PDF가 표시되지 않으면 여기를 클릭하여 다운로드

1
권순동, 최월, 방화룡, 고미현 (2010), “인터넷 쇼핑몰 성과의 영향 요인에 관한 한중 비교 연구,” 경영학연구, 제39권 3호, pp.851-877. (Kwon, S. D., Cui, Y., Fang, H. L., and Ko, M. H. (2020), “Comparative Study on the Influential Factors of Internet shopping mall Performance between Korea and China,” 39(3), pp.851-877.) Google Scholar ›
2
김상현, 김근아 (2012). “조직의 클라우드컴퓨팅 확산과정에 영향을 미치는 요인과 조직지원의 조절효과,” Entrue Journal of Information Technology, 제11권 2호, pp.197-213. (Kim, S. H. and Kim, G. A. (2012). “An Empirical Study of Factors Influencing Diffusion Process of Cloud Computing and the Moderating Effect of Organizational Supports,” Entrue Journal of Information Technology, 11(2), pp.197-213.) Google Scholar ›
3
김승한, 이원영, 함주호, 신현길 (2001). “전사적자원관리(ERP)의 확산에 관한 실증연구: 정보기술/정보시스템 혁신의 관점,” 경영학연구, 제30권 2호, pp.475-501. (Kim, S. H., Lee, W. Y., Ham, J. H., and Shin, H. G. (2001). “An Empirical Study on the Diffusion of ERP: An IT/IS Innovation Perspective,” Korean Management Review, 30(2), pp.475-501.) Google Scholar ›
4
김종호 (2022). “스마트 업무환경 변화에 대한 탐색적 분석: 공공부문과 민간부문 비교,” 정책개발연구, 제22권 제1호, pp.139-161. (Kim, J. H. (2022). “An Exploratory Analysis of Changes in the Smart Work Environment: A Comparison between the Public and Private Sectors,” Journal of Policy Development Research, 22(1), pp.161-161.) Google Scholar ›
5
김현정, 이영희, 김문선 (2013). “전사적자원관리(ERP) 시스템의 조직 내 확산에 대한 저항요인 분석,” 한국전자거래학회지, 제18권 1호, pp.129-146. (Kim, H. J., Lee, Y. H., and Kim, M. S. (2013). “An Analytical Study on the Influence of Resistance Factors in Adoption and Diffusion of Innovation as for Introducing ERP Systems into Universities,” The Journal of Society for e-Business Studies, 18(1), pp.129-146.) Google Scholar ›
6
김형주, 이주연 (2021). “공공부문과 민간부문 디지털 전환 추진요인 및 제약요인 비교연구,” 정보화정책연구, 제28권 제4호, pp.88-110. (Kim, H. J., and Lee, J. Y. (2021). “A Comparative Study on Drivers and Constraints of Digital Transformation in the Public and Private Sectors,” Journal of Informatization Policy, 28(4), pp.88-110.) Google Scholar ›
7
백상현 (2024). “디지털 리터러시 예측 요인 분석: MZ 세대와 기성세대 비교,” 아시아태평양융합연구교류논문지, 제10권 11호(통권 79호), pp.149-159. (Baek, S. H. (2024). “Analysis of Predictive Factors Affecting on Digital Literacy: Comparison of MZ Generation with Older Generation,” Asia-Pacific Journal of Convergent Research Interchange, 10(11), pp.149-159.) Google Scholar ›
8
신수행 (2022). “IT 서비스품질이 사용자만족과 고객충성도에 미치는 영향: MZ 세대와 기성세대간 인식차이를 중심으로,” 산업융합연구, 제20권 1호, pp.13-21. (Shin, S. H. (2022). “A Study on the Effect of IT Service Quality on User Satisfaction and Customer Loyalty: Focusing on the Perception Difference between the MZ Generation and the Existing Generation,” Industrial Convergence Research, 20(1), pp.13-21.) Google Scholar ›
9
송윤애, 남승하 (2021). “업무환경, 인사제도, 조직관리 특성이 조직협력과 성과에 미치는 영향: 조직협력의 매개효과를 중심으로,” GRI, 제23권 4호(통권 80호), pp.257-290. (Song, Y. and Nam, S. (2021). “A Study of Organizational Management Factors and Performance: The Mediating Role of Organizational Collaboration,” GRI REVIEW, 23(4), pp.257-290.) Google Scholar ›
10
신지형 (2019). “밀레니얼세대와 Z 세대의 미디어 이용,” KISDI STAT Report, 제19권 4호, pp.1-7. (Shin, J. H. (2019). “Media Use of Millennials and Generation Z,” KISDI STAT Report, 19(4), pp.1-7.) Google Scholar ›
11
우수한, 권순동, 장정주(2022). “스마트팩토리 개인 맞춤형 제품의 가격, 품질, 서비스의 소비자 인식 및 선호도에 관한 탐색적 연구,” 경영학연구, 제51권 6호, pp.1619-1647. (Woo, S.H., Kwon, S.D., and Jahng, J.J. (2022), "An Exploratory Study on Consumer Perceptions of Price, Quality, and Consumer Service for Personalized Products," Korean Management Review, 51(6), pp.1619-1647.) Google Scholar ›
12
임홍택 (2018). 90년생이 온다. 서울: 웨일북. (Lim, H. T. (2018). The Millennials Have Arrived. Seoul: Whalebooks.) Google Scholar ›
13
전영준, 남태우, 어광수 (2023). “디지털전환에 의한 테크노스트레스 결정요인 분석: MZ 세대와 기성세대 간비교,” 정책개발연구, 제23권 2호, pp.423-455. (Jeon, Y. J., Nam, T. W., and Eo, K. S. (2023). “Determinants of Technostress by Digital Transformation,” The Journal of Policy Development, 23(2), pp.423-455.) Google Scholar ›
14
정유진, 양희정 (2019). “공공기관 정보기술혁신 비교: 민간기업과의 차이 중심,” 한국행정학보, 제53권 제2호, pp.121-143. (Jeong, Y. J., and Yang, H. J. (2019). “Comparing Information Technology Innovation in Public Institutions: Focusing on Differences from Private Firms,” Korean Public Administration Review, 53(2), pp.121-143.) Google Scholar ›
