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Research Article • BAR, Braz. Adm. Rev. 21 (02) • 2024 • https://doi.org/10.1590/1807-7692bar2024230067 copy

Intelligence as an Innovation in Public Management: Premises for Institutionalization

Authorship SCIMAGO INSTITUTIONS RANKINGS

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.

Keywords:
intelligence; public management; institutional theory; smart government; innovation

Stages of the institutionalization process (Tolbert & Zucker, 1999Tolbert, P. S., & Zucker, L. G. (1999). A institucionalização da teoria institucional. In S. R. Clegg, C. Hardy, & W. R. Nordy (Orgs.), Handbook de estudos organizacionais: modelos de análise e novas questões em estudos organizacionais (pp. 196-219). Atlas.)	Theoretical relationship	Dimensions of intelligence in public management
Habitualization	The understanding of public management regarding the importance of structuring intelligence, intensifying the use of data and information from the environment, and taking advantage of available technologies.	D01 - Use of external data and information D03 - Effective use of technologies (big data, business intelligence)
Objectification	Organization of the intelligence structure, aiming for normative and cognitive legitimacy. This activity comes to have a shared meaning with public management and society. With positive results, other public bodies see the dissemination of the structure as an optimal choice.	D04 - Evidence-based decision-making D05 - Cross-departmental and interorganizational collaboration D06 - Innovation, co-creation, and collective intelligence D10 - Database organization and unification
Sedimentation	Consolidation and continuity of intelligence through generations of members of the organization, which, in the case of public management, can be related to the sustainability of the process beyond government exchanges.	D02 - Organizational culture based on intelligence D06 - Innovation, co-creation, and collective intelligence D07 - Agile government D08 - Management efficiency and effectiveness D09 - Social engagement

Intelligence dimensions	Definition	Theoretical basis
Use of external data and information (D01)	The importance of using data and information that is latent in the crowd and can contribute to public management.	Gil-Garcia et al. (2013Gil-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., 2016); Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.)
Organizational culture based on intelligence (D02)	Encouraging a culture of alertness and information sharing through networks, collecting external data and information, and using information to develop the work and decision-making of public managers.	Lesca and Janissek-Muniz (2015Lesca, H., & Janissek-Muniz, R. (2015). Inteligência Estratégica Antecipativa e Coletiva: O Método L.E.SCAnning. Pallotti.); Schoemaker and Day (2009Schoemaker, P. J., & Day, G. S. (2009). How to make sense of weak signals. In G. R. Hickman (Ed.), Leading organizations: Perspectives for a new era (cap. 4, pp. 37-47). Sage Publications.); Xu (2007Xu, M. (2007). Managing strategic intelligence: Techniques and technologies. IGI Global.)
Effective use of technologies (big data; business intelligence) (D03)	Information and communication technology (ICT) used in government to collect, process, and share data and information, which can then be used to make decisions and provide public services.	Gil-Garcia et al. (2013Gil-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., 2016); Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.); Johnston and Hansen (2011Johnston, 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.); Linders et al. (2015Linders, 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 https://doi.org/10.1016/j.giq.2015.08.00... ); Paula and Rover (2012Paula, G. D., & Rover, A. J. (2012). O governo eletrônico e a atividade de inteligência. Revista Democracia Digital e Governo Eletrônico, 6, 216-236.); Wang et al. (2016Wang, L. J., Zhang, Y., Li, Q., & Ruan, P. N. (2016). Under the background of smart city development of e-government performance evaluation: study in every districts of Beijing. Proceedings of the 6th International Conference on Information Technology for Manufacturing Systems. Prague, Czech Republic.)
Evidence-based decision-making (D04)	Decisions based on data and the intensification of its use through ubiquitous sensing, advanced measurement, and integrated applications allow the government to make more informed decisions.	Gil-Garcia et al. (2016Gil-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 https://doi.org/10.1016/j.giq.2016.03.00... ); Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.)
Cross-departmental and interorganizational collaboration (D05)	Sharing data and information between different public sector bodies through collaboration and developing unified public activities to better serve society.	Gil-Garcia et al. (2016Gil-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 https://doi.org/10.1016/j.giq.2016.03.00... ); Liu and Zheng (2015Liu, X., & Zheng, L. (2015). Cross-departmental collaboration in one-stop 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 https://doi.org/10.1016/j.giq.2015.12.00... )
Innovation, co-creation, and collective intelligence (D06)	Improving processes, insights for new public policies, new forms of communication between government and society, and sharing decisions by harnessing collective intelligence.	Eom et al. (2016Eom, 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 https://doi.org/10.1016/j.giq.2016.01.00... ); Gil-Garcia et al. (2016Gil-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 https://doi.org/10.1016/j.giq.2016.03.00... ); Guenduez et al. (2018Guenduez, 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 https://doi.org/10.5334/ssas.124... ); Juniawan et al. (2017Juniawan, 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.); Nam (2016Nam, T. (2016). Government-driven participation and collective intelligence: A case of the Government 3.0 Initiative in Korea. Information, 7(4), 55.)
Agile government (D07)	Speed up the provision of services to society by intensifying the use of ICT, the use of data and information, and society’s participation.	Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.); Johnston and Hansen (2011Johnston, 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.)
Management efficiency and effectiveness (D08)	Public management efficiency and effectiveness with effective use of ICT, data, and information and society’s participation.	Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.); Liu and Zheng (2015Liu, X., & Zheng, L. (2015). Cross-departmental collaboration in one-stop 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 https://doi.org/10.1016/j.giq.2015.12.00... )
Social engagement (D09)	Effective participation of society in public management development.	Eom et al. (2016Eom, 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 https://doi.org/10.1016/j.giq.2016.01.00... ); Gil-Garcia et al. (2014Gil-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 https://doi.org/10.1016/j.giq.2014.09.00... ); Gil-Garcia et al. (2013); Scholl and Scholl (2014Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. Proceedings of the iConference 2014 (pp. 163-176), Berlin, German.); Johnston and Hansen (2011Johnston, 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.)
Database organization and unification (D10)	Unification of the most diverse databases and integration of government systems.	Melati and Janissek-Muniz (2020Melati, C., & Janissek-Muniz, R. (2020). Governo inteligente: Análise de dimensões sob a perspectiva de gestores públicos. Revista de Administração Pública, 54(3), 400-415. https://doi.org/10.1590/0034-761220190226 https://doi.org/10.1590/0034-76122019022... )

