黄河流域文化产业集群时空格局与空间溢出效应研究

doi:10.12118/j.issn.1000-6060.2023.097

摘要/Abstract

摘要：

基于2005—2020年黄河流域62市面板数据，从集群规模、联系度和专业化3个维度匹配构建文化产业集群水平指标体系，采用莫兰指数（Moran’s I）和空间杜宾模型，在厘清空间溢出效应作用机制与路径的基础上，探究黄河流域文化产业集群时空格局及空间溢出效应影响因素。结果表明：（1） 2005—2020年黄河流域文化产业集群指数均值由0.07上升为0.21，整体呈“正三角”型分布模式。（2）城市间文化产业集群发展水平不均衡，存在明显的“虹吸效应”，各解释变量对溢出效应影响效果差异显著。（3）空间溢出效应与地理距离有明显的相关性，当地理距离达到500 km时，正向的空间溢出效应最强，超过850 km时，空间溢出效应逐渐消失，总体呈倒“U”型趋势。基于上述分析，为加快黄河流域文化产业集群发展，提高区域竞争力，缩小地区发展差距，提出加强区域协同合作、把握城市更新进程、避免同质化竞争等建议。

关键词: 黄河流域, 文化产业, 集群水平, 影响因素, 空间溢出效应

Abstract:

In the context of high-quality development in the Yellow River Basin of China, establishing cultural industry clusters and exploring of spatial spillover effects is of utmost importance for accelerating the transition toward high-quality development in the basin, while fostering balanced regional development. In this study, based on a comprehensive understanding of the concept of industrial clusters, a cultural industry cluster level index system, was devised. It leverages data from 62 cities in the Yellow River Basin, from 2005 to 2020, as samples. This study calculated cultural industry cluster levels in these urban regions, investigated the spatial correlation of these cluster levels using Moran’s I, and constructed different spatial weight matrices. The spatial Durbin model was employed to explore the influencing factors behind cultural industry cluster spillover effects and analyze the pathways of these influencing factors. The study results are as follows: (1) Between 2005 and 2020, the average index of cultural industry clusters in the Yellow River Basin increased from 0.07 to 0.21. However, this distribution was extremely uneven, showing a development pattern of “high in the east and low in the west.” The distribution of cities within different cluster levels showed a “positive triangle” pattern. (2) There is a noticeable negative spatial spillover effect on the cultural industry cluster levels in the Yellow River Basin, and the presence of a “Matthew effect” is very severe. (3) The decomposition of the spatial spillover effect reveals that the selected influencing factors have negative spillover effects on the cultural industry cluster levels in neighboring cities. (4) The spatial spillover effect shows a notable correlation with spatial distance. The positive spatial spillover effect is strongest when the geographical distance reaches 500 km, and it gradually diminishes as distances exceed 850 km, exhibiting an inverted “U” shape trend. Finally, the study uncovered a distinct “cluster shadow” phenomenon among cities in the Yellow River Basin, with a weak positive spillover effect. Therefore, to accelerate the development of cultural industry clusters in the Yellow River Basin, improve regional competitiveness, and narrow regional development gaps, establishing the theoretical concept of synergistic development is crucial. Leveraging opportunities for urban revitalization and adopting context-specific development modes according to the development of cultural industry clusters can considerably contribute to the high-quality development of the Yellow River Basin.

Key words: Yellow River Basin, cultural industry, cluster level, influencing factors, spatial spillover effect

鲁滋道, 宋婉怡, 王钺, 潘海泽, 孟小琳, 闫玉强. 黄河流域文化产业集群时空格局与空间溢出效应研究[J]. 干旱区地理, 2023, 46(11): 1927-1937.

LU Zidao, SONG Wanyi, WANG Yue, PAN Haize, MENG Xiaolin, YAN Yuqiang. Spatiotemporal pattern and spatial spillover effect of cultural industry clusters in the Yellow River Basin[J]. Arid Land Geography, 2023, 46(11): 1927-1937.

