隨著科技日新月異，技術不斷創新突破和網際網路蓬勃的發展，改變了人們的生活與習慣。透過網路的普及開始出現許多不同型態的社群網站，利用網路拓展其交友圈成為新趨勢，因此社群網站改變了人們的溝通方式為媒體的帶來新的樣貌。
發布貼文、關注他人動態消息、上傳照片，或瀏覽別人的相簿、影片等，已成為我們日常生活的一部分，社群媒體改變了以往的傳播方式，讓使用者與社群的互動更緊密，成為最有影響力的媒體。然而，因著社群網站緊密串連的特性，使用者在什麼地方、什麼時間、做什麼事以及和誰互動，都讓自己的資訊隱私在網路上無所遁形。
因此，隱私疑慮成為許多社群網站用戶的主要問題，但許多研究表明，用戶的資訊披露行為與他們的擔心疑慮有所不一致，而行為與疑慮之間的鴻溝差距被稱為隱私悖論。
本研究運用解釋水平理論對隱私悖論進行探討，按照理論定義事物與心理距離較遠時會以抽象的方式描述，反之，與心理距離較近時會以更具體的方式呈現。因此，本研究以隱私疑慮和科技樂觀作為遠期意圖，而模仿他人、習慣、感知有用性和隱私資訊不對稱為近期意圖，來探討使用者在面對隱私疑慮時，對繼續使用社群網站龍頭之Facebook有何影響。
研究發現，消費者的隱私疑慮對遠期使用意圖無相關性，且隱私疲勞在這兩者間也無調節作用，但科技樂觀對遠期使用意圖卻有正相關性；而就近期使用意圖而言，唯有感知有用性為無相關性，而模仿他人、習慣和隱私資訊不對稱則都有相關性。此外，根據解釋水平理論之定義，高解釋水平對遠期意圖的相關性會大於近期意圖，反之，低解釋水平對近期意圖的相關性會大於遠期意圖，而經交叉測試後發現兩者的差異性不大，高解釋水平和低解釋水平無法明顯被區分開，因此本研究認為此理論仍然值得繼續探討驗證。

New technological advancements have drastically changed our lives. The internet has become one of our necessities, improving our way of lives and bringing us more convenience than ever. For example, the use of social networking sites (SNSs) allows internet users to further expand their social circles, making our communications faster and more convenient.
Posting online content, updating latest news or fads, uploading photos, browsing music albums or videos, have become a part of our daily routines. SNS has changed the way we communicate, allowing us to interact more closely with the (online) community, particularly those in the more influential media. As SNSs are closely linked to one another, users are able to access them anywhere and anytime, to interact with anyone with convenience.
Privacy issues have become a major problem in the online community as studies have shown that internet users' information disclosure behavior is inconsistent with their dispositions and perceptions regarding privacy. The gap between behavior and concern is called the Privacy Paradox.
This research applies the Construal Level Theory to discuss the Privacy Paradox. Construal Level Theory is a social psychology theory that describes the relationship between psychological distance and the extent to which people’s thinking (about objects or events) is abstract (or concrete). It will be presented in a more specific way as it gets psychologically nearer. Therefore, to discuss the impact to users on privacy issues while using the mainstream SNS such as Facebook, this study explores the following constructs relating to the Distant-Future Intentions and Near-Future Intentions. Privacy Concerns and Technological Optimism constructs are presumed to be related more with the Distant-Future Intentions. Near-future Intentions related constructs factors are Imitation of Others, Habit, Perceived Usefulness, and Privacy Information Asymmetry.
The research has shown that Privacy Concerns have no correlation with Distant-Future Usage Intentions, and Privacy Fatigue has no moderating effect between the two. However, Technology Optimizing has a positive correlation with Distant-Future Usage Intentions. Imitating Others, Habit and Privacy Information Asymmetry have a positive correlation with Near-Future Usage Intentions, whereas Perceived Usefulness will not have that correlation. In addition, the test of the difference between two dependent correlations found that near-distant and future-distant cannot be clearly distinguished, which means this theory is still worth exploring and verifying to reconstruct.

