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Ghosts in the Machine: How Big Data Analytics Can Be Used to Strengthen Online Public Procurement Accountability

Author

Listed:
  • Mihai-Răzvan Sanda

    (Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania)

  • Marian-Ilie Siminică

    (Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania
    Institute of Financial Studies, 020805 Bucharest, Romania)

  • Costin-Daniel Avram

    (Department of Economics, Accounting and International Affairs, Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania)

  • Luminița Popescu

    (Department of Management, Marketing and Business Administration, Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania)

Abstract

The core of sustainable public procurement lies in its ability to stem uneconomical public expenditures that waste taxpayer money and stifle social trust and development. The external audit of public procurement proves problematic since current research fails to provide sufficient empirical studies aimed at identifying procurement fraud. The development of online portals with embedded e-procurement solutions, along with the big data revolution, open new horizons and allow us to reveal trends otherwise impossible to spot, such as transactions achieved in an exclusive commercial relationship, in which a vendor engages only with a single public entity. By using innovative data acquisition techniques, our research encompasses 2.25 million online direct public procurement procedures conducted in 2023 using the Romanian portal for public procurement, totaling EUR 3.22 billion. By aggregating databases obtained from various public sources, our analysis achieved remarkable granularity, using over 112 million data elements—50 pertaining to each transaction. Research results indicate a unique sub-population of public procurement procedures—those conducted with “ in-house ” vendors totaling 14.28% of all direct public acquisitions and which is significantly differentiated along the entire list of analyzed criteria—financial, geographical, statistical, or risk-wise—illustrating a troubling phenomenon: possible gerrymandering of the online public procurement landscape, which, at least in theory, resembles a perfect market, by cultivating preferential commercial relations, thus affecting the legality, regularity, and economical aspects of public procurement.

Suggested Citation

  • Mihai-Răzvan Sanda & Marian-Ilie Siminică & Costin-Daniel Avram & Luminița Popescu, 2024. "Ghosts in the Machine: How Big Data Analytics Can Be Used to Strengthen Online Public Procurement Accountability," Sustainability, MDPI, vol. 16(9), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3698-:d:1385191
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    References listed on IDEAS

    as
    1. Krieger, Felix & Drews, Paul & Velte, Patrick, 2021. "Explaining the (non-) adoption of advanced data analytics in auditing: A process theory," International Journal of Accounting Information Systems, Elsevier, vol. 41(C).
    2. Alles, Michael & Gray, Glen L., 2016. "Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors," International Journal of Accounting Information Systems, Elsevier, vol. 22(C), pages 44-59.
    3. Aristotelis Mavidis & Dimitris Folinas & Dimitrios Skiadas & Alexandros Xanthopoulos, 2024. "Emerging Technologies Revolutionising Public Procurement: Insights from Comprehensive Bibliometric Analysis," Administrative Sciences, MDPI, vol. 14(2), pages 1-29, January.
    4. Ni Wayan Rustiarini & Sutrisno T. & Nurkholis Nurkholis & Wuryan Andayani, 2019. "Why people commit public procurement fraud? The fraud diamond view," Journal of Public Procurement, Emerald Group Publishing Limited, vol. 19(4), pages 345-362, August.
    Full references (including those not matched with items on IDEAS)

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