Unveiling Public Innovation Management: What Data Mining Reveals by Analyzing Brazilian Experiences?

ABSTRACT Objective: the purpose of this article is to explain public sector innovation management, based on Brazilian experiences in public administration, relating six dimensions of innovation: drivers, facilitators, barriers, capabilities, outcomes, and impacts of innovation. Method: concerning qualitative methods, we analyze institutional documents about innovation experiences by applying content analysis and methodological triangulation among researchers. Regarding quantitative methods, we structured databases to operationalize the analysis, using data mining through the Apriori algorithm to identify association rules between the research constructs. Results: the results show 37 association rules that describe public innovation: human resources management for innovation, technology management for innovation, user knowledge, search for problem-solving, co-production between partners, and public co-producers. Conclusion: as a contribution, the research provides theoretical and empirical insights to improve the conceptual accuracy of the phenomenon and inform decision-making regarding policies and programs for managing public sector innovation.