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.
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.