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Effects of situation familiarity and financial incentives on use of the anchoring and adjustment heuristic for probability assessment
ORGANIZATIONAL
BEHAVIOR
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HUMAN
DECISION
PROCESSES
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Effects of Situation Familiarity and Financial Incentives on Use of the Anchoring and Adjustment Heuristic for Probability Assessment WILLIAM F. WRIGHT University of California, Irvine
AND URTONANDERSON University of Texas at Austin
Three experiments tested (1) whether anchoring (and insuflicient adjustment) will occur during generation of subjective probabilities and (2) whether situation familiarity and performance-contingent incentives will reduce any anchoring effect. A total of 336 business school students either chose between two alternatives based on a preliminary judgment of relatively unlikely (low anchor) or likely (high anchor) event probabilities before generating fmal probability assessments or were in a no-choice control condition. The results indicate a strong anchoring effect. The anchoring effect is so dominant that increasing situational familiarity did not result in decreased anchoring. Monetary/recognition incentives for accurate judgments did, however, result in significantly less anchoring. Implications are suggested for research on judg0 1989 ment processes and the concept of professional judgment expertise. Academic
Press, Inc.
Given initial results indicating the existence of judgment biases (Tversky & Kahneman, 1974),research on “cognitive heuristics” has evolved to consider the conditions under which judgment biases will occur, and the degree to which they will prevail (Hogarth, 1981; Nisbett & Ross, 1980; Payne, 1982; Ross, 1977; Shanteau, 1989). Anchoring and adjustment (Nisbett & Ross, 1980,pp. 41-42; Tversky & Kahneman, 1974)is a two-stage mental heuristic for generation of subjective probability judgments. The first stage is recall of a previous judgment or generation of a preliminary judgment. The second stage is adjustment of the first-stage estimate, given the remaining information; typically the adjustment is in Financial support for this research was provided by the McKnight Foundation and the Research Committee of the School of Management, University of Minnesota. Helpful comments provided by Richard Helleloid, Robin Keller, and John Payne are gratefully acknowledged. Requests for reprints should be sent to William F. Wright, Graduate School of Management, University of California, Irvine, CA 92717. 68 0749-5978189$3.00 copyrightQ 1989 by Academic Press, Inc. All iigbts
of reprcduction
in my form reserved.
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the expected direction but of insufficient magnitude. One alternative hypothesis to anchoring and insufficient adjustment is single stage, compensatory weighting and integration of the available information into a judgment, without any anchoring effects (see Wright, 1980, pp. 289-290). Situation familiarity could impact the results of cognitive heuristics (Joyce & Biddle, ,198l). In addition to any conceptual knowledge, instances of familiar situations have been described and/or experienced more frequently than instances of less familiar events. Therefore, knowledge of familiar situations provides for more reliable, and perhaps more complete, memory retrieval due to stronger associative bindings among more numerous situational linkages in memory (e.g., Anderson, 1980,pp. 169-221), and reduces the chance of an unintended anchoring bias. Also, if someone is familiar with a situation, there will be less chance for a nondiagnostic, artifactual situational characteristic to provide an anchoring effect. We predicted less anchoring given increasing situation familiarity. The possible anchor subjects made an initial choice, based on a preliminary subjective uncertainty assessment, before providing a final probability judgment. This potential anchoring context was adapted from Joyce and Biddle (1981) to make certain that additional information would not be provided to the subjects in the preliminary judgment conditions. The normative prediction is no effect of the preliminary judgment on a subject’s eventual probability assessment. Performance-contingent incentives may increase a subject’s motivation, causing the individual to think more carefully and completely about the judgment situation and his or her judgment, and therefore not display any anchoring effects. Accumulated knowledge of the situation and awareness of different ways to generate the needed judgment, e.g., anchoring and adjustment or simultaneous compensatory integration could provide a repertoire of available judgment procedures (with alternative levels of cognitive effort being required), without any anchoring necessarily being produced. Also, performance-contingent incentives focus attention on precisely how judgment errors will be measured. Given this focused cognitive effort and concrete specification of the error criterion, performance-contingent incentives were predicted to decrease any anchoring effect (cf. Wright & Aboul-Ezz 1988).The presence of incentives and, therefore, more motivated subjects, could also provide for a more refined and precise test of the familiarity hypothesis. The Three Experiments
In Experiment 1, we investigated whether the magnitude of any anchoring effects on probability assessmentswould decrease, given increas-
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ing situation familiarity. Experiment 2 provided additional investigation of any effects of situation familiarity on anchoring, given a wider range of familiarity levels. In Experiment 3, the motivational and attentiondirecting effects of performance-contingent incentives were predicted to reduce the degree of anchoring. EXPERIMENT 1 Subjects
The participants, 111 first-year Master of Business Administration (MBA) students at the University of Minnesota, participated voluntarily. All had some degree of formal training in probability and statistics. Task and Design
Subjects provided subjective probability (hereafter, SP)judgments for three situations using a direct probability encoding method (Wright, 1988),i.e., direct assignmentof probabilities to possible outcomes. Each subject was in either the control condition or one of two preliminary judgment conditions (low or high possible anchor). Subjects in the two preliminary judgment conditions chose between two alternatives based on their preliminary SP judgment before providing their final SP judgment (see Panel A, Appendix). The preliminary SP judgment was each subject’s own 0.25 (low anchor) or 0.75 (high anchor) cumulative probability. The preliminary judgment question was omitted from the materials to create the no anchor control condition. The alternative hypothesis to anchoring is no effect of the preliminary question, i.e., no anchoring effect. A mixed, two-factor design (anchor and familiarity conditions) was employed with repeated measureson the familiarity condition, i.e., each subject provided an SP for each of three situations. The presentation order of the three situations, and the three anchor conditions, were randomized across the subjects. Materials and Procedure
Familiarity was manipulated by selection of the three judgment situations, i.e., the fraud, compensation, and GPA situations (see Panel B, Appendix). The three situations were pretested for relative familiarity. We also aimed for the mean probabilities in the no-anchor condition to be approximately 0.50 to avoid any floor or ceiling effects, i.e., subject responses clustering at the ends of the response scale.’ Twenty business ’ A floor effect is when judgments cluster at the lower end of the scale without the
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school students pretested the materials. Familiarity was measured on a continuous 1-7 Likert scale with 7 as the highest familiarity.2 The mean familiarity scores are 3.46, 4.59, and 4.85 for the fraud, compensation, and grades situations, respectively, F(2,38) = 7.28, p < .Ol (ANOVA, blocking on subjects), with standard deviations of approximately 1.2. The subjects were told that the purpose of the study was to determine how accurately they could estimate the known relative frequencies. The materials were then distributed and completed. The relative familiarity of the three situations was then assessed as a manipulation check, using the same familiarity scale as was used for the pretest subjects. Results The manipulation check on perceived situation familiarity yielded results similar to those in the pretest, i.e., means of 2.96,4.00, and 4.28, and standard deviations of 1.11, 1.09, and 1.45, for the fraud, compensation, and grades situations, respectively. The familiarity of the three situations is significantly different, F(2,216) = 36.70, p < .OOOl (two-factor ANOVA, anchor factor and situation x anchor interaction not significant, F < 1). The Newman-Keuls test for the pair-wise comparisons indicated that the familiarity of both the compensation and grade situations is significantly different from the fraud situation (p < .Ol); however, the familiarity of the compensation and grade situations is not significantly different. Table 1, Panel A provides the mean, median, and standard deviation of the SPs for each situation and anchor condition (columns 2-4). The results suggest a strong, consistent anchoring effect of the preliminary judgment on the eventual SP assessments (see Fig. 1, Panel A). Relative to the no-choice control condition, the mean SP response is lower in the low anchor condition, and higher in the high anchor condition, for all six comparisons (p = .016, sign test). The anchoring effect of the preliminary judgment is highly significant, F(2,108) = 12.06, p < .OOOl.The ranges from the mean low anchor SP to the mean high anchor SP are 0.169, 0.164, and 0.163 for the fraud, compensation, and grades situations, respecitvely (Table 1, Panel A, column 5). There are no floor or ceiling effects in the SP response distributions across the conditions. opportunity for potential differences in treatments to be revealed; a ceiling effect is a similar occurrence at the upper end of a scale. * The scale endpoints were labeled “unfamiliar with general context and have no knowledge of even one specific case from the population for which the estimate is requested” (= 1); “familiar with general context, but knowledge of the population for which estimate is requested is limited” (=4); and “extremely familiar with general context and have knowledge of a number of cases from the population for which the estimate is requested” (= 7).
