Inteligência empresarial e o seu papel na geração de valor nos processos empresariais
DOI:
https://doi.org/10.22267/rtend.222302.222Palavras-chave:
administração de empresas, análise de dados, inteligência artificial, tecnologia da informação, tomada de decisões, sistemas especializadosResumo
O presente artigo tem como objetivo explorar a inteligência empresarial e seu papel na geração de valor nos processos de negócios; assim, esta bibliometria recoge, sintetiza e analisa 104 artigos sobre uma variedade de temas estreitamente relacionados com a Inteligência Empresarial (Business Intelligence – [BI]), e artigos publicados no período de 2009 a 2022, relacionados com o tema. A metodologia é de tipo qualitativo, para que se utilize a base de dados do Scopus. Alguns dos principais hallazgos sugeriram que existe uma associação entre inteligência empresarial e a competitividade, além de se encontrarem que é necessário ampliar as abordagens de BI para mitigar lagunas de conhecimento nesta área do conhecimento. Finalmente, fica evidenciado que o BI fornece um marco teórico e empírico para o desenvolvimento de uma teoria consistente, assim como uma base para o logro de um ES competitivo de alto nível.
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Referências
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(3) 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
(4) Al-edenat, M. & Alhawamdeh, N. (2022). Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediation-moderation model. Business: Theory and Practice, 23(2), 239-251. https://doi.org/10.3846/btp.2022.16548
(5) 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
(6) 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
(7) 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
(8) 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
(9) 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
(10) 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
(11) 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
(12) 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
(13) 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
(14) Candra, S. & Nainggolan, A. (2022). Understanding Business Intelligence and Analytics System Success from Various Business Sectors in Indonesia. CommIT Journal, 16(1), 37-52.
(15) 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
(16) 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
(17) 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
(18) 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
(19) 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
(20) 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
(21) 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
(22) 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
(23) 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
(24) 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.
(25) 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
(26) 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
(27) 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
(28) 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
(29) 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
(30) Kapil, S., Sharma, K. & Bajaj, M. (2022). DeepWalk Based Influence Maximization (DWIM): Influence Maximization Using Deep Learning. Intelligent Automation & Soft Computing, 35(1), 1087-1101. https://doi.org/10.32604/iasc.2023.026134
(31) Khaled, A. S., Sharma, D. K., Yashwanth, T., Reddy, V. M. K., Doewes, R. & Naved, M. (2022). Evaluating the Role of Robotics, Machine Learning and Artificial Intelligence in the Field of Performance Management. In S. Yadav, A. Haleem, P. Arora & H. Kumar. (Eds.), Proceedings of Second International Conference in Mechanical and Energy Technology (285-299). Editorial Springer, Singapore. https://doi.org/10.1007/978-981-19-0108-9_30
(32) Kumar, D., Kr Singh, R., Mishra, R. & Fosso, S. (2022). Applications of the internet of things for optimizing warehousing and logistics operations: A systematic literature review and future research directions. Computers & Industrial Engineering, 171, 108455. https://doi.org/10.1016/j.cie.2022.108455
(33) Laqua, I. (2010). Der sinnvolle Einsatz von Business Intelligence-Systemen in der Produktion. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 105(3), 237-240. https://doi.org/10.3139/104.110268
(34) Li, J. & Lakzi, A. (2022). A new model for assessing the role of IT-based systems, public policies and business intelligence on the export competitiveness’s efficiency. Kybernetes, 51(1), 77-94. https://doi.org/10.1108/K-07-2020-0430
(35) Mahayossanand, R., Chaipatnithikul, P., Chintrakul, N. & Nananukul, N. (2017). Business intelligence for online advertising. Advanced Science Letters, 23(5), 4091-4096. https://doi.org/10.1166/asl.2017.8326
(36) Mangwayana, T. B. & Budree, A. (2021). Technical capabilities of business intelligence systems in South African medium to large organisations. International Journal of Business Intelligence and Data Mining, 20(1), 77-92. https://doi.org/10.1504/IJBIDM.2022.120032
(37) Mashingaidze, K. & Backhouse, J. (2017). The relationships between definitions of big data, business intelligence and business analytics: A literature review. International Journal of Business Information Systems, 26(4), 488-505. https://doi.org/10.1504/IJBIS.2017.087749
