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題名 行為變遷：預測數位金融之創新模式
Behavioural Shift: Predicting the Innovation Model of Digital Finance作者 封宜君
Feng, Yi-Chun貢獻者 蕭瑞麟
Hsiao, Ruey-Lin
封宜君
Feng, Yi-Chun關鍵詞 行為變遷
服務創新
服務設計
Behavior shift
Service innovation
Service design日期 2022 上傳時間 5-Oct-2022 09:10:30 (UTC+8) 摘要 受到大環境的遷移如新冠肺炎的爆發、科技的進步，使用者的行為受到改變，例如對於無現金支付的利用，以及行動支付、數位金融服務的普及度及滲透度提高。在數位浪潮的趨勢下，各家企業以使用者為中心，強調顧客體驗，競相提出數位金融的產品與服務。可惜的是，大多企業以使用者旅程為分析脈絡，只看顧客的行為，忽略掉顧客行為的變遷，導致所產出的服務僅可以解決顧客當下的痛點，造成各家提供的金融服務大同小異，差異化不足。本研究以臺灣的金融場域為主，以行為變遷的理論為主軸，分析在環境變遷之下，顧客的行為增減如何改變，行為如何遷移，並以三個金融創新個案為例，分別說明連線銀行、台新銀行、以及永豐銀行為例，分別提出其創新產品以及服務。在理論貢獻上，本研究提出關於行為的遷移性，以及調適性，並說明這樣的分析方案可以看到對於行為的預測，以洞見未來使用者的需求。實務上，對於行為的遷移，可以幫助企業看到關於行為變遷的趨勢，以利服務設計可以被有效利用。此外，本研究提出若是企業採納行為變遷之理論，則可以提前佈局未來的策略。在未來環境變化快速的過程中，秉持防患未然、提前佈局的精神，達到顧客真正滿意，而企業境營永續，如此雙贏的結果。
As a result of the general environmental changes such as the outbreak of new pneumonia and the advancement of technology, user behavior has changed, such as the use of cashless payments, and the increased popularity and penetration of mobile payments and digital financial services. Under the trend of the digital wave, companies are putting emphasis on user-centered and customer experience and competing to propose digital financial products and services. Unfortunately, most of the companies take the user journey as the analysis context and only look at customer behavior, ignoring the changes in customer behavior, resulting in services that can only solve the current pain points of customers, resulting in similar financial services provided by different companies with insufficient differentiation. This study focuses on the financial field in Taiwan and applies the theory of behavioral change to analyze how people`s behaviors change and how behaviors migrate under the changing environment, and uses three financial innovation cases as examples to illustrate the innovative products and services of Line Bank, Taishin Bank, and Sinopac Bank. In terms of theoretical contribution, this study proposes the migration and adaptability of behavior and shows that such an analytical scheme can be used to predict behavior and gain insight into future user needs. In practice, the migration of behavior can help companies to capture the trend of behavior shifts, so that the service design can be effectively utilized. In addition, this study suggests that if companies adopt the theory of behavior change, they can plan their future strategies in advance. In the process of rapid environmental changes in the future, the spirit of prevention and advance planning can help achieve true customer satisfaction and sustainable business operations, which is a win-win situation for both parties.參考文獻 Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes., 50(2): 179-212.Alexander, M. W. 2012. Delight the customer: A predictive model for repeat purchase behavior. Journal of Relationship Marketing, 11(2): 116-123.Beaudry, A., & Pinsonneault, A. 2005. Understanding user response to information technology: A coping model of user adaptation. MIS Quarterly, 29(3): 493-526.Beckman, S. L., & Barry, M. 2007. Innovation as a learning process: Embedding design thinking. California Management Review, 50(1): 25-56.Brown, T. 2009. Change by