Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios

El presente artículo tiene como objetivo explorar la inteligencia empresarial y su rol en la generación de valor en los procesos de negocios; así, esta bibliometría recoge, sintetiza y analiza 104 artículos sobre una variedad de temas estrechamente relacionados con la Inteligencia Empresarial (BI, a...

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Autores:
Martínez Zabaleta , Mercedes
Rodríguez Luna , Raúl
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Universidad Cooperativa de Colombia
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Repositorio UCC
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OAI Identifier:
oai:repository.ucc.edu.co:20.500.12494/52559
Acceso en línea:
https://doi.org/10.22267/rtend.222302.222
https://hdl.handle.net/20.500.12494/52559
Palabra clave:
Administración de empresas
Análisis de datos
Inteligencia artificial
Tecnología de la información
Toma de decisiones
Sistema experto
Artificial intelligence
Business administration
Data analysis
Decision making
Expert systems
Information technology
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openAccess
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Atribución – No comercial – Sin Derivar
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dc.title.none.fl_str_mv Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
title Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
spellingShingle Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
Administración de empresas
Análisis de datos
Inteligencia artificial
Tecnología de la información
Toma de decisiones
Sistema experto
Artificial intelligence
Business administration
Data analysis
Decision making
Expert systems
Information technology
title_short Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
title_full Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
title_fullStr Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
title_full_unstemmed Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
title_sort Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios
dc.creator.fl_str_mv Martínez Zabaleta , Mercedes
Rodríguez Luna , Raúl
dc.contributor.author.none.fl_str_mv Martínez Zabaleta , Mercedes
Rodríguez Luna , Raúl
dc.subject.none.fl_str_mv Administración de empresas
Análisis de datos
Inteligencia artificial
Tecnología de la información
Toma de decisiones
Sistema experto
topic Administración de empresas
Análisis de datos
Inteligencia artificial
Tecnología de la información
Toma de decisiones
Sistema experto
Artificial intelligence
Business administration
Data analysis
Decision making
Expert systems
Information technology
dc.subject.other.none.fl_str_mv Artificial intelligence
Business administration
Data analysis
Decision making
Expert systems
Information technology
description El presente artículo tiene como objetivo explorar la inteligencia empresarial y su rol en la generación de valor en los procesos de negocios; así, esta bibliometría recoge, sintetiza y analiza 104 artículos sobre una variedad de temas estrechamente relacionados con la Inteligencia Empresarial (BI, abreviatura tomada del inglés) y artículos publicados en el periodo 2009 a 2022, relacionados con el tema objeto. La metodología es de tipo cualitativo, para ello se utilizó la base de datos de Scopus. Algunos de los principales hallazgos sugieren que, existe una asociación entre inteligencia empresarial y la competitividad, además se encontró que es necesario ampliar los enfoques BI para mitigar lagunas de conocimiento en esta área del saber. Finalmente, se evidenció que BI proporciona un marco teórico y empírico para el desarrollo de una teoría consistente, así como una base para el logro de una estrategia empresarial competitiva de alto nivel.
