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Improving work motivation and

performance in brainstorminggroups: The effects of three

group goal-setting strategiesJrgen Wegge

a& S. Alexander Haslam

b

aUniversity of Munich (LMU) , Germany

bSchool of Psychology , Exeter, UK

Published online: 17 Feb 2007.

To cite this article:Jrgen Wegge & S. Alexander Haslam (2005) Improving workmotivation and performance in brainstorming groups: The effects of three group goal-

setting strategies, European Journal of Work and Organizational Psychology, 14:4,

400-430, DOI: 10.1080/13594320500349961

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Improving work motivation and performance inbrainstorming groups: The effects of three group

goal-setting strategies

Ju rgen WeggeUniversity of Munich (LMU), Germany

S. Alexander HaslamSchool of Psychology, Exeter, UK

An experiment was conducted with 30 groups (n 120) solving brainstormingtasks under four different group goal conditions: do your best (DYB), directivegroup goal setting (DGGS), participative group goal setting (PGGS), andPGGS in combination with individual goal setting (PGGS IGS). Asexpected, all groups with specific and difficult group goals performed betterthan DYB control groups. It is hypothesized that these positive effects ofgroup goal setting on brainstorming performance arise because group goal

setting counteracts motivation losses such as social loafing. In addition,group goal setting should promote motivation gains arising from socialcompensation and related cognitive processes, in particular high identificationwith the group. Consistent with this hypothesis, it was found that group goalsetting increased team identification, the readiness to compensate for otherweak group members, the value of group success, and the value of groupfailure. Mediation analysis also indicated that concern to avoid group failurewas partly responsible for performance improvements. Finally, no largedifferences were found between PGGS IGS and PGGS or DGGS. On thisbasis group goal setting can be considered a robust strategy for improvingwork motivation and brainstorming performance in groups.

During the last few decades working in groups has become increasingly

popular in organizations. This is consistent not only with common beliefs

Correspondence should be addressed to Ju rgen Wegge, Ludwig-Maximilians-Universita t

Mu nchen (LMU), Department of Psychology, Psychology of Excellence, Martiusstrasse 4,

D-80802 Mu nchen, Germany. Email: [email protected]

This research was supported by a grant from the University of Dortmund (Kennzahl 81 14

31). The authors would like to thank Ed Locke, Daan van Knippenberg, Michael West, and

three anonymous reviewers for detailed comments on an earlier version of this article.

EUROPEAN JOURNAL OF WORK AND

ORGANIZATIONAL PSYCHOLOGY

2005, 14 (4), 400430

2005 Psychology Press Ltd

http://www.psypress.com/ejwop DOI: 10.1080/13594320500349961

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about the synergy that can emerge when people work in teams but also

with insights from organizational and social psychology. Compared to

more traditional forms of work design, collaboration in teams has been

found to enhance communication, innovation, and the quality of decision

making (Cohen & Bailey, 1997; Haslam, 2004; Kerr & Tindale, 2004; West,

2002; West, Borrill, & Unsworth, 1998). Moreover, working in teams or

groups (terms that we use here as synonyms) satisfies motivations for

collective self-actualization and meaningful work (Ellemers, de Gilder, &

Haslam, 2004). However, it is also widely recognized that teamwork is often

plagued with specific motivation and coordination problems. With respect to

group brainstorminga method of collective idea generation in groups

popularized by Osborn (1957)it is consistently found, for example, that

the inability for more than one group member to talk at a time (productionblocking) is a powerful process that can hamper team performance.

In addition, social loafing can occur when group members are not

individually identifiable or accountable for their performance (Karau &

Williams, 1993). Evaluation apprehensionwhereby group members are

concerned about the other group members appraisal of their ideasis also

another prominent motivation loss that can contribute to poor performance

on brainstorming tasks (see, for recent reviews, Kerr & Tindale, 2004;

Paulus, 2000; Paulus, Dugosh, Dzindolet, Coskun, & Putman, 2002;

Thompson, 2003).Based on this knowledge, research and applied literatures offer several

recommendations for improving traditional group brainstorming. For

example, prior research has documented the efficacy of using a facilitator

who is trained to minimize production blocking and evaluation apprehen-

sion (Oxley, Dzindolet, & Paulus, 1996). Other promising interventions

involve using electronic brainstorming (Pinsonneault, Barki, Gallupe,

& Hoppen, 1999) or exchanging written ideas in a sequential manner

(Paulus & Yang, 2000). The present research seeks to contribute to this

literature by analysing the efficiency of setting a specific and challenginggroup goal(e.g., trying to find 35 new ideas for solving a problem as a group

in 5 minutes). More specifically, the study examines the effects of three

group goal-setting strategies: (a) directive group goal setting by an authority

in a friendly and convincing tell and sell manner where a rationale for a

challenging group goal is given (DGGS), (b) participative group goal

setting by an authority realized within a fair group discussion about the

appropriate group goal (PGGS), and (c) PGGS in combination with

individual goal setting (PGGS IGS). All three strategies are based on

goal-setting theory (Locke & Latham, 1990, see below), and it is

expected that these techniques will motivate brainstorming groups

to work better than groups that are instructed simply to do their best

(DYB-control).

GROUP GOAL SETTING 401

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Almost no prior research has examined if and how different group goal-

setting interventions enhance performance in brainstorming groups (but for

preliminary positive tests see Wegge & Haslam, 2003; Wegge & Kleinbeck,

1996). Garnering empirical evidence on this issue is therefore important for

practical reasons. Accordingly, the first aim of this study is to assess whether

group goal setting should be added to the list of interventions that have the

potential to increase performance in brainstorming groups. From a more

theoretical perspective, the study also seeks to investigate the motivational

underpinnings of the expected performance improvements induced by group

goal setting. It will be argued that the positive effects of group goal setting

on brainstorming performance arise because group goal settingcounteracts

the occurrence of motivation losses in teams such as social loafing. In

addition, this procedure should promote motivation gains such as socialcompensation (e.g., a deliberate decision to compensate for the weaknesses

of other team members) and related cognitive and emotional processes

resulting from high identification with the group. These putative links

between different group goal-setting manipulations and motivation gains or

motivation losses in teams have rarely been analysed in previous research

(Ellemers et al., 2004; Hertel, 2000). Thus, the second aim of the study is to

examine whether there is a fruitful link to be made between goal-setting

theory and social psychological research into motivational processes in

teams.

