層級分析法（Analytic Hierarchy Process，縮寫為AHP）是一種多準則之決策理論與應用，可用以處理複雜的決策問題，尤其當該決策涉及多個相關標準與屬性時。目前AHP已經被廣泛應用於不同領域，舉凡醫療、環境管理、經濟、工程、市場分析、醫療決策等。
本研究之個案公司試圖透過結合智慧穿戴裝置與電子票證的技術來突破競爭激烈的市場。然而由於開發資源的限制，必須先從候選方案中選擇最有優勢的專案來開發。本研究按照層級分析法的步驟，探討各項影響要素、建立層級；透過專家問卷建立準則，最後將待選方案分別代入準則後評比，選定最佳方案進行開發。本研究替個案公司發展提供了重要的方向和依據。

The Analytic Hierarchy Process (AHP) is a decision-making theory and application. It is especially useful in handling complex decision problems, particularly when multiple interrelated standards and attributes are involved. Currently, AHP has been widely applied across various fields including healthcare, environmental management, economics, engineering, market analysis, and medical decision-making.
In this study, the company intends to increase their revenue by combining smart wearable device with Smart Card. However, due to limited development resources, it is necessary to select the most advantageous project from candidates for development. Following the steps of the Analytic Hierarchy Process, the study explores various influencing factors, establishes a hierarchy, and using questionnaires to establish criteria. Finally, the study helps this company find the best candidate in this project and it provides crucial direction for the company's development.

目錄
摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1-1 研究背景與動機 1
1-2 研究目的 2
1-3 研究架構 3
第二章 文獻探討 4
2-1 穿戴式裝置與行動支付 4
2-2 近代NFC技術與電子票證 5
2-2-1 近代電子票證 5
2-2-2 近代NFC技術 5
2-3 多屬性評估方法 7
2-3-1 簡易多屬性評等方法(SMART) 7
2-3-2 層級分析法(AHP) 8
2-3-3 網路層級分析法(ANP) 10
2-3-4 多屬性評估方法之比較與個案研究方法選定 11
第三章 研究方法 14
3-1 層級分析法 14
3-2 層級分析法之執行步驟 15
3-2-1 問題描述及影響要素探討 15
3-2-2 建立層級 15
3-2-3 問卷設計、問卷填寫 15
3-2-4 成對對比矩陣之建立 16
3-2-5 計算特徵值λmax與特徵向量W 17
3-2-6 層級內一致性檢定與整體層級結構一致性檢定 19
3-2-7 權重計算與最佳方案推理 21
第四章 個案分析 22
4-1問題描述 22
4-1-1 背景 22
4-1-2 決策團隊組成與界定問題 23
4-2 評選架構與要素分析建立 24
4-3 評選架構之確認 27
4-4權重取得與分析 28
4-4-1 問卷設計與對象 28
4-4-2 問卷回收與分析 29
4-4-3 小結 33
4-5 待選方案 35
4-5-1 資料調查 36
4-5-2 根本目標1: 成本 37
4-5-3 根本目標2: 市場潛力 44
4-5-4 根本目標3: 文化風氣 50
4-6 總目標: 電子票證市場導入地區 55
4-7 收益評估 56
第五章 結論 58
5-1 研究貢獻 58
5-2 未來研究方向 59
參考文獻 60
附錄一 AHP問卷 63

中文文獻
1.尹兆鈞，2021，應用層級分析程序法建立組裝代工廠評選制度，成功大學工業與資訊管理學系碩士在職專班論文。
2.陳信良，2021，運用層級分析法分析半導體產業新客戶導入之要件之研究，陽明交通大學管理學院工業工程與管理學系碩士論文。
英文文獻
1.Saaty, T.L. (1980), The Analytic Hierarchy Process, McGraw-Hill, New York
2.Taylor, F.A., Ketcham, A.F., & Hoffman, D. (1998), "Personnel evaluation with AHP," Management Decision, Vol. 36, No. 10, pp. 679-685.
3.Kamal M.Subbi, A. (2001), "Application of the AHP in project management, " International Journal of Project Management, Vol. 19, No. 1, pp. 19-27.
4.Byun, D.H. (2001), "The AHP approach for selecting an automobile purchase model," Information & Management, Vol. 38, No. 5, pp. 289-297.
5.Wolfslehner, B., Vacik, H., & Lexer, M.J. (2005), "Application of the analytic network process in multi-criteria analysis of sustainable forest management, " Forest Ecology and Management, Vol. 207, No. 1-2, pp. 157-170.
6.Promentilla M.A.B., Furuichi T., Ishii K., & Tanikawa N. (2006), "Evaluation of remedial countermeasures using the analytic network process", Waste Management, Vol. 26, No. 12, pp. 1410-1421.
7.Pelletier, M., Trepanier, M., & Morency, C. (2011), "Smart Card Date Use in Public transit: A Literature review, " Transportation Research Part C: Emerging Technologies, Vol. 19, No. 4, pp. 557-568.
8.Jain, G., & Dahiya, S. (2015), "NFC: Advantages, Limits and Future Scope," International Journal on Cybernetics & Informatics (IJCI), Vol.4, No. 4.,
pp. 1-12.
9.Rabaa'I, A., & Zhu, X. (2021), "Understanding the Determinants of Wearable Payment Adoption: An Empirical Study," Interdisciplinary Journal of Information, Knowledge, and Management, Vol. 16, pp. 173-211.
10.Andriani, S., & Meiriza, A. (2021), "Penerapan Metode Simple Multi Attribute Rating Technique Pada Pemberian Bonus Tahunan Karyawan," JuTISI, Vol. 7, No. 3., pp. 666.
11.Rosalina, V., Agustiawan, W., & Purnamasari, A. (2023), "A Decision Support System for Determining the Best Customer Using the Simple Multi-Attribute Rating Technique (SMART)," International Journal of Information Technology and Computer Science Applications, Vol. 1, No. 1, pp. 58–65.
網路資源
1.市調研究機構 canalys網頁 (2023年3月9日)。 Wearable Band market plummets 18% in Q4 2022, smartwatches to lead modest 2% growth in 2023.
https://www.canalys.com/newsroom/global-wearable-band-market-Q4-2022
2.市調研究機構 counterpoint網頁 (2023年11月30日)。Global Smartwatch Shipments Market Share (Q2 2022 – Q3 2023) https://www.counterpointresearch.com/global-smartwatch-shipments-market-share/