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題名 第三方支付滿意度影響因素研究
Influencing Factors on the Third- Party Payment Satisfaction作者 張惠詠
Chang, Hui-Yung貢獻者 姜家雄
Chiang,Alex
張惠詠
Chang,Hui-Yung關鍵詞 第三方支付
使用者滿意度
知覺有用性
持續使用意願
Third-Party Payment
User Satisfaction
Perceived Usefulness
Willingness to continue the use日期 2021 上傳時間 1-Oct-2021 10:13:13 (UTC+8) 摘要 隨著電子商務規模的快速擴張,第三方支付越來越普及,而新冠疫情加速了去現金化的過程。在這過程中可見第三方支付對於生活的緊密程度。COVID-19推動了數字支付的使用，各國央行發行數位貨幣並建立數字個人帳戶的想法變得越來越吸引人。COVID-19疫情過後，我們生活的許多方面都將發生改變，包括我們去的地方、我們見的人、我們如何旅行以及我們的整個支付方式。在covid-19疫情期間,萬事達卡的發布新聞,超過75%消費者因疫情提升行動支付使用頻率,而且且每天都會使用行動支付的「重度使用者」自疫情發生後增加了30%，全台每兩位行動支付使用者中，便有一人是行動支付重度使用者。線上交易從電子商務發展開始,至今第三方支付己成為主流。第三方支付業者想要在很多競爭對手中,優先留住客戶的注意力進而獲得成功,就必須觀注是什麼因素影響使用者的滿意度,選取大學生為研究對象,確定研究視角為:確認程度、知覺有用性、滿意度、持續使用意願,透過調查問券的方式收集數據,通過SPSS和PLS分析方法得出結論,為第三方支付業者提供建議。本文通過實證研究得出如下結論:期望確認程度、感知有用性、滿意度對接續使用意願有直接顯著正向影響,最後本文根據研究結論為第三方支付業者提出了幾項管理建議:優化操作流程、增強用戶感知易用性:提高用戶感知價值、優化產品服務品質、提高用戶滿意度。
With the rapid expansion of the e-commerce scale, third-party payment is becoming more and more popular, and the new crown epidemic has accelerated the process of de-cashing. In this process, we can see how close third-party payment is to live. COVID-19 has promoted the use of digital payments, and the idea of central banks issuing digital currencies and establishing digital personal accounts has become more and more attractive. After the COVID-19 epidemic, many aspects of our lives will change, including where we go, the people we meet, how we travel, and our entire payment method.During the covid-19 epidemic, Mastercard issued news that more than 75% of consumers have increased mobile payment use due to the epidemic. The number of "heavy users" who use mobile payment every day has increased by 30% since the outbreak. For every two mobile payment users, one is a heavy mobile payment user. Online transactions started from the development of e-commerce, and so far, third-party payment has become the mainstream.Suppose the third-party payment industry wants to retain the customer`s attention and achieve success among many competitors. In that case, it must pay attention to what factors affect the user`s satisfaction, select college students as the research object, and determine the research perspective as the degree of Perceived usefulness, confirmation, satisfaction, and Continuous use intention. Collect data through investigation and questionnaires. Conclude SPSS and PLS analysis methods, and provide suggestions for third-party payment companies. This paper outlines the following findings through empirical research: the degree of expected confirmation, perceived usefulness, and satisfaction directly and significantly positively impact the willingness to continue use. Finally, this paper puts forward several management recommendations for third-party payment companies based on the research conclusions: Optimize operation procedures Enhance user-perceived ease of use, improve user-perceived value, optimize product and service quality, and improve user satisfaction.參考文獻 Bearden, W. O., & Teel, J. E. (1983). Selected determinants of consumer satisfaction and Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 351-370. complaint reports. Journal of Marketing Research, 20(1), 21-28.Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation- confirmation model. MIS Quarterly, 351-370.Bickel, P. J., Breiman, L., Brillinger, D. R., Brunk, H. D., Pierce, D. A., Chernoff, H., ... & Wahba, G. (1977). Discussion: Consistent nonparametric regression. The Annals of Statistics, 5(4), 620-640.Cardozo, R. N. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2(3), 244-249.Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of marketing research, 19(4), 491-504.Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.Deming, W. E. (1981). Improvement of quality and productivity through action by management. National Productivity Review, 1(1), 12-22.Folkes, V. S. (1984). Consumer reactions to product failure: An attributional approach. Journal of Consumer Research, 10(4), 398-409.Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. (1996). The American customer satisfaction index: nature, purpose, and findings. Journal of Marketing, 60(4), 7-18.Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. Hair, J. F., Celsi, M., Ortinau, D. J., & Bush, R. P. (2010). Essentials of Marketing research (Vol. 2). New York, NY: McGraw-Hill/Irwin.Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage publications.Howard, J. A., & Sheth, J. N. (1969). The theory of Buyer Behavior (No. 658.834 H6).Juran, J. M., & Gryna, F. M. (1988). Juran’s quality control. Handbook, 4ème éd., New York.Kalakota, R., & Whinston, A. B. (1997). Electronic Commerce: a Manager`s Guide. Addison-Wesley Professional.Khai, N. T. N., & Huyen, N. T. T. Factors of Satisfaction and Intention Toward Using Peer-to-peer Accommodation-A Case of AIRBNB.Lee, T. H., & Suh, C. K. (2008). Effects of Individual Characteristics and Subject Norm on User Acceptance of e-Learning for Voluntary Studies. The Journal of Information Systems, 17(4), 99-127.Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of human-Computer Studies, 64(9), 799-810.Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.Lin, J., Handschin, C., & Spiegelman, B. M. (2005). Metabolic control through the PGC-1 family of transcription coactivators. Cell Metabolism, 1(6), 361-370.Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 705-737.Locke, E. A. (1976). The nature and causes of job satisfaction. Handbook of Industrial and Organizational Psychology.Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98.Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.Olshavsky, R. W., & Miller, J. A. (1972). Consumer expectations, product performance, and perceived product quality. Journal of Marketing Research, 9(1), 19-21.Ondrus, J., & Pigneur, Y. (2006). Towards a holistic analysis of mobile payments: A multiple perspectives approach. Electronic Commerce Research and Applications, 5(3), 246-257.Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 115-143.Pham, T. T. T., & Ho, J. C. (2015). The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Technology in Society, 43, 159-172.Regnault-Roger, C., & Hamraoui, A. (1995). Fumigant harmful activity and reproductive inhibition induced by monoterpenes on Acanthoscelides obtectus (Say)(Coleoptera), a bruchid of kidney bean (Phaseolus vulgaris L.). Journal of Stored Products Research, 31(4), 291-299.Rich, J. R., Rahi, G. S., Opperman, C. H., & Davis, E. L. (1989). Influence of the castor bean (Ricinus communis) lectin (ricin) on the motility of Meloidogyne incognita. Neotropical, 99-103.Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64(8), 683-696.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.Chinese Literature ReferenceChen Peiwen陳珮文. (2014). The Necessity and Development Thinking of the Legalization of Taiwan`s Third-Party Payment ─ Take the US PayPal and China Alipay as examples台灣第三方支付法制化的必要性與發展思考─ 以美國 PayPal 與中國支付寶為例. Degree Thesis of the Institute of Industrial Economics, Chuo University中央大學產業經濟研究所學位論文, 1-127.Websitehttps://www.lawinsider.com/dictionary/third-party-payment 描述 碩士
國立政治大學
亞太研究英語碩士學位學程(IMAS)
103926019資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103926019 資料類型 thesis dc.contributor.advisor 姜家雄 zh_TW dc.contributor.advisor Chiang,Alex en_US dc.contributor.author (Authors) 張惠詠 zh_TW dc.contributor.author (Authors) Chang,Hui-Yung en_US dc.creator (作者) 張惠詠 zh_TW dc.creator (作者) Chang, Hui-Yung en_US dc.date (日期) 2021 en_US dc.date.accessioned 1-Oct-2021 10:13:13 (UTC+8) - dc.date.available 1-Oct-2021 10:13:13 (UTC+8) - dc.date.issued (上傳時間) 1-Oct-2021 10:13:13 (UTC+8) - dc.identifier (Other Identifiers) G0103926019 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/137323 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 亞太研究英語碩士學位學程(IMAS) zh_TW dc.description (描述) 103926019 zh_TW dc.description.abstract (摘要) 隨著電子商務規模的快速擴張,第三方支付越來越普及,而新冠疫情加速了去現金化的過程。在這過程中可見第三方支付對於生活的緊密程度。COVID-19推動了數字支付的使用，各國央行發行數位貨幣並建立數字個人帳戶的想法變得越來越吸引人。