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TSSEM을 이용한 정보 프라이버시 메타분석

Meta-Analysis of Information Privacy Using TSSEM

  • Kim, Jongki (Dept. of Business Administration, Pusan National University)
  • 투고 : 2019.10.02
  • 심사 : 2019.11.20
  • 발행 : 2019.11.28

초록

정보기술의 활용이 보편화되면서 대중과 연구자 모두 정보 프라이버시 문제에 대한 관심이 높아지고 있다. 이러한 문제에 대한 연구가 기하급수적으로 증가하면서 연구결과에 대한 전반적인 이해가 어려워졌다. 이에 따라 과거연구에 대한 체계적인 검토가 요구된다. 본 연구는 정보 프라이버시 연구에 핵심적인 네 가지 연구개념을 두 가지 연구모형으로 설정하고 기존 연구에서 수집된 데이터를 이용하여 실증 분석하였다. TSSEM이라는 정량적 메타분석 기법이 적용되었는데, 이 기법은 MASEM의 한 가지로서 구조방정식모형과 메타분석 기법을 통합하여 분석하는 기능을 제공한다. 분석결과는 위험 중심적 모형이 염려 중심적 모형과 비교하여 보다 높은 모형 적합도를 나타내었다. 본 연구의 결과는 전통적인 염려 중심적 모형의 설명력에 의문을 제시하며, 사용자의 프라이버시 정보 제공의도를 설명하기 위하여 위험 중심적 모형을 고려할 필요가 있다는 점을 시사한다.

With widespread use of information technologies, information privacy issues have been gaining more attention by not only the public but also researchers. The number of studies on the issues has been increasing exponentially, which makes incomprehensible the whole picture of research outcome. Thus, it is necessary to conduct a systematic examination of past research. This study developed two competing models with four essential constructs in information privacy research and empirically tested the models with data obtained from previous studies. This study employed a quantitative meta-analysis method called TSSEM. It is one of MASEM methods in which structural equation modeling and meta-analysis are integrated. The analysis results indicated that risk-centric model exhibited much better model fits than those of concern-centric model. This study implies that traditional concern-centric model should be questioned it's explanatory power of the model and researchers may consider alternative risk-centric model to explain user's intention to provide privacy information.

