TY - JOUR
T1 - Mapping the future: Unveiling global trends in smart waste management research
AU - Boostani, Fatemeh
AU - Golzary, Abooali
AU - Huisingh, Donald
AU - Skitmore, Martin
N1 - Publisher Copyright:
© 2024
PY - 2024/12
Y1 - 2024/12
N2 - This study aims to investigate the current landscape and collaborative dynamics of research integrating Big Data with smart waste management (SWM) through a comprehensive bibliometric analysis. We examined 2,808 scientific articles published from 2007 to 2024 using advanced bibliometric tools, VOSviewer and R-Studio (Bibliometrix R Package), to understand trends, influential contributions, and research gaps. Our findings reveal key collaboration networks, author dynamics, and international cooperation patterns, highlighting productive countries, regions, and organizations in this emerging field. The analysis of publication and citation trends shows a significant growth in research output over the studied period, indicating increased interest and investment in SWM research. Additionally, we identified the top 10 journals, authors, countries, and organizations leading in productivity. By constructing author co-citation cluster networks from Web of Science data, we mapped prominent research clusters and organizational collaborations that drive advancements in SWM, particularly within smart cities. While the findings underscore notable progress, they also reveal that many organizations remain in the early stages of SWM exploration. These insights can help researchers and policymakers strengthen collaborative networks, accelerate research development, and support practical applications of SWM solutions. We also discuss limitations in bibliometric classification methods and propose future research directions, including more in-depth content analyses of SWM and related technologies.
AB - This study aims to investigate the current landscape and collaborative dynamics of research integrating Big Data with smart waste management (SWM) through a comprehensive bibliometric analysis. We examined 2,808 scientific articles published from 2007 to 2024 using advanced bibliometric tools, VOSviewer and R-Studio (Bibliometrix R Package), to understand trends, influential contributions, and research gaps. Our findings reveal key collaboration networks, author dynamics, and international cooperation patterns, highlighting productive countries, regions, and organizations in this emerging field. The analysis of publication and citation trends shows a significant growth in research output over the studied period, indicating increased interest and investment in SWM research. Additionally, we identified the top 10 journals, authors, countries, and organizations leading in productivity. By constructing author co-citation cluster networks from Web of Science data, we mapped prominent research clusters and organizational collaborations that drive advancements in SWM, particularly within smart cities. While the findings underscore notable progress, they also reveal that many organizations remain in the early stages of SWM exploration. These insights can help researchers and policymakers strengthen collaborative networks, accelerate research development, and support practical applications of SWM solutions. We also discuss limitations in bibliometric classification methods and propose future research directions, including more in-depth content analyses of SWM and related technologies.
UR - http://www.scopus.com/inward/record.url?scp=85211056886&partnerID=8YFLogxK
U2 - 10.1016/j.rineng.2024.103485
DO - 10.1016/j.rineng.2024.103485
M3 - Article
AN - SCOPUS:85211056886
SN - 2590-1230
VL - 24
SP - 1
EP - 16
JO - Results in Engineering
JF - Results in Engineering
M1 - 103485
ER -