Group Decision Making 1

Group Decision Making
R. Scott Tindale
Loyola University Chicago
Tatsuya Kameda
Hokkaido University
Verlin B. Hinsz
North Dakota State University

Authors’ Notes
This chapter was written with the support of grants from the National Science Foundation
to the first (SBR-9730822) and third (BCS-9905397) authors. Support to the second author wasprovided by the Grant- in-Aid for Scientific Research 11610096 from the Ministry of Education,
Culture, Sports, Science and Technology of Japan. The chapter was completed while the third
author held a National Research Council Senior Research Associateship Award at the Air Force
Research Laboratory, Human Effectiveness Directorate, Brooks Air Force Base. Direct
correspondence to R. Scott Tindale, Department of Psychology, Loyola University of Chicago,6525 N. Sheridan Rd., Chicago, IL 60626 – or via e-mail: rtindal@luc.edu.

To appear in M. A. Hogg & J. Cooper (Eds.) Sage handbook of social psychology. London:
Sage Publications, Inc.

Group Decision Making 2
Groups as decision-making bodies have been afforded a special status in society from atleast the times of the early Greek civilization that developed democratic voting structures. This
special status remains in tact in most societ ies and cultures today. Legislatures decide whichbills to pass into law; juries decide the guilt or innocence of defendants and the amount ofdamages awarded to plaintiffs; school boards decide how to structure the curricula used to teachour children; sales teams decide how to market new products; corporate boards decide whichinvestments are warranted and which person should serve as CEO. Although individuals makemany decisions in both the public and private sector, the truly important decisions are generally
assigned to groups.
Groups are seen as superior to individuals as decision-making entities for at least two
reasons. First, groups can represent a larger and more diverse set of perspectives, constituencies,
etc. Thus, they tend to be seen as more fair by providing “voice” or input from a greater portionof the body for which the decision is made (Darley & Tyler, this volume; Folger, 1977; Thibaut& Walker, 1975; Tyler & Smith, 1998). However, groups are also perceived as “better” than
individuals at making important decisions (Paulus, Dzindolet, Poletes, & Comacho, 1993). The
idea that “two heads are better than one” is widespread and typically accurate, based on theempirical record (Hastie, 1986; Hill, 1982; Kerr, MacCoun, & Kramer, 1996a ; Laughlin & Ellis,
1986). Although social psychological research has focused on both the fairness and performanceof group decisions, the main focus of this chapter will be on the latter. We will highlight someof what is currently known about how groups reach consensus on decision- making/problemsolving tasks, and how such consensus processes affect the quality or accuracy of the final groupresponse. Because the field is far too large to do a complete review of the literature, we will
focus on only those theories and studies that we feel best represent the current state of affairs.

Group Decision Making 3
Much of the early work on group decision- making focused on individual member
preferences as the legitimate inputs for group choice (Kameda, Tindale, & Davis, 2002). This
work stemmed, in part, from the political and economic work on “social choice theory” (Arrow,
1963; Black, 1958; Grofman & Owen, 1986). In social psychology, the seminal work by Lorge
and Solomon (1955) spawned a number of general models of social combination processes that
could be used to predict the final group outcome from member preferences (see Davis, 1973;
1996; Hinsz, 1999; Kerr, 1981; Laughlin & Hollingshead, 1995; Penrod & Hastie, 1981; Shiflett,1979; Stasser & Davis, 1981; Steiner, 1972). However, more recent work has begun to viewgroups as information processing systems (Brauner & Scholl, 2000; Hinsz, Tindale, & Vollrath,
1997; Larson & Christensen, 1993). As such, many recent models have begun to view cognition
as an additional legitimate le vel of aggregation (Gigone & Hastie, 1996; Ickes & Gonzalaz,
1994; Larson, Foster-Fishman, & Keys, 1994; Stasser & Titus, 1985; 1987; Stasser & Stewart,1992).
Hinsz et al. (1997) defined information processing at the group level as “the degree towhich information, ideas, or cognitive processes are shared or are being shared among the groupmembers …” (p. 43 – italics added). Kameda, Tindale, and Davis (2002) argued that “social
sharededness” is a multi- level phenomenon that can be used to understand group decision
making at both the preference (response) and information (cognitive) level. Kameda et al.
argued that the degree to which preferences and/or information were “socially shared” was a key
aspect to understanding group decision processes and outcomes. In essence, they argued thatthings that are shared among most or all of the group members exert an extraordinary influenceon group decision processes and outcomes. Tindale and Kameda (2000) extended the idea ofsocial sharedness to a variety of group characteristics besides preferences and information – e.g.,Group Decision Making 4group identities, mental models, metacognitions, etc. (see also Tindale, Meisenhelder, DykemaEngblade, and Hogg, 2001).
In the current chapter, we review the work on group decision- making using a “social
sharedness” theme. We attempt to show that much of the literature can be understood in relation
to sharedness at one of three levels: preferences, cognitions, and metacognitions. At each level,
the degree of sharedness is important for understanding both how groups reach consensus and on
the decision alternative or judgment position on which the group finally decides. In addition,
sharedness on different levels can interact to affect both group process and performance.
Although social sharedness is a fairly recent theme in the small groups literature, it provides aframework for both understanding much of the current literature and for guiding future researchendeavors. Thus, after reviewing the literature in terms of socially shared preferences,cognitions, and metacognitions, we outline some potentially fruitful avenues for further
investigation.
Socially Shared Preferences
Social Decision Scheme Theory
As stated above, the central problem for early work on group decision- making was how
individual member preferences are aggregated into a final group choice. In line with the socialchoice-theory tradition in economics and political science (e.g., Arrow, 1963; Black, 1958; Sen,
1977), these works regarded individual preferences as a main locus of group interaction, andfocused on how those preferences change over time and are combined to yield a final groupconsensus (Kerr, 1981; Penrod & Hastie, 1981; Stasser & Davis, 1981).
Among these approaches, probably the most comprehensive conceptual system fordescribing group aggregation processes is Davis’ Social Decision Scheme (SDS) theory (1973,

Group Decision Making 5
1996; Stasser, Kerr, & Davis, 1989). SDS theory assumes that small group interaction can beseen essentially as a combinatorial process, in w hich preferences for decision alternatives acrossgroup members are combined in such a way as to allow the group to reach consensus on a single
group choice. The combinatorial process appears to vary as a function of the group task,
environment and other factors. SDS theory provides a formal way to probe the aggregation
process that best summarizes the group interaction in a given setting or context. In this analysis,
candidates of combinatorial processes that may operate in the decision setting are represented as
stochastic matrices called decision schemes (Davis, 1973).
For purposes of illustration, suppose a six-person jury is working on a criminal case. As
shown in Table 1, there are 7 distinguishable preference-patterns that those 6 jurors may arra ythemselves over guilty and not-guilty verdicts (6G-0NG, 5G-1NG, …, 0G-6NG), prior to groupinteraction. Table 1 provides a matrix representation of two simple group -aggregation models,referred to as “social decision schemes ”; proportionality and majority-equiprobability-otherwise,that may characterize group aggregation process in this case. Each element of the matrix
represents the conditional probability that a group with a specific preference pattern (e.g., a jury
initially composed of 2 guilty-saye rs and 4 not-guilty sayers) decides on an alternative (guilty ornot- guilty) for a group-aggregation model. The proportionality model assumes that theprobability that a group will choose a particular alternative is the proportion of members favoringthat alternative. The majority-equiprobability otherwise model presupposes that whenever a
majority of the members favor a particular decision alternative, the alternative will be chosen by
the group. In cases where no majority exists (a 3G–3NG split), then any alternative selected isequally likely to be the group’s choice. Thus, the proportionality model assumes that factions
within the group are only as powerful as the relative size of that faction, whereas the majority-

Group Decision Making 6
equiprobability otherwise model assumes that majority factions are quite powerful and typicallydefine the group’s choice.
--------------------------------------------Insert Table 1 about here.
--------------------------------------------Representing various group-aggregation models as stochastic matrices, SDS theory
allows a systematic investigation into which aggregation model best describes the actual
consensus process in a given setting. More technically, by using the multinomial theorem (seeDavis, 1973; Kameda et al., 2002 for details), SDS theory provides a prediction about how groupdecisions should distribute over choice alternatives (e.g., probabilities of guilty and not guilty
verdicts in the criminal case) if a given aggregation model describes the actual consensus processreasonably well. Then, the predicted group -outcome distribution is tested against observed
distributions of group decisions. For example, the predictions from the two aggregation models
presented in Table 1 could be compared against observed data to assess which model betteraccounts for the data (see Davis, 1996; Kerr, Stasser, & Davis, 1979 ; Stasser, 1999 ; Stasser et al.,1989 for a comprehensive reviews of SDS theory).
The SDS approach has generated a large body of research addressing how groups reachconsensus in a variety of decision situations (see the 1999 special issue of the Organizational
Behavior and Human Decision Processes, Vol. 80(1), for a summary of recent developments
using this approach). Although a number of factors have been found to influence group decision
processes (Davis, 1982; Laughlin, 1980), one of the more consistent and robust findings fromthis research has been that majorities/pluralities “win” most of the time. This is particularly true
when no demonstrably correct alternative exists (Laughlin & Ellis, 1986). When groups cannot

