本研究旨在探討台灣半導體產業在面對全球技術快速演進、供應鏈重組與市場需求波動等高度不確定環境下之綜合效率表現。由於半導體產業具備高度資本密集與技術密集之特性，單一財務或經營指標較難完整反映企業之資源配置效率與多階段價值轉換過程。因此，本研究以 2020 年至 2024 年間 57 家台灣上市櫃IC企業為研究樣本，運用動態併行兩階段 RDM-DEA 模型（Dynamic Parallel Two-Stage RDM-DEA Model）進行整合性跨期效率評估，探討台灣半導體企業於財務效率、經營效率與市場效率之相對表現。
本模型將企業績效評估劃分為兩階段，第一階段包含財務效率與經營效率兩個併行階段，第二階段則為市場效率階段。此外，模型納入固定資產作為跨期連結變數，以反映半導體產業重資本投資之延續特性。實證結果顯示，台灣半導體企業之五年平均總效率為 0.59，整體效率變化可與研究期間半導體產業景氣循環相互對照。在各階段效率表現上，經營效率五年平均為 0.81，高於財務效率之 0.58 與市場效率之 0.35，顯示台灣半導體企業在人力與研發投入轉化為營收及創新成果方面具相對較佳表現，但第一階段所形成之財務與經營連結變數進一步反映於市場價值時，仍存在效率落差。
此外，透過產業鏈分群交叉分析發現，不同產業鏈位置之企業在效率配置上存在差異。中游企業的市場效率相對較高且配置較為集中，而上游與下游企業則較易出現經營效率與市場效率不一致之配置型態。綜合而言，本研究可作為企業檢視財務資源配置、研發與人力投入效率、連結變數管理及市場價值產出效率之輔助參考，並提供後續半導體產業效率評估研究之延伸基礎。然而，本研究結果主要適用於 2020 至 2024 年台灣 57 家上市櫃半導體企業，且產業鏈分群係依企業主要營運屬性進行分類，未必能完全反映企業多元化或跨領域之實際營運型態。並且四象限分析主要屬於描述性觀察，尚無法直接推論各階段效率之因果關係；市場效率亦可能受到總體經濟、產業景氣、投資人預期與資本市場估值等模型外因素影響。未來研究可進一步針對效率變動幅度較大或階段效率落差明顯之企業進行個案研究，並結合相關分析、迴歸模型或其他統計方法，檢驗財務效率、經營效率、市場效率與總效率之間的關聯性。

This study aims to explore the comprehensive efficiency performance of Taiwan's semiconductor industry under highly uncertain environments, such as rapid global technological evolution, supply chain restructuring, and market demand fluctuations. Due to the highly capital-intensive and technology-intensive nature of the semiconductor industry, a single financial or operational indicator can hardly fully reflect a firm's resource allocation efficiency and multi-stage value conversion process. Therefore, this study takes 57 listed IC companies in Taiwan from 2020 to 2024 as the research sample and applies the Dynamic Parallel Two-Stage RDM-DEA Model to conduct an integrated intertemporal efficiency evaluation, exploring the relative performance of Taiwanese semiconductor companies in terms of financial efficiency, operational efficiency, and market efficiency.
The model divides corporate performance evaluation into two stages. The first stage comprises two parallel stages: "financial efficiency" and "operational efficiency," while the second stage is the "market efficiency" stage. Furthermore, the model incorporates "fixed assets" as a carry-over variable to reflect the continuity characteristics of heavy capital investments in the semiconductor industry. Empirical results show that the five-year average total efficiency of Taiwanese IC companies is 0.59, and the overall efficiency changes correspond to the business cycles of the semiconductor industry during the research period. Regarding the efficiency performance in each stage, the five-year average operational efficiency is 0.81, which is higher than the financial efficiency of 0.58 and the market efficiency of 0.35. This indicates that Taiwanese IC companies perform relatively well in transforming human resources and R&D inputs into revenues and innovation outcomes; however, an efficiency gap still exists when the financial and operational link variables formed in the first stage are further reflected in market value.
Furthermore, the cross-analysis of industry chain groups shows that firms in different positions of the industry chain differ in their efficiency allocation patterns. Midstream firms exhibit relatively higher market efficiency and more concentrated efficiency distribution, while upstream and downstream firms are more likely to show inconsistent allocation patterns between operational efficiency and market efficiency.
Overall, this study may serve as a supplementary reference for firms to examine financial resource allocation, R&D and human resource input efficiency, link variable management, and market value output efficiency. It also provides a basis for future extended research on efficiency evaluation in the semiconductor industry.

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