THEORETICAL BACKGROUND

There are literally hundreds of studies that demonstrate a reliable impact of

goals on behaviour (Locke & Latham, 1990, 2002). Based on this evidence, it

is widely acknowledged that goals (intentions) are an immediate and

powerful regulator of human action. Goal-setting research has also

examined which aspects of goals are most important for predicting

differences in task performance. The current evidence on this question isconclusive. It has consistently been found that specific and difficult

performance goals lead to better performance than easy goals or unspecific

goal instructionstypified by invitations to Do your best.

The effects of goal setting, however, have typically been analysed in

relation to individual performance (Wagner, 1994). As a consequence, far

fewer studies have examined the impact ofgroup goals (an intention shared

by a group) on group performance. Nevertheless, there are several recent

studies indicating that group goal setting improves team performance

(DeShon, Kozlowski, Schmidt, Milner, & Wiechmann, 2004; Durham,

Locke, Poon, & McLeod, 2000; Wegge, 2000; Wegge & Haslam, 2003) even

though some failures have also been reported (e.g., see Sagie, 1996; Wegge &

Haslam, 2004). In a meta-analysis covering 26 effect sizes derived from

402 WEGGE AND HASLAM

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10 studies conducted between 1978 and 1991 and comprising data from 163

groups and 1684 individuals, OLeary-Kelly, Martocchio, and Frink (1994)

found that performance of groups striving for a specific difficult group goal

is almost one standard deviation higher (d .92) than the performance of

groups that do not have clear goals (DYB-instructions). This effect is

referred to here as the GGS-effect and building on this work we propose that

it will also be observed in brainstorming groups:

Hypothesis 1: Compared to control instructions (DYB), group goal-

setting techniques (DGGS, PGGS, PGGS IGS) will increase brain-

storming performance.

CURRENT EXPLANATIONS FOR GROUPGOAL-SETTING EFFECTS

What mediating mechanisms contribute to the overall GGS effect? At least

two distinct propositions have been developed by previous researchers.

Often it is suggested that the mediating processes of GGS effects areidentical

to those mechanismsincreased effort, high persistence, task focusing,

development and use of appropriate task strategiesthat are responsible for

goal-setting effects in individual performance situations (see DeShon et al.,

2004; Durham et al., 2000; Locke & Latham, 1990, 2002). This propositionis plausible since individual performance is usually the basis for team

performance. Moreover, team members sometimes set individual goals in

accordance with group goals (Widmeyer & Ducharme, 1997) so that

individual goals and corresponding mechanisms might mediate the effect of

group goals.

However, the individual goals of group members are sometimes in

conflict with either (a) the individual goals of other group members, (b) self-

set group goals, or (c) group goals suggested by group leaders (Crown &

Rosse, 1995; Haslam, 2004; Hinsz, 1995; Mitchell & Silver, 1990; Peterson,1999; Tjosvold, 1998). In the same situation, for example, some group

members might be guided by their individual goals (e.g., to work slowly and

reduce ones effort) while other group members strive for the group goal

(e.g., to work fast and achieve a high group standard). Various types of goal

conflicts can be found in groups (see Wegge, 2004, for a recent review) and

these goal conflicts serve to complicate predictions regarding the impact of

goal-setting manipulations by an (external) authority.

In the same vein, it is recognized that group work typically requires

additional processes such as communication and planning within the whole

team that are not necessarily required in individual performance situations.

Weldon and Weingart (1993) developed a model describing three specific

group-level mechanisms: (a) group planning (e.g., talking about who should


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do what, when, and where in the team), (b) cooperation (e.g., listening to the

ideas of others, helping team mates performing their work), and (c) morale-

building communication (e.g., statements that build a sense of collective

efficacy or that stimulate supportive emotions). In this model, it is assumed

that high values of these three processes increase the quality of group plans

and the expectancy of successelements that should serve to facilitate team

performance. To date, there is some evidence showing that the GGS effect is

mediated by task-specific group planning (e.g., Durham et al., 2000;

Weingart, 1992; Weldon, Jehn, & Pradhan, 1991). However, empirical

evidence for the two other group mechanisms is weak. Consistent with the

assumption of Weldon and Weingart (1993), in the present study it is argued

that goal-setting theory has to beextendedif it is applied at the group level.

More specifically, it is proposed that further empirical efforts to identifypossible group-specific mechanisms underlying group goal effects should

consider those motivational processes that are usually discussed under the

heading of motivationlosses and motivationgains in social psychology

(Haslam, 2004; Hertel, 2000; Karau & Williams, 1993; Stroebe, Diehl, &

Abakoumkin, 1996).

GROUP GOAL SETTING AND MOTIVATIONLOSSES IN GROUPS

The basic phenomenon of motivation losses in groups is well documented in

social psychology (Karau & Williams, 1993). When individuals work in a

group they sometimes exert less effort than they do when working

individually on the same task. This basic phenomenon is called motivation

loss and it takes on several different forms. In particular, research has

provided evidence of (a) social loafing effects (unintentional reduction of

work motivation and effort when working collectively; Karau & Williams,

1993), (b) free-riding effects (deliberate reduction of effort if a persons

contribution is seen to be unnecessary for the group to succeed; see Kerr &Bruun, 1983), and (c) sucker effects (the deliberate withdrawal of effort that

occurs if a person realizes that a capable team partner is free-riding; Kerr,

1983; Kerr & Bruun, 1983).

To our knowledge, only three previous studies have empirically examined

possible links between motivation losses and group goal setting. Matsui,

Kakuyama, and Onglatco (1987) argued that providing both individual and

group goals and corresponding performance feedback increases the

identifiability of individual performance in teams, thereby counteracting

social loafing. In addition, group goals and group feedback should prevent

the occurrence of sucker effects. This is because having a specific, difficult

group goal should make people feel that their own efforts are indispensable

even if other team members are free-riding. Matsui et al.s empirical work


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provides support for both propositions. Similarly, Erez and Somech (1996)

found that group performance loss (measured by the difference between

performance scores of individuals working alone and their scores when

working in groups) is less likely to occur when specific, difficult goals

(individual or group) are present. Finally, van Leeuwen and van

Knippenberg (2002) showed that group goal setting can improve group

performance because it affects social matching processes that might also lead

to motivation losses in groups (e.g., where individual standards regarding

ones own contribution to the group product are shifteddownwardsto match

low performance or the standards of weaker group members; see also Paulus

et al., 2002).

Even though these ideas and results are intuitively plausible, it is

important to note that there is no empirical evidence corroborating linksbetween different types of group goals and motivation losses. Moreover,

previous research has focused on task performance as a dependent variable.

