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NTIS 바로가기지식경영연구 = Knowledge Management Research, v.21 no.4, 2020년, pp.243 - 263
이규엽 (한국정보화진흥원 지능데이터기획팀) , 박상철 (대구대학교 경영학과) , 류성열 (대진대학교 경영학과)
The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of op...
공공데이터전략위원회 (2016). 제2차 공공데이터 기본계획. http://www.odsc.go.kr
공공데이터전략위원회 (2019). 제3차 공공데이터 기본계획. http://www.odsc.go.kr
김문구, 박종현 (2019). 빅데이터 플랫폼의 산업생태계 현황과 주요 이슈. 한국전자통신연구원(ETRI).
배동민, 박현수, 오기환 (2013). 빅데이터 동향 및 정책 시사점. 정보통신방송정책, 25(10), 37-74.
성욱준 (2017). 데이터 생애주기 관점에서 본 공공 부문 빅데이터 활성화 방안. 한국지역정보화학회지, 20(2), 25-41.
신승철, 하현주, 김소연, 손정숙 (2016). 전자정부서비스 수준진단 모델 개발 연구. 한국정보화진흥원.
이재호 (2014). 정부3.0실현을 위한 빅데이터 활용방안. 한국행정연구원.
정국환, 문정욱, 이시직, 유지연, 한은영, 왕재선, 서혁준 (2013). 공공데이터 개방.활용 성과측정을 위한 평가모델 연구. 정보통신정책연구원.
정승호, 정덕훈 (2013). 데이터 공학: 공공기관의 데이터 품질에 영향을 미치는 요인에 관한 연구. 정보처리학회 논문지: 소프트웨어 및 데이터 공학, 2(4), 251-266.
한정희 (2019). 플랫폼 비즈니스와 가치 창출: 개방형 공공데이터 활용. 지식경영연구, 20(1), 155-174.
현미환, 이혜진, 김혜선, 박진호 (2014). 개방형 데이터(Open Data) 평가를 위한 오픈데이터 측정지표 현황 분석. 한국과학기술정보연구원.
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182(4), 113-131.
Baesens, B., Bapna, R., Marsden, J. R., Vanthienen, J., & Zhao, J. L. (2016). Transformational issues of big data and analytics in networked business. MIS Quarterly, 40(4), 807-818.
Blaschke, M., Haki, K., Aier, S., & Winter, R. (2018). Capabilities for digital platform survival: Insights from a business-to-business digital platform. In Proceedings of 39th International Conference on Information Systems, San Francisco, USA.
Bourne, M., Franco, M., & Wikes, J. (2003). Corporate performance management. Measuring Business Excellence, 7(3), 15-21.
Cao, G., & Duan, Y. (2014). Gaining competitive advantage from analytics through the mediation of decision making effectiveness: An empirical study of UK manufacturing companies. In Proceedings of the Pacific Asia conference on information systems (PACIS), Chengdu, China.
Chen, H., Chian, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188.
Cosic, R., Shanks, G., & Maynard, S. (2012). Towards a business analytics capability maturity model. In Proceedings of the 23rd Australasian Conference on Information Systems(ACIS), Geelong, Australia.
Danneels, L., Viaene, S., & Bergh, J. (2017). Open data platforms: Discussing alternative knowledge epistemologies. Government Information Quarterly, 34(3), 365-378.
Ghazawneh, A., & Henfridsson, O. (2013). Balancing platform control and external contribution in third-party development: The boundary resources model. Information Systems Journal, 23(2), 173-192.
Grant, R. M. (1991). The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 33(3), 114-135.
Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049-1064.
Howson, C. (2008). Successful Business Intelligence: Secrets to Making BI a Killer App. McGraw-Hill Osborne Media.
Kim, G., Shin, B., & Kwon, O. (2012). Investigating the value of sociomaterialism in conceptualizing IT capability of a firm. Journal of Management Information Systems, 29(3), 327-362.
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research, 98, 261-276.
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), doi:10.1016/j.im.2019.05.004
Myerson, J. M. (2002). Enterprise systems integration (2nd ed.). Auerbach Publications.
