Cognitive Mapping, System Dynamics and the Bullwhip Effect

这个项目涉及牛鞭效应的问题，即当我们在供应链中向后移动时放大库存的问题。几十年来，这种效应一直在学术文献中得到强调，不可否认，它吸引了大量的科学研究。然而，所有相关项目都只侧重于数量有限的促成因素，尚未建立综合模式。尽管这些工作对于我们理解供应链的行为非常重要，但在工业应用中，这个问题仍然普遍存在。解决相关问题的支离破碎的方法很可能可以用相当大的相关复杂性来解释。也就是说，促成因素（如需求信号处理、配给/短缺博弈、订单波动和价格波动）必须被视为相互关联的组成部分（如它们在实践中的情况），而不是更广泛表述的独立问题，这显然增加了问题的理论复杂性。除非将造成这一影响的某些因素孤立出来并分别加以处理，否则无法找到分析解决办法。此外，为了便于对问题进行数学处理，需要作出许多假设，这些假设的有效性（或普遍适用性）也受到质疑。为了解决复杂的供应链/库存问题，如牛鞭效应，必须引入新的整体方法。这些复杂的问题表明了库存管理的工业重要性，以及它们的解决方案可能为现代组织提供的巨大好处。这样的解决方案需要一个跨学科的方法来制定问题和建模，这就是我们的建议所介绍的。有证据表明，系统动力学模型和认知地图的集成构成了一个非常有前途的方法，以组模型的建设，特别是适合于供应链模型与重要的行为组件。这个为期3个月的专门项目的目的是通过整合认知映射和系统动力学（存量和流量）建模，重新概念化牛鞭效应的复杂问题。这种方法除了探讨相互作用外，还考虑到行为因素。我们的研究中强调了两个这样的因素：i）预测的判断性变化和ii）补货订单的判断性变化。这两种方法在工业实践中都很普遍，它们被适当地纳入了我们的模型。除了研究这些模型在多大程度上代表现实之外，我们还打算探索它们作为那些新的判断预测的培训工具的潜力，并从长远来看，改变公司政策。

This project deals with the problem of the Bullwhip effect, i.e. that of magnifying inventories as we move backwards in a supply chain. This effect has been highlighted in the academic literature for many decades and, admittedly, it has attracted a tremendous amount of scientific research. However, all the relevant projects have focused on only a limited number of the contributory factors, with no integrative model having yet been established. Despite the importance of such work for developing our understanding of the behaviour of supply chains, the problem still prevails in industrial applications. The fragmented approach to the relevant problem solving may well be explained in terms of the considerable associated complexity. That is to say, the contributory factors (e.g. demand signal processing, rationing/shortage gaming, order batching and price fluctuations) have to be viewed as interrelated components (as they are in practice) rather than stand-alone issues of a wider formulation, and this obviously increases the theoretical complexity of the problem. Analytical solutions cannot be developed unless some of the factors that contribute to the effect are isolated and tackled separately. In addition, and in order to facilitate the mathematical treatment of the problem, many assumptions need to be made, the validity (or universal applicability) of which has also been questioned. It is viewed as imperative to introduce novel holistic approaches in order to solve complex supply chain/ inventory problems, such as the Bullwhip effect. These complex problems demonstrate the industrial importance of inventory management and the considerable benefit that their solution may offer to modern organizations. Such a solution necessitates an inter-disciplinary approach to problem formulation and modelling and this is what out proposal introduces. There is evidence to suggest that the integration of System Dynamics models and cognitive maps constitutes a very promising approach to group model building and is particularly appropriate for supply chain models with significant behavioural components. The aim of this dedicated 3-month project is to re-conceptualise the complex problem of the Bullwhip effect through the integration of Cognitive Mapping and System Dynamics (stock and flow) modelling. Such an approach allows for the consideration of behavioural factors in addition to exploring interactions. Two such factors are highlighted in our research: i) judgemental changes to forecasts and ii) judgemental changes to replenishment orders. Both have been shown to prevail in industrial practices and they are appropriately incorporated in our models. In addition to researching the extent to which such models represent reality, we also intend to explore their potential to act as a training tool for those new to judgemental forecasting and, in the longer term, to change company policies.