图/表 9

表1

表2

文化产业集群空间溢出效应影响因素"

一级指标	二级指标	指标变量	单位	指标含义	权重
物质空间环境	道路面积	$R A$	10⁴ m²	基础设施水平	0.1247
	建成区绿化覆盖率	$G C$	%	生态环境质量	0.0178
	城市夜间灯光总和	$D M S P$	-	城市发展水平	0.0804
	文化资源得分	$C H S$	-	文化资源禀赋	0.0919
社会经济环境	互联网用户数量	$I U$	10⁴户	现代化水平及知识交流便捷程度	0.1491
	人均国内生产总值	$R G D P$	元	劳动生产率	0.0852
	第三产业占GDP比重	$I S E$	%	产业结构	0.0214
	普通高等学校教师数量	$N T U$	名	劳动力素质	0.2765
	公共图书馆藏书量	$B C$	10⁴册	城市文化氛围	0.1526

表2

图1

图2

表3

黄河流域文化产业集群莫兰指数（Moran’s I）"

年份	$M o r a n ’ s I g l o b a l$	$B - M o r a n ’ s I g l o b a l$									$M o r a n ’ s I l o c a l$
年份	$M o r a n ’ s I g l o b a l$	RA	GC	DMSP	CHS	IU	RGDP	ISE	NTU	BC	$M o r a n ’ s I l o c a l$
2005	-0.071	-0.167	-0.147	-0.101	-0.124	-0.142	0.005	-0.034	-0.158	-0.174	-0.070
2010	-0.116	-0.112	0.072	0.020	-0.026	-0.115	0.089	0.004	-0.103	-0.121	-0.190
2015	-0.194	-0.057	-0.015	-0.056	-0.068	-0.116	0.060	-0.082	-0.082	-0.101	-0.262
2020	-0.239	-0.004	0.104	-0.092	0.012	-0.051	-0.018	-0.050	-0.050	-0.028	-0.273

表3

图3

表4

黄河流域文化产业集群影响因素空间杜宾模型（SDM）回归结果"

变量	系数	$t$ 统计量	变量	系数	$t$ 统计量
$R A$	-0.467^*	0.240	$W × R A$	-4.204^***	1.474
$G C$	2.004^***	0.696	$W × G C$	-5.239	5.170
$D M S P$	-0.026	0.207	$W × D M S P$	-3.759^***	1.352
$C H S$	0.613^***	0.085	$W × C H S$	-0.181	1.064
$I U$	0.893^**	0.347	$W × I U$	-0.082	1.098
$R G D P$	2.166^***	0.191	$W × R G D P$	5.412^***	0.893
$I S E$	6.165^***	0.573	$W × I S E$	-0.115	3.150
$N T U$	0.033	0.573	$W × N T U$	0.911^*	0.485
$B C$	2.065^***	0.087	$W × B C$	-0.976	1.032
$ρ$	-0.240^***	0.190	$L R S p a t i a l E r r o r$	137.520	-
$R 2$	0.666	-	$W a l d t e s t$	94.060	-
$L o g - l i k e l i h o o d$	1667.780	-	$H a u s m a n t e s t$	59.830	-
$L R S p a t i a l L a g$	154.980	-

