• DocumentCode
    3416131
  • Title

    Applied visual analytics for economic decision-making

  • Author

    Savikhin, Anya ; Maciejewski, Ross ; Ebert, David S.

  • Author_Institution
    Dept. of Econ., Purdue Univ., West Lafayette, IN
  • fYear
    2008
  • fDate
    19-24 Oct. 2008
  • Firstpage
    107
  • Lastpage
    114
  • Abstract
    This paper introduces the application of visual analytics techniques as a novel approach for improving economic decision making. Particularly, we focus on two known problems where subjectspsila behavior consistently deviates from the optimal, the Winnerpsilas and Loserpsilas Curse. According to economists, subjects fail to recognize the profit-maximizing decision strategy in both the Winnerpsilas and Loserpsilas curse because they are unable to properly consider all the available information. As such, we have created a visual analytics tool to aid subjects in decision making under the Acquiring a Company framework common in many economic experiments. We demonstrate the added value of visual analytics in the decision making process through a series of user studies comparing standard visualization methods with interactive visual analytics techniques. Our work presents not only a basis for development and evaluation of economic visual analytic research, but also empirical evidence demonstrating the added value of applying visual analytics to general decision making tasks.
  • Keywords
    data visualisation; decision making; econometrics; profitability; acquiring-a-company framework; data visualization method; economic decision-making; empirical evidence; interactive visual analytics technique; profit-maximization decision strategy; visual analytics tool; Application software; Decision making; Helium; Statistics; Uncertainty; Visual analytics; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on
  • Conference_Location
    Columbus, OH
  • Print_ISBN
    978-1-4244-2935-6
  • Type

    conf

  • DOI
    10.1109/VAST.2008.4677363
  • Filename
    4677363