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-08-28T20:05:21Z
dc.date.available.none.fl_str_mv 2023-08-28T20:05:21Z
dc.date.issued.none.fl_str_mv 2023-01-01
dc.type.none.fl_str_mv Artículos Científicos
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https://hdl.handle.net/20.500.12494/52559
dc.identifier.bibliographicCitation.none.fl_str_mv Martínez Zabaleta, M. E., & Rodríguez Luna, R. E. (2023). Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios. Tendencias, 24(1), 226–251. https://doi.org/10.22267/rtend.222302.222
identifier_str_mv 25390554
Martínez Zabaleta, M. E., & Rodríguez Luna, R. E. (2023). Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios. Tendencias, 24(1), 226–251. https://doi.org/10.22267/rtend.222302.222
url https://doi.org/10.22267/rtend.222302.222
https://hdl.handle.net/20.500.12494/52559
dc.relation.isversionof.none.fl_str_mv https://revistas.udenar.edu.co/index.php/rtend/article/view/7918
dc.relation.ispartofjournal.none.fl_str_mv Tendencias
dc.relation.references.none.fl_str_mv Ahmad, H. & Mustafa, H. (2022). The impact of artificial intelligence, big data analytics and business intelligence on transforming capability and digital transformation in Jordanian telecommunication firms. International Journal of Data and Network Science, 6(3), 727-732. https://doi.org/10.5267/j.ijdns.2022.3.009
Ahumada, E. y Perusquia, J. M. (2016). Inteligencia de Negocios: Estrategia para el Desarrollo de Competitividad en Empresas de Base Tecnológica en Tijuana, B.C. Contaduría y Administración, 61(1), 127-158. https://doi.org/10.1016/j.cya.2015.09.006
Ain, N., Vaia, G., DeLone, W. H. & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success – A systematic literature review. Decision Support Systems, 125, 113113. https://doi.org/10.1016/j.dss.2019.113113
Al-edenat, M. & Alhawamdeh, N. (2022). Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediationmoderation model. Business: Theory and Practice, 23(2), 239-251. https://doi.org/10.3846/btp.2022.16548
Ali, I., Balta, M. & Papadopoulos, T. (2022). Social media platforms and social enterprise: Bibliometric analysis and systematic review. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2022.102510
Arnott, D., Lizama, F. & Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, 58-68. https://doi.org/10.1016/J.DSS.2017.03.005
Asokan, D. R., Huq, F. A., Smith, C. M. & Stevenson, M. (2022). Socially responsible operations in the Industry 4.0 era: post-COVID-19 technology adoption and perspectives on future research. International Journal of Operations & Production Management, 42(13), 185- 217. https://doi.org/10.1108/IJOPM-01-2022-0069
Awawdeh, H., Abulaila, H., Alshanty, A. & Alzoubi, A. (2022). Digital entrepreneurship and its impact on digital supply chains: The mediating role of business intelligence applications. International Journal of Data and Network Science, 6(1), 233-242. https://doi.org/10.5267/J.IJDNS.2021.9.005
Bag, S., Yadav, G., Dhamija, P. & Kataria, K. (2021). Key resources for industry 4.0 adoption and its effect on sustainable production and circular economy: An empirical study. Journal of Cleaner Production, 281, 125233. https://doi.org/10.1016/j.jclepro.2020.125233
Balamurugan, S., Ayyasamy, A. & Suresh, J. (2020). Iot based supply chain traceability using enhanced naive bayes approach for scheming the food safety issues. International Journal of Scientific and Technology Research, 9(3), 1184-1192 https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85084209108&partnerID=40&md5=56174787d3b52fa0e9f2b30997a614
Boonsiritomachai, W., McGrath, G. M. & Burgess, S. (2016). Exploring business intelligence and its depth of maturity in Thai SMEs. Cogent Business and Management, 3(1) https://doi.org/10.1080/23311975.2016.1220663
Bordeleau, F. E., Mosconi, E. & de Santa, L. A. (2020). Business intelligence and analytics value creation in Industry 4.0: a multiple case study in manufacturing medium enterprises. Production Planning and Control, 31(2-3), 173-185. https://doi.org/10.1080/09537287.2019.1631458
Brooks, P., El-Gayar, O. & Sarnikar, S. (2013, 7-10 de enero). Towards a business intelligence maturity model for healthcare [conferencia]. 46th Hawaii International Conference on System Sciences, Wailea, HI, EE. UU. https://ieeexplore.ieee.org/xpl/conhome/6479598/proceeding
Candra, S. & Nainggolan, A. (2022). Understanding Business Intelligence and Analytics System Success from Various Business Sectors in Indonesia. CommIT Journal, 16(1), 37-52.
