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The Korean Journal of Public Administration
[ Article ]
Korean Journal of Public Administration - Vol. 63, No. 3, pp.213-236
ISSN: 1229-6694 (Print)
Print publication date 30 Sep 2025
Received 08 Jul 2025 Revised 02 Sep 2025 Accepted 08 Sep 2025
DOI: https://doi.org/10.24145/KJPA.63.3.8

공공데이터 채택의도의 영향 요인: 공무원과 시민 간의 집단적 차이를 중심으로

황슬아* ; 이태준**
*제1저자, KDI국제정책대학원 석사 졸업 totos3701@korea.kr
**교신저자, KDI국제정책대학원 교수 davidtjlee@kdischool.ac.kr
Determinants of Open Government Data Adoption: A Comparative Analysis of Citizens and Civil Servants
Seula Hwang* ; Taejun Lee**

초록

공공데이터는 정부혁신과 디지털 경제의 핵심 자원으로 가치가 증대되고 있다. 본 연구는 공공데이터 채택의도에 미치는 영향 요인이 공무원과 시민 집단 간에 어떻게 다른지 규명하고자 했다. 확장된 통합기술수용모델(UTAUT)을 적용하여 다중집단분석을 실시한 결과, 성과기대, 사회적 영향, 개인의 혁신성은 공통적인 정(+)의 영향 요인으로 나타났으나, 그 영향력 크기에는 차이가 있었다. 성과기대는 공무원에게, 개인의 혁신성은 시민에게 더 강한 영향을 미쳤다. 특히, 데이터 리터러시는 공무원 집단에서만 유의한 변수였으며, 시민의 경우 촉진조건과 인지된 위험이 채택의도를 저해하는 요인으로 확인되었다. 이러한 결과는 두 집단의 특성을 고려한 차별화된 공공데이터 활성화 정책이 필수적임을 시사한다. 구체적으로 공무원에게는 직무 성과와 연계된 데이터 리터러시 교육을 강화하고, 시민에게는 데이터 신뢰성 확보, 개인정보 위험 감소를 위한 안전한 활용 환경을 조성해야 한다. 나아가 정부는 시민들이 데이터를 쉽게 이해하도록 사용자 친화적 플랫폼 구축 및 데이터 시각화 도구 보급 등 실질적 지원을 강화할 필요가 있다.

Abstract

This study empirically investigates and compares the factors influencing the intention to adopt Open Government Data (OGD) among citizens and public sector employees in Korea. The analytical framework extends the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating individual innovativeness, data literacy, and perceived risk. Analyzing data from 456 citizens and 655 public officials, the study reveals common and distinct adoption drivers. Results show that performance expectancy, social influence, and individual innovativeness are significant predictors for both groups. However, data literacy positively influenced only public officials. For citizens, facilitating conditions and perceived risk were identified as significant deterrents to adoption. Multi-group analysis further confirmed that the effect of performance expectancy was stronger for public officials, while individual innovativeness was a more critical factor for citizens. These findings underscore the need for differentiated strategies that enhance the job-related value of OGD for officials while fostering an innovative and secure data ecosystem for the public. Tailored policies are crucial for maximizing OGD’s potential for public sector innovation and societal progress.

Keywords:

open government data(OGD), unified theory of acceptance and use of technology(UTAUT), public sector employees, citizens, multi-group analysis

키워드:

