Volume 11 Issue 6
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Article Navigation >  Journal of Environmental Engineering Technology  > 2021  >  11(6): 1217-1225
ZHAN Liping, ZHAO Rui, YANG Tianxue, YU Yang. A bibliometric analysis of research development regarding big data-driven municipal waste management[J]. Journal of Environmental Engineering Technology, 2021, 11(6): 1217-1225. doi: 10.12153/j.issn.1674-991X.20210081
Citation: ZHAN Liping, ZHAO Rui, YANG Tianxue, YU Yang. A bibliometric analysis of research development regarding big data-driven municipal waste management[J]. Journal of Environmental Engineering Technology, 2021, 11(6): 1217-1225. doi: 10.12153/j.issn.1674-991X.20210081
shu

A bibliometric analysis of research development regarding big data-driven municipal waste management

doi: 10.12153/j.issn.1674-991X.20210081
  • 1.

    Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University

  • 2.

    Research Laboratory of Solid Waste Utilization and Pollution Control, Chinese Research Academy of Environmental Sciences

More Information
  • Corresponding author: ZHAO Rui E-mail: ruizhao@swjtu.edu.cn; YANG Tianxue E-mail: ytx13@126.com
  • Received Date: 2021-03-22
  • Publish Date: 2021-11-20
    Abstract
  • The bibliometric approach was used to develop a holistic review on the research progress of big data driven municipal waste management. By using the literatures retrieved by the core collection database of Web of Science during the period of 2010-2020, a number of bibliometric indicators were incorporated into statistical analysis, including number of articles, research institutions, source journals and keywords, to understand its research status, grasp its development trend and identify the research hotspots, so as to provide a scientific basis for promoting the informatization and intelligent management of municipal solid waste management. The results showed that: The number of articles published increased year by year during the predefined time period, but the total number of articles published was relatively small, a total of 83, indicating that the research still belonged to a new and cutting-edge field. Publication carriers mainly included journal articles, conference articles and review articles, among which articles were mainly published in journals such as Sustainability, Journal of Cleaner Production, and Waste Management and had high citation frequency. Existing studies mainly considered the application of two dimensions of data engineering and data science to achieve the node management and control of the whole lifecycle of municipal waste, in which the former mainly focused on data source acquisition to record the flow direction and information of the waste lifecycle, and the latter provided decision support for improving management efficiency through modeling and analyzing all kinds of big data.

     

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