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The impact of network topological structures on systematic technology adoption and carbon emission reduction
This paper investigates how the topological structure of the technological spillover network among agents affects the adoption of a new clean technology and the reduction of system’s carbon emissions. Through building a systematic technology adoption model with technological spillover effect among a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517025/ https://www.ncbi.nlm.nih.gov/pubmed/34650133 http://dx.doi.org/10.1038/s41598-021-99835-3 |
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author | Chen, Huayi Shi, Huai-Long |
author_facet | Chen, Huayi Shi, Huai-Long |
author_sort | Chen, Huayi |
collection | PubMed |
description | This paper investigates how the topological structure of the technological spillover network among agents affects the adoption of a new clean technology and the reduction of system’s carbon emissions. Through building a systematic technology adoption model with technological spillover effect among agents from the network perspective, this paper first illustrates how the new technology diffuses from the earlier adopters to the later adopters under different network topological structures. Further, this paper examines how the carbon emission constraints imposed on pilot agents affect the carbon emissions of other agents and the entire system under different network topological structures. Simulation results of our study suggest that, (1) different topological structures of the technological spillover network have great influence on the adoption and diffusion of a new advanced technology; (2) imposing carbon emission constraints on pilot agents can reduce carbon emissions of other agents and thereby the entire system. However, the effectiveness of the carbon emission constraints is also largely determined by the network topological structures. Our study implies that the empirical research of the network topological structure among the participating entities is a pre-requisite to evaluate the real effectiveness of a carbon emission reduction policy from the system perspective. |
format | Online Article Text |
id | pubmed-8517025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85170252021-10-15 The impact of network topological structures on systematic technology adoption and carbon emission reduction Chen, Huayi Shi, Huai-Long Sci Rep Article This paper investigates how the topological structure of the technological spillover network among agents affects the adoption of a new clean technology and the reduction of system’s carbon emissions. Through building a systematic technology adoption model with technological spillover effect among agents from the network perspective, this paper first illustrates how the new technology diffuses from the earlier adopters to the later adopters under different network topological structures. Further, this paper examines how the carbon emission constraints imposed on pilot agents affect the carbon emissions of other agents and the entire system under different network topological structures. Simulation results of our study suggest that, (1) different topological structures of the technological spillover network have great influence on the adoption and diffusion of a new advanced technology; (2) imposing carbon emission constraints on pilot agents can reduce carbon emissions of other agents and thereby the entire system. However, the effectiveness of the carbon emission constraints is also largely determined by the network topological structures. Our study implies that the empirical research of the network topological structure among the participating entities is a pre-requisite to evaluate the real effectiveness of a carbon emission reduction policy from the system perspective. Nature Publishing Group UK 2021-10-14 /pmc/articles/PMC8517025/ /pubmed/34650133 http://dx.doi.org/10.1038/s41598-021-99835-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chen, Huayi Shi, Huai-Long The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title | The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title_full | The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title_fullStr | The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title_full_unstemmed | The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title_short | The impact of network topological structures on systematic technology adoption and carbon emission reduction |
title_sort | impact of network topological structures on systematic technology adoption and carbon emission reduction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517025/ https://www.ncbi.nlm.nih.gov/pubmed/34650133 http://dx.doi.org/10.1038/s41598-021-99835-3 |
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