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題名 從隱私計算理論探討個人化服務對隱私資訊揭露之影響
How Personalized Services Affect Disclosure of Personal Information: A privacy calculus perspective
作者 徐愛茹
Hsu, Ai-Ju
貢獻者 梁定澎<br>彭志宏
Liang, Ting-Peng<br>Peng, Chih-Hung
徐愛茹
Hsu, Ai-Ju
關鍵詞 隱私計算理論
個人化服務
感知資訊關聯
資訊敏感度
調節焦點
Information privacy
Personalized services
Privacy calculus
Relevance theory
Regulatory focus theory
日期 2020
上傳時間 2-Sep-2020 11:47:41 (UTC+8)
摘要 網路高度普及的時代來臨,加上人工智慧、大數據分析等應用的蓬勃發展,企業得以將握有的大量數據加以處理運用後,提供更符合消費者的個人化服務。但近年來隱私意識逐漸高漲,且個人化服務涉及不少隱私資訊的揭露,消費者在享受個人化及保護個人資料兩者間需要做出取捨,了解消費者如何做出隱私相關決策以找出平衡點也成為企業的重要課題。本研究鑒於個人化服務在現今數位環境中的重要性,以及與隱私議題的密切關係,將感知資訊關聯加入隱私計算理論以建構一擴充模型,探討在個人化服務中,不同因素對於使用者個人資訊揭露的影響,另將資訊敏感度設為干擾變數,進一步觀察是否會干擾感知資訊關聯性對感知風險及利益的關聯,也加入了調節焦點理論中的調節焦點為另一干擾變數,探討不同調節焦點下,感知利益及風險對個人資訊揭露意圖之間的關係是否會被干擾而有所不同。本研究使用問卷調查法在網路上發放問卷後,透過SmartPLS 3對回收之樣本以結構方程模式分析,並確認信度與效度後,對研究架構進行假說的檢定,研究結果發現感知資訊關聯會正向顯著影響感知利益、負向顯著影響感知風險,干擾變數調節焦點的效果則不顯著,表示不同調節焦點的人不會對感知利益及風險對個人資訊揭露意圖之間的關係有放大或縮小的效果,資訊敏感度則會調節感知資訊關聯與感知利益的關係。
Personalized services play a significant role in the current digital environment and have a close relationship with privacy issues. This research combines perceived information relevance and privacy calculus theory to build an expanded model to discuss how perceived information relevance impacts perceived benefits and perceived risks in personalized services. Regulatory focus of the user is treated as a moderator to discuss whether the regulatory focus (promoting focus/prevention focus) affect the impact of the perceived benefits and perceived risks on the intention to disclose personal information.
This research adopted the online experimental method that recruited subjects to fill out questionnaires via online distribution. The collected data was analyzed using SmartPLS 3 to conduct structural equation modeling. Upon ascertaining reliability and validity and hypothesis testing on the research framework, the results indicate that perceived information relevance has a significant positive impact on perceived benefits while having a significant negative impact on perceived risks. On the other hand, the moderating variable-regulatory focus does not have a significant effect, while the effects of perceived information relevance on perceived benefits were moderated by information sensitivity.
