Informatization Policy (정보화정책)

National Information Society Agency (한국지능정보사회진흥원)
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The Mediating Effect and Moderating Effect of Pseudonymized Information Combination in the Relationship Between Regulation Factors of Personal Information and Big Data Utilization

개인정보 규제요인과 빅데이터 활용간의 관계에서 가명정보 결합의 매개효과 및 조절효과

  • Received : 2020.06.30
  • Accepted : 2020.08.03
  • Published : 2020.09.30
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Abstract

Recently, increasing use of big data have caused regulation factors of personal information and combination of pseudonymized information to emerge as key policy measures. Therefore, this study empirically analyzed the mediating effect and moderating effect of pseudonymized information combination as the third variable in the relationship between regulation factors of personal information and big data utilization. The analysis showed the following results: First, among personal information regulation factors, definition regulation, consent regulation, supervisory authority regulation, and punishment intensity regulation showed a positive(+) relationship with the big data utilization, while among pseudonymized information combination factors, non-identification of combination, standardization of combined pseudonymized information, and responsibility of combination were also found to be in a positive relationship with the use of big data. Second, among the factors of pseudonymized information combination, non-identification of combination, standardization of combined pseudonymized information, and responsibility of combination showed a positive(+) mediating effect in relation to regulation factors of personal information and big data utilization. Third, in the relationship between personal information regulation factors and big data utilization, the moderating effect hypothesis that each combination institution type of pseudonymized information (free-type, intermediary-type, and designated-type) would play a different role as a moderator was rejected. Based on the results of the empirical research, policy alternatives of 'Good Regulation' were proposed, which would maintain balance between protection of personal information and big data utilization.

최근 빅데이터 활용의 영향요인으로 개인정보 규제요인과 가명정보 결합이 핵심 정책수단으로 등장하고 있다. 본 연구는 개인정보 규제요인과 빅데이터 활용의 관계에서 제3의 변수로서 가명정보 결합의 매개효과 및 조절효과를 실증분석하였다. 분석결과, 첫째, 개인정보 규제요인 중 개인정보 정의, 개인정보 동의, 법령위반 처벌강도 요인이, 그리고 가명정보 결합요인 중 결합 비식별성, 결합 가명정보 표준화, 결합 책임성이 빅데이터의 활용에 정(+)의 유의한 관계를 보였다. 둘째, 가명정보 결합 요인 중 결합 비식별성, 결합 가명정보 표준화, 결합 책임성이 개인정보 규제요인과 빅데이터 활용과의 관계에서 정(+)의 매개효과를 보였다. 셋째, 개인정보 규제요인과 빅데이터 활용과의 관계에서 가명정보 결합기관 유형인 자유형, 중개형, 지정형의 순서에 따라 조절효과가 다를 것이라는 가설은 기각되었다. 이상의 분석결과를 기반으로 개인정보 보호와 빅데이터 활용이 조화를 이루는 '착한규제'의 정책대안을 제시하였다.

