Smart City Gnosys
Smart city article details
| Title | Investigating The Role Of The Tech Industry, Renewable Energy, And Urbanization In Sustainable Environment: Policy Directions In The Context Of Developing Economies |
|---|---|
| ID_Doc | 33442 |
| Authors | Rasool S.F.; Zaman S.; Jehan N.; Chin T.; Khan S.; Zaman Q.U. |
| Year | 2022 |
| Published | Technological Forecasting and Social Change, 183 |
| DOI | http://dx.doi.org/10.1016/j.techfore.2022.121935 |
| Abstract | This paper investigates environmental sustainability by examining the impact of the tech industry, renewable energy, and urbanization environmental degradation in a developing country such as China. This study mainly relates to China for the period 1991 to 2015. Our findings may be extrapolated to other developing countries. We employ several econometric techniques, such as the augmented Dickey-Fuller, the Zivot-Andrew unit root test, autoregressive distributive lags, fully modified ordinary least squares, and canonical cointegrating regression tests, to draw our empirical inferences. Our findings show that there is a significant inverse connection between the tech industry, renewable energy consumption, urbanization, and environmental degradation in China. This negative connection indicates that adding value in the tech industry, increasing the share of renewable energy consumption, and increased urbanization can help reduce environmental degradation. The outcomes of this study suggest some useful policy implications. First, national- and local-level governments should establish specific budgets to promote the use of renewable energy in high-tech industries. Second, policymakers should develop strict policies to increase spending on technological and green innovations. Third, governments should build new smart cities equipped with the latest advanced technologies to encourage more people to move from less developed to highly developed regions. © 2022 Elsevier Inc. |
| Author Keywords | Autoregressive distributive lag model; Environmental degradation in China; Environmental sustainability; Renewable energy consumption; Tech industry; Urbanization |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
58342  | 0.893 | Chatti W.; Khan Z. | Towards Smart Sustainable Cities: Does Technological Innovation Mitigate G7 Co2 Emissions? Fresh Evidence From Cs-Ardl | Science of the Total Environment, 913 (2024) |
| 56141 | 0.886 | Aggarwal S.; Mahalik M.K. | The Nexus Of Urbanization And Renewable Energy Productivity: Implications For Sustainable Development In Developing Asia Nations | International Journal of Energy Sector Management (2025) |
| 10334 | 0.881 | Filiou D.; Kesidou E.; Wu L. | Are Smart Cities Green? The Role Of Environmental And Digital Policies For Eco-Innovation In China | World Development, 165 (2023) |
| 49340 | 0.877 | Yu, CF; Yu, JY; Gao, D | Smart Cities And Greener Futures: Evidence From A Quasi-Natural Experiment In China'S Smart City Construction | SUSTAINABILITY, 16, 2 (2024) |
| 10756 | 0.871 | Ge R.; Xu S.; Ullah M.; Mark P. | Assessing The Impact Of Urban Planning Policies On Renewable Energy: A Case A China Using The Did Estimation Model | Heliyon, 10, 5 (2024) |
| 59188 | 0.868 | Xu C.; Zhu Q.; Lee C.-C. | Two Birds With One Stone: Could China'S Smart City Pilot Promote Energy Efficiency And Energy Equality? | Journal of Cleaner Production, 486 (2025) |
| 20020 | 0.865 | Zhang C. | Digital Governance Leveraging Urbanization And Fintech Synergies For Sustainable Development In Brics | Scientific Reports, 14, 1 (2024) |
| 13283 | 0.864 | Liu H.; Wang L.; Shen Y. | Can Digital Technology Reduce Carbon Emissions? Evidence From Chinese Cities | Frontiers in Ecology and Evolution, 11 (2023) |
| 20904 | 0.862 | Guo C.; Wang Y.; Hu Y.; Wu Y.; Lai X. | Does Smart City Policy Improve Corporate Green Technology Innovation? Evidence From Chinese Listed Companies | Journal of Environmental Planning and Management, 67, 6 (2024) |
| 50422 | 0.861 | Huang Y.; Xiong N.; Liu C. | Smart City Policies And Corporate Renewable Energy Technology Innovation: Insights From Patent Text And Machine Learning | Energy Economics, 148 (2025) |