Keywords
coordination network
data integration
path dependency
institutional change
How to Cite
Abstract
This study analyses how the interagency coordination network for population data integration at a provincial office changed after a non-ministerial body was elevated into a ministry and identifies the implications for coordination effectiveness. A qualitative descriptive single-case design was conducted at the Kemendukbangga/BKKBN Provincial Office of Bengkulu, Indonesia. Semi-structured interviews with three internal key informants were undertaken in April-May 2026 and triangulated with non-participant observation and institutional documents. Analysis used historical institutionalism through path dependency, gradual institutional change, and coordination effectiveness. The network relies on inherited by-name-by-address micro-data and informal trust rather than structural authority. Institutional change occurs mainly through layering and conversion, while technical, organisational, personal and incentive barriers weaken coordination. A recognition gap with external partners indicates emerging institutional drift. The study is based on preliminary fieldwork with three internal informants and therefore reflects an internal institutional perspective. The findings offer practical guidance for maintaining interagency data coordination during institutional transition. The study extends gradual institutional change theory to subnational interagency data coordination and identifies drift in institutional identity and external recognition.
References
Ansell, C., & Gash, A. (2008). Collaborative governance in theory and practice. Journal of Public Administration Research and Theory, 18(4), 543-571. https://doi.org/10.1093/jopart/mum032
Christensen, T., & Lægreid, P. (2007). The whole-of-government approach to public sector reform. Public Administration Review, 67(6), 1059-1066. https://doi.org/10.1111/j.1540-6210.2007.00797.x
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Emerson, K., Nabatchi, T., & Balogh, S. (2012). An integrative framework for collaborative governance. Journal of Public Administration Research and Theory, 22(1), 1-29. https://doi.org/10.1093/jopart/mur011
Hall, P. A., & Taylor, R. C. R. (1996). Political science and the three new institutionalisms. Political Studies, 44(5), 936-957. https://doi.org/10.1111/j.1467-9248.1996.tb00343.x
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258-268. https://doi.org/10.1080/10580530.2012.716740
Lee, J. S., & Jun, S. P. (2021). Privacy-preserving data mining for open government data from heterogeneous sources. Government Information Quarterly, 38(1), 101544. https://doi.org/10.1016/j.giq.2020.101544
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Mahoney, J., & Thelen, K. (2010). Explaining institutional change: Ambiguity, agency, and power. Cambridge University Press. https://doi.org/10.1017/CBO9780511806414
Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.06.002
Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE Publications.
Pan, W., Hosli, M. O., & Lantmeeters, M. (2023). Historical institutionalism and policy coordination: Origins of the European Semester. Evolutionary and Institutional Economics Review, 20, 371-393. https://doi.org/10.1007/s40844-023-00253-z
Pierson, P. (2000). Increasing returns, path dependence, and the study of politics. American Political Science Review, 94(2), 251-267. https://doi.org/10.2307/2586011
Provan, K. G., & Kenis, P. (2008). Modes of network governance: Structure, management, and effectiveness. Journal of Public Administration Research and Theory, 18(2), 229-252. https://doi.org/10.1093/jopart/mum015
Rahman, S., Teicher, J., Wolfram Cox, J., & Alam, Q. (2023). Slipstreaming for public sector reform: How enterprising public sector leaders navigate institutional inertia. Journal of Public Administration Research and Theory, 33(1), 4-18. https://doi.org/10.1093/jopart/muac006
Rhodes, R. A. W. (1997). Understanding governance: Policy networks, governance, reflexivity and accountability. Open University Press.
Schmeling, J., Al Dakruni, S., & Mergel, I. (2025). Data collaboration in digital government research: A literature review and research agenda. Government Information Quarterly, 42(3), 102063. https://doi.org/10.1016/j.giq.2025.102063
Streeck, W., & Thelen, K. (2005). Beyond continuity: Institutional change in advanced political economies. Oxford University Press.
Thelen, K. (2004). How institutions evolve: The political economy of skills in Germany, Britain, the United States, and Japan. Cambridge University Press. https://doi.org/10.1017/CBO9780511790997
Wahyuni, H., Mutiarin, D., Pribadi, U., & Kumorotomo, W. (2024). Maturity of data interoperability cross-organizations in supporting the concept of one employment data. Cogent Social Sciences, 10(1), 2407936. https://doi.org/10.1080/23311886.2024.2407936
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Zhou, L., Hu, J., & Xu, J. (2022). Understanding interagency relationships in the sharing of government data: A meta-analysis. Information Research, 27(2).