design: How design thinking transforms organizations and inspires innovation. New York: Harper Collins.Dewar, R. D., & Dutton, J. E. 1986. The adoption of radical and incremental innovations: An empirical analysis. Management Science, 32(11): 1422-1433.Dey, B. L., Al-Karaghouli, W., & Muhammad, S. S. 2020. Adoption, adaptation, use and impact of information systems during pandemic time and beyond: Research and managerial implications. Information Systems Management, 37(4): 298-302.Hienerth, C., Keinz, P., & Lettl, C. 2011. Exploring the nature and implementation process of user-centric business models. Long Range Planning, 44(5–6): 344-374.Hsiao, R.-L., Wu, S. W., & Hou, S. T. 2008. Sensitive cabbies: Ongoing sense-making within technology structuring. Information and Organization, 18(4): 251–279.Jaakkola, E., & Alexander, M. 2014. The role of customer engagement behavior in value co-creation. Journal of Service Research, 17(3): 247-261.Jacobides, M. G., & Reeves, M. 2020. Adapt your business to the new reality. Harvard Business Review, 98(5): 74-81.Jasperson, J., Carter, P. E., & Zmud, R. W. 2005. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3): 525-557.Jiafu, S., Xu, C., Fengting, Z., Na, Z., & Fei, L. 2021. An intelligent method for lead user identification in customer collaborative product innovation. Journal of Theoretical & Applied Electronic Commerce Research, 16(5): 1571-1583.Karahanna, E., Straub, D. W., & Chervany, N. L. 1999. Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2): 183-213.Kouprie, M., & Visser, F. 2009. A framework for empathy in design: stepping into and out of the user`s life. Journal of Engineering Design, 20(5): 437-448.Kraatz, M. S., & Zajac, E. J. 2001. How organizational resources affect strategic change and performance in turbulent environments: Theory and evidence. Organization Science, 12(5): 632-657.Krishna, R., & Kummitha, R. 2019. Design thinking in social organizations: Understanding the role of user engagement. Creativity & Innovation Management, 28(1): 101-112.Lippert, S. K. 2007. Investigating post-adoption utilization: An examination into the role of inter-organizational and technology trust. IEEE Transactions on Engineering Management, 54(3): 468-483.Mathieson, K. 1991. Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3): 173-191.Möller, K., Rajala, R., & Westerlund, M. 2008. Service innovation myopia? A new recipe for client-provider value creation. California Management Review, 50(3): 31-48.Orlikowski, W. J. 1996. Improvising organizational transformation over time: A situated change perspective. Information Systems Research, 7(1): 63–93.Paterno, F., & Mancini, C. 2000. Effective levels of adaptation to different types of users in interactive Museum Systems. Journal of the American Society for Information Science, 51(1): 5-13.Schreier, M., Oberhauser, S., & Prugl, R. 2007. Lead users and the adoption and diffusion of new products: Insights from two extreme sports communities. Marketing Letters, 18(1/2): 15-30.Tyre, M., & Orlikowski, W. 1994. Windows of opportunity: Temporal patterns of technological adaptation in organizations. Organization Science, 5(1): 98-118.von Hippel, E. 1986. Lead users: A source of novel product concepts. Management Science, 32(7): 791-805.Walsham, G. 1995. Interpretive case studies in IS research: Nature and method. European Journal of Information Systems, 4: 74-81. 描述 碩士