Therefore, it is not clear whether different goal-setting strategies system-

atically change the expectations and judgements of group members that

underlie the occurrence of motivation losses in teams. A sucker effect arises

if group members realize or expect that other members of their team are

engaging in free-riding behaviour (Kerr & Bruun, 1983) and, therefore, this

phenomenon should not occur ifnofree-riding behaviour is expected. With

respect to social loafing, findings from previous research show that this canbe encouraged by lack of concern for group success or group failure (Hertel,

Konradt, & Orlikowski, 2004; Karau & Williams, 1993). Thus, placing value

on group success or on the prevention of group failure should counteract the

phenomenon of social loafing. The differentiation between the value placed

on success and failure is also introduced here in light of findings reported by

Higgins (1997), which show that the same behaviour might be motivated by

a promotion focus in self-regulation (i.e., to achieve positive states) or by a

prevention focus (to avoid negative states). Taken together, the following

hypothesis can thus be derived:

Hypothesis 2: Compared to control instructions (DYB), group goal-setting

techniques (DGGS, PGGS, PGGS IGS) enhance (a) the expectation that

other team members will not free-ride and (b) the subjective importance

of team success and team failure.

GROUP GOAL SETTING AND MOTIVATION GAINSIN GROUPS

With the exception of social facilitation induced by the mere presence of

(coacting) others (Bond & Titus, 1983), the possibility that groups can

contribute to motivation gains has, until recently, been largely overlooked


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(Stroebe et al., 1996). Nevertheless, an emerging body of research suggests

that group contexts provide specific stimuli that can motivate individuals to

exert more effort in groups than they do when working on the same task

individually. This basic phenomenon is called motivation gain. Whereas

the existence of such phenomena is now becoming widely accepted, there is

still debate about how many different motivation gains can and should be

distinguished (for recent reviews see Haslam, 2004; Hertel, 2000; Wegge,

2004).

In the present study, we focus on a motivation gain referred to associal

compensation. Williams and Karau (1991, p. 571) proposed that under some

conditions people may work harder in a collective setting than in a coactive

setting in order to compensate for others in their group. In support of this

idea, Karau and Williams (1997) and Williams and Karau (1991) foundevidence that group members sometimes compensate for the deficiencies of

other group members on a collective task (e.g., group brainstorming) in

order to ensure group success. Thus, contrary to the sucker effect, work

motivation is enhanced when a group member realizes or anticipates that

other group members are performing poorly (e.g., because of low work

motivation or low ability). Based on previous research, individuals

readiness to socially compensate for other group member should be

increased if the group task is perceived as meaningful (e.g., the task itself

is interesting and valuable) and if the person is concerned about how thegroups performance is evaluated (e.g., by other co-workers or by a

supervisor or other external agencies). Moreover, Williams and Karau

(1991, p. 580) suggest that social compensation should also be more

pronounced if the group is relatively small, when it appears that the

individual must continue to remain in the group, and at earlier stages of

the collective process. In addition, social compensation in teams should be

more likely if group cohesion is high (Karau & Hart, 1998) and if group

members identify with other members of the group so that the group is

perceived as a salient part of ones own social identity (Haslam, 2004;Haslam & Ellemers, 2005; van Knippenberg & Ellemers, 2003).

To our knowledge, there is almost no research that has examined possible

links between group goal setting and social compensation or other related

processes (e.g., social identification, task interest) that may contribute to this

relationship. Indeed, aside from a few studies showing that PGGS can

enhance group cohesion (Wegge & Kleinbeck, 1996; Widmeyer &

Ducharme, 1997), we have no indication that GGS has an impact on these

variables. However, having a clear performance goal and corresponding

feedback often makes tasks more valuable and intrinsically motivating

(Fried & Ferris, 1987; Mento, Locke, & Klein, 1992). Moreover, at the level

of individual performance and individual goal setting there is some evidence

showing that self-set goals increase intrinsic motivation, especially when


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these goals are challenging (Harackiewicz, Barron, Tauer, Carter, & Elliot,

2000; Latham, Erez, & Locke, 1988). In addition, thinking or talking as a

group about a common group goal inherently promotes a team focus

(Haslam et al., in press; Wegge & Haslam, 2003). Hence, it would be

expected that group goal setting has the power to promote the emergence of

social compensation along with feelings and judgements that bolster this

phenomenon. This leads to:

Hypothesis 3: Compared to control instructions (DYB), group goal-

setting techniques (DGGS, PGGS, PGGS IGS) enhance (a) readiness

to engage in social compensation, (b) group cohesion, (c) group

identification, and (d) intrinsic work motivation in groups.

A final objective of the study is to assess the relative strengths and

weaknesses of the three different group goal-setting strategies. Is it effective

to combine group goal setting and individual goal setting in teams

(PGGS IGS)? As successful work in groups (e.g., flying a plane) often

requires specific group members to do a specific job, adding individual goal-

setting procedures related to the subtasks of group members (e.g., flying

safely, being polite to passengers) seems a logical supplement to general

group goal setting (e.g., to produce high customer satisfaction). However, to

date, this type of goal-setting strategy has received little empirical attention(Crown & Rosse, 1995; Matsui et al., 1987; Mitchell & Silver, 1990) and

results are mixed (e.g., Mitchell and Silver, 1990, found no beneficial effect

of adding individual goals to group goals, whereas Matsui et al., 1987,

reported performance enhancements for the same manipulation). Therefore,

it is not clear if, and under which circumstances, this strategy might be

effectivein particular, because studies also differ with respect to the tasks

employed. Matsui et al., for example, used an additive task with low task

interdependence, whereas Mitchell and Silver employed a task in which

task interdependence was very high and competition (due to negative goalinterdependence introduced by an individual goal) was detrimental to

group performance. Accordingly, the present study seeks to collect more

evidence pertaining to this issue. In the same vein, the study explores

potential differences between participative and directive group goal-setting

strategies. Are the processes through which these interventions improve

group performance similar or different? We know from previous work (e.g.,

Erez, 1995; Latham et al., 1988) that assigning goals in a directive tell and

sell style can be as effective as participative goal setting. However, very few

similar comparisons have been made at the group level (but see Kerr &

Tindale, 2004, pp. 22.722.8; Wegge, 2000) and, as a result, firm conclusions

about the impact of different strategies at this level are hard to draw. It

might be the case, for example, that participation is more important at


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the group level because the group context intensifies the desire to have a

voice in decisions (Haslam, Eggins, & Reynolds, 2003) or because directive

supervisor behaviour has less influence in front of a group, in particular

when the going gets tough (Wegge & Haslam, 2003, 2004).

