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An Experimental Study of Decision Process with Interactive Technology

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  • Inkyoung Hur
  • Sung-Hee Kim
  • Anya Samek
  • Ji Soo Yi

Abstract

We investigate the effect of different interactive technologies on the decision-making process in an information search laboratory experiment. In our experiment, the participant makes a selection from a list of differently-valued objects with multiple attributes. We compare presenting information in static form to two methods of interactive presentation. In the first, the participant can manually sort objects by attribute, a capability similar to that found in spreadsheet software. In the second, we present an interactive visual tool that (1) automatically sorts all objects by attribute and (2) uses visual cues for comparisons. Manual sorting capability does not cause an improvement in decisions in this context. On the other hand, the visual tool increases the value of the objects selected by the participant and decreases time spent deliberating. We also find that our interactive presentations affect the decision-making process of participants by changing the number of intermediate options considered. Our results highlight the importance of investigating the effect of technology on information search, and suggest that appropriate interactive visual displays may improve search in practice.

Suggested Citation

  • Inkyoung Hur & Sung-Hee Kim & Anya Samek & Ji Soo Yi, 2015. "An Experimental Study of Decision Process with Interactive Technology," Artefactual Field Experiments 00427, The Field Experiments Website.
  • Handle: RePEc:feb:artefa:00427
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    References listed on IDEAS

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    1. Kelvin Balcombe & Iain Fraser & Eugene McSorley, 2015. "Visual Attention and Attribute Attendance in Multi‐Attribute Choice Experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 447-467, April.
    2. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    3. Tibor Besedeš & Cary Deck & Sudipta Sarangi & Mikhael Shor, 2012. "Age Effects and Heuristics in Decision Making," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 580-595, May.
    4. Andrew Caplin & Mark Dean & Daniel Martin, 2011. "Search and Satisficing," American Economic Review, American Economic Association, vol. 101(7), pages 2899-2922, December.
    5. Christine Kaufmann & Martin Weber & Emily Haisley, 2013. "The Role of Experience Sampling and Graphical Displays on One's Investment Risk Appetite," Management Science, INFORMS, vol. 59(2), pages 323-340, July.
    6. Johnson, Eric J. & Camerer, Colin & Sen, Sankar & Rymon, Talia, 2002. "Detecting Failures of Backward Induction: Monitoring Information Search in Sequential Bargaining," Journal of Economic Theory, Elsevier, vol. 104(1), pages 16-47, May.
    7. Sonntag, Axel, 2015. "Search costs and adaptive consumers: Short time delays do not affect choice quality," Journal of Economic Behavior & Organization, Elsevier, vol. 113(C), pages 64-79.
    8. George J. Stigler, 1961. "The Economics of Information," Journal of Political Economy, University of Chicago Press, vol. 69, pages 213-213.
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