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Decision making in groups: strategic behaviour, biased processing and interpersonal emotions Claudia Toma Laboratoire de Psychologie Sociale, Grenoble.

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Presentation on theme: "Decision making in groups: strategic behaviour, biased processing and interpersonal emotions Claudia Toma Laboratoire de Psychologie Sociale, Grenoble."— Presentation transcript:

1 Decision making in groups: strategic behaviour, biased processing and interpersonal emotions Claudia Toma Laboratoire de Psychologie Sociale, Grenoble University Louvain, May the 10th, 2007

2 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

3 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

4 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 Shared information Unshared information 1 Unshared information 2 Unshared information 3

5 Biased sampling effect POOLING: Shared  Unshared information REPETITION : Shared > Unshared information DISCUSSION TIME: Shared > Unshared information Poor decision quality (Stasser & Stewart, 1992; Stewart & Stasser, 1998; Stasser, Stewart, & Wittenbaum, 1995; Hollingshead, 1996; Larson, Christensen, Abbott, & Franz, 1996; Brodbeck, Kerschreiter, Mojzisch, Frey, & Schulz-Hardt, 2002)

6 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)

7 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).

8 Motivated information sharing and use (Wittenbaum et al., 2004) Features of Context Members’ Goals What Information is Mentioned ? How Information Is Used? To Whom ? Decision Quality Members Relations TASK AFFECTIVE OUTPUTS PROCESSES INPUTS Cooperation vs. Competition Unshared Shared Hidden Profile Discovery Mistrust Harmful Intentions Disconfirmation of initial decisions Goals Interdependence + and -

9 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:

10 Procedure PHASE 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 Group Discussion videotaped and coded =

11 Results on group processes: information sharing (H1) F(1,26) = 7.42, p <.05. Similar results were found for information repetition.

12 Results on group processes: disconfirmation of initial decisions (H2a & H2b): Cooperation (+1) Competition (-1) Disconfirmation.70*** (.01 ns) Initial decisions (dissent).85***.82*** z Sobel = 3.60 p<.001.70***

13 Results on outcome : Decision quality (H3a & H3b) Cooperation (+1) Competition (-1) Decision quality 1.74** (1.10 ns) Unshared information.60**.23* z Sobel = 2.18 p<.05 Disconfirmation.70*** 1.74** (.69 ns) 1.38* z Sobel = 2.31 p<.05 1.74**

14 Mistrust, harmful intentions and decision making  Mood influence information processing (Forgas, 1992).  And focusing in hypothesis testing (Gangemi & Mancini, 2007). 23456 1. Decision quality.74***.69***-.49**-.44*-.46* 2. Disconfirmation.81***-.48**-.42*-.44* 3. Unshared info-.55**-.48**-.51** 4. Mistrust91.***.84*** 5. Self harmful intentions.78*** 6. Others’ harmful intentions

15 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

16 Study I.3 We 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

17 Results on information sharing 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.

18 II. Biased processing: Study II.1.  Hypothesis : Less disconfirmation in competition reflects more focusing on initial decisions (confirmation bias). Incomplete information ↓ Decision 1 (suboptimal) Phase I Manipulation Coop, Comp Dissent Phase II All information available ↓ Final decision Phase IV Subsequent information evaluation (consistent inconsistent) Phase III  We manipulated: Cooperation vs. Competition Dissent (Yes vs. No) using an individual task with fictitious group discussion.

19 Confirmation bias: focusing on initial decisions χ² Wald (1, N=80) = 3.99, p <.05

20 Mediated moderation hypothesis Information value = consistent information – inconsistent information Cooperation Competition Confirmation Information value Dissent

21 PREDICTORS Equation 1 (DV=CB) Equation 2 (ME) Equation 3 (DV=CB) BWaldBtB IV : COOP, COMP 1.2316.01*-0.575-1.251.0883.46 MO: DISSENT.4640.85-0.808-1.760.1090.03 IV X MO 2.0053.98*-3.017-3.29***1.1030.89 ME: INFO VALUE -0.5299.73** ME X MO -0.3911.32 Muller, Judd, & Yzerbyt (2005)

22 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 and biased processing in decision making.

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

24 2) Emotion perception and decision making : biases in decoding others’ emotions Aim: Investigating when and why biases occur in decoding emotions ( e.g., fear of exploitation ) in threatening situations involving 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 and others with impact on decision processes.

25 3) Empathy and decision making : affective forecasting Aim: Investigating the role of expectations on affective forecasting and empathetic responses in cooperation and competition and how 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 leading to information withholding and distortion.

26 Decision making in groups: strategic behaviour, biased processing and interpersonal emotions Claudia Toma Laboratoire de Psychologie Sociale, Grenoble Louvain, May the 10th, 2007

27 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 possibility to identify shared from unshared information; (pilot study 5)  Perceived intragroup interdependence. (pilot study 6)

28 χ² (1, N=28) = 12.85, p <.001 Results on outcome: decision quality (H3a)

29 Mistrust and jealousy t(26)= 4.48 p <.001 t(26)= 1.70 p =.10

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