摘要：In this issue, the editor will introduce the background of the journal article “When Triple-A Supply Chains Meet Digitalization: T

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本期推文小编将从思维导图、精读内容、知识补充三个方面为大家介绍期刊论文《When Triple-A Supply Chains Meet Digitalization: The Case of JD.com’s C2M Model》的背景。

In this issue, the editor will introduce the background of the journal article “When Triple-A Supply Chains Meet Digitalization: The Case of JD.com’s C2M Model” from three aspects: mind mapping, intensive reading content, and knowledge supplement.

一、思维导图（Mind mapping）

二、精读内容（Intensive reading content）

1、Triple-A框架（Triple-A framework）

Lee（2004）在《哈佛商业评论》中提出“Triple-A供应链”概念，认为敏捷性（Agility）、适应性（Adaptability）与一致性（Alignment）是企业获得持续竞争优势的三大支柱。该框架在提出之初，着重解决全球化与市场不确定性背景下的供应链效率与响应问题。然而，随着经济数字化进程的加快，企业所面临的挑战已从传统的成本控制转向数据驱动下的柔性协同与可持续创新。数字技术不仅改变了信息获取方式，也重塑了Triple-A的内涵，使其成为连接数据智能与运营决策的桥梁。

Lee (2004) introduced the "Triple-A Supply Chain" concept in the Harvard Business Review, arguing that agility, adaptability, and alignment are the three pillars for companies to gain a sustainable competitive advantage. Initially, this framework focused on addressing supply chain efficiency and responsiveness in the context of globalization and market uncertainty. However, with the acceleration of economic digitalization, the challenges facing companies have shifted from traditional cost control to data-driven flexible collaboration and sustainable innovation. Digital technologies have not only changed the way information is accessed but have also reshaped the meaning of Triple-A, making it a bridge connecting data intelligence and operational decision-making.

2、供应链的数字化变革（Digital transformation of the supply chain）

近年来，数字化、智能化与大数据分析的兴起，使供应链管理从“经验驱动”转向“数据驱动”。以往企业依赖销售历史和市场调研进行需求预测，如今则能通过消费者的搜索、点击与评论等行为数据实现更高精度的预测。人工智能与机器学习算法的应用，使企业能够识别潜在需求趋势、优化生产计划、精准匹配库存结构。数字化不仅提升了信息透明度，也缩短了决策链条，从而在复杂环境中维持供应链的灵活性与稳健性。这种变革为Triple-A框架注入了新的技术内涵：敏捷性体现在数据响应速度上，适应性体现为算法优化能力，一致性则体现在跨环节数据共享与协同机制中。

In recent years, the rise of digitalization, intelligentization, and big data analytics has shifted supply chain management from "experience-driven" to "data-driven." Previously, companies relied on sales history and market research for demand forecasting; now, they can achieve more accurate forecasts through consumer behavioral data such as searches, clicks, and reviews. The application of artificial intelligence and machine learning algorithms enables companies to identify potential demand trends, optimize production plans, and precisely match inventory structures. Digitalization not only improves information transparency but also shortens the decision-making chain, thereby maintaining the flexibility and robustness of the supply chain in complex environments. This transformation has injected new technological connotations into the Triple-A framework: agility is reflected in data response speed, adaptability in algorithm optimization capabilities, and consistency in cross-link data sharing and collaboration mechanisms.

3、推拉机制与延迟差异化（Push-pull mechanism and latency differentiation）

供应链管理的核心在于推式与拉式机制的平衡。推式供应链追求规模化与成本效率，而拉式供应链强调快速响应与灵活性。Lee与Tang（1997）提出的“延迟差异化”理念，为两者提供了协调路径——通过标准化模块和生产流程的延后，将定制化环节推迟至需求明确之后，从而兼顾成本与响应速度。随着数字技术的发展，供应链能够基于实时数据动态调整推拉边界，形成“数据驱动的延迟差异化”。这种机制不仅提升了整体运营效率，也强化了Triple-A框架中“敏捷”与“适应”的双重能力，使供应链在波动环境中仍能实现稳定协调。

The core of supply chain management lies in balancing push and pull mechanisms. Push supply chains pursue scale and cost efficiency, while pull supply chains emphasize rapid response and flexibility. Lee and Tang (1997) proposed the concept of "delayed differentiation," providing a path for coordination between the two—by postponing standardized modules and production processes, customized steps are delayed until demand is clear, thus balancing cost and response speed. With the development of digital technology, supply chains can dynamically adjust push-pull boundaries based on real-time data, forming "data-driven delayed differentiation." This mechanism not only improves overall operational efficiency but also strengthens the dual capabilities of "agility" and "adaptability" within the Triple-A framework, enabling stable coordination of the supply chain even in volatile environments.

