隨著雲端服務、資料中心與高密度運算基礎設施的發展，伺服器技術創新已難以再以單一企業或單一硬體類別充分解釋，而是涉及硬體設備、軟體、網路通訊、儲存、雲端服務與系統整合等多類行動者之間的知識互動。基於創新生態系統理論，本研究將伺服器產業中的專利引證關係視為可觀察的知識網絡，探討此一知識網絡是否呈現多行動者相互依賴與結構分工，是否存在跨群體的核心與橋接位置，以及知識主幹是否隨時間形成與演化等特徵。
本研究以 2001 至 2025 年美國專利資料為基礎，先以特定 IPC 類別與伺服器相關關鍵字界定產業專利母體，據以建立 top 300 申請實體分析清單、組織家族層級行動者對應、產業群組與 NAICS 分類，並以 focal-window 設計觀察 2006 至 2020 年間專利引證網絡的承前啟後結構。方法上，本文整合結構位置與中心性分析、Gould and Fernandez 中介角色模型、SPLC 主路徑分析，以及 actor-level cross-entity backbone analysis，分別檢視伺服器創新生態系統知識網絡中的核心行動者、跨群體橋接者、patent-level knowledge backbone 與跨實體知識通道。
研究結果顯示，伺服器專利引證網絡並非由單一企業或單一產業群組線性主導。首先，Hardware Equipment 長期構成重要知識基礎，但 Software、ISP、Computer Systems Design and Related Services 與其他群組亦在不同時期占據可觀察的結構位置、扮演中介角色。其次，中心性位置、brokerage role 與 knowledge backbone 並不完全重疊，顯示伺服器創新生態系統中的「核心」、「橋接」與「主幹」應視為不同但相互關聯的網絡面向。再次，patent-level backbone 呈現伺服器技術路徑在可觀察期間的形成，以及與階段性收斂一致的趨勢；而排除同一實體內部引用後的 actor-level cross-entity backbone 則進一步顯示，部分軟體、雲端服務與基礎設施相關行動者在跨實體知識通道中具有重要位置，惟此一結果高度集中於少數虛擬化相關行動者，並對實體與組織家族的界定較為敏感。
本研究回應既有創新生態系統研究偏重概念與個案、而專利引證網絡研究較少同時整合結構位置、中介角色與知識主幹分析之缺口。理論上，本文將創新生態系統中的 actors、artifacts 與 relations 分別操作化為專利申請實體、作為技術知識人工物的專利及其 IPC 技術分類，以及專利引證關係，說明創新生態系統可如何在知識關係層被觀察。方法上，本文以 Structure、Brokerage 與 Knowledge Backbone 三軸架構整合中心性、中介角色與 SPLC 主路徑分析，避免將核心位置、橋接功能與主幹路徑混為同一種影響力。經驗與實務上，本文提供伺服器產業的量化知識網絡案例，有助於辨識不同組織家族與產業群組在專利知識互動中的結構位置與跨實體通道。然而，本文所觀察的是美國專利引證資料所呈現的知識關係層，並未直接測量完整商業合作、供應鏈治理、平台策略或市場績效。

With the growth of cloud services, data centers, and high-density computing infrastructure, innovation in server technologies can no longer be sufficiently explained by a single firm or a single hardware category. It involves knowledge interactions among multiple types of actors, including hardware equipment providers, software firms, network communication firms, storage providers, cloud service providers, and system integrators. Drawing on the innovation ecosystem perspective, this thesis treats patent citations in the server industry as an observable knowledge network and examines whether this knowledge network exhibits multi-actor interdependence and structural division of roles, whether core and cross-group brokerage positions emerge, and whether a knowledge backbone forms and evolves over time.
This study uses U.S. patent data from 2001 to 2025, delimiting the server-industry patent corpus through selected IPC classes and server-related keywords. On this basis it constructs a top 300 patent-applicant analysis list, organization-family-level actor mappings, industry group classifications, and NAICS classifications. A focal-window design is used to observe the forward- and backward-looking structure of patent citation networks from 2006 to 2020. Methodologically, the thesis integrates structural position and centrality analysis, the Gould and Fernandez brokerage role model, SPLC-based main path analysis, and actor-level cross-entity backbone analysis. These methods are used to examine core actors, cross-group brokers, patent-level knowledge backbones, and cross-entity knowledge channels within the knowledge network of the server innovation ecosystem.
The findings show that the server patent citation network is not linearly dominated by a single firm or a single industry group. Hardware Equipment remains an important knowledge base, but Software, ISP, Computer Systems Design and Related Services, and other groups also occupy observable structural and brokerage positions at different stages. The results further show that centrality, brokerage roles, and knowledge backbone positions do not fully overlap. Thus, "core," "brokerage," and "backbone" should be understood as distinct but related network dimensions. Patent-level backbone analysis indicates the formation of major technological paths and a consolidation trend consistent with stage-wise convergence within the observable period, while actor-level cross-entity backbone analysis, after excluding same-entity citations, further identifies software, cloud service, and infrastructure-related actors that occupy important positions in cross-entity knowledge channels. This cross-entity result is, however, concentrated in a small number of virtualization-related actors and is sensitive to how entities are aggregated into organization families.
This thesis addresses a gap between innovation ecosystem studies that often remain conceptual or case-based and patent citation network studies that rarely integrate structural position, brokerage roles, and knowledge backbone analysis in a single design. Theoretically, it operationalizes the actors, artifacts, and relations of an innovation ecosystem as patent applicants, patents (as technical knowledge artifacts) together with their IPC classifications, and patent citation relations, showing how an innovation ecosystem can be observed at the knowledge-relation layer. Methodologically, it integrates centrality analysis, brokerage role analysis, and SPLC-based main path analysis through a three-axis framework of Structure, Brokerage, and Knowledge Backbone, thereby distinguishing core position, bridging function, and backbone participation. Empirically and practically, it provides a quantitative knowledge-network case of the server industry and identifies the structural positions and cross-entity channels of different organization families and industry groups. However, the empirical scope of the thesis is limited to the knowledge-relation layer observable through U.S. patent citation data. It does not directly measure business collaboration, supply-chain governance, platform strategy, or market performance.

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