Decoding digital technology adoption in the accounting profession through theoretical lenses

Abstract

Digitalisation accounting remains in its early yet evolving stage, resulted in limited theoretical support for its adoption within accounting profession and arising the gap in identifying and aligning suitable theories which can suit with industry specific environment.  This study aims to decode the use of digital technology adoption theories in accounting research and to analyse key variables examined in digital technology adoption past studies. A two-phase of Systematic Literature Review (SLR) was conducted. The first SLR phase reviewed studies on technology adoption within the accounting profession by identifying commonly used theories. The second SLR phase focused on Technology-Organization-Environment (TOE) framework, extracting key constructs employed by prior researchers in examining factors influencing technology adoption. A total of 65 relevant articles were reviewed. The findings revealed that commonly used theories in this domain include the Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and the Technological-Organisational-Environmental (TOE) framework. This review also identified approximately over 60 variables across various studies that used the TOE framework, with fewer than 30 variables deemed most relevant and applicable for future research in the accounting profession. This study provides a structured understanding of digital technology adoption theories and key constructs within accounting domain, highlighting the limited theoretical application despite the field still at nascent phase. The identification of relavant theories and constructs offers a clearer foundation for future empirical research and theory development within accounting research. The findings also offer useful guidance for accounting practitioners, firms including audit, taxation, and advisory services, and policymakers in considering and prioritising relevant factors for digital technology adoption decision.