Paper ID
2269
Paper Type
short
Description
We are in the era of having too much information. While having more information is usually good for individual’s decision making, it could make the decision more difficult if the information is conflicting with each other. Previous research has shown that popularity information greatly impacts people’s choice in multiple online context, however these studies have not examined the impact of conflicting popularity information. In this paper, we study people’s decision making when popularity information conflicts, specifically when total number of view (VIEW) is not consistent with the percentage of dislike (DISLIKE%). We argue that people are more likely to choose a product that has higher VIEW and higher DISLIKE% when the proportion of change is higher in VIEW than in DISLIKE%. However, people would prefer lower VIEW and lower DISLIKE% products when DISLIKE% changes higher than VIEW. When the change in these two popularity information is the same, people tend to prefer product that has higher VIEW. Our findings have significant theoretical and practical contributions to both research and online website designs.
Recommended Citation
Jin, Qianran; Animesh, Animesh; and Pinsonneault, Alain, "Decision Making Under Conflicting Information" (2019). ICIS 2019 Proceedings. 15.
https://aisel.aisnet.org/icis2019/crowds_social/crowds_social/15
Decision Making Under Conflicting Information
We are in the era of having too much information. While having more information is usually good for individual’s decision making, it could make the decision more difficult if the information is conflicting with each other. Previous research has shown that popularity information greatly impacts people’s choice in multiple online context, however these studies have not examined the impact of conflicting popularity information. In this paper, we study people’s decision making when popularity information conflicts, specifically when total number of view (VIEW) is not consistent with the percentage of dislike (DISLIKE%). We argue that people are more likely to choose a product that has higher VIEW and higher DISLIKE% when the proportion of change is higher in VIEW than in DISLIKE%. However, people would prefer lower VIEW and lower DISLIKE% products when DISLIKE% changes higher than VIEW. When the change in these two popularity information is the same, people tend to prefer product that has higher VIEW. Our findings have significant theoretical and practical contributions to both research and online website designs.