表4

表5

图4

参考文献 36

[1]	陈汉欣. 中国文化创意产业的发展现状与前瞻[J]. 经济地理, 2008, 28(5): 728-733.
	[ Chen Hanxin. Chinese culture creative industry: Developmental actuality and prospect[J]. Economic Geography, 2008, 28(5): 728-733. ]
[2]	陶金, 罗守贵. 基于不同区域层级的文化产业集聚研究[J]. 地理研究, 2019, 38(9): 2239-2253. doi: 10.11821/dlyj020180370
	[ Tao Jin, Luo Shougui. Agglomeration economies in cultural industries: A comparison at the city and province level[J]. Geographical Research, 2019, 38(9): 2239-2253. ] doi: 10.11821/dlyj020180370
[3]	刘建华, 黄亮朝, 左其亭. 黄河流域生态保护和高质量发展协同推进准则及量化研究[J]. 人民黄河, 2020, 42(9): 26-33.
	[ Liu Jianhua, Huang Liangchao, Zuo Qiting. Synergetic promotion criteria and quantitative study of ecological protection and high quality development of the Yellow River Basin[J]. Yellow River, 2020, 42(9): 26-33. ]
[4]	周灿, 曾刚. 经济地理学视角下产业集群研究进展与展望[J]. 经济地理, 2018, 38(1): 11-19.
	[ Zhou Can, Zeng Gang. Progress and prospect of international research on industrial cluster: A perspective from economic geography[J]. Economic Geography, 2018, 38(1): 11-19. ]
[5]	胡慧源, 李叶. 长三角文化产业集群一体化发展: 现实瓶颈、动力机制与推进路径[J]. 现代经济探讨, 2022(9): 117-123.
	[ Hu Huiyuan, Li Ye. The integrated development of cultural industry clusters in the Yangtze River delta: Realistic bottleneck, dynamic mechanism and promotion path[J]. Modern Economic Research, 2022(9): 117-123. ]
[6]	杨永春, 穆焱杰, 张薇. 黄河流域高质量发展的基本条件与核心策略[J]. 资源科学, 2020, 42(3): 409-423. doi: 10.18402/resci.2020.03.01
	[ Yang Yongchuan, Mu Yanjie, Zhang Wei. Basic conditions and core strategies of high quality development in the Yellow River Basin[J]. Resources Science, 2020, 42(3): 409-423. ] doi: 10.18402/resci.2020.03.01
[7]	Porter M E. Clusters and the new economics of competition[M]. Boston: Harvard Business Review, 1998: 77-90.
[8]	陈羽洁, 赵红岩, 郑万腾. 不同集聚模式对产业发展阶段创新效率的影响——基于我国创意产业的分析[J]. 广东财经大学学报, 2020, 35(5): 58-68.
	[ Chen Yujie, Zhao Hongyan, Zheng Wanteng. The impact of different agglomeration modes on innovation efficiency in industrial development stage: Based on the analysis of creative industries in China[J]. Journal of Guangdong University of Finance & Economics, 2020, 35(5): 58-68. ]
[9]	Agovino M, Rapposelli A. Agglomeration externalities and technical efficiency in Italian regions[J]. Quality & Quantity, 2015, 49: 1803-1822.
[10]	卢飞, 刘明辉, 孙元元. 集聚、全要素生产率与产业增长[J]. 科学学研究, 2018, 36(9): 1575-1584, 1614.
	[ Lu Fei, Liu Minghui, Sun Yuanyuan. Agglomeration, TFP and industrial growth[J]. Studies in Science of Science, 2018, 36(9): 1575-1584, 1614. ]
[11]	郭新茹, 顾江, 陈天宇. 文化产业集聚、空间溢出与区域创新能力[J]. 江海学刊, 2019(6): 77-83.
	[ Guo Xinru, Gu Jiang, Chen Tianyu. Cultural industry agglomeration, spatial spillover, and regional innovation capability[J]. Jianghai Academic Journal, 2019(6): 77-83. ]
[12]	刘雅娇, 胡静波. 产业集聚、市场竞争性与劳动生产率——基于高技术产业面板数据的实证分析[J]. 产经评论, 2018, 9(1): 40-48.
	[ Liu Yajiao, Hu Jingbo. Industrial agglomeration, market competition and labor productivity: Based on the panel data of high technology industry[J]. Industrial Economic Review, 2018, 9(1): 40-48. ]
[13]	黄辰洋, 吕洪渠, 程文思. 产业集聚与环境依赖对文化产业效率的影响[J]. 华东经济管理, 2022, 36(1): 99-107.
	[ Huang Chenyang, Lü Hongqu, Cheng Wensi. The impact of industrial agglomeration and environmental dependence on the efficiency of cultural industry[J]. East China Economic Management, 2022, 36(1): 99-107. ]