Keywords

References

  1. 4Th Industrial Revolution Committee (2019). Recommendation for Government on 4Th Industrial Revolution.
  2. Bae, B. (2018). Mediating Effect and Moderating Effect Analysis.
  3. Barron, R., & Kenny, D. (1986). "The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical consideration." Journal of Personality and Social Psychology, 51(6): 1173-1182. https://doi.org/10.1037/0022-3514.51.6.1173
  4. Cha, Y. (2019). "Data Economy and the Trends of De-identification Technology in Personal Information Protection." Weekly Technology Trends . IITP(Institute of Information & Communications Technology Planning & Evaluation).
  5. Chae, S. (1997). Maketing Research. Seoul: Hakhyeonsa.
  6. Chan, F., Chong, A. & Zhou, L. (2013). "An empirical investigation of factors affecting e-collaboration diffusion in SMEs." International Journal of Production Economics, 138(2): 329-344. https://doi.org/10.1016/j.ijpe.2012.04.004
  7. Cho, S. (2017). Improvement Stragy of Information Usability under Personal Information Protection Legal System." Premium Report of Korea Information Society Development Institute.
  8. Choi, H. & Choi, Y. & Lee, S. (2018). A Study on Improvement of Personal Information Protection System. Booklet of Sustainable Growth Initiative.
  9. Choi, K. (2017). "Artificial Intelligence, Data, and Law" (ed.) Data Economy. Seoul: Hans media.
  10. Gartner (2011). How to Plan, Participate and Prosper in the Data Economy.
  11. Heo, S. (2014). "Big Data Legal Issues in Korea." Journal of Law & Public Utilities, 7(2), 7-21.
  12. IDC. (2017). Worldwide Semiannual Big Data and Analytics Spending Guide.
  13. IDC. (2019a). Worldwide Big Data and Analytics Software Forecast, 2019-2013.
  14. IDC. (2019b). Korea Big data and Analytics Forecast: 2018-2022.
  15. IMD. (2018). IMD World Digital Competitiveness Ranking 2018.
  16. Kang, B. (1997). Multivariate Statistical Analysis using Matrices and SPSS/PC. Seoul: Hakhyeonsa.
  17. Kang, J. (2017). "An Analysis on the Factors Affecting of Bigdata Utilization in Local Government: Focused on the Public Servants Perception in Seoul." Journal of Governance Studies, 12(1), 161-197.
  18. Kim, I. (2017). "A Study on the Role and Function of Personal Information Protection Commission." Study on the American Constitution, 28(2), 219-273.
  19. Kim, J. (2017). "Review the Regulation and the Improvement in the Big Data: Focusing on the Policy Directionsn and Legislation of the New Government." IT & Law Review, 15, 157-191. https://doi.org/10.37877/itnlaw.2017.08.15.5
  20. Kim, J. & Song, T. (2014). "A Study on Initial Characterization of Big Data Technology Acceptance: Moderating Role of Technology User & Technology Utilizer." Journal of the Korea Contents Association, 14(9), 538-555. https://doi.org/10.5392/JKCA.2014.14.09.538
  21. Kim, S. (2014). "A Study of the Personalization Service and Privacy Paradox in the Big Data Era-Focus on the Sociotechnical Perspective." Journal of the Korean Cadestre Information Association, 16(2), 193-207.
  22. Kim, S. & Kim, S. (2020a). "The effect of Personal Information Regulation Level and Data Combination on Big Data Utilization." Journal of Korea Technology Innovation Society, 23(2): 306-324.
  23. Kim, S. & Kim, S. (2020b). "An Exploration on Personal Information Regulation Factors and Data Combination Factors affecting Big Data Utilization." Journal of the Korea Institute of Information Security & Cryptology, 30(2): 287-304. https://doi.org/10.13089/JKIISC.2020.30.2.287
  24. Kim, T. & Lee, S. (2012). "Regulatory Stringency: with the Application of Report Regulations in Korea." Journal of Regulation Studies, 21(2), 147-185.
  25. Kim, Y. (2019). "A Study on the Improvement of Punishment System for Personal Information Violation." Doctoral dissertation, Soongsil University.
  26. Ko, H. (2019). "A Study on Factors Affecting the Intentio nto Use Big Data in Businesses." Doctoral dissertation. Soongsil University.
  27. Ko, H. (2019). The Effect on Korea's Personal Information Protection Law in GDPR era.
  28. Ko, H., Lee, D., Lee, S., Kim, E. & Jeong, J. (2017). De-identifying Personal Information. Seoul: PakYoungSa.
  29. Koo, T. (2017). Regulatory rationalization plan for innovative industry development. Korean Federation of Science and Technology Societies.
