English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113303/144284 (79%)
Visitors : 50796570      Online Users : 749
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/129659


    Title: e管家還是e管區?數位身分識別證下的隱私計算
    Convenience or Surveillance? Privacy Calculus Model for New eID Policy
    Authors: 黃宗賢
    Huang, Zong-Xian
    Contributors: 黃東益
    Huang, Tong-Yi
    黃宗賢
    Huang, Zong-Xian
    Keywords: 數位治理
    數位身分識別證
    隱私計算
    科技風險
    結構方程式
    Digital governance
    New eID
    Privacy calculus
    High-tech risk
    Structural Equation Modeling
    MyData
    Date: 2020
    Issue Date: 2020-05-05 11:59:13 (UTC+8)
    Abstract: 民眾授權個人資料的意願,是個人資料自主管理(MyData)政策成敗的關鍵。本研究以數位身分識別證政策為個案,應用隱私計算模型分析個人資料授權意願背後的隱私因素,採用偏最小平方法結構方程式(PLS-SEM)來探索數位身分識別證議題上,民眾在利益與風險間的權衡,並經由政治大學選舉研究中心建置的「線上調查實驗室」(PollcracyLab)進行資料蒐集。
    本研究發現財務報償、個性化服務與服務兼容性都有助於提高民眾的隱私利益認知,而隱私利益認知則進一步會提高授權個人資料的意願;然而,隱私風險認知並不會影響民眾透過數位身分識別證授權個人資料的意願,代表民眾對隱私所帶來的風險有過多的忽視。本研究援引了行為經濟學、隱私悖論與遲滯性風險的觀點,探討了導致此認知缺口的可能邏輯。
    本研究側面印證了臺灣是一個「遲滯型高科技風險社會」的推論,在具高度不確定性的科技議題上,民眾可能低估了潛在的隱私危害,並高估了預期效益。未來推動數位身分識別證的決策者,應跳脫僅以民意調查作為決策參考的思維,嘗試納入多元的決策機制於政策過程之中。最後,本研究討論了納入調節變項與高階構念等模型修正策略,以及建議未來研究者可以透過入選機率調整法(Propensity Score Adjustments)與實驗設計(experimental design)等方法修正調查方法上的偏誤。
    The success or failure of the MyData policy depends on citizens` willingness to authorize their personal data. This study applied privacy calculus model on the case of national electronic identification card (New eID) policy to analyze privacy factors which affect personal data disclosure intention. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to explore how citizens balance benefits and risks associated with the New eID issue. Research data were collected from PollcracyLab affiliated by Election Study Center of National Chengchi University (NCCU).
    The study concludes that financial compensation, personalized services, and service compatibility can enhance cognition of privacy-related benefits of citizens, while this cognition will further promote their willingness to authorize their personal data. Citizens` cognition of privacy-related risks, however, has no statistical effect within the model, and shows that citizens excessively neglect privacy-related risks. The perspective of behavioral economics, privacy paradox and delayed risk are cited in this study, to demonstrate the abovementioned cognitive gap.
    This study verifies the inference that Taiwan consists of a “Delayed High-tech Risk Society”. In technology issues with high uncertainties, citizens may underestimate the potential privacy-related risks, and overrate expected benefits. Therefore, policy makers in charge of implementing the New eID policy should incorporate diversified decision-making mechanisms into their policy process, and avoid taking opinion polls as the only reference.
    Finally, this study discusses model revising strategies such as adopting moderator variables and higher-order components. Future researchers are also recommended to correct survey method bias by such approaches as Propensity Score adjustments and experimental design.
