1. Pre-ICIS DSS Workshop - 2006 Presented by Naveen GUDIGANTALA PhD Student in MIS Texas Tech University Lubbock, Texas Maximizers versus Satisficers: The Effects of Web Based Decision Support Systems on Satisfaction

2. Motivation  Importance of incorporating decision support features in e-Commerce websites  How to support consumer decision making process and thereby increase their satisfaction has been the focal question of many research studies

3. Motivation – Prior Research  How do different formats of web-based DSS (non-compensatory, linear compensatory, equal weighted compensatory) influence satisfaction? In majority of the studies, participants preferred linear compensatory based web DSS to other formats (Widing & Talarzyk, 1993; Pereira, 2000; Song, Jones, & Gudigantala, forthcoming) One study by Olson and Widing (2002) found that participants were indifferent between linear compensatory based DSS and equal weighted compensatory based DSS Fasolo, McClelland, and Lange (2005) found that when positive inter attribute correlations exist, participants preferred compensatory and non-compensatory based web DSS equally

4. Motivation  First, there are some inconsistencies in the results  Second, none of the previous studies (with the exception of Hess, Fuller, and Matthew, 2005) considered individual differences

5. Research Question  How do individual differences and the format of web-based DSS influence satisfaction derived out of decision making process?

6. Maximizers vs. Satisficers  Maximizers are characterized by their tendency to find the best possible result in various domains of their lives  Satisficers are happy with a result that is good enough to meet some criterion (Schwartz, Ward, Monterosso, Lyubomisky, White, & Lehman, 2002)  Schwartz et al., (2002) developed and tested maximizing scale

7. Hypotheses Development  Uses the literature on choice and regret in decision making to develop the hypotheses  Do greater options please individuals? No (Cook, 1993; Iyengar & Lepper, 2000; Schwartz et al., 2006)  When people have more choices, they are faced with the burden of segregating good decisions from the bad ones. Any feeling of selecting a non optimal choice may result in regret for the decision maker (Iyengar & Lepper, 2000)

8. Hypotheses Development  As the number of alternatives increase, it is proposed that maximizers feel less satisfied compared to satisficers (Iyengar & Lepper, 2000; Iyengar, Wells, & Schwartz, 2006; Schwartz et al., 2002) Maximization Increased Regret Less Satisfaction

9. Hypotheses Development  Typical characteristics of Compensatory based web-DSS Allows trade-offs between attributes Takes consumers’ preferences as weights Calculates the score for every alternative based on the user provided weights All the information corresponding to alternatives is considered before the recommendations are made  Typical characteristics of Non-compensatory based web-DSS Do not allow trade-offs between attributes Considers consumers’ preferred attribute(s) Eliminates all the alternatives that do not match the threshold

10. Hypotheses  Hypothesis 1: Maximizers are more likely to be satisfied with a Compensatory web-DSS as opposed to a Non-compensatory web-DSS.  Hypothesis 2: Satisficers are more likely to be satisfied with a Non-compensatory web-DSS as opposed to a Compensatory web-DSS.

11. Research Design  An experiment will be conducted to test the hypotheses  A 2 (maximizers vs. satisficers) X 2 (non-compensatory DSS vs. compensatory DSS) factorial design will be used  Decision makers’ tendency to maximize or satisfice is considered as one of the independent variables in the study  The maximization scale developed by Schwartz et al., (2002) will be administered  A compensatory and non compensatory based DSS will be used by respondents to make apartment rental decisions

12. Research Design – Dependent Variable  The dependent variable for the study is the satisfaction with the decision making process  The participants will self report the level of satisfaction at two points of time: once after they interact with non-compensatory DSS and second time after interacting with compensatory DSS  The two items are: “How satisfied are you with the decision making process?”, and “How much did you enjoy the decision making process?” All responses will be provided on Likert scales, ranging from 1 (not at all) to 7 (extremely).

13. Implications  In a survey of 375 of e-commerce websites, it was found that none of the 375 websites provide any kind of compensatory-based support for online consumer decision making (Gudigantala, Song, & Jones, Working paper).  Provide support to both Compensatory and Non- Compensatory based decision making. Let the consumers decide.

14. THANK YOU!