  30. Korean Chamber of Commerce (2018). Institutional Improvement Survey on Personal Information Protection.
  31. Kwon, Y. (2015). "Thought on the Self-Determination Right to Peronal Information and the Consent Regime." 2015 Naver Privacy White Paper.
  32. Lee, E,, Oh, B., Im, J., Jang, Y. & Hwang, K. (2017). A Study on Introduction of Data Linkage & Combination Support System. Personal Information Protection Commission.
  33. Lee, H. (2019). "A study on Legislation of Social Regulation: the Perspective of Regulatory Paradox." Journal of Parliamentary Research, 13(1): 5-69.
  34. Lee, J. & Jang, M. (2018). "A Study on the Intention to Use Big data Based on the Technology Organization Environment and Innovation Diffusion Theory in Shipping and Port Organization." Journal of Korea Port Economic Association, 34(3), 159-181. https://doi.org/10.38121/kpea.2018.09.34.3.159
  35. Lee, S. (2016). "Research on Determinants for Big data System Adoption in Organization." Doctoral dissertation, Sungkyunkwan University.
  36. Lee, S. (2017). Suggestion of Improvement Plan for advancement of Personal Informantion Protection Act. Conference Booklet of 50th Anniversary of E-Government.
  37. Lee, S. (2019). "Personal Information Utilization and Role of Government." (ed.) Regulatory Reform Task and Case Study for promoting New Industries. Jinhan M&B.
  38. Lian, J., Yen, D. & Wang, Y. (2014). "An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital." International Journal of Information Management, 34, 28-36. https://doi.org/10.1016/j.ijinfomgt.2013.09.004
  39. Ministry of Interior and Safety (2020). Ex-notice on Combination and Export of Psudonymized Informatioin.
  40. Oliveira, T., Thomas, M. & Espadanal, M. (2014). "Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors." Information and Management, 51, 497-510. https://doi.org/10.1016/j.im.2014.03.006
  41. Park, K. (2018). "Big data Possibility in Personal Information Protection Legal system." (ed.) Personal Informaion in the 4th Industrial Revolution Era. Seoul: Sechang publisher.
  42. Park, N. (2016). "Improvement Review of Korea's Personal Information Protetion Legal system according to the Analysis of Personal Information Protection Act in major countries on Big Data." <2016 Naver Privacy White Paper.>
  43. People Power 21 (2018). 2007-2017 Worst 44 in Personal Information suffering history. Research paper.
  44. Personal Information Protection Commission. & Ministry of the Interior and Safety. (2018). 2018 Survey of Personal Information Protection in Korea.
  45. Shin, Y. (2018). A Study on Precautionary Regulatory Status Analysis and Improvment Plan for Personal Information Protection in Korea. Autume Conference Booklet in the Korean Association for Policy Studies, 17-41.
  46. Tornatzky, L. G., Fleischer, M., Chakrabarti, A. K. (1990). Processes of Technological Innovation. Lexington Books.
  47. Venkatesh, V., Moris, M. G., Davis, G. B., Davis, F. D. (2003). "User acceptance of information technology: Toward a unified view." Information Management, 27(3): 425-478.
  48. Weigend, A. (2018). Data for the people: how to make our post-privacy economy work for You, Trans. Hong, J. Paju: Four Season.
  49. Woo, S. (2018). "A Study on the Factors Affecting Personal Information De-identification Based on Big Data in the Financial Industry." Doctoral dissertation, Soongsil University.
  50. Yang, H. (2015). "the Effects of Applying Personal Information De-identification Technology on Intention to use Big data: Big data providers and consumers perspectives." Doctoral dissertation, Kwangwoon University.
  51. Yoon, H. (2014). "The effect on Big Data Utilization and Effectiveness of Organizational, Technological, Environmental Factors." Research on Business Management>, 7(2): 153-178.
  52. Yoon, H. (2018). "A Search for a new Regulatory Paradigm for Big data." Journal of Law and Economic Regulation, 11(1), 71-94.
  53. Yoon, K. (2018). A Study on Administrative Service Innovation using Information Technology in 4th Industrial Revolution Era. Research Paper of 'Korea Institute of Public Administration', 2018-16.
  54. Yoon, S, & Oh, J. (2018). "A Study on the Factors that Affect the Intention to Use Big Data by IT, Human and Organizational Resources." Journal of the Korean Operations Research and Management Science Society, 43(4), 67-94. https://doi.org/10.7737/JKORMS.2018.43.4.067