簡易檢索 / 詳目顯示

研究生: 楊重名
Danh, Duong Trong
論文名稱: The Personalization –Privacy Paradox: An Exploratory Study on the Intention to Disclose via Mobile Phone Applications
The Personalization –Privacy Paradox: An Exploratory Study on the Intention to Disclose via Mobile Phone Applications
指導教授: 王鈿
Wang, Tien
學位類別: 碩士
Master
系所名稱: 管理學院 - 國際經營管理研究所
Institute of International Management
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 84
外文關鍵詞: Privacy calculus, Intention to disclose, Privacy concerns, Information privacy, Mobile applications
相關次數: 點閱:144下載:3
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
  • This study investigates the issue of consumer intention to disclose personal information via mobile applications. The study proposed a theoretical framework that were integrated protection motivation behavior on the basis of privacy calculus in order to explain an individual’s information disclosure behavior. Self-presentation, personalized services, perceived severity, importance of information transparency and perceived control were served as direct antecedents of perceived benefits and perceived risks. This study extends intention to disclose personal information literature by theoretically develop and empirically test the model within the current occurrence of disclosing personal information via mobile applications. Implications and future research are also discussed in this paper.

    TABLE OF CONTENTS ABSTRACT I ACKNOWLEDGEMENTS II TABLE OF CONTENTS III LIST OF TABLES VII LIST OF FIGURES VIII CHAPTER ONE INTRODUCTION 1 1.1 Research Background and Motivation. 1 1.1.1 Research Background. 1 1.1.2 Research Motivation. 2 1.2 Research Objectives and Contribution. 4 1.2.1 Research Objectives. 4 1.2.2 Research Contribution. 5 1.3 Research Procedure. 6 CHAPTER TWO LITERATURE REVIEW 8 2.1.2 Protection Motivation Theory. 8 2.1 Theoretical Background. 9 2.1.1 Privacy Calculus. 9 2.1.3 Development of an Integrated Theoretical Framework. 12 2.1.4 Previous Intention to Disclose Personal Information Literature. 13 2.2 Definitions of Relevant Research Variables. 21 2.2.1 Perceived Severity. 21 2.2.2 Importance of Information Transparency. 22 2.2.3 Perceived Control. 22 2.2.4 Self-Presentation. 23 2.2.5 Personalized Services. 23 2.2.6 Perceived Benefits. 23 2.2.7 Perceived Risks. 24 2.2.8 Intention to Disclose. 24 2.3 Development of Hypotheses. 25 2.3.1 The Relationship between Self-Presentation, and Personalized Services and Perceived Benefits. 25 2.3.2 The Relationship between Perceived Severity, and Importance of Information Transparency and Perceived Risks. 26 2.3.3 The Relationship between Perceived Control and Perceived Risks. 28 2.3.4 The Relationship between Perceived Benefits and Perceived Risks and Intention to Disclose via Mobile Applications. 29 CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY 31 3.1 Conceptual Model. 31 3.2 Construct Measurement and Definitions of Variables. 32 3.3 Summary of Hypotheses. 33 3.4 Sampling Plan & Data Collection. 33 3.5 Measurement Scale of Variables. 34 3.5.1 Measurement Scale of Variables. 34 3.5.2 Control Variables. 36 3.6 Data Analysis Procedure. 36 3.6.1 Descriptive Statistical Analysis. 36 3.6.2 Confirmatory Factor Analysis (CFA). 37 3.6.3 Common Method Variance. 37 3.6.4 Validity and Reliability Test. 38 3.6.5 Partial Least Squares Regression (PLS) Path Modeling. 38 CHAPTER FOUR DATA ANALYSIS AND RESULTS 40 4.1 Respondent’s Characteristics. 40 4.2 Descriptive Analysis for Confirmatory Model. 43 4.3 PLS Approach: Confirmatory Factor Analysis and Validity and Reliability Test of the Measurement Variables. 46 4.3.1. Confirmatory Factor Analysis. 46 4.3.2. Discriminant Validity Test. 49 4.4 Common Method Bias. 52 4.5 PLS Approach: Assessment of Structural Model. 54 4.5.1 Model Analysis and Global Fit Measure for PLS Path Modeling. 54 4.5.2 Global Fit Measure for PLS Path Modeling. 54 4.5.3 The Main Effects Model. 55 CHAPTER FIVE CONCLUSIONS AND SUGGESTIONS 61 5.1 Discussions and Conclusions. 61 5.1.1 Discussion. 61 5.1.2 Conclusion. 62 5.2 Theoretical and Managerial Implications. 64 5.2.1 Theoretical Implications. 64 5.2.2 Managerial Implications. 65 5.3 Limitations and Future Researches. 67 REFERENCES 69 APPENDICES 75 Appendix 1: English Survey Questionnaire. 75 Appendix 2: Vietnamese Survey Questionnaire. 80

    REFERENCES
    Adomavicius, G., & Tuzhilin, A. (2005). Personalization technologies: A process-oriented perspective. Communications of the ACM, 48(10), 83-90.
