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Discovering themes and trends in electricity supply chain area research

Author

Listed:
  • Sumeet Sahay

    (Indian Institute of Technology (ISM))

  • Hemant Kumar Kaushik

    (IIFT)

  • Shikha Singh

    (Indian Institute of Technology (ISM))

Abstract

Electricity Supply Chain Management has become one of the foremost vital areas of research, as energy firms are extensively concerned about their supply chains in order to maximize profitability, reduce expenses, and gain market share. Thus, numerous research evaluations and implementation methodologies are observed in this area. However, only a few exceptional attempts have been undertaken in the past to summarize sporadic elements of knowledge obtained from these scientific endeavors. As a result, aiming to present a particular viewpoint of this topic, the paper utilizes three analyses—bibliometric analysis through Bibliomatrix R and VOSviewer, thematic analysis through Biblioshiny and text mining technique—topic modelling to give a summary of ESCM scientific investigation accomplished from 1975 to 2021. This study analyzes trends in publication, authorship patterns, and keyword usage. The study utilizes a probabilistic procreative model through structural topic modeling to decipher and extricate esoteric themes from ESCM-related research papers. According to this research, the most popular topics in the ESCM area are carbon emission, energy saving, risk and uncertainties, price regulations, smart grid, IoT, and game theory analysis. Other significant components include life cycle assessment, ICT system, static and dynamic transportation network equilibrium, and network modelling for evaluation and selection of suppliers. The article also identifies knowledge gaps that may guide future research.

Suggested Citation

  • Sumeet Sahay & Hemant Kumar Kaushik & Shikha Singh, 2023. "Discovering themes and trends in electricity supply chain area research," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1525-1560, September.
    • Handle: RePEc:spr:opsear:v:60:y:2023:i:3:d:10.1007_s12597-023-00648-x
    DOI: 10.1007/s12597-023-00648-x
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