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基于三阶段DEA的我国医药产业创新效率评价研究 被引量:10

Study on Evaluation of Innovation Efficiency of Pharmaceutical Industry in China Based on Three-stage Data Envelopment Analysis
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摘要 目的:为提升我国医药产业创新效率、促进我国医药产业高质量发展提供参考。方法:运用三阶段数据包络分析法(DEA),以经济发展、政策支持、产业基础和创新基础等4个因素作为环境变量,从《中国统计年鉴》和《中国高技术产业统计年鉴》中选取2012-2016年以及2018年我国31个省(区、市)的投入、产出及环境等相关指标数据,探讨我国医药产业创新效率变化规律并给出相应建议。结果与结论:有18个省(区、市)的医药产业创新效率被高估,13个省(区、市)被低估。其中,福建、黑龙江、吉林、江西、云南、辽宁、重庆调整前的创新效率存在0~0.1的高估,陕西、海南、甘肃和山西存在0.1~0.3的高估,内蒙古、贵州、广西、新疆和宁夏存在0.3~0.5的高估;而安徽、湖南、上海、北京、河北、四川、天津和河南调整前的创新效率存在0.1~0.3的低估,湖北、江苏、浙江、山东和广东存在0.3~0.5的低估;西藏、青海和广东受环境因素较大,其中西藏、青海调整前的创新效率比调整后分别高估了0.603、0.538,而广东则低估了0.470。总体而言,我国东部地区和中部地区调整前的创新效率被低估,而东北地区和西部地区被高估;调整前创新效率由高到低排序依次为中部、西部、东部和东北地区,而调整后变为东部、中部、东北和西部地区。我国医药产业创新效率受环境影响较大,因此各地要注重对医药产业的政策支持,加强对医药产业的政策引导作用;完善产业链及配套措施,营造良好的创新氛围;促进各地创新资源的流动,加强地区间合作与交流,以提升我国医药产业的创新效率、促进医药产业的高质量发展。 OBJECTIVE:To provide reference for improving the innovation efficiency of Chinese pharmaceutical industry and promoting the high-quality development of the pharmaceutical industry.METHODS:Using local economic development,policy support,industrial foundation and innovation foundation as environmental variables,three-stage data envelopment analysis(DEA)was used to explore the change regularity of innovation efficiency of the pharmaceutical industry by collecting related data such as input,output and invironment of 31 provinces(autonomous regions,municipalities)in China during 2012-2016 and in 2018 from China Statistical Yearbook and China High-tech Industry Statistical Yearbook.RESULTS&CONCLUSIONS:The innovation efficiency of the pharmaceutical industry in 18 provinces(autonomous regions,municipalities)were overestimated,and other 13 provinces(autonomous regions,municipalities)was underestimated.The innovation efficiency of Fujian,Heilongjiang,Jilin,Jiangxi,Yunnan,Liaoning and Chongqing before adjustment were overestimated 0-0.1,Shaanxi,Hainan,Gansu and Shanxi were overestimated 0.1-0.3,Inner Mongolia,Guizhou,Guangxi,Xinjiang and Ningxia were overestimated 0.3-0.5;while the innovation efficiency of Anhui,Hunan,Shanghai,Beijing,Hebei,Sichuan,Tianjin and Henan were underestimation 0.1-0.3,Hubei,Jiangsu,Zhejiang,Shandong and Guangdong had an underestimation of 0.3-0.5 before adjustment.Tibet,Qinghai and Guangdong were greatly affected by environmental factors.The innovation efficiency in Tibet and Qinghai before adjustment were overestimated by 0.603 and 0.538 compared with after adjustment,while Guangdong was underestimated by 0.470.The innovation efficiency value of the eastern and central regions of China before adjustment was underestimated,while the northeastern and western regions were overestimated overall.Before the adjustment,the order of innovation efficiency in descending order was the central,western,eastern and northeastern regions,and after the adjustment,it became the eastern,central,northeastern and western regions.The innovation efficiency of Chinese pharmaceutical industry is greatly affected by the environment,so all localities should pay attention to the policy support for the pharmaceutical industry and strengthen the policy guiding role for the pharmaceutical industry;improve the industrial chain and supporting measures to create a good innovation environment;promote the flow of innovation resources in different regions,strengthen the cooperation and exchange among regions,so as to improve the innovation efficiency of Chinese pharmaceutical industry and promote the highquality development of the pharmaceutical industry.
作者 徐俐颖 翁坤玲 蒋丹 褚淑贞 XU Liying;WENG Kunling;JIANG Dan;CHU Shuzhen(School of International Pharmaceutical Business,China Pharmaceutical University,Nanjing 211198,China;Research Center of National Drug Policy&Ecosystem,China Pharmaceutical University,Nanjing 211198)
出处 《中国药房》 CAS 北大核心 2020年第16期1921-1926,共6页 China Pharmacy
基金 国家社会科学基金资助项目(No.15ZDB167) 中国药科大学“双一流”学科创新团队建设项目(No.CPU2018GY39)。
关键词 医药产业 创新效率 三阶段数据包络分析法 经济发展 政策支持 产业基础 创新基础 Pharmaceutical industry Innovation efficiency Three-stage data development analysis Economic development Policy support Industrial foundation Innovation foundation
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