References
- 김경태 (2014), 빅데이터 활용사례, 한국지능정보시스템학회, 한국지능정보시스템학회 학술대회논문집, pp.71-84.
- 김문수, 김호 (2003), 기술 및 수요속성에 따른 정보통신서비스 확산 패턴, 기술혁신연구, 제11권, 제2호, pp.71-89
- 김방룡, 홍재표, 고순주 (2014) 특허분석을 통한 빅데이터 기술개발 동향, ETRI 보고서
- 김은영, 이정훈, 서동욱 (2013), 빅데이터 시스템의 수용의도에 영향을 미치는 수용조직의 환경요인에 관한 연구, 한국데이타베이스학회지, 제20권, 제4호, pp.1-18
- 김정경 (2016), 국내.외 빅데이터 동향 및 성공사례, 대한산업공학회, ie 매거진, 제23권, 제1호, pp.47-52.
- 김정선, 송태민 (2014), 빅데이터 기술수용의 초기 특성 연구, 한국콘텐츠학회논문지, 제14권, 제9호, pp.538-555 https://doi.org/10.5392/JKCA.2014.14.09.538
- 김준모, 신준석 (2014), 특허 인용 네트워크와 동적 기술트리 분석을 활용한 기술 진화 경로 연구: 초고압 직류송전 시스템 사례, 기술혁신연구, 제22권, 제4호, pp.117-143. https://doi.org/10.14383/SIME.2014.22.4.117
- 김지웅, 허준, 김장일 (2013), 빅데이터의 금융기관 활용 사례, 전자공학회지 제40권, 제8호, pp.49-54.
- 김지혜, 장재영, 윤홍준, 김한준 (2010). 키워드 관련도를 이용한 뉴스기사의 연관검색 기법. 한국정보과학회 학술발표논문집, 제37권, 제1C호, pp.53-57.
- 김현우, 최윤정, 문영호 (2015). 과학계량학적 HCP 분석을 통한 연구개발 성과 평가. 한국기술혁신학회 학술대회, pp.226-240.
- 문진희, 권의준, 금영정 (2017), 특허 동시분류분석과 텍스트마이닝을 활용한 사물인터넷 기술융합 분석. 기술혁신연구, 제25권, 제3호, pp.1-24. https://doi.org/10.14383/SIME.2017.25.3.1
- 박대민 (2013). 뉴스 기사의 빅데이터 분석 방법으로서 뉴스정보원연결망분석. 한국언론학보, 제57권, 제6호, pp.234-262.
- 박세환 (2014), 빅데이터 기술 및 시장 동향, 정보통신기술진흥센터 주간기술동향, pp.15-24.
- 박재득, (2011) 빅 데이타 산업현황 및 대응방안, 한국산업기술평가관리원, KEIT PD Issue, 제11권, 제4호
- 박종현, 주창림, 신혁, 김문구 (2015), 기업의 빅데이터 수용의 영향요인, 한국경영학회 통합학술발표논문집 , pp.72-76
- 복경수, 유재수 (2014), 빅데이터 활성화 정책 및 응용 사례, 한국정보과학회, 정보과학회지 32(11), pp.46-57.
- 서윤교, 김시정 (2016). 뉴스 내용분석과 하이프 사이클을 활용한 기술기획의 탐색적 연구. 기술혁신학회지, 제19권, 제1호, pp.80-104.
- 서환주, 안정화 (2001), 정보통신기술의 확산과 결정요인, 기술혁신연구, 제9권, 제2호, pp.56-76
- 신민수, 박민규, 배성훈. (2017). 나노 인포매틱스 기반 구축을 위한 구글트렌드와 데이터 마이닝 기법을 활용한 나노 기술 트렌드 분석. 산업경영시스템학회지, 제40권, 제4호, pp.237-245. https://doi.org/10.11627/jkise.2017.40.4.237
- 신인용, 김현호 (2014), "일반범용기술과 경제성장. 생산성논집, 제28권, 제2호, pp.337-360.
- 이영주, 양현철 (2017), 활용 주체별 빅데이터 수용 인식 차이에 관한 연구: 활용 목적, 조직 규모, 업종 특성을 중심으로, 정보화정책, 제24권, 제1호, pp. 79-99 https://doi.org/10.22693/NIAIP.2017.24.1.079
- 이응용, (2012) 미국정부의 빅데이터 R&D전략, 인터넷&시큐리티 이슈, 한국인터넷진흥원
- 이재윤, 최상희. (2015). 논문 인용 영향력 측정 지수의 편향성에 대한 연구. 정보관리학회지, 제32권, 제4호, pp.205-221. https://doi.org/10.3743/KOSIM.2015.32.4.205
- 임수정, 박덕근 (2018), 소셜미디어 분석을 활용한 재난안전산업 육성정책 수립방안, 기술혁신연, 제26권, 제1호, pp.31-57. https://doi.org/10.14383/SIME.2018.26.1.31
- 정보통신산업진흥원 (2013), 빅데이터 확산에 따른 도전과 기회, 주간기술동향 1498
- Accenture (2014). Big Success with Big Data.