參考文獻 一、 中文文獻:
[1] 何自然,冉永平(2000)。《關聯性:溝通與認知》導讀。外語教學與研究出版社。取自https://doi.org/10.1191/026765800673158592
[2] 賴立芸(2019)。資訊隱私悖論因素探討。國立政治大學資訊管理學系碩士論文,台北市。取自https://hdl.handle.net/11296/uzx2qt
[3] 林承穎(2017)。從調節焦點和隱私計算探討社群網站使用者隱私揭露之研究。淡江大學資訊管理學系碩士班碩士論文,新北市。取自https://hdl.handle.net/11296/xaf922
[4] 趙庭瑋(2009)。調節焦點對尋求多樣化之影響。國立臺灣大學商學研究所碩士論文,台北市。取自http://ntur.lib.ntu.edu.tw//handle/246246/184558
[5] 馬慶玲(2010)。調節焦點影響廣告效果之研究。國立政治大學心理學研究所碩士論文,台北市。 取自https://hdl.handle.net/11296/uemup5

二、 英文文獻:
[1] Anderson, C. L., &Agarwal, R. (2011). The digitization of healthcare: Boundary risks, emotion, and consumer willingness to disclose personal health information. In Information Systems Research (Vol. 22, Issue 3, pp. 469–490). https://doi.org/10.1287/isre.1100.0335
[2] 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. https://doi.org/10.1016/j.dss.2010.01.010
[3] Basyuk, D., Prymak, T., &Pohuda, N. (2018). The role of informational technologies in creating a personalized customer experience: a case study of tourism branch in Ukraine. Centre for European Studies (CES) Working Papers, 10(3),406–422. http://search.ebscohost.com/login.aspx?direct=true&db=asx&AN=133272521&lang=de&site=eds-live
[4] Brown, J. O., Broderick, A. J., &Lee, N. (2007). Online Communities : Conceptualizing the Online Social Network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir
[5] Celsi, R. L., &Olson, J. C. (1988). The Role of Involvement in Attention and Comprehension Processes. Journal of Consumer Research, 15(2), 210. https://doi.org/10.1086/209158
[6] Chellappa, R. K., &Raymond G. Sin. (2005). Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma. Information Technology and Management, 6(2–3), 181–202. https://doi.org/10.3138/cras.42.1.7
[7] Chellappa, R. K., &Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. https://doi.org/10.2753/MIS0742-1222240307
[8] Craciun, G. (2018). Choice defaults and social consensus effects on online information sharing: The moderating role of regulatory focus. Computers in Human Behavior, 88(June), 89–102. https://doi.org/10.1016/j.chb.2018.06.019
[9] Culnan, M. J., Armstrong, P. K., Science, S. O., Feb, N. J., Culnan, M. J., &Armstrong, P. K. (1999). Information Privacy Concerns , Procedural Fairness , and Impersonal Trust : An Empirical Investigation. 10(1), 104–115.
[10] Culnan, M. J., &Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323–342. https://doi.org/10.1111/1540-4560.00067
[11] Dienlin, T., &Metzger, M. J. (2016). An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample. Journal of Computer-Mediated Communication, 21(5), 368–383. https://doi.org/10.1111/jcc4.12163
[12] Dinev, T., &Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
[13] Dinev, T., Xu, H., Smith, J. H., &Hart, P. (2013). Information privacy and correlates: An empirical attempt to bridge and distinguish privacyrelated concepts. European Journal of Information Systems, 22(3), 295–316. https://doi.org/10.1057/ejis.2012.23
[14] Gauzente, C. (2004). Web Merchants’ Privacy and Security Statements : How Reassuring Are They for Consumers ? a Two-Sided Approach. Journal of Electronic Commerce Research, 5(3), 181–198.
[15] Gerber, N., Gerber, P., &Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers and Security, 77, 226–261. https://doi.org/10.1016/j.cose.2018.04.002
[16] Gupta, Ashish; Patel, Vimla L.; Greenes, R. A. (2016). Advances in Healthcare Informatics an Analytics. https://doi.org/10.1007/978-3-319-23294-2
[17] Higgins, E. T. (1998). Promotion and Prevention: Regulatory Focus as A Motivational Principle. Advances in Experimental Social Psychology, 30(C), 1–46. https://doi.org/10.1016/S0065-2601(08)60381-0
[18] Hsiao, C. H., Tsai, C. F., &Hsu, Y. H. (2012). The influences of self-construal and regulatory focus on impulsive buying behavior. NTU Management Review, 23(1), 119–150. https://doi.org/10.6226/NTURM2012.AUG.M5
[19] Jung, A. R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309. https://doi.org/10.1016/j.chb.2017.01.008
[20] 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. https://doi.org/10.1111/isj.12062
[21] Krasnova, H., Spiekermann, S., Koroleva, K., &Hildebrand, T. (2010). Online Social Networks: Why We Disclose Author Version. Journal of Information Technology, 25(2), 109–125.
[22] Krishnan, M. S., &Awad, N. F. (2006). The Personalization Privacy Paradox : An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization. 30(1), 13–28.
[23] 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.
[24] Li, H., &Sarathy, R. (2007). Understanding online information disclosure as a privacy calculus adjusted by exchange fairness. In ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems.