Group Decision Making 7
demonstrate that a particular alternative is empirically or axiomatically correct (or optimal)
during discussion, “correctness” tends to be defined by consensus, and larger factions tend to
define the group consensus. Majority/plurality type aggregation has been observed to describe
the consensus process of groups working on a variety of decision tasks/situations, including
mock juries (Davis, Kerr, Atkin, Holt, & Meek, 1975; Kameda, 1991, 1995; Kerr & MacCoun,
1985; MacCoun & Kerr, 1988; Tindale & Davis, 1983), risk taking (Davis, Kameda, & Stasson,
1992; Davis, Kerr, Sussman, & Rissman, 1974; Kameda & Davis, 1990), recognition memory
performance (Hinsz, 1990), choice of political candidates (Stasser & Titus, 1985), reward
allocation decisions (Tindale & Davis, 1985), and hiring job candidates (Kameda, 1993; Tindale,1989).
Social Judgment Schemes
One of the limitations of the general SDS approach is that it is primarily applicable topreferences defined by discrete decision alternatives. Although many important decisionsituations involve discrete choices (e.g., to promote or not), groups are often required to rendernumerical responses, as exemplified by a budget committee, a civil jury deciding on acompensation award, etc. (Davis, 1996; Hinsz, 1999). SDS theory is ill suited for continuous
response formats (Hinsz, 1999). Recently, Davis (1996) formulated a social judgment schemes
approach for continuous judgments that is analogous to the SDS approach, which has many of
the same properties discussed above for majority/plurality models (see also Hinsz, 1999, for analternative SDS approach for responses of a quantitative nature and Gigone & Hastie, 1996 for asocial judgment theory model for continuous responses). The Social Judgment Scheme (SJS)
model is based on position discrepancies (distance among preferences) along the response
continuum among the members of a group. The model assumes that group’s decision, G, is aGroup Decision Making 8
weighted sum of the r members preferences, x j, j = 1, 2, ..., r, where cj is the weight of the jthmember. That is
G = c1x1 + c2x2 + ... + crx r .
Given that the members’ preferences can be observed a priori, only the weights must be defined
further. The consensus weight of the jth member depends on the centrality of the member’s
position relative to other members of the group. The closer that member’s position is to othermembers’ positions, the more weight that member is given in defining the group consensus.
Thus, the weight of the jth member is defined byr∑ f (| x j − x j' |)
cj =

r

j '=1
r

∑ ∑ f (| x j − x j' |)j =1 j '=1

In the above equation, the social influence function, f, is defined asf(|x j - x j'|) = exp[-θ(|x j - xj'|)], j≠ j'where θ is a positive constant. In practical applications of the model to date, θ = 1.00.
This model tends to give little if any weight to the most discrepant member of the groupand fairly heavy weight to the most central member(s). Even though factions per se cannot be
defined, the group decision tends to be defined mainly by members who are similar (in proximity
along the response dimension) to each other, at the expense of members whose positions are
fairly discrepant. Thus, the SJS model essentially assumes a dominant role of central members(i.e., social sharedness) in guiding consensus, much like the majority/plurality models discussed
above. The model has fared well in recent empirical tests (Davis, Au, Hulbert, Chen, & Zarnoth,
1997; Hulbert, Parks, Chen, Nam & Davis, 1999; Ohtsubo, Masuchi, & Nakanishi, in press).

Group Decision Making 9
Macro consequences of consensus processes guided by socially-shared preferences
As we have seen above, group aggregation processes tend to be guided by the sharednessof the member preferences when the demonstrability of a preferred solution is low. This is seen
as initial majorities or pluralities in a discrete choice situation, or by members whose opinions
are mutually close (i.e., central in the group) in a continuous judgment case. In other words, thedegree of social-sharedness in members’ preferences at the ons et of interaction plays a criticalrole in determining final consensus outcomes. Although this observation may seem quite naturalon the surface, such consensus process guided by shared preferences may bring about rather
counter- intuitive phenomena at the macro level. We discuss two of such macro phenomena
below: group polarization and manipulability of group decisions.
Group polarization. In the June 1994 British elections for the European Parliament, theLabor Party, the Conservative Party, the Liberal Democratic Party obtained 44%, 28%, and 17%of the votes, and acquired 70%, 20%, and 2% of the seats respectively in the parliament. The
Labor Party, which was relatively advantageous in terms of the number of votes obtained, won
the landslide victory in terms of the final seats in the parliament. The electoral system used inthis election was a single-seat constituency system coupled with a plurality rule.
As readers correctly guess, consensual decision- making guided by initial
majorities/pluralities produces exactly the same accentuation effect at the group level (Hinsz etal., 1997). To illustrate, let us imagine a hypothetical investment decision- making situation.
There are 3 choice-alternatives that can be ordered in terms of their risk levels -- low risk,
moderate risk, and high risk. Suppose that an n-member representative committee, randomly
chosen from some population, is to discuss this investment issue to make a final decision. We
assume that consensual decision- making in this committee is essentially governed by a

Group Decision Making 10
majority/plurality process as mentioned earlier. Figure 1 displays distributions of individual
preferences in the population and theoretical distributions of group decisions assuming a simple
majority/plurality process.
--------------------------------------------Insert Figure 1 about here.
--------------------------------------------As can be seen in the figure, it is clear that the risky alternative that is most dominant at
the individual level (i.e., population level) becomes more dominant at the group level(accentuation), whereas the other weaker alternatives become even weaker at the group level(attenuation). For example, the most popular, high-risk alternative is supported by 60% of theindividuals in the population. The theoretical probability that this alternative is adopted as agroup choice is amplified to 68% in a 5-member committee and to 73% in a 9- member
committee. On the other hand, the least popular, low risk alternative (supported by only 10% of
the individuals) is adopted as a group choice only 0.8% of the times in the 5-member committee
and 0.08% in the 9- member committee. The change in choice probabilities from the individuallevel is more evident with the increase in group size, as can be seen from the comparison
between 5- and 9- member groups.
It is interesting to note that such an accentuation in the micro to macro transformation
never occurs if group aggregation is summarizable as a proportioality process (cf. the left panelof Table 1). If proportinality governs consensus process in the representative committee, thedistribution of group choices should be identical to the distribution of individual preferences.
Furthermore, although the above illustration used a discrete choice case, the same argument
applies to a continuous judgment case. If the process predicted by the SJS model characterizes

Group Decision Making 11
group aggregation in the committee, any skewness in the population distribution of individual
preferences toward a particular end of a response continuum would be exacerbated in the groupresponse distribution, due to the higher likelihood of committee members having preferences inthe smaller tail. In contrast, a simple averaging process in the committee should yield exactly the
opposite effect, viz., a less skewed distribution at the group level than at the individual level.
The group polarization phenomenon, which is observed widely in social decision-making beyond
risky situations, was a vigorous research topic in social psychology in the 70’s. Although several
individual- level explanations have been proposed (Vinokur & Burnstein, 1974; Sanders & Baron,
1977), notice that our view of this phenomenon focuses on the social aggregation process.
Consensus process affected by social sharedness (e.g., a majority/plurality or a SJS- likeaggregation) can theoretically produce polarization or distributional shifts at the group level evenwhen there is no attitude, preference change in individuals due to social interaction. Thus,
individual attitude change is not a necessary condition for group polarization (see Davis, 1973,
Davis & Hinsz, 1982, and Lamm & Myers, 1978 for a further discussion on this point).
Besides its obvious political implications (Kameda, Hulbert, & Tindale, 2002), thesegroup polarization phenomena are also important in relation to decision accuracy. Suppose thata group decision task triggers some “cognitive bias” (cf. Kahneman, Slovic, & Tversky, 1982).
If there is no external evidence proving why biased preferences are wrong, and/or if members
lack logical or statistical backgrounds to understand those corrective arguments, then consensual
processes would essentially be determined by shared preferences at the outset of interaction.
Then, the quality of group decisions should depend on what kinds of preferences are shared at
the outset in a given group stochastically. In this sense, the probability of an individual
member’s “biased” preference is key. If this individual probability is larger than a critical social

