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Politician–manager relationship, procurement decisions, and corruption risk in local governments

Bibliographic Data

ID6301644
AuthorsRiccardo Mussari (0000-0001-8305-2532, University of Siena), Fabio Monteduro (0000-0002-1144-8201, University of Rome Tor Vergata), Simona Caramia (University of Siena), Veronica Allegrini (0000-0002-3457-2387, University of Rome Tor Vergata)
Year2025
Pages1-24
Publication date2025-08-20
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueLocal Government Studies (JOURNAL)
Journal identifiersISSN: 0300-3930 • E-ISSN: 1743-9388
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/03003930.2025.2548485
OpenAlexW4413348939
LanguageEN
Citations received1
References cited67

This study combines agency and patronage theories to explore how the nature of local governing bodies–elected politicians or centrally appointed commissioners–influences managerial decisions and related corruption risks in public procurement. Agency theory suggests that discretion and weak oversight allow managers to exploit their expertise for personal gain, while patronage theory highlights how political actors may pressure managers to favour local elites. Analysing 16,953 procurement procedures from Italian municipalities, we applied multilevel mixed-effects and panel logistic regression models to compare decision-making under governing bodies having different nature. Results show that managers make more discretionary–and potentially more corruption-prone–procurement decisions under elected officials than under appointed commissioners. These findings highlight the dual risks of expertise asymmetry and political influence in high-discretion settings. Effective mechanisms are essential to prevent misuse and ensure discretion serves the public interest

Business · Language change · Local government · Political science · Procurement · Corruption and Economic Development · Public Administration · Public Procurement and Policy · Taxation and Compliance Studies · Accounting · Marketing

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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