[25] 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. https://doi.org/10.1080/08874417.2010.11645450
[26] Li, H., Sarathy, R., &Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434–445. https://doi.org/10.1016/j.dss.2011.01.017
[27] Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471–481. https://doi.org/10.1016/j.dss.2012.06.010
[28] Liberman, N., Idson, L. C., Camacho, C. J., &Higgins, E. T. (1999). Promotion and prevention choices between stability and change. Journal of Personality and Social Psychology, 77(6), 1135–1145. https://doi.org/10.1037/0022-3514.77.6.1135
[29] Liu, X. (2013). How Are People Enticed to Disclose Personal Information Despite Privacy Concerns in Social Network Sites? The Calculus Between Benefit and Cost. Journal of the American Society for Information Science and Technology, 64(July), 1852–1863. https://doi.org/10.1002/asi
[30] Lockwood, P., Jordan, C. H., &Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864. https://doi.org/10.1037/0022-3514.83.4.854
[31] 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. https://doi.org/10.1287/isre.1040.0032
[32] Milne, G. R. (1997). Consumer participation in mailing lists: A field experiment. Journal of Public Policy and Marketing, 16(2), 298–309. https://doi.org/10.1177/074391569701600210
[33] Milne, G. R., &Gordon, M. E. (1993). Direct Mail Privacy-Efficiency Trade-offs within an Implied Social Contract Framework. Journal of Public Policy & Marketing, 12(2), 206–215. https://doi.org/10.1177/074391569101200206
[34] Milne, G. R., Pettinico, G., Hajjat, F. M., &Markos, E. (2017). Information Sensitivity Typology: Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing. Journal of Consumer Affairs, 51(1), 133–161. https://doi.org/10.1111/joca.12111
[35] Mingwei Hsu, Kharlamov, A., &Glenn Parry. (2019). Managing personalization-privacy paradox of digital services: A systematic literature review. Data for Policy.
[36] 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. https://doi.org/10.1111/j.1745-6606.2006.00070.x
[37] Nowak, G. J., &Phelps, J. (1992). Understanding privacy concerns.An assessment of consumers’ information-related knowledge and beliefs. Journal of Direct Marketing, 6(4), 28–39. https://doi.org/10.1002/dir.4000060407
[38] Odel, L. I. M., Ersuasion, I. N. P., &Angst, B. C. M. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion.pdf. Management Information Systems Quarterly, 33(2), 339–370.
[39] Pavlou, P. A., &Stewart, D. W. (2000). Measuring the Effects and Effectiveness of Interactive Advertising. Journal of Interactive Advertising, 1(1), 61–77. https://doi.org/10.1080/15252019.2000.10722044
[40] Pham, M. T., &Avnet, T. (2004). Ideals and Oughts and the Reliance on Affect versus Substance in Persuasion. Journal of Consumer Research, 30(4), 503–518. https://doi.org/10.1086/380285
[41] Phelps, J., Nowak, G., &Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing, 19(1), 27–41. https://doi.org/10.1509/jppm.19.1.27.16941
[42] Pötzsch, S. (2009). Privacy awareness: A means to solve the privacy paradox? IFIP Advances in Information and Communication Technology, 298(216483), 226–236. https://doi.org/10.1007/978-3-642-03315-5_17
[43] Rohm, A. J., &Milne, G. R. (2004). Just what the doctor ordered. The role of information sensitivity and trust in reducing medical information privacy concern. Journal of Business Research, 57(9), 1000–1011. https://doi.org/10.1016/S0148-2963(02)00345-4
[44] Sassenberg, K., Landkammer, F., &Jacoby, J. (2014). The influence of regulatory focus and group vs. individual goals on the evaluation bias in the context of group decision making. Journal of Experimental Social Psychology, 54, 153–164. https://doi.org/10.1016/j.jesp.2014.05.009
[45] Schoenbachler, D. D., &Gordon, G. L. (2002). Trust and customer willingness to provide information in database-driven relationship marketing. Journal of Interactive Marketing, 16(3), 2–16. https://doi.org/10.1002/dir.10033
[46] Sharma, S., &Crossler, R. E. (2014). Disclosing too much? Situational factors affecting information disclosure in social commerce environment. Electronic Commerce Research and Applications, 13(5), 305–319. https://doi.org/10.1016/j.elerap.2014.06.007
[47] Sheehan, K. B., &Hoy, M. G. (2000). Dimensions of Privacy Concern Among Online Consumers. Journal of Public Policy & Marketing, 19(1), 62–73.
