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- W4280533913 abstract "This paper presents a bibliometric analysis of inventory models in a sustainable supply chain. The methodology contains reviewing previous research with a performance evaluation, network analysis, and science mapping to identify the applications, trends, and future research topics. Scientific mapping examines the periods and volumes of publications, authors, journals, countries, regions, organizations, subject areas, and citation analyses. The dataset was obtained with the Scopus database and analyzed using MS Excel and VOSviewer. The search equation identified 335 research papers, which resulted in 131 significant manuscripts on the subject after being screened and filtered. The most notable countries in developing research were Iran, India, China, the United States, Canada, Taiwan, France, the United Arab Emirates, Turkey, and Denmark. Saha, S., Ajay, S.Y., and Baboli, A. were the most cited authors. The journals that publish the most research were Sustainability, the Journal of Cleaner Production, and the International Journal of Production Economics. Some research focuses on reducing carbon emissions and polluting agents applied in different industries in China, Brazil, India, and others. The main findings were the number of industry sectors researching this topic, increasing the number of publications, and promoting the proper use of resources within a sustainable supply chain. There are many investigations of theoretical models that have applications in real-life cases. There is also evidence of the high importance of promoting sustainable development. The emissions regulations in a green supply chain applied to agricultural products have allowed for more actions to achieve responsible production and consumption, as seen in applied research in the pulp and paper industry." @default.
- W4280533913 created "2022-05-22" @default.
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- W4280533913 date "2022-05-15" @default.
- W4280533913 modified "2023-09-30" @default.
- W4280533913 title "Inventory Models in a Sustainable Supply Chain: A Bibliometric Analysis" @default.
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- W4280533913 doi "https://doi.org/10.3390/su14106003" @default.
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