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International Conference on Applied Technologies

ICAT 2019: Applied Technologies pp 254–268Cite as

Artificial Intelligence Techniques to Detect and Prevent Corruption in Procurement: A Systematic Literature Review

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1194))

Abstract

Transparency International estimates that the costs of corruption in public procurement reach between 20 and 25% of the contract value, sometimes reaching 40–50%. In this study, we analyzed differentness kinds of corruption like (bribery, collusion embezzlement, misappropriation, fraud, abuse of discretion, favoritism, nepotism), and six types of Artificial Intelligence techniques (classification, regression, clustering, prediction, outlier detection, and visualization). The methodology proposed by Torres-Carrion was used, and four research questions were raised, which allow knowing the types of research carried out, the characteristics of the organizations in which the investigations are carried out, the technological tools, and data mining methodologies and techniques. The search was done in the Scopus and Web of Science databases, getting 102 articles published between 2015 and 2019. The primary data mining techniques used are logistic models, neural networks, Bayesian networks, supported vector machines, and decision trees.

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Authors and Affiliations

  1. University of Salamanca, Plaza de la Merced, s/n, 37008, Salamanca, Spain

    Yeferson Torres Berru & Vivian Félix López Batista

  2. Instituto Superior Tecnológico Loja, Av. Granada y Turunuma, 1101608, Loja, Ecuador

    Yeferson Torres Berru & Maria Gabriela Jimenez

  3. Universidad Técnica Particular de Loja, San Cayetano Alto S/N, 1101608, Loja, Ecuador

    Pablo Torres-Carrión

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  1. Yeferson Torres Berru
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  2. Vivian Félix López Batista
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  3. Pablo Torres-Carrión
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  4. Maria Gabriela Jimenez
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Correspondence to Yeferson Torres Berru , Vivian Félix López Batista or Pablo Torres-Carrión .

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Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Técnica del Norte, Ibarra, Ecuador

    Marcelo Zambrano Vizuete

  3. Universidad Técnica Particular de Loja, Loja, Ecuador

    Pablo Torres-Carrión

  4. Universidad de las Fuerzas Armadas (ESPE), Quito, Ecuador

    Sergio Montes León

  5. Universidad Politécnica Salesiana, Guayaquil, Ecuador

    Guillermo Pizarro Vásquez

  6. International University of Sarajevo, Sarajevo, Bosnia and Herzegovina

    Benjamin Durakovic

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Torres Berru, Y., López Batista, V.F., Torres-Carrión, P., Jimenez, M.G. (2020). Artificial Intelligence Techniques to Detect and Prevent Corruption in Procurement: A Systematic Literature Review. In: Botto-Tobar, M., Zambrano Vizuete, M., Torres-Carrión, P., Montes León, S., Pizarro Vásquez, G., Durakovic, B. (eds) Applied Technologies. ICAT 2019. Communications in Computer and Information Science, vol 1194. Springer, Cham. https://doi.org/10.1007/978-3-030-42520-3_21

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  • DOI: https://doi.org/10.1007/978-3-030-42520-3_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42519-7

  • Online ISBN: 978-3-030-42520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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