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为研究我国中部6省近15a承接国际产业转移成效,探索提高承接国际产业转移水平路径,从投入产出角度构建了承接国际产业转移效率测度指标体系,采用EMS3.1软件测度了我国中部6省80个地级单元2000~2014年承接国际产业转移效率的时空分异特征,结合GeoDa095i软件分析了中部地区承接国际产业转移效率的时空分异格局及空间关联性;在分析影响承接国际产业转移效率机制的基础上,采用固定效应模型对我国中部6省承接国际产业转移效率的影响因素进行定量分析。结果表明:(1)2000~2014年间处于DEA有效的地市数量逐渐增加,处于波动上升的地市有52个,呈现下降趋势的有28个,省会城市及其周边地区DEA效率值相对高于其他地区;(2)中部地区承接国际产业转移效率空间分异显著,具有明显的空间群聚效应;(3)产业支撑因子、产业吸引因子、产业发展因子对中部地区承接国际产业转移效率影响较为显著,而产业鉴别因子影响相对较弱。影响因素回归系数由大到小分别为二、三产业从业人员比重、客运总量、职工平均工资、人均GDP、年末金融机构存款余额研究与试验发展(R&D)经费支出。基于研究结果对中部地区承接国际产业转移提出了相应对策建议。
In order to study the success of international industrial transfer in six provinces of central China in the past 15 years and to explore ways to increase the level of international industrial transfer, an index system of international industrial transfer efficiency was established from the perspective of input-output. By using EMS3.1 software, The spatial-temporal differentiation characteristics of 80 prefecture-level units undertaking the international industrial transfer efficiency from 2000 to 2014 were analyzed. The GeoDa095i software was used to analyze the temporal and spatial differentiation pattern and the spatial correlation of the international industrial transfer efficiency in the central region. After analyzing the influence of international industrial transfer efficiency Based on the fixed-effects model, the quantitative analysis of the factors affecting the efficiency of international industrial transfer undertaken by six provinces in central China was conducted. The results show that: (1) The number of effective DEA cities increased gradually from 2000 to 2014, with 52 in the fluctuating cities and 28 in the downward trend, and the DEA efficiency in the capital cities and surrounding areas was relatively higher than Other regions; (2) The central region undertakes the remarkable spatial heterogeneity of international industrial transfer efficiency and has obvious spatial clustering effect; (3) The industry supportive factor, industrial attractive factor and industrial development factor exert more influence on the international industrial transfer efficiency in the central region Significant, while the industry discriminant factor is relatively weak. The regression coefficients of influencing factors from largest to smallest are the proportion of employees in secondary and tertiary industries, total passenger volume, average wage of workers, per capita GDP, and research and development (R & D) expenditures of financial institutions at the end of the year. Based on the research results, some countermeasures and suggestions are proposed to undertake the international industrial transfer in the central region.