- Bai, J., Fan, J., & Tsay, R. (2016). Special Issue on Big Data, Journal of Business & Economic Statistics, Vol.34, pp.487-488 https://doi.org/10.1080/07350015.2016.1197681
- Bass, F. M. (1969). A new product growth for model consumer durables. Management science, Vol.15, No.5, pp.215-227. https://doi.org/10.1287/mnsc.15.5.215
- Bourgoin, M. O., & Smith, S. J. (1995). Big Data--Better Returns, Leveraging Your Hidden Data Assets to Improve ROI. Artificial Intelligence in the Capital Markets, Probus Publishing Company.
- Bresnahan, T. (2010). General purpose technologies. In Handbook of the Economics of Innovation (Vol. 2, pp. 761-791). North-Holland.
- Bresnahan, T. F., & Trajtenberg, M. (1995). General purpose technologies 'Engines of growth'?. Journal of econometrics, Vol.65, No.1,pp. 83-108. https://doi.org/10.1016/0304-4076(94)01598-T
- Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS quarterly, Vol.36, No.4, pp.1165-1188. https://doi.org/10.2307/41703503
- Choi, H., & Varian, H. (2012). Predicting the present with Google Trends. Economic Record, Vol.88, No.s1, pp.2-9. https://doi.org/10.1111/j.1475-4932.2012.00809.x
- Cox, M., & Ellsworth, D. (1997, October). Application-controlled demand paging for out-of-core visualization. In Proceedings of the 8th conference on Visualization'97 (pp. 235-ff). IEEE Computer Society Press.
- Demchenko, Y., Gruengard, E., & Klous, S. (2014). Instructional model for building effective Big Data curricula for online and campus education. In Cloud Computing Technology and Science (CloudCom), IEEE 6th International Conference (pp. 935-941)
- Devlin, B., Rogers, S., Myers, J. (2012). EMA and 9sight Consulting Report, http://www.9sight.com/pdfs/Big_Data_Comes_of_Age.pdf
- Diebold, F. (2012). A Personal Perspective on the Origin (s) and Development of'Big Data': The Phenomenon, the Term, and the Discipline, Second Version.
- Douglas, K. (2015). Technologies for Data. Working paper of SAF05 project.
- Ena, O., Mikova, N., Saritas, O., & Sokolova, A. (2016). A methodology for technology trend monitoring: the case of semantic technologies. Scientometrics, Vol.108, No.3, pp.1013-1041. https://doi.org/10.1007/s11192-016-2024-0
- Fanelli, D. (2013). Any publicity is better than none: newspaper coverage increases citations, in the UK more than in Italy. Scientometrics, Vol.95, No.3, 1167-1177. https://doi.org/10.1007/s11192-012-0925-0
- Fourt, L. A., & Woodlock, J. W. (1960). Early prediction of market success for new grocery products. The Journal of Marketing, Vol.25, No.2, pp.31-38. https://doi.org/10.1177/002224296002500206
- Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, Vol.35, No.2, pp.137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
- Gartner (2010) https://www.gartner.com/newsroom/id/1210613
- Gartner (2011) https://www.gartner.com/newsroom/id/1454221
- Gartner (2014). Survey analysis: Big Data Investment Grows but Deployments Remain Scarce in 2014.
- Gossart, C. (2015). Rebound effects and ICT: a review of the literature. In ICT innovations for sustainability (pp. 435-448). Springer, Cham.
- Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: systematic review and recommendations. The Milbank Quarterly, Vol.82, No.4, pp.581-629. https://doi.org/10.1111/j.0887-378X.2004.00325.x
- Greve, H. R. (2009). Bigger and safer: The diffusion of competitive advantage. Strategic Management Journal, Vol.30, No.1, pp.1-23. https://doi.org/10.1002/smj.721
- Greve, H. R., & Seidel, M. D. L. (2015). The thin red line between success and failure: Path dependence in the diffusion of innovative production technologies. Strategic Management Journal, Vol.36, No.4, pp.475-496. https://doi.org/10.1002/smj.2232
- Guerrieri, P. A. O. L. O., & Padoan, P. C. (2007). Modelling ICT as a general purpose technology. Evaluation, https://pardee.du.edu/sites/default/files/ModelingICT.pdf
- Helpman, E. (Ed.). (1998). General purpose technologies and economic growth. MIT press.
- Hu, J., & Zhang, Y. (2017). Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization. Scientometrics, Vol.112, No.1, pp.91-109. https://doi.org/10.1007/s11192-017-2383-1
- IBM (2012). The real-world use of big data: How innovative enterprises extract value from uncertain data
- Jewell, D., Barros, R. D., Diederichs, S., Duijvestijn, L. M., Hammersley, M., Hazra, A., ... & Portilla, I. (2014). Performance and capacity implications for big data. IBM Redbooks.
- Kearns, M. J. (2010). Designing a digital future: Federally funded research and development in networking and information technology.