Group Decision Making 12threshold (e.g., 50% in the case of a simple majority process), then consensual decision- making
leads groups astray. Improvement by grouping is expected only when the individual biasproneness is smaller than the social threshold (Kerr, MacCoun, & Kramer, 1996a, 1996b ).
Furthermore, as can be seen in the comparison of 5- and 9-member groups in Figure 1,
increasing group size accentuates such a group polarization tendency even further. Using alarger group means that the variance of group-decision qualities is also enlarged sta tistically –either a great success or a fiasco, depending on the degree of individual bias relative to thecritical social threshold in a focal context.
Manipulability of group decisions. Another important implication of consensus process
guided by shared preferences is procedural manipulability of group outcomes (Davis, 1992).
The most famous example of this sort, focusing particularly on majority/plurality aggregation, is
Condorcet’s voting paradox. When a group decides among 3 or more alternatives (say x, y, andz), “cyclical majorities” can exist. For example, if members’ preference orders are x>y>z, y>z>x,
and z>x>y respectively in a 3-person group, the majority in the group prefers x over y, y over z,
and z over x. (Notice that the “majority consists of different members in each preference.) Thus,
cyclicity (intransitivity) exists in the preferences of majority members. In such a situation, thegroup choice outcome via majority rule depends on a particular path by which pairwise votings
are conducted i.e., path-dependency of voting. For example, if one’s first preference is x, he/she
can guide group decision toward the alternative by first calling for a vote between y and z, andthen a vote between its winner (y) and x. Obviously, a chairperson who can choose which voting
order to take can potentially manipulate the group decision outcome to personal advantage (seeBlack, 1958; Mueller, 1989 for further discussion of paradoxes of voting).

Group Decision Making 13
Although the example above is taken from a voting situation, manipulability may also
play a substantive role in consensual decision-making. For instance, Kameda (1991)
demonstrated such a procedural manipulation in a situation where a group needs to consider
several key conditions to render a final decision. An example might be investment decisionmaking, in which several key criteria must be satisfied to make a final investment decision. Twocontrasting discussion procedures are conceivable in these situations. In the compoundprocedure, the chairperson solicits members’ overall conclusions from the outset, e ncouraging
members to express their overall preferences -- to invest or not. In contrast, the elemental
procedure takes the opposite approach, focusing on collaborative evaluations of the key criteria ;the chairperson asks for members’ judgments of each of the conditions respectively. Althoughthese two procedures are both plausible and seemingly neutral, the choice of a procedure
substantially impacts on final group outcome, as illustrated in Table 2.
--------------------------------------------Insert Table 2 about here.
--------------------------------------------Table 2 displays a hypothetical opinion configuration of 3 members working on theinvestment decision task. We assume that there are two key conditions to be satisfied to makethe investment and that person A serves as a chairperson of this committee. While member A
personally prefers to invest, the other two members do not. Therefore, provided that theconsensual process is guided by a majority process, member A has little chance to prevail, if the
discussion centers on exchanging members’ preferences (“compound procedure”). However,what if member A adopts the elemental procedure instead? Assuming that each member isfaithful to his /her original judgments, the same majority process should yield a positiveGroup Decision Making 14
collective judgment for each of the two criteria, allowing the chairperson to conclude thediscussion with investment decision.
It can be shown formally that the probability of investment will always be higher with theelemental procedure as compared to the compound procedure. In the example above, theelemental procedure can theoretically increase the probability of a decision to invest by the
maximum margin of .13 for a 3-person group, .23 for a 6-person group, and .37 for a 12-persongroup, compared to the compound procedure. Thus, the elemental procedure is moreadvantageous to a chairperson, if the person personally desires investment; if personally
preferring not to invest, the compound procedure should serve the chair’s interest. Using 4- and6-person groups, Kameda (1991) confirmed that consensus outcomes can be manipulated
procedurally as illustrated above. Even when a group was instructed explicitly to discuss theissue until they reach a unanimous agreement (i.e., majority voting was thus discouraged), thetwo procedures affected consensus outcomes as implied by the formal model. Furthermore, nomembers were aware of the manipulation; group outcomes were essentially ac cepted as fair andsatisfactory (cf. Darley & Tyler, this volume; Lind & Tyler, 1988).
As illustrated in this example, the social process guided by shared preferences makes thevoting paradox a central issue for consensual decision- making that lacks an explicit formal
voting procedure. In a similar vein, continuous group decisions can also be guided toward aparticular individual’s personal advantage through a procedural manipulation tactically utilizing
social sharedness. Although space does not allow us to discuss them here, various forms of suchprocedural influences have been studied in the small- group decision-making literature, including
effects of sequential straw polling (Davis, Stasson, Ono, & Zimmerman, 1988), local majorities(Davis et al., 1989; Kameda & Sugimori, 1995), consensus rules (Davis, Kerr, Atkin, Holt, &Group Decision Making 15
Meek, 1975; Miller, 1989), and agenda setting (Davis, Tindale, Nagao, Hinsz, & Robertson,
1984; Stasson, Kameda, & Davis, 1997). (See Davis, 1992, Davis, Hulbert, & Au, 1996,
Kameda, 1996, and Kameda, Hulbert, & Tindale, 2002 for further discussion on procedural
influence on consensual decision- making.)
Socially Shared Cognitions
Shared Information and the Common Knowledge
Although much of the early work on group decision making focussed on preferences,some exceptions did exist (Graesser, 1982; Vinokur & Burnstein, 1974). Probably the bestknown early attempt to understand groups at the cognitive level was Vinokur and Burnstein's
Persuasive Arguments Theory. In an attempt to expla in group polarization, Vinokur andBurnstein argued that for any given issue, there is a population of arguments associated with it.
They also argued that group discussion could be seen as members sampling arguments from that
population. If there were more and/or more persuasive arguments favoring positions on one endof the response continuum, then the sample of arguments would favor that end and would leadgroup members to move in that direction, producing group polarization. One of the key
assumptions of the theory was the importance of unshared or unique arguments (Vinokur &Burnstein, 1978). They assumed that shared arguments would have little impact when broughtup during discussion because everyone already had that information. In contrast, they argued
that unshared or unique information would affect member preferences and was crucial forpolarization to occur.
More recent research has demonstrated exactly the opposite in that shared information
dominates discussion and determines decisions. Stasser and Titus (1985) designed a paradigm
for studying the effects of shared and unshared information on group decision making that had aGroup Decision Making 16
major impact on the field of small group research. The paradigm has been referred to as thehidden profile technique and the basic finding has been called the common knowledge effect(Gigone & Hastie, 1993, 1996). Stasser and Titus had four-person groups choose one of threepolitical candidates based on information profiles about the candidates. In some of the groups,
all members were given complete information about all three candidates. However, in otherconditions, some information was shared by all members and some information was only held byindividual members. With complete information, most individuals typically preferred aparticular candidate (e.g., candidate A). However, in the hidden profile (unshared information)
condition, the positive information about candidate A was divided among the group members
while the negative information about A was shared. This led individual members to prefer someother candidate at the beginning of discussion. Even though the groups, with a thoroughdiscussion, should have been able to discover that Candidate A was optimal, this rarely happened.
Most of the groups chose an alternative candidate, and the group discussions contained mainly
shared information. In addition, a majority model tended to describe the group decision
processes at the preference level.
Stasser and Titus (1987) showed that a simple information-sampling model could accountfor the above effects. Research has shown that the likelihood of a piece of information being
recalled by a group is a function of the number of members presented with that information(Hinsz, 1990; Tindale & Sheffey, 2002; Vollrath, Sheppard, Hinsz, & Davis, 1989). Thus,
shared information is more likely to be recalled than unshared information at the group level. In
addition, even with perfect recall, the probability that a piece of information gets brought up isalso a function of the number of members who have it (Stasser, Taylor, & Hanna, 1989). Basedon these assumptions, Stasser and Titus (1987) formulated their information-sampling model.

