Governing By Data: A Critical Analysis Of Big Data’s Role In Urban Public Policy And Social Stratification In Southeast Asian Megacities
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Background. The rapid expansion of big data infrastructures in Southeast Asian megacities has reshaped the formulation and implementation of urban public policy, raising concerns about algorithmic governance and emerging forms of social stratification. Urban administrations increasingly rely on predictive analytics, biometric systems, and real-time surveillance tools to guide decision-making, yet the socio-political implications of these technologies remain insufficiently understood.
Purpose. This study aims to critically examine how big data systems influence policy priorities, resource allocation, and the lived experiences of marginalized urban communities.
Method. . A qualitative research design was employed, combining policy document analysis, expert interviews, and digital ethnography across three major Southeast Asian cities.
Results. The findings reveal that big data governance enhances administrative efficiency but simultaneously reinforces structural inequalities through opaque categorization practices, risk scoring models, and selective visibility regimes. These mechanisms privilege affluent districts while amplifying precarity in low-income urban populations.
Conclusion. The study concludes that big data functions as both a technocratic tool and a political instrument, producing uneven urban outcomes shaped by existing socio-economic hierarchies. The results underscore the need for transparent data governance frameworks and equity-oriented urban policy reforms.
Alka, T. A., Sreenivasan, A., & Suresh, M. (2024). Wheel of change: A systematic literature review on innovation and entrepreneurship in micro mobility solutions. Transport Economics and Management, 2, 154–168. https://doi.org/10.1016/j.team.2024.06.004
Boussaa, D., & Madandola, M. (2024). Cultural heritage tourism and urban regeneration: The case of Fez Medina in Morocco. Frontiers of Architectural Research, 13(6), 1228–1248. https://doi.org/10.1016/j.foar.2024.04.008
Cuervo, L. G., Villamizar, C. J., Osorio, L., Ospina, M. B., Cuervo, D. E., Cuervo, D., Bula, M. O., Zapata, P., Owens, N. J., Hatcher-Roberts, J., Martín, E. A., Piquero, F., Pinilla, L. F., Martínez-Herrera, E., & Jaramillo, C. (2024). Dynamic measurements of geographical accessibility considering traffic congestion using open data: A cross-sectional assessment for haemodialysis services in Cali, Colombia. The Lancet Regional Health - Americas, 34, 100752. https://doi.org/10.1016/j.lana.2024.100752
Dwivedi, Y. K., Jeyaraj, A., Hughes, L., Davies, G. H., Ahuja, M., Albashrawi, M. A., Al-Busaidi, A. S., Al-Sharhan, S., Al-Sulaiti, K. I., Altinay, L., Amalaya, S., Archak, S., Ballestar, M. T., Bhagwat, S. A., Bharadwaj, A., Bhushan, A., Bose, I., Budhwar, P., Bunker, D., … Walton, P. (2024). “Real impact”: Challenges and opportunities in bridging the gap between research and practice – Making a difference in industry, policy, and society. International Journal of Information Management, 78, 102750. https://doi.org/10.1016/j.ijinfomgt.2023.102750
Em, P. P., & Sheludkov, A. V. (2024). The fluctuating mosaic of socio-spatial inequalities in central Pyongyang under the pressures of marketization. Habitat International, 150, 103135. https://doi.org/10.1016/j.habitatint.2024.103135
Esquivel García, C. L., & Toro-García, G. L. (2024). Multidimensional energy poverty in Colombia: A department-level review from 2018 to 2022. Heliyon, 10(14), e34395. https://doi.org/10.1016/j.heliyon.2024.e34395