    Reference: 內政部(2019)。數位身分證之規劃、功能與經費。2020年 2 月 27 日,取自:https://lis.ly.gov.tw/lydb/uploadn/108/1080516/01.pdf。
    丘昌泰(2008)。公共政策:基礎篇。臺北:巨流圖書。
    何明諠(2016)。數位時代的隱私邊界:以健保資料庫與ETC交通資料庫為例。台灣人權學刊,3(4),139-153。
    余孝先、趙祖佑(2015)。巨量資料應用,打造資料驅動決策的智慧政府。國土及公共治理季刊,3(4),27-37。
    余致力(2002)。民意與公共政策:理論探討與實證研究。臺北:五南。
    李仲彬(2011)。「信任」在電子治理中所扮演的角色:以文獻檢閱為基礎的初探性分析。公共行政學報,39,105-147。
    李仲彬、洪永泰、朱斌妤、黃東益、黃婉玲、曾憲立(2017)。數位國情總綱調查(4):因應行動服務與共享經濟(資源)發展之策略(編號:NDC-MIS-105-001)。臺北:國家發展委員會。
    李伯璋、林寶鳳、張齡芝(2019)。健康存摺~你我的健康管家-整合民眾醫療資訊,一機在手健保跟著走。消費者報導雜誌,457,67-70。
    李承傑、董旭英(2017)。偏最小平方法結構方程模型。科學發展,539,20-25。
    李政忠(2004)。網路調查所面臨的問題與解決建議。資訊社會研究,6,1-24。
    杜文苓(2011)。環境風險與科技決策:檢視中科四期環評爭議。東吳政治學報,29(2),57-110。
    杜文苓、施麗雯、黃廷宜(2007)。風險溝通與民主參與:以竹科宜蘭基地之設置為例。科技醫療與社會,5,71-110。
    杜素豪(2015)。比較入選機率分組與其他加權方法對電話調查樣本的調整:上網率的推估,臺灣社會學刊,56,115-150。
    周家瑜(2016)。馴服《利維坦》?霍布斯與絕對主義。政治與社會哲學評論,59,51-91。
    周桂田(2002)。在地化風險之實踐與理論缺口-遲滯型高科技風險社會。台灣社會研究季刊,45,69-122。
    周桂田(2015)。臺灣風險社會十堂課:食安、科技與環境。臺北:巨流圖書。
    周桂田、張淳美(2006)。遲滯型高科技風險社會下之典範鬥爭:以換發身分證按捺指紋案為分析。政治與社會哲學評論,17,127-215.
    俞振華(2016)。網路民意調查的理論與實務。載於陳陸輝(編),民意調查新論(4版)(95-116頁)。臺北:五南。
    俞振華、涂志揚(2017)。探討以電訪資料及「入選機率調整法」修正網路調查偏誤的可行性。政治科學論叢,73,81-125。
    洪新原、梁定澎、張嘉銘(2005)科技接受模式之彙總研究。資訊管理學報,12(4),211-234。
    紀佳伶(2000)。電子化/網路化政府資訊內容隱私權之研究。國立政治大學公共行政學系碩士學位論文,未出版,臺北。
    國家發展委員會(2018)。服務型智慧政府推動計畫-第五階段電子化政府計畫。2020年 2 月 25 日,取自:https://reurl.cc/1QnjMG。
    國家發展委員會(2019)。智慧政府推動策略計畫。2020年 2 月 25 日,取自:https://reurl.cc/drdzQg。
    張順全、莊文忠(2017)。超越藍綠?政治版圖在2014年臺北市長選舉的新應用。選舉研究,24(1),97-132。
    陳怡君(2008)。優質網路政府主動服務新思維-民衆e管家。研考雙月刊,32(1),57-65。
    陳寬裕(2018)。結構方程模型分析實務:SPSS與SmartPLS的運用。臺北:五南。
    曾冠球、陳敦源、胡龍騰(2009)。推展公民導向的電子化政府:願景或幻想?。公共行政學報,33,1-43。
    曾憲立、洪永泰、朱斌妤、黃東益、謝翠娟(2018)。多元民意調查方法的比較研究。調查研究,41,87-117。
    曾憲立、蕭乃沂、宋同正(2020)。智慧政府下My Data個案推動與模式建構:數位身分識別與服務流程優化(編號:NDC-MIS-108-002)。臺北:國家發展委員會。
    湯家偉(譯)(2016)。結構方程模式:偏最小平方法PLS-SEM(原作者:Joseph F. Hair, Jr, G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt)。臺北:高等教育文化。
    黃東益、胡龍騰、李仲彬、黃婉玲、曾憲立、朱斌妤(2018)。數位國情總綱調查(5):區域發展策略(編號:NDC-MIS-106-001)。臺北:國家發展委員會。
    黃紀(2008)。因果推論與觀察研究:「反事實模型」之思考。社會科學論叢,2(1),1-22。
    黃紀(2013)。政治學計量方法的回顧與前瞻。載於吳玉山、林繼文、冷則剛(編),政治學的回顧與前瞻(39-64頁)。臺北:中央研究院政治研究所。
    廖興中、朱斌妤、黃婉玲、洪永泰、黃東益(2019)。數位國情總綱調查(6):區域數位分級與數位國情世代進展研析(編號:NDC-MIS-107-001)。臺北:國家發展委員會。
    榮予恆(2019)。邁向敏捷政府–敏捷專案管理在我國數位治理的應用與影響。國立政治大學公共行政學系碩士學位論文,未出版,臺北。
    管中祥(2001)。從「資訊控制」的觀點反思「電子化政府」的樂觀迷思。資訊社會研究,1,299-316。
    劉尚志、林三元、宋皇志(2006)。走出繼受,邁向立論:法學實證研究之發展。科技法學評論,3(2),1-48。
    劉靜怡(2002)。網際網路時代的資訊使用與隱私權保護規範:個人、政府與市場的拔河。資訊管理研究,4(3),137-161。
    蕭乃沂、朱斌妤(2018)。資料驅動創新的跨域公共治理。國土及公共治理季刊,6(4),74-85。
    蕭乃沂、陳恭、郭昱瑩(2017)。第五階段電子化政府服務精進:國際趨勢與民眾需求探勘(編號:NDC-MIS-105-003)。臺北:國家發展委員會。
    蕭新煌、徐世榮、杜文苓(2019)。面對台灣風險社會:分析與策略。臺北:巨流圖書。