Group Decision Making 17
The model (based on Lorge and Solomon's (1955) model A for predicting group problem solving
outcomes) basically assumes that the probability, p(D), that a given piece of information will be
discussed is 1 minus the probability that no one mentions the item during discussion. This canbe mathematically described as p(D) = 1 - [1 - p(M)]n , where p(M) is the probability of any given
member mentioning an item that he/she has, and n is the number of members having that item.
When only one member knows a given piece of information p(D) = p(M). However, as nincreases, so does p(D) so that shared information will always have an advantage over unshared
information in terms of it entering into the discussion content.
Gigone and Hastie (1993, 1996), using a rather different paradigm, demonstrated similarfindings and shed additional light on the processes underlying the common knowledge effect.
Gigone and Hastie used a multi-cue judgment task, and varied whether the cues were shared or
unshared among the group members. Each group made multiple judgments so Gigone andHastie could assess the degree of importance each cue had for predicting individual member andgroup judgments. Consistent with the Stasser and Titus (1985) findings, shared cues were more
important for predicting group judgments than were unshared cues, with importance generally
being a linear function of the degree of sharedness. Interestingly, cues that were actually broughtup during discussion did not increase in weight as a function of their being mentioned. In
addition, the effects of the cues on group judgments were totally mediated by the member
preferences. Thus, it seems that the distribution of information in the group (i.e., information or
cognitive sharedness) influences group judgments only indirectly through member preferences(i.e., preference sharedness) (though see Winquist & Larson, 1998 for an exception).
Although very robust and often replicated (see Wittenbaum & Stasser, 1996 for review),
the common knowledge effect can be attenuated by some procedural mechanisms. Larson,

Group Decision Making 18
Foster-Fishman, and Keys (1994) have shown that unshared information becomes moreprevalent in group discussion over time. Thus, extending the discussion time of groups should
help insure that unshared information gets brought up during discussion. However, the opposite
seems to happen when time pressures are put on the group. Groups focus on fewer alternatives
and place more emphasis on shared information when under time pressure (Janis, 1982; Karau &Kelly, 1992; Kelly & Karau, 1999). Recent work by Parks and Cowen (1996), Sawyer (1997)
and Sheffey, Tindale, and Scott (1989) has shown that allowing group members to have access to
informational records during discussion can attenuate hidden profile effects. Sawyer (1997) also
found that instructing group members not to form a priori jud gments helped to reduce the effects,
although this has not always been found to be effective (Sheffey et al., 1989).
Stasser and Stewart (1992) found that framing the task as a problem to be solved(implying a correct answer) led to greater sharing of unshared information during discussion.
More recently, Postmes, Spears, and Cihangir (2001) found that priming groups with a norm tothink critically led to greater information sharing and better performance than groups primed
with norm to reach consensus. In addition, Hollingshead (1996) showed that having groupmembers rank order decision alternatives rather than simply choosing one increased the sharingof unique information and the discovery of hidden profiles. Finally, Stewart and Stasser (1995)
demo nstrated that assigning roles associated with the information distribution (e.g., "you are theexpert on candidate x") led to more discussion of unshared information, but only when the roles
were known by all of the group members (see section on shared metacognition below – also see
Stasser & Birchmeier, 2002, for a more thorough description of methods for reducing thecommon knowledge effect).

Group Decision Making 19
Shared Information and Member Influence – Cognitive Centrality
Work on the common knowledge effect has focused on the effect of shared informationor knowledge per se on consensus. Little emphasis has been placed on group members' status or
power as a function of degree of knowledge-sharing with other members. For example, one
member may share a substantial amount of information with other members, while anothermember may share only a portion of it. Because shared information has a greater impact on final
group decisions, it seems likely that members having more shared information may acquire
pivotal power in the group. This idea was tested in a set of studies by Kameda, Ohtsubo, &Takezawa (1997). Using a social network framework, Kameda et al. devised a model torepresent the degree to which any given member was "cognitively central" in the group. Much
like Davis' (1996) SJS model, which locates members' preference centrality, Kameda et al.'s
measure of cognitive centrality defines members in terms of the degree of centrality in thesociocognitive network . The greater the degree of overlap between the information held by agiven member and the information held by other members on average, the greater the degree ofcentrality for that member.
Kameda et al. (1997) ran two studies to assess whether cognitively more central members
would be more influential in their groups, regardless of whether they were in minority or
majority factions. In Study 1, they had three person groups discuss whether a defendant in ahighly publicized trial deserved the death penalty. By coding contents of knowledge eachmember held prior to group interaction, they calculated a cognitive centrality score for eachmember in each group. They then used the members' cognitive centrality score to predict
participation rates and opinion change after group discussion. Members' ranking in terms ofcentrality were positively related to their ranking in terms of participation. For members inGroup Decision Making 20
minority factions, their degree of centrality also predicted (inversely) their amount of opinionchange, though centrality was unrelated to opinion change for majority members.
In Study 2, Kameda et al. manipulated the information given to each group member tocreate two different situations. In one condition, the most cognitively central member of thegroup was a lone minority (in terms of preference) against a two-person majority. In the othercondition, the most cognitively central person was part of the two-person majority, with theminority member being the least cognitively central. When the minority person was mostcognitively central, the group went with the minority position 67% of the time. When theminority person was most peripheral, the minority won only 42% of the time. In addition,groups were more confident in the conditions where the central minority person's preference waschosen by the group. Thus, being the most central person in the group allows that person agreater degree of influence, even when he/she is a minority in terms of preference. Kameda et al.
(1997) argue that such an enhanced social power accrues from perceptions of expertise for thecognitively central member in the focal knowledge domain.
Shared Task Representations: Intellective vs. Judgmental Tasks
Research on the common knowledge effect tends to show that shared information plays acentral role in group decision ma king. In addition, it shows that shared information and sharedpreferences tend to correspond with each other. Thus, the research on shared cognitions has
tended to fit nicely with the work on majority/plurality processes. However, there are a numberof instances in the small group literature where deviations from majority processes have been
observed. Probably the most notable is the work by Laughlin and his associates (Laughlin, 1980;
Laughlin & Ellis, 1986; Laughlin, 1996) on group problem solving. Problem solving(intellective) tasks are defined by Laughlin as tasks for which a "demonstrably correct solution"

Group Decision Making 21
exists, as opposed to decision making or “judgmental” tasks, where "correctness" tends to be
defined by the group consensus (Kameda, et al., 2002).
A demonstrably correct solution is one for which the group members can "demonstrate" aparticular alternative is correct or optimal during the group discussion. Research has shown thatmajority/plurality models tend to severely under-predict group performance on such tasks.
Models such as "truth wins" or "truth supported wins" (where either one or two members,
respectively, who prefer the correct alternative can win out over incorrect majorities) provide
much better fits to experimental data (Laughlin, 1980). In defining demonstrability, Laughlin
and Ellis (1986) argued that a key feature was a system of axioms or beliefs that were shared
among the group members. This shared belief system serves as a background for the members
understanding the logic behind the correctness of a given alternative. Thus, using the sharedbelief system, minority factions arguing for a correct alternative can win out over majorities
favoring an incorrect alternative.
Laughlin and associates (Laughlin & Ellis, 1986; Laughlin, Bonner, & Altermat, 1998)
have used the notion of demonstrability to explain how groups compare to individuals in termsof performance on both intellective and judgmental tasks. For judgmental tasks,
majorities/pluralities tend to define the group decision process, so performance depends onwhether the majority/plurality is correct. In such cases, groups may outperform the average
individual, but they will not consistently perform at the level of their best members, and may
perform considerably worse than even their average members on tasks where the correct answer
is chosen infrequently by members (Tindale, 1993). However, for intellective tasks (i.e., tasks
where some demonstrability exists), group performance should always be better than the average
individual and should approach the performance of the group’s best member for highly

