地理学报 ›› 2021, Vol. 76 ›› Issue (4): 992-1005.doi: 10.11821/dlxb202104014
收稿日期:
2019-12-18
修回日期:
2020-11-30
出版日期:
2021-04-25
发布日期:
2021-06-25
通讯作者:
夏丽丽(1975-), 女, 安徽寿县人, 博士, 副研究员, 研究方向为产业技术创新与空间演变、创新与区域发展。E-mail: hslily@163.com作者简介:
彭如霞(1995-), 女, 四川眉山人, 硕士生, 研究方向为创新与区域发展。E-mail: 2017022050@m.scnu.edu.cn
基金资助:
PENG Ruxia1(), XIA Lili1,2(
), LIN Jiange1
Received:
2019-12-18
Revised:
2020-11-30
Published:
2021-04-25
Online:
2021-06-25
Supported by:
摘要:
外商直接投资(FDI)企业按知识基础类型可分为解析型、合成型和象征型,从政策工具维度对珠江三角洲核心区六市2007—2016年的创新政策进行文本分析,以创新政策强度和创新政策协同度两个指标量化评估珠三角核心区六市创新政策环境,利用多项式逻辑回归模型识别和检验创新政策环境对异质性知识基础的外商直接投资企业区位选择的影响。结果表明:① 珠三角核心区六市创新政策环境时空分异显著,以2010年为时间节点创新政策强度显著提升而协同度明显降低,创新政策强度与协同度均呈楔形空间结构但二者空间异构明显;② 创新政策强度和创新政策协同度对FDI区位选择皆有显著的正效应,且随着创新政策协同度的提升区域更有可能成为解析型和合成型FDI区位选择的对象;③ 政府态度、企业进入方式和布局区位对FDI区位选择有显著影响,集聚因素中的商务服务水平对FDI区位选择的影响显著为正,而城市人口密度和集聚经济水平的影响显著为负。研究结果对地方政府实施更加本地化的创新政策吸引差异化知识基础的FDI,构建区域竞争优势带来重要启示。
彭如霞, 夏丽丽, 林剑铬. 创新政策环境对外商直接投资区位选择的影响——以珠江三角洲核心区六市为例[J]. 地理学报, 2021, 76(4): 992-1005.
PENG Ruxia, XIA Lili, LIN Jiange. The impact of innovation policy environment on location choice of foreign direct investment from the perspective of knowledge base: A case study of six cities in the core area of the Pearl River Delta[J]. Acta Geographica Sinica, 2021, 76(4): 992-1005.
表3
2007—2016年珠三角核心区创新政策强度与协同度值
年份 | 创新政策强度值 | 创新政策协同度值 | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
东莞 | 广州 | 深圳 | 中山 | 佛山 | 珠海 | 东莞 | 广州 | 深圳 | 中山 | 佛山 | 珠海 | ||
2007 | 40.74 | 11.55 | 52.10 | 14.99 | 82.26 | 1.53 | 0.61 | 0.79 | 0.39 | 0.60 | 0.07 | 0.89 | |
2008 | 40.06 | 199.76 | 78.90 | 38.44 | 14.74 | 3.68 | 0.63 | 0.13 | 0.00 | 0.09 | 0.52 | 0.83 | |
2009 | 59.70 | 1.07 | 104.77 | 12.23 | 14.32 | 0.00 | 0.41 | 0.89 | 0.15 | 0.65 | 0.49 | 0.93 | |
2010 | 99.54 | 103.88 | 16.12 | 25.30 | 9.84 | 0.00 | 0.08 | 0.18 | 0.67 | 0.47 | 0.52 | 0.93 | |
2011 | 87.66 | 180.05 | 219.77 | 121.13 | 165.08 | 67.13 | 0.40 | 0.09 | 0.25 | 0.31 | 0.37 | 0.07 | |
2012 | 294.45 | 160.24 | 98.59 | 100.14 | 20.66 | 196.52 | 0.06 | 0.00 | 0.00 | 0.23 | 0.40 | 0.35 | |
2013 | 170.64 | 14.28 | 161.49 | 108.81 | 76.06 | 83.22 | 0.04 | 0.62 | 0.20 | 0.24 | 0.09 | 0.11 | |
2014 | 199.26 | 120.21 | 59.04 | 27.72 | 25.15 | 66.58 | 0.00 | 0.25 | 0.38 | 0.50 | 0.32 | 0.37 | |
2015 | 113.82 | 176.90 | 56.17 | 78.41 | 36.11 | 20.14 | 0.00 | 0.04 | 0.43 | 0.28 | 0.20 | 0.51 | |
2016 | 109.47 | 81.38 | 39.37 | 37.53 | 53.97 | 72.72 | 0.37 | 0.24 | 0.53 | 0.32 | 0.08 | 0.23 | |
年均值 | 121.53 | 104.93 | 88.63 | 56.47 | 49.82 | 51.15 | 0.26 | 0.32 | 0.30 | 0.37 | 0.31 | 0.52 |
表4
模型变量定义
变量名称及符号 | 定义 |
---|---|
因变量 | |
企业知识基础类型 | 1=解析型;2=合成型;3=象征型 |
解释变量 | |
创新政策强度 | 反映创新政策力度和效力,用创新政策强度值表示 |
创新政策协同度 | 供给型、环境型和需求型创新政策两两间的协调程度,用创新政策协同度值表示 |
区位变量 | |
政府态度 | 0=限制类;1=允许类;2=鼓励类 |
企业进入方式 | 0=独资;1=合资 |
集聚经济水平 | 用企业所在地级市规模以上工业企业数自然对数来表示 |
城市人口密度 | 以城市人口/城市面积表示 |
商业服务水平 | 第三产业就业人员数/全部城镇单位就业人员数 |
布局区位 | 按样本进驻的城市进行区分:1=东莞;2=广州;3=深圳;4=中山;5=佛山;6=珠海 |
表5
珠三角核心区创新政策影响FDI区位选择的多项式逻辑回归结果
影响因素 | 解析型/象征型 | 合成型/象征型 | |||
---|---|---|---|---|---|
回归系数 | OR值 | 回归系数 | OR值 | ||
截距 | -1.114 | - | -0.276 | - | |
创新政策强度(x1) | 0.008*** | 1.008 | 0.008*** | 1.008 | |
创新政策协同度(x2) | 1.749*** | 5.750 | 1.518*** | 4.563 | |
[政府态度=0] | 0.328** | 1.388 | 0.560*** | 1.752 | |
[政府态度=1] | 0.266*** | 1.304 | 0.611*** | 1.842 | |
[政府态度=2] | - | - | - | - | |
[进入方式=0] | -0.155* | 0.857 | 0.133* | 1.142 | |
[进入方式=1] | - | - | - | - | |
集聚经济水平(x5) | -0.355*** | 0.701 | -0.464*** | 0.629 | |
城市人口密度(x3) | -0.00026*** | 1.000 | -0.00032*** | 1.000 | |
商业服务水平(x4) | 0.036*** | 1.037 | 0.037*** | 1.038 | |
[地级市=1] | 3.098*** | 22.152 | 3.224*** | 25.136 | |
[地级市=2] | -0.833*** | 0.435 | -0.505*** | 0.604 | |
[地级市=3] | 0.575*** | 1.778 | 1.034*** | 2.812 | |
[地级市=4] | 2.472*** | 11.849 | 3.617*** | 37.217 | |
[地级市=5] | 2.493*** | 12.092 | 4.081*** | 59.182 | |
[地级市=6] | - | - | - | - |
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