키워드

참고문헌

  1. N. Gerber, P. Gerber & M. Volkamer. (2018). Explaining the Privacy Paradox: A Systematic Review of Literature Investigating Privacy Attitude and Behavior. Computers & Security, 77, 226-261. DOI: 10.1016/j.cose.2018.04.002
  2. H. Yun, G. Lee & D. J. Kim. (2019). A chronological review of empirical research on personal information privacy concerns: An analysis of contexts and research constructs. Information & Management, 56(4), 570-601. DOI: 10.1016/j.im.2018.10.001
  3. S. Whang. Meta-Analysis Using R, Hakjisa, 2015.
  4. C. Okoli. (2015). A Guide to Conducting a Standalone Systematic Literature Review. Communications of the Association for Information Systems, 37, 879-910. DOI: 10.17705/1cais.03743
  5. S. Jak. (2015). Meta-analytic structural equation modeling. New York: Springer. DOI: 10.1007/978-3-319-27174-3
  6. M. W. L. Cheung. (2015). Meta-analysis: A structural equation modeling approach. John Wiley & Sons.
  7. R. S. Landis. (2013). Successfully Combining Meta-analysis and Structural Equation Modeling: Recommendations and Strategies. Journal of Business and Psychology, 28(3), 251-261. DOI: 10.1007/s10869-013-9285-x
  8. M. W. L. Cheung & W. Chan. (2005). Meta-Analytic Structural Equation Modeling: A Two-Stage Approach. Psychological Methods, 10(1), 40-64. DOI: 10.1037/1082-989x.10.1.40
  9. H. J. Smith, T. Dinev & H. Xu. (2011). Information Privacy Research: An Interdisciplinary Review. MIS Quarterly, 35(4), 989-1016. DOI: 10.2307/41409970
  10. Y. Li. (2011). Empirical studies on online information privacy concerns: Literature review and an integrative framework. CAIS, 28, 28. DOI: 10.17705/1cais.02828
  11. Y. Li. (2012). Theories in Online Information Privacy Research: A Critical Review and an Integrated Framework. Decision Support Systems, 54(1), 471-481. DOI: 10.1016/j.dss.2012.06.010
  12. T. Dinev, A. R. McConnell & H. J. Smith. (2015). Research commentary-informing privacy research through information systems, psychology, and behavioral economics: thinking outside the "APCO" box. Information Systems Research, 26(4), 639-655. DOI: 10.1287/isre.2015.0600
  13. S. Kokolakis. (2015). Privacy Attitudes and Privacy Behaviour: A Review of Current Research on the Privacy Paradox Phenomenon. Computers & Security, 64, 122-134. DOI: 10.1016/j.cose.2015.07.002
  14. S. Barth & M. D. De Jong. (2017). The privacy paradox-Investigating discrepancies between expressed privacy concerns and actual online behavior-A systematic literature review. Telematics and Informatics, 34(7), 1038-1058. DOI: 10.1016/j.tele.2017.04.013
  15. H. Jia, P. J. Wisniewski, H. Xu, M. B. Rosson & J. M. Carroll. (2015, February). Risk-taking as a learning process for shaping teen's online information privacy behaviors. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 583-599). ACM. DOI: 10.1145/2675133.2675293
  16. T. Zhou. (2015). Understanding user adoption of location-based services from a dual perspective of enablers and inhibitors. Information Systems Frontiers, 17(2), 413-422. DOI: 10.1007/s10796-013-9413-1
  17. N. K. Malhotra, S. S. Kim & J. Agarwal. (2004). Internet Users' Information Privacy Concerns (IUIPC):The Construct, the Scale, and a Causal Model. Information Systems Research, 15(4), 336-355. DOI: 10.1287/isre.1040.0032
  18. T. Dinev & P. Hart. (2004). Internet Privacy Concerns and Their Antecedents-Measurement Validity and a Regression Model. Behaviour & Information Technology, 23(6), 413-422. DOI: 10.1080/01449290410001715723
  19. M. J. Culnan & P. K. Armstrong. (1999). Information Privacy Concerns, Procedural Fairness, and Impersonal Trust:An Empirical Investigation. Organization Science, 10(1), 104-115. DOI: 10.1287/orsc.10.1.104
  20. M. Koohikamali, N. Gerhart & M. Mousavizadeh. (2015). Location disclosure on LB-SNAs: the role of incentives on sharing behavior. Decision Support Systems, 71, 78-87. DOI: 10.1016/j.dss.2015.01.008.
  21. M. K. Malhotra & V. Grover. (1998). An assessment of survey research in POM: from constructs to theory. Journal of Operations Management, 16(4), 407-425. DOI: 10.1016/s0272-6963(98)00021-7
  22. M. J. Keith, S. C. Thompson, J. Hale, P. B. Lowry & C. Greer. (2013). Information disclosure on mobile devices: Re-examining privacy calculus with actual user behavior. International journal of human-computer studies, 71(12), 1163-1173. DOI: 10.1016/j.ijhcs.2013.08.016
  23. Y. Li. (2014). A multi-level model of individual information privacy beliefs. Electronic Commerce Research and Applications, 13(1), 32-44. DOI: 10.1016/j.elerap.2013.08.002
  24. C. L. Miltgen & H. J. Smith. (2015). Exploring information privacy regulation, risks, trust, and behavior. Information & Management, 52(6), 741-759. DOI: 10.1016/j.im.2015.06.006
  25. K. S. Schwaig, A. H. Segars, V. Grover & K. D. Fiedler. (2013). A model of consumers’ perceptions of the invasion of information privacy. Information & Management, 50(1), 1-12. DOI: 10.1016/j.im.2012.11.002
  26. H. Xu, H. H. Teo, B. C. Tan & R. Agarwal. (2012). Research note-effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services. Information Systems Research, 23(4), 1342-1363. DOI: 10.1287/isre.1120.0416
  27. M. W. L. Cheung. (2015). metaSEM: An R package for meta-analysis using structural equation modeling. Frontiers in Psychology, 5, 1521. DOI : 10.3389/fpsyg.2014.01521
  28. E. E. Rigdon (2016). Choosing PLS path modeling as analytical method in European management research: A realist perspective. European Management Journal, 34(6), 598-605. DOI: 10.1016/j.emj.2016.05.006
  29. K. H. Kim (2016). A Convergence Study about Meta-Analysis on the Effects of ACT Intervention Program. Journal of the Korea Convergence Society, 7(5), 145-153. DOI: 10.15207/JKCS.2016.7.5.145
  30. S. H. Hwang, H. C. Jeong & J. W. Hwang. (2019). Effect of Laughter Therapy on Healthy Life: A Meta-analysis. Journal of the Korea Convergence Society, 10(9), 291-299. DOI: 10.15207/JKCS.2019.10.9.291
  31. B. Cho & J. Lee. (2018). A Meta Analysis on Effects of Flipped Learning in Korea. Journal of Digital Convergence, 16(3), 59-73. DOI: 10.14400/JDC.2018.16.3.059