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Visualising the Knowledge Domain of Reverse Logistics and Sustainability Performance: Scientometric Mapping Based on VOSviewer and CiteSpace

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  • Kaihan Yang

    (Faculty of Management, Universiti Teknologi Malaysia, Skudai 81310, Malaysia)

  • Ai Chin Thoo

    (Faculty of Management, Universiti Teknologi Malaysia, Skudai 81310, Malaysia)

Abstract

Considering reverse logistics’ benefit for sustainability, it has gained significant attention as a strategic decision. Additionally, a geometric expansion occurs in reverse logistics and sustainability performance. Despite this, little has been written about this evolution retrospectively. Therefore, this study aims to conceptualise and perform a systematic scientometric review of reverse logistics and sustainability performance to identify research hotspots and emerging trends and offer suggestions for future research agendas by reviewing, retrieving, and analysing 848 papers from the Scopus databases. Based on the analysis, there was a rapid rise in the number of publications within this domain, while, at the same time, increasing interdisciplinary subject research has appeared. Furthermore, scholars and institutions from China, India, and the USA were the most prolific in this research domain. Mainly, the current study underscored some pivotal research hotspots, such as assessing the reverse logistics effect on different sustainability performance dimensions and developing a reverse logistics and sustainability performance network. Moreover, emerging trends include game theory, artificial intelligence, Industry 4.0, the manufacturing industry of developing countries, and the circular economy. Finally, a moderator was also sought to be proposed to optimise the relationship between reverse logistics and sustainability performance due to the inconsistent link between them. Having a comprehensive overview of reverse logistics and sustainability performance over the last 24 years may help practitioners and researchers better understand global trends and directions in this field.

Suggested Citation

  • Kaihan Yang & Ai Chin Thoo, 2023. "Visualising the Knowledge Domain of Reverse Logistics and Sustainability Performance: Scientometric Mapping Based on VOSviewer and CiteSpace," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1105-:d:1027643
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    Cited by:

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    2. Natalya Ivanova & Ekaterina Zolotova, 2023. "Landolt Indicator Values in Modern Research: A Review," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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