Artificial Intelligence in Research Funding: A Bibliometric Analysis of Grant Discovery, Grant Matching, Proposal Development, and Funding Ecosystems

Dejina Thapa; Niranjan Devkota; Dipendra Karki; Majibur Rahman Siddique

doi:10.37497/rev.artif.intell.educ.v7ii.1388

Autores

Dejina Thapa Research Department, Policy Research Institute, Government of Nepal https://orcid.org/0000-0001-5764-1579
Niranjan Devkota Policy Research Institute, Kathmandu, Nepal https://orcid.org/0000-0001-9989-0397
Dipendra Karki Nepal Commerce Campus, Tribhuvan University, Kathmandu, Nepal https://orcid.org/0000-0001-9045-7423
Majibur Rahman Siddique Pokhara University, Gwarko, Lalitpur, Nepal https://orcid.org/0009-0004-0098-6110

DOI:

https://doi.org/10.37497/rev.artif.intell.educ.v7ii.1388

Palavras-chave:

Inteligência Artificial, Identificação de Oportunidades de Fomento, Financiamento à Pesquisa, Compatibilização de Editais, Desenvolvimento de Propostas, Avaliação de Propostas, Análise Bibliométrica, Ecossistema de Financiamento

Resumo

Contexto: A inteligência artificial (IA) vem transformando cada vez mais a forma como as oportunidades de financiamento à pesquisa são identificadas, buscadas e concedidas. Entretanto, a literatura fragmentada sobre esse domínio emergente ainda carece de uma síntese sistemática de sua estrutura intelectual e de um modelo integrador que articule suas diferentes aplicações. Este estudo busca preencher essa lacuna por meio da análise das tendências de pesquisa e do desenvolvimento de um framework conceitual sobre a aplicação da IA ao financiamento à pesquisa.

Objetivos: Este estudo tem como objetivos identificar e caracterizar as tendências de pesquisa relacionadas ao financiamento à pesquisa assistido por IA e desenvolver um framework conceitual que sintetize essas aplicações em um modelo integrado.

Método: Os dados bibliográficos foram extraídos da base Scopus, resultando em um conjunto final de 3.267 artigos científicos, posteriormente analisados por meio do Biblioshiny (pacote Bibliometrix, em R) e do VOSviewer.

Resultados: Os resultados revelam um campo em rápida expansão, com taxa de crescimento anual de 40,22% e aumento do número de publicações de 22, em 2017, para 826, em 2025. A produção científica concentra-se em um conjunto central de periódicos e autores altamente produtivos, com predominância de economias intensivas em pesquisa, lideradas pelos Estados Unidos, China e Reino Unido. A análise temática evidencia uma transição de temas fundamentais relacionados à IA e centrados em dados para aplicações voltadas ao financiamento e aos métodos, refletindo a passagem do campo da novidade tecnológica para a implementação operacional. Com base nesses achados, propõe-se um framework conceitual composto por cinco etapas — identificação de oportunidades de fomento, compatibilização de editais, desenvolvimento de propostas, avaliação de propostas e ecossistema de financiamento — destinado a orientar a integração responsável da IA ao longo do ciclo de financiamento à pesquisa.

Conclusão: A IA está transformando o ciclo de financiamento à pesquisa ao criar oportunidades para processos de fomento mais eficientes, acessíveis e orientados por dados. O framework de cinco etapas proposto oferece uma base para compreender e orientar a integração responsável da IA no financiamento à pesquisa, enfatizando, simultaneamente, a supervisão humana, a transparência, a equidade e a responsabilização.

Biografia do Autor

Dejina Thapa, Research Department, Policy Research Institute, Government of Nepal

Dr. Dejina Thapa is a nursing researcher with a PhD in Nursing from The Chinese University of Hong Kong. Her research interests include critical care nursing, healthcare quality, evidence-based practice, patient outcomes, and research synthesis. She has published research in international peer-reviewed journals, including studies on mechanical ventilation, ventilator-care bundles, and systematic reviews.

Niranjan Devkota, Policy Research Institute, Kathmandu, Nepal

Dr. Niranjan Devkota is currently serving as a Research Fellow at the Policy Research Institute, Government of Nepal. Prior to joining PRI, he worked as an Associate at the National Planning Commission, Government of Nepal. He is an economist with a special focus on cross-border economic activities and climate change adaptation issues. Dr. Devkota has over 15 years of experience in economic research, covering a wide range of dynamic and evolving themes. His recent research interests lie in development economics, particularly in cross-border trade and agriculture. He earned his PhD from Tribhuvan University, Nepal. He has substantial experience in impact assessment, economic modeling, and the preparation of strategic and implementation plans for various economic policy issues. He has received advanced training and participated in capacity-building workshops on international cooperation, natural resource management, and trade-related activities organized by esteemed international institutions such as SANDEE (ICIMOD), NDRC (China), Hi-AWARE (ICIMOD), and SANEM (Bangladesh), as well as through various reputed universities in online mode. Dr. Devkota is proficient in STATA and has a working knowledge of R. He is the author of the book "Quantitative and Applied Research Methodology in Economics: Researching, Reporting and Publishing", published by Routledge.

Dipendra Karki, Nepal Commerce Campus, Tribhuvan University, Kathmandu, Nepal

Dr. Dipendra Karki is an Assistant Professor of Finance at Tribhuvan University, Nepal Commerce Campus, Kathmandu. He earned PhD in Finance from Kathmandu University School of Management (KUSOM). His teaching interests include Global Finance, Behavioural Finance, and Financial Economics. Dr. Karki is a published author, having written several articles and books.

Majibur Rahman Siddique, Pokhara University, Gwarko, Lalitpur, Nepal

Mr. Majibur Rahman Siddique is an MBA Gold Medalist from Pokhara University and a Dean’s List BBA graduate. He serves as a Research Assistant at Quest Research Management Cell, specializing in bibliometric studies, systematic reviews, and advanced methods like PLS-SEM and ANN. He won Best Paper Award for his masters thesis and is an emerging scholar in technology, education and sustainability driven research.

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