(38) Mezzour, G., Boudanga, Z. & Benhadou, S. (2020). Smart pandemic management through a smart, resilient and flexible decision-making system. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 285-294. https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-285-2020
(39) Mishra, B. K., Hazra, D., Tarannum, K., & Kumar, M. (2016, 25-27 de November). Business intelligence using data mining techniques and business analytics [conference]. 2016 International Conference System Modeling & Advancement in Research Trends (SMART), Moradabad, India. https://ieeexplore.ieee.org/xpl/conhome/7891863/proceeding
(40) Mollekopf, H. (2009). Nutzen von Business Intelligence-Systemen. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 104(5), 411-414. https://doi.org/10.3139/104.110077
(41) Muthukumaran, K. & Hariharanath, K. (2022). Deep Learning Enabled Financial Crisis Prediction Model for Small-Medium Sized Industries. Intelligent Automation & Soft Computing, 35(1), 521-536. https://doi.org/10.32604/iasc.2023.025968
(42) O’Donnell, P., Sipsma, S. & Watt, C. (2012). The critical issues facing business intelligence practitioners. Journal of Decision Systems, 21(3), 203-216. https://doi.org/10.1080/12460125.2012.731967
(43) Paulino, E. (2022). Amplifying organizational performance from business intelligence: Business analytics implementation in the retail industry. Journal of Entrepreneurship, Management and Innovation, 18(2), 69-104. https://doi.org/10.7341/20221823
(44) Souibgui, M., Atigui, F., Zammali, S., Cherfi, S. & Yahia, S. (2019). Data quality in ETL process: A preliminary study. Procedia Computer Science, 159, 676-687. https://doi.org/10.1016/j.procs.2019.09.223
(45) Sriram, V. P., Sujith, A. V., Bharti, A., Jena, S. K., Sharma, D. K. & Naved, M. (2022). A Critical Analysis of Machine Learning’s Function in Changing the Social and Business Ecosystem. In S. Yadav, A. Haleem, P. Arora & H. Kumar. (Eds.), Proceedings of Second International Conference in Mechanical and Energy Technology (pp. 285-299). Editorial Springer, Singapore. https://doi.org/10.1007/978-981-19-0108-9_36
(46) Tarek, B. H. & Adel, G. (2016). Business Intelligence versus Entrepreneurial Competitive Intelligence and International Competitiveness of North African SMEs. Journal of International Entrepreneurship, 14(4), 539-561. https://doi.org/10.1007/s10843-016-0194-8
(47) Upadhyay, N., Upadhyay, S., Al-Debei, M. M., Baabdullah, A. M. & Dwivedi, Y. K. (2022). The influence of digital entrepreneurship and entrepreneurial orientation on intention of family businesses to adopt artificial intelligence: examining the mediating role of business innovativeness. International Journal of Entrepreneurial Behaviour and Research. https://doi.org/10.1108/IJEBR-02-2022-0154
(48) Wee, M., Scheepers, H. & Tian, X. (2022). The role of leadership skills in the adoption of business intelligence and analytics by SMEs. Information Technology & People. https://doi.org/10.1108/ITP-09-2021-0669
(49) Yang, M., Sulaiman, R., Yin, Y., Mallamaci, V. & Alrabaiah, H. (2022). The effect of business intelligence, organizational learning and innovation on the financial performance of innovative companies located in Science Park. Information Processing and Management, 59(2), 102852. https://doi.org/10.1016/j.ipm.2021.102852
(50) Zheng, W., Wu, Y. C. & Chen, L. (2018). Business intelligence for patient-centeredness: A systematic review. Telematics and Informatics, 35(4), 665-676. https://doi.org/10.1016/J.TELE.2017.06.015
(2) 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
(3) 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
(4) Al-edenat, M. & Alhawamdeh, N. (2022). Reconsidering individuals’ competencies in business intelligence and business analytics toward process effectiveness: mediation-moderation model. Business: Theory and Practice, 23(2), 239-251. https://doi.org/10.3846/btp.2022.16548
(5) 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
(6) 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
(7) 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
(8) 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
(9) 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
(10) 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
(11) 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
(12) 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
(13) 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
(14) Candra, S. & Nainggolan, A. (2022). Understanding Business Intelligence and Analytics System Success from Various Business Sectors in Indonesia. CommIT Journal, 16(1), 37-52.
(15) 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
(16) 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
(17) 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
(18) 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
(19) 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
(20) 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
(21) 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
(22) 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
(23) 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
(24) 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.
