Bibliometric Analysis of Computational and Mathematical Models of Innovation and Technology in Business

Castillo-Vergara, Mauricio; Muñoz-Cisterna, Víctor; Geldes, Cristian; Álvarez-Marín, Alejandro; Soto-Marquez, Mónica

doi:10.3390/axioms12070631

Cited by 5 publications

(3 citation statements)

References 103 publications

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“…The methodology employed in the study involves the analysis of three primary types of indicators, which are activity indicators, quality indicators, and relationship indicators. This approach is consistent with the framework outlined by Castillo-Vergara et al [80]. The inclusion of these indicators allows for a comprehensive assessment of the research, encompassing both quantitative and qualitative aspects of the study.…”

Section: Bibliometric Analysissupporting

confidence: 52%

“…The inclusion of these indicators allows for a comprehensive assessment of the research, encompassing both quantitative and qualitative aspects of the study. Activity indicators include the number of countries, journals, papers, and authors and are mainly used for productivity measurement [80,81]. Quality indicators refer to the impact factor, H-index, total number of citations, and average article citations per year [80], while relationship indicators deal with co-citations and co-authorship [80,81].…”

Section: Bibliometric Analysismentioning

confidence: 99%

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Tracking Happiness in Times of COVID-19: A Bibliometric Exploration

Jigani,

Delcea,

Florescu

et al. 2024

Sustainability

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The interest of the research community in happiness and its associated issues has been steadily growing over the years, including during the period marked by the COVID-19 pandemic. The pandemic has brought about significant changes in various aspects of people’s lives. In this study, the objective is to analyze the themes and the most significant trends in papers dedicated to happiness in the context of COVID-19 during the period following the onset of the pandemic. To achieve this, the authors have compiled a dataset of papers sourced from Clarivate Analytics’ Web of Science Core Collection database, which were extracted using keywords related to both happiness and COVID-19. This database comprises 1932 articles. The researchers have conducted a comprehensive bibliometric analysis of this dataset, providing insights into the most prolific authors in this field, the most frequently cited documents, and the preferred journals for publishing this research. The authors also explore details related to collaboration networks and author clusters. An n-gram analysis is performed on titles, abstracts, keywords, and keywords plus, offering a deeper understanding of the primary research themes. Furthermore, the contributors present a review of the top 10 most cited papers, which completes the analysis and underscores the research trends related to happiness in the context of COVID-19.

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Section: Bibliometric Analysissupporting

confidence: 52%

Section: Bibliometric Analysismentioning

confidence: 99%

Tracking Happiness in Times of COVID-19: A Bibliometric Exploration

Jigani,

Delcea,

Florescu

et al. 2024

Sustainability

View full text Add to dashboard Cite

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“…A detailed presentation of each step is shown in Table 1. As for the second part, related to dataset analysis, several works from the field of bibliometrics [21][22][23][24][25][26] were considered and, as a result, the analysis was divided into six main steps: dataset overview, source analysis, author analysis, paper analysis, word analysis, and a mixed analysis.…”

Section: Mixed Analysismentioning

confidence: 99%

Quantifying Neutrosophic Research: A Bibliometric Study

Delcea,

Domenteanu,

Ioanăș

et al. 2023

Axioms

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In recent years, neutrosophic theory has garnered increasing attention within scholarly circles due to its applicability in various domains. Within these domains, the field of decision-making has derived significant advantages from the progressions in neutrosophic theory. Notably, neutrosophic theory has made substantial contributions by advancing and offering a range of aggregation operators and information measures specifically designed for enhancing decision-making processes. In this context, this study aims to conduct a comprehensive bibliometric analysis of the current research landscape in the field of neutrosophic theory, with a specific focus on understanding its applications and development trends. Our analysis reveals that the scientific literature addresses neutrosophic theory in a diverse range of applications. This examination encompasses a scrutiny of key contributors, affiliated academic institutions, influential publications, and noteworthy journals within the neutrosophic domain. To achieve this, we have curated a dataset comprising scholarly papers retrieved from Clarivate Analytics’ Web of Science Core Collection database, employing keywords closely aligned with neutrosophic theory and its applications, spanning a specified timeframe starting from the year in which the first paper on neutrosophic theory was published, namely, from 2005 until 2022. Our findings underscore sustained and robust scholarly interest in neutrosophic theory, characterized by a considerable high annual growth rate of 43.74% during the specified period. Additionally, our investigation delves into the identification and analysis of pivotal keywords and emerging trends, shedding light on prominent research trajectories within this domain. Furthermore, we elucidate collaborative networks among authors, their academic affiliations, and the global distribution across diverse countries and territories, providing valuable insights into the worldwide proliferation of neutrosophic research and applications. Employing n-gram analysis techniques across titles, keywords, abstracts, and keyword-plus fields unveils a multitude of applications where neutrosophic theory plays a central role. The analysis culminates in a review of globally cited documents and a comprehensive discussion highlighting the significance of neutrosophic theory in contemporary research and problem-solving contexts.

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