Article ID: | iaor20081557 |
Country: | Netherlands |
Volume: | 42 |
Issue: | 4 |
Start Page Number: | 2093 |
End Page Number: | 2106 |
Publication Date: | Jan 2007 |
Journal: | Decision Support Systems |
Authors: | Liang Ting-Peng, Hung Shin-Yuan, Ku Yi-Cheng, Lee Chang-Jen |
Keywords: | artificial intelligence: decision support |
Assessing the value of decision support systems (DSS) is an important line of research. Traditionally, researchers adopt user satisfaction and decision performance to measure DSS success. In some cases, however, the use of DSS is not benefit driven. Instead, DSS adoption may be motivated by avoiding decision errors or reducing decision cost, indicating that regret avoidance may be a useful measure of DSS success. Regret is a post-decision feeling regarding not having chosen a better alternative. Recent behavioral research has indicated that, in addition to pursuing higher performance and user satisfaction, reducing decision regret is another important consideration for many decision-makers. This exploratory study extends prior research on DSS evaluation by proposing regret avoidance as an additional measure of DSS success. Experimental results regarding the use of DSS for stock investment demonstrate DSS use significantly reduces regret in situations involving low user satisfaction. Consequently, besides decision performance and user satisfaction, regret reduction is also important in measuring the effectiveness of DSS.