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Erschienen in: Theory and Decision 2/2018

31.05.2017

Are groups ‘less behavioral’? The case of anchoring

verfasst von: Lukas Meub, Till Proeger

Erschienen in: Theory and Decision | Ausgabe 2/2018

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Abstract

Economic small group research points to groups as more rational decision-makers in numerous economic situations. However, no attempts have been made to investigate whether groups are affected similarly by behavioral biases that are pervasive for individuals. If groups were also able to more effectively avoid these biases, the relevance of biases in actual economic contexts dominated by group decision-making might be questioned. We consider the case of anchoring as a prime example of a well-established, robust bias. Individual and group biasedness in three economically relevant domains are compared: factual knowledge, probability estimates and price valuations. In contrast to previous anchoring studies, we find groups to successfully reduce, albeit not eliminate, anchoring in the factual knowledge domain. For the other two domains, groups and individuals are equally biased by external anchors. Group cooperation thus reduces biases for predominantly intellective tasks only, while no such reduction is achieved when judgmental aspects are involved.

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Fußnoten
1
Other contributions questioning the robustness of behavioral biases under market conditions, mostly drawing on field evidence from well-functioning markets, include, e.g. (List 2003, 2004a, b, 2006), Levitt and List (2007), Cecchi and Bulte (2013).
 
2
Furnham and Boo (2011) provide a general overview, Epley and Gilovich (2010) sum up the discussions on the theoretical foundations of anchoring. There are several contradictory methodological notions within psychological research regarding the reasons and influences on anchoring. For a more detailed view into this recent discussion, we refer to Frederick and Mochon (2012), Critcher et al. (2014), Wegener et al. (2010a) and Russo (2010), Frederick et al. (2010), Epley and Gilovich (2010) and Wegener et al. (2010b).
 
3
The pictures shown to participants are documented in Appendix B. All respective brands were erased from the pictures to prevent subjects from being influenced by brand names. All items were sold on web-based platforms comparable to eBay. Although smartphones were banned during the experiment, we additionally ensured that the correct answers to our questions could not be easily looked up.
 
4
While 90 seconds may appear to be a too short as a timeframe, our pilot experiment indicated that the majority of groups did not use the entire time. Some groups would, however, decide on a correct solution within the first minute and spend the remainder of the time with idle talk on personal topics. We thus decided not to further extend the time frame for group discussions.
 
5
Screenshots of the decision screens presented to participants in the individual and group experiments in both treatments are provided in Appendix C.
 
6
An appropriate robustness check whether subjects were able to identify the answers relevant for their payment and adjust their effort accordingly can be undertaken by considering the time it took groups and individuals to enter an answer conditional on the domains of the questions. Group (individual) players took on average 82 (59) s to answer a factual knowledge question, 74 (60) seconds for probability and 75 (62) s for price estimates. This shows that groups actually took some more time for factual knowledge questions on average. However, a difference of five seconds could hardly support the claim that subjects were able to identify relevant questions and thus refrain from putting effort in the questions irrelevant for payoffs. After all, groups still discussed probabilities and prices for about 75 s on average. Further, for individuals no such difference can be found. These numbers, therefore, could not support the claim that probability and price estimates were ignored for their irrelevance to payments.
 
7
The full chat protocols can be obtained from the authors upon request.
 
8
The fixed payment for groups was implemented for the case that groups would regularly fail to provide matching responses within 90 s. In this case, group members were also shown another screen for 30 s asking them to provide a common answer to avoid missing values. However, this case rarely occurred.
 
9
We recorded demographic information, gender and fields of study of all participants in a questionnaire after the experiment, finding that there are no significant or systematic differences with respect to the distribution over treatments. In the individual (group) player experiment 52% (56%) were female, 91% (86%) native speakers and 83% (89%) already participated in at least one experiment (Fisher’s exact test, two-sided, p = 0.452 for gender; p = 0.345 for language; p = 0.135 for participation). On average they were 23.6 (24.4) years old and studied for 6.2 (5.5) semesters (Wilcoxon rank-sum test, z = −1.349, p = 0.1172 for age; z = 0.836, p = 0.4034 for semester). Also, there is no significant difference regarding the distribution across the major fields of study (Fisher’s exact test, two-sided, p = 0.26). The original instructions were in German and are available from the authors upon request. A translation is provided in Appendix A.
 
10
There are 2.5% missing values for individual decisions, i.e. no estimate was entered before the time limit. For groups, 67% of all decisions were taken within the 90 s time limit, 27% took up the additional 30 seconds and 6% are missing values.
 
11
E.g. for individuals players, the low anchor at exercise 7 is exactly 2121, for groups it is 1000. It cannot be ruled out that 2121 seems more or less plausible than a round number like 1000 per se, which might interfere with the anchoring bias. Accordingly, we round off thousands to hundreds and hundreds to tens.
 
12
We measure accuracy by estimations’ absolute deviations from correct values divided by these correct values to obtain absolute deviations in percentage points, which allow for pooling the results. For the five factual knowledge questions, this ratio on average amounts to 0.821 for individuals with a median of 0.563; for group players, the mean is 0.912 and the median 0.595. This difference is not statistically significant (Wilcoxon rank-sum test, z = 0.206, p = 0.8366). Please note that this result holds when excluding question 1 from the analysis. However, the numbers show that there are several extreme values in group decisions, which causes the means to be quite different, while medians are similar.
 
13
Due to the distributions of estimations in the calibration treatments, we have to assign estimations in the anchor conditions to the closest available estimation value in calibration and match the respective point value. For example, if an estimated value of 20 forms the 20th percentile and an estimation of 30 the 30th percentile, values in the anchor condition smaller or equal to 25 are assigned 20 points, while values greater than 25 transform to 30 points.
 
14
For theoretical consideration about the process underlying the overshooting adjustment according to the anchors, see, e.g. Jacowitz and Kahneman (1995), who also find higher anchors to be more effective.
 
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Metadaten
Titel
Are groups ‘less behavioral’? The case of anchoring
verfasst von
Lukas Meub
Till Proeger
Publikationsdatum
31.05.2017
Verlag
Springer US
Erschienen in
Theory and Decision / Ausgabe 2/2018
Print ISSN: 0040-5833
Elektronische ISSN: 1573-7187
DOI
https://doi.org/10.1007/s11238-017-9608-x

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