An information system for assessing the likelihood of child labor in supplier locations leveraging Bayesian networks and text mining

Thöni, Andreas and Taudes, Alfred and Tjoa, A Min (2018) An information system for assessing the likelihood of child labor in supplier locations leveraging Bayesian networks and text mining. Information Systems and e-Business Management, 16 (2). pp. 443-476. ISSN 1617-9846

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Abstract

This paper presents an expert system to monitor social sustainability compliance in supply chains. The system allows to continuously rank suppliers based on their risk of breaching sustainability standards on child labor. It uses a Bayesian network to determine the breach likelihood for each supplier location based on the integration of statistical data, audit results and public reports of child labor incidents. Publicly available statistics on the frequency of child labor in different regions and industries are used as contextual prior. The impact of audit results on the breach likelihood is calibrated based on expert input. Child labor incident observations are included automatically from publicly available news sources using text mining algorithms. The impact of an observation on the breach likelihood is determined by its relevance, credibility and frequency. Extensive tests reveal that the expert system correctly replicates the decisions of domain experts in the fields supply chain management, sustainability management, and risk management.

Item Type: Article
Additional Information: Open access funding provided by TU Wien (TUW).
Keywords: Social sustainability, Supply chain risk management, Child labor, Bayesian network risk model, Text mining
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Version of the Document: Published
Depositing User: Gertraud Novotny
Date Deposited: 04 Oct 2018 11:10
Last Modified: 04 Oct 2018 11:57
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/87176/
URI: https://epub.wu.ac.at/id/eprint/6558

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