Abstract
We developed an experimental decision support system (DSS) that enabled us to manipulate DSS performance feedback and response time, measure task motivation and DSS motivation, track the usage of the DSS, and obtain essential information for assessing decision performance through conjoint analysis. The results suggest the mediating role of DSS use in the relationship between DSS motivation and decision performance. Further, DSS motivation is highest in the presence of high task motivation, more positive DSS performance feedback, and fast DSS response time. The findings have important implications for both DSS research and practice.
1. Introduction
Despite the acknowledgment that decisions utilizing decision support systems (DSSs) can be made more quickly and accurately than unaided decisions [1,2], it is often surprising that potential users do not always take advantage of DSS to support their decision-making. This raises the need for understanding how to encourage DSS use. However, some studies on DSS use have concluded that decision performance is not always improved with increased DSS use [e.g.,3,4]. Our review of this literature suggests that the lack of benefits of DSS use is not due to the fact that the effect does not exist but the result of the contexts in which these studies are conducted. Specifically, we attribute lack of an effect of DSS use on decision performance to the use of self-reported measures of system use [5,6] and decision performance [7]. Researchers have argued that it is important to measure actual use rather than usage intention because the reported low correlations between intention and system use suggest that intention may not adequately proxy for actual use [8,9].
5.3. Limitations and suggestions for future research
The limitations of this study include the controlled experimental setting where the hypotheses are tested. Although an experimental design enables us to manipulate DSS performance feedback and response time, measure task motivation and DSS motivation, and assess DSS use and decision performance, the results may be less generalizable to other real-world settings. Future research should validate the constructs and overall model in different contexts where organizational factors (e.g., managerial pressure, economic issues, or mandatory use) that affect DSS motivation can be assessed. Further, although the study context is appropriate for our sample of student participants, generalizability can be improved by conducting the study with systems professionals in practice
