Leveraging Big Data Analytics Capability for Enhancing Organisational Performance in Government Organisations: A study in the United Arab Emirates

Abstract

This comprehensive study investigates the pivotal role of Big Data Analytics Capability (BDAC) in augmenting Organisational Performance (OP) within government organisations in the United Arab Emirates (UAE). To understand the business value of BDAC, this research integrates two intersecting theories: Information Technology (IT) mediation, and Dynamic Capabilities (DCs).

In a largely unexplored domain, this research endeavours to provide clarity and well-structured frameworks for comprehending how BDAC can elevate government performance within the emerging market economy of the UAE. As existing research predominantly focuses on the private sector, this study responds to emerging scholarly calls to examine BDAC's effect through an organisational lens, emphasizing the roles of Organisational Learning (OL) and Decision-Making
(DM) capabilities in supporting and amplifying BDAC's role in enhancing OP. Additionally, this research advocates the adaptation of DCs concepts, already prominent in the private sector, within government entities to enable the renewal, reconfiguration, and adaptation of organisational capabilities to accommodate technological changes.

Hence, the primary objective of this research is to contribute to the Information Systems (IS) and BDAC literature by addressing the following research questions:
1. How does big data analytics capability result in enhanced organisational performance in
the government sector?
2. How do organisational learning and decision-making capabilities affect the relationship
between big data analytics capability and organisational performance?
3. How do dynamic capabilities influence the effect of big data analytics capability on
organisational performance?

The study adopts a quantitative approach, collecting data from 120 government organisations in the UAE through online questionnaires. Data analysis is conducted utilizing the Partial Least Squares Structural Equation Modeling (PLS-SEM) method.

The study found that BDAC enhances OP in the government sector indirectly via organisational and dynamic capabilities. Hence, the study confirmed that the relationship between BDAC and OP is mediated by OL and DM capabilities as well as DCs. The study further confirmed the relevance of applying dynamic capabilities in the government sector as a mechanism to manage strategic changes and thus enhance performance.

This research significantly enriches IS literature with the understanding of how BDAC can meaningfully enhance government sector performance. It contributes by defining key concepts, identifying relevant variables, and offering empirical insights from an interdisciplinary perspective to better comprehend BDAC adoption in the government sector. Moreover, this study stands as one of the pioneering empirical works to introduce the concept of dynamic capabilities within the
government sector, and further creates five robust constructs unique to the government context: BDAC, OL, DM, DCs, and OP.

The implications of these findings are discussed for future academic research and practical applications, providing valuable guidance for managers striving to maximize value from BDAC applications in the government sector.

Date of Award	1 Jun 2024
Original language	English
Awarding Institution	King's College London
Supervisor	Wei Liu (Supervisor) & Crawford Spence (Supervisor)