Decision making in groups:strategic behaviour,

biased processing and interpersonal emotions

Claudia Toma Laboratoire de Psychologie Sociale, Grenoble University

Louvain, May the 10th, 2007

Overview of this talk

Research Directions

I. Strategic information sharing and decision quality

3 Studies ( I.1, I.2, & I.3)

II. Biased processing in decision making

3 Studies (II.1, II.2, & II.3)

Possible contributions to ADSR

Decision making in groups

Decision making involves information processing, namely sharing and use of available information that group members possess (Hinsz, Tindale, & Vollrath, 1997).

▪ Hidden profile studies:- groups are less than optimal users of information- group decisions are often suboptimal (Stasser, 1999).

The added value of decision making in groups (McGrath, 1984):

information gains & improved decision quality

Hidden profile paradigm

(Stasser & Titus, 1985, 1987, 2003)

Decision1

(Member 1)

Decision 2

(Member 2)

Decision 3

(Member 3)

Optimal Decision

(Group) PHASE I : individual decisionsPHASE II: group discussion

Sharedinformation

Unsharedinformation 1

Unshared

informatio

n 2

Unsh

ared

information

3

Biased sampling effect

POOLING: Shared Unshared information

REPETITION: Shared > Unshared information

DISCUSSION TIME: Shared > Unshared information

Poor decisionquality

(Stasser & Stewart, 1992; Stewart & Stasser, 1998; Stasser, Stewart, & Wittenbaum, 1995; Hollingshead, 1996; Larson, Christensen, Abbott, & Franz, 1996;Brodbeck, Kerschreiter, Mojzisch, Frey, & Schulz-Hardt, 2002)

Theoretical explanations

BIASED SHARING and PROCESSING Collective sampling bias (Stasser & Titus, 1985, 1987)

Confirmation bias (individual decisions focusing) (Greitemeyer & Schulz-Hardt, 2003 )

SOCIAL VALUE of SHARED INFORMATION Social validation (Wittenbaum, Hubbell, & Zuckerman, 1999)

Toward a “SOCIAL VALUE of UNSHARED

INFORMATION” explanation

The control of information is an important base of

social power (French & Raven, 1959).

Group members should be motivated to strategically use their information in order to get a competitive advantage in group.

Competition is likely to occur in hidden profiles

(Wittenbaum, Hollingshead, & Botero, 2004).

Motivated information sharing and use (Wittenbaum et al., 2004)

Features of Context

Members’Goals

What Information is Mentioned?

How InformationIs Used?

To Whom ?

DecisionQuality

MembersRelations

TASK

AFFECTIVE

OUTPUTS

PROCESSES

INPUTS

Cooperationvs.

Competition

UnsharedShared

HiddenProfile

Discovery

MistrustHarmful

Intentions

Disconfirmationof initial decisions

GoalsInterdependence

+ and -

Hypothesis 1: less information sharing, especially unshared information.

Hypothesis 2: a) lesser use of disconfirmation; b) mediation by expressed initial decisions (dissent).

Hypothesis 3: a) suboptimal decisions;b) mediation by unshared information and

disconfirmation.

I. Strategic information sharing and decision quality: Main Hypotheses

Competition, compared to cooperation, leads to:

ProcedurePHASE I: individual decisions

Member 1

Member 2

Member 3

Decision 1

Decision 2

Decision 3

Dissent

PHASE III: interpersonal emotions measures

PHASE II: group decision

COOPERATION

COMPETITION

GroupDiscussionvideotaped and coded

=

Results on group processes:

information sharing (H1)

F(1,26) = 7.42, p < .05.

Similar results were found for information repetition.

23,21

14,4613,14

10,43

0

5

10

15

20

25

cooperation competition

unshared

shared

Results on group processes:disconfirmation of initial decisions (H2a & H2b):

Cooperation (+1)

Competition (-1) Disconfirmation.70*** (.01 ns)

Initialdecisions(dissent).85*** .82***

zSobel = 3.60

p<.001

.70***

Results on outcome :Decision quality (H3a & H3b)

Cooperation (+1)

Competition (-1)Decisionquality1.74** (1.10 ns)

Unsharedinformation

.60** .23*

zSobel = 2.18

p<.05

Disconfirmation

.70***

1.74** (.69 ns)

1.38*

zSobel = 2.31

p<.05

1.74**

Mistrust, harmful intentions and decision making

Mood influence information processing (Forgas, 1992). And focusing in hypothesis testing (Gangemi & Mancini, 2007).

2 3 4 5 6

1. Decision quality .74*** .69*** -.49** -.44* -.46*

2. Disconfirmation .81*** -.48** -.42* -.44*

3. Unshared info -.55** -.48** -.51**

4. Mistrust 91.*** .84***

5. Self harmful intentions

.78***

6. Others’ harmful intentions

Preliminary Conclusions In competition (compared to cooperation) group members are

strategic when pooling less unshared but not less shared information.

Initial decisions are less mentioned in competition which explain that disconfirmation and unshared information were ineffective, leading to poor decision quality.