In sum, to our knowledge, previous research has not examined whether

different strategies of group goal setting (e.g., DGGS, PGGS) do have the

power to prevent motivation losses in teams such as social loafing and/or

whether they promote the occurrence of motivation gains in teams such as

social compensation. Moreover, it is unclear if the most common group

goal-setting strategies have similar impact with respect to their effectiveness

in improving work motivation and performance in teams. Given the lack of

previous work on these issues, the present study is largely exploratory with

respect to the comparative efficacy of the three group goal-settinginterventions whose impact it investigated.

METHOD

Participants

The sample consisted of 60 male and 60 female students (mean age 24.46

years, range 19 to 37 years, SD 1.48) from a large German University

with different majors (psychology excluded). Participants were recruited bymeans of advertisements on notice boards in the university. They worked

together in 30 four-person (2 male, 2 female) groups. Each person received

7.50 Euros for participating in the study. No further financial incentives

(e.g., for goal attainment) were provided.

General procedure

On arrival, participants were informed that the purpose of the study was to

analyse the effectiveness of brainstorming in groups. Group members werefirst requested to answer a personality questionnaire. This questionnaire

asked participants to provide biographic and demographic details (e.g., age,

sex). Next, students had to work together on a brainstorming task. All

groups were asked to solve three different trials (see below). After Trial 2

was finished, the experimenter determined in which condition the group was

placed. The experimenter was a trained student assistant who was blind to

the hypotheses that were tested in this study. After this, he enacted the

corresponding group goal manipulation (e.g., PGGS or DGGS). Immedi-

ately after this manipulation, andbeforeTrial 3 of the brainstorming task, a

second questionnaire was distributed that assessed several key variables

(e.g., perceived participation, group goal commitment; see the measure

section below). After completion of Trial 3, intrinsic motivation and desire


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for further team cooperation was assessed by means of a third ques-

tionnaire. Finally, participants were paid, debriefed, and asked not to

discuss the experiment with others.

Task and experimental design

All groups were asked to solve three trials of a brainstorming task. Each trial

lasted 3 minutes and presented a new problem. As a group, participants had

to find and write down individually as many different uses for common

objects (e.g., a pocket lamp) as they could. Group members were informed

that brainstorming typically seeks to produce as many different solutions

to a problem as possible and that, therefore, the number of unique uses

generated is the appropriate measure of team performance. After each trial,all group members were asked to read their ideas out aloud. The experi-

menter counted the number of unique uses (e.g., so that lighting a dark

room and lighting a cellar were counted as one idea) generated by all

group members and always verified his judgement with the group in a short

discussion.1

Trial 1 was a practice trial. In Trial 2 of the brainstorming task, all groups

were instructed to do their best (DYB) to establish a baseline for group

performance. In Trial 3, goal instructions varied according to the selected

group goal-setting strategy (see below). It should be noted that theexperimenter considered several points when deciding before Trial 3 in

which condition a group should be placed. First, it was important to have

similar performance values across the four conditions in Trial 2 because

otherwise it would be difficult to compare group performance. As the number

of groups was relatively small, the probability of fulfilling this desirable

condition by chance alone is low. Therefore, the experimenter followed the

principles of a matched-groups design: Groups were assigned as quad-

ruplets to conditions after performance in the baseline was known. As soon

as a match in baseline performance was found, the next available conditionwas selected randomly. Of course, to determine which group goals can be

assigned to DGGS groups, it is necessary to test some PGGS groups before.

Therefore, this type of group was tested most often. It was also decided that

six control groups would be sufficient for the purpose of this study.

1The correlations between quantity and quality of ideas (unique uses) was very high in this

study (e.g.,r .88,p5 .01 in Trial 2 andr .85,p5 .01 in Trial 3) so that only the number of

unique ideas is considered below as an indicator of group performance. This is not only

warranted in view of the high correlations but also because instructions emphasized the qualityof ideas and group goals were also formulated with respect to this performance indicator. It

should be also noted that brainstorming tasks often include additional features (building upon

other group members ideas) that were not present in our study.


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With the help of this procedure it was possible to hold both baseline

performance and goal difficulty constant across conditions even though

group assignment was still almost random.

For control groups (DYB, n 6), the DYB-instruction was simply

repeated in Trial 3. Groups in the participative group-goal condition

(PGGS,n 10) were asked to determine a specific group goal through group

discussion for Trail 3. For this purpose, each group member first made an

individual suggestion for the group goal. In order to facilitate a GGS effect,

the experimenter attempted to influence the suggestions of group members

by emphasizing that the group should agree on achallenginggroup goal. He

stated that, based on data from pilot studies, good groups achieve a

performance improvement of 40% from baseline. Thus, 40% more ideas

would constitute a challenging group goal. Next, individual suggestionswere collected and announced by the experimenter. The mean value of these

suggestions was computed and fed back to the group. As expected on the

basis of pilot testing, this value was usually below 40%. Next, the

experimenter asked the group to discuss these suggestions and to come up

with a more challenging group goal. The experimenter accepted every group

goal that represented an increase in difficulty (the mean of these goals is

between 34% and 38% in the three conditions with specific group goals, see

Table 3 below).

In the second participation condition (PGGS IGS, n 6), all groupmembers had to determine individual goals in combination with group goals

for Trial 3. After group goals had been established in the same manner as

PGGS, the experimenter explained that individual goal setting usually

assists group goal setting. Therefore, each group member was told to

formulate individual performance goals (e.g., finding 8 ideas) to support the

group goal (e.g., finding 32 ideas as a group in the last trial). The

experimenter then asked group members to write down these suggestions

and asked the group to discuss them so that the sum of the goals would be

consistent with the previously established group goal. The range of theseindividual goals was between 6 and 17 ideas (M 10.4 for the 24 relevant

participants) and the mean within-group variance of individual goals was

2.47 indicating that individual goals within groups were quite different.2

However, discussions were not difficult as all groups found it easy to agree

on a set of individual goals that was consistent with the group goal.

Finally, following the rules of a matched-group design, 8 of 10 group

goals that were set participatively in PGGS conditions were later assigned in

2Difficulty of individual performance goals is correlated both with individual performance in

baseline trials (r .74,p5 .01) and with difficulty of the first individual suggestion for a group

goal (r .41, p5 .05).


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a tell and sell style by the experimenter in the directive group goal

condition (DGGS, n 8). He referred to results from pilot studies and

stated, for example, that 34% performance improvements from baseline

constitute a challenging but reachable group goal. The experimenter

then encouraged the group to strive for this goal and calculated the number

of ideas that needed to be generated in order to achieve this goal in the

last trial.