國立政治大學
科技管理與智慧財產研究所
109364131資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109364131 資料類型 thesis dc.contributor.advisor 蕭瑞麟 zh_TW dc.contributor.advisor Hsiao, Ruey-Lin en_US dc.contributor.author (Authors) 封宜君 zh_TW dc.contributor.author (Authors) Feng, Yi-Chun en_US dc.creator (作者) 封宜君 zh_TW dc.creator (作者) Feng, Yi-Chun en_US dc.date (日期) 2022 en_US dc.date.accessioned 5-Oct-2022 09:10:30 (UTC+8) - dc.date.available 5-Oct-2022 09:10:30 (UTC+8) - dc.date.issued (上傳時間) 5-Oct-2022 09:10:30 (UTC+8) - dc.identifier (Other Identifiers) G0109364131 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/142107 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 科技管理與智慧財產研究所 zh_TW dc.description (描述) 109364131 zh_TW dc.description.abstract (摘要) 受到大環境的遷移如新冠肺炎的爆發、科技的進步，使用者的行為受到改變，例如對於無現金支付的利用，以及行動支付、數位金融服務的普及度及滲透度提高。在數位浪潮的趨勢下，各家企業以使用者為中心，強調顧客體驗，競相提出數位金融的產品與服務。可惜的是，大多企業以使用者旅程為分析脈絡，只看顧客的行為，忽略掉顧客行為的變遷，導致所產出的服務僅可以解決顧客當下的痛點，造成各家提供的金融服務大同小異，差異化不足。本研究以臺灣的金融場域為主，以行為變遷的理論為主軸，分析在環境變遷之下，顧客的行為增減如何改變，行為如何遷移，並以三個金融創新個案為例，分別說明連線銀行、台新銀行、以及永豐銀行為例，分別提出其創新產品以及服務。在理論貢獻上，本研究提出關於行為的遷移性，以及調適性，並說明這樣的分析方案可以看到對於行為的預測，以洞見未來使用者的需求。實務上，對於行為的遷移，可以幫助企業看到關於行為變遷的趨勢，以利服務設計可以被有效利用。此外，本研究提出若是企業採納行為變遷之理論，則可以提前佈局未來的策略。在未來環境變化快速的過程中，秉持防患未然、提前佈局的精神，達到顧客真正滿意，而企業境營永續，如此雙贏的結果。 zh_TW dc.description.abstract (摘要) As a result of the general environmental changes such as the outbreak of new pneumonia and the advancement of technology, user behavior has changed, such as the use of cashless payments, and the increased popularity and penetration of mobile payments and digital financial services. Under the trend of the digital wave, companies are putting emphasis on user-centered and customer experience and competing to propose digital financial products and services. Unfortunately, most of the companies take the user journey as the analysis context and only look at customer behavior, ignoring the changes in customer behavior, resulting in services that can only solve the current pain points of customers, resulting in similar financial services provided by different companies with insufficient differentiation. This study focuses on the financial field in Taiwan and applies the theory of behavioral change to analyze how people`s behaviors change and how behaviors migrate under the changing environment, and uses three financial innovation cases as examples to illustrate the innovative products and services of Line Bank, Taishin Bank, and Sinopac Bank. In terms of theoretical contribution, this study proposes the migration and adaptability of behavior and shows that such an analytical scheme can be used to predict behavior and gain insight into future user needs. In practice, the migration of behavior can help companies to capture the trend of behavior shifts, so that the service design can be effectively utilized. In addition, this study suggests that if companies adopt the theory of behavior change, they can plan their future strategies in advance. In the process of rapid environmental changes in the future, the spirit of prevention and advance planning can help achieve true