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Information sharing versus order aggregation strategies in supply chains

机译:供应链中的信息共享与订单汇总策略

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Purpose - The purpose of this paper is to explore how differently aggregated order data may affect inventories and service levels in a serial supply chain and compares the results against various levels of information sharing. By performing sensitivity analysis, critical parameters are identified and conjectures for explaining the divergent results on the value of information sharing in prior literature are given. Design/methodology/approach - By using discrete event simulation, the paper analyses various approaches of differently aggregated order data compared to shared demand information. Findings - The experiments show that suppliers cannot accurately estimate demand means and variances because of time-depending order quantities and biasing effects of order inter-arrival times. This may lead to inappropriate computations of reorder points and safety stocks. The aggregation of order data can improve the calculations resulting in lower inventories with almost identical service levels. The mean inventory can also be reduced by sharing information but may lead to considerably lower service levels. Research limitations/implications - As discovered in this paper, simplifications in the supply chain structure may have large effects on the experimental results. Therefore, the value of information sharing and order aggregation strategies should be analyzed in a more complex supply chain network. Practical implications - Some ordering mechanisms have the effect of increasing the demand variance for upstream companies. This amplification may lead to inefficiencies throughout the entire supply chain. The paper proposes solutions to managers on how they can benefit from order data aggregation and information sharing. The per period variances may be reduced leading to smaller safety stocks and lower costs for the entire supply chain. Originality/value - The paper shows that the performance of a supply chain may be improved by aggregating order data and compares the results with improvements derived from information sharing strategies.
机译:目的-本文的目的是探讨不同汇总的订单数据如何影响串行供应链中的库存和服务水平,并将结果与​​各个级别的信息共享进行比较。通过进行敏感性分析,确定关键参数,并给出用于解释现有文献中信息共享价值分歧结果的猜想。设计/方法/方法-通过使用离散事件模拟,本文分析了与共享需求信息相比,不同汇总订单数据的各种方法。结果-实验表明,由于时间相关的订单数量和订单到达时间的偏差影响,供应商无法准确估算需求均值和方差。这可能会导致对重新订购点和安全库存进行不正确的计算。订单数据的汇总可以改善计算结果,从而减少库存,并提供几乎相同的服务水平。通过共享信息也可以减少平均库存,但可能会导致服务水平大大降低。研究局限性/意义-正如本文所发现的那样,简化供应链结构可能会对实验结果产生重大影响。因此,应该在更复杂的供应链网络中分析信息共享和订单聚合策略的价值。实际意义-一些订购机制会增加上游公司的需求差异。这种放大可能导致整个供应链效率低下。本文向管理人员提出了有关如何从订单数据聚合和信息共享中受益的解决方案。每个期间的差异可能会减少,从而导致较小的安全库存和整个供应链的成本降低。原创性/价值-本文表明,通过汇总订单数据可以改善供应链的绩效,并将结果与​​信息共享策略带来的改进进行比较。

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