Paper Type

Research-in-Progress Paper

Description

Social sustainability issus such as child labour at a supplier pose significant reputational risk for companies. Therefore, many companies now require that suppliers follow certain standards or codes of conduct. However, in today´s complex supply chains with hundreds of sourcing locations, ongoing monitoring of compliance through audits for every supplier is hardly practical. Consequntly, an information technology system is investigated as a tool to establish ongoing monitoring of suppliers based on available information with regard to the risk that suppliers breach the compliance rules defined. This paper describes work on a system that uses a Bayesian network to integrate evidence from multiple public and private data sources in order to rank suppliers dynamically. A particular focus of future work will be a prototype based on the issu of child labour and the advantages of applying text mining methods.

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ONGOING SOCIAL SUSTAINABILITY COMPLIANCE MONITORING IN SUPPLY CHAINS

Social sustainability issus such as child labour at a supplier pose significant reputational risk for companies. Therefore, many companies now require that suppliers follow certain standards or codes of conduct. However, in today´s complex supply chains with hundreds of sourcing locations, ongoing monitoring of compliance through audits for every supplier is hardly practical. Consequntly, an information technology system is investigated as a tool to establish ongoing monitoring of suppliers based on available information with regard to the risk that suppliers breach the compliance rules defined. This paper describes work on a system that uses a Bayesian network to integrate evidence from multiple public and private data sources in order to rank suppliers dynamically. A particular focus of future work will be a prototype based on the issu of child labour and the advantages of applying text mining methods.