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30 years of intelligence models in management and business: A bibliometric review

Author

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  • López-Robles, J.R.
  • Otegi-Olaso, J.R.
  • Porto Gómez, I.
  • Cobo, M.J.

Abstract

The critical factors in the big data era are collection, analysis, and dissemination of information to improve an organization’s competitive position and enhance its products and services. In this scenario, it is imperative that organizations use Intelligence, which is understood as a process of gathering, analyzing, interpreting, and disseminating high-value data and information at the right time for use in the decision-making process. Earlier, the concept of Intelligence was associated with the military and national security sector; however, in present times, and as organizations evolve, Intelligence has been defined in several ways for the purposes of different applications. Given that the purpose of Intelligence is to obtain real value from data, information, and the dynamism of the organizations, the study of this discipline provides an opportunity to analyze the core trends related to data collection and processing, information management, decision-making process, and organizational capabilities. Therefore, the present study makes a conceptual analysis of the existing definitions of intelligence in the literature by quantifying the main bibliometric performance indicators, identifying the main authors and research areas, and evaluating the development of the field using SciMAT as a bibliometric analysis software.

Suggested Citation

  • López-Robles, J.R. & Otegi-Olaso, J.R. & Porto Gómez, I. & Cobo, M.J., 2019. "30 years of intelligence models in management and business: A bibliometric review," International Journal of Information Management, Elsevier, vol. 48(C), pages 22-38.
  • Handle: RePEc:eee:ininma:v:48:y:2019:i:c:p:22-38
    DOI: 10.1016/j.ijinfomgt.2019.01.013
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    Citations

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    Cited by:

    1. Akbari, Morteza & Foroudi, Pantea & Zaman Fashami, Rahime & Mahavarpour, Nasrin & Khodayari, Maryam, 2022. "Let us talk about something: The evolution of e-WOM from the past to the future," Journal of Business Research, Elsevier, vol. 149(C), pages 663-689.
    2. Akbari, Morteza & Foroudi, Pantea & Khodayari, Maryam & Zaman Fashami, Rahime & Shahabaldini parizi, Zahra & Shahriari, Elmira, 2022. "Sharing Your Assets: A Holistic Review of Sharing Economy," Journal of Business Research, Elsevier, vol. 140(C), pages 604-625.
    3. Steve J. Bickley & Ho Fai Chan & Benno Torgler, 2022. "Artificial intelligence in the field of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2055-2084, April.
    4. Antonio-José Moreno-Guerrero & María Elena Parra-González & Jesús López-Belmonte & Adrián Segura-Robles, 2022. "Science mapping analysis of “cultural” in web of science (1908–2019)," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 239-257, February.
    5. Huaruo Chen & Tingting Fang & Fan Liu & Liman Pang & Ya Wen & Shi Chen & Xueying Gu, 2020. "Career Adaptability Research: A Literature Review with Scientific Knowledge Mapping in Web of Science," IJERPH, MDPI, vol. 17(16), pages 1-21, August.
    6. Pedro Jurado de los Santos & Antonio-José Moreno-Guerrero & José-Antonio Marín-Marín & Rebeca Soler Costa, 2020. "The Term Equity in Education: A Literature Review with Scientific Mapping in Web of Science," IJERPH, MDPI, vol. 17(10), pages 1-17, May.
    7. Leonardo B. Furstenau & Bruna Rabaioli & Michele Kremer Sott & Danielli Cossul & Mariluza Sott Bender & Eduardo Moreno Júdice De Mattos Farina & Fabiano Novaes Barcellos Filho & Priscilla Paola Severo, 2021. "A Bibliometric Network Analysis of Coronavirus during the First Eight Months of COVID-19 in 2020," IJERPH, MDPI, vol. 18(3), pages 1-24, January.
    8. Maikel Luis Kolling & Leonardo B. Furstenau & Michele Kremer Sott & Bruna Rabaioli & Pedro Henrique Ulmi & Nicola Luigi Bragazzi & Leonel Pablo Carvalho Tedesco, 2021. "Data Mining in Healthcare: Applying Strategic Intelligence Techniques to Depict 25 Years of Research Development," IJERPH, MDPI, vol. 18(6), pages 1-20, March.
    9. Vilker Zucolotto Pessin & Luciana Harue Yamane & Renato Ribeiro Siman, 2022. "Smart bibliometrics: an integrated method of science mapping and bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3695-3718, June.
    10. Fabiana Liar Agudo & Barbara Stolte Bezerra & José Alcides Gobbo & Luis Alberto Bertolucci Paes, 2022. "Unfolding research themes for industrial symbiosis and underlying theories," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1682-1702, December.
    11. Antonio-José Moreno-Guerrero & Gerardo Gómez-García & Jesús López-Belmonte & Carmen Rodríguez-Jiménez, 2020. "Internet Addiction in the Web of Science Database: A Review of the Literature with Scientific Mapping," IJERPH, MDPI, vol. 17(8), pages 1-16, April.

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