近年受人工智慧（Artificial Intelligence, AI）、高效能運算（High Performance Computing, HPC）、先進封裝與智慧製造帶動，大型自動化系統需求持續增加；惟此類專案具高客製化、長交期與高資本投入等特性，執行階段常發生工期延遲、規格變更與驗收爭議。研究者於實務中發現，許多專案風險並非於執行階段才產生，而是於投標前即已隱藏於客戶之工作說明書（Statement of Work, SOW）、需求建議書（Request for Proposal, RFP）與採購規範文件之中。
有鑑於此，本研究以大型自動化系統專案為研究對象，探討企業如何透過投標前 SOW／RFP 規範分析與前端接單治理能力，建立系統化之風險辨識與評估機制，以提升接單品質與專案獲利品質。
本研究採單一個案研究法與專家訪談法，以 M 公司為研究個案，整合業務、專案管理、技術、法務與供應鏈等跨職能觀點，建構投標前風險分類架構與風險評分模型；理論上以資源基礎理論為主軸，輔以動態能力理論與企業風險管理觀點。
研究發現，大型自動化專案之高風險條款多數可於 SOW／RFP 文件中被具體辨識，前端接單治理能力對企業之接單品質與專案獲利品質具關鍵影響（完整發現與管理意涵詳見第五章）。本研究可作為大型自動化系統整合企業建立投標前風險治理機制之管理參考，並補足前端接單治理領域之研究缺口。

Driven by artificial intelligence, high performance computing, advanced packaging and smart manufacturing, demand for large-scale automation systems has expanded rapidly. Projects of this kind are highly customized, technically integrated, capital intensive and long in duration, and their execution is frequently disrupted by schedule delays, specification changes, acceptance disputes and cost overruns. This study argues that such risks are not created during execution: they are already embedded, before bidding, in the client's Statement of Work (SOW), Request for Proposal (RFP) and procurement specifications. Taking Company M, a listed Taiwanese automation system integrator, as a single case and drawing on cross-functional expert interviews, the study constructs a pre-bid risk scanning mechanism comprising high-risk clause identification, a seven-category risk taxonomy, a Risk Score model, a Bid/No-Bid governance framework and a red-yellow-green control mechanism. Applied to three de-identified projects, the model's risk gradings were directionally consistent with realized outcomes; reflection on the one case it under-scored led to the introduction of a Customer Governance Factor. Because the three cases were scored retrospectively, this exercise is a proof of concept for the model's operating logic rather than a test of predictive validity. The study argues that front-end order-taking governance, alongside order volume, may play an important role in the profitability quality of large project-based enterprises.

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