英文部分：
 Aarts, H., Verplanken, B., & Knippenberg, A. (1998). Predicting behavior from actions in the past: repeated decision making or a matter of habit?. Journal of Applied Social Psychology, 28, 1355-1374.
 Acquisti, A., & Grossklags, J. (2003). Losses, gains, and hyperbolic discounting: An experimental approach to information security attitudes and behavior. Economics of Information Security, 1-27.
 Acquisti, A., & Gross, R. (2006). Imagined communities: awareness, information sharing, and privacy on the Facebook, In Proceedings of the 6th Workshop on Privacy Enhancing Technologies (PET 2006),36-58.
 Acquisti, A., & Grossklags, J. (2007). What can behavioral economics teach us about privacy? In: Digital Privacy: Theory, Technologies and Practices. New York: Auerbach Publications (Taylor and Francis Group).
 Acquisti, A., Brandimarte, L., & Lcewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509-514.
 Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. New York: Sage Publications.
 Ajzen, I. (1991). The theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
 Akerlof, G. A. (1970). The Market for "Lemons": Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), 488-500.
 Alderman, E., & Kennedy, C. (1995). The Right to Privacy. New York: Knopf.
 Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
 Ax, S., Gregg, V. H., & Jones, D. (2001). Coping and illness cognitions: chronic fatigue syndrome. Clinical Psychology Review, 21(2), 161-82.
 Baek, Y. M., Kim, E-M., & Bae, Y. (2014). My privacy is okay, but theirs is endangered: Why comparative optimism matters in online privacy concerns. Computers in Human Behavior, 31(1), 48-56.
 Barnes, J. A. (1954). Class and Committees in a Norwegian Island Parish. Human Relations, 7, 39-58.
 Barnes, S. B. (2006). A privacy paradox: Social networking in the United States. First Monday, 11(9).
 Barnes, S. J. (2011). Understanding use continuance in virtual worlds: Empirical test of a research model. Information & Management, 48, 313-319.
 Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
 Belanger, F., & Crossler, R. E. (2011). Privacy in the Digital Age: A Review of Information Privacy Research in Information Systems. MIS Quarterly, 35(4), 1017-1041.
 Berendt, B., Gunther, O., & Spiekermann, S. (2005). Privacy in E-commerce: Stated Preferences vs. Actual Behavior. Communications of the ACM, 48, 101-106.
 Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214.
 Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3),351-370.
 Boyd, D., & Hargittai, E. (2010). Facebook privacy settings: Who cares?. First Monday, 15(8).
 Chellappa, R., & Sin, R. (2005). Personalization vs. privacy: an empirical examination of online consumers dilemma. Information Technology and Management, 6(2), 181-202.
 Chen, B., & Marcus, J. (2012). Students’ self-presentation on Facebook: An examination of personality and self-construal factors. Computers in Human Behavior, 28(6), 2091-2099.
 Cheung, C. M., Chiu, P. Y., & Lee, M. K.(2011). Online social networks: Why do students use Facebook? Computers in Human Behavior, 27(4), 1337-1343.
 Chin, W. W. (1998). Issues and Opinion on Structural Equation Modeling. MIS Quarterly, 22(1).
 Chiu, C. M., Hsu, M. H., Lai, H., & Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53(4), 835-845.
 Choi, H., Park, J., & Jung, Y. (2018). The role of privacy fatigue in online privacy behavior. Computers in Human Behavior, 81,42-51.
 Christofides, E., Muise, A., & Desmarais, S. (2009). Information disclosure and control on Facebook: are they two sides of the same coin or two different processes?. Cyberpsychology & behavior, 12(3), 341-345.
 Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73.
 Cialdini, R. (1984). Influence: how and why people agree to things. New York: William Morrow and Company.
 Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334.
 Crossler, R. E., & Bélanger, F. (2019). Why Would I Use Location-Protective Settings on My Smartphone? Motivating Protective Behaviors and the Existence of the Privacy Knowledge–Belief Gap. Information Systems Research, 30(3),995-1006.