Measures

Constructs were assessed by observation on the part of the experimenter and

with the help of three questionnaires distributed during the experiment.

Unless stated otherwise below, all self-report items used in Questionnaires13 were composed and developed in a series of experiments summarized by

Wegge (for details see Wegge, 2004).

Observation by the experimenter

For each group, the experimenter noted on a special sheet several aspects of

the group process for each trial. These variables were: (a) individual

performance (the number of different uses in one trial), (b) group

performance (the total number of unique uses found in one trial by allgroup members, always verified with the group in a short discussion, see

above), (c) individual suggestions for a group goal, (d) individual suggestion

for an individual goal, and (e) chosen individual and group goals.

Questionnaire 1

To collect demographic data (e.g., with respect to age, gender, major),

several questions were asked before Trial 1. Gender was balanced across

conditions. As the age of group members also did not vary systematicallyacross the four experimental conditions (F .06,p5 .98), and because data

in this study is analysed at the group level (see below), these variables are not

considered further.

Questionnaire 2

This questionnaire was administered before Trial 2 and assessed the

following eight variables:

Perceived participation. As a manipulation check, participants with

specific group goals responded to the following two items using 4-point

scales ranging from low (1) to high (4): I had a real voice in determining


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which group goal we selected to strive for and In comparison to

the experimenter, my impact on the difficulty of group goal was low;

reverse coded).

Group goal commitment. This was measured by means of nine items

using 4-point response scales ranging from low (1) to high (4). These items

assessed different antecedents of commitment to goals that have been

identified as important in previous studies (see Klein, Wesson, Hollenbeck,

& Alge, 1999): the value of goal attainment (e.g., If the group reaches its

goal, this will have pleasant consequences for me), expectancy of group

goal attainment (e.g., It is highly likely that we are a little bit better than

the group goal requires), and volitional strength during goal attainment (I

stick to the group goal even when I realize that my feelings divert me fromthis goal).

Group cohesion. This was assessed using six items, three indexing liking

of other group members (e.g., Quite frankly, I have to admit that I like the

other group members) and three items addressing pride in being a member

of the group (e.g., If you are a member of this group, you can feel proud).

Individuals responded to these items on 4-point response scales ranging

from low (1) to high (4).

Group identification. This was assessed with four items using 4-point

response scales ranging from low (1) to high (4) selected from Luhtanen and

Crocker (1992). Typical items were: My membership in this group has

much to do with how I feel as a person; The group I belong to is an

important reflection of who I am).

Social compensation. This was assessed by means of three items using 4-

point scales ranging from low (1) to high (4). A typical statement with which

participants stated their agreement was If other group members fail tosolve the group task because they do not have enough ability, I will work

especially hard to reach the group goal.

Value of group success andvalue of group failure. These were measured

with following two items: Please mark on the following scale how valuable

the success or failure of the group would be for you3 . . .. The value of

3

As success and failure are defined somehow differently in DYB groups (e.g., belonging tothe best groups is a success) and in groups with specific group goals (e.g., achieving the group

goal is a success), corresponding explanations were added in the specific questionnaires used in

these conditions.


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success can range from 0 without value to 5 of very high value;

the value of failure can range from 0 without meaning to 5 very

meaningful.

Expect no free-riding. This was measured with three items using 4-point

scales ranging from low (1) to high (4). An illustrative item was, In my

group we have a free-rider who is taking advantage of other group

members (reverse coded).

Questionnaire 3

After Trial 3 of the brainstorming task, a final questionnaire was

administered. This incorporated measures of the following two constructs:

Intrinsic motivation. This was assessed before performance feedback by

means of following three items: Even if we were not successful in reaching

the group goal . . . (a) working on the group task was really fun, (d) the

group task was interesting, and (c) during the group task time was passing

very quickly. Individuals responded to these items on a 5-point scale

ranging from low (1) to high (5).

Desire for further team cooperation. This was measured after performancefeedback from the experimenter as an index of future work motivation.

For this measure, individuals responded to three items (e.g., I can imagine

solving more tasks with this group) once again using 4-point answering scales

ranging from low (1) to high (4).

RESULTS

Measurement reliability, level of analysis, and descriptive data

Based on calculated alpha reliabilities, the measurement reliability of all

scales was good (see Table 1). Thus, all constructs are measured in a

consistent way.4 In this study, performance of whole intact groups is

examined. Even though individual performance data is available, for

theoretical reasons the level of analysis is the group (for a discussion of

4This is also true for the variable social compensation because this scale was comprised of

only three items. Here, an alpha of .60 still indicates a satisfactory measurement consistency

(Cortina, 1993). This is because the alpha statistic strongly depends on the number of items. Analpha of .50 would indicate, for example, a mean item correlation of .25 for a scale with 3 items

and this would be equal to an alpha of .77 for a scale with 10 items having the same average item

correlation.


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TAB

LE1

AlphaR

eliabilities(inparenthesis),A

verageWithin-Group-Variances(V),AverageWithin-Group

Agreement(Rwg),GroupMe

ans(M),

StandardDeviations(SD)andCorrelationsofVariablesforallG

roups

Variable

V

Rwg

M

SD

1

2

3

4

5

6

7

8

9

1.group

goalcommitment1

0.25

0.91

2.8

0.2

(.79)

2.group

cohesion

0.32

0.92

2.4

0.2

.47*

(.85)

3.group

identification

0.26

0.88

1.3

0.3

7.02

.23

(.83)

4.socialcompensation

0.34

0.82

3.1

0.3

.53*

*

.25

.37*

(.60)

5.intrinsicmotivation

0.57

0.84

3.8

0.4

.38

.51**

.25

.49**

(.70)

6.expect

nofree-riding

0.28

0.89

1.6

0.3

.24

.35*

.03

.40*

.18

(.74)

7.valueofgroupsuccess

1.20

0.60

2.2

0.8

.65*

*

.23

7.04

.41*

.41*

7.13

()

8.valueofgroupfailure

1.01

0.50

1.3

0.5

.47*

.32

.15

.38*

.34

7.18

.74**

()

9.furtherteamcooperation

0.41

0.82

2.9

0.2

.33

.53**

.11

.23

.52**

.14

.33

.49**

(.74)

10.performanceimprovement

10.1

5.6

.29

.17

.23

.18

.40*

.05

.20

.32

.31

Notes:

1n

24fourpersongroups(otherwisen

30fourpersongroups);*

p5

.05,**p5

.01.

