李小明
Research Associate Supervisor of Master's Candidates
Name (Simplified Chinese):李小明
Name (Pinyin):lixiaoming
E-Mail:xiaomingli45@126.com
Date of Employment:2022-07-01
School/Department:经济研究院
Education Level:With Certificate of Graduation for Doctorate Study
Business Address:邵逸夫科学馆502
Gender:Male
Contact Information:xiaomingli45@126.com ;15215043982
Degree:Doctoral Degree in Economics
Status:Employed
Alma Mater:重庆大学
Whether on the job:1
Academic Honor:
Honors and Titles:
2024-12-18 重庆市第十二次社会科学优秀成果特等奖
2023-05-04 山东大学评为体育美育工作先进教师
Hits:
Journal:JOURNAL OF CLEANER PRODUCTION
Key Words:Big data; Directed technical change; Environmental quality; Environmental regulation policy
Abstract:Big data applications, from its inception have experienced unprecedented changes in technological revolution and development. The need of the hour is to use big data to break through the incompatible bottleneck of environment protection and development. Therefore, this paper constructs a theoretical model to evaluate the changes of relative benefits big data have on R&D through "substitution effects", "complementary effects", and further lead to directed technical change and its impact on the environmental quality. For better understanding the role of big data, we compare different impacts on environmental quality both by considering the big data application and by ignoring it. In addition, we analyze the required environmental regulation policy adjustments under the influence of big data. The results show that: (1) By improving the relative benefits of clean technology R&D, the application of big data further enhances the quality of the environment. (2) Mere relying on the application of big data alone cannot prevent environmental disasters, but it must be supplemented with conducive environmental regulation policy to achieve the best results. (3) The application of big data can reduce the "subsidy" for clean technology R&D to avoid environmental disasters, while the impact of big data on "environmental taxes" varies with the development of clean technology levels. The results of this research will help to clarify the positive effects of big data on environmental quality and implement reasonable environmental regulation policy. (C) 2020 Elsevier Ltd. All rights reserved.
All the Authors:Huang Shoujun
First Author:Yang Jun
Indexed by:Journal paper
Correspondence Author:Li Xiaoming*
Document Code:10.1016/j.jclepro.2020.124126
Discipline:Economics
First-Level Discipline:Applied Economics
Document Type:J
Volume:275
Translation or Not:yes
Date of Publication:2020-10-01
Included Journals:SCI、SSCI