공공데이터, 통합기술수용모델(UTAUT), 공무원, 시민, 다중집단분석

References

  • 고현림･신종칠. (2020). 부동산 산업에서 4차 산업혁명 관련 기술의 수용 의도에 관한 연구–감정평가사 집단의 혁신성향을 중심으로. ｢부동산학연구｣, 26(4): 71-91.
  • 김기웅. (2017). 중소기업의 IoT 수용에 미치는 요인 및 정책적 시사점. ｢입법과 정책｣, 9(3): 341-362.
  • 김도승. (2024). 데이터기반행정 활성화를 위한 법적 과제. ｢법학논총｣, 48(1), 179-206.
  • 김영은･박지홍. (2022). 공공데이터 서비스의 지속이용의도에 영향을 미치는 요인에 관한 연구. ｢한국문헌정보학회지｣, 56(1): 277-296.
  • 김진우･조혜인･이봉규. (2019). 금융권 챗봇 서비스 수용의도에 영향을 미치는 요인 연구: UTAUT 모형을 중심으로. ｢디지털콘텐츠학회논문지｣, 20(1): 41-50.
  • 김효정. (2023). 확장된 UTAUT 모형을 활용한 ChatGPT 사용자들의 사용의도에 관한 연구. ｢디지털콘텐츠학회논문지｣, 24(7): 1465-1473.
  • 박상준･손삽. (2016). 기술수용모델에서 타인의 수용정도가 지각된 위험에 미치는 영향: 웨어러블 기기를 중심으로. ｢경영학연구｣, 45(5): 1645-1669.
  • 박종남･조예은. (2021). 데이터 리터러시와 데이터 분석 성숙도의 관계에서 조직문화의 조절효과. ｢정보화정책｣, 28(1): 43-63.
  • 서울디지털재단. (2024). ｢[데이터 이슈브리프] 내 손안의 서울 공공데이터: 인기 데이터 TOP10과 정책 활용 사례｣. 서울: 서울디지털재단.
  • 이문봉. (2012). 혁신성이 SNS 사용 의도에 미치는 영향: UTAUT를 중심으로. ｢한국산업정보학회논문지｣, 17(7): 177-186.
  • 이슬기. (2022). 통합기술수용이론(UTAUT)에 기반한 자율주행 모빌리티 서비스 수용의도에 관한 연구. ｢품질경영학회지｣, 50(3): 491-502.
  • 조봉주. (2019). ｢로보어드바이저에 대한 금융 투자자의 수용의도 영향 요인 연구｣. 서울대학교 행정대학원 박사학위논문.
  • 전병진･김희웅. (2017). 공공 빅데이터 개방 및 활용 활성화 방안에 대한 연구. ｢정보화정책｣, 24(3): 27-41.
  • 차영일･최성규･한경석. (2017). 민간의 공공데이터 활용을 위한 이용의도에 미치는 영향에 관한 실증적 연구. ｢디지털융복합연구｣, 15(6): 9-17.
  • Abdul Wahi, N. S., & Berényi, L. (2023). Validating UTAUT Model for E-Government Adoption Among Employees: A Pilot Study. GRADUS, 10(2): 1-6. [https://doi.org/10.47833/2023.2.ECO.009]
  • Abdul Wahi, N. S., & Berenyi, L. (2024). Examining the effect of social influence and facilitating conditions on e-government adoption by employees in mandatory condition. In Proceedings of the Central and Eastern European eDem and eGov Days 2024, 104-110. [https://doi.org/10.1145/3670243.3670244]
  • Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2): 204-215. [https://doi.org/10.1287/isre.9.2.204]
  • Alraja, M. N., Hammami, S., Chikhi, B., & Fekir, S. (2016). The influence of effort and performance expectancy on employees to adopt e-government: Evidence from Oman. International Review of Management and Marketing, 6(4): 930-934.
  • Alshehri, M., Drew, S., & Alghamdi, R. (2012). E-Government Services: Applying The UTAUT Model.
  • Attewell, P. (2001). Comment: The first and second digital divides. Sociology of Education, 74(3): 252-259. [https://doi.org/10.2307/2673277]
  • Bannister, F., & Connolly, R. (2011). Trust and transformational government: A proposed framework for research. Government Information Quarterly, 28(2): 137-147. [https://doi.org/10.1016/j.giq.2010.06.010]
  • Belanger, F., & Carter, L. (2008). Trust and risk in e-government adoption. Strategic Information Systems, 17(2): 165-176. [https://doi.org/10.1016/j.jsis.2007.12.002]
  • Chu, V. T., Tran, H. T., & Freel, M. (2025). How civic engagement sparks entrepreneurial intention: the mediating role of well-being. Entrepreneurship & Regional Development, 1-26. [https://doi.org/10.1080/08985626.2025.2463605]
  • Cimperman, M., Brenčič, M. M., & Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model. International Journal of Medical Informatics, 90: 22-31. [https://doi.org/10.1016/j.ijmedinf.2016.03.002]
  • Citrin, A. V., Sprott, D. E., Silverman, S. N., & Stem Jr, D. E. (2000). Adoption of internet shopping: the role of consumer innovativeness. Industrial Management & Data Systems, 100(7): 294-300. [https://doi.org/10.1108/02635570010304806]
  • Dawes, S. S. (2010). Stewardship and usefulness: Policy principles for information-based transparency. Government Information Quarterly, 27(4): 377-383. [https://doi.org/10.1016/j.giq.2010.07.001]
  • 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. [https://doi.org/10.1016/S1071-5819(03)00111-3]
