Regional Differences and Spatial Convergence of Innovation Efficiency #br#
of China’s Hightech Industry#br#
——Based on Shared Inputs Twostage DEA

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2016, Vol. 18 ›› Issue (1): 78-86.

Previous Articles Next Articles

Regional Differences and Spatial Convergence of Innovation Efficiency #br# of China’s Hightech Industry#br# ——Based on Shared Inputs Twostage DEA

School of Economics, Fujian Normal University, Fuzhou 350000, China

Received:2015-11-28 Online:2016-02-28

Abstract

Abstract:

Technical innovation process is divided into technical development stage and technical transformation stage in this paper By using the shared inputs twostage DEA model, the technical development efficiency, the technical transformation efficiency and the overall innovation efficiency of the hightech industry in China’s provinces from the year of 2000 to 2013 are measured and their spatial convergence trends are also tested The result shows the differences among provinces are obvious The technical development efficiency in the less developed provinces is obviously higher than the overall innovation efficiency and the technical transformation efficiency is lower than the overall innovation efficiency while the result is opposite in the developed provinces The technical development efficiency, the technical transformation efficiency and the overall innovation efficiency in the central region show obvious convergence trend Although the technical development efficiency and the technical transformation efficiency of the eastern region show convergence, the level of significance is low The technical development efficiency, the technical transformation efficiency and the overall innovation efficiency in the western region, even in the whole China, don’t form a convergence trend The above conclusions imply that the central government should consider the characteristics of high technology industry in different regions and provinces to take different supporting policies; and the local government should combine with their own situation, and take targeted incentives in different stages of technical innovation in hightech industry

Key words: hightech industry, innovation efficiency, spatial convergence, shared inputs twostage DEA

CLC Number:

F1243

XU Xia. Regional Differences and Spatial Convergence of Innovation Efficiency #br# of China’s Hightech Industry#br# ——Based on Shared Inputs Twostage DEA[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 18(1): 78-86.

References

［1］朱有为, 徐康宁. 中国高技术产业研发效率的实证研究［J］. 中国工业经济, 2006(11): 3845.
［2］王军, 杨惠馨. 2006—2008 年中国省际高技术产业效率实证研究［J］. 统计研究, 2010, 27(12): 4650.
［3］ Feng Feng, Wang Bo, Zou Yuanyuan, et al. A new internet DEA structure: measurement of Chinese R&D innovation efficiency in high technology industry［J］. International Journal of Business and Management, 2013, 8(21): 3240.
［4］鲁炜, 严夏. 高技术产业Ｒ＆Ｄ全要素生产率变动分析——基于DEA模型的Malmquist指数方法［J］. 西北农林科技大学学报（社会科学版）, 2012, 12(3): 5156.
［5］杨青峰. 高技术产业地区研发创新效率的决定因素——基于随机前沿模型的实证分析［J］. 管理评论, 2013, 25(6): 4758.
［6］ Xu Lixin, Cheng Min. A study on Chinese regional scientific innovation efficiency with a perspective of synergy degree［J］. Technology and Investment, 2013, 4(4): 229235.
［7］ Niu Dandan, Wang Renwen, Zhang Xinyue, et al. Comparative studies on efficiency of china’s regional innovation system on the basis of cooperation measurement model［J］. Journal of Emerging Trends in Economics and Management Sciences, 2013, 4(2): 147157.
［8］ Fare R, Grosskopf S. Productivity and intermediate products: a frontier approach［J］. Economics Letters, 2006(50): 6570.
［9］ Liu J S, Lu Wenxin. Networkbased method for ranking of efficient units in twostage DEA models［J］. The Journal of the Operational Research Society, 2012, 63(8): 11531164.
［10］ Chen Yao, Du Juan, Sherman H D, et al. DEA model with shared resources and efficiency decomposition［J］. European Journal of Operational Research, 2010, 207(1): 339349.
［11］ Chen C M. A networkDEA model with new efficiency measures to incorporate the dynamic effect in production networks［J］. European Journal of Operation Researches, 2009, 32(5): 687699.
［12］ Kao C, Wang S N. Efficiency decomposition in twostage data envelopment analysis: application onlife insurance companies in Taiwan［J］. European Journal of Operation Researches, 2008, 10(6): 418429.
［13］黄薇. 中国保险机构资金运用效率研究: 基于资源型两阶段DEA模型［J］. 经济研究, 2009, 44(8): 3749.
［14］陈凯华, 官建成. 共享投入型关联两阶段生产系统的网络DEA效率测度与分解［J］. 系统工程理论与实践, 2011, 31(7): 12111221.
［15］ Guan Jiancheng, Chen Kaihua. Measuring the innovation production process: a crossregion empirical study of China’s hightech innovations［J］. Technovation, 2010, 41(30): 348358.
［16］叶锐, 杨建飞, 常云昆. 中国省际高技术产业效率测度与分解——基于共享投入关联DEA模型［J］. 数量经济技术经济研究, 2012(7): 317.
［17］ Chen C P, Hu Jinli, Yang Chihai. An international comparison of R&D efficiency of multiple innovative outputs: the role of the national innovation system［J］. Innovation: Management, Policy & Practice, 2011, 13(3): 341360.
［18］ Lu Zhiying, Xia Yanmei. Innovation efficiency and impact factors of china’s strategic emerging industries［J］. Journal of Emerging Trends in Economics and Management Sciences, 2012, 3(5): 547552.
［19］刘志迎, 叶蓁, 孟令杰. 我国高技术产业技术效率的实证分析［J］. 中国软科学, 2007(5): 139143。
［20］吉生保, 周小柯. 基于三阶段DEA模型的中国高技术产业效率研究［J］. 中央财经大学学报, 2010(12): 6266.
［21］ Michael S, Delgado L. Productivity in China’s the hightech industry: regional heterogeneity and R&D［J］. Technological Forecasting & Social Change, 2012， 83(79): 127141.

[1]	WEI Long, ZHANG Hu. Impact of Environmental Regulation on Efficiency of Green Technology Innovation: Promotion or Inhibition?—From the Dual Perspectives of Innovation Value Chain and Spatial Spillover [J]. Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition), 2020, 22(4): 48-58.
[2]	ZHANG Wang，LIU Ping-feng，ZHOU Xin. Impact of Government Subsidies on Innovation Efficiency of China’s New Energy Enterprises#br# —Based on Stochastic Frontier Approach Study [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 21(3): 62-70.
[3]	LIU Shu-lin, CHEN Jing. Impact of Government Subsidies on Innovation Efficiency of China’s New Energy Enterprises#br# —Based on Stochastic Frontier Approach Study [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 21(3): 52-61.
[4]	CHA Hong-wang, CAI Gao-lou. Evaluation of Innovation Efficiency of Big Data Enterprises in China#br# ——Based on DEA Method [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 19(1): 71-78.
[5]	HAO Jin-lei， JIANG Shi-yao. High-Tech Enterprise’s Innovation Efficiency Based on Three-Stage #br# DEA Model in West Region [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2016, 18(3): 71-76.

Regional Differences and Spatial Convergence of Innovation Efficiency #br# of China’s Hightech Industry#br# ——Based on Shared Inputs Twostage DEA

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 5

Recommended Articles

Metrics

Comments