本研究以費城半導體指數 30 家成分股企業為樣本，運用 Bloomberg SPLC 供應 鏈關係數據，對 2016 至 2025 年間全球半導體供應鏈網絡結構在地緣政治衝擊下的 演變模式進行量化實證分析。研究設計四層論證架構:(一)Wilcoxon 符號秩檢定捕 捉 2018 年中美貿易戰、2020 年 COVID-19、2022 年 CHIPS Act 與 2024 年對中管 制升級等事件節點的「斷點式衝擊」;(二)Panel Regression with Cluster Standard Errors 分析地緣政治風險強度的「連續性影響」與企業類型異質性;(三)子群分析 比較純晶圓代工與整合元件製造商的差異反應;(四)Cluster Bootstrap 進行穩健性驗證。
實證結果揭示四項核心發現:第一，2018 年貿易戰後中國客戶佔比顯著上升、2022 年 CHIPS Act 後地理多元化指數顯著下降，地緣政治衝擊對供應鏈結構產生統 計顯著影響;第二，地緣政治衝擊呈現「斷點式」而非「連續性」特徵，事件研究法 與 Panel Regression 互為補充;第三，企業類型呈現顯著異質性，上游設備材料商對 GPR 的反應幅度顯著小於輕資產設計型企業;第四，重資產製造端內部Foundry 與 IDM 子群在事件反應上方向相反，解釋了組層級無顯著差異的成因。Cluster Bootstrap 兩版時間控制下 95% 信賴區間皆不跨越 0，提供高度穩健的實證證據。進一步的動 態 Panel 檢驗顯示，於控制供應鏈結構之路徑依賴後，上游設備材料商相對於中段重 資產製造端之低反應特性仍維持統計顯著(並由 10% 邊際顯著升級至 5% 顯著)， 核心異質性發現具備穩健性。
本研究在交易成本理論、供應鏈韌性理論與地緣政治經濟學三個層面提供實證貢
獻，並對「去風險化」與「全球供應鏈韌性」之間的政策張力提供實證基礎。

This study empirically examines the evolution of the global semiconductor supply chain network structure under geopolitical shocks from 2016 to 2025, using 30 constituent firms of the Philadelphia Semiconductor Index (SOX) and Bloomberg SPLC supply chain data. The research integrates four methods: Wilcoxon Signed-Rank Tests capture breakpoint shocks around the 2018 U.S.-China trade war, the 2020 COVID-19 disruption, the 2022 CHIPS Act, and the 2024 China export control escalation; Panel Regression with Cluster Standard Errors analyzes the continuous effects of geopolitical risk and firm-type heterogeneity; subgroup analysis compares foundries and integrated device manufacturers; and Cluster Bootstrap validates robustness.
Four findings emerge. First, geopolitical shocks produce significant structural impacts, including the rise in China customer share post-2018 and the decline in geographic diversification post-CHIPS Act. Second, shocks exhibit breakpoint rather than continuous characteristics. Third, upstream equipment and materials suppliers show significantly smaller responses to GPR than asset-light design-oriented firms. Fourth, foundries and IDMs exhibit opposite directional responses, explaining the absence of group-level effects. Bootstrap robustness checks confirm 95% confidence intervals do not cross zero. A further dynamic panel test, controlling for the path dependence of supply chain structure, shows that the lower responsiveness of upstream equipment and materials suppliers relative to mid-stream asset- heavy manufacturers remains statistically significant—strengthening from the 10% to the 5% level—confirming the robustness of the core heterogeneity finding.
This study contributes empirically to transaction cost theory, supply chain resilience theory, and geopolitical economics.

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