Group Decision Making 22
demonstrably tasks. Typically, groups perform about as well as their second best member on
intellective tasks (e.g., “truth-supported”wins). However, Laughlin and Ellis (1986) showed thatfor highly demonstrable tasks (e.g., simple math problems) a truth wins model provided the best
fit – which implies that groups performed at the level of their best member.
More recent work by Laughlin and colleagues (Laughlin, 1996; Laughlin et al, 1998;
Laughlin, VanderStoep, & Hollingshead, 1991) has also shown that information load affects thedegree to which groups perform as well as their best member. This work has focused on“collective induction” where groups attempt to generate hypotheses to explain available data.
Laughlin (1996) has argued that such tasks involve both intellective and judgmental components.
Distinguishing between plausible (consistent with current data) and implausible (inconsistent
with current data) hypotheses is an intellective task, while choosing among several plausible
hypotheses is more judgmental. Across several studies (Laughlin et al., 1991; Laughlin et al,1998), they showed that groups performed at the level of their second best member when theamount of evidence (data) was not too substantial. However, with very high information loads(looking at five arrays of data or more), groups performed as well as their best member, and in avery recent study with a different high information load task, groups performed better than theirbest member (Laughlin, Bonner, & Minor, in press). Thus, level of demonstrability andinformation load both affect how well groups will perform relative to the performance of each of
their members alone.
Laughlin’s work shows that minorities advocating correct positions can over-ride
incorrect majorities by using shared knowledge structures. Tindale, Smith, Thomas, Filkins, andSheffey (1996) generalized this notion to more judgmental situations and argued that whenever a"shared task representation" exists, alternatives consistent with the representation will be easierGroup Decision Making 23
to defend and thus more likely to end up as the groups' collective choice. Tindale et al. define ashared representation as "any task/situation relevant concept, norm, perspective, or cognitive
process that is shared by most or all of the group members" (p. 84). Task/situation relevantmeans that the representation must have implications for the choice alternatives involved, and thedegree to which a shared representation will impact on group decision processes will vary as afunction of relevance. Its impact should also vary as a function of the degree to which it isshared among the group members. If no shared task representation exists, or if multiple
conflicting representations are present, then groups will tend to follow a symmetricmajority/plurality type process. However, when one does exist, the group process will tend to
take on an asymmetric structure favoring the decision alternative that is consistent with therepresentation. Thus, majorities or minorities favoring the alternative consistent with the shared
representation will be more powerful within the group.
Although the work by Laughlin (1980) on group problem solving is the strongest
example of effects of shared representations, a number of others also exist. For example, muchof the work on mock jury decision making (Davis, 1980; MacCoun & Kerr, 1988; Tindale &Davis, 1983) has shown that "not guilty" is an easier verdict to defend than "guilty", which isconsistent with the shared processing objective of looking for "reasonable doubts" given to juries
in all US criminal cases. Thus, both majorities and minorities favoring not guilty are more
powerful than comparably sized factions favoring guilty (Tindale, Davis, Vollrath, Nagao, &Hinsz, 1990). Tindale and associates (Tindale, 1993; Tindale et al., 1996) have also shown thatshared decision biases or heuristics can produce similar deviations from symmetric majority
processes. For example, Tindale (1989) showed that biased feedback procedures intended to
produce conservative hiring or promotion practices allowed minorities voting against a job

Group Decision Making 24
candidate's promotion to win out over majorities favoring promotion. Tindale, She ffey, andScott (1993) found that groups given the "loss" version of the standard "Asian Disease" problem(Tversky & Kahneman, 1981) would choose the riskier alternative even when a majority of themembers favored the less risky alternative (see also Laughlin & Early, 1982). More recent work
has shown that shared values (fairness - Krebel, Munier, Anderson, Meisenhelder, DykemaEngblade, & Tindale, 2001) and shared motives (Morgan & Tindale, 2002) can work as shared
representations as well.
Studies focused on how shared representations function has shown that they potentiallyoperate in two different ways to affect group decisions. First, Smith, Tindale, and Steiner (1998),
using a "sunk cost" problem, found that sunk cost arguments were persuasive, even if only aminority of members mentioned them as reasons for their decisions. Thus, arguments that areconsistent with the shared representation can be especially influential in a group decision context.
Second, a recent study by Tindale, Anderson, Smith, Steiner, and Filkins (1998), continuing a
program of research looking at the estimation of conjunctive probabilities by individuals andgroups (Tindale, Sheffey, & Filkins, 1990; Tindale, Filkins, Thomas, & Smith, 1993), videotaped
the group discussions for conjunctive probability problems. Earlier research had shown thatminorities making non-normative (“erroneous”) estimates were more powerful than majorities
making normative estimates. The videotaped group discussions showed that groups rarely
discussed strategies as to how to make the estimates, but rather simply exchanged information
concerning their individual judgments. When groups went with a single member’s judgment as
the group judgment, which occurred more than 60% of the time, they were more likely toendorse the judgment of an incorrect member for conjunction problems that typically led toerrors. For conjunction problems that typically did not lead to errors, groups were more likely toGroup Decision Making 25
endorse the judgment of a correct member. These patterns were relatively independent of thepreference distribution in the group. Thus, it seems that shared task representations can affectgroup decisions even when only preference information is exchanged. As long as a given
individual preference is plausible within the shared representation, the group members will findit acceptable without thorough debate.
Shared cognitions come in various types and at various levels of generality (see Tindale& Kameda, 2000, and Tindale et al., 2001 for reviews). In addition, there are often several setsof shared cognitions present in groups. A limited amount of recent research has begun tocompare how different types of shared cognitions affect one another. For example, Postmes,
Spears, and Cihanger (2001) showed that giving groups a shared norm or processing goal
oriented toward “critical thinking” as opposed to “reaching consensus” led to a reduction of thecommon knowledge effect. Thus, shared norms can moderate the affects of shared information.
Shared identities can also influence the degree to which unique or novel ideas are tolerated in agroup. When deviant behavior or ideas violate important ingroup norms, they are tolerated better
when performed or proposed by outgroup as opposed to ingroup members (Abrams, Marques,
Bowen, & Henderson, 2000; Phillips, 2000). Finally, Stasser, Stewart, and Wittenbaum (1995)
and Stasser, Vaughn, and Stewart (2000) have shown that allowing group members to know
which other members are “experts” in particular areas or what information other members havealso attenuates the common knowledge affect. This type of “meta-cognitive” knowledge is thefocus our next section.
Socially Shared Metacognition
The sharing of knowledge in groups making decisions can also be considered fro m ametacognition perspective. Metacognition refers to the ways we think about thinking (Jost,
Kruglanski, & Nelson, 1998). We have discussed how group members may share cognition in

Group Decision Making 26
pursuit of a group decision. At a higher level, we can see metacognitio n as the ways that people
think about the ways they process information and perform cognitive tasks. Using this definition
we can also conceive of metacognition in groups: the ways group members think about the way
they process and share knowledge in groups and the ways groups perform cognitive tasks (Hinsz,
in press). For purposes of this chapter, we focus on higher-level processing of information onvery complex cognitive tasks: decision- making. Consequently, we can consider metacognition
in decision-making groups as how group members think about the ways they process and shareknowledge in an attempt to reach group decisions.
There has been substantial research on metacognition for individuals (Metcalfe &Shimamura, 1994). Perhaps the most useful is that by Nelson (1992, 1996; Nelson & Narens,1990). Nelson’s (1996) model representing the processes involved in metacognition proposes
object and a meta levels of analysis of cognitive processes. The object level reflects the processesof interest as they objectively occur. For decision-making groups, these would be the processes
involved in sharing information and reaching consensus whereas the meta level reflects people’s
subjective views of how groups share information and reach consensus. Research inmetacognition attempts to determine the accuracy of people’s metacognition in comparison tothe objective level. The actual content of the metacognition is also of interest. For example,
what are the beliefs group members hold about the way their group reaches a decision (e.g.,“committee meetings are a waste of time, we always choose what the chair wants, etc.).
According to Nelson’s model, there are two important processes involved inmetacognition. The monitoring process reflects the information gain ed about the activities at theobject level (e.g., “Will we be able to reach a decision in the time allotted?”). The control
process demonstrates the ways the respondent thinks about the decision situation (i.e., metalevel) to determine how to act (e.g., “We need to follow the agenda instead of going off on
tangents.”). If people have metacognition about decision making in groups, then it may be usefulGroup Decision Making 27
to consider how they monitor and control the activities involved in group decision-making.
Moreover, it might be fruitful to consider the metacognition for how groups share knowledge
and process information in pursuit of reaching group decisions.
Metacognition for group decision-making refers to how people think about how groups
make decisions. The more interesting instances arise for group members having metacognition
about how their groups make decisions. Group members’ metacognition for their own groups
are of interest because the assumption is that the beliefs that group members have about theirgroup are expected to influence the way the group members interact, which might influence theoutcomes of those group interactions (e.g., group decisions; Hinsz, in press). Consequently, themetacognition that group members have for their groups has the potential to influence thedecision- making processes and outcomes of groups.
Shared Objectives for Decision Making: Implicit and Explicit Agenda Effects
When groups try to reach a decision, they generally have a set of explicit and implicit
objectives they hope to attain. These objectives reflect metacognitive beliefs that groupmembers have about what the decision should be as well as the way the decision should bereached. Some members of the group will believe that the discussion should be an open and freeexchange of information about the decision situation. Other members might believe that theobjective is to reach a decision and focus on the response alternatives that are feasible. Hastie,
Penrod and Pennington (1983) found that these two different types of objectives described thepattern of deliberation for mock juries in their research. They described evidence-driven juries asones that focus on the evidence related to the crime and a discussion of its value and credibility.
On the other hand, verdict-driven juries tend to try to determine whether the defendant is guilty
or innocent, and discussion of the evidence is in support of one or the other alternatives. Hastie etal. demonstrated that the deliberation (e.g., time to verdict) and other features of the decision
making process was influenced by whether the jury focused on evidence or the verdict.

