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配，其中链长（通常是零售商等最终买家）主导了供应商关系。结果，风险被推到了较低级别的公司，这些公司必须应对增加的不确定性，因此，风险被推到了必须承担所需灵活性负担的工人身上。在比较优势原则驱动下的全球供应链找到了通往低层企业能够通过强迫劳动做法降低成本结构的网络。全球供应链的权力关系和碎片化要求采取共同责任的方法，涉及利益相关者的参与和影响。英国现代奴隶制法案正式赋予消费者在消除现代奴隶制中的关键作用，不仅通过实际需求，而且作为代表社会政治场景中其他利益相关者的关键利益相关者[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为的情境（例如行为偏见和社会影响）和心理（例如中立和合法化）障碍，评估消费者群体的特征，识别影响因素，并制定针对特定群体的策略，以推动行为走向无奴隶制的世界。这些策略的实际实施在很大程度上取决于供应链网络不同级别的需求预测的准确性，其特点是具有不同聚合级别的复杂层次结构。人工智能（特别是机器学习方法）在解决现代奴隶制问题上的应用为理论和实证途径提供了众多机会。这些方法允许通过使用大量观察和属性将行为考虑因素纳入决策中。它们还证明了利用多变量数据的优势开发准确的分层预测模型的前景。