金融科技快速發展下，行動支付的使用率近幾年在各國不斷地提升及以追求走向無現金化為目標，經濟發展好的國家與經濟發展較差的國家，行動支付使用的比例如今也產生較大的懸殊。2005年聯合國提出普惠金融，希望被金融體系排斥的人都可以享有金融服務與產品，因此也開始關注到低度開發國家的發展。
本研究主要探討影響低度開發國家在2013年至2018年行動支付帳戶、交易數與交易額的因素。本文應用簡單線性迴歸模型與縱橫資料迴歸模型，以通貨膨脹率、外國直接投資、經濟成長率、人口成長、城市人口、勞動參與率、失業率、貿易、網路用戶量、手機使用量、匯款、教育指數、人類發展指數及銀行密度來探討對行動支付的影響。
實證結果顯示，在以整體國家而言，人口因素（城市人口及人口成長）的影響最明顯。再來就是以網路設備及通訊基礎設施為主要的影響因素；低收入國家，以網路基礎設備及通訊基礎設施影響行動支付為主要因素；中低收入及高中收入的國家，宏觀經濟變數更能影響行動支付使用的因素。透過提升行動支付的使用量，有助於實現普惠金融，促進未來金融科技的發展。

In recent years, with the explosive growth in financial technology (Fintech) and the pursuit of a cashless society, the user rate of mobile payment has been continuously increasing in various countries. In mobile payment, the gap between countries in higher and lower economic development has been growing recently.  In 2005, the United Nations proposed inclusive finance, hoping that everyone excluded from the financial system could also enjoy financial services and products. Therefore, the attention of Fintech development in underdeveloped countries improves.
This research mainly explores the factors that affect mobile payment accounts, transaction numbers, and transaction value in underdeveloped countries from 2013 to 2018. In this study, Simple Linear Regression Model and Panel Data Regression Model applied to calculate the inflation rate, foreign direct investment, economic growth rate, population growth, urban population, labor force participation rate, unemployment rate, trade, internet users, mobile phone usage, remittances, education index, human development index, and bank density.
The result showed the demographic factors (urban population and population growth) impact the whole country most. Furthermore, in low-income countries, the improvement of network equipment and communication infrastructure is considerable. On the other hand, in low-middle income countries and high-middle income countries, macroeconomic variables can further affect the factors. Expending the utilize of the digital wallet will help to realize inclusive finance and promote the development of financial technology in the future.

目　錄
表　目　錄V
圖　目　錄VII
第一章　緒論1
第一節　研究背景與動機1
第二節　研究目的4
第三節　研究架構與流程5
第二章　理論與相關文獻7
第一節　金融科技7
第二節　行動支付10
第三節　宏觀經濟方法14
第三章　研究方法17
第一節　研究資料定義與來源17
第二節　簡單線性迴歸模型定義與概念26
第三節　縱橫資料迴歸分析模型定義與概念27
第四章　實證結果與分析34
第一節　敘述統計量分析34
第二節　相關性檢定分析36
第三節　縱橫資料迴歸模型分析39
第五章　結論與建議72
第一節　結論72
第二節　建議74
參考文獻75

表　目　錄
表 1　研究對象的基本資料18
表 2　研究資料名稱與來源19
表 3　X、Y變數名稱、代號及預期符號表25
表 4　2013年至2018年資料之基本敘述統計量35
表 5　相關係數矩陣－37
表 6　相關係數矩陣－38
表 7　變異數膨脹因子38
表 8　行動支付帳戶之模型適用檢定40
表 9　行動支付交易數之模型適用檢定41
表 10　行動支付交易額之模型適用檢定42
表 11　行動支付帳戶（低收入）之模型適用檢定43
表 12　行動支付交易數（低收入）之模型適用檢定44
表 13　行動支付交易額（低收入）之模型適用檢定45
表 14　行動支付帳戶（中低收入）之模型適用檢定46
表 15　行動支付交易數（中低收入）之模型適用檢定47
表 16　行動支付交易額（中低收入）之模型適用檢定48
表 17　行動支付帳戶（高中收入）之模型適用檢定49
表 18　行動支付交易數（高中收入）之模型適用檢定50
表 19　行動支付交易額（高中收入）之模型適用檢定51
表 20　縱橫資料迴歸分析－固定效果模型（Y1）53
表 21　縱橫資料迴歸分析－固定效果模型（Y2）54
表 22　縱橫資料迴歸分析－固定效果模型（Y3）56
表 23　縱橫資料迴歸分析－固定效果模型（Y1）低收入58
表 24　縱橫資料迴歸分析－隨機效果模型（Y2）低收入59
表 25　縱橫資料迴歸分析－隨機效果模型（Y3）低收入61
表 26　縱橫資料迴歸分析－隨機效果模型（Y1）中低收入63
表 27　縱橫資料迴歸分析－固定效果模型（Y2）中低收入64
表 28　縱橫資料迴歸分析－隨機效果模型（Y3）中低收入66
表 29　縱橫資料迴歸分析－固定效果模型（Y1）高中收入67
表 30　縱橫資料迴歸分析－隨機效果模型（Y2）高中收入69
表 31　縱橫資料迴歸分析－固定效果模型（Y3）高中收入70
 	 
圖　目　錄
圖 1　研究架構流程圖6

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三、其他網路資料
1.金融穩定委員會，https://www.fsb.org/work-of-the-fsb/financial-innovation-and-structural-change/fintech/。