本論文探究電腦原品牌製造商W公司於COVID-19疫情引發供應鏈中斷期間（2020–2021年），策略性導入並演進混合專案管理模式之情境，該模式整合傳統瀑布式與敏捷方法論。運用單一個案研究法，輔以主題分析內部文件、半結構化訪談及關鍵績效指標，本研究闡明此等混合框架如何緩解工廠停工、半導體短缺及物流障礙等挑戰，從而提升組織韌性、加速上市時間、最適化成本效率，並強化競爭定位。主要發現突顯混合模式於動盪環境中之效能，並提出營收連結透明專案管理框架，以促進營收導向之透明度。此外，本研究論述人工智慧之應用於預測分析、代理式自動化及人機協同工作流程，以鞏固未來供應鏈韌性。理論意涵豐富既有專案管理學術文獻，實務意涵提供製造業之操作範式，而政策洞見倡議人工智慧部署之倫理準則，並建議後續多案例實證驗證。

This dissertation aims to explore the strategic deployment and development of hybrid program management models, which combine traditional waterfall and agile methodologies, within the specific setting of Personal Computer (PC) Original Brand Manufacturer (OBM) Company W during the supply chain disruptions caused by the COVID-19 pandemic between 2020 and 2021. Through the utilization of a case study approach enhanced by thematic analysis of internal records, semi-structured interviews, and key performance indicators, this investigation clarifies how these hybrid frameworks addressed and improved challenges such as factory closures, shortages of semiconductor components, and logistical obstacles. Consequently, these actions enhanced the resilience of the organization, accelerated product launch times, optimized cost-effectiveness, and enhanced competitive positioning. The primary outcomes highlight the effectiveness of hybrid models in unpredictable environments, leading to the formulation of the Revenue-Linked Transparent Program Management Framework (RLTPMF) to promote transparent management focused on revenue. Additionally, the study discusses the integration of artificial intelligence for predictive analysis, autonomous decision-making, and collaborative human-artificial intelligence (AI) processes to strengthen future supply chain resilience. Theoretical implications contribute to the existing body of knowledge on program management, practical insights offer operational strategies for manufacturing firms, and policy recommendations advocate ethical standards for AI deployment, proposing avenues for subsequent empirical validation through multiple case studies.

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