[48] 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), 344–376.
[49] Siegrist, M., Cvetkovich, G., &Roth, C. (2000). Salient value similarity, social trust, and risk/benefit perception. Risk Analysis, 20(3), 353–362. https://doi.org/10.1111/0272-4332.203034
[50] Sitkin, S. B., &Pablo, A. L. (1992). Reconceptualizing the Determinants of Risk Behavior Author ( s ): Sim B . Sitkin and Amy L . Pablo Source : The Academy of Management Review , Vol . 17 , No . 1 ( Jan ., 1992 ), pp . 9-38 Published by : Academy of Management Stable URL : http://www.jstor. Academy of Management, 17(1), 9–38.
[51] Sperber, D., &Wilson, D. (1986). Relevance: Communication and Cognition. In Cambridge, MA: Harvard University Press. (Vol. 142). https://doi.org/10.1111/j.1468-0017.1989.tb00246.x
[52] Spiekermann, S., Grossklags, J., &Berendt, B. (2001). E-privacy in 2nd generation E-commerce: Privacy preferences versus actual behavior. Proceedings of the ACM Conference on Electronic Commerce, 38–47.
[53] Stone, D. L. (1981). The effects of the valence of outcomes for providing data and the perceived relevance of the data requested on privacy-related behaviors, beliefs, and attitudes.
[54] Sutanto, J., Palme, E., Tan, C.-H., &Phang, C. W. (2013). Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users. MIS Quarter, 37(4), 1141–1164.
[55] 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. https://doi.org/10.1016/j.ijinfomgt.2016.03.003
[56] Xu, H., Luo, X., 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. https://doi.org/10.1016/j.dss.2010.11.017
[57] Xu, H., Teo, H. H., Tan, B. C. Y., &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. https://doi.org/10.2753/MIS0742-1222260305
[58] Zhang, B., &Xu, H. (2016). Privacy nudges for mobile applications: Effects on the creepiness emotion and privacy attitudes. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 27, 1676–1690. https://doi.org/10.1145/2818048.2820073
[59] Zhang, E. M. (2010). Beauty as a tool: The effect of model attractiveness, product relevance, and elaboration likelihood on advertising effectiveness. Psychology & Marketing, 30(6), 461–469. https://doi.org/10.1002/mar
[60] Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. In Industrial Management and Data Systems (Vol. 111, Issue 2, pp. 212–226). https://doi.org/10.1108/02635571111115146
[61] Zhu, Y. Q., &Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442–447. https://doi.org/10.1016/j.chb.2016.08.048
[62] Zimmer, J. C., Arsal, R. E., Al-Marzouq, M., &Grover, V. (2010). Investigating online information disclosure: Effects of information relevance, trust and risk. Information and Management, 47(2), 115–123. https://doi.org/10.1016/j.im.2009.12.003
描述 碩士
國立政治大學
資訊管理學系
107356029
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107356029
資料類型 thesis
dc.contributor.advisor 梁定澎<br>彭志宏zh_TW
dc.contributor.advisor Liang, Ting-Peng<br>Peng, Chih-Hungen_US
dc.contributor.author (Authors) 徐愛茹zh_TW
dc.contributor.author (Authors) Hsu, Ai-Juen_US
dc.creator (作者) 徐愛茹zh_TW
dc.creator (作者) Hsu, Ai-Juen_US
dc.date (日期) 2020en_US
dc.date.accessioned 2-Sep-2020 11:47:41 (UTC+8)-
dc.date.available 2-Sep-2020 11:47:41 (UTC+8)-
