Abstract as per original application
(English/Chinese): |
In an era dominated by Big Data, China has emerged as a global leader in utilizing data-driven approaches to reshape its governance structures. One of the most notable examples of this innovation is the ongoing integration of the Social Credit System (SCS) with the Patent System, a process that began in 2022 and continues to evolve. This integration marks a significant paradigm shift in how intellectual property is regulated and protected, with far-reaching implications that extend beyond China’s borders. The merger of these two systems has given rise to two groundbreaking mechanisms: a data-informed reward and punishment system and a data-guided, tiered regulatory framework. These mechanisms are designed to address several long-standing challenges in patent administration, such as identifying fraudulent applications, combating infringement, and ensuring compliance with legal rulings.
However, the practical implementation and overall effects of these mechanisms remain largely unexplored, leaving a critical knowledge gap in our understanding of data-driven governance in intellectual property.
This research project seeks to bridge that gap by providing the first comprehensive, empirical investigation into how this integration is being realized in practice. Through in-depth qualitative fieldwork in Beijing and Guangzhou, the study will capture the nuanced realities of how these mechanisms are interpreted, implemented, and experienced by various stakeholders.
The insights generated by this study will have wide-ranging value. For policymakers, the findings will offer crucial evidence to assess the effectiveness of data-driven approaches in patent regulation, potentially informing similar initiatives in other countries. Legal scholars will benefit from a unique case study in the emerging field of “personalized law”, showcasing how big data can be used to tailor regulatory approaches to individual entities. For businesses and patent practitioners, this work will provide practical guidance on navigating this new regulatory landscape.
This project comes at a critical juncture, as the integration of the SCS and patent system is still in its formative stages. By capturing diverse stakeholder perspectives at this pivotal moment, the study can shape the future trajectory of this transformative initiative. Additionally, it also contributes to broader discussions on the intersection of technology, market regulation, and economic development.
The findings will be disseminated through two articles in leading peer-reviewed journals, a book proposal for a major academic press, and a conference bringing together academics, policymakers, and practitioners. These outputs will establish a foundational understanding of data-driven governance, informing policy discussions in this rapidly evolving field.
在大數據日益滲透治理實踐的背景下，中國逐步探索以數據驅動的方式加強制度運作。其中，社會信用體系與專利制度自2022年起開始進行的整合，成為具有代表性的制度實驗，並可能預示知識產權監管方式的新趨勢。此一整合已催生兩項新的治理機制：其一是以數據為依據的獎懲系統，其二是數據引導下的分級監管框架。這些機制旨在回應長期以來困擾知識產權行政管理的若干問題，例如不當申請的識別、侵權行為的治理，以及裁決結果的執行。然而，這些制度機制在實際運作中的表現與效果尚缺乏深入研究，顯示當前學界對知識產權數據治理仍存在重要認識空白。本研究擬就該整合進行系統性的實證分析，透過質性調查與案例觀察，探索上述機制在具體制度環境中的實踐情形，重點關注不同相關方如何理解、執行與回應這些新措施，以呈現政策落實過程中的實際面貌與複雜性。研究成果可望為當前數據治理模式下的知識產權監管提供初步經驗與實證素材。一方面，為政策制定部門提供參考資料，以評估數據應用於制度監管的可行性與限制；另一方面，亦為學術界提供一個觀察個體化監管與法律技術交錯發展的案例；同時對企業與專利實務從業者而言，也有助於理解監管環境的變化方向與應對策略。考慮到該整合尚處於初始階段，本研究希望能補足相關領域的研究空白，並對科技、法制與經濟治理之間的互動提供觀察與反思。預期研究成果將以期刊論文、專書提案及研討活動等形式發表，為後續相關討論提供資料與分析基礎。
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