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WRIGHT AND ANDERSON TABLE 1 SUBJECTIVEPROBABILITYJUDGMENTS
Panel A, Experiment 1: Mean, (median), and [standard deviation] Anchor condition Situation Low anchor No anchor (mean familiarity) High anchor Fraud (2.96) Compensation (4.00)
.295(.250) [. 1931 .575(.600)
w-41 Grades (4.28)
.323(.325) [. 1251
.391(.350) [.278] .5%(.600) [.269] .373(.350) [. 1771
.464(.400) [.276] .740(.800) [.216] .486(.500) [.158]
Panel B, Experiment 2: Mean, (median), and [standard deviation] Anchor condition Situation (mean familiarity) Low anchor No anchor High anchor Highways (2.19) Fraud (2.51) Dividends (2.79) Compensation (3.01) Weather (3.97) Grades (4.82)
.334(.240) [.229] .365(.220) i.3051 .351(.273) [.229] .364(.350) L.2223 .423(.395) [. 1701 .422(&O) [.223]
.471(.500)
r.2401 .364(.300)
L.2401 .412(.375) [.249] .583(.598) [.256] .402(.450) [.150] .618(.650) [.183]
.527(.500) [.261] .544(.500) [.265] .647(.750) [.217] .705(.850) [.247] .US(.SOO) [.205] .622(.602) [.152]
Low/high .169(.150) .164(.200) .163(.175)
Low/high raw .193(.260) .179(.280) .296(.478) .341(.501) .032(.105) .206(.202)
We predicted a significant anchoring x situation familiarity interaction, i.e., decreasing anchoring given increasing situation familiarity. The anchor x familiarity interaction is not significant, F < 1. As indicated in Fig. 1, Panel A, significantly increasing situation familiarity did not diminish the anchoring effect of the preliminary judgment question. The situation mean judgments are significantly different, F(2,216) = 55.88, p < .OOOl, given the overall mean SPs of .383, .637, and .394 for the fraud, compensation, and grades situations, respectively. EXPERIMENT 2 The results of Experiment 1 indicate that (1) there was a consistent anchoring effect of the preliminary judgment and (2) increasing situation familiarity did not result in decreasing anchoring. An alternative explanation concerning the familiarity hypothesis might be that the range of situation familiarity levels considered in Experiment 1 was too narrow to fully address this issue (despite statistically different levels of familiarity).
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l-Continued
Panel C, Experiment 3: Mean, (median), and [standard deviation] Anchor condition Question No anchor High anchor (mean familiarity) Low anchor
Low/high range
Moderate incentive Highways (2.29) Fraud (2.70) Dividends (2.55) Compensation (3.02) Weather (4.38) Grades (4.49) High incentive Highways (2.29) Fraud (2.70)
.296(.228) [.203] .288(.200) [.250] .383(.348) r.2201 .465(.438) i.2121 .494(.500) [.211] .482(&O) [.1781
.485(.450) [.242] .383(.300) i.3091 .479(.450) [.216] .565(.575) [.240] .544(.550) L.1971 .439(/m) [.227]
.665(.800) [.271] .491(.500) [.271] .6@4(.655) [.235] .657(.750) [.247] .651(.750) [.170] .587(.600) [.197]
.369(.573)
.380(.400) I.1931 .288(.260)
.366(.340) [.301] .463(.428) [.284] .624(.603) r.2121 .558(.600) [.257] .607(.633) [.162] .566(.600)
.518(.502) [.245] .473(.448) [.243] .543(.500) [.215] .634(.655) [.225] .618(.600) [.130] .620(.650) [.189]
.138(.102)
[.180] Dividends (2.55) Compensation (3.02) Weather (4.38) Grades (4.49)
.365(.350) [.202] .432(.350) [.243] .516(.500) [.165] .465(.450) [.207]
[.I%1
.203(.300) .221(.308) .192(.313) .157(.250) .267(.201)
.185(.188) .178(.150) .202(.305) .102(.100) .155(.200)
Using the same task structure as in Experiment 1, a new set of subjects responded to six situations that covered a wider range of familiarity. Subjects The subjects were 65 junior or senior business undergraduates at the University of Minnesota. Participation was voluntary. As in Experiment 1, all of the students had completed at least one introductory statistics course. Task and Design The task was the same as in Experiment 1, except that the subjects provided SP judgments for six situations. The mixed design consisted of anchor and familiarity factors.
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WRIGHT AND ANDERSON Panel A, Expetimcnt I(1 11 subjects)
;
0.6
: 0”
0.7
: % = i : : P E
: I
0.6 0.5 0.4 0.3 0.2
* Low Anchor + No Anchor -W High Anchor
I 2
Pad B. Experiment 2 (65 subjects) 0.7 0.6 0.5
+ + +
LOW Anchor No Anchor High Anchor
+ + +
Low Anchor No Anchor High Anchor
0.4
2
4
3 Mean Fsmlliarlty
5
Indication
Panel C. Expimcnt 3 (160 subjects)
FIG. 1. Mean probability and familiarity judgments for anchor conditions.
