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| The Construction Path of Smart Services Enabling Innovative Urban Agglomeration: from the Perspective of Physical and Virtual Industrial Agglomeration |
| Chen Yan1,Zhang Liyezi1,Song Wenbin2 |
| (1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China; 2. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China) |
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Abstract Nowadays, China's urbanization development has been changing from decentralized development model of small and medium-sized cities to the development model of innovative urban agglomeration centered on core cities. The smart service capabilities based on artificial intelligence technology have become the new driving force for cities to gain new regional competitive advantages. However, the overall innovation level of China's urban agglomeration is facing many bottlenecks such as the low level of investment, technology innovation and talents, which seriously restrict the coordinated development of regions. In this context, it is particularly urgent to explore the optimal path for the integrated development of urban agglomerations oriented to the innovation-driven development strategy. At the same time, the new generation of information technology has broken the limitations of physical space and promotes the transformation of industrial agglomeration from geographical agglomeration model to virtual agglomeration model centered on real-time data and information exchange, forming the dual industrial agglomeration model in which virtual agglomeration and geographical agglomeration coexist. Existing research has confirmed the important role of geographical agglomeration and virtual agglomeration in promoting regional innovation. However, most studies only examine the impact from a single perspective, and explore the impact of smart services on regional innovation without the consideration of the differences between physical agglomeration and virtual agglomeration. Therefore, this paper builds the theoretical framework from the perspective of dual industrial agglomeration to explore the construction path of smart service enabling innovative urban agglomerations and analyze the differential impact mechanism of dual industrial agglomeration on the relationship between smart services and regional innovation.#br#This paper selected the panel data of Chinese 271 cities from 2011 to 2019 as the sample and constructed a Chinese Regional Smart Service Development Index based on the three-dimensional data sources of regions, industries and enterprises. Then it empirically examined the impact of smart services on regional innovation performance as well as the underlying mechanism by employing a two-way fixed effects model.#br#The results show that smart services have a significant positive impact on the breadth and depth of regional innovation performance. In addition, affected by network externalities, smart services have a U-shaped nonlinear effect on regional innovation quantity, while a nonlinear effect on regional innovation quality which decreases first and then increases by marginal effect. The dual industrial agglomeration, physical agglomeration and virtual agglomeration play a mediating role in the relationship between regional smart services and regional innovation performance. The influence of smart services on regional innovation performance is heterogeneous among different regions. Specifically, the effect of smart services on regional innovation performance is significant in the eastern region, central cities and urban agglomeration of Beijing-Tianjin-Hebei, Yangtze River Delta, Chengdu-Chongqing and middle Reaches of Yangtze River, while it is not significant in Guanzhong Plain Urban agglomeration.#br#This paper makes the following theoretical contributions. First, it makes a comprehensive measurement of the development of smart services from the city level based on the three-dimensional data sources of regions, industries and enterprises. Compared with previous studies, this method can measure the regional differences of smart services more accurately. Second, this paper reveals the nonlinear dynamic relationship between the smart services and regional innovation, which providing theoretical support for the construction path of smart services enabling the innovative urban agglomerations. Third, different from the single perspective of previous studies on physical agglomeration and virtual agglomeration, this paper builds the dual paths of smart service enabling regional innovation in the digital age by introducing the concept of dual industrial agglomeration. This results provide guidance for regional transformation and upgrading from traditional factor input to the intelligent, high-end, and virtualized innovative industrial clusters. This paper is also of great significance for promoting China's regional innovation to improve quality and efficiency.#br#
