平台型电商供应链协同机制研究——基于数字化转型视角

Research on the Collaborative Mechanism of Platform-Based E-Commerce Supply Chain—From the Perspective of Digital Transformation

摘要: 本文围绕数字化转型背景下平台型电商供应链协同机制展开，重点关注技术赋能与协同效能转化这一核心问题。依靠对相关文献进行综述，梳理数字化转型、供应链协同以及二者融合研究的现有状况与存在的局限，构建起“技术驱动–组织协同–价值共创”理论分析框架，在此基础上建立“线性逻辑模型 + 系统动力学模型”的整合数学模型。静态线性模型将数字化技术DT、协同机制CM、供应链绩效SCP作为核心要素，运用公式对三者之间的因果关系以及路径系数进行量化；动态系统动力学模型借助微分方程组，描绘数字化投入DI、信息共享IS等变量的正反馈循环以及演化规律。研究说明，协同效能的提升需要技术、组织、治理等多个维度的协同配合，同时识别出数据安全、系统集成、协同治理、动态适应这四类挑战对模型参数产生的负面影响，并从平台企业、供应链参与主体、政策与行业层面提出优化路径，为平台型电商供应链协同实践提供理论支持与决策指导，最后指明未来可借助数据校准、引入扰动项、纳入新兴技术等方向深入开展研究。

Abstract: This study investigates the collaborative mechanism within platform-based e-commerce supply chains against the backdrop of digital transformation, with a primary focus on the core issue of translating technological empowerment into collaborative efficacy. Through a comprehensive review of relevant literature, the paper synthesizes the current state and limitations of research on digital transformation, supply chain collaboration, and their integration. It subsequently constructs a theoretical analysis framework of “technology-driven-organizational synergy-value co-creation”. Building upon this foundation, an integrated mathematical model combining a “linear logic model + system dynamics model” is established. The static linear model identifies digital technology (DT), collaborative mechanisms (CM), and supply chain performance (SCP) as core elements, employing mathematical formulations to quantify the causal relationships and path coefficients among them. The dynamic system dynamics model utilizes a system of differential equations to depict the positive feedback loops and evolutionary patterns of variables such as digital investment (DI) and information sharing (IS). The research demonstrates that enhancing collaborative efficacy requires synergistic efforts across multiple dimensions, including technology, organization, and governance. It also identifies four categories of challenges—data security, system integration, collaborative governance, and dynamic adaptation—that negatively impact model parameters. Optimization pathways are proposed from the perspectives of platform enterprises, supply chain participants, and policy/industry levels, offering theoretical support and decision-making guidance for collaborative practices. Finally, the study outlines future research directions, including model calibration with empirical data, the introduction of disturbance factors, and the incorporation of emerging technologies.