Materials and Procedure The GPA situation was modified to fit this subject population, use of the i.e., undergraduate grade point of a business school student versus that of an MBA student. Three new situations were added (see Panel B, Appendix). One of the new situations was aimed at very high situational familiarity (the local weather-situation No. 4). The other two situations were designed to be quite unfamiliar (dividends, the yield rate for a ran-
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domly selected common stock listed on the New York Stock Exchange, No. 5, and highways, state per capita expenditures on highways, No. 6). The l-7 Likert familiarity scale was simplified to have anchor labels of 1 = completely unfamiliar, 4 = moderately familiar, and 7 = extremely familiar. The scale used in Experiment 1 specified familiarity in terms of knowledge of the situation and number of observed occurrences (see footnote 2); the revised scale allowed the subject to make a direct assessment of the degree of situation familiarity. Results The six situations span a wide range of situation familiarity. Familiarity ranges from mean (and approximate median) scores of 2.19 to 4.82, with the other four means being spread out over the range (see Table 1, Panel B); the estimated standard deviations are approximately 1.30. The six familiarity means are significantly different, F(5,310) = 53.51, p< .OOOl, two-factor ANOVA. The anchor factor in the ANOVA is also significant, F(2,62) = 4.77, p < .05, given that the familiarity levels tended to be slightly higher in the high anchor condition; the situation by anchor interaction is not significant, F(10,310) = 1.48. Large anchoring effects are indicated in Table 1, Panel B and Fig. 1, Panel B. Relative to the no-choice control condition, the mean SP response is lower in the low anchor condition, and higher in the high anchor condition, in 10 of the 12 comparisons, p = .019 (sign test), usually by a wide margin. The anchoring effect of the preliminary judgment is highly significant, F(2,62) = 18.61, p < .OOOl.The simple effects for the three anchor condition means conditional on each of the six familiarity situations all are significant, F(2,358) = 4.10 or higher, p < .02, except for the weather situation. The mean SPs across the six situations are significantly different, F(5,310) = 4.88, p < .OOl. We predicted a significant anchoring x situation familiarity interaction, i.e., decreasing anchoring given increasing situation familiarity. The anchor x familiarity interaction is significant (F(10,310) = 2.24, p < .05); however, the pattern of the cell means is not as we predicted (Fig. 1, Panel B). There is no evidence for increasing situation familiarity diminishing the anchoring effect of the preliminary judgment question. EXPERIMENT 3 Experiments 1 and 2 reveal significant anchoring, and increasing situation familiarity did not decrease the degree of anchoring. We wondered whether providing performance-contingent incentives for judgment accuracy would (1) motivate the subjects to think more carefully about their SP assessments and (2) make the accuracy criterion more concrete to the
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subjects, therefore resulting in less anchoring, given the preliminary judgment. Both monetary and public recognition incentives contingent on subject performance were added to the task in Experiment 2. Subjects
The 160 undergraduates were randomly divided into two groups: 83 in the moderate incentive condition and 77 in the high incentive condition. As in the first two experiments, all subjects had at least some formal instruction in statistics. Task and Design
The task was the same as in Experiment 2, i.e., the subjects provided SP judgments for the same six situations (Panel B, Appendix). Subjects were in either a preliminary judgment condition (low or high anchor) or the no preliminary judgment control condition. There were two incentive conditions. In the moderate incentive group, the subjects received five points toward their grade in the class (less than 0.25% of the total possible points) for participating in the experiment. This reward was not conditional on their performance; the subjects removed a separate page from the materials and returned the sheet before beginning the task. Subjects in the high incentive group received the same five subjects points. They also were told at the beginning of the experiment that they could receive a financial reward based on how accurately they estimated the known relative frequencies. The payments were: Payment Ranking on accuracy lst-5th most accurate $15.00 6th-10th most accurate $12.00 1Ith-15th most accurate $ 8.00 16th-25th most accurate $ 6.00 $ 4.00 26th-35th most accurate 36th-45th most accurate $ 2.00. Accuracy was specified to the subjects to be the sum of the squared estimation errors for the six situations. To determine the judgment errors and distribute the payoffs, the relative frequencies were obtained from several sources.3 3 Estimates of the environmental relative frequencies for five of the six situations (unknown to the subjects, not for the fraud situation) were obtained to have some information on the “correct” answer and to determine the recipients of the monetary payments. While the accuracy of the subject judgments can be assessed relative to the obtained environmental frequencies, this procedure may be misleading since the reliability of the environmental
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The subjects indicated their name on the completed materials. They were told the final results would be posted publicly. The public recognition aspect may have further increased any motivation added by the monetary incentive. Materials and Procedure The materials and general procedure were the same as in Experiment 2. Results The mean familiarity levels ranged from 2.29 to 4.49 (Table 1, Panel C). A three-factor ANOVA model (incentive, anchor, and situation conditions) for the familiarity indications revealed significantly different familiarity levels for the six situations, F(5,770) = 113.25, p < BOOI; the anchor and incentive main effects, and all of the interactions, are not significant. As was reported for Experiments 1 and 2, the preliminary judgment produced significant anchoring, F(2,154) = 41.85, p < .OOOl(Fig. 1, Panel C). The anchor condition distributions of SPs shift toward the anchor condition levels: For the moderate incentive condition, 11 of the 12 mean SPs are consistent with anchoring (p = .003, sign test) while 10 of 12 means are consistent with anchoring (p = .019, sign test) for the high incentive subjects. The differences between the low anchor and high anchor means (Table 1, Panel C, column 5) are quite large. There is no reliable difference in the SPs across the two incentive conditions, F < 1. Performance-contingent incentives resulted in significantly less anchoring. The differences between the low and high anchor conditions are smaller for the high incentive vs the moderate incentive subjects in five of six situations (Table 1, Panel C, column 5). The significant incentive x anchor condition interaction, F(2,154) = 2.48, p < .W, confkms the hypothesized diminished anchoring, given high incentives. Analysis of the median (vs mean) differences between the low and high anchor conditions (Table 1, Panel C) indicates a stronger effect of high incentives, as clearly shown in Fig. 2. The anchor x familiarity interaction is not significant, F(10,770) = 1.38, n.s.; again there is no evidence that the powerful anchoring effect of the preliminary judgment is diminished by increased familiarity with the judgment situation. Moreover, Fig. 1, Panel C reveals an orderly separaanswers was not investigated. For example, multiple estimates of the environmental frequencies were not obtained. Nevertheless, we did conduct a preliminary analysis of the accuracy of the judgments in the control vs anchor conditions for both the moderate and high incentive conditions. The conclusion is that statistically significant differences do not exist among the incentive and control conditions.
WRIGHT AND ANDERSON
Moderate High
Hbhwrys
Fraud
D4vidmdrCoqms.
Weather
Gmdes
situatioas FIG. 2. Magnitude of effect of incentives on anchorring.
tion of the low anchor, control, and high anchor mean SPs for all of the six situation familiarity levels. The mean SPs for the six situations are significantly different, F(5,770) = 14.33, p < .OOOl.The incentive x familiarity and the three-way interaction are not significant. GENERAL DISCUSSION The results from Experiment 1, 2, and 3 suggest that anchoring is a resilient phenomenon. The effect of making the simple preliminary judgment, “Is the probability of {the target situation} greater than or less than/equal to 0.25 [0.75] (low[high] anchor condition),” was sufficient to affect the magnitude of subjective probabilities. While past studies have reported anchoring effects (e.g., Joyce & Biddle, 1981; Tversky & Kahneman, 1974), this study indicates the considerable impact and prevalence of this unintended anchoring and insufficient adjustment effect.4 4 Realistic anchor conditions were included in this design. Anchor levels could have been selected that were extreme, e.g., asking the subjects to initially focus on extremely unlikely or likely occurrences instead of the .25 and .75 probability levels. Anchoring might then be observed; however, the subjects might question the realism of the experiment, leading to responses that do not reflect their real-world information processing, or the subjects might complete the experiment in a nonserious manner. Another possibility is that subjects in overly extreme anchor conditions might tend to provide what they think the experimenter is looking for, given the extreme, and therefore conspicuous, anchor. Extreme anchors were not used in the current study to avoid these potential design limitations.