 Danah, M. B., & Nicole, B. E. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230.
 Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology)
 Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
 Debatin, B., Lovejoy, J. P., Horn, A. K. and Hughes, B. N. (2009). Facebook and Online Privacy: Attitudes, Behaviors, and Unintended Consequences. Journal of Computer-Mediated Communication, 15(1), 83-108.
 Dienlin, T., & Trepte, S. (2015). Is the privacy paradox a relic of the past? An in-depth analysis of privacy attitudes and privacy behaviors. European Journal of Social Psychology, 45(3), 285-297.
 Dinev, T., & Hart, P. (2006). An Extended Privacy Calculus Model for E-Commerce Transactions. Information Systems Research, 17(1), 61-80.
 Dinev, T., Xu, H., Smith, J. H., & Hart, P. (2013). Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts. European Journal of Information Systems, 22, 295–316.
 Douglas, W. O. (1952). Public Utilities Commission of the District of Columbia v. Pollak. Retrieved from https://supreme.justia.com/cases/federal/us/343/451/ (March 18, 2020)
 Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119-134.
 Eyal, T., Liberman, N., & Trope, Y. (2004). The pros and cons of temporally near and distant action. Journal of Personality and Social Psychology, 86(6), 781-795.
 Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
 Forster, J., Liberman, N., & Shapira, O. (2009). Preparing for novel versus familiar events: Shifts in global and local processing. Journal of Experimental Psychology: General, 138(3), 383-399.
 Freitas, A. L., Langsam, K. L., Clark, S., & Moeller, S. J. (2008). Seeing oneself in one's choices: Construal level and self-pertinence of electoral and consumer decisions. Journal of Experimental Social Psychology, 44(4), 1174-1179.
 Fried, C. (1968). Privacy, The Yale Law Journal,77, 475-482.
 Fujita, K., Eyal, T., Chaiken, S., Trope, Y., & Liberman, N. (2008). Influencing attitudes toward near and distant objects. Journal of Experimental Social Psychology, 44(3), 562-572.
 Goffman, E. (1959). The presentation of self in everyday life. Three Penny Review, 21(116), 14-15.
 Gold, A.H., Malhotra, A., & Segars, A.H. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18(1) ,185‐214.
 Gorsuch, R. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
 Gulnar, B., Balcı, S., & Cakır, V. (2010). Motivations of Facebook, Youtube and similar web sites users. Bilig Journal of Social Sciences of the Turkish World, 54, 161-184.
 Guo, X., Zhang, X., & Sun, Y. (2016). The privacy–personalization paradox in mHealth services acceptance of different age groups. Electronic Commerce Research and Applications, 16(2), 55-65.
 Hair, J. F., Anderson. R. E., Tatham. R. L., & Black. W. C., (1992). Multivariate Data Analysis with Reading 3 rd ed, New York: Macmillan.
 Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-151.
 Hair, J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool for Business Research. European Business Review, 26(2), 106-121.
 Hair, J., Sarstedt, M., & Ringle, C. M. (2017). Partial Least Squares Structural Equation Modeling. New York: Springer.
 Hallam, C., & Zanella, G. (2017). Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards. Computers in Human Behavior, 68, 217-227.
 Hansen, J., Alves, H., & Trope, Y. (2016). Psychological distance reduces literal imitation: Evidence from an imitation-learning paradigm. Journal of Experimental Psychology: Human Perception and Performance, 42(3), 320-330.
 Haythornthwaite, C. (2005). Social Networks and Internet Connectivity Effects. Information, Communication & Society, 8(2), 125-147.
 Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
 Herzog, S. M., Hansen, J., & Wanke, M. (2007). Temporal distance and ease of retrieval. Journal of Experimental Social Psychology, 43(3), 483-488.
 HEW (U.S. Department of Health, Education, and Welfare). (1973). Records, Computers, and the Rights of Citizens: Report of the Secretary’s Advisory Committee on Automated Personal Data Systems, U.S. Government Printing Office, Washington, D.C.