    羅清俊(2010)。社會科學研究方法:打開天窗說量化。臺北:威仕曼文化。
    顧振豪(2016)。完備資料開放與自主管理機制,建構數位國家發展基礎。國土及公共治理季刊,4(4),67-79。
    Abu-Shanab, E., & Al-Azzam, A. (2012). Trust Dimensions and the adoption of E-government in Jordan. International Journal of Information Communication Technologies and Human Development (IJICTHD), 4(1), 39-51.
    Acquisti, A., & Grossklags, J. (2007). What can behavioral economics teach us about privacy. Digital Privacy: Theory, Technologies and Practices, 18, 363-377.
    Acquisti, A., & Grossklags, J. (2012). An online survey experiment on ambiguity and privacy. Communications & Strategies, 88, 19-39.
    Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453-474.
    Albrechtslund, A. (2008). Online social networking as participatory surveillance. First Monday, 13(3). Retrieved from source https://firstmonday.org/ojs/index.php/fm/article/view/2142/1949http%3A.
    Allmer, T. (2011). Critical surveillance studies in the information society. tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society, 9(2), 566-592.
    Bansal, G., Zahedi, F. M. & Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138-150.
    Bélanger, F., & Carter, L. (2008). Trust and risk in e-government adoption. The Journal of Strategic Information Systems, 17(2), 165-176.
    Bernal, P. (2016). Data gathering, surveillance and human rights: recasting the debate. Journal of Cyber Policy, 1(2), 243-264.
    Bhansali, N. (2013). The Role of Data Governance in an Organization. In Bhansali, N. (Ed.). Data governance: Creating value from information assets (pp. 1-18). CRC Press.
    Carter, L., & Bélanger, F. (2005). The utilization of e-government services: citizen trust, innovation and acceptance factors. Information Systems Journal, 15(1), 5-25.
    Carter, L., & McBride, A. (2010). Information privacy concerns and e-government: a research agenda. Transforming Government: People, Process and Policy, 4(1), 10-13.
    Cespedes, F. V., & Smith, H. J. (1993). Database marketing: New rules for policy and practice. MIT Sloan Management Review, 34(4), 7-22.
    Chan, Y. E., & Reich, B. H. (2007). IT alignment: what have we learned?. Journal of Information Technology, 22(4), 297-315.
    Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104-115.
    Culnan, M. J., & Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323-342.
    Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
    de Bruijn, H., & Janssen, M. (2017). Building cybersecurity awareness: The need for evidence-based framing strategies. Government Information Quarterly, 34(1), 1-7.
    Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: the tailored design method (4th Ed.). New Jersey, NJ: John Wiley & Sons.
    Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80.
    Dinev, T., Bellotto, M., Hart, P., Russo, V., & Serra, I. (2006). Internet users` privacy concerns and beliefs about government surveillance: An exploratory study of differences between Italy and the United States. Journal of Global Information Management (JGIM), 14(4), 57-93.
    Dinev, T., Hart, P., & Mullen, M. R. (2008). Internet privacy concerns and beliefs about government surveillance–An empirical investigation. The Journal of Strategic Information Systems, 17(3), 214-233.
    Druckman, J. N., Green, D. P., Kuklinski, J. H., & Lupia, A. (2006). The growth and development of experimental research in political science. American Political Science Review, 100(4), 627-635.
    Foucault, M. (1995). Discipline and punish: the birth of the prison. New York, NY: Vintage Books.
    Giddens, A. (1985). The Nation-State and Violence: Volume 2 of A Contemporary Critique of Historical Materialism (2nd Ed.). California, CA: University of California Press.
    Goodsell, C. T. (1990). Public administration and the public interest. In Wamsley, G. L. (Ed.). Refounding public administration (pp. 96-113). Newbury Park, CA: Sage Publication.
    Granato, J., & Scioli, F. (2004). Puzzles, proverbs, and omega matrices: The scientific and social significance of empirical implications of theoretical models (EITM). Perspectives on Politics, 2(2), 313-323.
    Hagel III, J., & Rayport, J. F. (1997). The coming battle for customer information. The McKinsey Quarterly, 3, 64-77.
    Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565-580.
    Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277-319.
    Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597-606.
    Hui, K. L., Tan, B. C., & Goh, C. Y. (2006). Online information disclosure: Motivators and measurements. ACM Transactions on Internet Technology (TOIT), 6(4), 415-441.
    Isson, J. P., & Harriott, J. (2012). Win with advanced business analytics: Creating business value from your data (Vol. 62). John Wiley & Sons.
    Jabbour, C. J. C., Jugend, D., de Sousa Jabbour, A. B. L., Gunasekaran, A., & Latan, H. (2015). Green product development and performance of Brazilian firms: measuring the role of human and technical aspects. Journal of Cleaner Production, 87, 442-451.
    Janowski, T. (2015). Digital government evolution: From transformation to contextualization. Government Information Quarterly, 32, 221-236.
    Janssen, M., Rana, N. P., Slade, E. L., & Dwivedi, Y. K. (2018). Trustworthiness of digital government services: deriving a comprehensive theory through interpretive structural modelling. Public Management Review, 20(5), 647-671.
    Jeckmans, A. J., Beye, M., Erkin, Z., Hartel, P., Lagendijk, R. L., & Tang, Q. (2012). Privacy in recommender systems. In Ramzan, N., van Zwol, R., Lee, J. S., Clüver, K., & Hua, X. S. (Eds.). Social media retrieval (pp. 263-281). London, LON: Springer Science & Business Media.
    Jensen, C., Potts, C., & Jensen, C. (2005). Privacy practices of Internet users: self-reports versus observed behavior. International Journal of Human-Computer Studies, 63(1-2), 203-227.
    Kehr, F., Kowatsch, T., Wentzel, D., & Fleisch, E. (2015). Blissfully ignorant: the effects of general privacy concerns, general institutional trust, and affect in the privacy calculus. Information Systems Journal, 25(6), 607-635.
    Khatri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148-152.
    Kim, D., Park, K., Park, Y., & Ahn, J. H. (2019). Willingness to provide personal information: Perspective of privacy calculus in IoT services. Computers in Human Behavior, 92, 273-281.
    Kim, M. S., & Kim, S. (2018). Factors influencing willingness to provide personal information for personalized recommendations. Computers in Human Behavior, 88, 143-152.
    Kim, S., & Kim, J. (2016). A Study on Factors Influencing Privacy Decision Making on the Internet: Focus on Dual-Calculus Model. The Journal of Information Systems, 25(3), 197-215.
    Kokolakis, S. (2017). Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon. Computers & Security, 64, 122-134.
    Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: Why we disclose. Journal of Information Technology, 25(2), 109-125.