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The anchoring effect was so strong that increasing familiarity with judgment situations did not result in decreasing anchoring. Table 1 and Fig. 1 indicate that difference between the low and high anchor conditions remain over a wide range of situation familiarity. For example, in Experiment 1, the absolute values of the differences between the mean judgments for the low and high anchor groups remain approximately the same at 0.169,O.164,and 0.163, given meanfamiliarity indications of 2.96,4.00, and 4.28. Experienced professionals possessmore knowledge of the decision situation and event occurrences than novices (although situation familiarity does not necessarily imply judgment expertise). Professionals frequently make preliminary judgments. The results reported here imply different conclusions given preliminary judgments. If our results generalize to professional judgment situations, experienced professionals may be subject to an anchoring basis even though they are familiar with the judgment situation. Serious judgment limitations can occur if decisions of experts are affected by unintended anchoring effects (e.g., see Joyce & Biddle, 1981). The powerful unintended anchoring effect of the preliminary judgment, unimpinged upon by increased situation familiarity, was significantly diminished by the availability of performance-contingent incentives. Wright and Aboul-Ezz (1988) report a stronger incentive effect for a similar yet more complex and demanding subjective probability task. In contrast, Wright (1987) reports no effect of performance-contingent incentives on the accuracy of correlation judgments, a relatively simple, somewhat perceptual judgment task. Perhaps incentives have a marginal impact only when the task is significantly, but not excessively, demanding on a person’s cognitive resources, and the person is motivated to allocate suffi cient cognitive effort. APPENDIX
Panel A-Illustration
of (High) Anchor Condition
A chief executive officer of a manufacturing firm in the Fortune 1000 industrials is selected at random. (a) Do you believe the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000is greater or less than .75? (Circle 1 or 2 below.) I believe that the probability that the randomly selected CEO’s annual total compensation exceeds $300,000is greater than .75.. . .. . . . .. . . . .. . .. . . . . 1 I believe that the probability that the randomly
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selected CEO’s annual total compensation exceeds $300,000is less than or equal to .75 . . . . .. . . . .2 (b) More precisely, what is your estimate of the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000?(Indicate your estimate by placing a checkmark on the scale below.) !----!----!-___ !----!---_!----!-_-_!__--!__-_ !---_!-___ !-___ !-_--!____ !___. !___!__--!____ !_-__ !_-__ ! 0.0 .05 .l .15 .2 .25 .3 .35 .4 45 .5 .55 .6 .65 .7 .75 .8 .85 .9 .95 1.0 Panel B-Judgment
Situations for the Three Experiments
Experiment I. 1. An MBA student is selected at random from those who started the MBA program at the University of Minnesota this fall quarter. What is your estimate of the probability that this student will have a grade point average of 3.4 or higher at the end of fall quarter? (WA) 2. A chief executive officer of a manufacturing firm in the Fortune 1000industrials is selected at random. What is your estimate of the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000?(Compensation)
3. It is well known that many cases of management fraud go undetected even when competent audits are performed by CPAs. This is particularly true of one specific type of fraud designated by the term “embezzlement.” Specifically, “embezzlement” is defined as the fraudulent appropriation to one’s own personal use of property (money or other assets) lawfully in one’s possession on the job. At the level of higher management (i.e., plant, branch, or store managers and above) this is especially difficult to detect. The reason is that Generally Accepted Auditing Standards are not designed specitically for detection of embezzlement at these higher levels of management. We are interested in obtaining an estimate from those about to embark on careers in managementof their perception of the prevalence of higher management embezzlement as a first step in ascertaining society’s perception of the scope of the problem. If a firm whose financial statements are annually audited by CPAs is randomly selected, what is your estimate of the probability that in the last 12months there has been at least one occurrence, detected or undetected, of significant (i.e., involving assets or cash of $1000 or more) of higher managementembezzlement in this firm? (Fraud) Experiments 2 and 3. 1. An undergraduate student in the School of Management is selected at random. What is your estimate of the proba-
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bility that this student will have a grade point average of 3.1 or higher? (GPA) 2. Same as Question 2, Experiment 1. (Compensation) 3. Same as Question 3, Experiment 1. (Fraud) 4. Fred is a friend of yours who just this fall moved to Minneapolis from California. He has had enough of winter in Minnesota and is able to endure only by dreaming of spring. Fred is an avid fisherman and his current diversion is planning a fishing trip to Mille Lacs Lake (a lake about 90 miles northwest of Minneapolis) for the opening weekend of fishing season, May 15th and 16th. Fred is now at the point of deciding whether or not he should make a deposit on a cabin for that weekend. He will make the deposit if there is a good chance that at least one of the two days will be nice. Fred, being used to California weather, defines “nice” as a day with a high temperature of 65 degrees or above and no rain. As he is not familiar with what Minnesota springs are like, he asks your help in making his decision. What is your estimate of the probability that on the opening weekend of fishing season at least one of the days will be “nice”? (Weather) 5. A firm is randomly selected from a current list of firms whose common stock is listed on the New York Stock Exchange and currently pays a cash dividend. What is your estimate of the probability that this firm’s common stock will have a cash dividend yield (annual cash dividend divided by the market price as of today) of 5% or higher? (Dividends) 6. A state is selected at random from a listing of the 50 states of the United States. What is the probability that for the state selected, the direct expenditures for highways (that is, expenditures for the construction and maintenance of state and interstate highways as well as local roads) by the state and local governments excluding federal funds is $130 or more per person? (Highways) REFERENCES Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco, CA: Freeman. Hogarth, R. M. (1981). Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. Psychological Bulletin, 90, 197-217. Joyce, E. J., & Biddle, G. C. (1981). Anchoring and adjustment in probabilistic inference in auditing. Journal of Accounting Research, 19, 120-145. Nisbett, R., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Englewood Cliffs, NJ: Prentice-Hall. Payne, J.W. (1982). Contingent decision behavior. Psychological Bulletin, 92, 382-402. Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173-220). New York: Academic Press. Shanteau, J. (1989). Cognitive heuristics and biases in behavioral accounting: Review,
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comments and observations. Accounting, Organizations and Society, 14, 165-177. Paper presented at the Audit Judgment Symposium, Center for Accounting Research, University of Southern California, Los Angeles. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 112&1131. Wright, W. F. (1980). Cognitive information processing biases: Implications for producers and users of financial information. Decision Sciences, 11, 284-298. Wright, W. F. (1987). Superior decisions using graphical displays. Unpublished manuscript, Graduate School of Management, University of California, Irvine. Wright, W. F. (1988). Empirical comparison of subjective probability encoding methods. Contemporary Accounting Research, 5, 47-57. Wright, W. F., & Aboul-Ezz, M. (1988). Effects of extrinsic incentives on the quality of frequency assessments. Organizational Behavior and Human Decision Processes, 41, 143-152. RECEIVED: July 31, 1987
BEHAVIOR
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Effects of Situation Familiarity and Financial Incentives on Use of the Anchoring and Adjustment Heuristic for Probability Assessment WILLIAM F. WRIGHT University of California, Irvine
AND URTONANDERSON University of Texas at Austin
Three experiments tested (1) whether anchoring (and insuflicient adjustment) will occur during generation of subjective probabilities and (2) whether situation familiarity and performance-contingent incentives will reduce any anchoring effect. A total of 336 business school students either chose between two alternatives based on a preliminary judgment of relatively unlikely (low anchor) or likely (high anchor) event probabilities before generating fmal probability assessments or were in a no-choice control condition. The results indicate a strong anchoring effect. The anchoring effect is so dominant that increasing situational familiarity did not result in decreased anchoring. Monetary/recognition incentives for accurate judgments did, however, result in significantly less anchoring. Implications are suggested for research on judg0 1989 ment processes and the concept of professional judgment expertise. Academic
Press, Inc.