[14]	Branzanti C. Creative clusters and district economies: Towards a taxonomy to interpret the phenomenon[J]. European Planning Studies, 2015, 23(7): 1401-1418. doi: 10.1080/09654313.2014.935930
[15]	Scott A J. Cultural products industries and urban economic development: Prospects for growth and market contestation in global context[J]. Urban Affairs Review, 2005, 39(4): 461-490. doi: 10.1177/1078087403261256
[16]	Krugman P. Increasing returns and economic geography[J]. Journal of Political Economy, 1991, 99(3): 483-499. doi: 10.1086/261763
[17]	卫志民. 文化创意产业发展的现状、制约与突破——一项基于北京文化创意产业发展的研究[J]. 河南大学学报(社会科学版), 2017, 57(2): 15-21.
	[ Wei Zhimin. The present situation, restriction and breakthrough of Beijing cultural and creative industry[J]. Journal of Henan University (Social Sciences Edition), 2017, 57(2): 15-21. ]
[18]	陈天宇, 解学芳. 文化产业集聚提升了区域创新能力吗?——基于空间计量模型的实证检验[J]. 经济问题探索, 2023(3): 111-125.
	[ Chen Tianyu, Xie Xuefang. Has agglomeration of cultural industries enhance regional innovation capability?: An empirical test based on spatial econometric model[J]. Inquiry into Economic Issues, 2023(3): 111-125. ]
[19]	贺小荣, 章雨之, 刘源. 长江经济带文化产业空间集聚与溢出效应研究[J]. 文化产业研究, 2022(1): 124-141.
	[ He Xiaorong, Zhang Yuzhi, Liu Yuan. Study on spatial agglomeration and spillover effects of culture industries in the Yangtze River Economic belt[J]. Cultural Industry Research, 2022(1): 124-141. ]
[20]	雷宏振, 潘龙梅. 中国文化产业空间集聚特征研究[J]. 东岳论丛, 2011, 32(8): 114-117.
	[ Lei Hongzhen, Pan Longmei. Research on the spatial agglomeration characteristics of China’s cultural industry[J]. Dongyue Tribune, 2011, 32(8): 114-117. ]
[21]	陈红霞, 吴姝雅. 文化创意产业的空间集聚特征及其区际差异比较——基于地级市的实证研究[J]. 城市发展研究, 2018, 25(7): 25-33.
	[ Chen Hongxia, Wu Zhuya. Spatial agglomeration characteristics and regional difference of cultural and creative industries: An empirical study based on prefecture-level cities[J]. Urban Development Studies, 2018, 25(7): 25-33. ]
[22]	任英华, 沈凯娇, 游万海. 不同空间权重矩阵下文化产业集聚机制和溢出效应——基于2004—2011年省际面板数据的实证[J]. 统计与信息论坛, 2015, 30(2): 82-87.
	[ Ren Yinghua, Chen Kaijiao, You Wanhai. Cultural industry agglomeration mechanism and spillover effect under different spatial weight matrix: An empirical study on provincial spatial panel data 2004—2011 of China[J]. Journal of Statistics and Information, 2015, 30(2): 82-87. ]
[23]	乔彬, 张蕊, 雷春. 高铁效应、生产性服务业集聚与制造业升级[J]. 经济评论, 2019(6): 80-96.
	[ Qiao Bin, Zhang Rui, Lei Chun. The effect of high speed railway, agglomeration of productive service industry and upgrading of manufacturing industry[J]. Economic Review, 2019(6): 80-96. ]
[24]	田小波, 胡静, 贾垚焱, 等. 高质量发展阶段旅游业发展水平空间分异成因探测——基于因素分解的黄河流域实证[J]. 干旱区地理, 2023, 46(3): 460-470.
	[ Tian Xiaobo, Hu Jing, Jia Yaoyan, et al. Exploring the causes of spatial differentiation of tourism development level in the high-quality development stage: Empirical evidence of Yellow River Basin based on factor decomposition[J]. Arid Land Geography, 2023, 46(3): 460-470. ]
[25]	许卫华, 张力仁, 崔晶晶, 等. 黄河流域现代产业体系耦合协同水平测度及其时空演变[J]. 地域研究与开发, 2023, 42(2): 1-6, 13.
	[ Xu Weihua, Zhang Liren, Cui Jingjing, et al. Measurement and spatio-temporal evolution of coupling coordination of modern industrial system in the Yellow River Basin[J]. Areal Research and Development, 2023, 42(2): 1-6, 13. ]
[26]	宓泽锋, 周灿, 尚勇敏, 等. 本地知识基础对新兴产业创新集群形成的影响——以中国燃料电池产业为例[J]. 地理研究, 2020, 39(7): 1478-1489. doi: 10.11821/dlyj020190595
