سیستم پشتیبانی تصمیم گیری (DSS) و عملکرد تصمیم گیری: انگیزش DSS و پیشینه آن Decision support system (DSS) use and decision performance: DSS motivation and its antecedents

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]. The other reason for the inconsistent findings is that researchers have suggested the role of yet another variable, DSS motivation, within the use–performance relationship. The argument is that within a DSS context where the system directly supports users with a desired goal of making a better decision, intrinsic determinants such as “interest” and “importance” in using the DSS should influence DSS use and decision performance [10,11]. Increased DSS motivation and usage of a DSS, which incorporates an accurate additive difference compensatory decision strategy, should lead to improved decision performance. The additive difference compensatory decision strategy requires users to engage in iterative comparisons of all the available alternatives to arrive at a final choice. Decision makers prefer the additive difference compensatory decision strategy when a DSS provides high support for this strategy [12].