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

Andréa Aparecida Costa Mineiro (), Victor Eduardo Mello Valério (), Isabel Cristina Silva Arantes (), Sandra Miranda Neves () and Rita Cassia Arantes ()
Additional contact information
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

Quality & Quantity: International Journal of Methodology, 2025, vol. 59, issue 2, No 15, 1353-1381

Abstract: 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.

Keywords: Systematic review; ChatGPT; R software; Triple helix; Quadruple Helix; Quintuple Helix (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11135-024-02012-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:qualqt:v:59:y:2025:i:2:d:10.1007_s11135-024-02012-7

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11135

DOI: 10.1007/s11135-024-02012-7

Access Statistics for this article

Quality & Quantity: International Journal of Methodology is currently edited by Vittorio Capecchi

More articles in Quality & Quantity: International Journal of Methodology from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().