dc.date.issued (上傳時間) 2-Sep-2020 11:47:41 (UTC+8)-
dc.identifier (Other Identifiers) G0107356029en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/131499-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 107356029zh_TW
dc.description.abstract (摘要) 網路高度普及的時代來臨,加上人工智慧、大數據分析等應用的蓬勃發展,企業得以將握有的大量數據加以處理運用後,提供更符合消費者的個人化服務。但近年來隱私意識逐漸高漲,且個人化服務涉及不少隱私資訊的揭露,消費者在享受個人化及保護個人資料兩者間需要做出取捨,了解消費者如何做出隱私相關決策以找出平衡點也成為企業的重要課題。本研究鑒於個人化服務在現今數位環境中的重要性,以及與隱私議題的密切關係,將感知資訊關聯加入隱私計算理論以建構一擴充模型,探討在個人化服務中,不同因素對於使用者個人資訊揭露的影響,另將資訊敏感度設為干擾變數,進一步觀察是否會干擾感知資訊關聯性對感知風險及利益的關聯,也加入了調節焦點理論中的調節焦點為另一干擾變數,探討不同調節焦點下,感知利益及風險對個人資訊揭露意圖之間的關係是否會被干擾而有所不同。本研究使用問卷調查法在網路上發放問卷後,透過SmartPLS 3對回收之樣本以結構方程模式分析,並確認信度與效度後,對研究架構進行假說的檢定,研究結果發現感知資訊關聯會正向顯著影響感知利益、負向顯著影響感知風險,干擾變數調節焦點的效果則不顯著,表示不同調節焦點的人不會對感知利益及風險對個人資訊揭露意圖之間的關係有放大或縮小的效果,資訊敏感度則會調節感知資訊關聯與感知利益的關係。zh_TW
dc.description.abstract (摘要) Personalized services play a significant role in the current digital environment and have a close relationship with privacy issues. This research combines perceived information relevance and privacy calculus theory to build an expanded model to discuss how perceived information relevance impacts perceived benefits and perceived risks in personalized services. Regulatory focus of the user is treated as a moderator to discuss whether the regulatory focus (promoting focus/prevention focus) affect the impact of the perceived benefits and perceived risks on the intention to disclose personal information.
This research adopted the online experimental method that recruited subjects to fill out questionnaires via online distribution. The collected data was analyzed using SmartPLS 3 to conduct structural equation modeling. Upon ascertaining reliability and validity and hypothesis testing on the research framework, the results indicate that perceived information relevance has a significant positive impact on perceived benefits while having a significant negative impact on perceived risks. On the other hand, the moderating variable-regulatory focus does not have a significant effect, while the effects of perceived information relevance on perceived benefits were moderated by information sensitivity.
en_US
dc.description.tableofcontents 謝辭 i
摘要 ii
目次 iv
表次 vi
圖次 vii
第一章 緒論 1
研究背景與動機 1
研究目的 4
研究流程 5
第二章 文獻探討 6
第一節 個人化服務 6
第二節 隱私悖論 9
第三節 隱私計算理論 11
第四節 感知資訊關聯 14
第五節 資訊敏感度 17
第六節 調節焦點理論 19
第三章 研究架構與方法 21
第一節 研究架構 21
第二節 研究假說 22
第三節 研究方法 27
第四節 實驗設計 36
第四章 研究分析與結果 51
第一節 資料收集與樣本結構分析 51
第二節 樣本檢驗與信效度分析 54
第三節 結構模型分析與假說檢定 58
第四節 研究假設驗證結果 66
第五章 研究結論與建議 68
第一節 研究結果與討論 68
第二節 研究貢獻與建議 70
第六章 參考文獻 73
附件 83
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dc.format.extent 4052177 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107356029en_US
dc.subject (關鍵詞) 隱私計算理論zh_TW
dc.subject (關鍵詞) 個人化服務zh_TW
dc.subject (關鍵詞) 感知資訊關聯zh_TW
dc.subject (關鍵詞) 資訊敏感度zh_TW
dc.subject (關鍵詞) 調節焦點zh_TW
dc.subject (關鍵詞) Information privacyen_US
dc.subject (關鍵詞) Personalized servicesen_US
dc.subject (關鍵詞) Privacy calculusen_US
dc.subject (關鍵詞) Relevance theoryen_US
dc.subject (關鍵詞) Regulatory focus theoryen_US
dc.title (題名) 從隱私計算理論探討個人化服務對隱私資訊揭露之影響zh_TW
dc.title (題名) How Personalized Services Affect Disclosure of Personal Information: A privacy calculus perspectiveen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 一、 中文文獻:
[1] 何自然,冉永平(2000)。《關聯性:溝通與認知》導讀。外語教學與研究出版社。取自https://doi.org/10.1191/026765800673158592
[2] 賴立芸(2019)。資訊隱私悖論因素探討。國立政治大學資訊管理學系碩士論文,台北市。取自https://hdl.handle.net/11296/uzx2qt
[3] 林承穎(2017)。從調節焦點和隱私計算探討社群網站使用者隱私揭露之研究。淡江大學資訊管理學系碩士班碩士論文,新北市。取自https://hdl.handle.net/11296/xaf922
[4] 趙庭瑋(2009)。調節焦點對尋求多樣化之影響。國立臺灣大學商學研究所碩士論文,台北市。取自http://ntur.lib.ntu.edu.tw//handle/246246/184558
[5] 馬慶玲(2010)。調節焦點影響廣告效果之研究。國立政治大學心理學研究所碩士論文,台北市。 取自https://hdl.handle.net/11296/uemup5

二、 英文文獻:
[1] Anderson, C. L., &Agarwal, R. (2011). The digitization of healthcare: Boundary risks, emotion, and consumer willingness to disclose personal health information. In Information Systems Research (Vol. 22, Issue 3, pp. 469–490). https://doi.org/10.1287/isre.1100.0335
[2] 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. https://doi.org/10.1016/j.dss.2010.01.010
[3] Basyuk, D., Prymak, T., &Pohuda, N. (2018). The role of informational technologies in creating a personalized customer experience: a case study of tourism branch in Ukraine. Centre for European Studies (CES) Working Papers, 10(3),406–422. http://search.ebscohost.com/login.aspx?direct=true&db=asx&AN=133272521&lang=de&site=eds-live
[4] Brown, J. O., Broderick, A. J., &Lee, N. (2007). Online Communities : Conceptualizing the Online Social Network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir
[5] Celsi, R. L., &Olson, J. C. (1988). The Role of Involvement in Attention and Comprehension Processes. Journal of Consumer Research, 15(2), 210. https://doi.org/10.1086/209158
[6] Chellappa, R. K., &Raymond G. Sin. (2005). Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma. Information Technology and Management, 6(2–3), 181–202. https://doi.org/10.3138/cras.42.1.7
[7] Chellappa, R. K., &Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. https://doi.org/10.2753/MIS0742-1222240307
[8] Craciun, G. (2018). Choice defaults and social consensus effects on online information sharing: The moderating role of regulatory focus. Computers in Human Behavior, 88(June), 89–102. https://doi.org/10.1016/j.chb.2018.06.019
[9] Culnan, M. J., Armstrong, P. K., Science, S. O., Feb, N. J., Culnan, M. J., &Armstrong, P. K. (1999). Information Privacy Concerns , Procedural Fairness , and Impersonal Trust : An Empirical Investigation. 10(1), 104–115.
[10] Culnan, M. J., &Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323–342. https://doi.org/10.1111/1540-4560.00067
[11] Dienlin, T., &Metzger, M. J. (2016). An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample. Journal of Computer-Mediated Communication, 21(5), 368–383. https://doi.org/10.1111/jcc4.12163
[12] Dinev, T., &Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
[13] Dinev, T., Xu, H., Smith, J. H., &Hart, P. (2013). Information privacy and correlates: An empirical attempt to bridge and distinguish privacyrelated concepts. European Journal of Information Systems, 22(3), 295–316. https://doi.org/10.1057/ejis.2012.23
[14] Gauzente, C. (2004). Web Merchants’ Privacy and Security Statements : How Reassuring Are They for Consumers ? a Two-Sided Approach. Journal of Electronic Commerce Research, 5(3), 181–198.
