臺灣博碩士論文加值系統

本研究聚焦人工智能於醫學影像輔助診斷服務之商業模式分析，應用創新密集服務分析模式(Innovation Intensive Service, IIS)架構，藉由內部服務價值活動與外部資源涵量兩大構面，評量及分析人工智能醫學影像服務產業目前與未來之策略定位掌握程度。其內部服務價值活動分析囊括服務設計、測試認證、行銷、配銷、售後服務、支援活動等六大核心構面，外部資源涵量則包括互補資源提供者、研究發展、技術、生產、服務、市場、其他使用者等七大關鍵因素。最後輔以四種客製化程度為橫軸與五種創新方式為縱軸，建構一4x5 矩陣對企業進行經營型態分析，以了解未來（5~10年）的策略演進趨勢。相關產業專家的訪談及問卷調查結果將作為IIS 統計數據來源。
研究結果顯示，由專家問卷與訪談所歸納的人工智能醫學影像服務產業當前的策略定位為「產品創新(P1)／一般型服務(G)」，而未來的策略定位則為「結構創新(S)／選擇型服務(S)」。經IIS模式分析後，此未來策略定位的可行性具有一定難度，應予以修正；或依IIS架構重新分析後的策略與營運模式定位「產品創新(P1)/一般型服務(G)」強化其關鍵成功要素，提升產業價值與競爭力。

關鍵字：人工智能、醫學影像、創新密集服務模式、內部服務價值活動、外部資源涵量

This thesis focuses on an analysis of business models for artifical intelligence service in medical imaging. By applying an integrated model of Innovation Intensive Service (IIS), it analyzes the current and future strategic positioning of AI assistant in medical imaging from the aspect of internal value activities and externalities. The internal value activities contains 6 key factors which includes Design, Validation of Testing, Marketing, Delivery, After Service and Supporting Activities, while the Externalities comprise 7 key factors which are Complementary Assets Supplier, R&D, Technology, Production, Servicing, Market and Other Users. Last but not least, structuring a matrix, which encompasses four customization degrees abd five innovation modes, to illustrate the strategic development trend of future in next 5-10 years. The sources of statistics data for IIS are collected through questionnaires and interviews with industry experts.
The result of this study indicates that the present positioning of AI assistant in medical imagining via questionnaires and interviews with industry experts is at "Product Innovation (P1)/Generic Service (G)", while the future positioning is at "Structure Innovation (S)/ Selective Service (S)". However, by analysis through IIS, the future strategic positioning mentioned above should be repositioned as "Product Innovation (P1)/Generic Service (G)", since the one suggested by industry experts is not feasible. The companies may follow the study result to strengthen key successul factors accordingly in order to increase industrial value and competitiveness.

Keywords: Artifical Intelligence, Medical Imaging, Innovation Intensive Services, IIS, Internal Value Activities, Externalities

摘要 i
Abstract ii
致謝 iii
目錄 iv
圖目錄 vii
表目錄 viii
第一章、緒論 1
1.1研究背景 1
1.2 研究動機 5
1.3研究目的 8
1.4研究方法 8
1.5研究對象 8
1.6研究架構 9
1.7研究步驟 11
1.8研究限制 11
第二章、文獻探討 13
2.1人工智能醫學影像診斷服務文獻探討 13
2.1.1醫學影像診斷之文獻 13
2.1.2人工智能定義 20
2.1.3人工智能醫學影像診斷服務相關文獻 25
2.2創新密集服務分析模式理論依據 27
2.2.1服務業性質探討 27
2.2.2 服務價值創造流程與內部核心能力 31
2.2.3 關鍵成功因素與外部資源涵量 35
2.3創新密集服務業分析模式 39
2.3.1創新密集服務定位矩陣 39
2.3.2 創新密集服務平台分析模式 40
第三章、產業分析 42
3.1人工智能醫學影像診斷服務產業介紹 42
3.1.1人工智能醫學影像診斷服務介紹 42
3.2 人工智能醫學影像診斷服務產業市場概況 44
3.2.1人工智能醫學影像診斷服務產業之各國政策與規範 44
3.2.2人工智能醫學影像診斷服務產業價值鏈 49
3.2.3人工智能醫學影像服務產業之領導廠商 53
3.3 人工智能醫學影像服務產業趨勢 55
3.3.1 全球人工智能醫學影像服務產業趨勢 55
3.3.2 人工智能醫學影像診斷服務產業之應用 58
第四章、理論模式 60
4.1 創新密集服務業模式 60
4.1.1 服務價值活動矩陣 60
4.1.2 外部資源矩陣 63
4.1.3 創新密集服務矩陣 67
4.2 創新密集服務業策略分析 68
4.2.1 服務價值活動實質優勢矩陣 68
4.2.2 外部資源實質優勢矩陣 73
4.2.3 創新密集服務策略分析 77
第五章、研究結果 79
5.1 樣本敘述 79
5.1.1敘述性統計 79
5.1.2信度與效度分析 80
5.2創新密集服務業分析 81
5.2.1創新密集服務矩陣定位 81
5.2.2服務價值活動目前掌握程度與未來需求程度 83
5.2.3外部資源目前掌握程度與未來重要程度 87
5.3服務價值活動評量 91
5.3.1服務價值活動創新評量 91
5.3.2服務價值活動實質優勢矩陣 93
5.4外部資源評量 95
5.4.1外部資源創新評量 95
5.4.2外部資源實質優勢矩陣 97
5.5策略分析 98
5.5.1創新密集服務實質優勢矩陣 98
5.5.2策略意圖分析 100
5.5.3產業管理意涵分析 103
第六章、結論與建議 105
6.1研究結論與建議 105
6.1.1研究結論 105
6.1.2策略建議 106
6.2後續研究建議 107
參考書目 109
(一)、英文部分 109
(二)、中文部分 113
(三)、網站資料 114
附錄 115

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