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Does Transportation Infrastructure Construction Enhance Enterprise Innovation Resilience in China?

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  • Enji Li

    (School of Business Administration, Hebei University of Economics and Business, Shijiazhuang 050061, China
    Hebei Collaborative Innovation Center for Urban-rural Integrated Development, Shijiazhuang 050061, China)

  • Ziwei An

    (School of Business Administration, Hebei University of Economics and Business, Shijiazhuang 050061, China)

Abstract

With increasing uncertainty and ambiguity in the external business environment, the risks and challenges faced by enterprises also increase accordingly; resilience has become a necessary characteristic for the evolution and upgrading of enterprise innovation systems, and improving enterprise innovation resilience becomes the key for enterprises to establish sustainable competitive advantages and achieve sustainable development. Based on the panel data of Chinese listed companies and cities, we employ the common factor method to measure enterprise innovation resilience and explore the impact of transportation infrastructure construction on enterprise innovation resilience. The results reveal that, firstly, enterprise innovation resilience shows an overall upward trend, but there is a certain degree of temporal–spatial and industrial disparity. Secondly, transportation infrastructure construction, represented by HSR opening, can significantly improve enterprise innovation resilience. However, this effect performs the following heterogeneity: (1) Regionally, the promotion effect is more obvious in eastern regions, central cities, and non-central cities within 107 km and 764 km away from the central city. (2) For enterprises, compared to state-owned enterprises and non-high-tech industries, transportation infrastructure construction has a greater effect in non-state-owned enterprises and high-tech industries. (3) The higher the degree of centrality and closeness centrality, the more obvious the promotion effect of transportation infrastructure construction. Finally, mechanism tests show that enterprise resource acquisition and resource allocation abilities are important channels for transportation infrastructure construction, to enhance enterprise innovation resilience.

Suggested Citation

  • Enji Li & Ziwei An, 2024. "Does Transportation Infrastructure Construction Enhance Enterprise Innovation Resilience in China?," Sustainability, MDPI, vol. 16(7), pages 1-21, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2931-:d:1368527
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    1. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    2. Gabriel M Ahlfeldt & Arne Feddersen, 2018. "From periphery to core: measuring agglomeration effects using high-speed rail," Journal of Economic Geography, Oxford University Press, vol. 18(2), pages 355-390.
    3. Robert Hauswald & Robert Marquez, 2006. "Competition and Strategic Information Acquisition in Credit Markets," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 967-1000.
    4. Natalia Ortiz-de-Mandojana & Pratima Bansal, 2016. "The long-term benefits of organizational resilience through sustainable business practices," Strategic Management Journal, Wiley Blackwell, vol. 37(8), pages 1615-1631, August.
    5. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    6. Li, He & Lu, Juan & Guo, Feiyu, 2022. "High speed rail and corporate social responsibility performance: Analysis of intra-regional location and inter-regional spillover," Transport Policy, Elsevier, vol. 128(C), pages 65-75.
    7. Jaisy Aghniarahim Putritamara & Budi Hartono & Hery Toiba & Hamidah Nayati Utami & Moh Shadiqur Rahman & Dewi Masyithoh, 2023. "Do Dynamic Capabilities and Digital Transformation Improve Business Resilience during the COVID-19 Pandemic? Insights from Beekeeping MSMEs in Indonesia," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    8. Li, Pei & Lu, Yi & Wang, Jin, 2016. "Does flattening government improve economic performance? Evidence from China," Journal of Development Economics, Elsevier, vol. 123(C), pages 18-37.
    9. Ejaz Ghani & Arti Grover Goswami & William R. Kerr, 2016. "Highway to Success: The Impact of the Golden Quadrilateral Project for the Location and Performance of Indian Manufacturing," Economic Journal, Royal Economic Society, vol. 126(591), pages 317-357, March.
    10. Holl, Adelheid, 2016. "Highways and productivity in manufacturing firms," Journal of Urban Economics, Elsevier, vol. 93(C), pages 131-151.
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