The diffusion of innovations under normative induction in Brazil
DOI:
https://doi.org/10.1108/RAUSP-10-2020-0250Keywords:
Public administration, Innovation diffusion, Innovation adoption, Management practices, Innovation drivers, Managerial innovationAbstract
PurposeHierarchically superior bodies develop normative instructions to induce the diffusion of innovations, stimulating the adoption of management practices in supervised public bodies and seeking public administration efficiency increase. Despite this, the effectiveness of these normative instructions is unknown, as well as its inducing and lasting effects in the diffusion of these innovations, especially in Brazil. This study aims to understand the effects of normative induction.
Design/methodology/approachThe adoption of risk management, integrity & ethics and information security practices was evaluated over a decade (2009 to 2019), including the adoption behavior of more than 200 Brazilian federal agencies. Public open data were collected and analyzed with multinomial logistic regression.
FindingsThe normative instructions’ effectiveness in propagating the evaluated practices is remarkable; however, its mere development by the superior bodies cannot be considered enough since the general adoption index can be considered good but not excellent. No evaluated practice reached a saturation level above 75%.
Research limitations/implicationsThis paper contributes to bringing the international literature’s generic knowledge on the adoption of innovation to the specific Brazilian public administration context, providing insightful implications for policymakers, public managers and researchers.
Practical implicationsThis work is unique, as it systematically analyzes multiple innovation adoption and presents excellent opportunities for future researchers by reproducing all scripts and automation developed. Furthermore, all data are available and hosted on public platforms with detailed steps and documentation.
Social implicationsThe use of open data from governmental sources allows enhanced transparency and the discovery of affecting variables while observing innovation adoption in the public administration.
Originality/valueThe presence of normative instructions and their adoption rate is rarely measured in the Brazilian public administration
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References
Bezdrob, M., & Šunje, A. (2015). Management innovation – designing and testing a theoretical model. Southeast European Journal of Economics and Business, 9(1), 16–29, doi: 10.2478/jeb-2014-0004.
Bloch, C. (2011). Measuring public innovation in the Nordic countries (MEPIN). Nordic Innovation Centre (NICe) - the Danish Centre for studies in research and research policy (CFA), pp. 1–63. (February, available at: http://www.diva-portal.org/smash/get/diva2:707193/FULLTEXT01.pdf
Boyne, G. A., & Chen, A. A. (2008). Performance targets and public service improvement. Journal of Public Administration Research and Theory, 17(3), 455–477, doi: 10.1093/jopart/mul007.
BRAZIL. (2016a). Instrução normativa conjunta in 01/2016, Brasília, DF: Ministério do Planejamento, Orçamento e Gestão, Controladoria-Geral da União.
BRAZIL. (2016b). Tribunal de contas da união. Referencial Para avaliação da governança do centro de governo, Brasília, DF: Secretaria de Controle Externo da Administração do Estado.
Bysted, R., & Hansen, J. R. (2015). Comparing public and private sector employees' innovative behaviour: understanding the role of job and organizational characteristics, job types, and subsectors. Public Management Review, 17(5), 698–717, doi: 10.1080/14719037.2013.841977.
Creswell, J. W. (2014). The selection of a research approach. Research Design, 3–23.https://doi.org/45593:01
Damanpour, F. (1991). Organizational innovation: a meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555–590, doi: 10.2307/256406.
Damanpour, F. (2014). Footnotes to research on management innovation. Organization Studies, 35(9), 1265–1285, doi: 10.1177/0170840614539312.
Damanpour, F., & Aravind, D. (2012). Managerial innovation: conceptions, processes and antecedents. Management and Organization Review, 8(2), 423–454, doi: 10.1111/j.1740-8784.2011.00233.x.
Damanpour, F., Sanchez-Henriquez, F., & Chiu, H. H. (2018). Internal and external sources and the adoption of innovations in organizations. British Journal of Management, 29(4), 712–730, doi: 10.1111/1467-8551.12296.
Damanpour, F., & Schneider, M. (2009). Characteristics of innovation and innovation adoption in public organizations: Assessing the role of managers. Journal of Public Administration Research and Theory, 19(3), 495–522, doi: 10.1093/jopart/mun021.
De Vries, H., Bekkers, V., & Tummers, L. (2016). Innovation in the public sector: a systematic review and future research agenda. Public Administration, 94(1), 146–166, doi: 10.1111/padm.12209.
De Vries, H., Tummers, L., & Bekkers, V. (2018). The diffusion and adoption of public sector innovations: a meta-synthesis of the literature. Perspectives on Public Management and Governance, 1(3), 159–176, doi: 10.1093/ppmgov/gvy001.
