簡易檢索 / 詳目顯示

研究生: 張玟涓
Chang, Wen-Chuan
論文名稱: 社會影響與創新抵制對行動支付使用意願之影響
Impact of Social Influence and Innovation Resistance on Intention to Use Mobile Payment
指導教授: 施人英
Shih, Jen-Ying
口試委員: 何宗武
Ho, Tsung-Wu
江艾軒
Chiang, Ai-Hsuan
施人英
Shih, Jen-Ying
口試日期: 2022/07/26
學位類別: 碩士
Master
系所名稱: 全球經營與策略研究所
Graduate Institute of Global Business and Strategy
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 53
中文關鍵詞: 行動支付創新抵制社會影響新冠肺炎結構方程模式
英文關鍵詞: Mobile payment, Innovation Resistance theory, Social Influence, COVID-19, Structural Equation Model
DOI URL: http://doi.org/10.6345/NTNU202201065
論文種類: 學術論文
相關次數: 點閱:150下載:18
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 2020年全球受到新冠肺炎(COVID-19)疫情影響至今,改變了消費者的消費習慣與支付方式,行動支付產業在疫情的時空背景下迅速發展,普及率明顯上升,此外,台灣政府致力於宣導民眾使用行動支付作為防疫新生活的概念,推廣民眾多使用行動支付,也持續擴大行動支付的使用場景。因行動支付在台灣不如國外普及,經過疫情催化下有更多人開始使用行動支付,本研究旨在探討消費者受到外界的社會影響下,對於行動支付的抵制意願是否下降,以創新抵制理論作為本次研究基礎,了解消費者對於行動支付的使用意願。
    本研究透過網路平台共收集521份問卷,有效問卷為386份,其中有使用過行動支付者有323份,未使用過行動支付者有63份,以Smart PLS進行結構方程模型分析。使用過行動支付者實證結果在社會影響與創新抵制障礙的關係中,僅風險障礙不顯著,社會影響皆顯著負向影響使用障礙、價值障礙與傳統障礙,在創新抵制障礙與使用意願的關係中,使用障礙與傳統障礙顯著負向影響使用意願,但價值障礙與風險障礙則無。未使用過行動支付者實證結果在社會影響與創新抵制障礙的關係中,社會影響負向影響消費者的使用障礙、價值障礙、風險障礙及傳統障礙皆不顯著,在創新抵制障礙與使用意願的關係中,結果與有使用行動支付者相同。

    In 2020, the world has been affected by the Coronavirus disease (COVID-19) pandemic, which has changed the consumption habit and payment methods of consumers. In addition, the Taiwan government committed to promoting mobile payment as a new concept during the pandemic life, popularized the people to use mobile payment, and keep extending the usage scenario. Because mobile payment in Taiwan is not as universal as in other countries, however, more people began to use it under the COVID-19 situation. The study aims to explore whether the willingness of consumers to resist mobile payment has declined under social influence, and understand consumers’ willingness to use mobile payment by Innovation Resistance Theory as the basis of this study.
    This research collected 521 online questionnaires through the internet platform, and 386 of them were valid, including 323 who have experience in using mobile payment, and 63 who have no experience. Structural Equation Model (SEM) analysis was be performed with Smart PLS. Empirical results of those who have experience of using mobile payment shows that social influence significantly negatively affect usage barriers, value barriers and traditional barriers, except the risk barriers. In the relationship between innovation resistance and willingness to use, usage barriers and traditional barriers significantly negatively affecting the willingness to use, but value barriers and risk barriers were not. Empirical results of those who have no experience of using mobile payment reveals that there’s no significant relationship between social influence and innovation resistance, and the relationship between innovation resistance and willingness to use was the same as those who have experience in using mobile payment.

