Benchmarking supplier risks using Bayesian networks
Purpose - The purpose of this paper is to provide a methodology for benchmarking supplier risks through the creation of Bayesian networks. The networks are used to determine a supplier's external, operational, and network risk probability to assess its potential impact on the buyer organization...
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Veröffentlicht in: | Benchmarking : an international journal 2011-01, Vol.18 (3), p.409-427 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose - The purpose of this paper is to provide a methodology for benchmarking supplier risks through the creation of Bayesian networks. The networks are used to determine a supplier's external, operational, and network risk probability to assess its potential impact on the buyer organization.Design methodology approach - The research methodology includes the use of a risk assessment model, surveys, data collection from internal and external sources, and the creation of Bayesian networks used to create risk profiles for the study participants.Findings - It is found that Bayesian networks can be used as an effective benchmarking tool to assist managers in making decisions regarding current and prospective suppliers based upon their potential impact on the buyer organization, as illustrated through their associated risk profiles.Research limitations implications - A potential limitation to the use of the methodology presented in the study is the ability to acquire the necessary data from current and potential suppliers needed to construct the Bayesian networks.Practical implications - The methodology presented in this paper can be used by buyer organizations to benchmark supplier risks in supply chain networks, which may lead to adjustments to existing risk management strategies, policies, and tactics.Originality value - This paper provides practitioners with an additional tool for benchmarking supplier risks. Additionally, it provides the foundation for future research studies in the use of Bayesian networks for the examination of supplier risks. |
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ISSN: | 1463-5771 1758-4094 |
DOI: | 10.1108/14635771111137787 |