Exploring the underlying mechanisms leading to decision-making quality in business intelligence analytics-driven environments: integrated task-technology-fit and DeLone & McLean perspectives

Abstract

While numerous studies have explored the field of business intelligence and analytics systems (BIASs), few studies have focused on understanding their actual value for decision-making quality (DMQ) and the processes by which it can be achieved. To address this gap, this study aims to explore the underlying mechanisms involved in managerial DMQ. The research model consists of five core dimensions derived from the Task-Technology-Fit (TTF) and DeLone and McLean (D&M) models, namely, ‘TTF,’ ‘INTENTION TO USE,’ ‘USE,’ ‘SATISFACTION,’ and ‘NET BENEFITS,’ referred to as ‘DMQ’ for the purpose of this research. The paths assumed between these variables were built upon a unified conception between both models. Structural equation modeling under the partial least squares approach was applied to data collected from 150 BIAS users for decision-making purposes from various industries. The hypothesized paths between the investigated variables were supported, except for the one linking ‘USE’ with ‘DMQ.’ Accordingly, the superiority of user satisfaction over system usage is confirmed through this investigation as a success measure. TTF also plays a crucial role in enhancing DMQ through direct and indirect effects. Overall, this study reports the first empirical evidence of the integration of the D&M and TTF models to better understand the role of BIAS in DMQ, which significantly enhances the explanatory power of the findings. Considering the underlying mechanism uncovered, this research is also useful for both managers and developers, enabling them to directly enhance the level of fit between technology and user tasks, especially during the early stages of designing a BIAS tool, which in turn can also be enhanced through user satisfaction. Furthermore, when assessing the success or failure of a BIAS tool, managers should focus on users’ satisfaction (attitude) rather than use (behavior) itself as a success measure. The limitations of this research lie in the fact that the conceptual model does not consider all indirect factors from the TTF and D&M models. To remedy this limitation, future research may seek to integrate antecedent dimensions derived from the underpinning models, which may need to be validated with a larger sample size.