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Helix innovation models: systematic literature review with data analysis script by R software and ChatGPT

Author

Listed:
  • Andréa Aparecida Costa Mineiro

    (Itajubá Federal University)

  • Victor Eduardo Mello Valério

    (Itajubá Federal University)

  • Isabel Cristina Silva Arantes

    (Itajubá Federal University)

  • Sandra Miranda Neves

    (Itajubá Federal University)

  • Rita Cassia Arantes

    (UFLA)

Abstract

Studies of systematic review of the literature have grown as a strategy for understanding certain epistemological fields, considering that these follow specific protocols of analysis in order to compile approaches to various documental corpus. In these terms, this article addresses specifically a systematic review, aiming to know the state of the art about Helix (Triple, Quadruple, Quintuple) and compile theoretical and methodological perspectives for data analysis via statistical language and artificial intelligence. The procedural scope involved compiling the studies and providing a real contribution to the scientific field, operationalizing a systematic review of a quantitative nature, by means of meta-analysis via R software-with pre-programmed operations in Bibliometrix, which allows multiple evaluations in different perspectives in analogy to ChatGPT search results. A total of 21,180 articles were found, distributed in the Web of Science (WOS) and Scopus databases, and meeting exclusion criteria, 1,545 articles were considered for analysis. The results indicate an open and emerging field for studies on Innovation Helices. Furthermore, the results show that at certain stages of the systematic literature review, sometimes R Software performed better, sometimes ChatGPT. Therefore, the use of artificial intelligence can be a complementary and effective way to construct literature reviews. However, the researcher’s knowledge is essential to ensure the quality and scientific rigor of the research. The contribution of the research is threefold. First, it highlights the state of the art of Innovation Helices. Second, it presents the potential of artificial intelligence in literature reviews. Third, it presents a roadmap for data analysis using R software and ChatGPT to guide research and systematic literature reviews in different modalities.

Suggested Citation

  • Andréa Aparecida Costa Mineiro & Victor Eduardo Mello Valério & Isabel Cristina Silva Arantes & Sandra Miranda Neves & Rita Cassia Arantes, 2025. "Helix innovation models: systematic literature review with data analysis script by R software and ChatGPT," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1353-1381, April.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:2:d:10.1007_s11135-024-02012-7
    DOI: 10.1007/s11135-024-02012-7
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    References listed on IDEAS

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