Innovative Production Efficiency in Chinese High-Tech Industries during the 13th Five-Year Plan: Evidence from a Three-Stage DEA Model

Junlin He, Wei Theng Lau, Yanjun Liu
{"title":"Innovative Production Efficiency in Chinese High-Tech Industries during the 13th Five-Year Plan: Evidence from a Three-Stage DEA Model","authors":"Junlin He, Wei Theng Lau, Yanjun Liu","doi":"10.47852/bonviewglce3202910","DOIUrl":null,"url":null,"abstract":"Innovative production in high-tech industries is seen as a promoter of corporate profitability and a driver of China's economic growth. However, some scholars point out that high-tech industry is in its infancy and has insufficient innovative production efficiency, which severely restricts regional economic development. To explore this further, we studied the innovation production efficiency of China's high-tech industry during the 13th Five-Year Plan period (2016-2020). The three-stage Data Envelopment Analysis model was utilized to calculate the efficiency of the innovation production in this industry, and we initially employed the DEA-BCC model to calculate the efficiency for 31 provinces and applied similar-stochastic frontier analysis regression to eliminate the potential influence of external environmental factors. The empirical results findings reveal significant inter-regional differences in the efficiency of innovation production, with the Eastern region is the most efficient in innovation production, the Western region has greater growth potential, and the Central region requires to improve its overall efficiency by increasing technological inputs. In addition, we attempt to provide recommendations to policy makers based on our conclusions.","PeriodicalId":489841,"journal":{"name":"Green and Low-Carbon Economy","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Green and Low-Carbon Economy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47852/bonviewglce3202910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Innovative production in high-tech industries is seen as a promoter of corporate profitability and a driver of China's economic growth. However, some scholars point out that high-tech industry is in its infancy and has insufficient innovative production efficiency, which severely restricts regional economic development. To explore this further, we studied the innovation production efficiency of China's high-tech industry during the 13th Five-Year Plan period (2016-2020). The three-stage Data Envelopment Analysis model was utilized to calculate the efficiency of the innovation production in this industry, and we initially employed the DEA-BCC model to calculate the efficiency for 31 provinces and applied similar-stochastic frontier analysis regression to eliminate the potential influence of external environmental factors. The empirical results findings reveal significant inter-regional differences in the efficiency of innovation production, with the Eastern region is the most efficient in innovation production, the Western region has greater growth potential, and the Central region requires to improve its overall efficiency by increasing technological inputs. In addition, we attempt to provide recommendations to policy makers based on our conclusions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
“十三五”期间中国高技术产业创新生产效率:基于三阶段DEA模型的证据
高科技产业的创新生产被视为企业盈利能力的推动者和中国经济增长的驱动力。但也有学者指出,高技术产业尚处于起步阶段,创新生产效率不足,严重制约了区域经济的发展。为了进一步探讨这一点,我们研究了“十三五”期间中国高技术产业的创新生产效率。采用三阶段数据包络分析模型计算了该行业的创新生产效率,初步采用DEA-BCC模型计算了31个省份的创新生产效率,并采用类似随机前沿分析回归消除了外部环境因素的潜在影响。实证结果表明,区域间创新生产效率存在显著差异,东部地区创新生产效率最高,西部地区创新生产增长潜力更大,中部地区需要通过增加技术投入来提高整体效率。此外,我们试图根据我们的结论向政策制定者提供建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Safe Transfer of Ammonia in Pipelines: An Analysis of Risk Addressing Loss and Damage from Climate Change Through Tokenized Rainfall Futures Role of Stakeholder Engagement in Sustainable Development in Estonian Small and Medium-Sized Enterprises Has the Low-Carbon City Pilot Policy Reduced Urban Carbon Emissions in China? Corporate Social Entrepreneurship (CSE) Model for the Construction Industry of Sri Lanka
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1