The effects of structural characteristics of explanations on use of a DSS M. Sinan Gönül a , Dilek Önkal a, ⁎ , Michael Lawrence b a Faculty of Business Administration, Bilkent University, 06800 Ankara, Turkey b School of Information Systems, University of New South Wales, Sydney 2052, Australia Received 7 April 2005; received in revised form 23 September 2005; accepted 6 December 2005 Available online 24 January 2006 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. © 2005 Elsevier B.V. All rights reserved. Keywords: Explanation; Forecast; Judgment; Adjustment 1. Introduction The last few decades have witnessed a significant increase in the availability and accessibility of informa- tion providers that target the decision makers in a variety of fields ranging from medical to financial sectors [5,14]. Decision makers routinely seek various forms of external information assistance to support their decision making processes with forecasts constituting one of the most widely used forms of such external assistance. However, decision makers choose to trust and use these forecasts only if they believe these predictions are justifiable, relevant, and valuable in effectively manag- ing the uncertainties about the future [8]. What makes an individual use an external forecast, then, is a direct function of his/her perceptions of its acceptability. A provided forecast may be considered accurate, justifi- able and informative from a provider's perspective; however, its utilization is totally dependent on whether the user is persuaded that this is the case. This acceptability issue is a major concern especially for developers of decision support systems (DSS). What makes a DSS successful is not simply the accuracy of its results, but the acceptance of these results by its users. However, research evidence suggests reluctance by decision makers to trust the advice provided by a DSS [2,17,22]. In the field of sales forecasting, despite ready availability of excellent software, surveys continue to show that many organisations develop their forecasts using only management judgement [32], and when Decision Support Systems 42 (2006) 1481 – 1493 www.elsevier.com/locate/dss ⁎ Corresponding author. Tel.: +90 312 290 1596; fax: +90 312 266 4958. E-mail address: onkal@bilkent.edu.tr (D. Önkal). 0167-9236/$ - see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.dss.2005.12.003