Examining the influence of green innovations in industrial enterprises on China's smart city development

Shubo Yang, Atif Jahanger and Muhammad Usman

Technological Forecasting and Social Change, 2024, vol. 199, issue C

Abstract: In this modern era, smart cities are an essential strategy for China to achieve high-quality development representing an essential issue at the stage of high-quality development to drive urban innovation and lead China to be among the innovative countries. In order to achieve this goal, this study employs a time-varying difference-in-difference (DID) model to test the above questions in a multidimensional manner based on micro-firm data from the China Tax Survey Database and the China Innovative Enterprise Database from 2010 to 2015. The estimated results explore that China's smart city pilot policies (SCPP) encourage green innovation at the firm level, a finding that still holds after a sequence of robustness tests. Furthermore, the empirical evidence indicates that the influence of green innovations on the SCPP was more important for firms in non-state-owned enterprises, heavily polluting industries and non-resource-based cities relative to state-owned firms, firms in lightly-polluting industries and firms in non-resource-based cities. In addition, this study finds that the smart city pilot policy can provide a new incentive for the green innovation behaviour of enterprises via policy and agglomeration effects. Overall, the estimated findings suggest that the government should continue to play a positive role in constructing smart cities for enterprises' green innovation and implement smart city construction programmes following local conditions to help China's high-quality economic development.

Keywords: Smart cities; Green innovations; Chinese industrial enterprises; A time-varying DID model (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:199:y:2024:i:c:s0040162523007163

DOI: 10.1016/j.techfore.2023.123031

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