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題名 新冠疫情期間社群媒體對民眾數位支付接受度的影響
Social Media Impacts on the Acceptance of Digital Payment during the Pandemic作者 游筑茵
Yu, Chu-Yin貢獻者 王信實
游筑茵
Yu, Chu-Yin關鍵詞 新冠肺炎
金融科技
行動支付
電子支付
社群媒體
合成控制
COVID-19
Fintech
mobile payment
electronic payment
social media
Synthetic Control Method日期 2022 上傳時間 1-Aug-2022 18:27:23 (UTC+8) 摘要 本研究透過社群媒體大數據探討在新冠疫情期間社群媒體對我國民眾使用數位支付接受度的影響。從服務需求者角度，藉由趨勢檢定結果可發現：疫情對數位支付聲量影響力，在疫情前期已經產生正向的作用，中後期則是持續的影響。從服務提供者角度利用合成控制法及Difference-in-Differences方法分析得知：在疫情期間，國泰及合庫分別是民營銀行及官股銀行中數位支付使用量有較明顯增加的金融機構。國泰在台灣出現首例確診後(2020年1月)，因疫情干擾所產生的實驗效果最為顯著，而合庫則是在全球確診超過1000萬後(2020年6月)，所產生的實驗效果較為明顯。最後，無國泰民營銀行在疫情後數位支付使用量有顯著增加。反之，無合庫官股銀行在疫情後數位支付使用量沒有顯著的變化。
This study applies social media big data to explore the impact of social media on the acceptance of digital payment in Taiwan during the COVID-19 pandemic. From the service demand perspective, the trend test results indicate that the pandemic impact on the digital payment had a positive effect in the early stage of the pandemic, and had a continuous impact in the middle and later stages. From the service provider perspective, by using the Synthetic Control and the Difference-in-Differences Methods, Cathay United Bank and Taiwan Cooperative Bank were the financial institutions that had a significant increase in the digital payments among private banks and state-owned banks during the pandemic, respectively. After first confirmed case in Taiwan (2020.1), the experimental effect of Cathay United Bank caused by the pandemic intervention was the most significant, while the experimental effect of Taiwan Cooperative Bank was more significant after the global confirmed cases exceeded 10 million (2020.6). Finally, the digital payment services provided by non-Cathay United private banks had increased significantly after the pandemic. On the contrary, those provided by non-Taiwan Cooperative state-owned banks did not change significantly after the pandemic.參考文獻 一、中文文獻陳柏琪, & 顏晃平. (2018). 台灣銀行業經營效率之分析 ─ 共用投入下網絡資料包絡分析法之應用. 應用經濟論叢, (104), 145-191.二、英文文獻Abadie, A., & Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American economic review, 93(1), 113-132.Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American statistical Association, 105(490), 493-505.Alber, N., & Dabour, M. (2020). The dynamic relationship between FinTech and social distancing under COVID-19 pandemic: Digital payments evidence. International Journal of Economics and Finance, 12(11), 109-117.Aji, H. M., Berakon, I., & Md Husin, M. (2020). COVID-19 and e-wallet usage intention: A multigroup analysis between Indonesia and Malaysia. Cogent Business & Management, 7(1), 1804181.Barnes, S. J., & Vidgen, R. T. (2002). An integrative approach to the assessment of e-commerce quality. J. Electron. Commer. Res., 3(3), 114-127.Beaunoyer, E., Dupéré, S., & Guitton, M. J. (2020). COVID-19 and digital inequalities: Reciprocal impacts and mitigation strategies. Computers in human behavior, 111, 106424.Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-1022.Bartik, A. W., Bertrand, M., Cullen, Z., Glaeser, E. L., Luca, M., & Stanton, C. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the national academy of sciences, 117(30), 17656-17666.Camara, Youssouf. (2021). Digital Payments and Business Resilience : Evidence in the Time of COVID-19. Policy Research Working PaperDavis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Massachusetts Institute of Technology.Daragmeh, A., Lentner, C., & Sági, J. (2021). FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment. Journal of Behavioral and Experimental Finance, 32, 100574.Fu, J., & Mishra, M. (2021). Fintech in the time of COVID-19: Trust and technological adoption during crises. Swiss Finance Institute Research Paper, 20-38.Kendall, M. G. (1975). Rank Correlation Measures; Charles Griffin Book Series.Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the econometric society, 245-259.Niswah, F. M., & Legowati, D. A. (2019). Muslim millennial’s intention of donating for charity using fintech platform. Journal of Islamic Monetary Economics and Finance, 5(3), 623-644.Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., ... & Agha, R. (2020). The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International journal of surgery, 78, 185-193.Pal, R., & Bhadada, S. K. (2020). Cash, currency and COVID-19. Postgraduate medical journal, 96(1137), 427-428.Stewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information & Computer Security.Sahay, M. R., von Allmen, M. U. E., Lahreche, M. A., Khera, P., Ogawa, M. S., Bazarbash, M., & Beaton, M. K. (2020). The promise of fintech: Financial inclusion in the post COVID-19 era. International Monetary Fund.Sen, P. K. 1968. “Estimates of the Regression Coefficient Based on Kendall`s Tau,”. Journal of the American Statistical Association, 63: 1379–1389.Sreelakshmi, C. C., & Prathap, S. K. (2020). Continuance adoption of mobile-based payments in Covid-19 context: an integrated framework of health belief model and expectation confirmation model. International Journal of Pervasive Computing and Communications.Theil, H. 1950. “A Rank-Invariant Method of Linear and Polynomial Regression Analysis,”. Koninklijke Nederlandse Akademie var Wetenschappen Proceedings, 53: 386–392.Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481.Zhao, Y., & Bacao, F. (2021). How does the pandemic facilitate mobile payment? An investigation on users’ perspective under the COVID-19 pandemic. International journal of environmental research and public health, 18(3), 1016. 描述 碩士
國立政治大學
經濟學系
109258014資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109258014 資料類型 thesis dc.contributor.advisor 王信實 zh_TW dc.contributor.author (Authors) 游筑茵 zh_TW dc.contributor.author (Authors) Yu, Chu-Yin en_US dc.creator (作者) 游筑茵 zh_TW dc.creator (作者) Yu, Chu-Yin en_US dc.date (日期) 2022 en_US dc.date.accessioned 1-Aug-2022 18:27:23 (UTC+8) - dc.date.available 1-Aug-2022 18:27:23 (UTC+8) - dc.date.issued (上傳時間) 1-Aug-2022 18:27:23 (UTC+8) - dc.identifier (Other Identifiers) G0109258014 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141247 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 109258014 zh_TW dc.description.abstract (摘要) 本研究透過社群媒體大數據探討在新冠疫情期間社群媒體對我國民眾使用數位支付接受度的影響。從服務需求者角度，藉由趨勢檢定結果可發現：疫情對數位支付聲量影響力，在疫情前期已經產生正向的作用，中後期則是持續的影響。從服務提供者角度利用合成控制法及Difference-in-Differences方法分析得知：在疫情期間，國泰及合庫分別是民營銀行及官股銀行中數位支付使用量有較明顯增加的金融機構。國泰在台灣出現首例確診後(2020年1月)，因疫情干擾所產生的實驗效果最為顯著，而合庫則是在全球確診超過1000萬後(2020年6月)，所產生的實驗效果較為明顯。最後，無國泰民營銀行在疫情後數位支付使用量有顯著增加。反之，無合庫官股銀行在疫情後數位支付使用量沒有顯著的變化。 zh_TW dc.description.abstract (摘要) This study applies social media big data to explore the impact of social media on the acceptance of digital payment in Taiwan during the COVID-19 pandemic. From the service demand perspective, the trend test results indicate that the pandemic impact on the digital payment had a positive effect in the early stage of the pandemic, and had a continuous impact in the middle and later stages. From the service provider perspective, by using the Synthetic Control and the Difference-in-Differences Methods, Cathay United Bank and Taiwan Cooperative Bank were the financial institutions that had a significant increase in the digital payments among private banks and state-owned banks during the pandemic, respectively. After first confirmed case in Taiwan (2020.1), the experimental effect of Cathay United Bank caused by the pandemic intervention was the most significant, while the experimental effect of Taiwan Cooperative Bank was more significant after the global confirmed cases exceeded 10 million (2020.6). Finally, the digital payment services provided by non-Cathay United private banks had increased significantly after the pandemic. On the contrary, those provided by non-Taiwan Cooperative state-owned banks did not change significantly after the pandemic. en_US dc.description.tableofcontents 第一章 前言 1第一節 研究背景 1第二節 研究動機與介紹 1第三節 研究架構與流程 3第二章 文獻探討 4第一節 疫情期間使用數位支付可以降低傳染風險 4第二節 COVID-19爆發導致數位支付的使用量增加 4第三節 COVID-19是影響數位支付使用意願的因素 6第三章 資料 8第一節 資料介紹 8第二節 資料整合串接 9第三節 變數處理與說明 9第四節 敘述性統計與趨勢 10第四章 研究方法 13第一節 趨勢檢定法 13一、 Mann-Kendall檢定法 13二、 Theil-Sen 斜率推估法 14第二節 主題模型 14一、 隱含狄利克雷分布(Latent Dirichlet Allocation) 15二、 評估指標 16第三節 合成控制法 16一、 合成控制 16二、 In Space Placebo 17第五章 實證結果 18第一節 服務需求者角度 18一、 數位支付聲量影響力在疫情重大事件時間點的反應 18二、 疫情前後不同主題貼文的比例變化及對數位支付使用量的影響 20第二節 服務提供者角度 23一、 疫情後金融機構透過社群平台行銷數位支付的成效是否提高 23二、 比較其餘民營銀行與官股銀行數位支付的行銷成效 31第六章 結論與限制 36參考文獻 IA. 附錄 VI. OPVIEW關鍵字設定 VII. 數位聲量影響力之敏感度分析 VIIII. 金融機構社群媒體官方帳號對應名稱 VIIIV. 各主題分類下主文之文字雲 VIIIV. 合成控制法延遲效果分析 IXVI. 