Neely, A. D., Adams, C., & Crowe, P. (2001). The performance prism in practice. Measuring Business Excellence, 5(2), 6-12.
Neely, A. D., Adams, C., & Kennerley, M. (2002). The performance prism, the scorecard for measuring and managing business success. London: FT Prentice Hall.
Newman, D. (2011). How to plan, participate and prosper in the data economy. Gartner.
NIST (2018). NIST big data interoperability framework: Volume 1-9. National Institute of Standards and Technology, U.S. Department of Commerce.
NIST(National Institute of Standards and Technology) (2018). NIST big data interoperability framework: Volume 1-9. U.S. Department of Commerce.
OECD (2015). Government at a glance 2015. Paris: OECD Publishing.
OECD (2017). Government at a glance 2017. Paris: OECD Publishing.
OECD (2019). Government at a glance 2019. Paris: OECD Publishing.
Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2018). Big data and business analytics ecosystems: Paving the way towards digital transformation and sustainable societies. Information Systems and e-Business Management, 16(3), 479-491.
Parker, G., Alstyne, M. V., & Jiang, X. (2017). Platform ecosystems: How developers invert the firm. MIS Quarterly, 41(1), 256-266.
Pee, L. G., & Chua, A. Y. K. (2016). Duration, frequency, and diversity of knowledge contribution: Differential effects of job characteristics. Information and Management, 53(4), 435-446.
Ramaamurthy, K., Sen, A., & Sinha, A. (2008). An empirical investigation of the key determinants of datawarehouse adoption. Decision Support Systems, 44(4), 817-841.
Ren, J. F., Wamba, S. F., Akter, S., Dubey, R., & Childe, S. J. (2017). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011-5026.
Seddon J. J., & Currie W. L. (2017). A model for unpacking big data analytics in high-frequency trading. Journal of Business Research, 70(1), 300-307.
Setia, P., & Patel, P. C. (2013). How information systems help create OM capabilities: Consequents and antecedents of operational absorptive capacity. Journal of Operations Management, 31(6), 409-431.
Shanks, G., Bekmamedova, N., & Sharma, R. (2011). Creating value from business analytics systems: The impact of strategy. In Proceedings of 15th Pacific Asia Conference on Information Systems(PACIS), Brisbane, Australia.
Tan, B., Lu, X., Pan, S. L., & Huang, L. (2015). The role of IS capabilities in the development of multi-sided platforms: The digital ecosystem strategy of Alibaba.com. Journal of the Association for Information Systems, 16(4), 248-280.
Tiwana, A., Konsynski, B., & Bush, A. A. (2010). Platform evolution: Coevolution of platform architecture, governance, and environmental dynamics. Information Systems Research, 21(4), 675-687.
Tsai, H. T., & Bagozzi, R. P. (2014). Contribution behavior in virtual communities: Cognitive, emotional, and social influences. MIS Quarterly, 38(1), 143-163.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365.
Watson, H. J., & Wixom, B. (2007). Enterprise agility and mature BI capabilities. Business Intelligence Journal, 12(3), 4-6.
Weill, P., & Subramani, M. (2002). Infrastructure for strategic agility. Sloan Management Review, 44(1), 57-65.
K-ICT 빅데이터센터 (2020). https://kbig.kr/portal/, 접속일자: 2020년 11월 19일.
공공데이터포털 (2020). http://www.data.go.kr, 접속일자: 2020년 10월 20일.
대한민국 정책브리핑 (2020). 정책위키-한눈에 보는 정책: 데이터경제. https://www.korea.kr/special/policyCurationView.do?newsId148863563, 접속일자: 2020년 11월 11일.
빅데이터플랫폼 통합데이터 지도 (2020). https://www.bigdata-map.kr/, 접속일자: 2020년 11월 11일.
한국정보화진흥원 (2020). 빅데이터 플랫폼 및 센터 구축사업-공모안내서. https://www.nia.or.kr/site/nia_kor/ex/bbs/View.do?cbIdx78336&bcIdx22675&parentSeq22675, 접속일자: 2020년 11월 11일.
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