Which network effectively supports urban economic growth? Evidence from China

References

• Arbex, M., Caetano, S., & O’Dea, D. (2016). The implications of labor market network for business cycles. Economics Letters, 144, 37–40.
   Web of Science ®Google Scholar
• Bianchi, C., Galaso, P., & Palomeque, S. (2021). The trade-offs of brokerage in inter-city innovation networks. Regional Studies, 57, 225–238. doi:10.1080/00343404.2021.1973664
   Web of Science ®Google Scholar
• Boheim, R., & Taylor, M. (2007). From the dark end of the street to the bright side of the road? The wage returns to migration in Britain. Labour Economics, 14, 99–117.
   Web of Science ®Google Scholar
• Cao, Z., Derudder, B., & Dai, L. (2022). Buzz-and-pipeline’ dynamics in Chinese science: The impact of interurban collaboration linkages on cities’ innovation capacity. Regional Studies, 56(2), 290–306.
   Web of Science ®Google Scholar
• Capello, R. (2000). The city network paradigm: Measuring urban network externalities. Urban Studies, 37(11), 1925–1945.
   Web of Science ®Google Scholar
• Castells, M. (1996). The rise of the network society. Oxford: Blackwell.
   Google Scholar
• Chen, J., Su, Y. S., de Jong, J. P. J., & Hippel, E. (2020). Household sector innovation in China: Impacts of income and motivation. Research Policy, 49(4), 103931.
   Web of Science ®Google Scholar
• Cheng, Z. (2016). The spatial correlation and interaction between manufacturing agglomeration and environmental pollution. Ecological Indicators, 61, 1024–1032.
   Web of Science ®Google Scholar
• Cheong, T. S., Li, J., & Cheng, W. W. (2021). Distribution dynamics of China’s regional housing price disparity. International Journal of Urban Sciences, 25(1), 51–70.
   Web of Science ®Google Scholar
• Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Cambridge, MA: Harvard Business School Press.
   Google Scholar
• Conroy, T., & Weiler, S. (2019). Local and social: Entrepreneurs, information network effects, and economic growth. The Annals of Regional Science, 62(3), 681–713.
   Web of Science ®Google Scholar
• Costales, E. (2022). Identifying sources of innovation: Building a conceptual framework of the Smart City through a social innovation perspective. Cities, 120, 103459.
   Web of Science ®Google Scholar
• Costantini, V., & Crespi, F. (2008). Environmental regulation and the export dynamics of energy technologies. Ecological Economics, 66(2-3), 447–460.
   Web of Science ®Google Scholar
• Dai, L., Derudder, B., Cao, Z., & Ji, Y. (2022). Examining the evolving structures of intercity knowledge networks: The case of scientific collaboration in China. International Journal of Urban Sciences, 27, 371–389. doi:10.1080/12265934.2022.2042365
   Web of Science ®Google Scholar
• Davis, D., & Weinstein, D. (1996). Does economic geography matter for international specialization? NBER Working Paper, 5706.
   Google Scholar
• Deng, Y. (2021). Agglomeration of technology innovation network of new energy automobile industry based on IoT and artificial intelligence. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-021-03102-2.
   Web of Science ®Google Scholar
• Doh, S., & McNeely, C. L. (2011). A multi-dimensional perspective on social capital and economic development: An exploratory analysis. The Annals of Regional Science, 49(3), 821–843.
   Web of Science ®Google Scholar
• D’Oliveira, D., Leigh, R., & Campanaro, R. (2000). Below the Waterline of Public Visibility: Roundtable on Volunteerism and Social Development.
   Google Scholar
• Fainshmidt, S., Witt, M. A., Aguilera, R. V., & Verbeke, A. (2020). The contributions of qualitative comparative analysis (QCA) to international business research. Journal of International Business Studies, 51(7), 455–466.
   Google Scholar
• Frambach, R. T., Fiss, P. C., & Ingenbleek, P. T. (2016). How important is customer orientation for firm performance? A fuzzy set analysis of orientations, strategies, and environments. Journal of Business Research, 69, 1428–1436.
   Web of Science ®Google Scholar
• Fritsch, M., & Kauffeld-Monz, M. (2008). The impact of network structure on knowledge transfer: An application of social network analysis in the context of regional innovation networks. The Annals of Regional Science, 44(1), 21–38.
   Web of Science ®Google Scholar
• Fuellhart, K., Dai, L., Grubesic, T., & Derudder, B. (2021). The U.S. essential air service program and SARS C0V-2, 2019–2020. Journal of Transport Geography, 96, 103169.
   Web of Science ®Google Scholar
• Ge, F., Chen, W., Zeng, Y., & Li, J. (2021). The nexus between urbanization and traffic accessibility in the middle reaches of the Yangtze River urban agglomerations, China. International Journal of Environmental Research and Public Health, 18(7), 3828.
   PubMed Web of Science ®Google Scholar
• Hanckel, B., Petticrew, M., Thomas, J., & Green, J. (2021). The use of Qualitative Comparative Analysis (QCA) to address causality in complex systems: A systematic review of research on public health interventions. BMC Public Health, 21(1), 877.
