Artigo em revista científica Q1
Tracing the evolution of digitalisation research in business and management fields: Bibliometric analysis, topic modelling and deep learning trend forecasting
Mojtaba Talafidaryani (Talafidaryani, M.); Seyed Mohammad Jafar Jalali (Jalali, S. M.); Sérgio Moro (Moro, S.);
Título Revista
Journal of Information Science
Ano (publicação definitiva)
N/A
Língua
Inglês
País
Reino Unido
Mais Informação
Web of Science®

N.º de citações: 2

(Última verificação: 2024-12-22 12:08)

Ver o registo na Web of Science®


: 1.1
Scopus

N.º de citações: 7

(Última verificação: 2024-12-17 15:23)

Ver o registo na Scopus


: 2.5
Google Scholar

N.º de citações: 10

(Última verificação: 2024-12-16 23:30)

Ver o registo no Google Scholar

Abstract/Resumo
Research on digitalisation trends and digital topics has become one of the most prolific streams of research within the fields of business and management during the course of the past few years. The purpose of this study is to provide a general picture of the intellectual structure and the conceptual space of this research realm. To this purpose, 6067 publications related to digital topics, indexed in the business and management categories of Web of Science (WoS), and dated from 1990 to 2020 are explored based on the approaches of bibliometric analysis, topic modelling and trend forecasting. The results of the bibliometric analysis comprise insights into the publication and citation structure, the most productive authors, the most productive universities, the most productive countries, the most productive journals, the most cited studies and the most prevalent themes and sub-themes on digitalisation in business and management. In addition, the outcomes of the topic modelling give new knowledge on the latent topical structure along with the rising, falling and fluctuating trends of this literature. In addition, the results of the trend forecasting enable readers to have a glimpse of how the underlying trends of the literature will probably change within the next years until 2025. These results provide guidance and orientation for both academics and practitioners who are initiating or currently developing their efforts in this discipline.
Agradecimentos/Acknowledgements
--
Palavras-chave
Bibliometric analysis,Business and management,Digital transformation,Digital X,Digitalization,Topic modelling,Trend forecasting
  • Ciências da Computação e da Informação - Ciências Naturais
  • Ciências da Comunicação - Ciências Sociais
  • Outras Ciências Sociais - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UIDB/04466/2020 Fundação para a Ciência e a Tecnologia
UIDP/04466/2020 Fundação para a Ciência e a Tecnologia
Projetos Relacionados

Esta publicação é um output do(s) seguinte(s) projeto(s):