414

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these issues see Klein & Kozlowski, 2000). Thus, with the exception of

alpha reliabilities, statistical analysis is based on group means. In order to

check whether aggregation at the group level is appropriate, within-

group variance (V) of variables was calculated. This measure is easily

interpretable and recommended5 by Schmidt and Hunter (1989). As

documented in Table 1, the average within-group variance is below the

critical value of 1.00 for almost all variables indicating that analysing the

data at the group level is justified. A more fine-grained examination of this

index reveals that only 7 out of 204 group values are larger than 1.00 for

variables measured with scales. For the two one-item measures (value of

group success and group failure) the within-group variance is higher.

However, only 9 out of 60 groups have values greater 1.50 so for these

variables there is moderate within-group consistency. As most priorresearchers have used the Rwg-index developed by James, Demaree, and

Wolf (1984) to estimate within-group agreement, we also calculated this

index (assuming random measurement error). Similar conclusions can be

drawn with respect to this data. Mean values of the Rwg-index for all

constructs that were measured using scales are higher than .70, a value

typically considered to indicate substantial within-group agreement. For

the two one-item measures, average within-group agreement is lower.

Accordingly, taken together, this analysis indicates that aggregation to the

group level is justified as there is moderate to very high within-groupconsistency.

In view of the observed correlations, the following points are worth

noting. First, all correlations are meaningful. For example, high group goal

commitment correlates positively with high group cohesion and with

readiness to engage in social compensation. Second, in most cases the

correlations are of low to moderate strength. Thus, it can be concluded that

different scales (e.g., group cohesion and group identification) do indeed

measure different constructs. Third, the correlations with respect to

improvement in group performance (ideas in Trial 3 minus ideas in Trial 2)are in line with various theories of work motivation. Here we obtain

positive correlations between performance improvement and group goal

5This measure is similar to the typically computed Rwg-index but less dependent on scale

features. For a detailed discussion about differences see Schmidt and Hunter (1989) as well as

James, Demaree, and Wolf (1993). Some researchers argue that ICC values should be computed

for this purpose, too. These values determinebetweengroup inconsistency. However, we follow

the argument of George and James (1993) who explained why documenting between group

inconsistency is not required for justifying aggregation at the group level if consistency withingroups is assumed. According to the terms defined by Klein and Kozlowski (2000), our model

for aggregation of the data to the group level is a consensus model. Thus, we do not analyse the

variancebetween groups but only the agreement within the group.


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commitment, group cohesion, group identification, and value of group

success. These correlations are not significant in this sample. Nevertheless,

they are of similar strength to effects observed in recent meta-analyses that

have examined the impact of these variables (e.g., r .23 for the goal

commitmentperformance relationship; see Klein et al., 1999). Finally, there

is also one significant correlation with respect to performance improvement

in this study. Performance enhancement is correlated positively with

intrinsic task motivation, r .40, p5 .05. As this variable was measured

aftertask completion, the correlation probably reflects not only the effects of

motivation on performance but also the effects of group performance on

motivation.

Manipulation checks

Table 2 presents data relevant to examination of the effectiveness of the

experimental manipulations. First, with respect to the degree of perceived

participation it was found, as expected, that group members in

participative groups (PGGS and PGGS IGS) reported having more

input in determining the group goal than group members with assigned

group goals, t73.46, p5 .01. There were no differences between PGGS

and PGGS IGS and both values are significantly higher (p5 .05) than

values from DGGS groups. Thus, in both conditions group membersperceived themselves to have more voice than in DGGS groups. Second, as

expected, it was also found that group goal commitment was high in all

these conditions. Thus, goal setting was effective in establishing commit-

ment to group goals. Third,baseline performance (ideas in Trial 2) did not

differ significantly across the four experimental conditions even though the

number of groups in each condition is rather small. Thus, experimental

procedures to assign groups to conditions were effective. Finally, a further

potential confound in this study is group goal difficulty as a direct

comparison between directive and participative goals is only justified if thegoal difficulty is similar. Furthermore, a GGS effect is only expected for

teams striving for challenging group goals. Again, the data with respect to

both issues (see Table 2) indicates that all manipulations were successful.

Compared to baseline performance (ideas in Trial 2), all specific group

goals can be considered to have been difficult. On average, groups

intended (or were asked by the experimenter when goals were assigned)

to improve their performance by more than 30% (DGGS38%;

PGGS38%; PGGSIGS 34%). This is almost twice as much as

the average performance improvement usually observed in goal-setting

studies. Thus, group goal difficulty was high and comparable across

conditions with specific group goals and, therefore, a GGS effect should be

observed.


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TAB

LE2

Means(M)andstandar

ddeviations(SD)ofselected

variablesandcorresponding

resultsfrom

MANOVAs

DYB(n

6)

DGGS(n

8)

PGGS(n

10)

PGGS

IGS

(n

6)

C-A

D-P

P1-P2

M

SD

M

SD

M

SD

M

SD

Perceivedparticipation

2.3

0.7

3.0

0.3

3.1

0.3

73.46**

Groupgoalcommitment

2.9

0.2

2.8

0.2

2.7

0.2

Ideasintr

ial2

27.0

5.5

28.4

6.5

28.3

9.8

26.8

2.6

Groupgoalsfortrial3

38.3

8.9

37.6

12.3

34.2

3.9

Ideasintr

ial3

32.8

8.4

40.0

5.0

40.1

12.9

36.5

4.6

Performan

ceimprovement

5.8

a

6.3

11.6

b

5.5

11.8

b

5.6

9.7

b

3.8

C-A(trial23)72.12*

Notes:DY

B

doyourbest,DGGS

direc

tivegroupgoalsetting,PGGS

participativegroupgoalsetting,

PGGS

IGS

PGGSincombinationwith

individual

goalsetting,C-A

HelmertcontrastDYB-controlvs.allotherconditions,D-P

Helmertcon

trastdirectivevs.participative

conditions,

P1-P2H

elmertcontrastPGGSvs.PGGS

IGS;*p5

.05,**p5

.01,onlysignificantt-valuesarepresented.

a,

b

indicatehomogeneoussub

-groupings

thatdiffer

accordingtoadditionallycondu

ctedposthoctestswithp5

.10

.