    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
    Anderson, R., Babin, B., Black, W., & Hair, J. (2010). Multivariate data analysis–A global perspective. Upper Saddle River: Pearson Prentice Hall.
    Andrade, E. B., Kaltcheva, V., & Weitz, B. (2002). Self-disclosure on the web: The impact of privacy policy, reward, and company reputation. Advances in Consumer Research, 29(1), 350-353.
    Awad, N. F., & Krishnan, M. (2006). The personalization privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quarterly, 30(1), 13-28.
    Bagozzi, R. P. (1975). Marketing as exchange. The Journal of Marketing, 39(4), 32-39.
    Bansal, G., Zahedi, F., & 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.
    Barwise, P., & Strong, C. (2002). Permission-based mobile advertising. Journal of Interactive Marketing, 16(1), 14-24.
    Becker, G. S., & Murphy, K. M. (1988). A theory of rational addiction. The Journal of Political Economy, 96(4), 675-700.
    Cavoukian, A., Polonetsky, J., & Wolf, C. (2010). Smartprivacy for the smart grid: Embedding privacy into the design of electricity conservation. Identity in the Information Society, 3(2), 275-294.
    Chang, C.-W., & Chen, G. M. (2014). College students’ disclosure of location-related information on Facebook. Computers in Human Behavior, 35(0), 33-38.
    Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information Technology and Management, 6(2-3), 181-202.
    Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
    Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189-217.
    Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lauwrence Erlbaum Associactes.
    Conroy, D. E., Motl, R. W., & Hall, E. G. (2000). Progress toward construct validation of the self-presentation in exercise questionnaire (SPEQ). Journal of Sport and Exercise Psychology, 22(1), 21-38.
    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.
    Derlega, V. J., & Chaikin, A. L. (1977). Privacy and self‐disclosure in social relationships. Journal of Social Issues, 33(3), 102-115.
    Dinev, T., & Hart, P. (2004). Internet privacy concerns and their antecedents -measurement validity and a regression model. Behaviour and Information Technology, 23(6), 413-422.
    Dinev, T., & Hart, P. (2005). Internet privacy concerns and social awareness as determinants of intention to transact. International Journal of Electronic Commerce, 10(2), 7-29.
    Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80.
    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.
    Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-474.
    Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
    Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 2-77.
    Goodwin, C. (1991). Privacy: Recognition of a consumer right. Journal of Public Policy & Marketing, 10(1), 149-166.
    Graeff, T. R., & Harmon, S. (2002). Collecting and using personal data: Consumers’ awareness and concerns. Journal of Consumer Marketing, 19(4), 302-318.
    Granados, N., Gupta, A., & Kauffman, R. J. (2010). Research commentary-information transparency in business-to-consumer markets: Concepts, framework, and research agenda. Information Systems Research, 21(2), 207-226.
