全球城市知识流动网络的结构特征与影响因素
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桂钦昌, 杜德斌, 刘承良, 徐伟, 侯纯光, 焦美琪, 翟晨阳, 卢函
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Structural characteristics and influencing factors of the global inter-city knowledge flows network
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GUI Qinchang, DU Debin, LIU Chengliang, XU Wei, HOU Chunguang, JIAO Meiqi, ZHAI Chenyang, LU Han
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表2 负二项式的重力模型回归结果
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Tab. 2 Regression results of the negative binomial gravity models
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| 模型1 | 模型2 | 模型3 | 模型4 | | 城市i发文量 | 0.32750*** | 0.31521*** | 0.32182*** | 0.23175*** | | (0.01140) | (0.01043) | (0.01017) | (0.00830) | | 城市j发文量 | 0.33523*** | 0.32794*** | 0.33285*** | 0.20712*** | | (0.01205) | (0.01091) | (0.01088) | (0.00907) | | 城市i人口数 | 0.01690*** | 0.02252*** | 0.04210*** | 0.02666*** | | (0.00451) | (0.00425) | (0.00435) | (0.00365) | | 城市j人口数 | 0.00740* | 0.01069*** | 0.02956*** | 0.01398*** | | (0.00437) | (0.00413) | (0.00422) | (0.00345) | | 城市i一流大学 | 0.00005 | 0.00006 | 0.00005 | 0.00046*** | | (0.00006) | (0.00006) | (0.00005) | (0.00004) | | 城市j一流大学 | 0.00004 | 0.00004 | 0.00003 | 0.00057*** | | (0.00006) | (0.00006) | (0.00005) | (0.00004) | | 制度邻近性 | | 0.30082*** | 0.16768*** | 0.30144*** | | | (0.01472) | (0.01620) | (0.01330) | | 地理邻近性 | | | -0.08666*** | -0.06924*** | | | | (0.00484) | (0.00394) | | 社会邻近性 | | | | 1.14789*** | | | | | (0.02571) | | 常数 | -0.72820*** | -0.81986*** | -0.72664*** | 0.11746 | | (0.13271) | (0.12082) | (0.12156) | (0.09622) | | 样本量 | 5312 | 5312 | 5312 | 5312 | | Alpha | 0.09514 | 0.08036 | 0.07227 | 0.03873 | | Log likelihood | -19390.632 | -19072.32 | -18886.488 | -17881.985 |
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