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Dataset . 2023
License: CC BY
Data sources: Datacite
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Mendeley Data
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Mendeley Data
Dataset . 2023
License: CC BY
Data sources: Datacite
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Green Manufacturing Research Corpus

Authors: Ahmi, Aidi;

Green Manufacturing Research Corpus

Abstract

The "Green Manufacturing Research Corpus" is a meticulously curated dataset that comprises a comprehensive collection of documents dedicated to the domain of green manufacturing. This dataset was meticulously assembled through an extensive search, with a primary focus on documents delving into the intersection of green, sustainable, eco-friendly, and low-carbon practices within the manufacturing sector. Our search strategy involved utilizing a combination of keywords such as green, sustainable, environment, eco-friendly, clean, renewable, zero-waste, and low carbon, alongside the term manufacturing, all within the article titles. This precision ensured that the dataset exclusively features precise and pertinent articles directly tied to the subject of green manufacturing, as of March 6, 2023. In total, the initial search yielded an impressive 3,577 documents, encompassing a diverse array of articles exploring the convergence of green manufacturing with environmental and sustainability dimensions. This dataset forms the cornerstone for our systematic review, allowing us to furnish an authentic portrayal of the current state of the field. It also empowers us to identify emerging trends and confront existing challenges within the realm of green manufacturing. Moreover, we meticulously refined the dataset by excluding specific document types, thereby ensuring that our analysis predominantly centered on original research articles. Document categories excluded from the dataset encompassed review articles (148), conference reviews (39), errata (10), retracted articles (3), and reports (1). This scrupulous curation process culminated in a dataset of 3,376 original research articles. These articles served as the bedrock for our assessment of the present state of green manufacturing research, as well as the identification of key trends, challenges, and opportunities within the field. By relying on this rigorously assembled dataset, we assure that our analysis is firmly anchored in primary sources, capturing recent and relevant discoveries within the dynamic and evolving domain of green manufacturing. Note: This dataset consists of raw files sourced from Scopus. This dataset stands as a valuable resource for researchers, scholars, and policymakers with an interest in the dynamic and ever-evolving field of green manufacturing. It provides a comprehensive overview of the current research landscape, rendering it an indispensable tool for those seeking to gain insights into and contribute to the advancement of sustainable manufacturing practices.

Keywords

Manufacturing, Sustainability, Bibliometrics, Sustainable Manufacturing

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average