Glavovic, B. (2024). 7.18—Governance Experiences and Prospects in Estuarine and Coastal Communities. Dalam D. Baird & M. Elliott (Ed.), Treatise on Estuarine and Coastal Science (Second Edition) (hlm. 411–447). Academic Press. https://doi.org/10.1016/B978-0-323-90798-9.00129-3
Helen, N., & Ellisa, E. (2024). Investigating the knowledge commons practice in high-density low-income residential urban Kampung during COVID-19 pandemic. Cities, 148, 104901. https://doi.org/10.1016/j.cities.2024.104901
Heley, J., Sanders, A., Caerwynt, F., Zaidi, N., & Power, S. (2024). The royal Welsh agricultural society: Patronage and the reproduction of elites in rural Wales. Journal of Rural Studies, 108, 103291. https://doi.org/10.1016/j.jrurstud.2024.103291
Karyamsetty, H. J., Khan, S. A., & Nayyar, A. (2024). Chapter 9—Envisioning toward modernization of society 5.0—A prospective glimpse on status, opportunities, and challenges with XAI. Dalam F. Al-Turjman, A. Nayyar, M. Naved, A. K. Singh, & M. Bilal (Ed.), XAI Based Intelligent Systems for Society 5.0 (hlm. 223–267). Elsevier. https://doi.org/10.1016/B978-0-323-95315-3.00005-X
Lay Maw, T. T., & Seo, D. (2024). Historical geographies of grid city development: Mandalay from Burma to Myanmar. Journal of Historical Geography, 86, 133–148. https://doi.org/10.1016/j.jhg.2024.07.005
Li, H., Liu, Y., & Lu, Z. (2024). Can digital factor participation create opportunities for “rags to riches”? Based on the perspective of intergenerational income mobility. International Review of Economics & Finance, 96, 103708. https://doi.org/10.1016/j.iref.2024.103708
Li, J., & Huang, Q. (2024). Navigating Ethical Dilemmas in AI-Enhanced Education: International Journal of Knowledge Management, 21(1). https://doi.org/10.4018/IJKM.382384
Li, Y., Zhu, P., Mlecnik, E., Qian, Q. K., & Visscher, H. J. (2024). Dissemination, manipulation or monopolization? Understanding the influence of stakeholder information sharing on resident participation in neighborhood rehabilitation of urban China. Land Use Policy, 147, 107359. https://doi.org/10.1016/j.landusepol.2024.107359
Liu, X., Pei, T., Wang, X., Liu, T., Fang, Z., Jiang, L., Jiang, J., Yan, X., Wu, M., Peng, Y., Ge, D., Gao, X., Song, C., & Chen, J. (2024). Travel flow patterns of diverse population groups and influencing built environment factors: A case study of Beijing. Cities, 151, 105096. https://doi.org/10.1016/j.cities.2024.105096
Mazorra Rodríguez, Á. (2024). Social inequality and residential segregation trends in Spanish global cities. A comparative analysis of Madrid, Barcelona, and Valencia (2001-2021). Cities, 149, 104935. https://doi.org/10.1016/j.cities.2024.104935
Mohamad, U. H. (2025). Chapter 6—Comparative analysis of AI and nanotech approaches for pandemic prediction. Dalam A. Ahmadian, F. Ghaemi, A. K. Yadav, M. J. Ebadi, & S. Salahshour (Ed.), The Prediction of Future Pandemics (hlm. 69–104). Elsevier. https://doi.org/10.1016/B978-0-443-33871-7.00006-4
Monlezun, D. J. (2024). 1—Power and artificial intelligence: Transformation of the global public health ecosystem. Dalam D. J. Monlezun (Ed.), Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem (hlm. 1–65). Morgan Kaufmann. https://doi.org/10.1016/B978-0-443-21597-1.00001-9
Monlezun, D. J. (2025). Chapter 5—Quantum AI for public health. Dalam D. J. Monlezun (Ed.), Quantum Health AI (hlm. 125–154). Academic Press. https://doi.org/10.1016/B978-0-443-33353-8.00003-5
Musarat, M. A., Alaloul, W. S., Khan, M. H. F., Ayub, S., & Guy, C. P. L. (2024). Evaluating cloud computing in construction projects to avoid project delay. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), 100296. https://doi.org/10.1016/j.joitmc.2024.100296