 Ho, A., Maiga, A., & Aimeur, E. (2009). Privacy Protection Issues in Social Networking Sites. In Computer Systems and Applications, 1, 271-278
 Hoffman, D., Novak, T. P., & Peralta, M. A. (1999). Building Consumer Trust Online. Communications of the ACM, 42(4), 80-85.
 Hofstede, G. (1980) Culture’s Consequences: International Differences in Work-related Values. New York: SAGE Publications.
 Horzum, M. B. (2016). Examining the relationship to gender and personality on the purpose of Facebook usage of Turkish university students. Computers in Human Behavior, 64, 319-328.
 Hsu, C. W. (2007). Staging on the Internet: Research on online photo album users in Taiwan with the spectacle/performance paradigm. Cyberpsychology & Behavior, 10(4), 596-600.
 Hughes-Roberts, T. (2013). Privacy and Social Networks: Is Concern a Valid Indicator of Intention and Behaviour?. IEEE, 909-912.
 Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20, 195-204.
 International Telecommunication Union. (2018). ITU releases 2018 global and regional ICT estimates. Retrieved from https://www.itu.int/en/mediacentre/Pages/2018-PR40.aspx (March 18, 2020)
 James, L. R., & Brett, J. M. (1984). Mediators, moderators, and tests for mediation. Journal of Applied Psychology, 69(2), 307-321.
 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), 203-227.
 Jiga-Boy, G. M., Clark, A. E., & Semin, G. R. (2013). Situating Construal Level: The Function of Abstractness and Concreteness in Social Contexts. Social Cognition, 31(2),201-221
 Jin, C. (2013). The perspective of a revised TRAM on social capital building: The case of Facebook usage. Information & Management, 50(4),162-168.
 Joinson, A. (2008). Looking at, Looking up or Keeping up with people? Motives and uses of Facebook. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1027-1036.
 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.
 Kiesler, C.A., Collins, B.E., & Miller, N. (1969). Attitude change: a critical analysis of theoretical approaches. New York: John Wiley and Sons.
 Kim, G. S., Park, S-B., & Oh, J. (2008). An examination of factors influencing consumer adoption of short message service (SMS). Psychology and Marketing, 25(8), 769-786.
 Kivetz, Y., & Tyler, T. R. (2007). Tomorrow I'll be me: The effect of time perspective on the activation of idealistic versus pragmatic selves. Organizational Behavior and Human Decision Processes, 102(2), 193-211.
 Kraemer, H. C., & Blasey, C. M. (2004). Centring in regression analyses: a strategy to prevent errors in statistical inference. International Journal of Methods in Psychiatric Research, 13(3), 141-51.
 Kreilinger, V., & Sevignani, S. (2014). Online Privacy Paradox and Social Networks. New York: Springer.
 Lascu, D., & Zinkhan, G. M. (1999). Consumer conformity: Review & applications for marketing theory & practice. Journal of Marketing Theory and Practice, 7(3), 1-12.
 Lauren Feiner. (2019, August 23). Facebook learned about Cambridge Analytica as early as September 2015, new documents show. CNBC News. Retrieved from https://www.cnbc.com/2019/08/23/facebook-releases-new-cambridge-analytica-documents.html (March 20, 2020)
 Lee, H., Park, H., & Kim, J. (2013). Why do people share their context information on Social Network Services? A qualitative study and an experimental study on users' behavior of balancing perceived benefit and risk. International Journal of Human-Computer Studies, 71(9), 862-877.
 Lee, I. A., & Preacher, K. J. (2013). Calculation for the test of the difference between two dependent correlations with one variable in common [Computer software]. Retrieved April 20, 2020, from http://quantpsy.org
 Lee, J. M., & Rha, J. Y. (2016). Personalization-privacy paradox and consumer conflict with the use of location-based mobile commerce. Computers in Human Behavior, 63(5), 453-462.
 Levav, J., Heitmann, M., Herrmann, A., & Iyengar, S. (2010). Order in product customization decisions: Evidence from field experiments. Journal of Political Economy, 118(2), 274-299.