Given initial results indicating the existence of judgment biases (Tversky & Kahneman, 1974),research on “cognitive heuristics” has evolved to consider the conditions under which judgment biases will occur, and the degree to which they will prevail (Hogarth, 1981; Nisbett & Ross, 1980; Payne, 1982; Ross, 1977; Shanteau, 1989). Anchoring and adjustment (Nisbett & Ross, 1980,pp. 41-42; Tversky & Kahneman, 1974)is a two-stage mental heuristic for generation of subjective probability judgments. The first stage is recall of a previous judgment or generation of a preliminary judgment. The second stage is adjustment of the first-stage estimate, given the remaining information; typically the adjustment is in Financial support for this research was provided by the McKnight Foundation and the Research Committee of the School of Management, University of Minnesota. Helpful comments provided by Richard Helleloid, Robin Keller, and John Payne are gratefully acknowledged. Requests for reprints should be sent to William F. Wright, Graduate School of Management, University of California, Irvine, CA 92717. 68 0749-5978189$3.00 copyrightQ 1989 by Academic Press, Inc. All iigbts
of reprcduction
in my form reserved.
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the expected direction but of insufficient magnitude. One alternative hypothesis to anchoring and insufficient adjustment is single stage, compensatory weighting and integration of the available information into a judgment, without any anchoring effects (see Wright, 1980, pp. 289-290). Situation familiarity could impact the results of cognitive heuristics (Joyce & Biddle, ,198l). In addition to any conceptual knowledge, instances of familiar situations have been described and/or experienced more frequently than instances of less familiar events. Therefore, knowledge of familiar situations provides for more reliable, and perhaps more complete, memory retrieval due to stronger associative bindings among more numerous situational linkages in memory (e.g., Anderson, 1980,pp. 169-221), and reduces the chance of an unintended anchoring bias. Also, if someone is familiar with a situation, there will be less chance for a nondiagnostic, artifactual situational characteristic to provide an anchoring effect. We predicted less anchoring given increasing situation familiarity. The possible anchor subjects made an initial choice, based on a preliminary subjective uncertainty assessment, before providing a final probability judgment. This potential anchoring context was adapted from Joyce and Biddle (1981) to make certain that additional information would not be provided to the subjects in the preliminary judgment conditions. The normative prediction is no effect of the preliminary judgment on a subject’s eventual probability assessment. Performance-contingent incentives may increase a subject’s motivation, causing the individual to think more carefully and completely about the judgment situation and his or her judgment, and therefore not display any anchoring effects. Accumulated knowledge of the situation and awareness of different ways to generate the needed judgment, e.g., anchoring and adjustment or simultaneous compensatory integration could provide a repertoire of available judgment procedures (with alternative levels of cognitive effort being required), without any anchoring necessarily being produced. Also, performance-contingent incentives focus attention on precisely how judgment errors will be measured. Given this focused cognitive effort and concrete specification of the error criterion, performance-contingent incentives were predicted to decrease any anchoring effect (cf. Wright & Aboul-Ezz 1988).The presence of incentives and, therefore, more motivated subjects, could also provide for a more refined and precise test of the familiarity hypothesis. The Three Experiments
In Experiment 1, we investigated whether the magnitude of any anchoring effects on probability assessmentswould decrease, given increas-
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ing situation familiarity. Experiment 2 provided additional investigation of any effects of situation familiarity on anchoring, given a wider range of familiarity levels. In Experiment 3, the motivational and attentiondirecting effects of performance-contingent incentives were predicted to reduce the degree of anchoring. EXPERIMENT 1 Subjects
The participants, 111 first-year Master of Business Administration (MBA) students at the University of Minnesota, participated voluntarily. All had some degree of formal training in probability and statistics. Task and Design
Subjects provided subjective probability (hereafter, SP)judgments for three situations using a direct probability encoding method (Wright, 1988),i.e., direct assignmentof probabilities to possible outcomes. Each subject was in either the control condition or one of two preliminary judgment conditions (low or high possible anchor). Subjects in the two preliminary judgment conditions chose between two alternatives based on their preliminary SP judgment before providing their final SP judgment (see Panel A, Appendix). The preliminary SP judgment was each subject’s own 0.25 (low anchor) or 0.75 (high anchor) cumulative probability. The preliminary judgment question was omitted from the materials to create the no anchor control condition. The alternative hypothesis to anchoring is no effect of the preliminary question, i.e., no anchoring effect. A mixed, two-factor design (anchor and familiarity conditions) was employed with repeated measureson the familiarity condition, i.e., each subject provided an SP for each of three situations. The presentation order of the three situations, and the three anchor conditions, were randomized across the subjects. Materials and Procedure
Familiarity was manipulated by selection of the three judgment situations, i.e., the fraud, compensation, and GPA situations (see Panel B, Appendix). The three situations were pretested for relative familiarity. We also aimed for the mean probabilities in the no-anchor condition to be approximately 0.50 to avoid any floor or ceiling effects, i.e., subject responses clustering at the ends of the response scale.’ Twenty business ’ A floor effect is when judgments cluster at the lower end of the scale without the
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school students pretested the materials. Familiarity was measured on a continuous 1-7 Likert scale with 7 as the highest familiarity.2 The mean familiarity scores are 3.46, 4.59, and 4.85 for the fraud, compensation, and grades situations, respectively, F(2,38) = 7.28, p < .Ol (ANOVA, blocking on subjects), with standard deviations of approximately 1.2. The subjects were told that the purpose of the study was to determine how accurately they could estimate the known relative frequencies. The materials were then distributed and completed. The relative familiarity of the three situations was then assessed as a manipulation check, using the same familiarity scale as was used for the pretest subjects. Results The manipulation check on perceived situation familiarity yielded results similar to those in the pretest, i.e., means of 2.96,4.00, and 4.28, and standard deviations of 1.11, 1.09, and 1.45, for the fraud, compensation, and grades situations, respectively. The familiarity of the three situations is significantly different, F(2,216) = 36.70, p < .OOOl (two-factor ANOVA, anchor factor and situation x anchor interaction not significant, F < 1). The Newman-Keuls test for the pair-wise comparisons indicated that the familiarity of both the compensation and grade situations is significantly different from the fraud situation (p < .Ol); however, the familiarity of the compensation and grade situations is not significantly different. Table 1, Panel A provides the mean, median, and standard deviation of the SPs for each situation and anchor condition (columns 2-4). The results suggest a strong, consistent anchoring effect of the preliminary judgment on the eventual SP assessments (see Fig. 1, Panel A). Relative to the no-choice control condition, the mean SP response is lower in the low anchor condition, and higher in the high anchor condition, for all six comparisons (p = .016, sign test). The anchoring effect of the preliminary judgment is highly significant, F(2,108) = 12.06, p < .OOOl.The ranges from the mean low anchor SP to the mean high anchor SP are 0.169, 0.164, and 0.163 for the fraud, compensation, and grades situations, respecitvely (Table 1, Panel A, column 5). There are no floor or ceiling effects in the SP response distributions across the conditions. opportunity for potential differences in treatments to be revealed; a ceiling effect is a similar occurrence at the upper end of a scale. * The scale endpoints were labeled “unfamiliar with general context and have no knowledge of even one specific case from the population for which the estimate is requested” (= 1); “familiar with general context, but knowledge of the population for which estimate is requested is limited” (=4); and “extremely familiar with general context and have knowledge of a number of cases from the population for which the estimate is requested” (= 7).
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WRIGHT AND ANDERSON TABLE 1 SUBJECTIVEPROBABILITYJUDGMENTS
Panel A, Experiment 1: Mean, (median), and [standard deviation] Anchor condition Situation Low anchor No anchor (mean familiarity) High anchor Fraud (2.96) Compensation (4.00)
.295(.250) [. 1931 .575(.600)
w-41 Grades (4.28)
.323(.325) [. 1251
.391(.350) [.278] .5%(.600) [.269] .373(.350) [. 1771
.464(.400) [.276] .740(.800) [.216] .486(.500) [.158]
Panel B, Experiment 2: Mean, (median), and [standard deviation] Anchor condition Situation (mean familiarity) Low anchor No anchor High anchor Highways (2.19) Fraud (2.51) Dividends (2.79) Compensation (3.01) Weather (3.97) Grades (4.82)
.334(.240) [.229] .365(.220) i.3051 .351(.273) [.229] .364(.350) L.2223 .423(.395) [. 1701 .422(&O) [.223]
.471(.500)
r.2401 .364(.300)
L.2401 .412(.375) [.249] .583(.598) [.256] .402(.450) [.150] .618(.650) [.183]
.527(.500) [.261] .544(.500) [.265] .647(.750) [.217] .705(.850) [.247] .US(.SOO) [.205] .622(.602) [.152]
Low/high .169(.150) .164(.200) .163(.175)
Low/high raw .193(.260) .179(.280) .296(.478) .341(.501) .032(.105) .206(.202)
We predicted a significant anchoring x situation familiarity interaction, i.e., decreasing anchoring given increasing situation familiarity. The anchor x familiarity interaction is not significant, F < 1. As indicated in Fig. 1, Panel A, significantly increasing situation familiarity did not diminish the anchoring effect of the preliminary judgment question. The situation mean judgments are significantly different, F(2,216) = 55.88, p < .OOOl, given the overall mean SPs of .383, .637, and .394 for the fraud, compensation, and grades situations, respectively. EXPERIMENT 2 The results of Experiment 1 indicate that (1) there was a consistent anchoring effect of the preliminary judgment and (2) increasing situation familiarity did not result in decreasing anchoring. An alternative explanation concerning the familiarity hypothesis might be that the range of situation familiarity levels considered in Experiment 1 was too narrow to fully address this issue (despite statistically different levels of familiarity).
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l-Continued
Panel C, Experiment 3: Mean, (median), and [standard deviation] Anchor condition Question No anchor High anchor (mean familiarity) Low anchor
Low/high range
Moderate incentive Highways (2.29) Fraud (2.70) Dividends (2.55) Compensation (3.02) Weather (4.38) Grades (4.49) High incentive Highways (2.29) Fraud (2.70)
.296(.228) [.203] .288(.200) [.250] .383(.348) r.2201 .465(.438) i.2121 .494(.500) [.211] .482(&O) [.1781
.485(.450) [.242] .383(.300) i.3091 .479(.450) [.216] .565(.575) [.240] .544(.550) L.1971 .439(/m) [.227]
.665(.800) [.271] .491(.500) [.271] .6@4(.655) [.235] .657(.750) [.247] .651(.750) [.170] .587(.600) [.197]
.369(.573)
.380(.400) I.1931 .288(.260)
.366(.340) [.301] .463(.428) [.284] .624(.603) r.2121 .558(.600) [.257] .607(.633) [.162] .566(.600)
.518(.502) [.245] .473(.448) [.243] .543(.500) [.215] .634(.655) [.225] .618(.600) [.130] .620(.650) [.189]
.138(.102)
[.180] Dividends (2.55) Compensation (3.02) Weather (4.38) Grades (4.49)
.365(.350) [.202] .432(.350) [.243] .516(.500) [.165] .465(.450) [.207]
[.I%1
.203(.300) .221(.308) .192(.313) .157(.250) .267(.201)
.185(.188) .178(.150) .202(.305) .102(.100) .155(.200)
Using the same task structure as in Experiment 1, a new set of subjects responded to six situations that covered a wider range of familiarity. Subjects The subjects were 65 junior or senior business undergraduates at the University of Minnesota. Participation was voluntary. As in Experiment 1, all of the students had completed at least one introductory statistics course. Task and Design The task was the same as in Experiment 1, except that the subjects provided SP judgments for six situations. The mixed design consisted of anchor and familiarity factors.
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;
0.6
: 0”
0.7
: % = i : : P E
: I
0.6 0.5 0.4 0.3 0.2
* Low Anchor + No Anchor -W High Anchor
I 2
Pad B. Experiment 2 (65 subjects) 0.7 0.6 0.5
+ + +
LOW Anchor No Anchor High Anchor
+ + +
Low Anchor No Anchor High Anchor
0.4
2
4
3 Mean Fsmlliarlty
5
Indication
Panel C. Expimcnt 3 (160 subjects)
FIG. 1. Mean probability and familiarity judgments for anchor conditions.
Materials and Procedure The GPA situation was modified to fit this subject population, use of the i.e., undergraduate grade point of a business school student versus that of an MBA student. Three new situations were added (see Panel B, Appendix). One of the new situations was aimed at very high situational familiarity (the local weather-situation No. 4). The other two situations were designed to be quite unfamiliar (dividends, the yield rate for a ran-
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domly selected common stock listed on the New York Stock Exchange, No. 5, and highways, state per capita expenditures on highways, No. 6). The l-7 Likert familiarity scale was simplified to have anchor labels of 1 = completely unfamiliar, 4 = moderately familiar, and 7 = extremely familiar. The scale used in Experiment 1 specified familiarity in terms of knowledge of the situation and number of observed occurrences (see footnote 2); the revised scale allowed the subject to make a direct assessment of the degree of situation familiarity. Results The six situations span a wide range of situation familiarity. Familiarity ranges from mean (and approximate median) scores of 2.19 to 4.82, with the other four means being spread out over the range (see Table 1, Panel B); the estimated standard deviations are approximately 1.30. The six familiarity means are significantly different, F(5,310) = 53.51, p< .OOOl, two-factor ANOVA. The anchor factor in the ANOVA is also significant, F(2,62) = 4.77, p < .05, given that the familiarity levels tended to be slightly higher in the high anchor condition; the situation by anchor interaction is not significant, F(10,310) = 1.48. Large anchoring effects are indicated in Table 1, Panel B and Fig. 1, Panel B. Relative to the no-choice control condition, the mean SP response is lower in the low anchor condition, and higher in the high anchor condition, in 10 of the 12 comparisons, p = .019 (sign test), usually by a wide margin. The anchoring effect of the preliminary judgment is highly significant, F(2,62) = 18.61, p < .OOOl.The simple effects for the three anchor condition means conditional on each of the six familiarity situations all are significant, F(2,358) = 4.10 or higher, p < .02, except for the weather situation. The mean SPs across the six situations are significantly different, F(5,310) = 4.88, p < .OOl. We predicted a significant anchoring x situation familiarity interaction, i.e., decreasing anchoring given increasing situation familiarity. The anchor x familiarity interaction is significant (F(10,310) = 2.24, p < .05); however, the pattern of the cell means is not as we predicted (Fig. 1, Panel B). There is no evidence for increasing situation familiarity diminishing the anchoring effect of the preliminary judgment question. EXPERIMENT 3 Experiments 1 and 2 reveal significant anchoring, and increasing situation familiarity did not decrease the degree of anchoring. We wondered whether providing performance-contingent incentives for judgment accuracy would (1) motivate the subjects to think more carefully about their SP assessments and (2) make the accuracy criterion more concrete to the
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subjects, therefore resulting in less anchoring, given the preliminary judgment. Both monetary and public recognition incentives contingent on subject performance were added to the task in Experiment 2. Subjects
The 160 undergraduates were randomly divided into two groups: 83 in the moderate incentive condition and 77 in the high incentive condition. As in the first two experiments, all subjects had at least some formal instruction in statistics. Task and Design
The task was the same as in Experiment 2, i.e., the subjects provided SP judgments for the same six situations (Panel B, Appendix). Subjects were in either a preliminary judgment condition (low or high anchor) or the no preliminary judgment control condition. There were two incentive conditions. In the moderate incentive group, the subjects received five points toward their grade in the class (less than 0.25% of the total possible points) for participating in the experiment. This reward was not conditional on their performance; the subjects removed a separate page from the materials and returned the sheet before beginning the task. Subjects in the high incentive group received the same five subjects points. They also were told at the beginning of the experiment that they could receive a financial reward based on how accurately they estimated the known relative frequencies. The payments were: Payment Ranking on accuracy lst-5th most accurate $15.00 6th-10th most accurate $12.00 1Ith-15th most accurate $ 8.00 16th-25th most accurate $ 6.00 $ 4.00 26th-35th most accurate 36th-45th most accurate $ 2.00. Accuracy was specified to the subjects to be the sum of the squared estimation errors for the six situations. To determine the judgment errors and distribute the payoffs, the relative frequencies were obtained from several sources.3 3 Estimates of the environmental relative frequencies for five of the six situations (unknown to the subjects, not for the fraud situation) were obtained to have some information on the “correct” answer and to determine the recipients of the monetary payments. While the accuracy of the subject judgments can be assessed relative to the obtained environmental frequencies, this procedure may be misleading since the reliability of the environmental
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The subjects indicated their name on the completed materials. They were told the final results would be posted publicly. The public recognition aspect may have further increased any motivation added by the monetary incentive. Materials and Procedure The materials and general procedure were the same as in Experiment 2. Results The mean familiarity levels ranged from 2.29 to 4.49 (Table 1, Panel C). A three-factor ANOVA model (incentive, anchor, and situation conditions) for the familiarity indications revealed significantly different familiarity levels for the six situations, F(5,770) = 113.25, p < BOOI; the anchor and incentive main effects, and all of the interactions, are not significant. As was reported for Experiments 1 and 2, the preliminary judgment produced significant anchoring, F(2,154) = 41.85, p < .OOOl(Fig. 1, Panel C). The anchor condition distributions of SPs shift toward the anchor condition levels: For the moderate incentive condition, 11 of the 12 mean SPs are consistent with anchoring (p = .003, sign test) while 10 of 12 means are consistent with anchoring (p = .019, sign test) for the high incentive subjects. The differences between the low anchor and high anchor means (Table 1, Panel C, column 5) are quite large. There is no reliable difference in the SPs across the two incentive conditions, F < 1. Performance-contingent incentives resulted in significantly less anchoring. The differences between the low and high anchor conditions are smaller for the high incentive vs the moderate incentive subjects in five of six situations (Table 1, Panel C, column 5). The significant incentive x anchor condition interaction, F(2,154) = 2.48, p < .W, confkms the hypothesized diminished anchoring, given high incentives. Analysis of the median (vs mean) differences between the low and high anchor conditions (Table 1, Panel C) indicates a stronger effect of high incentives, as clearly shown in Fig. 2. The anchor x familiarity interaction is not significant, F(10,770) = 1.38, n.s.; again there is no evidence that the powerful anchoring effect of the preliminary judgment is diminished by increased familiarity with the judgment situation. Moreover, Fig. 1, Panel C reveals an orderly separaanswers was not investigated. For example, multiple estimates of the environmental frequencies were not obtained. Nevertheless, we did conduct a preliminary analysis of the accuracy of the judgments in the control vs anchor conditions for both the moderate and high incentive conditions. The conclusion is that statistically significant differences do not exist among the incentive and control conditions.
WRIGHT AND ANDERSON
Moderate High
Hbhwrys
Fraud
D4vidmdrCoqms.
Weather
Gmdes
situatioas FIG. 2. Magnitude of effect of incentives on anchorring.
tion of the low anchor, control, and high anchor mean SPs for all of the six situation familiarity levels. The mean SPs for the six situations are significantly different, F(5,770) = 14.33, p < .OOOl.The incentive x familiarity and the three-way interaction are not significant. GENERAL DISCUSSION The results from Experiment 1, 2, and 3 suggest that anchoring is a resilient phenomenon. The effect of making the simple preliminary judgment, “Is the probability of {the target situation} greater than or less than/equal to 0.25 [0.75] (low[high] anchor condition),” was sufficient to affect the magnitude of subjective probabilities. While past studies have reported anchoring effects (e.g., Joyce & Biddle, 1981; Tversky & Kahneman, 1974), this study indicates the considerable impact and prevalence of this unintended anchoring and insufficient adjustment effect.4 4 Realistic anchor conditions were included in this design. Anchor levels could have been selected that were extreme, e.g., asking the subjects to initially focus on extremely unlikely or likely occurrences instead of the .25 and .75 probability levels. Anchoring might then be observed; however, the subjects might question the realism of the experiment, leading to responses that do not reflect their real-world information processing, or the subjects might complete the experiment in a nonserious manner. Another possibility is that subjects in overly extreme anchor conditions might tend to provide what they think the experimenter is looking for, given the extreme, and therefore conspicuous, anchor. Extreme anchors were not used in the current study to avoid these potential design limitations.