customer satisfaction and sustainable business operations, which is a win-win situation for both parties. en_US dc.description.tableofcontents 聲明頁 I感謝誌 II中文摘要 III英文摘要 IV圖目錄 IX表目錄 IX壹、緒論 10第一節 研究動機 10一、實務問題：環境遷移下的創新服務 10二、理論問題：行為變遷與轉化創新 11第二節 研究目標 13一、分析數位金融趨勢 14二、分析行為的增減 15三、分析創新服務的形成 15第二節 研究預期效益 16一、理論上的貢獻 16二、實務上的貢獻 17第三節 論文章節佈局 18貳、文獻回顧 19第一節 名詞定義 19一、使用者行為 19二、行為變遷 22三、數位金融 23第二節 採納前的行為 25一、條件行為 25二、涉入行為 27三、領先行為 28四、同理行為 28第三節 調適後的行為 30一、採納行為 30二、因應行為 31三、採納關鍵時機 32四、情境實踐行為 34第四節 變遷的行為 35參、研究方法 36第一節 方法論的選用 36第二節 案例選擇與理論取樣 37一、行為消長跟隨趨勢 37二、行為變遷伴隨心理狀況 38三、行為變遷展現新常態 38第三節 分析架構的發展 40一、分析架構的設計 40二、資料分析步驟 41第四節 資料蒐集與分析 48一、研究背景 48二、訪問對象與訪綱設計 50三、次級資料整理 52肆、研究發現 55第一節 數位金融的服務創新 55第二節 夢想帳戶的行為變遷分析 57一、查找服務，開啟帳戶 57（一）環境趨勢：單一服務入口 59（二）行為變遷：入口查找不易 60（三）服務設計：多元服務入口 60二、存入金額，查找利率 64（一）環境趨勢：固定利率儲蓄 64（二）行為變遷：無趣低利率活存 65（三）服務設計：階梯式利率 66三、利息即時回饋 69（一）環境趨勢：查帳不直覺 69（二）行為變遷：查帳變管帳 69（三）服務設計：利息入帳即時訊息 71四、金融遊戲化 74（一）環境趨勢：單向式金融 74（二）行為變遷：互動性金融 75（三）服務設計：遊戲化金融 76五、小結：夢想帳戶的服務設計分析 77第三節 豐存股的行為變遷分析 80一、臺美股一站式平台、績效一目瞭然 81（一）環境趨勢：美股的重視 81（二）行為變遷：美股投資佈局 81（三）服務設計：投資暨績效整合平台 83二、好好投資，獲取最佳的投資報酬 85（一）環境趨勢：被動投資標的，無投資建議 85（二）行為變遷：不知道該如何投資 86（三）服務設計：提供標的精準分析建議，與報酬回測 88三、購物車下單匣 89（一）環境趨勢：投資理財變為長期需求 89（二）行為變遷：美股投資程序多，不知如何下單 90（三）服務設計：極大化投資效益，購物車模式下單 91四、臺幣美幣隨你扣款 94（一）環境趨勢：申購美股以美金扣款 94（二）行為變遷：彈性利用資產 94（三）服務設計：不限定臺幣與美金扣款 95五、小結：豐存股的服務設計分析 96第四節 RICHART LIFE的行為變遷分析 99一、金融帳務管家 100（一）環境趨勢：金融服務融入生活 100（二）行為變遷：金融如水電般簡單 102（三）服務設計：應用金融服務讓生活更加值 103二、Richart Mart行動商城 105（一）環境趨勢：習慣虛實整合服務 105（二）行為變遷：無法輕易獲取金融服務 106（三）服務設計：將金融產品與消費產品整合 106三、點數生態圈 108（一）環境趨勢：數位身份及點數的擴大應用 108（二）行為變遷：數位身份過多的資訊混雜，數位點數的兌換受限 109（三）服務設計：提供顧客點數整合儀表板 110四、咖啡寄杯服務 113（一）環境趨勢：資產數位化 113（二）行為變遷：單一通路寄杯服務 113（三）服務設計：數位寄杯通路整合，提供轉贈服務 114五、小結：Richart Life的服務設計分析 115伍、討論 118第一節 學術貢獻 118二、行為調適性 119三、行為的預測性 120四、服務的佈局與轉換 121第三節 研究限制與未來建議 123ㄧ、行為變遷的分析 123二、行為交互調適的回應 124三、商業模式的創新 124陸、結論 125參考文獻 126附件一：論文口試委員問題答覆稿 128圖目錄圖 1：分析架構與步驟─探索行為變遷的過程 40圖 2：連線銀行—夢想帳戶的行為變遷分析 58圖 3：永豐銀行的行為變遷分析 82圖 4：台新銀行的行為變遷分析 101表目錄表 1：使用者行為文獻正反合觀點整理 21表 2：田野調查與資料蒐集方法 49表 3：夢想帳戶的行為變遷分析 79表 4：豐存股行為變遷分析 98表 5：台新銀行Richart Life行為變遷分析 116 zh_TW dc.format.extent 2891558 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109364131 en_US dc.subject (關鍵詞) 行為變遷 zh_TW dc.subject (關鍵詞) 服務創新 zh_TW dc.subject (關鍵詞) 服務設計 zh_TW dc.subject (關鍵詞) Behavior shift en_US dc.subject (關鍵詞) Service innovation en_US dc.subject (關鍵詞) Service design en_US dc.title (題名) 行為變遷：預測數位金融之創新模式 zh_TW dc.title (題名) Behavioural Shift: Predicting the Innovation Model of Digital Finance en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes., 50(2): 179-212.Alexander, M. W. 2012. Delight the customer: A predictive model for repeat purchase behavior. Journal of Relationship Marketing, 11(2): 116-123.Beaudry, A., & Pinsonneault, A. 2005. Understanding user response to information technology: A coping model of user adaptation. MIS Quarterly, 29(3): 493-526.Beckman, S. L., & Barry, M. 2007. Innovation as a learning process: Embedding design thinking. California Management Review, 50(1): 25-56.Brown, T. 2009. Change by design: How design thinking transforms organizations and inspires innovation. New York: Harper Collins.Dewar, R. D., & Dutton, J. E. 1986. The adoption of radical and incremental innovations: An empirical analysis. Management Science, 32(11): 1422-1433.Dey, B. L., Al-Karaghouli, W., & Muhammad, S. S. 2020. Adoption, adaptation, use and impact of information systems during pandemic time and beyond: Research and managerial implications. Information Systems Management, 37(4): 298-302.Hienerth, C., Keinz, P., & Lettl, C. 2011. Exploring the nature and implementation process of user-centric business models. Long Range Planning, 44(5–6): 344-374.Hsiao, R.