    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 研究流程 5 第二章、文獻探討 6 第一節 臺灣行動支付與電子支付定義 6 第二節 創新抵制理論 8 第三節 社會影響 10 第三章、研究方法 12 第一節 研究架構 12 第二節 研究假設 12 第三節 變數操作型定義與衡量題項及資料收集 15 第四節 統計分析方法 17 第四章、統計結果與分析 19 第一節 敘述統計分析 19 第二節 信效度分析 31 第三節 結構方程模型分析 35 第五章、結論與建議 39 第一節 研究結果 39 第二節 研究貢獻與實務建議 41 第三節 研究限制與建議 42 參考文獻 44 附錄 48

    一、中文部分
    邱皓政. (2011). 當 PLS 遇上 SEM: 議題與對話. αβγ 量化研究學刊, 3(1), 20-53.
    國家發展委員會.(2018). 台灣經濟論壇衡: 行動支付與電子化支付普及之關鍵, (16), 29-37
    楊運秀, & 趙行義. (2019). 以創新抵制探討行動支付的使用意圖. 東吳經濟商學學報, (99), 91-124
    賴明政, 李姿穎, & 楊燕枝. (2018). 創新的採用與抵制: 以行動支付服務為例. Marketing Review/Xing Xiao Ping Lun, 15(2), 291-319
    李于宏. (2020). 純網銀篇》將來銀行執行副總梅驊:網銀 創金融共贏. 財金資訊季刊, 98, 16-21

    二、英文部分
    Balabanis, G., Reynolds, N., & Simintiras, A. (2006). Bases of e-store loyalty: Perceived switching barriers and satisfaction. Journal of Business Research, 59(2), 214-224.
    BOKU. (2021). 2021 Mobile Wallets Report.
    Chong, A. Y. L. (2013). Predicting m-commerce adoption determinants: A neural network approach. Expert systems with applications, 40(2), 523-530.
    Davis, K. A. (2004). Information technology change in the architecture, engineering, and construction industry: An investigation of individuals' resistance, Ph.D. dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA.
    Ferneley, E. H., & Sobreperez, P. (2006). Resist, comply or workaround? An examination of different facets of user engagement with information systems. European Journal of Information Systems, 15(4), 345-356.
    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
    Ishak, S. S. M., & Newton, S. (2016). An innovation resistance factor model. Construction Economics and Building, 16(3), 87-103.
    Kaur, P., Dhir, A., Singh, N., Sahu, G., & Almotairi, M. (2020). An innovation resistance theory perspective on mobile payment solutions. Journal of Retailing and Consumer Services, 55, 102059.
    Khanra, S., Dhir, A., Kaur, P., & Joseph, R. P. (2021). Factors influencing the. adoption postponement of mobile payment services in the hospitality sector during a pandemic. Journal of Hospitality and Tourism Management, 46, 26-39.
    Knoke, D., & Kuklinski, J. H. (1991). Network analysis: basic concepts. Markets, hierarchies and networks: The coordination of social life, 173-82.
    Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537-554.
    Kuisma, T., Laukkanen, T., & Hiltunen, M. (2007). Mapping the reasons for resistance to Internet banking: A means-end approach. International journal of information management, 27(2), 75-85.
    Laumer, S., & Eckhardt, A. (2010). Why do people reject technologies?–Towards an understanding of resistance to it-induced organizational change. Thirty first international conference on information systems, St. Louis, USA.
    Laukkanen, T. (2016). Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking. Journal of Business Research, 69(7), 2432-2439.
    López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & management, 45(6), 359-364.
    Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization science, 11(4), 404-428.
    Park, S. T., Im, H., & Noh, K. S. (2016). A study on factors affecting the adoption of LTE mobile communication service: The case of South Korea. Wireless Personal Communications, 86(1), 217-237.
    Park, J., Ahn, J., Thavisay, T., & Ren, T. (2019). Examining the role of anxiety and. social influence in multi-benefits of mobile payment service. Journal of Retailing and Consumer Services, 47, 140-149.
    Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: the marketing problem and its solutions. Journal of consumer marketing. 6(2), 5-14.
    Ram, S. (1989). Successful innovation using strategies to reduce consumer resistance an empirical test. Journal of Product Innovation Management, 6(1), 20-34.
    Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.
    Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic commerce research and applications, 9(3), 209-216.
    Tan, G. W. H., Ooi, K. B., Chong, S. C., & Hew, T. S. (2014). NFC mobile credit card: the next frontier of mobile payment?. Telematics and Informatics, 31(2), 292-307.
    Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International journal of medical education, 2, 53–55.
    Teo, A. C., Tan, G. W. H., Ooi, K. B., Hew, T. S., & Yew, K. T. (2015). The effects of convenience and speed in m-payment. Industrial Management & Data Systems, 115(2), 311-331.
    Valente, T. W. (1996). Social network thresholds in the diffusion of innovations. Social networks, 18(1), 69-89.
    Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
    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.

    下載圖示
    QR CODE