    Laufer, R. S., & Wolfe, M. (1977). Privacy as a concept and a social issue: A multidimensional developmental theory. Journal of Social Issues, 33(3), 22-42.
    Lee, Y., & Larsen, K. R. (2009). Threat or coping appraisal: determinants of SMB executives’ decision to adopt anti-malware software. European Journal of Information Systems, 18(2), 177-187.
    Li, H., Sarathy, R., & Xu, H. (2010). Understanding situational online information disclosure as a privacy calculus. Journal of Computer Information Systems, 51(1), 62-71.
    Li, H., Wu, J., Gao, Y., & Shi, Y. (2016). Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective. International Journal of Medical Informatics, 88, 8-17.
    Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471-481.
    Longhurst, C. A., Harrington, R. A., & Shah, N. H. (2014). A ‘green button’ for using aggregate patient data at the point of care. Health Affairs, 33(7), 1229-1235.
    Lwin, M., Wirtz, J., & Williams, J. D. (2007). Consumer online privacy concerns and responses: a power–responsibility equilibrium perspective. Journal of the Academy of Marketing Science, 35(4), 572-585.
    MacKenzie, S. B., Podsakoff, P. M., & Jarvis, C. B. (2005). The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions. Journal of Applied Psychology, 90(4), 710-730.
    Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users` information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336-355.
    McCallister, E. (2010). Guide to protecting the confidentiality of personally identifiable information. Pennsylvania, PA: Diane Publishing.
    Meinert, D. B., Peterson, D. K., Criswell, J. R., & Crossland, M. D. (2006). Privacy policy statements and consumer willingness to provide personal information. Journal of Electronic Commerce in Organizations (JECO), 4(1), 1-17.
    Mergel, I. (2016). Agile innovation management in government: A research agenda. Government Information Quarterly, 33(3), 516-523.
    Mills, J. L. (1993). Data torturing. The New England Journal of Medicine, 329(16), 1196-1199.
    Miltgen, C. L., & Smith, H. J. (2015). Exploring information privacy regulation, risks, trust, and behavior. Information & Management, 52(6), 741-759.
    Milutinovic, M., & De Decker, B. (2015). Privacy-Friendly Management of Electronic Health Records in the eHealth Context. In C. Dolicanin, E. Kajan, D. Randjelovic, & B. Stojanovic (Eds.). Handbook of research on democratic strategies and citizen-centered e-government services (pp. 251-264). Pennsylvania, PA: IGI Global.
    Monecke, A., & Leisch, F. (2012). semPLS: Structural equation modeling using partial least squares. Retrieved March 10, 2020, from https://cran.r-project.org/web/packages/semPLS/vignettes/semPLS-intro.pdf.
    Moore, G. C., & Benbasat, I. (1996). Integrating diffusion of innovations and theory of reasoned action models to predict utilization of information technology by end-users. In Kautz, K., & Pries-Heje, J. (Eds.). Diffusion and adoption of information technology (pp. 132-146). Springer, Boston, MA.
    Mutimukwe, C., Kolkowska, E., & Grönlund, Å. (2019). Information privacy in e-service: Effect of organizational privacy assurances on individual privacy concerns, perceptions, trust and self-disclosure behavior. Government Information Quarterly. Retrieved from https://www.sciencedirect.com/science/article/pii/S0740624X19300735.
    Norberg, P. A., Horne, D. R., & Horne, D. A. (2007). The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100-126.
    Papadopoulou, P., M. Nikolaidou, & D. Martakos (2010, January). What is trust in e- government? A proposed typology. The 43th Hawaii International Conference on System Sciences, Koloa, Kauai, HI, USA.
    Perry, J. L. (2012). How can we improve our science to generate more usable knowledge for public professionals?. Public Administration Review, 72(4), 479-482.
    Phelps, J., Nowak, G., & Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy & Marketing, 19(1), 27-41.
    Poikola, A., Kuikkaniemi, K., & Honko, H. (2015). Mydata a nordic model for human-centered personal data management and processing. Finnish Ministry of Transport and Communications.
    Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change1. The Journal of Psychology, 91(1), 93–114.
    Roth, A. E. (1995). Introduction to experimental economics. In Kagel, J. H. & Roth, A. E. (Eds.) The Handbook of Experimental Economics (pp. 3-109). Princeton, NJ: Princeton University Press.
