Development and Evolution of Organizational Dynamic Capabilities during Digital-Intelligence Transformation—A Case Study of AiScholar
DOI:
https://doi.org/10.55578/jedip.2511.010Keywords:
Digital-Intelligence Transformation, Dynamic Capability, Capability Building, Case Study, Scientific Research ServiceAbstract
Amidst the boom of the digital economy across the globe, one question confronts both scholars and practitioners alike: how can organisations build dynamic capabilities to achieve a successful digital-intelligence transformation? In the present work, an interpretive longitudinal case study on AiScholar, a one-stop scientific research service (SRS) platform, is performed based on the dynamic capabilities theory to investigate its decade-long journey of digital-intelligence transformation. It is revealed that successful transformation relies on a phased evolution of organizational capabilities from “operational optimization”, “integration & reconfiguration”, to “ecosystem empowerment”, with strict path dependency between each phase. Moreover, this phased evolution is driven by a dynamic combination of four mechanisms—strategic consensus guidance, experimental learning, knowledge codification, and ecosystem synergy. The integrated “phase-capability-mechanism” model proposed here unveils the intrinsic drivers of digital-intelligence transformation from a micro-process perspective, extends the application of the dynamic capabilities theory to research on digital-intelligence transformation, and provides strategic insights into the capability-building of knowledge-intensive service providers.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Copyright (c) 2025 He Wan, Bin Xie (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.