Collaborative Research: Behavioral Causes of Information Distortion in Supply Chains

合作研究：供应链中信息失真的行为原因

• 批准号: 0214337
• 负责人: Elena Katok
• 金额: $ 7.29万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2004-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0214337&HistoricalAwards=false
• 关键词: Collaborative; Research; Behavioral; Causes; Information

Managing a supply chain has been shown to be prone to systematic errors that often lead to spectacularly dysfunctional outcomes. For example, the drilling for oil and gas fluctuates three times more than the actual petroleum production, the demand for machine tools is at least twice as variable as automobile sales (the auto industry being the main consumer of machine tools), and the production of semiconductors is much more variable than industrial production as a whole (reported in Sterman 2000, pp. 666-667). This pattern of "oscillation, amplification, and phase lag," known collectively as the bullwhip effect, has been also noted in individual firms' supply chains (see Lee et al. 2000), as well as in the laboratory Sterman (1989). Sterman's results demonstrated that individuals do not act optimally even in the relatively simple laboratory setting, but significantly underweight inventory they already ordered that has not yet arrived (called the supply line). He concluded, "the key to improved performance lies within the policy individuals use to manage the system and not in the external environment. Even a perfect forecast will not prevent a manager who ignores the supply line from over ordering." (Sterman 1989, p. 336).The bullwhip effect is costly because it causes excessive inventories, poor customer service, and unnecessary capital investment. We separate explanations of the causes of the bullwhip effect into those that rely on participants' own cognitive limitations, their inability to determine the optimal way to adjust their inventory position, and those that rely on coordination, participants' beliefs about others' abilities or actions. The experiments we propose to conduct will be using both traditional supply chains with four participants and supply chains where a human participant plays one of the roles, and the other three roles are played by computerized agents programmed (and known) to act optimally. If deviations from optimal behavior are caused by an individual's cognitions, behavior should be the same in the treatments with all human subjects as with one human subject. If instead, behavior is being caused by an individual's beliefs about the decisions his supply chain partners make, behavior should be worse in treatments with all human subjects.The results from our study can have potentially broad implications on the type of decision support tools that should be included in Enterprise Resource Planning (ERP) software. If behavioral causes of the bullwhip effect are important than the recent focus on reducing operational causes provides at best an incomplete solution. The question of what information or tools can be effective in mitigating behavioral causes of the bullwhip effect has not been addressed in the literature, and it is our hope that this study will open the door to this new research agenda.

事实证明，管理供应链很容易出现系统性错误，而这些错误往往会导致严重的功能失调结果。 例如，石油和天然气钻探的波动是实际石油产量的三倍，机床的需求波动至少是汽车销售的两倍（汽车工业是机床的主要消费领域），半导体比整个工业生产的可变性要大得多（Sterman 2000 年报告，第 666-667 页）。 这种“振荡、放大和相位滞后”模式，统称为牛鞭效应，在各个公司的供应链中（参见 Lee 等人，2000 年）以及 Sterman 实验室（1989 年）中也有所体现。 斯特曼的结果表明，即使在相对简单的实验室环境中，个人也不会采取最佳行动，而是会严重低估他们已经订购但尚未到达的库存（称为供应线）。 他总结道：“提高绩效的关键在于个人用于管理系统的政策，而不是外部环境。即使是完美的预测也无法阻止忽视供应线的管理者过度订购。” （Sterman 1989，第 336 页）。牛鞭效应的成本高昂，因为它会导致库存过多、客户服务不佳以及不必要的资本投资。 我们将牛鞭效应的原因分为两类：一类是依赖于参与者自身的认知限制，即他们无法确定调整库存位置的最佳方式；另一类是依赖于协调，即参与者对他人能力或行为的信念。 。 我们建议进行的实验将使用具有四个参与者的传统供应链和其中人类参与者扮演其中一个角色的供应链，而其他三个角色由经过编程（并且已知）以最佳方式执行的计算机代理扮演。 如果偏离最佳行为是由个体认知引起的，则所有人类受试者的治疗行为应与一名人类受试者的行为相同。 相反，如果行为是由个人对其供应链合作伙伴做出的决策的信念引起的，那么在对所有人类受试者进行治疗时，行为应该会更糟。我们的研究结果可能会对决策支持工具的类型产生潜在的广泛影响。纳入企业资源规划 (ERP) 软件。 如果牛鞭效应的行为原因很重要，那么最近对减少操作原因的关注最多只能提供一个不完整的解决方案。 文献中尚未解决哪些信息或工具可以有效减轻牛鞭效应的行为原因的问题，我们希望这项研究将为这一新的研究议程打开大门。