Noor, F., Saleem, M. A. U., Rafique, A., Danish, M. A. U., Bano, F., Shehzad, M. S. U., Noor, A., Fatima, I., Kamal, M. A., Muzammil, A., & Rehman, A. (2026). Chapter 13—Computational tools and techniques for disease modeling: Bridging the gap. Dalam S. N. Rai, S. K. Singh, & V. Singh (Ed.), Advancements in Modeling-Based Therapeutics and Technology for Chronic Diseases (hlm. 373–418). Academic Press. https://doi.org/10.1016/B978-0-443-33877-9.00017-3
Ojah, K., & Kodongo, O. (2024). Effective financial inclusion and the need to put the horse before the cart: Saving! International Review of Financial Analysis, 96, 103737. https://doi.org/10.1016/j.irfa.2024.103737
O’Meara, L., Sison, C., Isarabhakdi, P., Turner, C., & Harris, J. (2024). ‘Whatever we have is what we eat’: How marginalised urban populations in the Philippines and Thailand experienced their food environments, food security and diets through COVID-19. Health & Place, 88, 103279. https://doi.org/10.1016/j.healthplace.2024.103279
Ong, J. C. L., Seng, B. J. J., Law, J. Z. F., Low, L. L., Kwa, A. L. H., Giacomini, K. M., & Ting, D. S. W. (2024). Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions. Cell Reports Medicine, 5(1), 101356. https://doi.org/10.1016/j.xcrm.2023.101356
Santra, D. (2025). Artificial intelligence in urban health epidemic management. Dalam Advances in Computers. Elsevier. https://doi.org/10.1016/bs.adcom.2025.10.001
Schmid, F. B., Hersperger, A. M., Grêt-Regamey, A., & Kienast, F. (2024). Effects of different land-use planning instruments on urban shrub and tree canopy cover in Zurich, Switzerland. Urban Forestry & Urban Greening, 94, 128272. https://doi.org/10.1016/j.ufug.2024.128272
Sha, K., Taeihagh, A., & De Jong, M. (2024). Governing disruptive technologies for inclusive development in cities: A systematic literature review. Technological Forecasting and Social Change, 203, 123382. https://doi.org/10.1016/j.techfore.2024.123382
Soltani, A., & Lee, C. L. (2024). The non-linear dynamics of South Australian regional housing markets: A machine learning approach. Applied Geography, 166, 103248. https://doi.org/10.1016/j.apgeog.2024.103248
Thakur, R., Baghel, M., Bhoj, S., Jamwal, S., Chandratre, G. A., Vishaal, M., Badgujar, P. C., Pandey, H. O., & Tarafdar, A. (2024). CHAPTER 8—Digitalization of livestock farms through blockchain, big data, artificial intelligence, and Internet of Things?. Dalam A. Tarafdar, A. Pandey, G. K. Gaur, M. Singh, & H. O. Pandey (Ed.), Engineering Applications in Livestock Production (hlm. 179–206). Academic Press. https://doi.org/10.1016/B978-0-323-98385-3.00012-8
Timilsina, R. R., Jena, P. R., Rahut, D. B., & Managi, S. (2024). Towards parity: Examining the closing gender gap on electricity access in India using data from 1998 to 2021. Energy for Sustainable Development, 80, 101450. https://doi.org/10.1016/j.esd.2024.101450
Villar, E., Francke, P., & Loewenson, R. (2024). Learning from Perú: Why a macroeconomic star failed tragically and unequally on Covid-19 outcomes. SSM - Health Systems, 2, 100007. https://doi.org/10.1016/j.ssmhs.2023.100007
Wang, L., & Hamid, M. O. (2024). The transformation of neoliberalism: A critical analysis of shadow education governance policy in China. International Journal of Educational Research, 127, 102422. https://doi.org/10.1016/j.ijer.2024.102422
Wang, W. W. (2024). Contextualizing Personal Information: Privacy’s Post-Neoliberal Constitutionalism and Its Heterogeneous Imperfections in China. Computer Law & Security Review, 55, 106030. https://doi.org/10.1016/j.clsr.2024.106030
Wang, Z., Hu, T., Liu, J., Xia, B., & Chileshe, N. (2024). Spatial differences, evolutionary characteristics and driving factors on economic resilience of the construction industry: Evidence from China. Engineering, Construction and Architectural Management, 32(10), 6888–6916. https://doi.org/10.1108/ECAM-01-2024-0021
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