Understanding and modelling the impact of consumer purchasing behaviour on the global supply chains' decisions in adapting anti-slavery practices

了解消费者购买行为对全球供应链采取反奴隶制做法的决策的影响并对其进行建模

• 批准号: 2887334
• 金额: --
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2887334
• 关键词: Understanding; modelling; impact; consumer; purchasing

The growth of global supply chains has caused an asymmetrical distribution of risk and profit within the chains where chain captains - often end buyers, such as retailers - dominate supplier relationships. As a result, risk is pushed down the chain to lower-tier firms, which have to address increased uncertainties and consequently, to workers who have to shoulder the burden of required flexibility. Global supply chains driven by the principle of comparative advantage find their way to networks where lower-tier firms are able to reduce their cost structure by resorting to forced labor practices. Power relationships and fragmentation of global supply chains call for adopting a shared responsibility approach, involving participation and leverage of stakeholders.The UK Modern Slavery Act formally assigns consumer a critical role in eradicating modern slavery not only through actual demand but also as a key stakeholder who represents other stakeholders in the socio-political scene [5, 6]. The demand-side management of anti-slavery practices is still an under-researched academic field. It highlights the need to investigate the contextual (e.g. behavioral biases and social influence) and psychological (e.g. neutralization and legitimation) barriers to consumer action, assess characteristics of consumer segments, identify influential factors, and develop segment-specific strategies to nudge behavior towards a slavery free world. Practical implementation of these strategies depends highly on the accuracy of demand forecasts at different levels of the supply chain network characterized by complex hierarchies with different levels of aggregation.The application of AI, especially machine learning methods, in tackling modern slavery offers numerous opportunities for theoretical and empirical pathways. These methods allow for the incorporation of behavioral considerations into decision-making by using a large number of observations and attributes. They also prove promising for the development of accurate hierarchical forecasting models exploiting the benefit of multi-variate data.

全球供应链的增长导致了供应链内部风险和利润的不对称分布，在这些供应链中，连锁企业的负责人--通常是零售商等最终买家--主导着供应商关系。其结果是，风险沿着链条向下推至较低级别的公司，这些公司必须解决增加的不确定性，从而转嫁给不得不承担所需灵活性负担的工人。在比较优势原则的驱动下，全球供应链找到了通往网络的途径，在那里，较低级别的公司能够通过诉诸强制劳动做法来降低成本结构。权力关系和全球供应链的碎片化要求采取分担责任的方法，包括利益相关者的参与和杠杆作用。英国《现代奴隶法》正式赋予消费者在根除现代奴隶制方面的关键作用，不仅通过实际需求，而且作为代表社会政治舞台上其他利益攸关方的关键利益攸关方[5，6]。反奴隶制实践的需求方管理仍然是一个研究不足的学术领域。它强调需要调查消费者行动的背景障碍(例如行为偏见和社会影响)和心理障碍(例如中和和合法化)，评估消费者群体的特征，确定影响因素，并制定特定群体的战略，将行为推向一个没有奴隶制的世界。这些策略的实际实施高度依赖于供应链网络不同层次需求预测的准确性，供应链网络具有复杂的层次结构和不同的聚合水平。人工智能的应用，特别是机器学习方法，在解决现代奴隶制问题方面提供了大量的理论和经验路径机会。这些方法允许通过使用大量的观察和属性将行为考虑纳入决策。它们也被证明在开发利用多变量数据的准确的分层预测模型方面很有前途。