- Kubacki, K., Rundle-Thiele, S., Pang, B., & Buyucek, N. (2015). Minimizing alcohol harm: A systematic social marketing review (2000-2014). Journal of Business Research, Vol.68, No.10, pp.2214-2222. https://doi.org/10.1016/j.jbusres.2015.03.023
- Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, Vol.6, No.70.
- Liao, H., Wang, B., Li, B., & Weyman-Jones, T. (2016). ICT as a general-purpose technology: The productivity of ICT in the United States revisited. Information Economics and Policy, Vol.36, pp.10-25. https://doi.org/10.1016/j.infoecopol.2016.05.001
- Liu, N., An, H., Gao, X., Li, H., & Hao, X. (2016). Breaking news dissemination in the media via propagation behavior based on complex network theory. Physica A: Statistical Mechanics and its Applications, 453, pp.44-54. https://doi.org/10.1016/j.physa.2016.02.046
- McKinsey Global Institute (2011). Big data: The next frontier for innovation, competition, and productivity
- Mashey, J. R. (1997, October). Big Data and the next wave of infraS-tress. In Computer Science Division Seminar, University of California, Berkeley.
- McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, Vol.90, No.10, 60-68.
- Meade, N., & Islam, T. (2006). Modelling and forecasting the diffusion of innovation-A 25-year review. International Journal of forecasting, Vol.22, No.3, pp.519-545. https://doi.org/10.1016/j.ijforecast.2006.01.005
- Narin, F. (1995). Patents as indicators for the evaluation of industrial research output. Scientometrics, Vol.34, No.3, pp.489-496. https://doi.org/10.1007/BF02018015
- National Information Agency (2014). Year of Information Society Static
- O'Leary, D. E. (2013). BIG DATA', THE 'INTERNET OF THINGS'AND THE 'INTERNET OF SIGNS. Intelligent Systems in Accounting, Finance and Management, Vol.20, No.1, pp.53-65. https://doi.org/10.1002/isaf.1336
- Pateli, A. G., & Giaglis, G. M. (2005). Technology innovation-induced business model change: a contingency approach. Journal of Organizational Change Management, Vol.18, No.2, pp.167-183. https://doi.org/10.1108/09534810510589589
- Pradhan, R. P., Arvin, M. B., & Norman, N. R. (2015). The dynamics of information and communications technologies infrastructure, economic growth, and financial development: Evidence from Asian countries. Technology in Society, Vol.42, pp.135-149. https://doi.org/10.1016/j.techsoc.2015.04.002
- Preis, T., Moat, H. S., & Stanley, H. E. (2013). Quantifying trading behavior in financial markets using Google Trends. Scientific reports, 3, srep01684.
- Rogers, E. M. (1976). New product adoption and diffusion. Journal of consumer Research, Vol.2, No.4, pp.290-301. https://doi.org/10.1086/208642
- Seyedghorban, Z., Matanda, M. J., & LaPlaca, P. (2016). Advancing theory and knowledge in the business-to-business branding literature. Journal of Business Research, Vol.69, No.8, pp.2664-2677. https://doi.org/10.1016/j.jbusres.2015.11.002
- Sheng, J., Amankwah-Amoah, J., & Wang, X. (2017). A multidisciplinary perspective of big data in management research. International Journal of Production Economics, Vol.191, pp.97-112. https://doi.org/10.1016/j.ijpe.2017.06.006
- Shollo, A., & Galliers, R. D. (2016). Towards an understanding of the role of business intelligence systems in organisational knowing. Information Systems Journal, Vol.26, No.4, pp.339-367. https://doi.org/10.1111/isj.12071
- Taylor, L., Schroeder, R., & Meyer, E. (2014). Emerging practices and perspectives on Big Data analysis in economics: Bigger and better or more of the same?. Big Data & Society, Vol.1, No.2,
- Thoma, G. (2008). Striving for a large market: evidence from a general purpose technology in action. Industrial and Corporate Change, Vol.18, No.1, pp.107-138. https://doi.org/10.1093/icc/dtn050
- Tilly, C. (1984). The old new social history and the new old social history. Review (Fernand Braudel Center), Vol.7, No.3, pp.363-406.
- Wang, L., & Alexander, C. A. (2015). Big data in design and manufacturing engineering. American Journal of Engineering and Applied Sciences, 8, No.2, pp.223. https://doi.org/10.3844/ajeassp.2015.223.232
- Watanabe, C., Naveed, K., & Neittaanmaki, P. (2015). Dependency on un-captured GDP as a source of resilience beyond economic value in countries with advanced ICT infrastructure: Similarities and disparities between Finland and Singapore. Technology in Society, Vol.42, pp.104-122. https://doi.org/10.1016/j.techsoc.2015.04.003
- Zhang, L., Xu, K., & Zhao, J. (2017). Sleeping beauties in meme diffusion. Scientometrics, Vol.112, No.1, pp.383-402. https://doi.org/10.1007/s11192-017-2390-2