    Hair, J., Anderson, R., Tatham, R., & Black, W. (2006). Multivariate data analysis (5 ed.). New Jersey: Prentice-Hall.
    Harman, H. H. (1976). Modern factor analysis. Princeton, New Jersey: University of Chicago Press.
    Hong, W., & L. Thong, J. Y. (2013). Internet privacy concerns: An intergrated conceptualization and four empirical studies. MIS Quarterly, 37(1), 275-298.
    Ifinedo, P. (2012). Understanding information systems security policy compliance: An integration of the theory of planned behavior and the protection motivation theory. Computers & Security, 31(1), 83-95.
    Junglas, I., & Watson, R. T. (2006). The u-constructs: Four information drives. Communications of the Association for Information Systems, 17(1), 569-592.
    Junglas, I. A., Johnson, N. A., & Spitzmüller, C. (2008). Personality traits and concern for privacy: An empirical study in the context of location-based services. European Journal of Information Systems, 17(4), 387-402.
    Keith, M. J., Thompson, S. C., Hale, J., Lowry, P. B., & Greer, C. (2013). Information disclosure on mobile devices: Re-examining privacy calculus with actual user behavior. International Journal of Human-Computer Studies, 71(12), 1163-1173.
    Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564.
    Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: Guilford Press.
    Knijnenburg, B. P., Kobsa, A., & Jin, H. (2013). Dimensionality of information disclosure behavior. International Journal of Human-Computer Studies, 71(12), 1144-1162.
    Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580.
    LaRose, R., Rifon, N., Liu, S., & Lee, D. (2005). Online safety strategies: A content analysis and theoretical assessment. Paper presented at the The 55th Annual Conference of the International Communication Association, New York City.
    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.
    Leary, M. R., & Kowalski, R. M. (1990). Impression management: A literature review and two-component model. Psychological Bulletin, 107(1), 34-47.
    Lee, C. H., & Cranage, D. A. (2011). Personalisation–privacy paradox: The effects of personalisation and privacy assurance on customer responses to travel web sites. Tourism Management, 32(5), 987-994.
    Lee, D. H., Im, S., & Taylor, C. R. (2008). Voluntary self‐disclosure of information on the Internet: A multimethod study of the motivations and consequences of disclosing information on blogs. Psychology & Marketing, 25(7), 692-710.
    Lee, E., Ahn, J., & Kim, Y. J. (2014). Personality traits and self-presentation at Facebook. Personality and Individual Differences, 69(0), 162-167.
    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.
    Lee-Won, R. J., Shim, M., Joo, Y. K., & Park, S. G. (2014). Who puts the best “face” forward on Facebook? Positive self-presentation in online social networking and the role of self-consciousness, actual-to-total friends ratio, and culture. Computers in Human Behavior, 39(0), 413-423.
    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., 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.
    Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471-481.
    Li, Y. (2014). A multi-level model of individual information privacy beliefs. Electronic Commerce Research and Applications, 13(1), 32-44.
    Lin, S.-W., & Liu, Y.-C. (2012). The effects of motivations, trust, and privacy concern in social networking. Service Business, 6(4), 411-424.
    Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123-146.
    Maddux, J. E., & Rogers, R. W. (1983). Protection motivation and self-efficacy: A revised theory of fear appeals and attitude change. Journal of Experimental Social Psychology, 19(5), 469-479.
    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.
    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.
    Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping. Journal of Consumer Affairs, 35(1), 27-44.
    Mohamed, N., & Ahmad, I. H. (2012). Information privacy concerns, antecedents and privacy measure use in social networking sites: Evidence from Malaysia. Computers in Human Behavior, 28(6), 2366-2375.
    Nicolaou, A. I., & McKnight, D. H. (2006). Perceived information quality in data exchanges: Effects on risk, trust, and intention to use. Information Systems Research, 17(4), 332-351.
    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.
    Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105-136.
    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.
    Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.
    Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531-544.
