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      Industrial revolution and environmental sustainability: an analytical interpretation of research constituents in Industry 4.0

      , , , , ,
      International Journal of Lean Six Sigma
      Emerald

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          Abstract

          Purpose

          Environmental sustainability is quickly becoming one of the most critical issues in industry development. This study aims to conduct a systematic literature review through which the author can provide various research areas to work on for future researchers and provide insight into Industry 4.0 and environmental sustainability.

          Design/methodology/approach

          This study accomplishes this by performing a backward analysis using text mining on the Scopus database. Latent semantic analysis (LSA) was used to analyze the corpus of 4,364 articles published between 2013 and 2023. The authors generated ten clusters using keywords in the industrial revolution and environmental sustainability domain, highlighting ten research avenues for further exploration.

          Findings

          In this study, three research questions discuss the role of environmental sustainability with Industry 4.0. The author predicted ten clusters treated as recent trends on which more insight is required from future researchers. The authors provided year-wise analysis, top authors, top countries, top sources and network analysis related to the topic. Finally, the study provided industrialization’s effect on environmental sustainability and the future aspect of automation.

          Research limitations/implications

          The reliability of the current study may be compromised, notwithstanding the size of the sample used. Poor retrieval of the literature corpus can be attributed to the limitations imposed by the search words, synonyms, string construction and variety of search engines used, as well as to the accurate exclusion of results for which the search string is insufficient.

          Originality/value

          This research is the first-ever study in which a natural language processing technique is implemented to predict future research areas based on the keywords–document relationship.

          Related collections

          Most cited references98

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          A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL

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            • Abstract: not found
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            Indexing by latent semantic analysis

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              • Record: found
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              A framework to overcome sustainable supply chain challenges through solution measures of industry 4.0 and circular economy: An automotive case

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                Author and article information

                Journal
                International Journal of Lean Six Sigma
                IJLSS
                Emerald
                2040-4166
                2040-4166
                May 16 2023
                May 16 2023
                Article
                10.1108/IJLSS-02-2023-0030
                9c045d0a-f1cb-438c-93c9-feab246b93d0
                © 2023

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