Carbajal, A., Ninaquispe, J. & Cabanillas, M. (2022). Business Intelligence in Strategic Business Decision Making in Times of COVID-19: A Systematic Review of the Literature. In X. Yang, S. Sherratt, N. Dey & A. Joshi. (Eds.), Proceedings of Seventh International Congress on Information and Communication Technology (pp. 425-435). Editorial Springer. https://link.springer.com/book/10.1007/978-981-19-2394-4
Cardoso, E. & Su, X. (2022). Designing a Business Intelligence and Analytics Maturity Model for Higher Education: A Design Science Approach. Applied Sciences, 12(9), 4625. https://doi.org/10.3390/app12094625
Chugh, R. & Grandhi, S. (2013). Why Business Intelligence? Significance of Business Intelligence Tools and Integrating BI Governance with Corporate Governance. International Journal of E-Entrepreneurship and Innovation, 4(2), 1-14. https://doi.org/10.4018/ijeei.2013040101
Chung, W., Pauleen, D. & Taskin, N. (2022). Enterprise systems, emerging technologies, and the data-driven knowledge organisation. Knowledge Management Research & Practice, 20(1), 1-13. https://doi.org/10.1080/14778238.2022.2039571
Elbashir, M. Z., Collier, P. A. & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9(3), 135–153. https://doi.org/10.1016/j.accinf.2008.03.001
García, C., Barón, E. y Sánchez, S. (2021). La inteligencia de negocios y la analítica de datos en los procesos empresariales. Revista Científica de Sistemas e Informática, 1(2), 38-53. https://doi.org/10.51252/rcsi.v1i2.167
Ghlala, R., Kodia, Z. & Said, L. B. (2022). Enhancing Decision-Making Consistency in Business Process using a Rule-Based Approach. Journal of Telecommunications and the Digital Economy, 10(2), 44-61. https://doi.org/10.18080/jtde.v10n2.539
Goldberg, D. M. & Abrahams, A. S. (2022). Sourcing product innovation intelligence from online reviews. Decision Support Systems, 157, 113751. https://doi.org/10.1016/j.dss.2022.113751
Hagendorff, T. (2022). A Virtue-Based Framework to Support Putting AI Ethics into Practice. Philosophy & Technology, 35(3). https://doi.org/10.1007/s13347-022-00553-z
Hsu, P. C., Huang, W. N., Kuo, K. M. & Yeh, Y. T. (2022). Application of Business Intelligence in Decision Support to Hospital Management: An Example of Outpatient Clinic Schedule Arrangement. In P. Otero, P. Scott, S. Martin & E. Huesing. (Eds.), MEDINFO 2021: One World, One Health-Global Partnership for Digital Innovation (pp. 1050-1051). Editorial IOS Press.
Huber, M., Meier, J. & Wallimann, H. (2022). Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets. Transportation Research Part B: Methodological, 163, 22-39. https://doi.org/10.1016/j.trb.2022.06.006
Jalali, S. M., Park, H., Vanani, I. & Pho, K. (2021). Research trends on big data domain using text mining algorithms. Digital Scholarship in the Humanities, 36(2), 361-370. https://doi.org/10.1093/llc/fqaa012
Janyapoon, S., Liangrokapart, J. & Tan, A. (2021). Critical Success Factors of Business Intelligence Implementation in Thai Hospitals. International Journal of Healthcare Information Systems and Informatics, 16(4), 19-21. https://doi.org/10.4018/IJHISI.20211001.oa19
Jourdan, Z., Rainer, R. K. & Marshall, T. E. (2008). Business intelligence: An analysis of the literature. Information Systems Management, 25(2), 121-131. https://doi.org/10.1080/10580530801941512
Kanchanapoom, K. & Chongwatpol, J. (2020). Applications of business intelligence and marketing analytics in the complementary and alternative medicine industry. Journal of Information Technology Teaching Cases, 11(1), 30-42. https://doi.org/10.1177/2043886920910430
