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dc.contributor.authorÁlvarez Meaza, Izaskun ORCID
dc.contributor.authorZarrabeitia Bilbao, Enara ORCID
dc.contributor.authorRío Belver, Rosa María ORCID
dc.contributor.authorGarechana Anacabe, Gaizka ORCID
dc.date.accessioned2024-02-08T11:14:30Z
dc.date.available2024-02-08T11:14:30Z
dc.date.issued2021-09-24
dc.identifier.citationTechnology in Society 67 : 2021 // Article ID 101758es_ES
dc.identifier.issn0160-791X
dc.identifier.issn1879-3274
dc.identifier.urihttp://hdl.handle.net/10810/65494
dc.description.abstractThe strengthening of measures to reduce greenhouse gas emissions meant that manufacturing scheduling had to acquire a green approach. The need to reduce energy consumption becomes necessary for companies to achieve sustainable development. Therefore, a new challenge for the scientific community was foreseen, researching new algorithms or knowledge hubs to achieve green scheduling. Green scheduling may be considered one of the principles of green manufacturing, aimed at minimizing environmental damage and energy waste. A review of the literature shows that there are no research works that analyze the scientific development carried out in “green scheduling” through methodologies based on bibliometric analysis, thus the need and the novelty of this research. Based on a dataset formed by 420 scientific documents published from 2006 to 2020 a bibliometric and network analysis is carried out to find the scientific trends, the main relationships according to collaborations and intermediaries, and the research hubs that help to establish the research agenda. The results show that “green scheduling” is a growing research area in the scientific community and in recent years the number of new research topics has experienced considerable growth. This research is developed in Asia, Europe and America, but China stands out as the most productive, collaborative, intermediary, influential and active country at present, through its organizations which are mainly universities, such as Huanzhong University of Science and Technology and Tongji University. However, research development related to green scheduling is carried out in a collaborative environment between institutions located in different countries, allowing countries that are not scientific powerhouses to develop research in the area. The network analysis makes it possible to define the research framework through the clustering of the dataset's research keywords, highlighting that the main areas of research focus on the development of new methods through algorithms aimed at improving energy efficiency in production environments, in areas of computational development such as cloud computing, and in transportation. The most cited research papers, considered the main drivers of knowledge, are published in high-quality research journals, and are mainly developments in scheduling algorithms for different work environments with a green approach. Research findings can provide the academic community with relevant information about green scheduling to make appropriate decisions and become a research agenda for future research.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectschedulinges_ES
dc.subjectgreen schedulinges_ES
dc.subjectbibliometric analysises_ES
dc.subjectnetwork analysises_ES
dc.subjectgreen manufacturinges_ES
dc.titleGreen scheduling to achieve green manufacturing: Pursuing a research agenda by mapping sciencees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0160791X21002335
dc.identifier.doi/10.1016/j.techsoc.2021.101758
dc.departamentoesOrganización de empresases_ES
dc.departamentoeuEnpresen antolakuntzaes_ES


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© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license
Except where otherwise noted, this item's license is described as © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license