(25) 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
(26) 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
(27) 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
(28) 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
(29) 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
(30) Kapil, S., Sharma, K. & Bajaj, M. (2022). DeepWalk Based Influence Maximization (DWIM): Influence Maximization Using Deep Learning. Intelligent Automation & Soft Computing, 35(1), 1087-1101. https://doi.org/10.32604/iasc.2023.026134
(31) Khaled, A. S., Sharma, D. K., Yashwanth, T., Reddy, V. M. K., Doewes, R. & Naved, M. (2022). Evaluating the Role of Robotics, Machine Learning and Artificial Intelligence in the Field of Performance Management. In S. Yadav, A. Haleem, P. Arora & H. Kumar. (Eds.), Proceedings of Second International Conference in Mechanical and Energy Technology (285-299). Editorial Springer, Singapore. https://doi.org/10.1007/978-981-19-0108-9_30
(32) Kumar, D., Kr Singh, R., Mishra, R. & Fosso, S. (2022). Applications of the internet of things for optimizing warehousing and logistics operations: A systematic literature review and future research directions. Computers & Industrial Engineering, 171, 108455. https://doi.org/10.1016/j.cie.2022.108455
(33) Laqua, I. (2010). Der sinnvolle Einsatz von Business Intelligence-Systemen in der Produktion. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 105(3), 237-240. https://doi.org/10.3139/104.110268
(34) Li, J. & Lakzi, A. (2022). A new model for assessing the role of IT-based systems, public policies and business intelligence on the export competitiveness’s efficiency. Kybernetes, 51(1), 77-94. https://doi.org/10.1108/K-07-2020-0430
(35) Mahayossanand, R., Chaipatnithikul, P., Chintrakul, N. & Nananukul, N. (2017). Business intelligence for online advertising. Advanced Science Letters, 23(5), 4091-4096. https://doi.org/10.1166/asl.2017.8326
(36) Mangwayana, T. B. & Budree, A. (2021). Technical capabilities of business intelligence systems in South African medium to large organisations. International Journal of Business Intelligence and Data Mining, 20(1), 77-92. https://doi.org/10.1504/IJBIDM.2022.120032
(37) Mashingaidze, K. & Backhouse, J. (2017). The relationships between definitions of big data, business intelligence and business analytics: A literature review. International Journal of Business Information Systems, 26(4), 488-505. https://doi.org/10.1504/IJBIS.2017.087749
(38) Mezzour, G., Boudanga, Z. & Benhadou, S. (2020). Smart pandemic management through a smart, resilient and flexible decision-making system. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 285-294. https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-285-2020
(39) Mishra, B. K., Hazra, D., Tarannum, K., & Kumar, M. (2016, 25-27 de November). Business intelligence using data mining techniques and business analytics [conference]. 2016 International Conference System Modeling & Advancement in Research Trends (SMART), Moradabad, India. https://ieeexplore.ieee.org/xpl/conhome/7891863/proceeding
(40) Mollekopf, H. (2009). Nutzen von Business Intelligence-Systemen. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 104(5), 411-414. https://doi.org/10.3139/104.110077
(41) Muthukumaran, K. & Hariharanath, K. (2022). Deep Learning Enabled Financial Crisis Prediction Model for Small-Medium Sized Industries. Intelligent Automation & Soft Computing, 35(1), 521-536. https://doi.org/10.32604/iasc.2023.025968
(42) O’Donnell, P., Sipsma, S. & Watt, C. (2012). The critical issues facing business intelligence practitioners. Journal of Decision Systems, 21(3), 203-216. https://doi.org/10.1080/12460125.2012.731967
(43) Paulino, E. (2022). Amplifying organizational performance from business intelligence: Business analytics implementation in the retail industry. Journal of Entrepreneurship, Management and Innovation, 18(2), 69-104. https://doi.org/10.7341/20221823
(44) Souibgui, M., Atigui, F., Zammali, S., Cherfi, S. & Yahia, S. (2019). Data quality in ETL process: A preliminary study. Procedia Computer Science, 159, 676-687. https://doi.org/10.1016/j.procs.2019.09.223
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Publicado
2023-01-01
Como Citar
Martínez Zabaleta, M. E., & Rodríguez Luna, R. E. (2023). Inteligência empresarial e o seu papel na geração de valor nos processos empresariais. Tendencias, 24(1), 226–251. https://doi.org/10.22267/rtend.222302.222
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