数字化赋能的多元主体联合创新团队适应机制研究
Research on the Adaptive Mechanism of Multi-Subject Joint Innovation Team Empowered by Digital Platforms

突破关键核心技术领域被“卡脖子”的难题，迫切需要政产学研用多方主体通过融通创新开展跨组织协作。然而，联合创新团队往往面临认知定位模糊、结构机制割裂与协同难度大等适应性“梗阻”。数字经济背景下，工业互联网平台、云平台与生态创新中心等数字平台正成为关键核心技术攻关的重要组织基础设施。基于此，本文选取海尔、阿里、华为三家领军企业的联合创新数字平台实践为案例样本，运用程序性扎根理论进行多案例比较分析。研究发现：数字化赋能的多元主体联合创新团队三类适应机制。行为机制体现为借助数据识别与平台化匹配实现“目标–任务–资源”的快速对齐；动力机制体现为以平台生态治理为基础，推动技术、资金、人才等要素跨主体流动并实现共生耦合；认知机制体现为通过敏捷迭代与团队学习将显性规则与隐性共识沉淀为可复制的方法论，进而优化前两类机制。本文从数字化视角揭示数字平台与数据要素嵌入并强化联合创新团队的适应过程，为提升跨主体协作效率与创新绩效提供理论框架与实践启示。
Breaking through the bottlenecks in key core technology fields, which are often constrained by critical dependencies, urgently requires multi-stakeholder collaboration involving government, industry, academia, research institutions, and end-users through integrated innovation. However, joint innovation teams frequently face adaptive “obstructions”, such as unclear cognitive positioning, fragmented structural mechanisms, and high coordination difficulty. In the context of the digital economy, digital platforms such as industrial Internet platforms, cloud platforms, and ecosystem innovation centers are becoming essential organizational foundations for tackling key core technologies. Based on this, this paper selects the joint innovation practices of three leading companies—Haier, Alibaba, and Huawei—as case samples and applies procedural grounded theory for a comparative multi-case analysis. The study finds three types of adaptive mechanisms in multi-subject joint innovation team enabled by digital platforms. Behavioral mechanisms are reflected in the rapid alignment of “goals–tasks–resources” through data-driven identification and platform-based matching; motivational mechanisms are manifested in cross-stakeholder flow and symbiotic coupling of technology, capital, talent, and other elements based on platform ecosystem governance; cognitive mechanisms are demonstrated by embedding explicit rules and implicit consensus into replicable methodologies through agile iteration and team learning, thereby optimizing the first two types of mechanisms. From a digital perspective, this paper reveals how digital platforms and data elements are embedded to strengthen the adaptation processes of joint innovation teams, providing theoretical explanations and practical insights for improving cross-stakeholder collaboration efficiency and innovation performance.