	[ Mi Zefeng, Zhou Can, Shang Yongmin, et al. The impact of local knowledge base on the formation of innovation clusters in emerging industries: The case study of China’s fuel cell industry[J]. Geographical Research, 2020, 39(7): 1478-1489. ] doi: 10.11821/dlyj020190595
[27]	苏丹妮, 盛斌, 邵朝对, 等. 全球价值链、本地化产业集聚与企业生产率的互动效应[J]. 经济研究, 2020, 55(3): 100-115.
	[ Su Danni, Sheng Bin, Shao Chaodui, et al. Global value chain, industry agglomeration and firm productivity’s interactive effect[J]. Economic Research Journal, 2020, 55(3): 100-115. ]
[28]	谷昊鑫, 秦伟山, 赵明明, 等. 黄河流域旅游经济与生态环境协调发展时空演变及影响因素探究[J]. 干旱区地理, 2022, 45(2): 628-638.
	[ Gu Haoxin, Qin Weishan, Zhao Mingming, et al. Spatial and temporal evolution and influencing factors of coordinated development of tourism economy and ecological environment in the Yellow River Basin[J]. Arid Land Geography, 2022, 45(2): 628-638. ]
[29]	莫惠斌, 罗珂, 王少剑, 等. 广州市中心城区餐饮店空间分异与机制差异研究——基于传统店与外卖店的对比[J]. 地理研究, 2022, 41(12): 3318-3334. doi: 10.11821/dlyj020220200
	[ Mo Huibin, Luo Ke, Wang Shaojian, et al. Spatial heterogenicity and mechanism difference of restaurant in the central urban area of Guangzhou: A comparison between traditional restaurant and take-out restaurant[J]. Geographical Research, 2022, 41(12): 3318-3334. ] doi: 10.11821/dlyj020220200
[30]	杨顺华. 基于空间回归模型的土壤有机质区域分布特征研究[D]. 武汉: 华中农业大学, 2016.
	[ Yang Shunhua. Study on the regional distribution of soil organic matter baesd on spatial regression model[D]. Wuhan: Huazhong Agricultural University, 2016. ]
[31]	陶长琪, 杨海文. 空间计量模型选择及其模拟分析[J]. 统计研究, 2014, 31(8): 88-96.
	[ Tao Changqi, Yang Haiwen. Spatial econometric model selection and its simulation analysis[J]. Statistical Research, 2014, 31(8): 88-96. ]
[32]	吴子豪, 童滋雨. 城市形态空间格局与城市热环境关联性研究——以南京市为例[J]. 南京师大学报(自然科学版), 2022, 45(2): 16-25.
	[ Wu Zihao, Tong Ziyu. Study on the correlation between the spatial patterns of urban form and the urban thermal environment: A case study of Nanjing[J]. Journal of Nanjing Normal University (Natural Science Edition), 2022, 45(2): 16-25. ]
[33]	李婧, 谭清美, 白俊红. 中国区域创新生产的空间计量分析——基于静态与动态空间面板模型的实证研究[J]. 管理世界, 2010(7): 43-55, 65.
	[ Li Jing, Tan Qingmei, Bai Junhong. Spatial econometric analysis of China’s regional innovative production: An empirical study based on static and dynamic spatial panel models[J]. Journal of Management World, 2010(7): 43-55, 65. ]
[34]	Henderson V. Medium size cities[J]. Regional Science and Urban Economics, 1997, 27(6): 583-612. doi: 10.1016/S0166-0462(96)02169-2
[35]	LeSage J P, Fischer M M. Spatial growth regressions: Model specification, estimation and interpretation[J]. Spatial Economic Analysis, 2008, 3(3): 275-304. doi: 10.1080/17421770802353758
[36]	谢倩芸, 蔡翼飞. “十四五”时期我国教育人力资本供需形势分析[J]. 中国人力资源开发, 2020, 37(12): 17-33.
	[ Xie Qianyun, Cai Yifei. Analysis of China’s education human capital supply and demand in the 14^th Five-Year Plan Period[J]. Human Resources Development of China, 2020, 37(12): 17-33. ]

维度	具体指标	指标变量	权重
文化产业集群规模	文化产业主体数量	N	1/3
文化产业集群联系度	文化产业企业平均最近邻指数	ANN	1/3
文化产业集群专业化程度	区位熵	LQ	1/3

解释变量	直接效应（t统计量）	间接效应（t统计量）
RA	0.436^*（0.252）	-3.403^**（1.472）
GC	2.014^***（0.696）	-4.715^**（4.100）
DMSP	0.004（0.203）	-3.000^***（0.993）
CHS	0.620^***（0.084）	-0.319（0.870）
IU	0.883^**（0.346）	-0.226（0.994）
RGDP	2.129^***（0.175）	3.973^***（1.085）
ISE	6.173^***（0.565）	-1.332^**（2.521）
NTU	0.023（0.092）	0.759^**（0.347）
BC	2.086^***（0.184）	-1.208（0.804）