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大数据背景下制造业转型升级的思路与对策研究 被引量:31

A Study about the Thinking and Measure on the Transformation and Upgrading of Manufacturing Industry in the Era of Big Date
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摘要 改革开放以来,中国制造业取得了长足的发展,为促进经济社会发展、增强综合国力作出了重要贡献。2010年我国制造业规模就已超越美国,成为全球第一制造业大国,但与发达国家相比,还存在诸如生产业绩下滑、产能过剩等突出问题,面临着"大而不强"的窘迫局面。随着全球产业竞争格局的重大调整,我国制造业面对着机遇与挑战并存的新常态,制造业转型升级、做强做精的历史任务十分艰巨。大数据产业的兴起,为我国制造业提质增效、创新驱动发展提供了崭新途径,加速推动着我国从制造业大国向制造业强国转型升级。 Since the reform and opening up,Chinese manufacturing industry has made great progress and has made important contributions to promoting economic and social development,to enhancing comprehensive national strength,The scale of China’s manufacturing industry has surpassed the United States and became the largest manufacturing country in the world since 2010. However,compared with the developed countries,there are still outstanding problems such as decline in production performance,overcapacity and so on,facing the embarrassment of "big and not strong". With the adjustment of the global industrial competition pattern,Chinese manufacturing industry is going to move from a big manufacturing country to a powerful one.Facing the new normal with opportunities and challenges,the task of transformation and upgrading of manufacturing industry will be arduous. The rise of large data industry provides a new way for China’s manufacturing industry to improve efficiency and innovation driven development,accelerating the transformation and upgrading of China from a large manufacturing country to a manufacturing power.
作者 房建奇 沈颂东 亢秀秋 FANG Jian-qi;SHEN Song-dong;KANG Xiu-qiu
机构地区 吉林大学商学院
出处 《福建师范大学学报(哲学社会科学版)》 CSSCI 北大核心 2019年第1期21-27,168,共8页 Journal of Fujian Normal University:Philosophy and Social Sciences Edition
基金 2015国家社科基金重大项目"十三五时期环境治理与经济发展方式转变相互协调机制研究"(15ZDA015)
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  • 1黄新祥,陈衍泰.循环经济下企业破坏性创新的商业模式的研究[J].科学学研究,2005,23(B12):270-274. 被引量:9
  • 2MCAFEE, E BRYNJOLFSSON. Big data: the management revolution[J]. Harvard Business Review, 2012,10 : 1-9.
  • 3VALLE S L,LESSER E,SHOCKLEY R,et al. Big data, analyties and the path from insights to value[J]. MIT sloan management review,2011,52(2) :20-32.
  • 4MEGLER V M,MAIER D. When big data leads to lost data [C]// Proceedings of the 5th Ph.D. Workshop on Informa- tion and Knowledge,PlKM' 12. Hawaii:ACM,2012 1-8.
  • 5Sultan N. Knowledge management in the age o{ cloud com- puting and web 2. 0: experiencing the power of disruptive innovations[J]. International Journal of Information Man- agement,2013, 33(1) :160 165.
  • 6Bolloju N, Khalifa M, Turban E. Integrating knowledge management into enterprise environments for the next gen- eration decision support [ J ]. Decision Support Systems, 2002,33(2) :163-176.
  • 7Becerra D,Pham T,Williams T. How big data is revolutioni- zing business[J]. Decision Support Systems, 2012,11 1-16.
  • 8MODIS T. Technological substitutions in the computer in- dustry[J]. Technological Forecasting and Social Change, 1993,43(2) :157-167.
  • 9CHAUDHURI S. What next: a half-dozen data manage- ment research goals for big data and the cloud[C]//Pro ceedings of the 31st symposium on Principles of Database Systems. New York .. ACM, 2012 .. 1-4.
  • 10CUZZOCREA A,SONG I Y,DAVIS K C. Analytics over large-scale multidimensional data: the big data revolution [C]// DOLAP '11 Proceedings of the ACM 14th interna tional workshop on Data Warehousing and OLAP. Glas- gow: ACM,2011 : 101-104.

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