 Lewin, K. (1951). Field theory in social science: Selected theoretical papers (edited by dorwin cartwright.).
 Liberman, N., & Trope, Y. (1998). The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology, 75(1), 5–18.
 Liberman, N., Sagristano, M. D., & Trope, Y. (2002). The effect of temporal distance on level of mental construal. Journal of Experimental Social Psychology, 38(6), 523-534.
 Liberman, N., Trope, Y., & Stephan, E. (2007). Psychological distance. Social Psychology: Handbook of Basic Principles, 2, 353-383.
 Likert, R. (1932). A technique for measurement of attitudes. Archives of Psychology, 140, 5-55.
 Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. Management Information Systems Quarterly, 31(4), 705-737.
 Lindqvist, J., Cranshaw, J., Wiese, J., Hong, J., & Zimmerman, J. (2011). I'm the mayor of my house: examining why people use foursquare - a social-driven location sharing application. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2409-2418.
 Ling, L. M., & Moi, C. (2007). Professional students’ technology readiness, prior computing experience and acceptance of an e-Learning System. Malaysian Accounting Review, 6(1), 85-99.
 Liu, Q., Shao, Z., & Fan, W. (2018). The impact of users’ sense of belonging on social media habit formation: Empirical evidence from social networking and microblogging websites in China. International Journal of Information Management, 43, 209-223.
 Lu, J. (2014). Are personal innovativeness and social influence critical to continue with mobile commerce?. Internet Research, 24(2), 134-159.
 Lutz, C., & Strathoff, P. (2014). Privacy Concerns and Online Behavior – Not so Paradoxical after All? Viewing the Privacy Paradox Through Different Theoretical Lenses.  SSRN Electronic Journal, 81-99.
 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.
 Marsden, P. V., & Campbell, K. E. (1984). Measuring Tie Strength. Social Forces, 63, 482-501.
 Marx, G. T. (1996).Privacy and Technology. Retrieved from https://web.mit.edu/gtmarx/www/privantt.html (March 28, 2020)
 Marx, G. (2001). Murky Conceptual Waters: The Public and the Private. Ethics and Information Technology, 3(3),157-169.
 Metcalfe, J., & Mischel, W. (1999). A hot/cool-system analysis of delay of gratification: Dynamics of willpower. Psychological Review, 106(1), 3-19.
 Mims, C. (2018). Privacy Is Dead. Here’s What Comes Next. Retrieved from https://www.wsj.com/articles/privacy-is-dead-heres-what-comes-next-1525608001 (April 23, 2020)
 Mowen, J. C., & Minor, M. (1998). Consumer Behavior. Journal of Marketing Management, 5, 487-489.
 Nabavi, A., Taghavifard, M., Hanafizadeh, P., & Taghva, R. (2016). Information Technology Continuance Intention: A Systematic Literature Review. International Journal of e-Business Research, 12(1), 58-95.
 New poll reveals 7 in 10 people want governments to regulate Big Tech over personal data fears. (December 4, 2019). Amnesty International. Retrieved from https://www.amnesty.org/en/latest/news/2019/12/big-tech-privacy-poll-shows-people-worried/ (March 18, 2020)
 Nilsen, P., Roback, K., Brostrom, A., & Ellstrom, P. E. (2012). Creatures of habit: accounting for the role of habit in implementation research on clinical behaviour change. Implementation Science, 7(1) ,53.
 Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). NY: McGraw-Hill, Inc.
 Oetzel, M., & Gonja, T. (2011). The online privacy paradox: A social representations perspective. Extended Abstracts on Human Factors in Computing Systems, 2107–2112.
 Olivia Solon & Cyrus Farivar. (2019, November 6). Leaked documents show Facebook leveraged user data to fight rivals and help friends. NBC News. Retrieved from https://www.nbcnews.com/news/all/leaked-documents-show-facebook-leveraged-user-data-fight-rivals-help-n1076986 (March 20, 2020)
 Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54–74.
