直播电商决策路径的SICAS模型优化与产教实践研究

Optimization of the SICAS Model for Live Streaming E-Commerce Decision Paths and Industry-Education Practice Research

摘要: 数字经济时代催生直播电商的繁荣，也对消费者行为理论的迭代创新提出了迫切需求。针对经典SICAS模型在阐释直播电商数据驱动与网络效应方面的局限性，本文构建数据–社交双循环增强型SICAS模型。该模型通过引入数据赋能循环与社交裂变循环两大核心机制，提升了其对直播电商非线性、动态化决策路径的解释力。更进一步，本文将这一商业模型升华为方法论，从中提炼出“场景化–数据化–社交化”三位一体的人才培养新范式，为高等教育体系的产教融合改革提供了一条可迁移、可复用的创新路径。研究成果首要地为直播电商的高效运营与范式演进提供了创新的理论框架与实践指引，同时将其升华为方法论，为破解数字经济中人才供给与产业需求的结构性矛盾提供一种探索性的理论框架。

Abstract: The era of digital economy has fostered the prosperity of live-streaming e-commerce and also urgently demanded the iterative innovation of consumer behavior theory. Addressing the limitations of the classic SICAS model in explaining the data-driven and network effects of live-streaming e-commerce, this paper constructs an enhanced SICAS model with a dual-cycle of data and social interaction. By introducing two core mechanisms—the data empowerment cycle and the social virality cycle—this model improves its explanatory power for the nonlinear and dynamic decision-making paths in live-streaming e-commerce. Furthermore, the paper elevates this business model into a methodology, distilling a new paradigm for talent cultivation known as the “scenario-based, data-driven, and socialized” trinity. This provides a transferable and reusable innovative pathway for the integration of industry and education in the higher education system. The research findings primarily offer an innovative theoretical framework and practical guidance for the efficient operation and paradigm evolution of live-streaming e-commerce, while also elevating it into a methodology to systematically address the structural mismatch between talent supply and industrial demand in the digital economy.