417

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Statistical group comparisons

To test mean differences across the four experimental conditions,

MANOVAs were used in which data from all groups is analysed

simultaneously. Here the use of Helmert contrasts is most appropriate

because this form of contrast compares (a) the first group (DYB) to the

remaining groups (C A, this reveals overall GGS effects), (b) the second

group (DGGS) to the remaining groups (D P, this reveals differences

due to participation) and (c) the third group (PGGS) to the last

group (P1P2, this shows differences due to adding IGS). It should be

noted that this form of contrast does not constitute a post hoc com-

parison of groups as our corresponding hypotheses require testing exactly

these differences. In addition, results from post hoc tests (Duncan)are reported below to describe other significant differences between

groups in order to provide a more fine-grained analysis of motivational

variables.

Tests of Hypothesis 1

As shown in Table 2, consistent with goal-setting theory and in support of

Hypothesis 1, striving for specific, difficult group goals (DGGS, PGGS, and

PGGS IGS) improved group performance more than striving for DYBgoals. A MANOVA with the factor group (the four group goal conditions)

and the factor trial (Trial 2 vs. Trial 3) as a repeated-measures factor was

conducted in order to examine this effect more closely. In this analysis, two

effects were significant: the main effect for trial, F(1, 26) 95.14, p5 .01,

indicating that all groups improved their performance over time, and the

theoretically relevant contrast of the interaction (DYB vs. all other groups

for performance differences across trials),t(26)72.12,p5 .05, indicating

that all groups with specific group goals showed improved performance

relative to DYB control groups. As can be seen from Table 2, there wasevidence of a substantial GGS effect as groups with challenging,

specific group goals improved performance about twice as much as control

groups.

To estimate the effect size of this interaction,6 an additional regression

analyses was conducted in which a dummy variable was computed that

recoded the four conditions in such a way that DYB groups had the value 0

and all other groups the value 1. As expected, a regression of this dummy

6Unfortunately, the SPSS (11.0) output for the MANOVA procedure does not report effect

sizes for Helmert contrasts (solely t-values are given), so additional computations are necessary

to get this information.


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variable (representing the corresponding Helmert contrast C A) on

performance improvements from Trial 2 to Trial 3 yielded a significant

effect, standardized .39, R2 .15, F(1, 29) 5.1, p5 .03. Thus, about

15% of variance in group performance improvement was based on the use

of group goal-setting interventions.


Table 3 presents data with respect to those motivational variables that

were expected to underlie the GGS effect. Do group goal-setting

techniques decrease the probability of a sucker effect by enhancing the

expectation that other team members showno free-riding behaviour? This

Hypothesis (2a) finds only weak support in the data as the correspondingHelmert contrast (C A) is not significant. However, the results of post

hoc testing indicate that the combination of both group and individual

goals (PGGS IGS) enhances this expectation compared to control

groups. In line with expectations, the results also show that the value of

group success, t(26)72.15, p5 .05, and the value of group failure,

t(26)72.62, p5 .02, is indeed much higher in groups with specific

group goals than in DYB groups (Hypothesis 2b). As social loafing in

groups is typically considered to be a motivation loss that is linked with

low values for group success and low value of group failure, socialloafing should therefore be less likely in groups striving for challenging

group goals.


With respect to potential motivation gains four variables are relevant. As

expected, groups striving for specific, difficult group goals reported a higher

readiness to engage in social compensation than DYB groups. However,

results from post hoc tests and the significant Helmert contrast comparingDGGS to the two participative conditions (DP), indicate that this finding

was only obtained for DGGS groups. Thus, only directive group goal-

setting procedures increased group members readiness to compensate for

other weak group members, t(26) 2.71, p5 .01. A parallel result was

found with respect to the variable intrinsic motivation. Once again, DGGS

was the best strategy for enhancing this motivational state, t(26) 2.17,

p5 .05. With respect to group cohesion there were no significant differences.

However, for the group identification measure we found the expected

pattern such that groups with specific, challenging group goals identified

more with their group than DYB groups, t(26)72.23, p5 .04. Finally,

the desire for further team activity was generally quite high and did not vary

across conditions.


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TAB

LE3

Means

(M)andstandarddeviations

(SD)ofvariablesacrossfour

groupgoalconditionsandco

rrespondingresultsfrom

MA

NOVAs

DYB(n

6)

DGGS(n

8)

PGGS(n

10)

PGGSIG

S

(n

6)

C-A

D-P

P1-P2

M

SD

M

SD

M

SD

M

S

D

Expectno

free-riding

1.5

a

0.4

1.7

ab

0.2

1.6

ab

0.3

1.8

b

0

.1

Valueofg

roupsuccess

1.6

a

1.0

2.5

b

0.6

2.3

b

0.5

2.1

ab

0

.9

72.15*

Valueofg

roupfailure

0.9

a

0.6

1.6

b

0.5

1.5

b

0.3

1.2

ab

0

.5

72.62**

Socialcom

pensation

2.9

a

0.3

3.3

b

0.2

3.0

a

0.2

3.1

a

0

.1

2.71**

Groupcohesion

2.5

0.2

2.4

0.3

2.4

0.2

2.4

0

.2

Groupide

ntification

1.1

a

0.1

1.4

b

0.3

1.4

b

0.2

1.3

ab

0

.1

72.23*

Intrinsicm

otivation

3.6

a

0.2

4.1

b

0.4

3.8

ab

0.5

3.7

a

0

.4

2.17*

Furtherte

amcooperation

3.0

0.2

3.1

0.4

3.0

0.2

2.9

0

.1

Notes:DY

B

doyourbest,DGGS

direc

tivegroupgoalsetting,PGGS

participativegroupgoalsetting,

PGGS

IGS

PGGSincombinationwith

individual

goalsetting,C-A

Helmertcon

trastDYB-controlvs.allotherc

onditions,D-P

Helmertcontra

stdirectivevs.participativeconditions,P1-

P2

Helm

ertcontrastPGGSvs.PGGS

IGS;*p5

.05,**p5

.01;onlysignificantt-valuesarepresented;a

,b

indicatehomogeneoussub-groupingsthat

differacco

rdingtoadditionallyconducted

posthoctestswithp5

.10.

420

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Mediational analysis

We intimated above that the prevention of motivation losses and the

promotion of motivation gains in groups could be a causal processes

responsible for performance improvements arising from group goal setting.

To explore this possibility, exploratory hierarchical regression analyses

were conducted. First, a variable was computed that recoded the four

conditions such that DYB groups had the value 0 and all other groups the

value 1. As already described above, a regression of this variable on

performance improvements from Trial 2 to Trial 3 yielded a significant

effect, standardized .39, R2 .15, F(1, 29) 5.1, p5 .03. Next, we

tested whether this effect could be substantially reduced by incorporating

the three potential mediator variables7 in the regression before the dummyvariable is entered. This was not the case for value of success, .37,

p5 .06, or group identification, .43, p5 .03. However, when the value

of group failure is entered as a potential mediating variable, the effect

was reduced, .31, p5 .12, R2 .11, reduction in R2 .04. This finding

suggests that the value placed on group failure plays an important role in

explaining group goal-setting effects on performance in brainstorming

groups. That is, teams striving for difficult group goals seem to be

concerned to avoid failure and this contributes to good brainstorming

performance.