    Sang, S., Lee, J. D., & Lee, J. (2009). E-government adoption in ASEAN: the case of Cambodia. Internet Research, 19(5), 517-534.
    Shadbolt, N. (2013). Midata: towards a personal information revolution. In O`Hara, K., Waidner, M., & Hildebrandt, M. (Eds.). Digital Enlightenment Yearbook 2013: The Value of Personal Data (pp. 202-224). IOS Press.
    Sheng, H., Nah, F. F. H., & Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 15.
    Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: an interdisciplinary review. MIS Quarterly, 35(4), 989-1016.
    Steinfeld, N. (2017). Track me, track me not: Support and consent to state and private sector surveillance. Telematics and Informatics, 34(8), 1663-1672.
    Stone, E. F., & Stone, D. L. (1990). Privacy in organizations: Theoretical issues, research findings, and protection mechanisms. Research in Personnel and Human Resources Management, 8(3), 349-411.
    Stone, E. F., Gueutal, H. G., Gardner, D. G., & McClure, S. (1983). A field experiment comparing information-privacy values, beliefs, and attitudes across several types of organizations. Journal of Applied Psychology, 68(3), 459.
    Stoycheff, E. (2016). Under surveillance: Examining Facebook’s spiral of silence effects in the wake of NSA Internet monitoring. Journalism & Mass Communication Quarterly, 93(2), 296-311.
    Stoycheff, E., Liu, J., Xu, K., & Wibowo, K. (2019). Privacy and the panopticon: Online mass surveillance’s deterrence and chilling effects. New Media & Society, 21(3), 602-619.
    Teo, T. S., Srivastava, S. C., & Jiang, L. (2009). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-132.
    Thompson, N., Ravindran, R., & Nicosia, S. (2015). Government data does not mean data governance: Lessons learned from a public sector application audit. Government Information Quarterly, 32(3), 316-322.
    Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143.
    Tsai, J. Y., Egelman, S., Cranor, L., & Acquisti, A. (2011). The effect of online privacy information on purchasing behavior: An experimental study. Information Systems Research, 22(2), 254-268.
    Turvey, C., Klein, D., Fix, G., Hogan, T. P., Woods, S., Simon, S. R., ... & Wakefield, B. (2014). Blue Button use by patients to access and share health record information using the Department of Veterans Affairs` online patient portal. Journal of the American Medical Informatics Association, 21(4), 657-663.
    Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
    Wang, J. C., & Chang, C. H. (2013). How online social ties and product-related risks influence purchase intentions: A Facebook experiment. Electronic Commerce Research and Applications, 12(5), 337-346.
    Wang, T., Duong, T. D., & Chen, C. C. (2016). Intention to disclose personal information via mobile applications: A privacy calculus perspective. International Journal of Information Management, 36(4), 531-542.
    Warkentin, M., Gefen, D., Pavlou, P., & Rose, G. (2002). Encouraging Citizen Adoption of e-Government by Building Trust. Electronic Markets, 12(3), 157-162.
    Wells, C., & Thorson, K. (2017). Combining big data and survey techniques to model effects of political content flows in Facebook. Social Science Computer Review, 35(1), 33-52.
    Wirtz, J., Lwin, M. O., & Williams, J. D. (2007). Causes and consequences of consumer online privacy concern. International Journal of Service Industry Management, 18(4), 326-348.
    Xie, E., Teo, H. H., & Wan, W. (2006). Volunteering personal information on the internet: Effects of reputation, privacy notices, and rewards on online consumer behavior. Marketing Letters, 17(1), 61-74.
    Xu, H., Luo, X. R., Carroll, J. M., & Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision-making process for location-aware marketing. Decision Support Systems, 51(1), 42-52.
    Xu, H., Teo, H. H., Tan, B. C., & Agarwal, R. (2009). The role of push-pull technology in privacy calculus: the case of location-based services. Journal of Management Information Systems, 26(3), 135-174.
    Description: 碩士
    國立政治大學
    公共行政學系
    105256015
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105256015
    Data Type: thesis
    DOI: 10.6814/NCCU202000421
    Appears in Collections:[公共行政學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    601501.pdf2841KbAdobe PDF258View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback