Judgment and Decision Making - Zmf 5.pdf Notes

Judgment and decision making The organization as a brain - - - Within the brain metaphor it is essentially about information o The organization as an Information Processing Entity How do organizations deal with information? o Perception o Judgment o Decision making Individual level: o How do peop...

Judgment and decision making The organization as a brain - - - Within the brain metaphor it is essentially about information o The organization as an Information Processing Entity How do organizations deal with information? o Perception o Judgment o Decision making Individual level: o How do people judge and decide? Group level: o How do groups of people judge and decide? o Group processes are covered in the context of the metaphor "culture” Use of information o Rational versus irrational? o Time horizon: Learning! Normative versus descriptive decision theories -> Prüfungsrelevant - - - - Descriptive statements: o Show how people actually judge and behave o They can be right or wrong in relation to empirical observations. o Example: On average, people give more than zero CHF to person B in a dictator game. Normative statements: o Subjective value statements which cannot be checked for correctness. o Example: People should always give 50% of the endowment in the dictator game. Prescriptive statements: o Describe how people should act, assuming certain goals or values. o Example: People should give up their entire equipment in Public Good if they want to maximize group welfare. Today: Descriptive theories: How do people actually judge and decide in reality? Examples Are these lines parallel to each other? Which horizontal line is longer? Warm up: Why are you here - You've made a decision: o To take this course this semester o Not to do this last or next semester o To study this field of study Looking at the cube, it. changes its direction Freedom of choice does not necessarily mean freedom - - Many possibilities make it more difficult to choose "the right thing". o to make choices at all! Example: Study "When choice is demotivating" (Iyengar & Lepper, 2000) o 24 exotic varieties Wilkin & Sons jam on the shelf o 1. setting: tasting table with 6 varieties o 2. setting: Tasting table with all 24 varieties More people stop at the large tasting table (60% vs. 40%). At both tables about the same number of jams are tried (1.38 vs. 1.5). 30% of those who were able to try the small selection bought a jam. But only 3% of those who tasted from the large selection bought a jam! -> loading People with a choice set, lowers the possibility of finding a match Tyranny of choice... - education market job market Consumer goods market communications market electricity market healthcare sector relationship market religions identities Making good decisions is not easy... -> Self Knowledge - Did you have a choice about your studies? Do you know your "preferences"? (Self-knowledge) Did you know all the alternatives? (Availability) Do you know whether and how these preferences (e.g. in your studies) are served by the alternatives? (Ambiguity) Was it the best choice? (Maximize?) Do you regret it? Towards others (social comparison) Compared to other alternatives (regrets) Is that why you left a back door open? Compared to your expectations? (Comparison with yourself) How well do we know our „preferences“? - Do people know their "preferences"? Experienced utility Expected utility Remembered utility If these three dimensions point in the same direction should be clear what one wants. -> But often they don’t point into the same direction. Problem 1: Remembered Utility -> Peak-End-Rule (Redelmeier & Kahneman, 1996) Peak-End Rule and colonoscopy - Simple experiment o Control group: Normal colonoscopy o - Experimental group: Colonoscopy(Darmspiegelung) "plus" (plus = examination device not moved for 20 seconds at the end of treatment) Experimental group reported the same continuous unpleasant feeling during treatment as the control group and then slightly less in the last 20 seconds. In summary, however, the experimental group rated the whole colonoscopy less unpleasant than the control group. Both groups had the same negative peak, but the experimental group had a less unpleasant final experience. Probability to come to follow-up (after 5 years) was higher in the experimental group. Peak-End Rule - Memories of experiences are mainly determined by o sensations during the (positive or negative) peak o sensation when the experience ended Expected utility - - - - Laboratory experiment "Do the day's shopping" (Simonsohn, 1990): Day shopping from 8 different categories of basic foods. Control group: o 3 daily purchases with one good each from the 8 categories (i.e. 8 goods per day): 1. for today, then 2. for tomorrow, then 3. for the day after tomorrow. Experimental group: o Do your shopping today for the next three days directly: so choose three things from each of the 8 categories today. Result: o People from the experimental group select much more varied, mistakenly assuming that they wanted to eat something different every day. o People from the experimental group repeatedly tend to pick their favorite food. Philosophical question: What are the "real" preferences? How well do we know our preferences? - Neither remembered utility nor expected utility reflect the utility experienced. Nevertheless, a decision at this point in time is influenced by both dimensions! Making good decisions is not easy -> Availability - Did you have a choice? Do you know your "preferences"? (Self-knowledge) Did you know all the alternatives? (Availability) Do you know whether and how these preferences (e.g. in your studies) are served by the alternatives? (Ambiguity) Was it the best choice? (Maximize?) Do you regret it? (perhaps especially at this moment) Towards others (social comparison) Compared to other alternatives (regrets) Is that why you left a back door open Compared to your expectations? (Comparison with yourself) What influences the perception of alternatives? - Availability heuristics (e.g. Slovic et al., 1979) risk assessments "Estimate the number of annual deaths due to a total of 40 different causes" (Fischhoff et al., 1978). Result: o o subjects estimated that as many people aspire to accidents as to illnesses Actual ratio: 1:17 Availability of information - Test subjects estimated that death by murder is just as common as stroke. o Actual ratio: 1:11 Spectacular causes overestimated as cause of death o Accidents, murders, storms, floods, fires Everyday causes are underestimated o diabetes, asthma, stroke, tuberculosis Reason: o Spectacular causes are more available through newspaper reports, news, etc. Did you know all your alternatives? - - Probably not Bern: Master in Philosophy of Economics, Politics, and Justice What is it, what do you do? Source dependency o Family (Which books do the parents have in the shelves, what do the parents do themselves?) o Friends (What do friends tell you?) -> Do I study Business Administration because of my friends? o Ranking information (Which business studies are the best?) o Reporting (Scandal at Uni XY...) etc. Availability is conditioned by an abundance of environmental conditions that affect intrinsic preference development Availability heuristics - - Probability estimates depend on the degree of (cognitive) accessibility. In the (subjective) assessment of probabilities of occurrence or events, the information is weighted more strongly the o easier they are accessible to one’s memory (perceived effort in the search) o Timing of the last access (recency effect) o more salient and lively they appear (conspicuousness, imaginability) Tversky & Kahnemann (1974) In the study were different People aksed what the most common reason for the problem when a car won’t start is. The first 50% were given a larger amount of possibilities than the second 50%, this shows us, that the concept of „Out of sight, out of mind“ is right. This also exists in experts - A correct error analysis, or the attempt to achieve a correct assessment of probabilities of causes (or events), depends on whether all possibilities are taken into account. (Fischhoff, Slovic, Lichtenstein, 1978) Whether they are taken into account seems to depend on the availability of the possibilities. The problem also exists with experts! “out of sight, out of mind” What is salience? - High visibility, attention-grabbing presence, so that the information in question is particularly conspicuous. Anchoring and adjustment Anchoring effects in business decision making - - (Any) information forms a (judgment) anchor which serves as a reference point. The subsequent adaptation is insufficient. -> For example I know that another person gets for the exact same work more salary Examples: o Consumption (Shafir, Simenson, Tversky, 1973 ▪ » First there was a baking machine for the price of $279 in the assortment, later a more expensive luxury model ($429) was added. ▪ » Result: Doubling of the sales figures of the inexpensive appliance, since it is a bargain in comparison. Labor decisions (Abeler et al., 2006 o Allocation as Person 1 or Person 2 in a laboratory task o Person 1 receives fixed salary for task (e.g. 9 Euro vs. 3 Euro) o Person 2 receives variable salary for task (e.g. 20 cent per task) » Variable: Productivity o People 2 work so much that they get 9 Euro vs. 3 Euro Anchoring and the law... - - Study by Englich et al., (2009) Case descriptions were presented to young judges (!!!). Cases submitted should be judged with a penalty of their own. The sentence demanded by the public prosecutor belonging to the case description should be thrown (with two dice): Control group: o Cubes together always showed 3 months (1 and 2 eyes) o required sentence: 5.28 months Experimental group: o Cubes together always showed 9 months (3 and 6 eyes) o required sentence: 7.81 months Framing of decisions - Different presentation (context) causes different decisions: The presentation of the facts (as loss or loss of profit) manipulates the reference point. Pay 1,50€/l petrol if you pay without credit card! Petrol 1,55€/l if you pay with credit card! The cash price (1,50€) can either be used as a discount for cash payers (1,50€) or as a penalty for credit card payers (1,55€). The decisive factor for this perception is the reference price. And what reference is is influenced by framing. Written exam: o Bonus points for task vs. malus points for task Work context: o Bonus payments vs. 13th monthly wage (etc.) Framing of decisions (Tversky & Kahneman, 1974 Science) - Vignette about doctor in a village: 600 people suffer from a life-threatening disease. They have two methods at their disposal to combat the disease: o Method A saves 200 people. o With method B you have a 1/3 chance of saving all 600 people; consequently a 2/3 chance of saving no one. - Do you choose method A or B? o Method A is preferred on average ———————————————————————————————————————————————————— - Almost