[15] Gerber, N., Gerber, P., &Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers and Security, 77, 226–261. https://doi.org/10.1016/j.cose.2018.04.002
[16] Gupta, Ashish; Patel, Vimla L.; Greenes, R. A. (2016). Advances in Healthcare Informatics an Analytics. https://doi.org/10.1007/978-3-319-23294-2
[17] Higgins, E. T. (1998). Promotion and Prevention: Regulatory Focus as A Motivational Principle. Advances in Experimental Social Psychology, 30(C), 1–46. https://doi.org/10.1016/S0065-2601(08)60381-0
[18] Hsiao, C. H., Tsai, C. F., &Hsu, Y. H. (2012). The influences of self-construal and regulatory focus on impulsive buying behavior. NTU Management Review, 23(1), 119–150. https://doi.org/10.6226/NTURM2012.AUG.M5
[19] Jung, A. R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309. https://doi.org/10.1016/j.chb.2017.01.008
[20] 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. https://doi.org/10.1111/isj.12062
[21] Krasnova, H., Spiekermann, S., Koroleva, K., &Hildebrand, T. (2010). Online Social Networks: Why We Disclose Author Version. Journal of Information Technology, 25(2), 109–125.
[22] Krishnan, M. S., &Awad, N. F. (2006). The Personalization Privacy Paradox : An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization. 30(1), 13–28.
[23] 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.
[24] Li, H., &Sarathy, R. (2007). Understanding online information disclosure as a privacy calculus adjusted by exchange fairness. In ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems.
[25] 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. https://doi.org/10.1080/08874417.2010.11645450
[26] Li, H., Sarathy, R., &Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434–445. https://doi.org/10.1016/j.dss.2011.01.017
[27] Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471–481. https://doi.org/10.1016/j.dss.2012.06.010
[28] Liberman, N., Idson, L. C., Camacho, C. J., &Higgins, E. T. (1999). Promotion and prevention choices between stability and change. Journal of Personality and Social Psychology, 77(6), 1135–1145. https://doi.org/10.1037/0022-3514.77.6.1135
[29] Liu, X. (2013). How Are People Enticed to Disclose Personal Information Despite Privacy Concerns in Social Network Sites? The Calculus Between Benefit and Cost. Journal of the American Society for Information Science and Technology, 64(July), 1852–1863. https://doi.org/10.1002/asi
[30] Lockwood, P., Jordan, C. H., &Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864. https://doi.org/10.1037/0022-3514.83.4.854
[31] 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. https://doi.org/10.1287/isre.1040.0032
[32] Milne, G. R. (1997). Consumer participation in mailing lists: A field experiment. Journal of Public Policy and Marketing, 16(2), 298–309. https://doi.org/10.1177/074391569701600210
[33] Milne, G. R., &Gordon, M. E. (1993). Direct Mail Privacy-Efficiency Trade-offs within an Implied Social Contract Framework. Journal of Public Policy & Marketing, 12(2), 206–215. https://doi.org/10.1177/074391569101200206
[34] Milne, G. R., Pettinico, G., Hajjat, F. M., &Markos, E. (2017). Information Sensitivity Typology: Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing. Journal of Consumer Affairs, 51(1), 133–161. https://doi.org/10.1111/joca.12111
[35] Mingwei Hsu, Kharlamov, A., &Glenn Parry. (2019). Managing personalization-privacy paradox of digital services: A systematic literature review. Data for Policy.
[36] 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. https://doi.org/10.1111/j.1745-6606.2006.00070.x
[37] Nowak, G. J., &Phelps, J. (1992). Understanding privacy concerns.An assessment of consumers’ information-related knowledge and beliefs. Journal of Direct Marketing, 6(4), 28–39. https://doi.org/10.1002/dir.4000060407
[38] Odel, L. I. M., Ersuasion, I. N. P., &Angst, B. C. M. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion.pdf. Management Information Systems Quarterly, 33(2), 339–370.
