The Anchoring Effect in Decision-Making with Visual Analytics

Anchoring effect is the tendency to focus too heavily on one piece of information when making decisions. In this paper, we present a novel, systematic study and resulting analyses that investigate the effects of anchoring effect on human decision-making using visual analytic systems. Visual analytic...

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Bibliographic Details
Published in2017 IEEE Conference on Visual Analytics Science and Technology (VAST) pp. 116 - 126
Main Authors Cho, Isaac, Wesslen, Ryan, Karduni, Alireza, Santhanam, Sashank, Shaikh, Samira, Dou, Wenwen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Analytical models
Anchoring Effect
Cognitive Bias
Data visualization
Decision making
Interaction Log Analysis
K.6.1 [Management of Computing and Information Systems]: Project and People Management-Life Cycle
K.7.m [The Computing Profession]: Miscellaneous-Ethics
Sense Making
Task analysis
Uncertainty
Visual analytics
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Summary:Anchoring effect is the tendency to focus too heavily on one piece of information when making decisions. In this paper, we present a novel, systematic study and resulting analyses that investigate the effects of anchoring effect on human decision-making using visual analytic systems. Visual analytics interfaces typically contain multiple views that present various aspects of information such as spatial, temporal, and categorical. These views are designed to present complex, heterogeneous data in accessible forms that aid decision-making. However, human decision-making is often hindered by the use of heuristics, or cognitive biases, such as anchoring effect. Anchoring effect can be triggered by the order in which information is presented or the magnitude of information presented. Through carefully designed laboratory experiments, we present evidence of anchoring effect in analysis with visual analytics interfaces when users are primed by representation of different pieces of information. We also describe detailed analyses of users' interaction logs which reveal the impact of anchoring bias on the visual representation preferred and paths of analysis. We discuss implications for future research to possibly detect and alleviate anchoring bias.
DOI:10.1109/VAST.2017.8585665