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Exploring Antecedents, Consequences, Research Constituents and Future Directions of Circular Economy: A Predictive Analysis in the Preview of Text Mining
被引:2
|作者:
Mishra, Manoj Kumar
[1
]
Sharma, Chetan
[2
]
Sharma, Shamneesh
[2
]
Kumar, Sunil
[3
]
Srivastav, Arun Lal
[4
]
机构:
[1] OP Jindal Univ, Sch Management, Raigarh, India
[2] upGrad Educ Pvt Ltd, Bangalore, India
[3] GITAM, GITAM Sch Business, Visakhapatnam, India
[4] Chitkara Univ, Sch Engn & Technol, Himachal Pradesh, India
关键词:
Circular economy;
Environmental sustainability;
Scopus;
Latent Dirichlet Allocation (LDA);
Natural language processing;
Industry;
4.0;
PRINCIPLES;
ENERGY;
MODEL;
D O I:
10.1007/s13132-024-02184-5
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
The organization uses traditional models, but a circular economy has emerged as an alternative to achieve the environmental sustainability goals. In the struggle against the depletion of global resources and environmental damage, frameworks for a circular economy have arisen as a significant issue for discussion and intervention. Scopus provides the data used to execute topic modeling in this research. For information modeling, we employ Latent Dirichlet Allocation (LDA) to extract the study topics in environmental sustainability from the corpus of 4488 research articles published between 2005 and 2023. Predicted research subjects for the circular economy, which requires further study in the future, include 2, 5, and 10 and are based on a bag of words identified by clustering techniques. The academic community needs more investigation of these tendencies for their long-term viability. The circular economy aims to reduce or eliminate waste. It's a system that creates lots of money for the economy yet doesn't harm the environment too much. Of the 17 research trends identified by the applied LDA techniques, 5 are the most explored by the researchers, while 4 have received the least attention.
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