4、信息时滞的缩短（Shortening of information delay）

过去全球化导致的供应链延伸往往带来信息滞后与协调困难，而数字化手段显著改变了这一局面。物联网、云计算与区块链等技术的应用，使信息流能够在全球范围内实现实时共享。尽管物理运输距离可能仍然较长，但信息流的即时性有效降低了预测误差和协同成本。企业可借助数字可视化平台实现库存动态监控、供应异常预警及多节点协同决策，从而在时滞缩短的同时提升韧性与响应速度。这种信息流优化不仅强化了供应链的敏捷性，也为企业在数字时代实现高水平一致性奠定了基础。

In the past, globalization-driven supply chain extensions often led to information lags and coordination difficulties, but digitalization has significantly changed this situation. The application of technologies such as the Internet of Things (IoT), cloud computing, and blockchain enables real-time information sharing globally. Although physical transportation distances may still be long, the immediacy of information flow effectively reduces forecasting errors and coordination costs. Enterprises can leverage digital visualization platforms to achieve dynamic inventory monitoring, supply anomaly alerts, and multi-node collaborative decision-making, thereby improving resilience and responsiveness while reducing time lags. This optimization of information flow not only strengthens supply chain agility but also lays the foundation for enterprises to achieve a high level of consistency in the digital age.

5、C2M模式的兴起（The rise of C2M model）

在数字化背景下，消费者对制造商（C2M）模式成为供应链创新的新方向。该模式通过电商平台建立消费者与制造端的直接连接，消费者需求数据能够实时传递至生产环节，从而实现反向定制与柔性制造。以京东和拼多多为代表的平台企业，分别通过数据挖掘与社交化团购机制，将海量消费信息转化为可操作的制造信号，极大提升了需求响应速度与资源配置效率。C2M模式不仅体现了数字化供应链的敏捷与适应，也展示了一致性的新形态——数据驱动下的多主体协同。它将Triple-A框架的三要素统一于数据闭环中，为数字经济时代的供应链提供了新的解释路径。

In the digital age, the Consumer-to-Manufacturer (C2M) model has emerged as a new direction for supply chain innovation. This model establishes a direct connection between consumers and manufacturers through e-commerce platforms, enabling real-time transmission of consumer demand data to the production process, thus achieving reverse customization and flexible manufacturing. Platform companies like JD.com and Pinduoduo, through data mining and social group-buying mechanisms, respectively, transform massive amounts of consumer information into actionable manufacturing signals, significantly improving demand response speed and resource allocation efficiency. The C2M model not only embodies the agility and adaptability of the digital supply chain but also demonstrates a new form of consistency—data-driven multi-entity collaboration. It unifies the three elements of the Triple-A framework within a data closed loop, providing a new interpretive path for the supply chain in the digital economy era.

三、知识补充（Knowledge supplementation）

1、延迟差异化（Delayed differentiation）

延迟差异化是供应链管理中的一种灵活生产与库存策略，其核心思想是：企业在生产早期仅制造标准化、通用性的基础产品或模块，而将具体型号、功能、颜色、包装等差异化处理环节延后到收到客户订单或市场需求更加明确之后再进行。这样做的目的是在保持一定规模经济的同时，降低预测错误导致的库存风险和滞销成本，并提升企业应对需求波动的灵活性。延迟分化通过推迟最终定制点，使供应链从“以预测驱动”向“以需求驱动”转变，从而在成本与响应速度之间实现平衡。

Delayed differentiation is a flexible production and inventory strategy in supply chain management. Its core idea is that companies manufacture only standardized, general-purpose basic products or modules in the early stages of production, while postponing the differentiation processes—such as specific models, functions, colors, and packaging—until customer orders are received or market demand becomes clearer. The aim is to maintain economies of scale while reducing inventory risk and unsold costs due to forecasting errors, and improving the company's flexibility in responding to demand fluctuations. By delaying the final customization point, delayed differentiation shifts the supply chain from "forecast-driven" to "demand-driven," thereby achieving a balance between cost and response speed.

2、敏捷供应链（Agile supply chain）

敏捷供应链通常是指基于供应链整合的快速响应型物流体系，即所谓的敏捷物流。它以供应链成员的协同整合为基础，借助信息技术与业务流程的融合，构建出高效的快速反应机制。其主要特征体现在动态企业联盟的形成、供应链运行的可视化、信息技术的深层次应用以及外包策略的优化。通过连接供应商、制造商与终端消费者等环节，该模式构建起协同化的功能网络，以战略联盟的形式应对市场环境的波动。同时，利用延迟策略和VMI库存管理等方法，实现物流过程的时间压缩与资源配置优化。与传统物流模式相比，敏捷物流更强调反应速度和客户需求的契合度，特别是在电子商务及大规模定制场景中表现出明显的竞争优势。

Agile supply chain typically refers to a rapid-response logistics system based on supply chain integration, also known as agile logistics. It is based on the collaborative integration of supply chain members, leveraging the integration of information technology and business processes to build an efficient and rapid response mechanism. Its main characteristics are reflected in the formation of dynamic enterprise alliances, visualization of supply chain operations, deep application of information technology, and optimization of outsourcing strategies. By connecting suppliers, manufacturers, and end consumers, this model builds a collaborative functional network, responding to market fluctuations through strategic alliances. Simultaneously, it utilizes delay strategies and VMI (Vendor Managed Inventory) methods to achieve time compression and resource allocation optimization in the logistics process. Compared to traditional logistics models, agile logistics places greater emphasis on responsiveness and alignment with customer needs, demonstrating a significant competitive advantage, particularly in e-commerce and mass customization scenarios.

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翻译：Google翻译

参考资料：百度、Chatgpt

参考文献： Ho Yinmak, Zuo Junmaxshen. When triple‐A supply chains meet digitalization: The case of JD. com's C2M model [J]. Production and Operations Management, 2021, 30(3): 656-665.

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