-L., Wu, S. W., & Hou, S. T. 2008. Sensitive cabbies: Ongoing sense-making within technology structuring. Information and Organization, 18(4): 251–279.Jaakkola, E., & Alexander, M. 2014. The role of customer engagement behavior in value co-creation. Journal of Service Research, 17(3): 247-261.Jacobides, M. G., & Reeves, M. 2020. Adapt your business to the new reality. Harvard Business Review, 98(5): 74-81.Jasperson, J., Carter, P. E., & Zmud, R. W. 2005. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3): 525-557.Jiafu, S., Xu, C., Fengting, Z., Na, Z., & Fei, L. 2021. An intelligent method for lead user identification in customer collaborative product innovation. Journal of Theoretical & Applied Electronic Commerce Research, 16(5): 1571-1583.Karahanna, E., Straub, D. W., & Chervany, N. L. 1999. Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2): 183-213.Kouprie, M., & Visser, F. 2009. A framework for empathy in design: stepping into and out of the user`s life. Journal of Engineering Design, 20(5): 437-448.Kraatz, M. S., & Zajac, E. J. 2001. How organizational resources affect strategic change and performance in turbulent environments: Theory and evidence. Organization Science, 12(5): 632-657.Krishna, R., & Kummitha, R. 2019. Design thinking in social organizations: Understanding the role of user engagement. Creativity & Innovation Management, 28(1): 101-112.Lippert, S. K. 2007. Investigating post-adoption utilization: An examination into the role of inter-organizational and technology trust. IEEE Transactions on Engineering Management, 54(3): 468-483.Mathieson, K. 1991. Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3): 173-191.Möller, K., Rajala, R., & Westerlund, M. 2008. Service innovation myopia? A new recipe for client-provider value creation. California Management Review, 50(3): 31-48.Orlikowski, W. J. 1996. Improvising organizational transformation over time: A situated change perspective. Information Systems Research, 7(1): 63–93.Paterno, F., & Mancini, C. 2000. Effective levels of adaptation to different types of users in interactive Museum Systems. Journal of the American Society for Information Science, 51(1): 5-13.Schreier, M., Oberhauser, S., & Prugl, R. 2007. Lead users and the adoption and diffusion of new products: Insights from two extreme sports communities. Marketing Letters, 18(1/2): 15-30.Tyre, M., & Orlikowski, W. 1994. Windows of opportunity: Temporal patterns of technological adaptation in organizations. Organization Science, 5(1): 98-118.von Hippel, E. 1986. Lead users: A source of novel product concepts. Management Science, 32(7): 791-805.Walsham, G. 1995. Interpretive case studies in IS research: Nature and method. European Journal of Information Systems, 4: 74-81. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202201534 en_US
