Abstract In the context of the increasingly complex industrial competition environment globally, providing efficient and accurate competitive intelligence services has become increasingly urgent for the industrial competition and development through data empowerment, driven by multisource data and supplemented by technologies such as artificial intelligence. Therefore, exploring a systematic and multisource data-driven intelligent service mechanism for industrial competitive intelligence, creating a collaborative, systematic, and sustainable industrial competitive intelligence service environment, and ensuring the coordinated and stable operation of various service elements are urgent goals. This study adopts the semi-structured interview method to conduct in-depth interviews with working groups related to in-depth research on competitive intelligence and uses grounded theory to extract 47 initial concepts, 12 basic categories, and 4 main categories. Then, the logical relationship between categories is sorted and the function model of the intelligent service mechanism of industrial competitive intelligence driven by multisource data is finally constructed. The results indicated that the supply-and-demand coupling mechanism with demand deviation minimization - intelligence cognition maximization as the core, the collaborative guarantee mechanism with data power - intelligent technology - service ecology as the core, the linkage management mechanism with comprehensive perception - personality customization - situation guidance as the core, and the dynamic optimization mechanism with government empowerment - user energy storage - co-creation and release of energy - feedback extraction as the core form a four-in-one intelligent service mechanism system for the industrial competitive intelligence of target-core-sublimation-extension.
Zheng Rong,Wei Mingzhu,Wang Xiaoyu, et al. Intelligent Service Mechanism of Industrial Competitive Intelligence Driven by Multisource Data: Exploratory Research Based on Grounded Theory[J]. 情报学报, 2023, 42(7): 790-800.
