adoption of Big Data Analytics and Banks’ Performance: The Moderating Role of Analytics Capability
MCS – 4 AMAN CED Building
Purpose: Big Data Analytics emerged as a tool for revolutionizing data-driven decision-making in the financial industry. This study aims to investigate the factors that influence the implementation of big data analytics. The mediating role of adoption of big data analytics and its effect on bank performance in the context of Pakistani banks. The study fills the gap by taking into consideration analytics capability and bank strategy alignment as the moderator.
Design/methodology/approach: The study uses a quantitative research approach by collecting primary data from managers of both public and private sector banks of Pakistan through a structured questionnaire. The study uses SPSS software for the data analysis. The hypotheses are tested through regression analysis, and mediation and moderation results are determined through Model 14 of Preacher and Hayes PROCESS macro.
Findings: The results reveal that all three factors i.e. technological, organizational, and environmental influence the adoption of big data analytics which in turn positively influences the performance of the banks. Moreover, the adoption of big data analytics mediates the relationship between all three factors and bank performance. However, analytics capability and bank strategy alignment do not act as a moderator.
Practical implications: This research helps policy-makers of the banks in better understanding the need to align the banks’ analytics capability and strategy, which is currently lacking in the system of the banks.
Originality/value: The study is the first empirical study to investigate the moderating role of analytics capability and bank strategy alignment.