Mistrust and harmful intentions are linked to decision quality.

ADDITIONAL QUESTIONS :

Is competition responsible for the biased sampling effect ?

Under which conditions? Study I.3

Ineffective disconfirmation (in competition) might reflect a biased

processing, namely focusing on initial decisions. Study II.1

Study I.3We manipulated task uncertainty with regard to the final decision:

- High uncertainty (four alternatives are equally probable)- Low uncertainty (one alternative is probable)

Reducing uncertainty is a main concern when taking decisions(Raiffa, 1968; Tversky & Kahneman, 1974).

Uncertainty leads to two distinct effects:a) motivates information search (Lanzetta & Driscoll, 1966, 1968);

COOPERATION : unshared > shared information

b) results in higher levels of threat (Conolley, Gerard, & Kline, 1978).

COMPETITION : shared > unshared information

Results on information sharing

18,42

11,67

5,25

10,92

4

9

14

19

24

29

cooperation competition

27,08

11,67

21,25

18,25

4

9

14

19

24

29

cooperation competition

unshared

shared

Low uncertainty High uncertainty

F (1,43) = 4.43, p <.05

Participants’ ratings : more information was needed and more competition was perceived under high uncertainty.

II. Biased processing: Study II.1.

Hypothesis : Less disconfirmation in competition reflects more focusing on initial decisions (confirmation bias).

Incompleteinformation

↓Decision 1

(suboptimal)

Phase I

Manipulation

Coop, Comp

Dissent

Phase II

All informationavailable

↓Final decision

Phase IV

Subsequentinformationevaluation

(consistentinconsistent)

Phase III

We manipulated: Cooperation vs. Competition

Dissent (Yes vs. No)

using an individual task with fictitious group discussion.

Confirmation bias: focusing on initial decisions

χ²Wald (1, N=80) = 3.99, p < .05

4

14

67

0

2

4

6

8

10

12

14

16

cooperation competition

dissent

no dissent

Mediated moderation hypothesis

Information value = consistent information – inconsistent information

CooperationCompetition

ConfirmationInformation

value

Dissent

PREDICTORS

Equation 1

(DV=CB)

Equation 2

(ME)

Equation 3

(DV=CB)

B Wald B t B Wald

IV : COOP, COMP 1.231 6.01* -0.575 -1.25 1.088 3.46

MO: DISSENT .464 0.85 -0.808 -1.76 0.109 0.03

IV X MO 2.005 3.98* -3.017 -3.29*** 1.103 0.89

ME: INFO

VALUE-0.529 9.73**

ME X MO -0.391 1.32

Muller, Judd, & Yzerbyt (2005)

General Conclusions

In decision making tasks involving social threat (competition) and interdependence with others (hidden profile) :

people are strategic when pooling information; this effect is reinforced under high uncertainty;

people are biased when processing subsequent information;

strategic information pooling and biased processing result in poor decision quality;

mistrust and harmful intentions are linked to strategic andbiased processing in decision making.

Possible contributions to ADSR

1)Emotion perception and decision making :others’ emotions as a source of information

Aim: Directly investigating the effect of mistrust and others’ harmful intentions on post-decisional information search andbiased processing.

General Hypothesis: Mistrust and harmful intentions should lead to focus on initial decision and increase in search for consistent information.

2) Emotion perception and decision making :biases in decoding others’ emotions

Aim: Investigating when and why biases occur in decodingemotions (e.g., fear of exploitation) in threatening situationsinvolving social interdependence and how this impacts decisions(e.g., playing cooperatively).

General Hypothesis: Biases in decoding others emotions should occur more likely when there is high similarity between self andothers with impact on decision processes.

3) Empathy and decision making :affective forecasting

Aim: Investigating the role of expectations on affective forecastingand empathetic responses in cooperation and competition andhow this impact behavioral decisions (e.g., information sharing).

General Hypothesis: In competition, compared to cooperation,individuals underestimate others cooperative behavior and therefore they should primarily infer negative emotional state(e.g., distress), manifest counter empathetic responses leadingto information withholding and distortion.

Decision making in groups:strategic behaviour,

biased processing and interpersonal emotions

Claudia Toma Laboratoire de Psychologie Sociale, Grenoble

Louvain, May the 10th, 2007

Task characteristics

Dissent between individual decisions and a disconfirmation strategy leading to an optimal decision; (pilot studies 1- 4)

Known diagnostic value of unshared information and possibilityto identify shared from unshared information; (pilot study 5)

Perceived intragroup interdependence. (pilot study 6)

χ² (1, N=28) = 12.85,

p < .001

Results on outcome:

decision quality (H3a) 13

4

1

10

0

2

4

6

8

10

12

14

cooperation competition

success

failure

Mistrust and jealousy

1,63

3,04

2,24

1,45

0

0,5

1

1,5

2

2,5

3

3,5

Mistrust Jealousy

cooperation

competition

t(26)= 4.48p < .001

t(26)= 1.70p = .10