Business intelligence and its role in generating value in business processes
DOI:
https://doi.org/10.22267/rtend.222302.222Keywords:
artificial intelligence, business administration, data analysis, decision making, expert systems, information technologyAbstract
The present article aims to explore business intelligence and its role in the generation of value in business processes; thus, this bibliometry collects, synthesizes and analyzes 104 articles on a variety of topics closely related to Business Intelligence (Business Intelligence – [BI]), and articles published in the period 2009 to 2022, related to the subject matter. The methodology is of a qualitative type, for which the Scopus database was used. Some of the main hallmarks suggest that there is an association between business intelligence and competitiveness, in addition to the fact that it is necessary to expand BI approaches to mitigate knowledge gaps in this area of knowledge. Finally, it was shown 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 SE.
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References
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(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
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(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
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(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
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(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
(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
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Published
2023-01-01
How to Cite
Martínez Zabaleta, M. E., & Rodríguez Luna, R. E. (2023). Business intelligence and its role in generating value in business processes. Tendencias, 24(1), 226–251. https://doi.org/10.22267/rtend.222302.222
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