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Patterns In Public Contracting: A Network Theory Perspective on Procurement Dynamics in Brazil

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Public procurement plays a critical role in ensuring transparency and efficiency in government spending. In Brazil, recent regulatory advances such as the implementation of the National Public Procurement Platform (PNCP) have expanded the availability of procurement data, enabling new forms of analysis. Motivated by concerns over inefficiencies, fragmentation, and limited competition, this study applies Network Analysis Theory (NAT) to examine structural patterns in Brazilian federal procurement between 2022 and mid-2024. Procurement relationships are modeled as bipartite graphs linking public agencies to suppliers, and metrics such as degree, betweenness, closeness, and eigenvector centrality are used alongside community detection algorithms. The analysis reveals persistent supplier concentration, cyclical contracting aligned with fiscal calendars, and growing network fragmentation over time. Central positions are consistently held by a small group of actors, while most remain marginal, suggesting low institutional integration and potential barriers to competition. The study demonstrates the scalability and reproducibility of NAT applied to large procurement datasets and proposes integrating real-time network monitoring into PNCP to enhance transparency. These findings contribute to the field of data-driven public procurement by illustrating how analytical tools can complement legal reforms to strengthen accountability and promote more equitable public contracting in Brazil and similar contexts.

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Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Data Science for Marketing

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Public procurement Network analysis Contracting networks Centrality measures Community structure SDG 8 - Decent work and economic growth SDG 10 - Reduced inequalities SDG 16 - Peace, justice and strong institutions SDG 17 - Partnerships for the goals

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