 Pavlou, P. A. (2011). State of The Information Privacy Literature: Where Are We Now and Where Should We Go?. MIS Quarterly, 35(4), 977-988.
 Pentina, I., Zhang, L., Bata, H., & Chen, Y. (2016). Exploring privacy paradox in information-sensitive mobile app adoption: A cross-cultural comparison. Computers in Human Behavior, 65(9), 409-419.
 Petronio, S. (2000). The boundaries of privacy: Praxis of everyday life. New Jersey: Lawrence Erlbaum Associates.
 Petronio, S. (2002). Boundaries of privacy: Dialectics of disclosure. New York: State University of New York Press.
 Phelps, J. E., Nowak, G. J., & Ferrell, E. (2000). Privacy Concerns and Consumer Willingness to Provide Personal Information. Journal of Public Policy and Marketing, 19(1), 27-41.
 Pirouz, D. (2016). An Overview of Partial Least Squares. Available at SSRN Electronic Journal: https://ssrn.com/abstract=1631359 or http://dx.doi.org/10.2139/ssrn.1631359
 Potempa, K., Lopez, M., Reid, C., & Lawson, L. (1986). Chronic Fatigue. Journal of Nursing Scholarship, 18(4), 165-169.
 PPSC (Privacy Protection Study Commission). (1977). Personal Privacy in an Information Society: Report of the Privacy Protection Study Commission, U.S. Government Printing Office, Washington, D.C.
 Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891
 Pronin, E., & Ross, L. (2006). Temporal differences in trait self-ascription: When the
self is seen as an other. Journal of Personality and Social Psychology, 90(2), 197-209.
 Prosser, W. (1960). Privacy. California Law Review, 48, 383-423.
 Rambam, S. (2010). Privacy Is Dead, Get Over It. Retrieved April 24, 2020, from https://www.youtube.com/watch?v=DaYn_PkrfvQ
 Ream, E., & Richardson, A. (1996). Fatigue: A concept analysis. International Journal of Nursing Studies, 33(5), 519-529.
 Ringle, C. M., Wende, S., & Will, A. (2020). SmartPLS-Version 3.2.9 Germany: University at Hamburg. Retrieved April 13, 2020, from http://www.smartpls.de.
 Rogers, T., & Bazerman, M. H. (2008). Future lock-in: Future implementation increases selection of 'should' choices. Organizational Behavior and Human Decision Processes, 106(1), 1-20.
 Ryan, T., & Xenos, S. (2011). Who uses Facebook? An investigation into the relationship between the big five, shyness, narcissism, loneliness, and Facebook usage. Computers in Human Behavior, 27(5), 1658-1664.
 Sauro, J., & Lewis, J. R. (2016). Quantifying the User Experience: Practical Statistics for User Research. Burlington, MA, USA: Morgan Kaufmann.
 Scheier, M. F., & Carver, C. S. (1987). Dispositional Optimism, and physical well-being: the influence of generalized outcome expectancies on health. Journal of Personality and Social Psychology, 55, 169-210.
 Scheier, M. F., & Carver, C. S. (1992). Effects of optimism on psychological and physical well-being: Theoretical overview and empirical update. Cognitive Therapy and Research, 16, 201-228.
 Seidman, G. (2013). Self-presentation and belonging on Facebook: How personality influences social media use and motivations. Personality and Individual Differences, 54(3), 402-407.
 Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information Privacy: Measuring Individuals' Concerns about Organizational Practices. MIS Quarterly, 20(2), 167-196.
 Smith, H. J., Dinev, T., & Xu, H. (2011). Information Privacy Research: An Interdisciplinary Review. MIS Quarterly, 35(4), 989-1015.
 Sobel, M. E. (1982). Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models. Sociological Methodology, 13, 290-321.
 Solomon, M. R., White, K., Dahl, D., Zaichkowsky, J. L., & Polegato, R. (2014). Consumer behaviour : buying, having, and being. Toronto : Pearson.
 Solove, D. J.(2002). Conceptualizing Privacy. California Law Review, 90, 1087-1152.
