Intelligence as an Innovation in Public Management: Premises for Institutionalization
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Abstract
Objective: Intelligence in public management is recognized as an innovative approach that leverages technologies to enhance decision-making processes and facilitate democratic planning by establishing formal structures, engaging public servants and managers, and fostering social involvement for efficient data and information management. Despite its innovative potential, intelligence in public management requires legitimacy within government spheres. The objective of this study is to validate a model for the institutionalization of intelligence in public management, grounded in a theoretical framework encompassing ten dimensions of intelligence categorized into organizational structure, technological infrastructure, human capital, and social engagement. Methods: Employing quantitative research, data were collected through a survey conducted among managers and civil servants in the Brazilian context. Results: The results demonstrate a positive impact of the analyzed categories on the institutionalization of intelligence in public management, with human capital emerging as the most influential factor. Conclusions: This study underscores the significance of adopting an institutional perspective in structuring intelligence processes within public management, thereby offering avenues for theoretical advancement in the field and suggesting pathways toward establishing legitimacy for intelligence activities within government frameworks.
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Melati, C., & Janissek-Muniz, R. (2024). Intelligence as an Innovation in Public Management: Premises for Institutionalization. Brazilian Administration Review, 21(2), e230067. https://doi.org/10.1590/1807-7692bar2024230067
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References
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Chatfield, A. T., & Reddick, C. G. (2019). A framework for Internet of Thingsenabled smart government: A case of IoT cybersecurity policies and use cases in the US federal government. Government Information Quarterly, 36(2), 346- 357. https://doi.org/10.1016/j.giq.2018.09.007
Chen, S., Miau, S., & Wu, C. (2014). Toward a smart government: An experience of e-invoice development in Taiwan. Proceedings of the Pacific Asia Conference on Information Systems.
Chiusoli, C. L., & Rezende, D. A. (2019). Sistema de informações municipais como apoio à tomada de decisões dos cidadãos. NAVUS-Revista de Gestão e Tecnologia, 9(3), 124-142. https://doi.org/10.22279/navus.2019.v9n3.p124-142.893
Choi, Y., Gil-Garcia, J., Burke, G. B., Costello, J., Werthmuller, D., & Aranay, O. (2021). Towards data-driven decision-making in government: Identifying opportunities and challenges for data use and analytics. Proceedings of the 54th Hawaii International Conference on System Sciences, United States.
Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: The role of espoused cultural values and perceived risk. Behaviour & Information Technology, 38(1), 42-64. https://doi.org/10.1080/0144929X.2018.1513563
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Psychology Press.
Criado, J. I., & Gil-Garcia, J. R. (2019). Creating public value through smart technologies and strategies: From digital services to artificial intelligence and beyond. International Journal of Public Sector Management, 32(5), 438-450. https://doi.org/10.1108/IJPSM-07-2019-0178
DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147-160. https://doi.org/10.2307/2095101 DiMaggio, P. J., & Powell, W. W. (1991). Introduction. In W. W Powell & P. J. DiMaggio (Eds.), The new institutionalism in organizational analysis (pp. 1-40). University of Chicago Press.
Eom, S. J., Choi, N., & Sung, W. (2016). The use of smart work in government: Empirical analysis of Korean experiences. Government Information Quarterly, 33(3), 562-571. https://doi.org/10.1016/j.giq.2016.01.005
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
Gartner. (2021). Gartner identifies top 10 government technology trends for 2021. https://www.gartner.com/en/newsroom/press-releases/2021-03-29-gartner-identifies-top-10-government-technology-trend.
Guenduez, A. A., Singler, S., Tomczak, T., Schedler, K., & Oberli, M. (2018). Smart government success factors. Yearbook of Swiss Administrative Sciences, 9(1), 96-110. https://doi.org/10.5334/ssas.124
Gil-Garcia, J. R., Helbig, N., & Ojo, A. (2014). Being smart: Emerging technologies and innovation in the public sector. Government Information Quarterly, 31, I1-I8. https://doi.org/10.1016/j.giq.2014.09.001
Gil-Garcia, J. R., Pardo, T. A., & Aldama-Nalda, A. (2013). Smart cities and smart governments: Using information technologies to address urban challenges. In Proceedings of the 14th Annual International Conference on Digital Government Research (pp. 296-297), Quebec, Canada.
Gil-Garcia, J. R., Zhang, J., & Puron-Cid, G. (2016). Conceptualizing smartness in government: An integrative and multi-dimensional view. Government Information Quarterly, 33(3), 524-534. https://doi.org/10.1016/j.giq.2016.03.002
Hair, J. F., Jr., Anderson, R. O., & Tatham, R. (1987). Multidimensional data analysis. Macmillan.
Hair, J. F., Jr., Babin, B., Money, A., & Samouel, P. (2005). Fundamentos de métodos de pesquisa em administração. Bookman.
Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis: Pearson new international edition. Pearson Education Limited.
Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage.
Hair, J. F., Jr., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139- 152. https://doi.org/10.2753/MTP1069-6679190202
Hair, J. F., Jr., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi.org/10.1108/EBR-10-2013-0128
Halaweh, M. (2018). Artificial Intelligence Government (Gov. 3.0): The UAE Leading Model. Journal of Artificial Intelligence Research, 62, 269-272. https://doi.org/10.1613/jair.1.11210
Harrison, T. M., & Luna-Reyes, L. F. (2020). Cultivating trustworthy artificial intelligence in digital government. Social Science Computer Review, 40(2) 494- 511. https://doi.org/10.1177/0894439320980122
Hidayat, T., & Kurniawan, N. B. (2017). Smart city service system engineering based on microservices architecture: Case study: Government of tangerang city. In Proceedings of ICT For Smart Society (ICISS).
Hujran, O., Alsuwaidi, M., Alarabiat, A., & Al-Debei, M. (2021). Embracing smart government during the COVID-19 pandemic: Evidence from the United Arab Emirates. In Proceedings of 25 Pacific Asia Conference on Information Systems, Dubai.
Johnston, E. W., & Hansen, D. L. (2011). Design lessons for smart governance infrastructures. Transforming American governance. In E. W. Johnston, & D. L. Hansen, Transforming American Governance: Rebooting the Public Square (pp. 197-212). Routledge.
Juniawan, M. A., Sandhyaduhita, P., Purwandari, B., Yudhoatmojo, S. B., & Dewi, M. A. A. (2017). Smart government assessment using Scottish Smart City Maturity Model: A case study of Depok city. In Proceedings of the 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS), Bali, Indonésia.
Kankanhalli, A., Charalabidis, Y., & Mellouli, S. (2019). IoT and AI for smart government: A research agenda. Government Information Quarterly, 36(2), 304-209. https://doi.org/10.1016/j.giq.2019.02.003
Kim, S., Andersen, K. N., & Lee, J. (2022). Platform government in the era of smart technology. Public Administration Review, 82(2), 362- 368. https://doi.org/10.1111/puar.13422
Koufteros, X. A. (1999). Testing a model of pull production: A paradigm for manufacturing research using structural equation modeling. Journal of Operations Management, 17(4), 467-488. https://doi.org/10.1016/S0272-6963(99)00002-9
Kumar, A., & Sharma, A. (2017). Systematic literature review on opinion mining of big data for government intelligence. Webology, 14(2), 6-47.
Layne, K., & Lee, J. (2001). Developing fully functional E-government: A four stage model. Government information quarterly, 18(2), 122-136. https://doi.org/10.1016/S0740-624X(01)00066-1
Lewis, B. R., & Byrd, T. A. (2003). Development of a measure for the information technology infrastructure construct. European Journal of Information Systems, 12(2), 93-109. https://doi.org/10.1057/palgrave.ejis.3000449 Lesca, H. (2003). Veille stratégique: La méthode LE SCAnning®. EMS.
Lesca, H., & Janissek-Muniz, R. (2015). Inteligência Estratégica Antecipativa e Coletiva: O Método L.E.SCAnning. Pallotti.
Li, Z., & Liao, Q. (2018). Economic solutions to improve cybersecurity of governments and smart cities via vulnerability markets. Government Information Quarterly, 35(1), 151-160. https://doi.org/10.1016/j.giq.2017.10.006
Lin, H.-F., Su, J-Q., & Higgins, A. (2015). How dynamic capabilities affect adoption of management innovations. Journal of Business Research, 69(2), 862-876. https://doi.org/10.1016/j.jbusres.2015.07.004
Linders, D., Liao, C. Z. P., & Wang, C. M. (2015). Proactive e-governance: Flipping the service delivery model from pull to push in Taiwan. Government Information Quarterly, 35(4), S68-S76. https://doi.org/10.1016/j.giq.2015.08.004
Liu, X., & Zheng, L. (2015). Cross-departmental collaboration in onestop service center for smart governance in China: Factors, strategies and effectiveness. Government Information Quarterly, 35(4), S54-S60. https://doi.org/10.1016/j.giq.2015.12.001
Malomo, F., & Sena, V. (2017). Data intelligence for local government? Assessing the benefits and barriers to use of big data in the public sector. Policy & Internet, 9(1), 7-27. https://doi.org/10.1002/poi3.141
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