The predictors of the quality of accounting information system: Do big data analytics moderate this conventional linkage?

Abstract

Although accounting information systems (AIS) of firms are well-established, little is known about their effectiveness and the underlying sources essential to enhance the quality of accounting information system (QAIS). This research aims to identify the readily available resources that can be employed to enhance QAIS of relatively less studied institutions (Islamic social institutions). The theory of dynamic capability view (DCV) is underpinned to conceptualize top management support (TMS), knowledge of system users (KSU), and organizational culture (OC) as the strategic resources to enhance QAIS. Also, the use of big data analytics (UBDA) is imported as a moderator between these variables. To verify the theoretical assumptions of this study, data were drawn from 286 respondents through a personally designed survey and analyzed using the partial least square (PLS) technique. The findings confirmed that TMS and KSU are the significant and positive predictors of QAIS whereas, OC is an insignificant and positive predictor of QAIS. The moderator of UBDA has a significant positive impact on the relationship between TMS/QAIS and KSU/QAIS while an insignificant positive effect on the relationship between OC/QAIS. Our results authenticate TMS, KSU, and OC as reliable tools to enhance the QAIS and import UBDA for maintaining the effectiveness of QAIS. This study contributes to proposing a strategic solution for institutions looking to achieve and maintain a competitive advantage by ensuring effective management of QAIS through dynamic strategic resources.