The Impact of Big Data Technology on Public Decision Making in Digital Governance: Literature Review
DOI:
https://doi.org/10.71435/Keywords:
Big Data Technology, Public Decision Making, Digital Governance, Data-Driven Policy, Institutional CapacityAbstract
Purpose: This study aims to examine and synthesize existing scholarly literature on the impact of big data technology on public decision making within the context of digital governance. It seeks to clarify how big data influences policy processes, administrative performance, and governance outcomes, while also identifying institutional and ethical conditions that shape its effectiveness.
Subjects and Methods: The study adopts an integrative qualitative literature review design guided by the PRISMA framework. Academic articles were systematically identified from Scopus, Web of Science, and Google Scholar using predefined keywords related to big data, digital governance, and public decision making. Following identification, screening, and eligibility assessment, nine peer-reviewed studies were selected for in-depth analysis. Data were analyzed using thematic analysis and cross-study synthesis to identify recurring patterns, key themes, and relational mechanisms across studies.
Results: The findings indicate that big data technology enhances evidence-based decision making by enabling predictive analytics, real-time analysis, and policy optimization. However, its impact is highly conditional, depending on mediating factors such as data quality, analytical skills, and institutional capacity. The literature also highlights significant challenges related to ethics, accountability, transparency, and unequal access to data and skills. These issues underscore the tension between data-driven efficiency and democratic governance principles.
Conclusions: Big data technology functions as an enabling but non-deterministic force in digital governance. Its contribution to public decision making depends on supportive institutions, ethical safeguards, and inclusive governance practices that align technological innovation with public values.
References
Babazadeh, A. (2025). The Role of Big Data and Intelligent Systems in Improving Public Policy Design and Evaluation in Modern Governments and Digital Societies. Advanced Journal of Management, Humanity and Social Science, 1(12), 716-724. https://doi.org/10.5281/zenodo.17930905
Barry, E., & Bannister, F. (2014). Barriers to open data release: A view from the top. Information Polity, 19(1-2), 129-152. https://doi.org/10.3233/IP-140327
Bena, Y. A., Ibrahim, R., Mahmood, J., Al-Dhaqm, A., Alshammari, A., Nasser, M., ... & Ayemowa, M. O. (2025). Big data governance challenges arising from data generated by intelligent systems technologies: a systematic literature review. IEEE Access, 13, 12859-12888. https://doi.org/10.1109/ACCESS.2025.3528941
Bertot, J. C., Gorham, U., Jaeger, P. T., Sarin, L. C., & Choi, H. (2014). Big data, open government and e-government: Issues, policies and recommendations. Information polity, 19(1-2), 5-16. https://doi.org/10.3233/IP-140328
Bibri, S. E. (2019). On the sustainability of smart and smarter cities in the era of big data: an interdisciplinary and transdisciplinary literature review. Journal of Big Data, 6(1), 25. https://doi.org/10.1186/s40537-019-0182-7
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188. https://doi.org/10.2307/41703503
Fountain, J. E. (2004). Building the virtual state: Information technology and institutional change. Rowman & Littlefield.
Fredriksson, C., Mubarak, F., Tuohimaa, M., & Zhan, M. (2017). Big data in the public sector: A systematic literature review. Scandinavian Journal of Public Administration, 21(3), 39-61. https://doi.org/10.58235/sjpa.v21i3.11563
Fredriksson, C., Mubarak, F., Tuohimaa, M., & Zhan, M. (2017). Big data in the public sector: A systematic literature review. Scandinavian Journal of Public Administration, 21(3), 39-61. https://doi.org/10.58235/sjpa.v21i3.11563
Hossin, M. A., Du, J., Mu, L., & Asante, I. O. (2023). Big data-driven public policy decisions: Transformation toward smart governance. Sage Open, 13(4), 21582440231215123. https://doi.org/10.1177/21582440231215123
Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33(3), 371-377. https://doi.org/10.1016/j.giq.2016.08.011
Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big data & society, 1(1), 2053951714528481. https://doi.org/10.1177/2053951714528481
Lăzăroiu, G., Kovacova, M., Kliestikova, J., Kubala, P., Valaskova, K., & Dengov, V. V. (2018). Data governance and automated individual decision-making in the digital privacy General Data Protection Regulation. Administratie si Management Public, (31), 132-142.
Margetts, H., & Dunleavy, P. (2013). The second wave of digital-era governance: a quasi-paradigm for government on the Web. Philosophical transactions of the royal society A: mathematical, physical and engineering sciences, 371(1987), 20120382. https://doi.org/10.1098/rsta.2012.0382
Masoudi, M. (2025). Algorithmic Governance, Data-Driven Decision Making, and the Transformation of Democratic Accountability in Contemporary States. Advanced Journal of Management, Humanity and Social Science, 2(1), 10-22. https://doi.org/10.5281/zenodo.18009536
Meijer, A. (2015). E-governance innovation: Barriers and strategies. Government information quarterly, 32(2), 198-206. https://doi.org/10.1016/j.giq.2015.01.001
Meijer, A. (2018). Datapolis: A public governance perspective on “smart cities”. Perspectives on public management and governance, 1(3), 195-206. https://doi.org/10.1093/ppmgov/gvx017
Meijer, A. J., Lips, M., & Chen, K. (2019). Open governance: A new paradigm for understanding urban governance in an information age. Frontiers in Sustainable Cities, 1, 3. https://doi.org/10.3389/frsc.2019.00003
Mir, S., & Raza, A. (2025). Big Data and Public Policy: Shaping Decision-Making in the 21st Century. International Journal of Multidisciplinary Research, 3(02), 52-59.
Olszak, C. M., & Mach-Król, M. (2018). A conceptual framework for assessing an organization’s readiness to adopt big data. Sustainability, 10(10), 3734. https://doi.org/10.3390/su10103734
Raj, M. S., Kaulwar, P. K., Raja, P. S., Pokhriyal, S., Ponnusamy, S., & Ramani, G. G. (2025, May). Future Proof Civic Participation Platforms with Behavioral Insight Driven Policy Making Artificial Intelligence and Big Data Analytics. In International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024) (pp. 648-660). Atlantis Press. https://doi.org/10.2991/978-94-6463-718-2_56
Rayner, S. (2003). Democracy in the age of assessment: reflections on the roles of expertise and democracy in public-sector decision making. Science and public policy, 30(3), 163-170. https://doi.org/10.3152/147154303781780533
Song, M., Cen, L., Zheng, Z., Fisher, R., Liang, X., Wang, Y., & Huisingh, D. (2017). How would big data support societal development and environmental sustainability? Insights and practices. Journal of Cleaner Production, 142, 489-500. https://doi.org/10.1016/j.jclepro.2016.10.091
Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government information quarterly, 36(2), 368-383. https://doi.org/10.1016/j.giq.2018.09.008
Zuiderwijk, A., Janssen, M., & Dwivedi, Y. K. (2015). Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology. Government information quarterly, 32(4), 429-440. https://doi.org/10.1016/j.giq.2015.09.005
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Asian Digital Governance Problems

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
