Robust Sourcing from Suppliers under Ambiguously Correlated Major Disruption Risks

• 成果类型: Article
• 署名作者: Zhao, Ming; Freeman, Nickolas K.
• 署名单位: University of Houston System; University of Houston; University of Alabama System; University of Alabama Tuscaloosa
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12933
• 发表日期: 2019
• 页码: 441-456
• 关键词: Supply uncertainty; multiple sourcing; distributional uncertainty; supplier selection

摘要

As the severity and frequency of supply chain disruptions increases due to globalization and outsourcing, companies are faced with the challenge of managing correlated disruption risks. However, correctly estimating supplier correlations is difficult and relying on incorrect estimates can be costly. Motivated by these challenges, we consider models for managing disruption risks when suppliers are ambiguously correlated. Our models are based on profit-oriented correlation structures that only require accurate estimates of the marginal disruption probabilities for available suppliers. Analysis of the models, along with extensive numerical studies, show that they offer high-quality solutions and provide several important insights regarding supplier selection, appropriate budgets for efforts to better understand the prevailing correlation structure, and identifying subsets of the available suppliers that should be considered for strategic alliances. In addition to these benefits, we discuss a progressive, profit-oriented approach for risk management that is based on these models and is easily implemented in situations with minimal in formation regarding supplier correlations.