Group Decision Making 28
A more explicit way in which objectives influence decision-making is in terms of theagendas that are used to guide the group decision- making process. As previously discussed,
research indicates that the way the agenda is arranged can have remarkable influences on thedecisions reached (Davis, et al., 1984; Kameda, et al., 2002; Levine & Plott, 1977). Implicit andhidden agendas can likewise influence the decision making process. Davis (1992; Davis et al.,1988) describes how a clever committee chair could arrange the polling of people about theirpreferences to influence undecided members to respond in a way consistent with the chair’s
initial preference. Both explicit and implicit agendas demonstrate that the expectations groupmembers have for their decision- making groups are metacognitive beliefs about objectives that
may control group interaction and decision outcomes.
Shared Metacognitive Beliefs about Groups: Shared Mental Models
Just as group members may have shared representations of tasks, they may also haveshared representations of the groups of which they are members (Hinsz, 1995). Some of theresearch examining how group members think about how their group’s function can be found in
the shared mental models literature (Cannon-Bowers, Salas, & Converse, 1993; Hinsz, 1995, inpress; Kraiger & Wenzel, 1997; Rentsch & Hall, 1994; Stout, Cannon-Bowers, & Salas, 1996 ).
Mental models reflect cognitive representations that people have of systems and the way theyinteract with those systems (Hinsz, 1995; Rouse & Morris, 1985). If we take the perspective thatgroups are complex, adaptive, and dynamic systems (McGrath, Arrow, & Berdahl, 2000), thenmental models can be metacognitive representations of how their groups function and operate(Hinsz, in press). If group members have mental models of how groups deliberate and makedecisions, these mental models may be predictive of how the groups actually deliberate andreach a decision. Important questions for the consideration of member mental models include
whether they accurately represent the process of decision- making by a group and how sharedthese mental models are among the members of the group.

Group Decision Making 29
The accuracy of the mental model reflects the degree that the group members’ beliefs
about the way their group makes decisions accurately reflect the way their group actually makes
decisions. Group members may have mental models of their group decision-making but they canbe flawed in important ways such that they are inaccurate representations. Groups may havemembers acting with regard to the wrong decision situation, (Picken & Dess, 1998).
Alternatively, if group members have accurate mental models about how their group shouldmake decisions, then the members should act in ways that will produce better decision outcomes(Cannon-Bowers et al., 1993).
The sharedness of the mental models group members may have for decision making isanother key question for the consideration of metacognitive representations (Cannon-Bowers, etal., 1993; Hinsz, 1995, in press; Hinsz, et al., 1997). If accurate mental models are shared, thenthere are a host of potential benefits for group decision- making. However, sharedness of mental
models is not sufficient. It is important that the group members share accurate mental models. Ifgroup members share mental models of the way their group should reach decisions, there shouldbe less disagreement among the members about the way to reach a decision. The group should be
more efficient and effective in reaching a decision and the group members will believe that theirgroup was effective and efficient in its use of time. Consequently, the members will be moresatisfied with the decision making process and be more willing to participate in the group in the
future (Hackman, 1987; McGrath et al., 2000).
Shared Memory and Remembering: Transactive Memory
Memory processes are one aspect of metacognition for decision-making groups that hasreceived attention. Just as metamemory (how people think about how they remember and forget)
has received attention for individual cognition, similarly the memory processes of decisionmaking groups has also attracted attention. In the case of decision-making groups, themetacognition questions concern how the group members think about the way their groups

Group Decision Making 30
remember and how this memory by the group influences decision making by the group.
Substantial research has examined how memory by groups may influence decision- making(Clark & Stephenson, 1989; Hinsz, 1990; Stephenson, Clark & Wade, 1986; Stewart & Stasser,
1992; Vollrath, et al., 1989). These research efforts support the general assumption that the better
memory of the group, the greater the likelihood the group will achieve a better decision (Vollrath,et al., 1989).
Some of the most relevant research on shared memory processes in groups concerns
transactive memory (Wegner, 1987, 1995; Wegner, Erber, & Raymond, 1991). Transactive
memory is based on how group members use and rely on each other in remembering material.
Transactive memory reflects a set of strategies that group members can use to encode, store andretrieve information that will be used by a group. These strategies allow one person to focus onremembering specific information and other group members can later rely on this person toremember that particular information. As a consequence of these transactive memory systems,groups can remember more information in total than if they had not used a transactive memory
strategy (Hollingshead, 1998).
For a group to remember some information, it is necessary for the group to place theinformation into some form of storage. A first question that a group would need to determine,probably derived from encoding, is whether the information should be stored at all. If theinformation is considered irrelevant for the group’s purposes, then the controlling function of
metacognitive processes would suggest that the information does not need to be stored by anygroup member. However, if the information is going to be stored, a set of tactically subsequent
questions arises. An apparent aspect of memory in groups is that the group has many morememories than an individual acting alone (Hinsz, 1990). So, one metacognitive issue the group
has to consider is who will store the information. Will the storage of the information occur for all
the group members, indicating that the storage of the information is shared and redundant?

Group Decision Making 31
Alternatively, the group may decide that only one or a few group members will be
responsible for storing the information. Assigning responsibility for storing the information to
select individuals would be a transactive memory strategy that would allow the other groupmembers to focus on other information to be remembered (Wegner, 1987). Research ontransactive memory has found that the information is remembered better if the member(s) storing
the information have interest or expertise with regard to the information content (Wegner, 1987;
Wegner, Giuliano, & Hertel, 1985). These individuals with interest and expertise are likely to beable to represent the information in a more coherent fashion, and thus would be more likely torecall the information accurately when it is needed.
Transactive memory also suggests that the retrieval of information will be easier if thegroup members have good representations that allow the information to be encoded in a coherent
fashion. These group members can then more easily retrieve the information. One transactive
memory strategy would use members with specific expertise and interests as storehouses of
information that is related to the group members’ expertise and interest. From a perspective ofmetacognition, the group members would monitor the incoming information and identify
information related to their arenas of expertise. When such information is brought forth,particular members control their memory processes to focus on remembering that information.
The other members of the group would come to expect that group members would try toremember information related to their areas of expertise and interest (Wegner et al., 1991).
Consequently, later, when specific information is needed to make a decision, the group members
will turn to the member with the expertise to retrieve the desired information. If the transactive
memory system increases the retrieval of relevant information, this should lead to improved
group decisions.

