Big Data Analytics and Accounting Education: A Systematic Literature Review

Abstract

Accounting professionals can contribute to forward-thinking strategic partners in the organization if they have the skills for both understanding data and solving business problems. Thereby, accountants now need to possess advanced analytical skills. These skills are required to be embedded in the accounting curriculum, in order to support the graduates in being able to extract value from big data. This chapter aims to examine the emerging themes from the systematic literature review of the big data analytics and accounting education literature. The research gaps associated with past empirical work in big data and accounting education are also identified along with the agenda for future research. The systematic quantitative literature review was conducted for big data analytics and accounting education academic articles published between 2010 and 2019 journals that are indexed in Scopus and Web of Science. The categorization and selection of articles were based on specific criteria that included: research topic, conceptual and theoretical characterization; type of data, and data collection methods. Findings show that literature on big data analytics and accounting education is limited and fragmented. In line with the professional body requirements of AICPA, AAA, and CMA, the higher education institutions have begun integrating data analytics in accounting courses. However, in some of the fields such as auditing, there are no specific professional body requirements thereby data analytics usage is not compulsory. The trend suggests that students need to be taught to understand and analyze data.