Integrating performance and risk aspects of supply chain design processes
Integrating performance and risk aspects of supply chain design processes
复制标题
DOI：
10.1080/09537287.2018.1520314
复制
发表时间：
2018-11-18
影响因子：
8.3
通讯作者：
Gloet, Marianne
中科院分区：
文献类型：
--
作者：
Samson, Danny;Gloet, Marianne
供应链设计是一个复杂且结构相对较差的过程，涉及选择许多决策参数，通常需要考虑许多不确定性来源。许多传统的供应链设计过程都涉及对供应链有效性的重要度量（如成本、质量、交付可靠性和服务水平）采用确定性方法（使用点估计）。无论是在研究文献中还是在实践中，供应链中断通常被单独视为风险，这意味着采取纯粹传统的风险管理和风险最小化方法。我们已经开发并应用了一种方法，该方法将供应链设计者的智慧和经验与蒙特卡罗模拟模型所提供的评估能力相结合，该模型使用决策分析技术来明确地将整个范围内的不确定量纳入考虑中的替代供应链设计。在定义并列出16个不同的供应链设计决策类别的一般决策变量和不确定性因素后，我们应用该方法将决策者的概率建模方法与概率建模方法相结合，迭代地实现这种方法的最佳两个元素。这种新的方法，充分整合供应链设计的性能和风险因素，然后说明了一个案例研究。最后，我们呼吁开展进一步的发展研究和实地工作，以完善这一方法。
Supply chain design is a complex and relatively poorly structured process, involving choosing many decisional parameters and it usually requires consideration of numerous sources of uncertainty. Many conventional processes of supply chain design involve taking a deterministic approach, using point estimates, on important measures of supply chain effectiveness such as cost, quality, delivery reliability and service levels. Supply chain disruptions are often separately considered as risks, both in the research literature and in practice, meaning that a purely traditional risk management and risk minimization approach is taken. We have developed and applied an approach that combines the intellect and experience of the supply chain designer with the power of evaluation provided by a Monte Carlo simulation model, which uses decision analysis techniques to explicitly incorporate the full spectrum of uncertain quantities across the set of alternative supply chain designs being considered. After defining and setting out the general decision variables and uncertainty factors for 16 distinct supply chain design decision categories, we then apply that approach to combine the decision-makers' heuristics with the probabilistic modeling approach, iteratively, to achieve the best of both elements of such an approach. This novel approach to fully integrating performance and risk elements of supply chain designs is then illustrated with a case study. Finally, we call for further developmental research and field work to refine this approach.