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Received: 15 November 2021
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| [1] 方创琳. 城市群发展能级的提升路径[J]. 国家治理,2018，5(48):3-10. [2] BRYNJOLFSSON E , HITT L M , KIM H H. Strength in numbers: how does data-driven decisionmaking affect firm performance [EB/OL]. http://ssrn. com/abstract:1819486. [3] GRAETZ G, MICHAELS G. Robots at work[J]. Review of Economics and Statistics,2018,100: 753-768. [4] 韩民春,乔刚. 工业机器人对中国区域经济的异质性影响研究——基于新结构经济学的视角[J]. 技术经济,2020,39(8):85-94. [5] 钞小静,周文慧. 人工智能对劳动收入份额的影响研究——基于技能偏向性视角的理论阐释与实证检验[J]. 经济与管理研究,2021,42(2):82-94. [6] 钞小静,薛志欣,孙艺鸣. 新型数字基础设施如何影响对外贸易升级——来自中国地级及以上城市的经验证据[J]. 经济科学,2020,42(3):46-59. [7] 刘亮,刘军,李廉水,等. 智能化发展能促进中国全球价值链攀升吗[J]. 科学学研究,2021,39(4):604-613. [8] 聂秀华,江萍,郑晓佳,等. 数字金融与区域技术创新水平研究[J]. 金融研究,2021，64(3):132-150. [9] KRUGMAN P. Increasing returns and economic geography [J]. Journal of Political Economy,1991,99(3):483-499. [10] 王如玉,梁琦,李广乾. 虚拟集聚:新一代信息技术与实体经济深度融合的空间组织新形态[J]. 管理世界,2018,34(2):13-21. [11] 陈文涛,罗震东. 互联网时代的产业分工与集聚——基于淘宝村与专业市场互动机制的空间经济学分析[J]. 南京大学学报(哲学·人文科学·社会科学),2020,57(2):65-78，158-159. [12] HOOVER E M. Location theory and the shoe and leather industries[M]. Cambridge: Harvard University Press, 1937. [13] ARROW K J. The economic implications of learning by doing[M]//Readings in the theory of growth. London: Palgrave Macmillan, 1971: 131-149. [14] ROMER P M. Endogenous technological change[J]. Journal of Political Economy, 1990, 98(5, Part 2): S71-S102. [15] GLAESER E L ,KALLAL H D ,SCHEINKMAN J A , et al. Growth in cities[J]. Journal of Political Economy,1992, 100(6):1126-1152. [16] JACOBS J. The economies of cities[M]. London: Jonathan Cape,1970. [17] BEAUDRY C ,SCHIFFAUEROVA A. Who's right, marshall or jacobs? the localization versus urbanization debate[J]. Research Policy, 2009, 38(2):318-337. [18] STERNBERG R R. Special issue on causes and effects of new business creation:empirical evidence from the global entrepreneurship monitor (GEM)/Entrepreneurship: the role of clusters theoretical perspectives and empirical evidence from Germany[J]. Small Business Economics, 2005, 24(3):267-292. [19] KOEN, FRENKEN, FRANK, et al. Related variety, unrelated variety and regional economic growth[J]. Regional Studies, 2007, 41(5): 685-697. [20] 张睿倩,刘昊倬,谢一臻,等. 虚拟集聚型网络关系、制度逻辑差异与数字赋能型企业成长——基于云计算企业的研究[J]. 科研管理,2021,42(8):92-101. [21] NORTH D C. Institutions, institutional change, and economic performance [M]. Cambridge University Press, 1990. [22] 陈岩,张平. 数字全球化的内涵、特征及发展趋势[J]. 人民论坛,2021,30(13):26-29. [23] 龚达宁,王雪梅,曹磊. 全球5G商用发展及趋势展望[J]. 信息通信技术与政策,2020(12):7-10. [24] PORTER ME，HEPPELMANN JE. How smart, connected products are transforming competition[J]. Harvard Business Review, 2014, 92(11) : 64-88. [25] 张彩江,覃婧,周宇亮. 技术扩散效应下产业集聚对区域创新的影响研究——基于两阶段价值链视角[J]. 科学学与科学技术管理,2017,38(12):124-132. [26] ACEMOGLU D. Training and innovation in an imperfect labor market[J]. Review of Economic Studies, 1997, 64(3):445-464. [27] 孙早,席建成. 产业互补、协调失灵与企业的关联创新[J]. 当代经济科学,2013,35(2):43-51,125-126. [28] HANSEN B E. Threshold effects in non-dynamic panels: estimation, testing, and inference[J]. Journal of Econometrics, 1999, 93(2):345-368. [29] 柳卸林,杨博旭. 多元化还是专业化?产业集聚对区域创新绩效的影响机制研究[J]. 中国软科学,2020(9):141-161. [30] LAFUENTE E , VAILLANT Y , VENDRELL-HERRERO F. Territorial servitization: exploring the virtuous circle connecting knowledge-intensive services and new manufacturing businesses[J]. International Journal of Production Economics, 2017, 192:19-28. [31] LIU Y, LATTEMANN C, XING Y, et al. The emergence of collaborative partnerships between knowledge-intensive business service (KIBS) and product companies: the case of Bremen, Germany[J]. Regional Studies, 2019, 53(3): 376-387. [32] 陈建军,刘月,邹苗苗. 产业协同集聚下的城市生产效率增进——基于融合创新与发展动力转换背景[J]. 浙江大学学报(人文社会科学版),2016,46(3):150-163. [33] 肖仁桥,沈佳佳,钱丽. 数字化水平对企业新产品开发绩效的影响——双元创新能力的中介作用[J]. 科技进步与对策,2021,38(24):106-115. [34] 方创琳. 新发展格局下的中国城市群与都市圈建设[J]. 经济地理,2021,41(4):1-7. [35] 黄群慧,余泳泽,张松林. 互联网发展与制造业生产率提升：内在机制与中国经验[J]. 中国工业经济,2019,37(8):5-23. [36] NUNN N， N QIAN. U. S. Food aid and civil conflict [J]. American Economic Review，2014，104(6):1630-1666. |
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