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Can industrial transfer improve urban innovation efficiency?

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  • Liu, Hongwei
  • Zhang, Aodi
  • Wu, Jie

Abstract

Investigating whether industry transfers to different cities and regions contribute to innovative efficiency improvement is a critical issue in addressing the development of urban innovation. Using the implementation of national industrial relocation demonstration zones (NIRDZ) in China as a quasi-natural experiment, this study empirically assesses the impact of industrial relocation upon urban innovation efficiency. This study first measures the urban innovation efficiency of 194 prefectural cities during 2005–2019 using a two-stage data envelopment analysis model. Then, a multiperiod difference-in-differences model is used to evaluate the innovation effects of national-level demonstration zones for undertaking industrial transfers. The results are as follows. First, industrial relocation does contribute to urban innovation efficiency. This conclusion is supported by a series of robustness tests confirming that the NIRDZ pilot policy indeed contributes to this efficiency, including a placebo test, propensity score matching, shortened time window, winsorized outliers, and lag treatment. Secondly, a regional heterogeneity analysis shows that the pilot policy significantly promotes innovation efficiency of cities located in the central region, but there is an insignificant effect in western region cities. The analysis of city size heterogeneity shows that the pilot policy promotes innovation efficiency more significantly in small cities. In contrast, the promotion effect on big cities is not significant. Third, when considering the potential impact mechanisms, the NIRDZ policy positively affects urban innovation efficiency by enhancing the informatization level and improving economic development. Based on the analysis above, this study recommends establishing an effective mechanism for industrial transfer, realizing the transfer between different regions and cities according to local conditions, and deepening the NIRDZ policy implementation. Policymakers should also increase investment in the construction of an informatization platform, plan resource usage rationally, promote regional integration development, change the philosophy of education, and recognize how the NIRDZ policy influences urban innovation through economic development and informatization.

