High earnings through firm influence

Sturm, Niclas Frederic; Candia, Cristian; Damásio, Bruno; Pinheiro, Flávio L.

http://hdl.handle.net/10362/182045

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Autores

Sturm, Niclas Frederic

Candia, Cristian

Damásio, Bruno

Pinheiro, Flávio L.

Resumo(s)

Public procurement, a critical but often overlooked aspect of governance, plays a pivotal role in steering the acquisition of goods, services and the commissioning of public works. Our study, analyzing over one million public procurement contracts from the Portuguese public administration, applies network science to unravel the complexities of this market. We uncover a market characterized by highly modular and hierarchical networks, with notable service specialization, regional diversity, and entity diversification. Our findings reveal a clear pattern: firms occupying influential positions within the networks consistently achieve higher earnings per bid. This disparity in earnings indicates a market where competition is constrained and entry barriers for new firms are high. Similarly, markets in the Portuguese public procurement system exhibit high levels of concentration, which raises both integrity and supplier risks that should be monitored by policymakers. The empirical framework developed in this article contributes to a growing body of literature that analyzes the levels of competition in public procurement systems. The network-based method applied here facilitates the analysis of firms’ positioning within their network of competitors and helps to quantify firm capabilities in a way that moves beyond a monolithic view of firm size and market power.

Descrição

Sturm, N. F., Candia, C., Damásio, B., & Pinheiro, F. L. (2025). High earnings through firm influence: the role of hierarchical structures in public procurement. EPJ Data Science, 14, 1-20. Article 27. https://doi.org/10.1140/epjds/s13688-025-00543-z --- NFS, BD, and FLP acknowledge the financial support provided by FCT Portugal under the projects 2024.07378.IACDC, 2024.07601.IACDC, and UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) (https://doi.org/10.54499/UIDB/04152/2020).

Palavras-chave

Public Procurement Tenders Market Organization Network Analysis Competition Complexity Modelling and Simulation Computer Science Applications Computational Mathematics SDG 8 - Decent Work and Economic Growth