    Raschke, R. L., Krishen, A. S., & Kachroo, P. (2014). Understanding the components of information privacy threats for location based services. Journal of Information Systems, 28(1), 227-242.
    Rensel, A. D., Abbas, J. M., & Rao, H. R. (2006). Private transactions in public places: An exploration of the impact of the computer environment on public transactional web site use. Journal of the Association for Information Systems, 7(1), 19-51.
    Rifon, N. J., LaRose, R., & Choi, S. (2005). Your privacy is sealed: Effects of web privacy seals on trust and personal disclosures. Journal of Consumer Affairs, 39(2), 339-362.
    Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93-114.
    Rui, J., & Stefanone, M. A. (2013). Strategic self-presentation online: A cross-cultural study. Computers in Human Behavior, 29(1), 110-118.
    Sangmi, C., Bagchi-Sen, S., Morrell, C., Rao, H. R., & Upadhyaya, S. J. (2009). Internet and online information privacy: An exploratory study of preteens and early teens. IEEE Transactions on Professional Communication, 52(2), 167-182.
    Stewart, K. A., & Segars, A. H. (2002). An empirical examination of the concern for information privacy instrument. Information Systems Research, 13(1), 36-49.
    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.
    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 Quarterly, 37(4), 1141-1164.
    Taylor, D., Davis, D., & Jillapalli, R. (2009). Privacy concern and online personalization: The moderating effects of information control and compensation. Electronic Commerce Research, 9(3), 203-223.
    Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159-205.
    Vance, A., Siponen, M., & Pahnila, S. (2012). Motivating IS security compliance: Insights from habit and protection motivation theory. Information & Management, 49(3–4), 190-198.
    Wakefield, R. (2013). The influence of user affect in online information disclosure. The Journal of Strategic Information Systems, 22(2), 157-174.
    Westin, A. F. (1967). Privacy and freedom. New York: Atheneum.
    Wetzels, M., Odekerken-Schroder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. Management Information Systems Quarterly, 33(1), 11.
    Xiao, B., & Benbasat, I. (2011). Product-related deception in e-commerce: A theoretical perspective. MIS Quarterly, 35(1), 169-196.
    Xu, D. J., Liao, S. S., & Li, Q. (2008). Combining empirical experimentation and modeling techniques: A design research approach for personalized mobile advertising applications. Decision Support Systems, 44(3), 710-724.
    Xu, H., & Luo, X. (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., 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. (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.
    Yao, M. Z., Rice, R. E., & Wallis, K. (2007). Predicting user concerns about online privacy. Journal of the American Society for Information Science and Technology, 58(5), 710-722.
    Youn, S. (2005). Teenagers' perceptions of online privacy and coping behaviors: A risk–benefit appraisal approach. Journal of Broadcasting & Electronic Media, 49(1), 86-110.
    Youn, S. (2009). Determinants of online privacy concern and its influence on privacy protection behaviors among young adolescents. Journal of Consumer Affairs, 43(3), 389-418.
    Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. The Journal of Marketing, 52(3), 2-22.
    Zhang, L., & McDowell, W. C. (2009). Am I really at risk? Determinants of online users' intentions to use strong passwords. Journal of Internet Commerce, 8(3-4), 180-197.
    Zhao, L., Lu, Y., & Gupta, S. (2012). Disclosure intention of location-related information in location-based social network services. International Journal of Electronic Commerce, 16(4), 53-90.
    Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. Industrial Management & Data Systems, 111(2), 212-226.
    Zhu, K. (2004). Information transparency of business-to-business electronic markets: A game-theoretic analysis. Management Science, 50(5), 670-685.
    Zimmer, J. C., Arsal, R., Al-Marzouq, M., Moore, D., & Grover, V. (2010). Knowing your customers: Using a reciprocal relationship to enhance voluntary information disclosure. Decision Support Systems, 48(2), 395-406.

    無法下載圖示 校內:2020-02-12公開
    校外:不公開
    電子論文尚未授權公開,紙本請查館藏目錄
    QR CODE