| dc.contributor.advisor | 羅明琇 | zh_TW |
| dc.contributor.author (Authors) | 蕭郁欣 | zh_TW |
| dc.contributor.author (Authors) | Hsiao, Yu-Hsia | en_US |
| dc.creator (作者) | 蕭郁欣 | zh_TW |
| dc.creator (作者) | Hsiao, Yu-Hsia | en_US |
| dc.date (日期) | 2025 | en_US |
| dc.date.accessioned | 1-Jul-2025 14:22:18 (UTC+8) | - |
| dc.date.available | 1-Jul-2025 14:22:18 (UTC+8) | - |
| dc.date.issued (上傳時間) | 1-Jul-2025 14:22:18 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0112932001 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/157691 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 經營管理碩士學程(EMBA) | zh_TW |
| dc.description (描述) | 112932001 | zh_TW |
| dc.description.abstract (摘要) | 在當今科技快速變遷的數位時代，數位轉型已成為企業提升競爭力及追求永續發展的關鍵策略。其核心概念是透過應用人工智慧（AI）、物聯網 (IoT)等技術，全面重塑企業的經營模式及組織架構。資策會產業情報研究所 (MIC)，將數位轉型劃分為三階段：首先是「數位化」，即將實體資料轉為數位格式；其次是「優化」，利用數位工具改善現有流程與服務以提升效率；最終是「轉型」，運用數位科技創造全新的產品、服務或商業模式。許多企業初期著重於系統導入等數位化工作，然而，隨著 AI 技術的飛速發展，企業的數位轉型策略應積極將 AI 作為核心驅動力，進而提升企業營運效率、建立差異化優勢，並創造新價值。
本研究以台灣知名電子代工服務 (EMS) 企業 C 公司為個案，採用深度個案研究法，旨在深入探討其自 2012 年以來的數位轉型歷程，並進一步分析其在面臨轉型瓶頸後，導入人工智慧技術作為加速轉型新動能的策略與實踐。研究呈現 C 公司從初期數位基礎建設 (2012-2017)，到中期策略建構與組織賦能 (2018-2020)，進而至數位應用擴散(2020-2024)，以及 AI 驅動深化轉型的完整轉型演進路徑。
研究結果顯示，C 公司透過自上而下的轉型推動架構、跨部門協作機制與數位人才培育制度，成功建立轉型基礎。然而，隨著轉型深化，企業亦面臨流程再造停滯、數據價值難以轉化、創新應用場景有限等挑戰。在此背景下，AI 被視為突破現況的關鍵技術。C 公司進一步將 AI 技術應用於製造、研發、供應鏈等核心業務，並設立 AI Tribe 組織與內部培訓體系，導入生成式 AI 與決策自動化，實踐從「工具導入」到「價值重構」的轉型升級。研究最終指出，AI 不僅是技術升級，更是驅動組織文化創新與流程重構的核心力量，為傳統製造業的智慧轉型提供實證與策略參考。 | zh_TW |
| dc.description.abstract (摘要) | In today's rapidly evolving digital era, digital transformation has become a critical strategy for enterprises to enhance competitiveness and pursue sustainable development. Its core concept involves comprehensively reshaping business models and organizational structures through the application of technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT). The Market Intelligence & Consulting Institute (MIC) divides digital transformation into three stages: first, "Digitization," which is the conversion of physical data into digital formats; second, "Optimization," which utilizes digital tools to improve existing processes and services to enhance efficiency; and finally, "Transformation," which employs digital technologies to create entirely new products, services, or business models. While many enterprises initially focus on digitization efforts like system implementation, with the rapid advancement of AI technology, corporate digital transformation strategies should proactively embrace AI as a core driving force to improve operational efficiency, establish differentiated advantages, and create new value.
This study employs an in-depth case study methodology to investigate Company C, a prominent Taiwanese Electronics Manufacturing Services (EMS) firm, focusing on its digital transformation journey since 2012. It further analyzes the company's strategies and practices in adopting Artificial Intelligence (AI) as a new impetus to accelerate transformation after encountering bottlenecks. The research reveals Company C's complete transformation trajectory, progressing from the initial phase of digital infrastructure construction (2012-2017), through the intermediate phase of strategy formulation and organizational enablement (2018-2020), followed by digital application expansion and traditional AI exploration (2020-2024), and AI-driven in-depth transformation.
The findings indicate that Company C successfully established a foundation for transformation through a top-down implementation framework, cross-departmental collaboration mechanisms, and digital talent development systems. However, as the transformation deepened, the company faced challenges including stagnant process re-engineering, difficulties in converting data into value, and limited opportunities for innovative application scenarios. Against this backdrop, AI emerged as the key technology to overcome these limitations. Company C further applied AI technologies to core operations such as manufacturing, R&D, and supply chain management. It established the AI Tribe organization and internal training systems, introduced Generative AI and decision automation, thereby upgrading its transformation from mere "tool adoption" to comprehensive "value reconstruction."
This research concludes that AI is not merely a technological upgrade but a core force driving organizational culture innovation and process restructuring. It provides empirical evidence and strategic references for the intelligent transformation of the traditional manufacturing industry. | en_US |
| dc.description.tableofcontents | 第一章、 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究流程 4
第二章、 產業背景與個案公司介紹 5
第一節 電子代工服務產業介紹 5
第二節 個案公司介紹 7
第三節 名辭釋義 12
第三章、 數位轉型歷程 14
第一節 數位基礎建設與製造數據化 14
第二節 策略制定與組織建立 17
第三節 數位化應用治理與擴展 21
第四節 數位轉型後期瓶頸浮現 29
第四章、 AI 驅動的轉型深化 33
第一節 AI意識醞釀與初步探索 33
第二節 AI轉型策略的全面啟動 35
第三節 AI轉型的組織架構調整 41
第四節 AI轉型應用案例與成效 45
第五章、 轉型挑戰與應對策略 52
第一節 數位轉型階段的挑戰與對應策略 52
第二節 AI轉型階段的挑戰與對應策略 56
第六章、 結論與建議 61
第一節 研究發現 61
第二節 研究貢獻 75
第三節 研究建議 77
參考文獻 78 | zh_TW |
| dc.format.extent | 2151546 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0112932001 | en_US |
| dc.subject (關鍵詞) | 數位轉型 | zh_TW |
| dc.subject (關鍵詞) | AI轉型 | zh_TW |
| dc.subject (關鍵詞) | 電子代工服務 | zh_TW |
| dc.subject (關鍵詞) | 組織變革 | zh_TW |
| dc.subject (關鍵詞) | Digital Transformation | en_US |
| dc.subject (關鍵詞) | AI Transformation | en_US |
| dc.subject (關鍵詞) | Electronics Manufacturing Services (EMS) | en_US |
| dc.subject (關鍵詞) | Organizational Change | en_US |
| dc.title (題名) | 大型電子代工服務業數位轉型與AI轉型之策略研究 – 以C公司為例 | zh_TW |
| dc.title (題名) | A Strategic Study on Digital and AI Transformation in Large Electronics Manufacturing Services (EMS) Enterprises: A Case Study of Company C | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | 1.詹文男, 李震華, 周維忠, 王義智 (2020). 數位轉型力。台北市，商周。
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