Demircioglu, M. A. (2020). The effects of organizational and demographic context for innovation implementation in public organizations. Public Management Review, 22(12), 1852–1875, doi: 10.1080/14719037.2019.1668467.
Demircioglu, M. A., & Audretsch, D. B. (2017). Conditions for innovation in public sector organizations. Research Policy, 46(9), 1681–1691, doi: 10.1016/j.respol.2017.08.004.
Demircioglu, M. A., & Audretsch, D. B. (2020). Conditions for complex innovations: Evidence from public organizations. Journal of Technology Transfer, 45(3), 820–843, doi: 10.1007/s10961-018-9701-5.
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, doi: 10.2307/2095101.
Ferreira, P. C. G., & Neiva, E. R. (2018). Antecedents of turnover in federal public administration. RAUSP Management Journal, doi: 10.1108/RAUSP-04-2018-008.
Freedman, D. A. (2009). Statistical models: Theory and practice (2nd), New York, NY: CAMBRIDGE UNIVERSITY.
Garson, G. D. (2012). Testing statistical assumptions. Blue Book Series, 1–52, Retrieved from http://www.statisticalassociates.com/assumptions.pdf
Hair, J. F., & Fávero, L. P. (2019). Multilevel modeling for longitudinal data: Concepts and applications. RAUSP Management Journal, doi: 10.1108/RAUSP-04-2019-0059.
Hassan, S., & Al-Hakim, L. A. Y. (2011). The relationships among critical success factors of knowledge management, innovation and organizational performance: A conceptual framework. In 2011 International Conference on Management and Artificial Intelligence, p. 10, Bali, Indonesia.
Isidro-Filho, A. (2017). Inovação no setor público: Teoria, tendências e casos no brasil. Retrieved from http://repositorio.enap.gov.br/handle/1/2989
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning (Vol. 103). New York, NY: Springer New York, NY. 10.1007/978-1-4614-7138-7
Janka, M., Heinicke, X., & Guenther, T. W. (2019). Beyond the “good” and “evil” of stability values in organizational culture for managerial innovation: the crucial role of management controls. Review of Managerial Science, 42, doi: 10.1007/s11846-019-00338-3.
Kung, L., & Kung, H.-J. (2015). External environment pressure on organizational innovation adoption: From literature to a conceptual model. International Journal of Management Theory and Practice, 99–115.
Lu, X., & White, H. (2014). Robustness checks and robustness tests in applied economics. Journal of Econometrics, 178(PART 1), 194–206, doi: 10.1016/j.jeconom.2013.08.016.
Mol, M. J., & Birkinshaw, J. (2009). The sources of management innovation: When firms introduce new management practices. Journal of Business Research, 62(12), 1269–1280, doi: 10.1016/j.jbusres.2009.01.001.
Mol, M. J., & Birkinshaw, J. (2014). The role of external involvement in the creation of management innovations. Organization Studies, 35(9), 1287–1312, doi: 10.1177/0170840614539313.
OECD/Eurostat. (2018). Oslo manual 2018, OECD. (4th)10.1787/9789264304604-en
Oliveira, L. B., & Costa, E. M. T. C. M. D. (2019). Comparing attitudes of public servants and outsourced employees. RAUSP Management Journal, doi: 10.1108/RAUSP-07-2018-0049.
Plonsky, L. (2017). Quantitative research methods, in Loewen, S., & Sato, M., (Eds.), The SAGE encyclopedia of educational research, measurement, and evaluation, pp. 505–521. Thousand Oaks (CA: SAGE Publications, Inc. 10.4135/9781506326139.n562
Shumacker, R. E., & Lomax, R. G, 2nd. (2008). A beginner's guide to structural equation modeling, NJ: Taylor & Francis e-Library.
Sincorá, L. A., Oliveira, M. P. V. D., Zanquetto-Filho, H., & Ladeira, M. B. (2018). Business analytics leveraging resilience in organizational processes. RAUSP Management Journal, doi: 10.1108/RAUSP-04-2018-002.
Spanos, Y. E. (2009). Innovation adoption: an integrative model. SPOUDAI – Journal of Economics and Business, 59(1), 100–124.
Swiss, J. E. (2005). A framework for assessing incentives in results-based management. Public Administration Review, 65(5), 592–602, doi: 10.1111/j.1540-6210.2005.00486.x.
UNESCO. (2011). The international standard classification of education (ISCED 2011). (I. for statistics, Ed.). Prospects, Montreal, Quebec: UNESCO. Retrieved from: http://www.uis.unesco.org
Walker, R. M., Damanpour, F., & Devece, C. A. (2011). Management innovation and organizational performance: the mediating effect of performance management. Journal of Public Administration Research and Theory, doi: 10.1093/jopart/muq043.
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