15
정지나 (2018). “병원정보시스템 품질이 사용자 만족과 서비스혁신 성과에 미치는 영향,” 한국융합학회논문지, 제9권 10호, pp.441-448. (Jeong, J. (2018). “The Impacts of Hospital Information System Quality on Satisfaction of System Users and Service Innovation Performance,” Journal of the Korean Convergence Society, 9(10), pp.441-448.) Google Scholar ›
16
조성용, 이지석, 박진솔 (2024). “조직문화가 공무원의 이직의도에 미치는 영향: 밀레니얼세대와 Z 세대의 조절효과를 중심으로,” 한국행정연구, 제33권 1호, pp.69-107. (Cho, S. Y., Lee, J. S., and Park, J. S. (2024). “The Effects of Organizational Culture on the Turnover Intention of Public Officials: Focusing on the Moderating Role of Millennials and Generation Z,” Korean Public Administration Review, 33(1), pp.69-107.) Google Scholar ›
17
행정안전부 (2012). 행정기관 클라우드 사무환경 도입 가이드라인, 정보자원정책과. (Ministry of the Interior and Safety (2012). Guidelines for Introducing Cloud-based Office Environment in Administrative Agencies. Division of Information Resources Policy.) Google Scholar ›
18
행정안전부 (2020). 공공부문 정보시스템 클라우드 전환·도입 가이드라인. (Ministry of the Interior and Safety (2020). Guidelines for Cloud Transition and Adoption of Public Sector Information Systems.) Google Scholar ›
19
Aubhi, R. U. H., Rana, M. S., Mishad, N.-A., Sharmin, S., Rakib, A., and Kalam, F. A. (2025). Factors Influencing Smartphone Satisfaction among Generation Z: A Contemporary Analysis. Open Journal of Business and Management, 13(2), pp.1356-1376. Google Scholar ›
20
Bassellier, G., Benbasat, I., and Reich, B. H. (2003). The influence of business managers’ IT competence on championing IT. Information Systems Research, 14(4), 317-336. Google Scholar ›
21
Bharati, P., and Chaudhury, A. (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems, 37(2), pp.187-197. Google Scholar ›
22
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. Google Scholar ›
23
Bijker, R., Merkouris, S. S., Dowling, N. A., and Rodda, S. (2024). ChatGPT for automated qualitative research: Content analysis. Journal of Medical Internet Research, 26(2), e59050. Doi:10.2196/59050. Google Scholar ›
24
Burton-Jones, A., and Gallivan, M. J. (2007). Toward a deeper understanding of system usage in organizations: A multilevel perspective. MIS Quarterly, 31(4), pp.657-679. Google Scholar ›
25
Casaló, L. V., Flavián, C., and Guinalíu, M. (2008). The role of satisfaction and website usability in developing customer loyalty and positive word-of-mouth in the e-banking services. International Journal of Bank Marketing, 26(6), 399-417. Google Scholar ›
26
Charness, N., and Boot, W. R. (2009). Aging and information technology use: Potential and barriers. Current Directions in Psychological Science, 18(5), pp.253-258. Google Scholar ›
27
Chatterjee, D., Grewal, R., and Sambamurthy, V. (2002). Shaping up for e-commerce: Institutional enablers of the organizational assimilation of web technologies. MIS Quarterly, 26(2), pp.65-89. Google Scholar ›
28
Colbert, A., Yee, N., and George, G. (2016). The digital workforce and the workplace of the future. Academy of Management Journal, 59(3), pp.731-739. Google Scholar ›
29
Cordella, A., and Bonina, C. M. (2012). A public value perspective for ICT enabled public sector reforms: A theoretical reflection. Government Information Quarterly, 29(4), 512-520. Google Scholar ›
30
Cordella, A., and Iannacci, F. (2010). Information systems in the public sector: The e-Government enactment framework. The Journal of Strategic Information Systems, 19(1), pp.52-66. Google Scholar ›
31
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), pp.319-340. Google Scholar ›
32
de Vries, H., Tummers, L., and Bekkers, V. (2018). The diffusion and adoption of public sector innovations: A meta-synthesis of the literature. Perspectives on Public Management and Governance, 1(3), pp.159-176. Google Scholar ›
33
DeLone, W. H., and Mc Lean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95. Google Scholar ›
34
DeLone, W. H., and Mc Lean, E. R. (2003). The DeLone and Mc Lean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), pp.9-30. Google Scholar ›
35
