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Feasibility of risk-based inspections in organic farming: results from a probabilistic model

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  • Danilo Gambelli
  • Francesco Solfanelli
  • Raffaele Zanoli

Abstract

A risk-based inspection system might improve the efficiency of the organic farming certification system and ultimately provide a basis for increased competitiveness of this sector. This requires the definition of an effective inspection procedure that allows statistical evaluation of critical risk factors for noncompliance. In this article, we present a study based on data from selected control bodies in five European countries that is aimed at determining the feasibility of risk-based inspections in the organic sector according to the data that are currently routinely recorded. Bayesian networks are used for identification of the factors that can affect the risk of noncompliance. The results show that previous/concurrent noncompliant behavior explains most of the risk, and that the risk increases with farm size and the complexity of their operations. The data currently recorded by control bodies appear to be insufficient to establish an effective risk-based approach to these inspections.

Suggested Citation

  • Danilo Gambelli & Francesco Solfanelli & Raffaele Zanoli, 2014. "Feasibility of risk-based inspections in organic farming: results from a probabilistic model," Agricultural Economics, International Association of Agricultural Economists, vol. 45(3), pages 267-277, May.
    • Handle: RePEc:bla:agecon:v:45:y:2014:i:3:p:267-277
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    File URL: http://hdl.handle.net/10.1111/agec.12063
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    References listed on IDEAS

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    1. Lauritzen, Steffen L., 1995. "The EM algorithm for graphical association models with missing data," Computational Statistics & Data Analysis, Elsevier, vol. 19(2), pages 191-201, February.
    2. Zanoli, Raffaele & Gambelli, Danilo & Bruschi, Viola, 2012. "Analysis of non-compliances in the organic certification system in Turkey," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(4, suppl.), pages 76-79.
    3. Danilo Gambelli & Francesco Solfanelli & Raffaele Zanoli, 2011. "Un sistema di certificazione risk-based per i controlli in agricoltura biologica: un?applicazione tramite Bayesian networks," Economia agro-alimentare, FrancoAngeli Editore, vol. 13(3), pages 37-56.
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    Cited by:

    1. Thi Huong Tran, 2018. "Critical factors and enablers of food quality and safety compliance risk management in the Vietnamese seafood supply chain," Papers 1805.12109, arXiv.org.
    2. Gambelli, Danilo & Solfanelli, Francesco & Zanoli, Raffaele & Zorn, Alexander & Lippert, Christian & Dabbert, Stephan, 2014. "Non-compliance in organic farming: A cross-country comparison of Italy and Germany," Food Policy, Elsevier, vol. 49(P2), pages 449-458.
    3. Annalisa Zezza & Federica Demaria & Tiziana Laureti & Luca Secondi, 2020. "Supervising third-party control bodies for certification: the case of organic farming in Italy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-14, December.
    4. Solfanelli, Francesco & Ozturk, Emel & Pugliese, Patrizia & Zanoli, Raffaele, 2021. "Potential outcomes and impacts of organic group certification in Italy: An evaluative case study," Ecological Economics, Elsevier, vol. 187(C).
    5. Zorn, Alexander & Lippert, Christian & Dabbert, Stephan, 2014. "Organic controls in Germany – is there a need to harmonize?," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182837, European Association of Agricultural Economists.
    6. Raffaele Zanoli & Danilo Gambelli & Francesco Solfanelli, 2014. "Assessing Risk Factors in the Organic Control System: Evidence from Inspection Data in Italy," Risk Analysis, John Wiley & Sons, vol. 34(12), pages 2174-2187, December.

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