Suggested Citation

  • Liu, Hongwei & Zhang, Aodi & Wu, Jie, 2023. "Can industrial transfer improve urban innovation efficiency?," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:soceps:v:90:y:2023:i:c:s0038012123002628
    DOI: 10.1016/j.seps.2023.101750
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    as
    1. Li, Mengna & Pan, Xiongfeng & Yuan, Sai, 2022. "Do the national industrial relocation demonstration zones have higher regional energy efficiency?," Applied Energy, Elsevier, vol. 306(PA).
    2. Liu, Yunqiang & Zhu, Jialing & Li, Eldon Y. & Meng, Zhiyi & Song, Yan, 2020. "Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    3. Lee, Chien-Chiang & Hussain, Jafar, 2023. "An assessment of socioeconomic indicators and energy consumption by considering green financing," Resources Policy, Elsevier, vol. 81(C).
    4. Paunov, Caroline & Rollo, Valentina, 2016. "Has the Internet Fostered Inclusive Innovation in the Developing World?," World Development, Elsevier, vol. 78(C), pages 587-609.
    5. Cooke, Philip & Gomez Uranga, Mikel & Etxebarria, Goio, 1997. "Regional innovation systems: Institutional and organisational dimensions," Research Policy, Elsevier, vol. 26(4-5), pages 475-491, December.
    6. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    7. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    10. Longcan Zou & Jim Huangnan Shen & Jun Zhang & Chien‐Chiang Lee, 2022. "What is the rationale behind China's infrastructure investment under the Belt and Road Initiative," Journal of Economic Surveys, Wiley Blackwell, vol. 36(3), pages 605-633, July.
    11. Lee, Chien-Chiang & Wang, Fuhao & Chang, Yu-Fang, 2023. "Towards net-zero emissions: Can green bond policy promote green innovation and green space?," Energy Economics, Elsevier, vol. 121(C).
    12. Monarch, Ryan & Park, Jooyoun & Sivadasan, Jagadeesh, 2017. "Domestic gains from offshoring? Evidence from TAA-linked U.S. microdata," Journal of International Economics, Elsevier, vol. 105(C), pages 150-173.
    13. Eliana La Ferrara & Alberto Chong & Suzanne Duryea, 2012. "Soap Operas and Fertility: Evidence from Brazil," American Economic Journal: Applied Economics, American Economic Association, vol. 4(4), pages 1-31, October.
    14. Xiao Jie Liu & Haiyue Liu & Shi Yi Liu & Jim Huangnan Shen & Chien‐Chiang Lee, 2022. "Profit sharing, industrial upgrading, and global supply chains: Theory and evidence," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2454-2493, November.
    15. Mohsin, Muhammad & Hanif, Imran & Taghizadeh-Hesary, Farhad & Abbas, Qaiser & Iqbal, Wasim, 2021. "Nexus between energy efficiency and electricity reforms: A DEA-Based way forward for clean power development," Energy Policy, Elsevier, vol. 149(C).
    16. An, Qingxian & Yan, Hong & Wu, Jie & Liang, Liang, 2016. "Internal resource waste and centralization degree in two-stage systems: An efficiency analysis," Omega, Elsevier, vol. 61(C), pages 89-99.
    17. Bai, Hanyu & Irfan, Muhammad & Hao, Yu, 2022. "How does industrial transfer affect environmental quality? Evidence from China," Journal of Asian Economics, Elsevier, vol. 82(C).
    18. Nie, Hongguang & Kemp, René, 2014. "Index decomposition analysis of residential energy consumption in China: 2002–2010," Applied Energy, Elsevier, vol. 121(C), pages 10-19.
    19. Raymond Vernon, 1966. "International Investment and International Trade in the Product Cycle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 80(2), pages 190-207.
    20. Lin, Tzu-Yu & Chiu, Sheng-Hsiung & Yang, Hai-Lan, 2022. "Performance evaluation for regional innovation systems development in China based on the two-stage SBM-DNDEA model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    21. Dong, Feng & Li, Yangfan & Li, Kun & Zhu, Jiao & Zheng, Lu, 2022. "Can smart city construction improve urban ecological total factor energy efficiency in China? Fresh evidence from generalized synthetic control method," Energy, Elsevier, vol. 241(C).
    22. Wang, Jinxiu & Deng, Kun, 2022. "Impact and mechanism analysis of smart city policy on urban innovation: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 574-587.
    23. Marianne Bertrand & Sendhil Mullainathan, 2003. "Enjoying the Quiet Life? Corporate Governance and Managerial Preferences," Journal of Political Economy, University of Chicago Press, vol. 111(5), pages 1043-1075, October.
    24. Cheng, Zhonghua & Wang, Lan, 2023. "Can new urbanization improve urban total-factor energy efficiency in China?," Energy, Elsevier, vol. 266(C).
    25. Gao, Kang & Yuan, Yijun, 2022. "Government intervention, spillover effect and urban innovation performance: Empirical evidence from national innovative city pilot policy in China," Technology in Society, Elsevier, vol. 70(C).
    26. Lin, Boqiang & Wang, Chonghao, 2023. "Does industrial relocation affect regional carbon intensity? Evidence from China's secondary industry," Energy Policy, Elsevier, vol. 173(C).
    27. Zhu, Chen & Lee, Chien-Chiang, 2022. "The effects of low-carbon pilot policy on technological innovation: Evidence from prefecture-level data in China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    28. Jesús F. Lampón, 2020. "The impact of uncertainty on production relocation: Implications from a regional perspective," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 427-446, June.
    29. Chen, Yongmin & Jiang, Haiwei & Liang, Yousha & Pan, Shiyuan, 2022. "The impact of foreign direct investment on innovation: Evidence from patent filings and citations in China," Journal of Comparative Economics, Elsevier, vol. 50(4), pages 917-945.
    30. Marlous Blankesteijn & Bart Bossink & Peter Sijde, 2021. "Science-based entrepreneurship education as a means for university-industry technology transfer," International Entrepreneurship and Management Journal, Springer, vol. 17(2), pages 779-808, June.
    31. Todd Mitton, 2022. "Methodological Variation in Empirical Corporate Finance," The Review of Financial Studies, Society for Financial Studies, vol. 35(2), pages 527-575.
    32. Zhang, Yaoyu & Liu, Jin & Wang, Bo, 2022. "The impact of High-Speed Rails on urban expansion: An investigation using an SDID with dynamic effects method," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    33. Lee, Chien-Chiang & Yuan, Zihao & Lee, Chi-Chuan & Chang, Yu-Fang, 2022. "The impact of renewable energy technology innovation on energy poverty: Does climate risk matter?," Energy Economics, Elsevier, vol. 116(C).
    34. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.
    35. Tao, Zhuang & Shuliang, Zhao, 2022. "Collaborative innovation relationship in Yangtze River Delta of China: Subjects collaboration and spatial correlation," Technology in Society, Elsevier, vol. 69(C).
    36. Tom Broekel, 2012. "Collaboration Intensity and Regional Innovation Efficiency in Germany—A Conditional Efficiency Approach," Industry and Innovation, Taylor & Francis Journals, vol. 19(2), pages 155-179, February.
    37. Jan Lambooy, 2004. "The transmission of knowledge, emerging networks, and the role of universities: An evolutionary approach," European Planning Studies, Taylor & Francis Journals, vol. 12(5), pages 643-657, July.
    38. Cassandra C. Wang & George C. S. Lin, 2013. "Dynamics of innovation in a globalizing china: regional environment, inter-firm relations and firm attributes," Journal of Economic Geography, Oxford University Press, vol. 13(3), pages 397-418, May.
    39. Song, Malin & Wang, Shuhong & Sun, Jing, 2018. "Environmental regulations, staff quality, green technology, R&D efficiency, and profit in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 1-14.
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