Group Decision Making 32
Shared Rules for Decision Making: Social Decision Heuristics
The decision a group reaches is often based on selecting one alternative from some initial
set of alternatives (Davis, Laughlin & Komorita, 1976). Thus, the group’s definition of theinitial alternative set is of utmost importance. Group members may not know all the feasible
alternatives, and as such, may miss opportunities to choose the most appropriate alternative. For
example, in many jurisdictions in the United States, a jury can decide that the law used to try adefendant does not apply in a particular case. The jury ca n disregard the evidence and return averdict of not guilty (i.e., jury nullification; Horowitz, 1985). Consequently, the beliefs thegroup members share about the feasible decision alternatives limits the ultimate decision a group
might reach.
Metacognition is important in how group members monitor their group’s progression to adecision. The metacognitive process of monitoring could focus on the timeliness, quality(reasonableness), and acceptance of the group decision (Vroom, 1969). Some research has
examined the ways groups progress to reach an agreement (Kerr, 1981, Goodwin & Restle,
1974; Hinsz & Saum, 1996). Group members and their leaders will likely monitor how well or
poorly their group is doing in approaching a decision in a timely fashion. Similarly, groupmembers may monitor quality during the group decision-making process by considering whether
the decision meets the requirements and constraints of the decision situation. Group members
also will be motivated to monitor the acceptance of the likely group choice. Members will note
directly whether they endorse or accept the likely group decision. If they don’t, they may engage
in more vigorous discussion of the alternatives. The group members will also be concerned withthe acceptance of the decision by external entities. If there is an audience or other collective towhich the group will be held accountable in their decision, the group members will often
consider and possibly discuss how this audience will respond to their likely choice (Tetlock,1985). If the group believes the audience will disapprove of, negate, disavow, or overturn theirGroup Decision Making 33
decision if they select a particular alternative (e.g., appellate court), the group may choose to
move on to consider an different alternative that will receive more support from the audience,even if it is not the best decision overall.
Decision-making groups often engage in metacognitive strategies to control how theyreach decisions. Earlier, agendas were noted to influence the processing objective, but agendas
can also influence how a decision is reached. Standard operating procedures, bylaws, andconstitutions of groups often dictate the rules used to control deliberation and determine thealternative selected. If a group chooses to follow Roberts’ Rules of Order, they are applying ametacognitive strategy to control how discussion, deliberation, and debate will be held.
Similarly, as we mentioned earlier, there may be rules determining how voting in the group is
conducted, which will often dictate the decision rule that is applied (e.g., majority wins).
Group decision- making research has considered group decision rules (Miller, 1989).
Some of this research has focused on the group decision rules that are considered best by thegroup members (Miller, 1989). Other research has focused on the decision rules that willproduce the best group decision outcome (Grofman & Owen, 1986). Furthermore, other researchhas examined decision- making groups to determine the implicit decision rules that groups appear
to use when trying to reach a decision (Davis, 1973, 1980, 1992). One finding from this researchis that the preferred, best, and implicit group decision rules vary greatly as a function of thedecision situation. Decisions that are considered important to the group members appear torequire higher levels of agreement among the group members before a decision can be reached.
Alternatively, unimportant decisions, or ones for which group members have difficulty
advocating strongly for a specific alternative, seem to require much less agreement (Hinsz, 1990;
Hinsz, et al., 1997; Laughlin, 1980).
One of the characteristics of the application of decision rules in groups is that theygenerally vary in terms of the degree of consensus required to lead to the selection of anGroup Decision Making 34
alternative. From a metacognitive perspective, the consensus requirements are generally known
and applied by group members. However, another interesting question that arises is the origin of
these metacognitive beliefs about consensus requirements? The emergence of evolutionarysocial psychology may provide a basis to consider this question (Buss & Kendrick, 1998;
Simpson & Gangestad, 1998).
An evolutionary psychology perspective may suggest that conflicting opinions are
inherent in any social group facing decisions (Latane & Bourgeois, 2001). Because of thediffering experiences, knowledge, and capabilities, group members will necessarily come to thegroup with some divergent opinions about the proper group response to a decision situation.
These divergent opinions are contrary to the agreement that is necessary for the group to proceed
in its efforts. Consequently, from an evolutionary perspective, social groups should develop
ways to resolve these differences of opinion. Moreover, the members of the group would need tobe motivated to resolve these differences. Hence, we should find that differences of opinion
should make members of tight-knit groups perceive that conflict exists (Festinger, 1964). This
perceived conflict would lead to the experience of negative, unpleasant arousal which groupmembers would be motivated to reduce (Matz, 2001). Hence social groups would inherently
carry with them the divergent opinions leading to conflict as well as the pressures to uniformitythat will lead to the resolution of the differences (Latane & Bourgeois, 2001).
The evolutionary perspective here only suggests that social groups, such as decision
making groups, should be motivated to find ways to reduce the conflict, but that the specificconflict resolution and consensus attainment procedures could be unique to different aggregatesand societies. Cross-cultural research could explore whether the negative, unpleasant state
associated with conflicting opinions in a group are universal, eve n though the means of resolving
these disagreements are particular to groups and cultures. Our consideration of the implications

Group Decision Making 35
of evolutionary psychology and the potential of cross-cultural research suggest that many
additional directions for research on group decision making exist.
Social Sharedness: Where Can We Go From Here?
Group decision-making and adaptation
This chapter has focused mainly on group decision performance. Although groupdecisions often fail to achieve optimal levels of performance due to various process losses(Steiner, 1972), on balance, the notion of delegating important decisions to groups is favored by
the research evidence. Interestingly, such reliance on decision- making groups is not necessarily
limited to industrialized, “democratic” societies, but is observed in more traditional, tribal
societies as well. Anthropologist Boehm (1996) surveyed the ethnographic literature about how
tribal societies make decisions, especially in crisis situations. Decisions about raiding andwarfare made by Mae Enga living in highland New Guinea, provide a prototypical example. In
such crisis situations, the Big Man of Mae Enga calls for a tribal meeting composed of adultmales, and solicits public responses without offering his personal opinion (Meggitt, 1977). Hisrole is rather like a chairperson of the meeting, basically adopting an alternative endorsed by amajority of the group as the tribe’s decision. Three other ethnographic records reviewed byBoehm (1996) converge with this observat ion.
Such ubiquitous roles of decision-making groups in various human societies, ranging
from tribal to highly industrialized societies, leads us to contemplate the adaptive or evolutionary
functions achieved by group decision- making (Barkow, Cosmides, & Tooby, 1992; Campbell,
1994; Caporael & Baron, 1997). As Boyd & Richerson (1985) and Wilson (1997) have argued,group decisions, or any other social mechanisms that bind individual behaviors (such as social
norms or conventions: cf. Henrich & Boyd, 1998; Kameda, Takezawa, & Hastie, submitted;
Kameda, Takezawa, Tindale, & Smith, 2002) decreases variability of individual fitness within aGroup Decision Making 36
group, while increasing the variability across groups. Because individuals belonging to the samegroup behave in essentially the identical manner due to these binding mechanisms, their levels offitness are similar within the group, but may greatly differ from those belonging to other groups.
Then, group decision making, as a representative binding mechanism in human societies, might
have played a specific role in hominid evolution, because it enhances the chance that the groupfunctions as a unit of natural selection. It is usually argued in evolutionary biology that natural
selection operating at the group level may be theoretically possible but weak enough to beignored. However, the common usage of group decision-making in human societies may add a
unique feature, increasing the chance of a meaningful impact of group- level selection in hominid
evolution (see Wilson & Sober, 1994; Sober & Wilson, 1998 for a comprehensive argument on
multi- level selection in evolution).
Evolutionary thinking highlights various adaptive issues associated with group decisionmaking. For example, why does social sharedness matter so much at various levels in guiding
group consensus? Why do people tend to endorse group decisions, even if their personal
preferences are not reflected in the decisions directly? We have revealed proximate causes toanswer these questions, but the ultimate causes (Barkow et al., 1992) behind these phenomena
are still largely unknown. Recently, several researchers have launched projects related to thesequestions. For example, Sorkin and his colleagues (Sorkin, West, & Robinson, 1998; Sorkin,
Hays, & West, 2001) examined adaptive efficiencies of group decision making under noisy
environmental conditions. Based on the signal- detection framework, these researchersdeveloped a model of how group performance depends on the group size, the competence ofmembers, correlation among members’ judgments, the constraints on member interaction, andGroup Decision Making 37
the group’s decision rule. In particular, they showed that a simple majority rule often achieves
quite efficient performance in group decision- making.
A similar approach has also been taken by Kameda & Hastie (in preparation). Stimulated
by recent work on “fast and frugal heuristics” in individual decision- making (Gigerenzer, Todd,& ABC Research Group, 1999), they examined adaptive efficiencies of various group decisionrules under uncertainty by a series of computer simulation. Implementing a stochastic
environment where the property of adaptive target is known only probabilistically throughseveral proximal cues (cf. Hammond, 1996), Kameda & Hastie conducted a systematic
evaluation of various group-level decision rules or heuristics. The results indicated that, despite
being fast and frugal in terms of necessary computation, majority rule is fairly robust against
random noises, missing information, etc., and consistently outperforms other decision rules.
Together with the Sorkin et al. studies, these results provide one, though still incomplete, answer
to why majority rule based on shared preferences may operate so strongly in consensus groups(see also Henrich & Boyd, 1998; Kameda & Nakanishi, submitted, for adaptive basis ofconformity in groups). Extending such an adaptive perspective to the functioning of social
sharedness at other levels, viz., shared cognition and shared metacognition, seems a promising
future direction, which may link social psychological work on group decision making toevolutionary anthropology (Boyd & Richerson, 1985; 1996) and evolutionary biology (Dugatkin& Reeve, 1994) in an integrated manner.
Dynamical Systems, Social Sharedness and Group Deci sion Making
Another area with potential relevance to small group decision- making, and social
sharedness, is dynamical systems theory (Vallacher & Nowak, 1994). Much of the past work on
small group decision-making has tended to focus on linear, antecedent-consequence type