Dezdar, S. (2017). Promoting enterprise system success: A meta-analytic approach based on the DeLone and Mc Lean model. Journal of Systems and Software, 126, 143-158. Google Scholar ›
36
Dimock, M. (2018). Defining generations: Where Millennials end and Generation Z begins. Pew Research Center. https://www.pewresearch.org, Retrieved May 2025. Google Scholar ›
37
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., and Williams,M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 Google Scholar ›
38
Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp.39-50. Google Scholar ›
39
Gallivan, M. J. (2001). Organizational adoption and assimilation of complex technological innovations: Development and application of a new framework. DATA BASE for Advances in Information Systems, 32(3), 51-85. Google Scholar ›
40
Goodhue, D. L., and Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), pp.213-236. Google Scholar ›
41
Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE. Google Scholar ›
42
Haug, N., Dan, S., and Mergel, I. (2023). Digitally-induced change in the public sector: A systematic review and research agenda. Public Management Review, 26(7), pp. 1963-1987. https://doi.org/10.1080/14719037.2023.2234917 Google Scholar ›
43
Henseler, J., Ringle, C. M., and 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), pp.115-135. Google Scholar ›
44
Henseler, J., Ringle, C. M., and Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), pp.405-431. Google Scholar ›
45
Hinds, P., and Kiesler, S. (2002). Distributed work. MIT Press. Google Scholar ›
46
Hou, C. K. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronics industry. International Journal of Information Management, 32(6). Google Scholar ›
47
Lam, T., Cho, V., and Qu, H. (2007). A study of hotel employee behavioral intentions towards adoption of information technology. International Journal of Hospitality Management, 26(1), pp.49-65. Google Scholar ›
48
Lee, C., and Coughlin, J. F. (2015). Older adults’ adoption of technology: An integrated approach to identifying determinants and barriers. Journal of Product Innovation Management, 32(5), pp.747-759. Google Scholar ›
49
Lee, G., and Xia, W. (2010). Toward agile: An integrated analysis of quantitative and qualitative field data on software development agility. MIS Quarterly, 34(1), pp.87-114. Google Scholar ›
50
Lee, S., Lim, S., and Lee, Y. (2022). Cloud computing adoption in the Korean public sector: Policy, process, and challenges. Government Information Quarterly, 39(2), 101675. https://doi.org/10.1016/j.giq.2021.101675 Google Scholar ›
51
Liang, H., Saraf, N., Hu, Q., and Xue, Y. (2007). Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), pp.59-87. Google Scholar ›
52
Mannheim, K. (1928). The problem of generations. Essays on the Sociology of Knowledge. Google Scholar ›
53
Marchiori, D. M., Mainardes, E. W., and Rodrigues, R. G. (2019). Do individual characteristics influence the types of technostress reported by workers? International Journal of Human-Computer Interaction, 35(3), pp.218-230. Google Scholar ›
54
Mergel, I., Edelmann, N., and Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.06.002 Google Scholar ›
55
Moore, G. C., and Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), pp.192-222. Google Scholar ›
56
Myers, K. K., and Sadaghiani, K. (2010). Millennials in the workplace: A communication perspective on millennials’ organizational relationships and performance. Journal of Business and Psychology, 25(2), pp.225-238. Google Scholar ›
57
Nunnally, B., and Farkas, D. (2020). UX research: Practical techniques for designing better products. O'Reilly. Google Scholar ›
58
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), pp.1-6. Google Scholar ›
59
Pu, J. (2022). Internal online communities and employee performance in geographically dispersed organizations. Journal of Organizational Computing and Electronic Commerce, 32(1), pp.45-67. Google Scholar ›
60
Rai, A., Lang, S. S., and Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), pp.50-69. Google Scholar ›
61
Reich, B. H., and Benbasat, I. (2000). Factors that influence the social dimension of alignment between business and information technology objectives. MIS Quarterly, 24(1), pp.81-113. Google Scholar ›
