Savikhin et al. (2008) utilize the application of visual
analytics to improve an individuals' economic decision-making skills. The authors investigated the application of
visual analytics to common problems noticed in economics, the winner’s and
loser’s curse. The winner’s curse is
the individual who tends to overpay for certain items or services, either the
individual is worse off for buying the product or service, or the value of the
asset is less than the bidder perceived.
The loser’s curse is when an individual pursues an asset that is below
their profit-maximizing bid, or a competing entity attains the bid. The main
problems apparent is that economists are unable to see the potential for
creating a business strategy that is able to maximize profit, with most
economists are unable to consider all the information that could guide these
decisions. Thus, the authors apply
visual analytics to improve the decision-making abilities in both winner’s and
loser’s curse situations. The hypothesis by Sayikhin et al. (2008) for
their study was the subjects who participated in their interactive visual
analysis study would bid closer to the profit maximization decision as opposed
to those who participated in simple visual or tabular studies.
Sayikhin et al. (2008) conducted six different treatment groups, 3
for winner’s curse scenarios and 3 for loser’s curse scenarios. The three different visual aids the
participants looked at to help with their decision-making were an interactive
visual analytic model, a simple visual, and a tabular table. Each subject in the experiment acted independently from other subjects in the study. All were given the scenario of being a
decision-maker who had to decide how much to bid for a company.
Participants were given a possible data range that they could bid for
each company. Decisions on how much to bid were conducted on a computer generated program that would
randomly decide the value of the company and display the three different types of graphics.
Over the course of the experiment the participants switched between the
three types of visual aids and would base their bid value off their
interpretation of what the visuals portrayed.
In each of the three different visual representations individuals were given 30
different opportunities to bid on various companies.
Overall, subjects that were given the interactive visual
analytics treatment learned what the best bid/optimal solution would be more
often as compared to those individuals who were given simple visual or tabular representation of the bidding information. Moreover, for both the
winner’s and loser’s curse scenario groups, the periods of using interactive
visual analytics outperformed subjects given the other visual treatments. Overall, results were statistically significant in this regard. Each increased usage of the interactive visual analytics model allowed the
participants to learn from past decisions on bids and allowed these individuals
to make more optimal bids as opposed to other participants who received the other two visual treatments. It is also important to note that even a
simple visual aide provided more effective decision making capabilities as
opposed to viewing information with tabular formed displays.
Critique:
I found that this study was useful as it provided a way in
which to help individuals within the business realm to make more efficient decisions by analyzing their situation with interactive visual aids. It is important to avow that this study seems to suggest the usefulness
of showing information visually to overcome cognitive thinking judgments from
decision-making and improve learning capabilities. Moreover, it would be
interesting for a future study to demonstrate how interactive visuals seem to
engage our thinking more than just a simple visual does. One limit of this study was that the sample
size was small, so it would be interesting to conduct this study over a much
larger sample size to replicate the results. Another limitation
of this study other than sample size was that the authors only looked at bidding
patterns in winner’s curse or loser’s curse scenarios, not any other economic
conditions. Even though this is a topic
that would come up often within the business environment, it would be
interesting to see what other areas in business decision-making scenarios would
interactive visual analytics improve the process of decision-making. I would hypothesize that interactive visual
analytics would be able to be applied to multiple areas in the business
realm, especially for those individuals who learn more effectively visually.
Source: Savikhin, A.,Maciejewski, R., & Ebert, D.S. (2008). Applied visual analytics for economic decision-making. IEEE Symposium on Visual Analytics Science and Technology, 107-114. Retrieved from https://www.bioinformatics.purdue.edu/discoverypark/vaccine/assets/pdfs/publications/pdf/Applied%20Visual%20Analytics%20for%20Economic%20Decision-Making.pdf.
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Did the article address at all the learning preferences of decision-makers and the effect of such a thing on the results of this research? In a different article I read, the authors contested that the spatial ability, their term for how well people comprehend certain visualizations, is part of what determines to what extent visualizations will aid in comprehension of information.
ReplyDeleteI agree with your suggestion that further research into comparing simple visuals with complex, interactive visuals and their respective effects on decision-makers. I imagine this too would depend on participants' spatial ability.
You brought up a very good question. Throughout the paper I do not recall if they asked participants what their preferred method of learning was in terms of visual aids or other forms of learning. That could be a possible limitation of the study that would need to be addressed if this study was replicated using a much larger sample size.
ReplyDeleteThe application of visual analytics to improve decision-making skills in both the winner's and loser's curse scenarios is an interesting topic. The fact that the study not only yielded results that were statistically significant but showed that even a simple visual aid improved decision-making skills slightly is an important finding. I would also be interested to see if interactive visuals engage our thinking more and to what degree they are effective in improving decision-making skills, not only in economics but in other fields.
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