identical vignette about a doctor in a village: - 600 people suffer from a life-threatening disease. They have two methods at their disposal to combat the disease: o With method C, exactly 400 people will die. o With method D you have a 1/3 chance that no one dies; consequently a 2/3 chance that everyone dies. - Do you choose method C or D? o Method D is preferred on average ———————————————————————————————————————————————————— - Profit/rescue opportunities: o Method A: 1*200 = 200 o Method B: 1/3*600 = 200 - Loss / Death risks: o Method C: 1*400 = 400 o Method D: 2/3*600 = 400 - A=C, B=D - C<D (representation as safe loss -> risk) - A>B (representation as safe profit -> riskless) Typical behavioral pattern in framing - Smaller, secure gains are preferred to larger, uncertain gains. However, in the case of losses, a larger, uncertain loss is accepted in order to avoid a smaller, secure one. Profits and losses are perceived differently o Losses loom larger than gains -> You are willing to pay more to avoid a loss than you are to willing to pay for a potential gain Prospect Theory - Horizontal axis: objective gains and losses. Vertical axis: subjective utility (in K&T misleadingly referred to as v (value) - and not u=utility). Outcomes (prospects) are assessed relative to the reference point (which is often the status quo) Effects of total assets on function are considered negligible. Kahneman and Tversky have made no statements about where the reference points in the real world come from (large current field of research). o Expectations o Social comparisons etc. Evaluation - value function Gains and losses relative to (neutral) reference point In the profit area concave Convex in the loss range Value function is steeper in the loss area than in the profit area A loss in the amount x hurts more than a profit in the amount x gives pleasure (loss aversion). Decision weight function - - Probabilities are not included directly (1:1) in the assessment. Example: (A) 30€ certain or (B) 80% chance of winning 45€ in a lottery? o A:1*u(30) =30 B:.80*u(45) =36 o Typical subjective preferences: A>B C) Win 45€ with a 20% chance or (D) 30€ with a 25% chance? o C: 20*u(45) =9 D:.25*u(30) =7.5 o Questioning: D<C Both probabilities were only divided by 4. Both inequalities cannot be true at the same time! Safety (prob=1) is overrated compared to other probabilities -> certainty effect. - Highest sensitivity to changes near the endpoints Larger change if probability changes from 0 to .10 or from .90 to 1 than from e.g. .30 to .40 Very small probabilities are overweighted Large probabilities are underweighted - Summary - The way the alternatives are presented influences decisions (framing) The perception of gains and losses is reference-dependent The utility is linked to (relative) profits and losses, not to final asset values Losses weigh more heavily than profits of the same amount (value function in the loss area steeper) The combination of the overweight of small probabilities and the concave/convex value function results in a o risk-averse behavior in case of gains with moderate probabilities (e.g. selling rising stocks too early) and in case of losses with small probabilities (e.g. insurance against aircraft crash); o risk-seeking behavior in the case of losses with moderate probabilities (e.g. selling falling stocks too late) and in the case of profits with small probabilities (e.g. Lottery games) Nobel Prize (Economic Science) 2002 for Daniel Kahneman “for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.” Endowment-Effect (status-quo) - Mr. S. buys a box of good wine for 5€ the bottle and puts it in his cellar. A few years later his wine supplier offers him to buy it back for 100€ per bottle. Mr. S. refuses this, although he himself has never paid or would never pay more than 35€ for a bottle of wine. Based on R. Thaler (1980) Mental Accounting - - - - - People keep mental subaccounts the marginal spending propensity of these sub-accounts is different in each case. Example: o 1. you go to a concert that you know costs 20€ admission. Before the entrance you notice that you have lost 20€ on the way. Are you buying a new ticket? ~90%: yes o 2. you go to a concert where you bought the ticket for 20€ in advance. In front of the entrance you will notice that you have lost your ticket. Are you buying a new ticket? ~50%: yes The outcome is always the same: o Visit the concert: Costs 40€. o Do not visit the concert: Costs 20€. Situation 1: o They wanted to pay the 20€ first at the cash desk, until then it was money. o You have lost 20€ on the account "cash". o You then spend 20€ from the account "concert visits". Situation 2: o You had already bought the ticket before. o You have already withdrawn 20€ from the "Concert Visits" account. o Now the concert becomes twice as expensive due to the loss - you would have liked to have visited two concerts from your "concert visits" account for the 40€. Of course, there are many different accounts: Apart from "cash" and "concert visits" e.g. the “Dating-Account". Summary - - Beware of judgment and decision making influences in organizational decision making and strategy o Status-quo bias o Loss aversion o Availability/Salience o Decision inertia resulting from too many options – Etc. Most models take into account utility o Although it is unclear what «preferences» are exactly Expert knowledge may also be biased o Link to evidence-based procedures and learning