Categories	Definition	Intelligence dimensions
Organizational structure	Redesign of the technical structure through the centralization of information, new management and organizational culture mechanisms, engagement, and leadership, alongside definitions of intelligence processes.	D01 - Use of external data and information D02 - Organizational culture based on intelligence D05 - Cross-departmental and interorganizational collaboration D07 - Agile government D08 - Management efficiency and effectiveness
Technological structure	Practices and real effects of data and information technology in the development and legitimacy of intelligence in public management.	D03 - Effective use of technologies D06 - Innovation, co-creation, and collective intelligence D07 - Agile government D10 - Database organization and unification
Human capital	Training and human development aimed at increasing the analytical capacity of public servants. Incentives for public managers and servants focused on intelligence.	D02 - Organizational culture based on intelligence D04 - Evidence-based decision-making
Social engagement	Set up government and society co-creation processes. Implement an open data policy and interaction mechanisms with the business sector and other social actors.	D06 - Innovation, co-creation, and collective intelligence

Characteristics	Category	Frequency	%
Age	18-30 years old	9	4.27%
	31-40 years old	86	40.76%
	41-50 years old	68	32.23%
	51-60 years old	29	13.74%
	over 60 years old	19	9.00%
Education level	High school/Technical	10	4.74%
	Higher education	51	24.17%
	Specialization	104	49.29%
	Master’s degree	33	15.64%
	Doctorate degree	13	6.16%
Length of service in the public sector	Up to 1 year	3	1.42%
	From 1 to 5 years	29	13.74%
	From 6 to 10 years	53	25.12%
	From 11 to 15 years	48	22.75%
	More than 15 years	78	36.97%
Position	Management	49	23.22%
	Direction	21	9.95%
	Technician/Analyst	141	66.82%
Public sphere of action	Municipal	24	11.37%
	State	156	73.93%
	Federal	31	14.69%
Public power of action	Executive	178	84.36%
	Legislative	14	6.64%
	Judiciary	19	9.00%
State of operation	Acre	0	0.00%
	Alagoas	0	0.00%
	Amapá	0	0.00%
	Amazonas	0	0.00%
	Bahia	0	0.00%
	Ceará	0	0.00%
	Distrito Federal	6	2.84%
	Espírito Santo	0	0.00%
	Goiás	0	0.00%
	Maranhão	0	0.00%
	Mato Grosso	0	0.00%
	Mato Grosso do Sul	1	0.47%
	Minas Gerais	0	0.00%
	Pará	1	0.47%
	Paraíba	3	1.42%
	Paraná	3	1.42%
	Pernambuco	1	0.47%
	Piauí	1	0.47%
	Rio de Janeiro	6	2.84%
	Rio Grande do Norte	0	0.00%
	Rio Grande do Sul	174	82.46%
	Rondônia	2	0.95%
	Roraima	0	0.00%
	Santa Catarina	2	0.95%
	São Paulo	7	3.32%
	Sergipe	4	1.90%
	Tocantins	0	0.00%

