IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v95y2024ics0038012124001873.html
   My bibliography  Save this article

Sustainability and high-level corruption in healthcare procurement: Profiles of Italian contracting authorities

Author

Listed:
  • Del Sarto, Simone
  • Gnaldi, Michela
  • Salvini, Niccolò

Abstract

Addressing corruption is crucial for building a sustainable healthcare system that ensures access, quality, and equity in healthcare delivery. Despite that, many current strategies to combat corruption in the healthcare sector do not evaluate high-level corruption, such as corruption risks occurring at sub-national levels. This work bridges this gap by providing corruption risk profiles of Italian contracting authorities responsible for procuring goods and services for healthcare facilities in the public procurement process. Using an array of 14 red flags of corruption risk and an extended Item Response Theory model applied to a big data source made available by the Italian Anti-corruption Authority, our main findings show that: i. the risk of corruption is a multidimensional occurrence, which can be represented as a four-dimensional latent variable; ii. there are eight clusters of contracting authorities, having distinct and well-defined risk profiles over the four ascertained dimensions of corruption risk; iii. the distribution of risk profiles at sub-national level showcases relevant geographic variations and emphasises the need for tailored anti-corruption strategies to effectively address region-specific challenges and risk factors.

Suggested Citation

  • Del Sarto, Simone & Gnaldi, Michela & Salvini, Niccolò, 2024. "Sustainability and high-level corruption in healthcare procurement: Profiles of Italian contracting authorities," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
  • Handle: RePEc:eee:soceps:v:95:y:2024:i:c:s0038012124001873
    DOI: 10.1016/j.seps.2024.101988
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012124001873
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2024.101988?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J Gallego & G Rivero & J.D. MartÔøΩnez, 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 16724, Universidad del Rosario.
    2. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
    3. Francesco Bartolucci, 2007. "A class of multidimensional IRT models for testing unidimensionality and clustering items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 141-157, June.
    4. Treisman, Daniel, 2000. "The causes of corruption: a cross-national study," Journal of Public Economics, Elsevier, vol. 76(3), pages 399-457, June.
    5. Clifford M. Hurvich & Chih‐Ling Tsai, 1993. "A Corrected Akaike Information Criterion For Vector Autoregressive Model Selection," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(3), pages 271-279, May.
    6. Oriana Bandiera & Andrea Prat & Tommaso Valletti, 2009. "Active and Passive Waste in Government Spending: Evidence from a Policy Experiment," American Economic Review, American Economic Association, vol. 99(4), pages 1278-1308, September.
    7. F. Bartolucci & G. Montanari & S. Pandolfi, 2012. "Dimensionality of the Latent Structure and Item Selection Via Latent Class Multidimensional IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 782-802, October.
    8. Lisciandra, Maurizio & Milani, Riccardo & Millemaci, Emanuele, 2022. "A corruption risk indicator for public procurement," European Journal of Political Economy, Elsevier, vol. 73(C).
    9. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    10. Arvind K. Jain, 2001. "Corruption: A Review," Journal of Economic Surveys, Wiley Blackwell, vol. 15(1), pages 71-121, February.
    11. Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
    12. Fazekas, Mihály & Kocsis, Gábor, 2020. "Uncovering High-Level Corruption: Cross-National Objective Corruption Risk Indicators Using Public Procurement Data," British Journal of Political Science, Cambridge University Press, vol. 50(1), pages 155-164, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emmanuel Akwandoh & Jiang Xinyu & Z. Y. Medin & Ying Ma & Estella Efiba Baffoe, 2025. "Assessing the Impacts of Competitive Tendering on the Effectiveness of Medical Logistics in Ghana’s Healthcare Sector at Both Effia-Nkwanta Regional Hospital and Tepa Government Hospital," SN Operations Research Forum, Springer, vol. 6(2), pages 1-35, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michela Gnaldi & Simone Del Sarto, 2018. "Variable Weighting via Multidimensional IRT Models in Composite Indicators Construction," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1139-1156, April.
    2. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.
    3. J Gallego & M Prem & J. F Vargas, 2020. "Corruption in the times of pandemia," Documentos de Trabajo 18178, Universidad del Rosario.
    4. Michael Brusco & Hans-Friedrich Köhn & Douglas Steinley, 2015. "An Exact Method for Partitioning Dichotomous Items Within the Framework of the Monotone Homogeneity Model," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 949-967, December.
    5. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    6. Belev, S. & Veterinarov, V. & Matveev, E., 2023. "Vertical collusion in public procurement: Estimation based on data for R&D composite auctions," Journal of the New Economic Association, New Economic Association, vol. 59(2), pages 36-63.
    7. Gallego, J & Prem, M & Vargas, J. F, 2020. "Corruption in the times of pandemia," Documentos de Trabajo 18178, Universidad del Rosario.
    8. Michela Gnaldi & Simone Del Sarto, 2018. "Time Use Habits of Italian Generation Y: Dimensions of Leisure Preferences," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 1187-1203, August.
    9. Simone Del Sarto & Michela Gnaldi, 2022. "Spare time use: profiles of Italian Millennials (beyond the media hype)," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1403-1428, December.
    10. Michela Gnaldi & Simone Del Sarto, 2024. "Validating Corruption Risk Measures: A Key Step to Monitoring SDG Progress," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(3), pages 1045-1071, December.
    11. Michela Gnaldi & Simone Del Sarto, 2024. "Measuring Corruption Risk in Public Procurement over Emergency Periods," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 172(3), pages 859-877, April.
    12. Florin Alexandru Roman & Monica Violeta Achim & Robert W. McGee, 2023. "Fraud related to EU funds. The case of Romania," Journal of Financial Studies, Institute of Financial Studies, vol. 14(8), pages 120-142, May.
    13. Bin Dong & Benno Torgler, 2010. "The Causes of Corruption: Evidence from China," Working Papers 2010.72, Fondazione Eni Enrico Mattei.
    14. Majeed, Muhammad Tariq & MacDonald, Ronald, 2010. "Corruption and the Military in Politics: Theory and Evidence from around the World," SIRE Discussion Papers 2010-91, Scottish Institute for Research in Economics (SIRE).
    15. Goel, Rajeev K. & Nelson, Michael A., 2007. "Are corrupt acts contagious?: Evidence from the United States," Journal of Policy Modeling, Elsevier, vol. 29(6), pages 839-850.
    16. Yan Leung Cheung & P. Raghavendra Rau & Aris Stouraitis, 2012. "How much do firms pay as bribes and what benefits do they get? Evidence from corruption cases worldwide," NBER Working Papers 17981, National Bureau of Economic Research, Inc.
    17. Rajeev Goel & Michael Nelson, 2011. "Measures of corruption and determinants of US corruption," Economics of Governance, Springer, vol. 12(2), pages 155-176, June.
    18. Arminen, Heli & Menegaki, Angeliki N., 2019. "Corruption, climate and the energy-environment-growth nexus," Energy Economics, Elsevier, vol. 80(C), pages 621-634.
    19. Torgler, Benno & Schneider, Friedrich, 2009. "The impact of tax morale and institutional quality on the shadow economy," Journal of Economic Psychology, Elsevier, vol. 30(2), pages 228-245, April.
    20. Lalountas, Dionisios A. & Manolas, George A. & Vavouras, Ioannis S., 2011. "Corruption, globalization and development: How are these three phenomena related?," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 636-648, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:95:y:2024:i:c:s0038012124001873. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.