数字经济背景下，搭建工业互联网平台以推动新质生产力发展尤为重要。结合组态视角与复杂性关系理论，采用混合QCA和空间回归方法构建复杂中介模型，深入探究数据要素视角下工业互联网平台如何驱动新质生产力发展。研究发现：多种工业互联网平台组态能充分释放数据要素价值（数据要素应用、数据要素维护、数字人才集聚），进而驱动新质生产力发展，具体表现为云服务—核心平台驱动型、边缘—大数据平台驱动型和全平台驱动型3种模式。研究结论对全面推进平台化战略、加速新质生产力发展具有重要启示。

In the context of digital China, how to build a strong industrial internet platform to promote the development of new quality productive forces is particularly important. As the product of the deep integration of digitalization and industrialization under the new industrial revolution, the industrial internet platform can realize the ubiquitous connection, flexible supply, and intelligent decision-making of manufacturing resources and is a strategic infrastructure to accelerate the formation of new quality productive forces. At present, how to build an effective industrial internet platform architecture to bridge the gap in the use of data elements and promote the development of new quality productive forces is a key problem to be solved.
This study selects 278 cities in China as research samples, and employs a mixed-methods approach, integrating qualitative comparative analysis with regression analysis, to develop a sophisticated mediation model. This methodology is designed to provide a comprehensive view of the intricate interactions among variables. The study combines the relationship between configuration perspective and complexity, and uses mixed QCA and spatial regression analysis methods to analyze how the industrial internet platform drives the development of new quality productive forces from the perspective of data elements in a more granular manner. The results show that (1) the configuration analysis shows that all industrial internet platforms fully release the value of data elements in the way of "different paths lead to the same goal". Specifically, there are six paths for data element application, which can be classified into three modes: cloud service-core platform-driven, edge computing-driven, and edge-cloud service-core platform-driven. There is only one path for data element maintenance, which is platform driven. While there are four paths for the aggregation of digital talents, which can be classified into three modes: edge-big data platform-driven, distributed platform-driven under non-high cloud services, and distributed platform-driven under non-high data. (2) The complex intermediary mechanism shows that the four configurations of cloud service-core platform-driven, full platform-driven, and edge-big data platform-driven fully unleash the value of data elements, thereby driving the development of new quality productive forces. However, due to some incomplete architectures, while improving data elements, there are still difficulties in enterprise cloud migration, inflexible platform architecture, and low data utilization efficiency, which is insufficient to achieve a qualitative enhancement in productivity.
The article's marginal contributions are threefold. First, it pioneers a shift in focus from viewing industrial internet platforms as monolithic entities to recognizing them as collaborative ecosystems of sub-platforms, driving the evolution of new quality productive forces. This approach significantly diverges from traditional research, thereby broadening the scope and application range of digital platform studies. Second, it innovatively introduces the perspective of data elements, combines the relationship between configuration ideas and complexity, and reveals the complex relationship between the configuration of industrial internet platform and the development of new quality productive forces in a more granular way, which has important practical significance for the development of new quality productive forces in China under the complex system view. Third, this study develops a hybrid method of QCA and spatial regression analysis, providing new ideas and methods for analyzing complex mediation problems and expanding the statistical applications of complex mediation models in digital contexts.
The management implications are as follows:First, from the perspective of complex systems, it is necessary to grasp the "diversity of platforms" and "concentration of combinations" to avoid the development dilemma of constructing a single platform. Second, it is imperative to expedite the ongoing cycle of data element accumulation, application, maintenance, and development. This proactive management of data elements will empower industrial internet platforms and their applications to extend their reach into a broader range of industries and domains. Third, it is essential to adhere to the concept of the system, focus on the grand strategy of "digital China" ,and advance the convergence and integration of policies related to industrial Internet, digital transformation and the development of new quality productive forces.