Group Decision Making 38
relations with manipulations of independent variables (e.g., group size, task type) seen as causingchanges in dependent variables (e.g., group choice, implicit decision rule). Although thisapproach has taught us much about group decision-making, its very nature focuses attention on
one or a few variables while ignoring virtually all others. In addition, even relatively short
discussions leading to a decision involve multiple exchanges along numerous dimensions. Eachmember speaks, listens, looks, laughs, frowns, agrees, disagrees, etc. and each action can affect,
and is affected by, each and every other action. In groups with longer durations (e.g., teams,
corporate boards), these factors vary over time and are affected by characteristics of the specificmembers, the group, and the social/institutional context (Arrow, McGrath, & Berdahl, 2000).
The dynamical systems approach focuses on patterns of change as a function the current
state of a system and the dynamical variables that control the system (i.e., order parameters).
The current state of the system is defined by the current values of the dynamical variables. Thus,
the dynamical variables define the system as well as changes within it. Often the system is seen
as a point in a multi-dimensional space (the phase space). The “control parameters” are thefunctions that define the relationships among the dynamical variables (see Guestello, 1996, orVallacher & Nowak, 1994 for a more complete discussion of the dynamical systems approach).
Such models can capture the complexity of systems (like groups) and can help to explain
seemingly inconsistent or erratic aspects of the systems behavior. Chaos, catastrophe, andcomplexity theory are all derivatives of this approach.
In the small group arena, probably the most well developed models of this type are Arrow,
McGrath, and Berdahl’s (2000) complex systems theory of small groups and Nowak, Szamrej,
and Latané (1990) dynamic social impact theory. Arrow et al. outline a general theory of small
group formation, coordination, development, and adaptation using a complex dynamical systems

Group Decision Making 39
approach. They define three levels of dynamical variables: constituent elements of the group or
local dynamics (e.g., members, tasks, norms), characteristics of the group as an entity or global
dynamics (e.g., size, structure, goals), and the contexts in which the groups are embedded orcontextual dynamics (e.g., culture, organization, community). Although group decision- making
per se is not a major focus of their work, decision- making is one aspect of the local dynamics ofmany groups. The theory is very recent and has yet to receive much research attention (though
see Berdahl, 1998; 1999), but could hold much promise as a context for future theoretical andempirical developments.
Dynamic social impact theory (Nowak et al., 1990, Latané & Bourgeois, 2001) is anextension of Latané’s (1981) theory of social impact that posited three key aspects of social
influence associated with the influence source – strength (e.g., power, persuasiveness),
immediacy (physical and/or social distance) and number of influence sources compared to thenumber of targets. The dynamic version of the theory (Nowak, Szamrej, & Latané, 1990; Latané& Bourgeois, 2001) uses a dynamical systems approach to incorporate the dynamic andreciprocal nature of social influence. In addition to the assumptions specified above, thedynamic version of the model adds three more. First, it assumes that individuals (varying instrength and other attributes) are distributed in a social space. Their location in the space defines
their immediacy in terms of other individuals within the space. That is, immediacy reflects thedegree group members share the same social space. Second, each individual is influenced by
his/her own position (e.g., belief, attitude, preference) and by the other people in proportion to a
multiplicative function of their strength, immediacy, and number. Third, a person will change
his/her position if and only if the total persuasive impact (the pressure to change to a different
position) outweighs the pressure to maintain one’s own position (the strength of the initial

Group Decision Making 40
position plus any supportive impact). Dynamic social impact is then taken to be the cumulative
effect of the iterative, recursive influence present during interaction
Using computer simulations (SITSIM, Nowak & Latané, 1994), Latané and colleagues
have discovered a number of consistent findings, which have then been tested in different
experimental settings. The most central finding for current concerns is that people tend to clusterin the social space in terms of position similarity. In other words, a random distribution of
positions within the space will soon become organized into “belief clusters”. Thus, social
sharedness develops naturally as a function of basic dynamic social processes. Second, the space
will tend to consolidate in such a way that majority positions tend to become stronger (moreprevalent) and minority positions weaker. However, unless the initial majority is extremely large,
minority clusters remain even after thousands of iterations. Thus, diversity of opinion continues
despite the consolidation process. An additional aspect of the simulations shows that people inclusters tend to become similar to each other on multiple issues – what Latané has called
correlation. Thus, sharedness on one dimension induces sharedness on other dimensions. Each ofthese simulation results have received empirical support in a number of different social
aggregates, even in situations where there are few if any reasons for people to change theirpositions to match those around them (Latané & L’Herrou, 1996). Again, although not yet
directly applied to group decision- making, this seems like a rich framework for exploring boththe formation and implications of social sharedness in decision- making groups.
Shared Social Identity and Group Decision Making
Although originally a theory of intergroup relations, social identity theory (Abrams &Hogg, 1990; Hogg, 2001; Tajfel & Turner, 1979) has begun to play a major role inunderstanding small group processes. Based mainly on Turner's (1985) related notions of selfGroup Decision Making 41
categorization and group prototypes, a number of researchers have shown that making group
identity salient impacts on the social influence processes associated with group consensus (e.g.,
Hogg, Turner, & Davidson, 1990). These theories are reviewed thoroughly in another part ofthis volume (Hogg & Abrams, Chapter 19), so we will only provide a brief discussion here. The
basic ideas stem from the notion that people categorize themselves on many levels, with mostlevels defined by group membership. When membership in a particular group is made salient,
the self becomes defined, in part, by the group. Thus, group norms become more important. Self
categorization theory goes on to argue that members hold a prototype of the typical groupmember and attempt to behave in accordance with (or more like) this prototype. In addition,group identity allows o ne to differentiate one's self and one's group from other groups, much likeany form of categorization both defines what an item is and what it is not. This tends to lead toprototypes that help the differentiation process.
For example, if one categorizes oneself as a member of the group of people who oppose
capital punishment, differentiating oneself from people who favor capital punishment would
make one more prototypic of one's group. This notion has been used to help explain grouppolarization and increased conformity to group norms (Abrams, Marques, Bowen, & Henderson,
2000; Hogg et al., 1990). In a sense, the notion of social sharedness is inherent in the idea ofsocial identity. By categorizing one's self as a member of a group, one implicitly recognizes asharing of whatever characteristics define group membership. Thus, there should be a number of
implications of shared social identities for group decision making besides group polarization.
One interesting aspect of shared social identities that has yet to be explored involves
whether they can function as shared task representations (Tindale et al., 1996). Shared identities
should lead to shared preferences, but if they don’t, arguments or positions consistent with theGroup Decision Making 42
shared identity should be particularly influential. There is some evidence that arguments
consistent with shared group memberships (religion) can be persuasive even when presented by aminority (Smith et al., 2000). However, much more work in this area is needed to fully
understand the role that social identity plays in decision-making groups.
Probably the major theme underlying the future directions discussed here is that decisionmaking groups are context situated and context sensitive (Hinsz, et al., 1997; Levine, Resnick &Higgins, 1993).

Group decisions are made within evolutionary/adaptive, cultural, institutional,

intergroup, and historical/normative intragroup contexts developed over the history of thegroup’s existence. The research reviewed here does not pay enough attention to these contextual
aspects of group decision- making. However, shared contexts probably play as important a rolein decision making groups as do shared preferences, cognitions, and metacognitions. In fact,
sharedness at the levels discussed here probably stem from these contextual features. We hopethat recent developments in theoretical frameworks that explicitly mention such contextual
features will correct this deficiency in the future.

Group Decision Making 43
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Group Decision Making 64
Table 1Social Decision Scheme Matrices for Two Models: Proportionality and Majority Equiprobability Otherwise

Pre-Discussion

Proportionalitya

Otherwise b

Preference Patterna

Majority-Equiprobability

G

NG

G

NG

G

NG

6

0

1.00

0.00

1.00

0.00

5

1

0.83

0.17

1.00

0.00

4

2

0.67

0.33

1.00

0.00

3

3

0.50

0.50

0.50

0.50

2

4

0.33

0.67

0.00

1.00

1

5

0.17

0.83

0.00

1.00

0

6

0.00

1.00

0.00

1.00

Combinatorial process that the probability that a group will choose a particular alternative isequal to the proportion of members favoring the alternative at the outset of group interaction.
b

Combinatorial process that an alternative endorsed by a majority of members at the outset ofinteraction will be chosen by the group (in cases where no initial majority exists, then eachalternative is equally likely to be the group’s choice).

Group Decision Making 65
Table 2An Illustrative Example of Group Decision -Making Involving Several Conditional Judgments---------------------------------------------------------------------------------------------------------Member
Condition 1 Condition 2 Preference---------------------------------------------------------------------------------------------------------A
Yes
Yes
InvestB
YesNo
Not investCNo
Yes
Not invest----------------------------------------------------------------------------------------------------------

Group Decision Making 66

Proportions of preferences/decisions

0.8
0.7
0.6
0.5

Individual

0.4

5-member
group

0.3

9-member
group

0.2
0.1
0
Low

Moderate

High risk

Figure 1. Majority/Plurality Processes and Group Polarization