Exploring Business Analytics Initiatives in the Accounting Literature: are all accounting areas equal?
DOI:
https://doi.org/10.14392/asaa.2024170211Keywords:
Business Analytics, Accounting Information Systems, Accounting AreasAbstract
Objectives: The goal of our research is to understand why Business Analytics (BA) practices are selected and how they are adopted across various accounting areas. To achieve this, our study maps and analyzes the analytics initiatives documented in the literature that have been adopted by the accounting profession, categorizing these initiatives by accounting area.
Method: We conducted a Systematic Literature Review, drawing on publications from the Web of Science and Scopus databases, as well as prominent journals in Information Systems and Accounting Information Systems. Data analysis utilized categorical content analysis with theory- and data-driven codes, aligned with research objectives.
Results: Our results provide a comprehensive mapping of Business Analytics literature in accounting, detailing the dimensions - Domain, Orientation, and Technique - by accounting area. This mapping provides a deeper understanding of the relationship between the specific characteristics of each accounting area and the use of Business Analytics. Additionally, we propose a taxonomy based on usage purposes in each area. Finally, we present a research agenda, summarizing key contributions and offering suggestions for future research.
Contributons: This research contributes academically by enabling a comparison of Business Analytics adoption and use across different accounting areas, highlighting those with greater maturity in Business Analytics. Additionally, the proposed taxonomy, which considers the purpose of BA within these accounting areas, helps clarify and promote alignment between the accounting discipline and analytics techniques, reducing both conceptual and practical confusion. Furthermore, this research serves as a foundation for accounting professionals to develop their skills in analytics initiatives.
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References
Ahmad, F. (2019). A systematic review of the role of Big Data Analytics in reducing the influence of cognitive errors on the audit judgement. Revista de Contabilidad-Spanish Accounting Review, 22(2), 187-202. https://doi.org/10.6018/rcsar.382251
Al-Htaybat, K., & von Alberti-Alhtaybat, L. (2017). Big Data and corporate reporting: impacts and paradoxes. Accounting, Auditing & Accountability Journal, 30(4), 850-873. https://doi.org/10.1108/AAAJ-07-2015-2139
Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017a). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29-44. https://doi.org/10.1016/j.accinf.2017.03.003
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017b). Big Data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1-27. https://doi.org/10.2308/ajpt-51684
Araújo, L., Behr, A., & Schiavi, G. S. (2023). Adoção de business analytics na contabilidade. Revista Contabilidade & Finanças, 34, e1771. https://doi.org/10.1590/1808-057x20231771.en
Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., & Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of business research, 96, 228-237. https://doi.org/10.1016/j.jbusres.2018.11.028
Bardin, L. 1977. Content Analysis – São Paulo. Edições 70, 2011(in portuguese)
Bhimani, A., & Willcocks, L. (2014). Digitisation,‘Big Data’and the transformation of
accounting information. Accounting and Business Research, 44(4), 469-490. https://doi.org/10.1080/00014788.2014.910051
Božič, K., & Dimovski, V. (2019). Business intelligence and analytics use, innovation ambidexterity, and firm performance: A dynamic capabilities perspective. The Journal of Strategic Information Systems, 28(4), 101578. https://doi.org/10.1016/j.jsis.2019.101578
Camm, J. D., Bowers, M.R. & Davenport, T.H. (2020, June 16). The Recession’s Impact on Analytics and Data Science. MIT Sloan Management Review. Recuperado em 03 de julho, 2020, de https://sloanreview.mit.edu/article/the-recessions-impact-on-analytics-and-data-science/
Cangemi, M. P. (2017). Addressing the C-Level Question: How Effectively are Assurance Functions Contributing and Using Automated Analytics?. EDPACS, 55(5), 1-12. https://doi.org/10.1080/07366981.2017.1324702
Cavalcanti, C. X., & Silva, A. R. L. D. (2020). Business analytics and sociomateriality: A study on the practice of revenue management in an airline company. BBR. Brazilian Business Review, 17(4), 419-438. https://doi.org/10.15728/bbr.2020.17.4.4
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188. https://doi.org/10.2307/41703503
Cheng, C., Sapkota, P., & Yurko, A. J. (2021). A case study of effective tax rates using data analytics. Issues in Accounting Education, 36(1), 65-89. https://doi.org/10.2308/ISSUES-19-060
Cockcroft, S., & Russell, M. (2018). Big data opportunities for accounting and finance practice and research. Australian Accounting Review, 28(3), 323-333. https://doi.org/10.1111/auar.12218
Coyne, E. M., Coyne, J. G., & Walker, K. B. (2018). Big Data information governance by accountants. International Journal of Accounting & Information Management, 26(1), 153-170. https://doi.org/10.1108/IJAIM-01-2017-0006
Davenport, T. H., Barth, P., & Bean, R. (2012). How'big data'is different. MIT Sloan Management Review.
Davenport, T., & Harris, J. (2017). Competing on analytics: Updated, with a new introduction: The new science of winning. Harvard Business Press.
Deloitte (2020). O futuro da área de finanças – uma visão a ser compartilhada. Recuperado em 03 de julho, 2020, de https://www2.deloitte.com/content/dam/Deloitte/br/Documents/finance/cfo/CFO-futuro-financas.pdf
Dzuranin, A. C., Jones, J. R., & Olvera, R. M. (2018). Infusing data analytics into the accounting curriculum: A framework and insights from faculty. Journal of Accounting Education, 43, 24-39. https://doi.org/10.1016/j.jaccedu.2018.03.004
Earley, C. E. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493-500. https://doi.org/10.1016/j.bushor.2015.05.002
Elshandidy, T., Shrives, P. J., Bamber, M., & Abraham, S. (2018). Risk reporting: A review of the literature and implications for future research. Journal of Accounting Literature, 40, 54-82. https://doi.org/10.1016/j.acclit.2017.12.001
Gal, G., Singh, K., & Best, P. (2016). Interactive visual analysis of anomalous accounts payable transactions in SAP enterprise systems. Managerial Auditing Journal, 31(1), 35-63. https://doi.org/10.1108/MAJ-10-2014-1117
Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102-115. https://doi.org/10.1016/j.acclit.2017.05.003
Gerhardt, T. E., & Silveira, D. T. (2009). Métodos de pesquisa. Plageder.
Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
Holsapple, C., Lee-Post, A., & Pakath, R. (2014). A unified foundation for business analytics. Decision Support Systems, 64, 130-141. https://doi.org/10.1016/j.dss.2014.05.013
Knudsen, D. R. (2020). Elusive boundaries, power relations, and knowledge production: A systematic review of the literature on digitalization in accounting. International Journal of Accounting Information Systems, 36, 100441. https://doi.org/10.1016/j.accinf.2019.100441
Lamboglia, R., Lavorato, D., Scornavacca, E., & Za, S. (2020). Exploring the relationship between audit and technology. A bibliometric analysis. Meditari Accountancy Research, 29(5), 1233-1260. https://doi.org/10.1108/MEDAR-03-2020-0836
Lee, J. H., & Park, S. C. (2005). Intelligent profitable customers segmentation system based on business intelligence tools. Expert systems with applications, 29(1), 145-152. https://doi.org/10.1016/j.eswa.2005.01.013
Medeiros, M. M., Maçada, A. C. G., & Hoppen, N. (2021). O papel da administração e análise de big data como habilitadoras da gestão do desempenho corporativo. Revista de Administração Mackenzie, 22(6), 1–32. doi:10.1590/1678-6971/eRAMD210063
MicroStrategy (2020). 2020 Global State of Enterprise Analytics: minding the data-drive gap. Virginia: MicroStrategy.
Milhomem, L. D. S., Sincorá, L. A., Oliveira, M. P. V. D., & Brandão, M. M. (2022). The Impact of Business Analytics on Collaborative Advantage: the mediating role of managing transaction costs. BBR. Brazilian Business Review, 19, 59-77. https://doi.org/10.15728/bbr.2022.19.1.4
Mustikarini, A. and Adhariani, D. (2021). In auditor we trust: 44 years of research on the auditor-client relationship and future research directions. Meditari Accountancy Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MEDAR-11-2020-1062.
Nielsen, S. (2018). Reflections on the applicability of business analytics for management accounting–and future perspectives for the accountant. Journal of Accounting & Organizational Change, 14(2), 167-187. https://doi.org/10.1108/JAOC-11-2014-0056
Phillips-Wren, G., Daly, M., & Burstein, F. (2021). Reconciling business intelligence, analytics and decision support systems: More data, deeper insight. Decision Support Systems, 146, 113560. https://doi.org/10.1016/j.dss.2021.113560
Rezaee, Z., Dorestani, A., & Aliabadi, S. (2018). Application of Time Series Analyses in Big Data: Practical, Research, and Education Implications. Journal of Emerging Technologies in Accounting, 15(1), 183-197. https://doi.org/10.2308/jeta-51967
Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big Data analytics: Opportunity or threat for the accounting profession?. Journal of Information Systems, 31(3), 63-79. https://doi.org/10.2308/isys-51805
Rikhardsson, P., & Yigitbasioglu, O. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29, 37-58. https://doi.org/10.1016/j.accinf.2018.03.001
Rozario, A. M., & Issa, H. (2020). Risk-based data analytics in the government sector: A case study for a US county. Government Information Quarterly, 37(2), 101457. https://doi.org/10.1016/j.giq.2020.101457
Schneider, G. P., Dai, J., Janvrin, D. J., Ajayi, K., & Raschke, R. L. (2015). Infer, predict, and assure: Accounting opportunities in data analytics. Accounting Horizons, 29(3), 719-742. https://doi.org/10.2308/acch-51140
Singh, N., Lai, K. H., Vejvar, M., & Cheng, T. E. (2019). Data driven auditing: A predictive modeling approach to fraud detection and classification. Journal of Corporate Accounting & Finance, 30(3), 64-82. https://doi.org/10.1002/jcaf.22389
Spraakman, G., Sanchez-Rodriguez, C., & Tuck-Riggs, C. A. (2020). Data analytics by management accountants. Qualitative Research in Accounting & Management, 18(1), 127-147. https://doi.org/10.1108/QRAM-11-2019-0122
Tang, F., Norman, C. S., & Vendrzyk, V. P. (2017). Exploring perceptions of data analytics in the internal audit function. Behaviour & Information Technology, 36(11), 1125-1136. https://doi.org/10.1080/0144929X.2017.1355014
Tangen, S. (2005). Demystifying productivity and performance, International Journal of Productivity and Performance Management, 54(1), 34-46. https://doi.org/10.1108/17410400510571437
Trieu, V. H. (2017). Getting value from Business Intelligence systems: A review and research agenda. Decision Support Systems, 93, 111-124. https://doi.org/10.1016/j.dss.2016.09.019
Urbaczewski, A. & Keeling, K. B. (2019). Invited Paper: The Transition from MIS Departments to Analytics Departments. Journal of Information Systems Education, 30(4), 303-310.
Uyar, M. (2021). The role of business analytics in transforming management accounting information into cost performance. Ege Academic Review, 21(4), 373-389. https://doi.org/10.21121/eab.1015665
Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626-639. https://doi.org/10.1016/j.ejor.2017.02.023
Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, xiii-xxiii.
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Copyright (c) 2024 Leticia Silva Araujo, Ariel Behr, Carla Marcolin, Eusebio Scornavacca
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