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The anchoring effect was so strong that increasing familiarity with judgment situations did not result in decreasing anchoring. Table 1 and Fig. 1 indicate that difference between the low and high anchor conditions remain over a wide range of situation familiarity. For example, in Experiment 1, the absolute values of the differences between the mean judgments for the low and high anchor groups remain approximately the same at 0.169,O.164,and 0.163, given meanfamiliarity indications of 2.96,4.00, and 4.28. Experienced professionals possessmore knowledge of the decision situation and event occurrences than novices (although situation familiarity does not necessarily imply judgment expertise). Professionals frequently make preliminary judgments. The results reported here imply different conclusions given preliminary judgments. If our results generalize to professional judgment situations, experienced professionals may be subject to an anchoring basis even though they are familiar with the judgment situation. Serious judgment limitations can occur if decisions of experts are affected by unintended anchoring effects (e.g., see Joyce & Biddle, 1981). The powerful unintended anchoring effect of the preliminary judgment, unimpinged upon by increased situation familiarity, was significantly diminished by the availability of performance-contingent incentives. Wright and Aboul-Ezz (1988) report a stronger incentive effect for a similar yet more complex and demanding subjective probability task. In contrast, Wright (1987) reports no effect of performance-contingent incentives on the accuracy of correlation judgments, a relatively simple, somewhat perceptual judgment task. Perhaps incentives have a marginal impact only when the task is significantly, but not excessively, demanding on a person’s cognitive resources, and the person is motivated to allocate suffi cient cognitive effort. APPENDIX
Panel A-Illustration
of (High) Anchor Condition
A chief executive officer of a manufacturing firm in the Fortune 1000 industrials is selected at random. (a) Do you believe the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000is greater or less than .75? (Circle 1 or 2 below.) I believe that the probability that the randomly selected CEO’s annual total compensation exceeds $300,000is greater than .75.. . .. . . . .. . . . .. . .. . . . . 1 I believe that the probability that the randomly
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selected CEO’s annual total compensation exceeds $300,000is less than or equal to .75 . . . . .. . . . .2 (b) More precisely, what is your estimate of the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000?(Indicate your estimate by placing a checkmark on the scale below.) !----!----!-___ !----!---_!----!-_-_!__--!__-_ !---_!-___ !-___ !-_--!____ !___. !___!__--!____ !_-__ !_-__ ! 0.0 .05 .l .15 .2 .25 .3 .35 .4 45 .5 .55 .6 .65 .7 .75 .8 .85 .9 .95 1.0 Panel B-Judgment
Situations for the Three Experiments
Experiment I. 1. An MBA student is selected at random from those who started the MBA program at the University of Minnesota this fall quarter. What is your estimate of the probability that this student will have a grade point average of 3.4 or higher at the end of fall quarter? (WA) 2. A chief executive officer of a manufacturing firm in the Fortune 1000industrials is selected at random. What is your estimate of the probability that this CEO’s annual total compensation (i.e., all compensation including salary, bonuses, stock options, etc.) exceeds $300,000?(Compensation)
3. It is well known that many cases of management fraud go undetected even when competent audits are performed by CPAs. This is particularly true of one specific type of fraud designated by the term “embezzlement.” Specifically, “embezzlement” is defined as the fraudulent appropriation to one’s own personal use of property (money or other assets) lawfully in one’s possession on the job. At the level of higher management (i.e., plant, branch, or store managers and above) this is especially difficult to detect. The reason is that Generally Accepted Auditing Standards are not designed specitically for detection of embezzlement at these higher levels of management. We are interested in obtaining an estimate from those about to embark on careers in managementof their perception of the prevalence of higher management embezzlement as a first step in ascertaining society’s perception of the scope of the problem. If a firm whose financial statements are annually audited by CPAs is randomly selected, what is your estimate of the probability that in the last 12months there has been at least one occurrence, detected or undetected, of significant (i.e., involving assets or cash of $1000 or more) of higher managementembezzlement in this firm? (Fraud) Experiments 2 and 3. 1. An undergraduate student in the School of Management is selected at random. What is your estimate of the proba-
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bility that this student will have a grade point average of 3.1 or higher? (GPA) 2. Same as Question 2, Experiment 1. (Compensation) 3. Same as Question 3, Experiment 1. (Fraud) 4. Fred is a friend of yours who just this fall moved to Minneapolis from California. He has had enough of winter in Minnesota and is able to endure only by dreaming of spring. Fred is an avid fisherman and his current diversion is planning a fishing trip to Mille Lacs Lake (a lake about 90 miles northwest of Minneapolis) for the opening weekend of fishing season, May 15th and 16th. Fred is now at the point of deciding whether or not he should make a deposit on a cabin for that weekend. He will make the deposit if there is a good chance that at least one of the two days will be nice. Fred, being used to California weather, defines “nice” as a day with a high temperature of 65 degrees or above and no rain. As he is not familiar with what Minnesota springs are like, he asks your help in making his decision. What is your estimate of the probability that on the opening weekend of fishing season at least one of the days will be “nice”? (Weather) 5. A firm is randomly selected from a current list of firms whose common stock is listed on the New York Stock Exchange and currently pays a cash dividend. What is your estimate of the probability that this firm’s common stock will have a cash dividend yield (annual cash dividend divided by the market price as of today) of 5% or higher? (Dividends) 6. A state is selected at random from a listing of the 50 states of the United States. What is the probability that for the state selected, the direct expenditures for highways (that is, expenditures for the construction and maintenance of state and interstate highways as well as local roads) by the state and local governments excluding federal funds is $130 or more per person? (Highways) REFERENCES Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco, CA: Freeman. Hogarth, R. M. (1981). Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. Psychological Bulletin, 90, 197-217. Joyce, E. J., & Biddle, G. C. (1981). Anchoring and adjustment in probabilistic inference in auditing. Journal of Accounting Research, 19, 120-145. Nisbett, R., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Englewood Cliffs, NJ: Prentice-Hall. Payne, J.W. (1982). Contingent decision behavior. Psychological Bulletin, 92, 382-402. Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173-220). New York: Academic Press. Shanteau, J. (1989). Cognitive heuristics and biases in behavioral accounting: Review,
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comments and observations. Accounting, Organizations and Society, 14, 165-177. Paper presented at the Audit Judgment Symposium, Center for Accounting Research, University of Southern California, Los Angeles. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 112&1131. Wright, W. F. (1980). Cognitive information processing biases: Implications for producers and users of financial information. Decision Sciences, 11, 284-298. Wright, W. F. (1987). Superior decisions using graphical displays. Unpublished manuscript, Graduate School of Management, University of California, Irvine. Wright, W. F. (1988). Empirical comparison of subjective probability encoding methods. Contemporary Accounting Research, 5, 47-57. Wright, W. F., & Aboul-Ezz, M. (1988). Effects of extrinsic incentives on the quality of frequency assessments. Organizational Behavior and Human Decision Processes, 41, 143-152. RECEIVED: July 31, 1987