COVID-19疫情過後，我們生活的許多方面都將發生改變，包括我們去的地方、我們見的人、我們如何旅行以及我們的整個支付方式。在covid-19疫情期間,萬事達卡的發布新聞,超過75%消費者因疫情提升行動支付使用頻率,而且且每天都會使用行動支付的「重度使用者」自疫情發生後增加了30%，全台每兩位行動支付使用者中，便有一人是行動支付重度使用者。線上交易從電子商務發展開始,至今第三方支付己成為主流。第三方支付業者想要在很多競爭對手中,優先留住客戶的注意力進而獲得成功,就必須觀注是什麼因素影響使用者的滿意度,選取大學生為研究對象,確定研究視角為:確認程度、知覺有用性、滿意度、持續使用意願,透過調查問券的方式收集數據,通過SPSS和PLS分析方法得出結論,為第三方支付業者提供建議。本文通過實證研究得出如下結論:期望確認程度、感知有用性、滿意度對接續使用意願有直接顯著正向影響,最後本文根據研究結論為第三方支付業者提出了幾項管理建議:優化操作流程、增強用戶感知易用性:提高用戶感知價值、優化產品服務品質、提高用戶滿意度。 zh_TW dc.description.abstract (摘要) With the rapid expansion of the e-commerce scale, third-party payment is becoming more and more popular, and the new crown epidemic has accelerated the process of de-cashing. In this process, we can see how close third-party payment is to live. COVID-19 has promoted the use of digital payments, and the idea of central banks issuing digital currencies and establishing digital personal accounts has become more and more attractive. After the COVID-19 epidemic, many aspects of our lives will change, including where we go, the people we meet, how we travel, and our entire payment method.During the covid-19 epidemic, Mastercard issued news that more than 75% of consumers have increased mobile payment use due to the epidemic. The number of "heavy users" who use mobile payment every day has increased by 30% since the outbreak. For every two mobile payment users, one is a heavy mobile payment user. Online transactions started from the development of e-commerce, and so far, third-party payment has become the mainstream.Suppose the third-party payment industry wants to retain the customer`s attention and achieve success among many competitors. In that case, it must pay attention to what factors affect the user`s satisfaction, select college students as the research object, and determine the research perspective as the degree of Perceived usefulness, confirmation, satisfaction, and Continuous use intention. Collect data through investigation and questionnaires. Conclude SPSS and PLS analysis methods, and provide suggestions for third-party payment companies. This paper outlines the following findings through empirical research: the degree of expected confirmation, perceived usefulness, and satisfaction directly and significantly positively impact the willingness to continue use. Finally, this paper puts forward several management recommendations for third-party payment companies based on the research conclusions: Optimize operation procedures Enhance user-perceived ease of use, improve user-perceived value, optimize product and service quality, and improve user satisfaction. en_US dc.description.tableofcontents Table of ContentsChapter 1 Introduction 11.1 Research Background 11.2 Research Development and Current Situation 51.3 Research Purposes 10Chapter 2 State of Third-Party Payment and Review of the Literature 142.1 E-commerce 142.2 Third-Party Payment 152.3 Consumer Behavior 232.4 IS Continuance Model 32Chapter 3 Methods 353.1 Research Model 353.2 Research Objective 363.3 Research Hypothesis 39Chapter 4 Research Findings 464.1 Sample Analysis and Recovery 464.2 Basic Data Analysis 474.3 Scale Quality Testing 484.4 Structural Model Analysis and Verification 56Chapter 5 Conclusion 625.1 Research Findings and Results 625.2 Research Contributions and Research Limitations 63References 72 zh_TW dc.format.extent 1056932 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103926019 en_US dc.subject (關鍵詞) 第三方支付 zh_TW dc.subject (關鍵詞) 使用者滿意度 zh_TW dc.subject (關鍵詞) 知覺有用性 zh_TW dc.subject (關鍵詞) 持續使用意願 zh_TW dc.subject (關鍵詞) Third-Party Payment en_US dc.subject (關鍵詞) User Satisfaction en_US dc.subject (關鍵詞) Perceived Usefulness en_US dc.subject (關鍵詞) Willingness to continue the use en_US dc.title (題名) 第三方支付滿意度影響因素研究 zh_TW dc.title (題名) Influencing Factors on the Third- Party Payment Satisfaction en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Bearden, W. O., & Teel, J. E. (1983). Selected determinants of consumer satisfaction and Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 351-370. complaint reports. Journal of Marketing Research, 20(1), 21-28.Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation- confirmation model. MIS Quarterly, 351-370.Bickel, P. J., Breiman, L., Brillinger, D. R., Brunk, H. D., Pierce, D. A., Chernoff, H., ... & Wahba, G. (1977). Discussion: Consistent nonparametric regression. The Annals of Statistics, 5(4), 620-640.Cardozo, R. N. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2(3), 244-249.Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of marketing research, 19(4), 491-504.Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.Deming, W. E. (1981). Improvement of quality and productivity through action by management. National Productivity Review, 1(1), 12-22.Folkes, V. S. (1984). Consumer reactions to product failure: An attributional approach. Journal of Consumer Research, 10(4), 398-409.Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. (1996). The American customer satisfaction index: nature, purpose, and findings. Journal of Marketing, 60(4), 7-18.Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. Hair, J. F., Celsi, M., Ortinau, D. J., & Bush, R. P. (2010). Essentials of Marketing research (Vol. 2). New York, NY: McGraw-Hill/Irwin.Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage publications.Howard, J. A., & Sheth, J. N. (1969). The theory of Buyer Behavior (No. 658.834 H6).Juran, J. M., & Gryna, F. M. (1988). Juran’s quality control. Handbook, 4ème éd., New York.Kalakota, R., & Whinston, A. B. (1997). Electronic Commerce: a Manager`s Guide. Addison-Wesley Professional.Khai, N. T. N., & Huyen, N. T. T. Factors of Satisfaction and Intention Toward Using Peer-to-peer Accommodation-A Case of AIRBNB.Lee, T. H., & Suh, C. K. (2008). Effects of Individual Characteristics and Subject Norm on User Acceptance of e-Learning for Voluntary Studies. The Journal of Information Systems, 17(4), 99-127.Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of human-Computer Studies, 64(9), 799-810.Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.Lin, J., Handschin, C., & Spiegelman, B. M. (2005). Metabolic control through the PGC-1 family of transcription coactivators. Cell Metabolism, 1(6), 361-370.Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 705-737.Locke, E. A. (1976). The nature and causes of job satisfaction. Handbook of Industrial and Organizational Psychology.Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98.Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.Olshavsky, R. W., & Miller, J. A. (1972). Consumer expectations, product performance, and perceived product quality. Journal of Marketing Research, 9(1), 19-21.Ondrus, J., & Pigneur, Y. (2006). Towards a holistic analysis of mobile payments: A multiple perspectives approach. Electronic Commerce Research and Applications, 5(3), 246-257.Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 115-143.Pham, T. T. T., & Ho, J. C. (2015). The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Technology in Society, 43, 159-172.Regnault-Roger, C., & Hamraoui, A. (1995). Fumigant harmful activity and reproductive inhibition induced by monoterpenes on Acanthoscelides obtectus (Say)(Coleoptera), a bruchid of kidney bean (Phaseolus vulgaris L.). Journal of Stored Products Research, 31(4), 291-299.Rich, J. R., Rahi, G. S., Opperman, C. H., & Davis, E. L. (1989). Influence of the castor bean (Ricinus communis) lectin (ricin) on the motility of Meloidogyne incognita. Neotropical, 99-103.Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64(8), 683-696.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.Chinese Literature ReferenceChen Peiwen陳珮文. (2014). The Necessity and Development Thinking of the Legalization of Taiwan`s Third-Party Payment ─ Take the US PayPal and China Alipay as examples台灣第三方支付法制化的必要性與發展思考─ 以美國 PayPal 與中國支付寶為例. Degree Thesis of the Institute of Industrial Economics, Chuo University中央大學產業經濟研究所學位論文, 1-127.Websitehttps://www.lawinsider.com/dictionary/third-party-payment zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202101573 en_US