   PubMed Web of Science ®Google Scholar
• He, Z., Chen, Z., & Feng, X. (2022). Different types of industrial agglomeration and green total factor productivity in China: Do institutional and policy characteristics of cities make a difference? Environmental Sciences Europe, 34(1), 64.
   Web of Science ®Google Scholar
• Jin, P., Mangla, S. K., & Song, M. (2022). The power of innovation diffusion: How patent transfer affects urban innovation quality. Journal of Business Research, 145, 414–425.
   Web of Science ®Google Scholar
• Krings, G., Calabrese, F., Ratti, C., & Blondel, V. D. (2009). Urban gravity: A model for inter-city telecommunication flows. Journal of Statistical Mechanics: Theory and Experiment, 2009(07), L07003.
   Web of Science ®Google Scholar
• Kuchler, T., Li, Y., Peng, L., Stroebel, J., & Zhou, D. (2022). Social proximity to capital: Implications for investors and firms. The Review of Financial Studies, 35(6), 2743–2789.
   Web of Science ®Google Scholar
• Li, B., Gao, S., Liang, Y., Kang, Y., Prestby, T., Gao, Y., & Xiao, R. (2020). Estimation of regional economic development indicator from transportation network analytics. Scientific Reports, 10(1), 2647.
   PubMed Web of Science ®Google Scholar
• Liu, S., Song, L., & Huang, Y. (2022). Measurement and convergence test of green economic efficiency of the Yangtze River economic belt under different spatial network correlation. Frontiers in Environmental Science, 10, 828207. doi:10.3389/fenvs.2022.828207
   Web of Science ®Google Scholar
• Liu, X., Dai, L., & Derudder, B. (2017). Spatial inequality in the Southeast Asian intercity transport network. Geographical Review, 107(2), 317–335.
   Web of Science ®Google Scholar
• Loury, L. D. (2006). Some contacts are more equal than others: Informal networks, job tenure, and wages. Journal of Labor Economics, 24(2), 299–318.
   Web of Science ®Google Scholar
• Mancini, S., & González, J. L. C. (2021). Role of technology transfer, innovation strategy and network: A conceptual model of innovation network to facilitate the internationalization process of SMEs. Technology and Investment, 12(02), 82–128.
   Google Scholar
• Martinez-Zarzoso, I., & Nowak-Lehmann, F. (2003). Augmented gravity model: An empirical application to Mercosur-European Union trade flows. Journal of Applied Economics, 6(2), 291–316.
   Google Scholar
• Misangyi, V. F., Greckhamer, T., Furnari, S., Fiss, P. C., Crilly, D., & Aguilera, R. (2017). Embracing causal complexity: The emergence of a neo-configurational perspective. Journal of Management, 43(1), 255–282.
   Web of Science ®Google Scholar
• Muller, E., & Peres, R. (2019). The effect of social networks structure on innovation performance: A review and directions for research. International Journal of Research in Marketing, 36(1), 3–19.
   Web of Science ®Google Scholar
• Opsahl, T., & Panzarasa, P. (2009). Clustering in weighted networks. Social Networks, 31(2), 155–163.
   Web of Science ®Google Scholar
• Pan, S., & Chong, Z. (2023). Effects of FDI on trade among countries along the belt and road: A network perspective. The Journal of International Trade & Economic Development, 32(1), 84–103.
   Web of Science ®Google Scholar
• Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in information systems and marketing. International Journal of Information Management, 58, 102310.
   Web of Science ®Google Scholar
• Peng, J., Zhao, S., Liu, Y., & Tian, L. (2016). Identifying the urban-rural fringe using wavelet transform and kernel density estimation: A case study in Beijing City, China. Environmental Modelling & Software, 83, 286–302.
   Web of Science ®Google Scholar
• Pflieger, G., & Rozenblat, C. (2010). Urban networks and network theory: The city as the connector of multiple networks. Urban Studies, 47(13), 2723–2735.
   Web of Science ®Google Scholar
• Ragin, C. C. (1987). The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley: University of California Press.
   Google Scholar
• Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond. Chicago, IL: University of Chicago Press.
   Google Scholar
• Ragin, C. C. (2009). Redesigning social inquiry: Fuzzy sets and beyond. Social Forces, 88(4), 1936–1938.
   Web of Science ®Google Scholar
• Rowley, T., Behrens, D., & Krackhardt, D. (2000). Redundant governance structures: An analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Management Journal, 21(3), 369–386.
   Web of Science ®Google Scholar
• Sajedianfard, N., Hadian, E., Samadi, A. H., Dehghan Shabani, Z., Sarkar, S., & Robinson, P. A. (2021). Quantitative analysis of trade networks: Data and robustness. Applied Network Science, 6(1), 46.
   Google Scholar
• Shrestha, H. K., & Upadhyay, M. P. (2004). Political economy of regional trading arrangements in South Asia. Journal of Economic Integration, 19, 427–446.
   Google Scholar
• Simmel, G. (1917). Grundfragen der Soziologie [Fundamental questions of sociology]. Berlin: Göschen.