[39] Pavlou, P. A., &Stewart, D. W. (2000). Measuring the Effects and Effectiveness of Interactive Advertising. Journal of Interactive Advertising, 1(1), 61–77. https://doi.org/10.1080/15252019.2000.10722044
[40] Pham, M. T., &Avnet, T. (2004). Ideals and Oughts and the Reliance on Affect versus Substance in Persuasion. Journal of Consumer Research, 30(4), 503–518. https://doi.org/10.1086/380285
[41] Phelps, J., Nowak, G., &Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing, 19(1), 27–41. https://doi.org/10.1509/jppm.19.1.27.16941
[42] Pötzsch, S. (2009). Privacy awareness: A means to solve the privacy paradox? IFIP Advances in Information and Communication Technology, 298(216483), 226–236. https://doi.org/10.1007/978-3-642-03315-5_17
[43] Rohm, A. J., &Milne, G. R. (2004). Just what the doctor ordered. The role of information sensitivity and trust in reducing medical information privacy concern. Journal of Business Research, 57(9), 1000–1011. https://doi.org/10.1016/S0148-2963(02)00345-4
[44] Sassenberg, K., Landkammer, F., &Jacoby, J. (2014). The influence of regulatory focus and group vs. individual goals on the evaluation bias in the context of group decision making. Journal of Experimental Social Psychology, 54, 153–164. https://doi.org/10.1016/j.jesp.2014.05.009
[45] Schoenbachler, D. D., &Gordon, G. L. (2002). Trust and customer willingness to provide information in database-driven relationship marketing. Journal of Interactive Marketing, 16(3), 2–16. https://doi.org/10.1002/dir.10033
[46] Sharma, S., &Crossler, R. E. (2014). Disclosing too much? Situational factors affecting information disclosure in social commerce environment. Electronic Commerce Research and Applications, 13(5), 305–319. https://doi.org/10.1016/j.elerap.2014.06.007
[47] Sheehan, K. B., &Hoy, M. G. (2000). Dimensions of Privacy Concern Among Online Consumers. Journal of Public Policy & Marketing, 19(1), 62–73.
[48] 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), 344–376.
[49] Siegrist, M., Cvetkovich, G., &Roth, C. (2000). Salient value similarity, social trust, and risk/benefit perception. Risk Analysis, 20(3), 353–362. https://doi.org/10.1111/0272-4332.203034
[50] Sitkin, S. B., &Pablo, A. L. (1992). Reconceptualizing the Determinants of Risk Behavior Author ( s ): Sim B . Sitkin and Amy L . Pablo Source : The Academy of Management Review , Vol . 17 , No . 1 ( Jan ., 1992 ), pp . 9-38 Published by : Academy of Management Stable URL : http://www.jstor. Academy of Management, 17(1), 9–38.
[51] Sperber, D., &Wilson, D. (1986). Relevance: Communication and Cognition. In Cambridge, MA: Harvard University Press. (Vol. 142). https://doi.org/10.1111/j.1468-0017.1989.tb00246.x
[52] Spiekermann, S., Grossklags, J., &Berendt, B. (2001). E-privacy in 2nd generation E-commerce: Privacy preferences versus actual behavior. Proceedings of the ACM Conference on Electronic Commerce, 38–47.
[53] Stone, D. L. (1981). The effects of the valence of outcomes for providing data and the perceived relevance of the data requested on privacy-related behaviors, beliefs, and attitudes.
[54] Sutanto, J., Palme, E., Tan, C.-H., &Phang, C. W. (2013). Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users. MIS Quarter, 37(4), 1141–1164.
[55] 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. https://doi.org/10.1016/j.ijinfomgt.2016.03.003
[56] Xu, H., Luo, X., 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. https://doi.org/10.1016/j.dss.2010.11.017
[57] Xu, H., Teo, H. H., Tan, B. C. Y., &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. https://doi.org/10.2753/MIS0742-1222260305
[58] Zhang, B., &Xu, H. (2016). Privacy nudges for mobile applications: Effects on the creepiness emotion and privacy attitudes. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 27, 1676–1690. https://doi.org/10.1145/2818048.2820073
[59] Zhang, E. M. (2010). Beauty as a tool: The effect of model attractiveness, product relevance, and elaboration likelihood on advertising effectiveness. Psychology & Marketing, 30(6), 461–469. https://doi.org/10.1002/mar
[60] Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. In Industrial Management and Data Systems (Vol. 111, Issue 2, pp. 212–226). https://doi.org/10.1108/02635571111115146
[61] Zhu, Y. Q., &Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442–447. https://doi.org/10.1016/j.chb.2016.08.048
[62] Zimmer, J. C., Arsal, R. E., Al-Marzouq, M., &Grover, V. (2010). Investigating online information disclosure: Effects of information relevance, trust and risk. Information and Management, 47(2), 115–123. https://doi.org/10.1016/j.im.2009.12.003
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dc.identifier.doi (DOI) 10.6814/NCCU202001598en_US