  • Gascó-Hernández, M., Martin, E. G., Reggi, L., Pyo, S., & Luna-Reyes, L. F. (2018). Promoting the use of open government data: Cases of training and engagement. Government Information Quarterly, 35(2): 233-242. [https://doi.org/10.1016/j.giq.2018.01.003]
  • Grimmelikhuijsen, S., Porumbescu, G., Hong, B., & Im, T. (2013). The effect of transparency on trust in government: A cross‐national comparative experiment. Public Administration Review, 73(4): 575-586. [https://doi.org/10.1111/puar.12047]
  • Hair, J. F., Hult, G. T. M., Ringle, M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling. Sage Publications. [https://doi.org/10.15358/9783800653614]
  • Ibrahim, F., Münscher, J. C., Daseking, M., & Telle, N. T. (2025). The technology acceptance model and adopter type analysis in the context of artificial intelligence. Frontiers in Artificial Intelligence, 7: 1496518. [https://doi.org/10.3389/frai.2024.1496518]
  • Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information Systems Management, 28(1): 1-8. [https://doi.org/10.1016/j.im.2010.09.001]
  • JIRUI, D. (2023). THE EFFECT OF TECHNOLOGY ADOPTION MODEL ON CULTURALLY MEDIATED BEHAVIORAL INTENTION AND RISK PERCEPTION ON THE PURCHASE OF ELECTRONIC AND HOME LIVING PRODUCTS. Journal of Theoretical and Applied Information Technology, 101(3).
  • Kim, H. W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. MIS Quarterly, 33(3): 567-582. [https://doi.org/10.2307/20650309]
  • Koltay, T. (2015). Data literacy: in search of a name and identity. Journal of Documentation, 71(2): 401-415. [https://doi.org/10.1108/JD-02-2014-0026]
  • Kroll, A., & Vogel, D. (2021). Why public employees manipulate performance data: Prosocial impact, job stress, and red tape. International Public Management Journal, 24(2): 164-182. [https://doi.org/10.1080/10967494.2021.1874579]
  • Marikyan, M., & Papagiannidis, P. (2021). Unified theory of acceptance and use of technology. TheoryHub book.
  • Nov, O., & Ye, C. (2008). Users’ personality and perceived ease of use of digital libraries: The case for conceptualizing task-technology fit. Journal of the American Society for Information Science and Technology, 59(10): 1632-1643. [https://doi.org/10.1002/asi.20800]
  • Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54: 102144. [https://doi.org/10.1016/j.ijinfomgt.2020.102144]
  • Ridsdale, C., Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., & Wuetherick, B. (2015). Strategies and best practices for data literacy education: Knowledge synthesis report.
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.).
  • Sayogo, D. S., Pardo, T. A., & Cook, M. (2014). A framework for benchmarking open government data efforts. In 2014 47th Hawaii International Conference on System Sciences, 1896-1905. IEEE. [https://doi.org/10.1109/HICSS.2014.240]
  • Shuhaiber, A. (2016). How facilitating conditions impact students’ intention to use virtual lectures? An empirical evidence. AICT 2016, 79.
  • Taylor, J. (2010). Public service motivation, civic attitudes and actions of public, nonprofit and private sector employees. Public Administration, 88(4): 1083-1098. [https://doi.org/10.1111/j.1467-9299.2010.01870.x]
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3): 425-478. [https://doi.org/10.2307/30036540]
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1): 157-178. [https://doi.org/10.2307/41410412]
  • Yavetz, G., & Aharony, N. (2022). The users’ point of view: towards a model of government information behavior on social media. Heliyon, 8(8). [https://doi.org/10.1016/j.heliyon.2022.e10146]
  • Zuiderwijk, A., Janssen, M., & Davis, C. (2014). Innovation with open data: Essential elements of open data ecosystems. Information Polity, 19(1-2): 17-33. [https://doi.org/10.3233/IP-140329]