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The Heterogeneous Influence of Infrastructure Construction on China’s Urban Green and Smart Development—The Threshold Effect of Urban Scale

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  • Lingyan Xu

    (School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, China
    Research Center for Green Development and Environmental Governance, Jiangsu University, Zhenjiang 212013, China)

  • Dandan Wang

    (School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, China)

  • Jianguo Du

    (School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang 212013, China
    Research Center for Green Development and Environmental Governance, Jiangsu University, Zhenjiang 212013, China)

Abstract

The construction of green and smart cities is an important approach to enhancing the level of high-quality development and modern governance, in which infrastructure construction is the antecedent condition. From the perspective of green total factor productivity (GTFP), this paper adopts the SBM–GML (Slack-Based Model and Global Malmquist–Luenberger) index to measure the urban green and smart development level (GSDL) considering smart input–output factors. Based on the panel data of China’s 223 prefecture-level cities from 2005 to 2018, the dynamic impacts, temporal, and spatial differences of energy, transportation, and telecommunication infrastructure construction on the urban GSDL are discussed, and the threshold effects of urban scale are tested. The following conclusions are drawn: (1) On the whole, energy infrastructure inhibits the urban GSDL, while transportation and telecommunication infrastructures significantly promote it. There are distinct spatial and temporal characteristics among the impacts of these three infrastructures on the urban GSDL, in which the facilitating role of transportation and telecommunication infrastructures are further enhanced during the period of 2013–2018. Furthermore, the impacts of these three infrastructures on the urban GSDL all show “U” shape in terms of non-linearity. (2) Economic development level and industrial structure have significant positive effects on the urban GSDL, whereas human capital only has positive effect in the northeast and southwest regions, and government scale shows no positive impact yet. (3) There is a single threshold for the impact of urban scale on these three infrastructures, among which the impacts of energy and transportation infrastructures on the urban GSDL remain consistent before and after the threshold, while the impact of telecommunication infrastructure on the urban GSDL varies from having no significance to being positive when crossing the threshold. Thus, capital investment for infrastructure construction should be further allocated reasonably, the positive potential of human capital should be fully released, and the urban scale should be appropriately controlled in the future.

Suggested Citation

  • Lingyan Xu & Dandan Wang & Jianguo Du, 2021. "The Heterogeneous Influence of Infrastructure Construction on China’s Urban Green and Smart Development—The Threshold Effect of Urban Scale," Land, MDPI, vol. 10(10), pages 1-17, September.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:10:p:1015-:d:644583
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    Cited by:

    1. Doan, Quang Cuong, 2024. "The spatiotemporal trends of urban-rural green spaces and their heterogeneous relationships with population and economic vitality: Evidence from the Red River Delta, Vietnam," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    2. liu, Zhizhong & Ju, Bin, 2023. "Network infrastructure construction and heterogeneous enterprise innovation quasi-natural experiment based on “Broadband China”," Information Economics and Policy, Elsevier, vol. 65(C).
    3. Chendi Li & Lei Wang & Yang Liu, 2023. "The Impact Factors and Spatial Spillover of Industrial Green Development: Based on Cities in the Northwest Segment of the Silk Road Economic Belt," Sustainability, MDPI, vol. 16(1), pages 1-18, December.
    4. Lingyan Xu & Dandan Wang & Jianguo Du, 2022. "Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities," IJERPH, MDPI, vol. 19(7), pages 1-19, March.

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