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Agata Michalaszek Joanna Sokolowska

Differences in information searching in risk judgment between sophisticated and no n sophisticated subjects. Agata Michalaszek Joanna Sokolowska. Perceived risk. What is perceived risk ? people do not need more explanation to judge riskiness risk rates are consistant

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Agata Michalaszek Joanna Sokolowska

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  1. Differences in information searching in risk judgment between sophisticated and non sophisticated subjects. Agata Michalaszek Joanna Sokolowska

  2. Perceived risk • What is perceived risk? • people do not need more explanation to judge riskiness • risk rates are consistant • no common definition of perceived risk

  3. Perceived risk two major point of controversy: • the relativeinputofpositive and negativeinformationinto risk judgment • the relativeinputofpayoffs and probabilitiesinto risk judgment

  4. R–V Models – Markowitz: • decisions are based on both expected return and its uncertainty or variability (related to risk) (Markowitz, 1959) • risk is associated with the dispersion of the random variable • risk as indepedent concept WTP(x) = f {V(x), R(x)}

  5. Perceived risk as dispersion Input of negativeoutcomeintoriskjudgmentismoreimportant Subjects’ rates: R(x2) < R(x1) < R(x3) • X1: [+10, 50%; -10, 50%] • X2: [+20, 50%; -10, 50%] • X3: [+10, 50%; -20, 50%] R(x1) < R(x2)=R(x3)

  6. Positive information • In everyday language: • emphasise negative connotation to the possibility of outcomes • underline extra rewards that can be gained only at the price of uncertainty and possible loss • Proverbs: • uncertainty (‘do not buy a pig in a poke’) • possible loss (‘gold may be bought to dear’) • necessary condition of success (‘nothing ventured, nothing gained’)

  7. Payoffs vs. probabilities Risk jugdment: • Probabilities are more important in experiments • Values are more important in real life situations • difficult to asses probability in everyday activities • Open questions – few about probabilities, much more about payoffs in different categories (Tyszka and Zaleskiewicz, 2006)

  8. Payoffs vs. probabilities Methodology: • differentscales for payoffsandprobabilities Resolution approach: • providewithvaguemagnitude of payoffs and probabilities • useprocesstracingmethod – Mouselab

  9. Vague information • in USA new virus of dangerous flu is spreading • it is necessary to rate riskiness of a purchase of the various vaccines for employees • both vaccines are safe in the same way and have the same price • differences with: seriousness of negative effects probability of those effects

  10. Vague information Precise information: • 5% chances of negative effects • $45 costs Imprecise information: • Vaccine A Vaccine B • 3-7% chances of negative 5% chances of negative effects effects • $75 costs $45-105costs (Kuhn and Budescu,1996)

  11. Process tracing method • investigating the process by investigating which information is used by people when judging risk • Information: • type • amount • order • reaction time

  12. Educational background Empirical findings: • people in general use incorrect representation of random events • gambler’s fallacy • law of small numbers • subaaditivity of probability for complementary events • conjunction fallacy

  13. Educational background • people cannot get information about probability in real life ‘expert’s’ group: • people who are trained to use probabilistic representation of reality • greater knowlegde of mathematics and statistics • more sensitive to probabilities

  14. Research questions and hypothesis • What is the relative input of information about payoffs and probabilities into risk judgment? • Information about negative aspects of a risky situation impact risk judgment more than information about positive aspects. • Training in statistics and mathematics enhanced the relative importance of information about probabilities in risk judgment (and has no impact on relative importance of information about positive and negative aspects).

  15. Experiment - design • respondents were presented with6 differentrisky situations related to financial risk • everysituation consisted of 3 alternative options (A, B, C) • each option consisted of 5 possible outcomes • 2 losses, break even, 2 gains • 2 losses, 3 gains • payoffs were quantitative

  16. Experiment - design • information was presented in the table (Payne, 1976) • MouseLabWEB (Willemsen and Johnson 2006) http://www.mouselabweb.org/

  17. Experiment - design • information was hidden behind boxes – to access the information, the decision maker clicked the mouse pointer over the box on the screen • participants could disclose as much detailed information about the options as necessary

  18. Experiment - design two orders of location of gains and losses

  19. Experiment - design • Respondents’ taks – judge riskiness of each option Measure of perceived risk • subjects rated riskiness on an 11-point scale (from 0 ‘not risky at all’ to 10 ‘extremely risky’) • Respondents: NASA group – 75: Polish group – 67: female – 33 female – 35 male – 42 male – 32 0 10

  20. Results • ca 50% available information • in NASA group more acquired information (M=19,29; SD=9,74) F(1, 125)=7,69; p<0,01

  21. Results • no effect of order • ratio positive/negative NASA group: Polish group: from 1,13 to 0,91 from 1,02 to 0,91 F(1, 111)=0,24; p>0,05

  22. Results • no differences between groups • the same amount of positive and negative – ratio close to 1 • no correlation: • positive information and risk rates, r=0,07; p>0,05 • negtive informatin and risk rates, r=0,01; p>0,05

  23. Results • ratio value/probability NASA group: Polish group: from 0,93 to 0,78 from 1,11 to 0,94 F(1, 104)=4,69; p<0,05

  24. Results • differences between groups • more payoffs – Polish group • moreprobabilities – NASAgroup • NASA group: Polish group: from 0,93 to 0,78 from 1,11 to 0,94 • more probiabilites considered in NASA group, t(139)=2,76; p<0,01.

  25. Results – risk rates • no differences between groups (t(140)=0,28; p>0,05) • positive correlations between risk rates and information aboutprobabilities NASA group: Polish group: r=0,41; p<0,001 r=0,36; p<,01 • more probabilities – higher risk rates • negative correlation for values

  26. Conclusions: • In NASA group acquired more information and more information about probabilities • In both groups the same amount of positive and negative • More probabilities – more risky • Risk rates similar in both grups

  27. Thank you.

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