The effects of structural characteristics of explanations on use of a DSS

Abstract

Research in the field of expert systems has shown that providing supporting explanations may influence effective use of system developed advice. However, despite many studies showing the less than optimal use made of DSS prepared advice, almost no research has been undertaken to study if the provision of explanations enhances the users' ability to wisely accept DSS advice. This study outlines an experiment to examine the effects of structural characteristics of explanations provided within a forecasting DSS context. In particular, the effects of explanation length (short vs. long) and the conveyed confidence level (weak vs. strong confidence) are examined. Strongly confident and long explanations are found to be more effective in participants' acceptance of interval forecasts. In addition, explanations with higher information value are more effective than those with low information value and thus are persuasive tools in the presentation of advice to users.