62
Robey, D., Ross, J. W., and Boudreau, M. C. (2002). Learning to implement enterprise systems: An exploratory study of the dialectics of change. Journal of Management Information Systems, 19(1), 17-46. Google Scholar ›
63
Rocheleau, B., and Wu, L. (2002). Public versus private information systems: Do they differ in important ways? A review and empirical test. American Review of Public Administration, 32, pp.379-397. https://doi.org/10.1177/027507402237866 Google Scholar ›
64
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. Google Scholar ›
65
Sarstedt, M., Ringle, C. M., and Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. In Homburg, C., Klarmann, M., and Vomberg, A. (Eds.), Handbook of Market Research. Springer. Google Scholar ›
66
Schepers, J., and Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), pp.90-103. Google Scholar ›
67
Senyo, P. K., Addo, A., and Effah, J. (2024). Government-led digital transformation in Fin Tech ecosystems. The Journal of Strategic Information Systems, 33(3), 101849, https://doi.org/10.1016/j.jsis.2024.101849 Google Scholar ›
68
Sharma, R., and Yetton, P. (2003). The contingent effects of management support and task interdependence on successful information systems implementation. MIS Quarterly, 27(4), pp.533-556. Google Scholar ›
69
Strong, D. M., and Volkoff, O. (2010). Understanding organization-enterprise system fit: A path to theorizing the information technology artifact. MIS Quarterly, 34(4), pp.731-756. Google Scholar ›
70
Sykes, T. A., Venkatesh, V., and Gosain, S. (2009). Model of acceptance with peer support: A social network perspective to understand employees' system use. MIS Quarterly, 33(2), pp.371-393. Google Scholar ›
71
Tai, S. R., Lozano, J., Giacone, D., Schuerch, J., and Walker, L. A. (2024). A framework for deductive qualitative coding with ChatGPT: Insights from implementing a pilot research study. International Journal of Qualitative Methods, 23, 16094069241231168. doi:10.1177/16094069241231168. Google Scholar ›
72
Varma, K. M., and Se, G. B. (2022). “Efficient Scalable Migrations in the Cloud,” in Proceedings of the International Conference on Big Data, Cloud Computing, Data Science & Engineering. IEEE. https://doi.org/10.1109/BCD54882.2022.9900725 Google Scholar ›
73
Vatanasombut, B., Igbaria, M., Stylianou, A. C., and Rodgers, W. (2008). Information systems continuance intention of web-based applications customers: The case of online banking. Information & Management, 45(7), pp.419-428. Google Scholar ›
74
Venkatesh, V., and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), pp.186-204. Google Scholar ›
75
Venkatesh, V., Brown, S. A., and Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS Quarterly, 37(1), pp.21-54. Google Scholar ›
76
Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), pp.425-478. Google Scholar ›
77
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., and Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, pp.889-901. Google Scholar ›
78
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), pp.118-144. Google Scholar ›
79
Voorhees, C. M., Brady, M. K., Calantone, R. J., and Ramirez, E. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), pp.119-134. Google Scholar ›
80
Wang, Y., and Haggerty, N. (2011). Individual virtual competence and its influence on work outcomes. Journal of Management Information Systems, 27(4), pp.299-334. Google Scholar ›
81
Wessel, L., Baiyere, A., Ologeanu-Taddei, R., Cha, J., and Blegind-Jensen, T. (2021). Unpacking the difference between digital transformation and IT-enabled organizational transformation. Journal of the Association for Information Systems, 22(1), pp.102-129. Google Scholar ›
82
Wixom, B. H., and Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), pp.85-102. Google Scholar ›
83
Yamauchi, Y., and Swanson, E. B. (2010). Local assimilation of an enterprise system: Situated learning by means of familiarity pockets. Information and Organization, 20(3-4), 187-206. Google Scholar ›

공공기관의 클라우드 전환에서 시스템 품질이 사용자 만족 및 전사적 확산에 미치는 영향: 근무지 및 세대 간 비교