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spelling Martínez Zabaleta , MercedesRodríguez Luna , RaúlVol. 24.2023-08-28T20:05:21Z2023-08-28T20:05:21Z2023-01-0125390554https://doi.org/10.22267/rtend.222302.222https://hdl.handle.net/20.500.12494/52559Martínez Zabaleta, M. E., & Rodríguez Luna, R. E. (2023). Inteligencia empresarial y su rol en la generación de valor en los procesos de negocios. Tendencias, 24(1), 226–251. https://doi.org/10.22267/rtend.222302.222El presente artículo tiene como objetivo explorar la inteligencia empresarial y su rol en la generación de valor en los procesos de negocios; así, esta bibliometría recoge, sintetiza y analiza 104 artículos sobre una variedad de temas estrechamente relacionados con la Inteligencia Empresarial (BI, abreviatura tomada del inglés) y artículos publicados en el periodo 2009 a 2022, relacionados con el tema objeto. La metodología es de tipo cualitativo, para ello se utilizó la base de datos de Scopus. Algunos de los principales hallazgos sugieren que, existe una asociación entre inteligencia empresarial y la competitividad, además se encontró que es necesario ampliar los enfoques BI para mitigar lagunas de conocimiento en esta área del saber. Finalmente, se evidenció que BI proporciona un marco teórico y empírico para el desarrollo de una teoría consistente, así como una base para el logro de una estrategia empresarial competitiva de alto nivel.This article aims to explore business intelligence and its role in generating value in business processes; Thus, this bibliometrics collects, synthesizes and analyzes 104 articles on a variety of topics closely related to Business Intelligence (BI, abbreviation taken from English) and articles published in the period 2009 to 2022, related to the subject matter. The methodology is qualitative, for this the Scopus database was used. Some of the main findings suggest that there is an association between business intelligence and competitiveness, and it was also found that it is necessary to expand BI approaches to mitigate knowledge gaps in this area of knowledge. Finally, it was evidenced that BI provides a theoretical and empirical framework for the development of a consistent theory, as well as a basis for the achievement of a high-level competitive business strategy.https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000486450https://scienti.minciencias.gov.co/cvlac/EnRecursoHumano/inicio.dohttps://orcid.org/0000-0002-1818-8975https://orcid.org/0000-0002-8718-2681mercedes.martinez@campusucc.edu.coraul.rodriguez@campusucc.edu.co226 - 251Universidad de NariñoUniversidad cooperativa de Colombia, sede Santa Marta, programa de Comercio InternacionalComercio InternacionalAdministración de EmpresasSanta Martahttps://revistas.udenar.edu.co/index.php/rtend/article/view/7918TendenciasAhmad, H. & Mustafa, H. (2022). The impact of artificial intelligence, big data analytics and business intelligence on transforming capability and digital transformation in Jordanian telecommunication firms. International Journal of Data and Network Science, 6(3), 727-732. https://doi.org/10.5267/j.ijdns.2022.3.009Ahumada, E. y Perusquia, J. M. (2016). Inteligencia de Negocios: Estrategia para el Desarrollo de Competitividad en Empresas de Base Tecnológica en Tijuana, B.C. Contaduría y Administración, 61(1), 127-158. https://doi.org/10.1016/j.cya.2015.09.006Ain, N., Vaia, G., DeLone, W. H. & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success – A systematic literature review. Decision Support Systems, 125, 113113. https://doi.org/10.1016/j.dss.2019.113113Al-edenat, M. & Alhawamdeh, N. (2022). Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediationmoderation model. Business: Theory and Practice, 23(2), 239-251. https://doi.org/10.3846/btp.2022.16548Ali, I., Balta, M. & Papadopoulos, T. (2022). Social media platforms and social enterprise: Bibliometric analysis and systematic review. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2022.102510Arnott, D., Lizama, F. & Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, 58-68. https://doi.org/10.1016/J.DSS.2017.03.005Asokan, D. R., Huq, F. A., Smith, C. M. & Stevenson, M. (2022). Socially responsible operations in the Industry 4.0 era: post-COVID-19 technology adoption and perspectives on future research. International Journal of Operations & Production Management, 42(13), 185- 217. https://doi.org/10.1108/IJOPM-01-2022-0069Awawdeh, H., Abulaila, H., Alshanty, A. & Alzoubi, A. (2022). Digital entrepreneurship and its impact on digital supply chains: The mediating role of business intelligence applications. 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