Abstract
The digitalization of industry, the growth and development of artificial intelligence are attributed to the advent of big data and hence there has been increased interest in research into business analytics, business intelligence, and big data analytics. Business analytics is seen as a complex continuum of data analytics, statistical analytics, and the ability to gain information and knowledge for decision-making. Business analytics is generally understood to support the information society, knowledge-based economy, and digital innovation. The research publications in business analytics have by and large been systematic reviews of literature with a limited number of empirical studies in business analytics. Hence, this paper seeks to review some of the most significant extant literature on business analytics while emphasizing on important theoretical and empirical contributions relating to business analytics in industry, education, and professional training. Second, this paper proposes future issues relating to business intelligence, advanced data mining, applied analytics, and reporting.
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References
Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44.
Bayrak, T. (2015). A review of business analytics: A business enabler or another passing fad. Procedia-Social and Behavioral Sciences, 195, 230–239.
Brock, V. F., & Khan, H. U. (2017). Are enterprises ready for big data analytics? A survey-based approach. International Journal of Business Information Systems, 25(2), 256–277.
Calof, J., Richards, G., & Smith, J. (2015). Foresight, competitive intelligence and business analytics—Tools for making industrial programmes more efficient. Journal of the National Research University Higher School of Economics., 9(1), 68–81.
Chae, B., & Olson, D. (2013). Business analytics for supply chain: A dynamic-capabilities framework. International Journal of Information Technology & Decision Making, 12, 9–26. https://doi.org/10.1142/S0219622013500016
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 1165–1188.
El Alfy, S., Gómez, J. M., & Dani, A. (2019). Exploring the benefits and challenges of learning analytics in higher education institutions: A systematic literature review. Information Discovery and Delivery., 47(1), 25–34.
Gorman, M. F., & Klimberg, R. K. (2014). Benchmarking academic programs in business analytics. Interfaces, 44(3), 329–341.
Griva, A., Bardaki, C., Pramatari, K., & Papakiriakopoulos, D. (2016). Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications, 100, 1–16.
Jahantigh, F. F., Habibi, A., & Sarafrazi, A. (2019). A conceptual framework for business intelligence critical success factors. International Journal of Business Information Systems, 30(1), 109–123.
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.
Okoli, C. (2015). A guide to conducting a standalone systematic literature review. Communications of the Association for Information Systems, 37(1), 43.
Parks, R., & Thambusamy, R. (2017). Understanding business analytics success and impact: A qualitative study. Information Systems Education Journal, 15(6), 43.
Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decision Support Systems, 54(1), 729–739.
Priya, L. K., Devi, M. K., & Nagarajan, S. (2017). Data analytics: Feature extraction for application with small sample in classification algorithms. International Journal of Business Information Systems, 26(3), 378–401.
Sharda, R., Asamoah, D. A., & Ponna, N. (2013). Research and pedagogy in business analytics: Opportunities and illustrative examples. Journal of Computing and Information Technology, 21(3), 171–183.
Shen, K. Y., & Tzeng, G. H. (2016). Contextual improvement planning by fuzzy-rough machine learning: A novel bipolar approach for business analytics. International Journal of Fuzzy Systems, 18(6), 940–955.
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of big data challenges and analytical methods. Journal of Business Research, 70, 263–286.
Troilo, M., Bouchet, A., Urban, T. L., & Sutton, W. A. (2016). Perception, reality, and the adoption of business analytics: Evidence from north American professional sport organizations. Omega, 59, 72–83.
Vanani, I. R., & Jalali, S. M. J. (2018). A comparative analysis of emerging scientific themes in business analytics. International Journal of Business Information Systems, 29(2), 183–206.
Varshney, K. R., & Mojsilović, A. (2011). Business analytics based on financial time series. IEEE Signal Processing Magazine, 28(5), 83–93.
Ward, M. J., Marsolo, K. A., & Froehle, C. M. (2014). Applications of business analytics in healthcare. Business Horizons, 57(5), 571–582.
Wixom, B. H., Yen, B., & Relich, M. (2013). Maximizing value from business analytics. MIS Quarterly Executive, 12(2).
Yesufu, L. O. (2018). Motives and measures of higher education internationalisation: A case study of a Canadian university. International Journal of Higher Education, 7(2), 155–168.
Yesufu, L. O. (2020). The impact of employee type, professional experience and academic discipline on the psychological contract of academics. International Journal of Management in Education, 14(3), 311–329.
Yesufu, L. O. (2021). Predictive learning analytics in higher education. In Data analytics in marketing, entrepreneurship, and innovation (p. 151).
Yin, J., & Fernandez, V. (2020). A systematic review on business analytics. Journal of Industrial Engineering and Management, 13(2), 283–295.
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Yesufu, L.O., Alajlani, S. (2022). The Impact of Business Analytics on Industry, Education, and Professional Development. In: Marx Gómez, J., Yesufu, L.O. (eds) Sustainable Development Through Data Analytics and Innovation. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-031-12527-0_1
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