不分民營及官股銀行合成控制結果 XI zh_TW dc.format.extent 4192179 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109258014 en_US dc.subject (關鍵詞) 新冠肺炎 zh_TW dc.subject (關鍵詞) 金融科技 zh_TW dc.subject (關鍵詞) 行動支付 zh_TW dc.subject (關鍵詞) 電子支付 zh_TW dc.subject (關鍵詞) 社群媒體 zh_TW dc.subject (關鍵詞) 合成控制 zh_TW dc.subject (關鍵詞) COVID-19 en_US dc.subject (關鍵詞) Fintech en_US dc.subject (關鍵詞) mobile payment en_US dc.subject (關鍵詞) electronic payment en_US dc.subject (關鍵詞) social media en_US dc.subject (關鍵詞) Synthetic Control Method en_US dc.title (題名) 新冠疫情期間社群媒體對民眾數位支付接受度的影響 zh_TW dc.title (題名) Social Media Impacts on the Acceptance of Digital Payment during the Pandemic en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文文獻陳柏琪, & 顏晃平. (2018). 台灣銀行業經營效率之分析 ─ 共用投入下網絡資料包絡分析法之應用. 應用經濟論叢, (104), 145-191.二、英文文獻Abadie, A., & Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American economic review, 93(1), 113-132.Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American statistical Association, 105(490), 493-505.Alber, N., & Dabour, M. (2020). The dynamic relationship between FinTech and social distancing under COVID-19 pandemic: Digital payments evidence. International Journal of Economics and Finance, 12(11), 109-117.Aji, H. M., Berakon, I., & Md Husin, M. (2020). COVID-19 and e-wallet usage intention: A multigroup analysis between Indonesia and Malaysia. Cogent Business & Management, 7(1), 1804181.Barnes, S. J., & Vidgen, R. T. (2002). An integrative approach to the assessment of e-commerce quality. J. Electron. Commer. Res., 3(3), 114-127.Beaunoyer, E., Dupéré, S., & Guitton, M. J. (2020). COVID-19 and digital inequalities: Reciprocal impacts and mitigation strategies. Computers in human behavior, 111, 106424.Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-1022.Bartik, A. W., Bertrand, M., Cullen, Z., Glaeser, E. L., Luca, M., & Stanton, C. (2020). The impact of COVID-19 on small business outcomes and expectations. Proceedings of the national academy of sciences, 117(30), 17656-17666.Camara, Youssouf. (2021). Digital Payments and Business Resilience : Evidence in the Time of COVID-19. Policy Research Working PaperDavis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Massachusetts Institute of Technology.Daragmeh, A., Lentner, C., & Sági, J. (2021). FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment. Journal of Behavioral and Experimental Finance, 32, 100574.Fu, J., & Mishra, M. (2021). Fintech in the time of COVID-19: Trust and technological adoption during crises. Swiss Finance Institute Research Paper, 20-38.Kendall, M. G. (1975). Rank Correlation Measures; Charles Griffin Book Series.Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the econometric society, 245-259.Niswah, F. M., & Legowati, D. A. (2019). Muslim millennial’s intention of donating for charity using fintech platform. Journal of Islamic Monetary Economics and Finance, 5(3), 623-644.Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., ... & Agha, R. (2020). The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International journal of surgery, 78, 185-193.Pal, R., & Bhadada, S. K. (2020). Cash, currency and COVID-19. Postgraduate medical journal, 96(1137), 427-428.Stewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information & Computer Security.Sahay, M. R., von Allmen, M. U. E., Lahreche, M. A., Khera, P., Ogawa, M. S., Bazarbash, M., & Beaton, M. K. (2020). The promise of fintech: Financial inclusion in the post COVID-19 era. International Monetary Fund.Sen, P. K. 1968. “Estimates of the Regression Coefficient Based on Kendall`s Tau,”. Journal of the American Statistical Association, 63: 1379–1389.Sreelakshmi, C. C., & Prathap, S. K. (2020). Continuance adoption of mobile-based payments in Covid-19 context: an integrated framework of health belief model and expectation confirmation model. International Journal of Pervasive Computing and Communications.Theil, H. 1950. “A Rank-Invariant Method of Linear and Polynomial Regression Analysis,”. Koninklijke Nederlandse Akademie var Wetenschappen Proceedings, 53: 386–392.Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481.Zhao, Y., & Bacao, F. (2021). How does the pandemic facilitate mobile payment? An investigation on users’ perspective under the COVID-19 pandemic. International journal of environmental research and public health, 18(3), 1016. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202200985 en_US