 Statista. (2020). Most popular social networks worldwide as of January 2020, ranked by number of active users (in millions). Retrieved from https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/ (March 18, 2020)
 Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245-251.
 Sudman, S. (1976). Applied Sampling. New York: Academic Press.
 Sun, H. (2009). Understanding Herd Behavior in Technology Adoption and Continued Use: A Longitudinal Perspective. DIGIT 2009 Proceedings. Paper 11
 Taddicken, M. (2014). The ‘Privacy Paradox’ in the Social Web: The Impact of Privacy Concerns, Individual Characteristics, and the Perceived Social Relevance on Different Forms of Self‐Disclosure. Journal of Computer-Mediated Communication, 19(2), 248–273.
 Technopedia. (2011). Definition of social media fatigue. Retrieved from www.techopedia.com/definition/27372/social-media-fatigue (April 5, 2020)
 Todorov, A., Goren, A., & Trope, Y. (2007). Probability as a psychological distance: Construal and preferences. Journal of Experimental Social Psychology, 43(3), 473-482.
 Triandis, H. C. (1980). Values, attitudes, and interpersonal behavior. Nebraska Symposium on Motivation, 27, 195-259.
 Trope, Y., & Liberman, N. (2000). Temporal construal and time-dependent changes in preference. Journal of Personality and Social Psychology, 79(6), 876-889.
 Trope, Y., & Liberman, N. (2003). Temporal construal. Psychological Review, 110(3), 403–421.
 Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance. Psychological Review, 117(2), 440-463.
 Van Slyke, C., Shim, T., Johnson, R., & Jiang, J. (2006). Concern for information privacy. Journal of the Association for Information Systems, 7(6), 415-444.
 Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behaviour: is habit an empty construct or an interesting case of goal-directed automaticity?. European Review of Social Psychology, 10, 101-134.
 Vohs, K., Baumeister, R., Schmeichel, B., Twenge, J., Nelson, N., & Tice, D. (2014). Making choices impairs subsequent self-control: A limited-resource account of decision making, self-regulation, and active initiative. Journal of Personality and Social Psychology, 94(5), 883-898.
 Walczuch, R., Lemmink, J., & Streukens, S. (2007). The effect of service employees’ technology readiness on technology acceptance. Information & Management, 44(2),206-215.
 Warren, S. D., & Brandeis, L. D. (1890). The Right to Privacy. Harvard Law Review, 4(5), 193-220.
 We Are Social ＆ Hootsuite. (2019). Digital 2019 Taiwan. Retrieved from https://datareportal.com/reports/digital-2019-taiwan (March 18, 2020)
 Westin, A. F. (1967). Privacy and Freedom. New York: Atheneum Publishers.
 Westin, A. F., & Baker, M. A. (1972). Databanks in a Free Society. New York: Quadrangle Books.
 Williams, L. J., & Hazer, J. T. (1986). Antecedents and consequences of satisfaction and commitment in turnover models: A reanalysis using latent variable structural equation methods. Journal of Applied Psychology, 71(2), 219-231.
 Wood, W., Quinn, J., & Kashy, D. (2002). Habits in everyday life: thought, emotion, and action. Journal of Personality and Social Psychology, 83, 1281-1297.
 Xu, H., Dinev, T., Smith, Jeff., & Hart, P. (2011). Information Privacy Concerns: Linking Individual Perceptions with Institutional Privacy Assurances. Journal of the Association for Information Systems, 12(12),798-824.
 Xu, H., Gupta, S., Rosson, M. B., & Carroll, J.M. (2012). Measuring Mobile Users' Concerns for Information Privacy. International Conference on Information Systems, 3, 2278-2293.
 Yu, S. C. (2015). Happiness or Addiction: An Example of Taiwanese College Students’ Use of Facebook. International Journal of Technology and Human Interaction, 11(4), 26-40.
 Zhao, L., Lu, Y., Wang, B., Chau, P. Y. K., & Zhang, L. (2012). Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective. International Journal of Information Management, 32(6), 574-588.

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