Factor	Cronbach’s alpha	Number of items
Human Capital (HC)	0.713	6
Organizational Structure (OS)	0.799	8
Technological Structure (TS)	0.802	7
Social Engagement (SE)	0.820	5
Institutionalization of Intelligence in Public Management (INST)	0.842	11

Factor	KMO	Bartlett’s test of sphericity (significance)
Human Capital (HC)	0.776	0.000
Social Engagement (SE)	0.813	0.000
Organizational Structure (OS)	0.792	0.000
Technological Structure (TS)	0.850	0.000
Institutionalization of Intelligence in Public Management (INST)	0.873	0.000

Items	HC	Items	SE	Items	OS	Items	TS	Items	INST
HC01	0.447	SE01	0.679	OS01	0.688	TS01	0.513	INST01	0.563
HC02	0.722	SE02	0.811	OS02	0.755	TS02	0.724	INST02	0.688
HC03	0.677	SE03	0.850	OS03	0.661	TS03	0.678	INST03	0.701
HC04	0.743	SE04	0.733	OS04	0.750	TS04	0.752	INST04	0.399
HC05	0.814	SE05	0.737	OS05	0.735	TS05	0.793	INST05	0.696
HC06	0.407			OS06	0.296	TS06	0.611	INST06	0.694
				OS07	0.578	TS07	0.655	INST07	0.629
				OS08	0.654			INST08	0.469
								INST09	0.716
								INST10	0.726
								INST11	0.544

Factor	Items	External loads	Cronbach’s alpha	Composite reliability	AVE
Human Capital	HC02	0.770	0.759	0.847	0.581
	HC03	0.711
	HC04	0.763
	HC05	0.802
Social Engagement	SE01	0.677	0.820	0.874	0.583
	SE02	0.780
	SE03	0.851
	SE04	0.766
	SE05	0.731
Organizational Structure	OS01	0.679	0.818	0.864	0.477
	OS02	0.729
	OS03	0.647
	OS04	0.730
	OS05	0.739
	OS06	Excluded (Table 7)
	OS07	0.620
	OS08	0.683
Technological Structure	TS02	0.714	0.804	0.860	0.507
	TS03	0.689
	TS04	0.771
	TS05	0.791
	TS06	0.631
	TS07	0.664
Institutionalization of Intelligence in Public Management	INST01	0.589	0.845	0.879	0.450
	INST02	0.709
	INST03	0.720
	INST04	Excluded (Table 7)
	INST05	0.695
	INST06	0.694
	INST07	0.628
	INST09	0.713
	INST10	0.723
	INST11	0.536

Factor	HC	SE	OS	TS	INST
Human Capital (HC)	0.762
Social Engagement (SE)	0.466	0.763
Organizational Structure (OS)	0.484	0.402	0.691
Technological Structure (TS)	0.561	0.368	0.608	0.712
Institutionalization of Intelligence in Public Management (INST)	0.683	0.505	0.603	0.622	0.670

Factor	VIF (factors)	VIF (items)
Human Capital (HC)	1.686	1.357 - 1.618
Social Engagement (SE)	1.351	1.561 - 2.201
Organizational Structure (OS)	1.722	1.299 - 2.234
Technological Structure (TS)	1.865	1.316 - 1.810
Institutionalization of Intelligence in Public Management (INST)	-	1.299 - 1.903

Hypothesis	Relationship	Values of t	Significance (p-value)	Evaluation
H1	OS INST	4.244	0.000	Supported
H2	TS INST	3.381	0.001	Supported
H3	HC INST	5.198	0.000	Supported
H4	SE INST	2.630	0.009	Supported

Relationship between variables	f²
OS INST	0.076
TS INST	0.062
HC INST	0.222
SE INST	0.046
H4	SE INST

Constructs of institutionalization of intelligence in public management	Proposed organizational actions
Organizational Structure	Formalization of intelligence processes; Qualification of the information flow in the organization between sectors; Improved data and information management; Development of an organizational culture focused on data intelligence; Structuring projects to involve society.
Technological Structure	Develop interoperability of government systems; Government database organization and unification; Effective use of technologies for managing large amounts of data; Developing tools that help social participation for co-creation, innovation, and harnessing collective intelligence.
Human Capital	Development of training trails in data science; Development of training trails on public data and information management; Leadership development aimed at structuring and encouraging a culture of intelligence in government.
Social Engagement	Develop mechanisms to encourage social participation; Set up government-society co-creation processes; Making effective use of collective intelligence.

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