   Google Scholar
• Sun, Y. (2021). Case based models of the relationship between consumer resistance to innovation and customer churn. Journal of Retailing and Consumer Services, 61, 102530.
   Web of Science ®Google Scholar
• Tandelova, O. M., & Dzhioeva, O. O. (2021). The information economy as part of the information management resource society. CEUR Workshop Proceedings, 2914, 472–478.
   Google Scholar
• Ter Wal, A. L. J., & Boschma, R. A. (2008). Applying social network analysis in economic geography: Framing some key analytic issues. The Annals of Regional Science, 43(3), 739–756.
   Web of Science ®Google Scholar
• Thiem, A., Baumgartner, M., & Bol, D. (2016). A correction of three misunderstandings between configurational comparativists and regression analysts. Comparative Political Studies, 49, 742–774.
   Web of Science ®Google Scholar
• Thompson, C. A., Saxberg, K., Lega, J., Tong, D., & Brown, H. E. (2019). A cumulative gravity model for inter-urban spatial interaction at different scales. Journal of Transport Geography, 79, 102461.
   Web of Science ®Google Scholar
• Tinbergen, J. (1962). Shaping the world economy. New York: The Twentieth Century Fund.
   Google Scholar
• Tripathi, S., Kutsenko, E., & Boos, V. (2022). How different patterns of urbanization affect regional innovation? Evidence from Russia. International Journal of Urban Sciences, 26(2), 213–243.
   Web of Science ®Google Scholar
• van der Wouden, F., & Rigby, D. L. (2019). Co-inventor networks and knowledge production in specialized and diversified cities. Papers in Regional Science, 98(4), 1833–1853.
   Web of Science ®Google Scholar
• Wang, F., Ren, J., Liu, J., Dong, M., Yan, B., & Zhao, H. (2021d). Spatial correlation network and population mobility effect of regional haze pollution: Empirical evidence from Pearl River Delta urban agglomeration in China. Environment, Development and Sustainability, 23(11), 15881–15896.
   Web of Science ®Google Scholar
• Wang, H., & Li, M. (2020). Improved gravity model under policy control in regional logistics. Measurement and Control, 54(5-6), 811–819.
   Web of Science ®Google Scholar
• Wang, S., Wang, J., Wang, Y., & Wang, X. (2023). Spillover and re-spillover in China's collaborative innovation. International Regional Science Review, 46(1), 38–68.
   Web of Science ®Google Scholar
• Wang, S., Wang, J., Wei, C., Wang, X., & Fan, F. (2021a). Collaborative innovation efficiency: From within cities to between cities – empirical analysis based on innovative cities in China. Growth and Change, 52(3), 1330–1360.
   Web of Science ®Google Scholar
• Wang, S., Wang, X., Lu, F., & Fan, F. (2021b). The impact of collaborative innovation on ecological efficiency – empirical research based on China’s regions. Technology Analysis & Strategic Management, 33(2), 242–256.
   Web of Science ®Google Scholar
• Wang, T., Xiao, S., Yan, J., & Zhang, P. (2021c). Regional and sectoral structures of the Chinese economy: A network perspective from multi-regional input-output tables. Physica A: Statistical Mechanics and Its Applications, 581, 126196.
   Web of Science ®Google Scholar
• Wanzenböck, I., Scherngell, T., & Brenner, T. (2014). Embeddedness of regions in European knowledge networks: A comparative analysis of inter-regional R&D collaborations, co-patents and co-publications. The Annals of Regional Science, 53(2), 337–368.
   Web of Science ®Google Scholar
• Wu, D., Song, J., Bian, Y., Zheng, X., & Zhang, Z. (2020). Risk perception and intelligent decision in complex social information network. Industrial Management & Data Systems, 121(1), 99–110.
   Web of Science ®Google Scholar
• Wu, K., & Yao, C. (2021). Exploring the association between shrinking cities and the loss of external investment: An intercity network analysis. Cities, 119, 103351.
   Web of Science ®Google Scholar
• Wuryandari, T., Hoyyi, A., Kusumawardani, D. S., & Rahmawati, D. (2014). Identifikasi Autokorelasi Spasial Pada Jumlahpengangguran Di Jawa Tengah Menggunakan Indeks Moran. Media Statistika, 7(1), 1–10.
   Google Scholar
• Zhang, W., Wang, B., Wang, J., Wu, Q., & Wei, Y. D. (2022). How does industrial agglomeration affect urban land use efficiency? A spatial analysis of Chinese cities. Land Use Policy, 119, 106178.
   Web of Science ®Google Scholar
• Zhou, G., Zhao, C., Wu, M., Chen, Y., & Zhou, F. (2022). Spatial heterogeneity of coupling coordination development between logistics and economy in central plains of China. Discrete Dynamics in Nature and Society, 2022, 7388666.
   Web of Science ®Google Scholar
• Zhu, S., & He, C. (2019). Moving beyond Anglo-American economic geography: The significance of non-Anglo-American model. International Journal of Urban Sciences, 23(2), 191–197.
   Web of Science ®Google Scholar