The impact of business intelligence and organizational foresight on performance management in UAE's public sector

• Main Author: Al Hindaassi, Mohamed Obaid Jemei
• Format: Thesis
• Language: English; English; English
• Published: 2025
• Subjects: HF5001-6182 Business
• Online Access: https://etd.uum.edu.my/12008/1/Depositpermission-Embargo%202years_s904738.pdf; https://etd.uum.edu.my/12008/2/s904738_01.pdf; https://etd.uum.edu.my/12008/3/s904738_02.pdf; https://etd.uum.edu.my/12008/

This study examines the impact of business intelligence and analytics (BIA) on performance management (PM), performance management systems (PMS), and organizational foresight (OF) within the UAE public sector, with a particular focus on the Federal Authority for Government Human Resources (FAHR). This study investigates the interplay between these four variables, where BIA (independent variable) is assessed through technical infrastructure quality, management capability, and personnel expertise. Organizational foresight (environmental scanning and strategic selection) serves as a mediator influencing PMS, which encompasses developing and planning, managing, reviewing, and rewarding. Additionally, PMS itself plays a mediating role between BIA and PM, which is characterized by mission clarity, framework effectiveness, and control mechanisms. While PMS is a fundamental component of performance management, PM extends beyond the system, covering broader organizational activities related to performance enhancement. The UAE's heavy involvement in technology use, particularly in the government sector, provides a relevant empirical environment for this research. Besides, in the UAE context, no such studies performed before to provide empirical feedback to the UAE decision-makers. Two theories contribute to this study, Resource-Based View (RBV) theory, and Dynamic Capabilities theory. The study uses quantitative methods and depends upon primary data. The population of this research is all employees from operational management, supervisors, operational managers, and departmental managers of the FAHR in the UAE. The total number of employees in all department and in the seven states are approximately 3750, and the suitable sample size based on Morgan and Kerjice formula is 489. The data are collected from the eight locationbased groups based on the employees’ population and the technique used for selecting samples is quota sampling. The data was collected online by using a well-structured questionnaire that is adapted from previous studies. The findings indicate that BIA has a significant positive impact on both OF and PMS, reinforcing the role of data-driven decision-making in enhancing organizational foresight and performance systems. Additionally, PMS mediates the relationship between BIA and PM, highlighting the importance of structured performance management systems in optimizing business intelligence for improved organizational performance.