Modelling the Adoption of Big Data Analytics Among Accounting Practitioners in Nigeria

Simon Ayo ADEKUNLE; Timothy Onechojon USMAN; Oghenovo Owigho OKERE; Eseoghene KOKOGHO; Chioma Magdalene ISAIAH; Ngozi Joan ISIBOR

Simon Ayo ADEKUNLE University of Benin, Edo State
Timothy Onechojon USMAN Federal Inland Revenue Service, Abuja,
Oghenovo Owigho OKERE Senior Auditor, Deloitte & Touche LLP, Dallas, TX
Eseoghene KOKOGHO Senior Auditor, Deloitte & Touche LLP, Dallas, TX
Chioma Magdalene ISAIAH 15303 Dallas Parkway, Ste 1400, Addison, 75001, Texas, USA
Ngozi Joan ISIBOR Audit Senior, Deloitte & Touche LLP

Keywords: Accountants, Big data analytics, Data quality, Technology, Top management support

Abstract

The competitive terrains in many organisations have changed as a result of rapid development in information technology. Accounting practitioners are not exempted from this because of the unprecedented level of unstructured and semi-structured large volume of data the firms are to manage to gain competitive advantage innovatively. This study is built on the technology acceptance model to investigate and model the adoption of big data analytics among accountants using constructs such as perceived benefits, technology complexity, data quality, and IT infrastructure. The study also examined the mediating role of top management support in adopting big data analytics. Cross-sectional research design was employed by designing and distributing questionnaire electronically to accounting practitioners working in selected organisations in Nigeria. Data obtained from 264 responses were analysed descriptively and the research model estimated using regression analysis to establish the links among the variables. The results showed that perceived benefits, technology complexity, and data quality positively and significantly impact BDA adoption. IT infrastructure has a positive but non-significant impact on BDA adoption. It is recommended that organisations harness the power of big data analytics to achieve increased data value and derive valuable insights from complex datasets to make informed business decisions.