DISCUSSION

The results of this study are important in several aspects. First, we found the

expected group goal-setting effect in groups performing group brainstorm-

ing tasks. This effect was substantial in magnitude with groups striving for

challenging group goals generating approximately twice as many additional

ideas (11 ideas) as DYB control groups (6 ideas). On this basis, it can be

concluded that group goal-setting techniques do indeed have the capacity toimprove brainstorming performance in groups. As performance improve-

ments were similar for all three of the group goal-setting strategies (DGGS,

PGGS, and PGGS IGS) examined in this study, we can draw the

additional conclusion that this effect is not only substantial but also quite

robust: It can be achieved in several ways. In addition, if we consider that

performance improvements in DYB groups probably reflect group learning

7

Following the basic logic of Baron and Kenny (1986), there are three potential mediatingvariables that might underlie the interaction found for group performance because similar

interactions (CA) were found for these variables (Table 3). A further test in which all three

variables were considered did not lead to different results.


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processes, it can further be concluded that this effect is found even when

these learning processes are controlled.

A second objective of this study was to explore how group goal setting

improves work motivation and performance in teams. With respect to this

goal, several new insights were gained. Previous research has shown that

group goal setting improves performance in teams for cognitive reasons

(e.g., by motivating group planning and knowledge exchange; Weldon &

Weingart, 1993). Here, we proposed that group goal setting (GGS) also

improves group performance for motivational reasons. It was argued that

GGS enhances work motivation in teams by preventing motivation losses

such as social loafing and sucker effects and by promoting motivation gains

such as social compensation and related phenomena (e.g., group identifica-

tion). In support of this idea, we found (a) that PGGS IGS increased theexpectation that no-one is free-riding in the group (thereby reducing the

likelihood of a sucker effect), (b) that GGS increased the value of group

success and the value of group failure (thereby counteracting social loafing),

(c) that GGS increased group identification, and (d) that DGGS, in

particular, increased intrinsic task motivation and the readiness of group

members to engage in social compensation.

The finding that the establishment of group goals has an impact on group

identification is quite novel (Wegge & Haslam, 2003). As group identifica-

tion is an important variable in explaining other motivation gains (e.g.,social labouring) and motivations losses (e.g., soldiering) in teams, and

because high group identification can also promote organizational citizen-

ship behaviour (e.g., helping new colleagues; Haslam, Powell, & Turner,

2000; Tyler & Blader, 2000) and other forms of positive organizational

functioning (e.g., see Haslam et al., 2003), this observation deserves further

attention (see van Knippenberg & Ellemers, 2003; Worchel, Rothgerber,

Day, Hart, & Butemeyer, 1998). Although the present results suggest that

this effect is not especially strong, group goal setting did increase group

identificationsuggesting that this manipulation also has the potential to beuseful in situations where achieving high team identification is a meaningful

objective in itself.

Considering these findings together, it indeed seems promising to examine

the possible links between goal-setting theory and social psychological

processes pertaining to motivation losses and motivation gains in teams.

However, it is worth noting that the reduction of motivation losses and the

promotion of motivation gains that was observed on the basis of

corresponding attitude measures didnot mediate the performance improve-

ments produced by the various group goal-setting strategies. Only one

variable (i.e., the value of group failure) emerged as a significant mediating

variable in this respect. Thus, even though some attitudes related to

motivation gains and losses in teams varied significantly as a function of


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condition, there may well have been other processes that were responsible

for the performance improvements obtained in this study (e.g., investing

more cognitive effort, differences in search of long term memory, a reduction

of evaluation apprehension; see Paulus et al., 2002; Wegge, 2001). This is

clearly an issue that merits investigation in future research.

Third, this study provided an opportunity to explore potential differences

in the efficacy of three different group goal-setting strategies. With respect to

this issue, the findings are rather meagre as the differences between

conditions were weak. It was not possible, for example, to show that

striving for a combination of participatively set group goals and partici-

patively set individual performance goals was superior to striving for group

goals alone (PGGS or DGGS). Even though previous evidence regarding

this issue is mixed, we expected a positive effect for PGGS IGS becausecommitment to group goals should be increased. This assumption can also

be derived from findings in the area of volitional psychology which

document an increase in goal commitment and goal fulfilment as a result of

having clear, specific implementation intentions (e.g., Brandsta tter, Leng-

felder, & Gollwitzer, 2001). Why was there no comparable effect in the

present study? In our view, the most plausible explanation is that the rather

simple group task used here was not one that is especially likely to lead to

improvement in goal commitment and performance due to combining both

types of goals. That is, group brainstorming was an additive task and therewas no specialization of labour within the group. Therefore, establishing a

common group goal (to produce 32 ideas as a group) almost inevitably

makes it clear which goals individual members should strive for (i.e., if the

group has four members then every group member should produce 8 ideas).

It might therefore be the case that the effectiveness of this group goal-setting

strategy would be more pronounced in relation to more complex tasks (i.e.,

those with high task interdependence or high task complexity). Nevertheless,

we should not forget that, consistent with the findings from Crown and

Rosse (1995), the data from the present study also indicate that acombination of both goals might establish a group-supportive performance

orientation as expectations that other group members willnot free ride were

only increased in this condition. Hence, this group goal-setting strategy

could prove to be most appropriate in situations where sucker effects are a

potential problem.

In sum, the results of this study clearly demonstrate that goal-setting

theory has to be extended when moving from the individual to the group

level. Moving beyond the work of Weldon and Weingart (1993), the study

has shown that the effects of different group goals on group performance

rely on the promotion of motivation gains and the prevention of multiple

motivation losses in groups. Therefore, these motivational processes should

be considered as important mediating variables in an extended theory of


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group goal setting. However, it is also worth noting that further work

linking goal-setting research to research traditions within social psychology

will not only be of benefit to group goal-setting research. It can be expected

that social psychological theories that deal with motivational phenomena in

groups (e.g., social compensation, social labouring) can also be substantially

advanced (see Ellemers et al., 2004, for a similar argument). In particular,

there seems to be considerable potential for integrating the principles of the

social identity approach (Haslam, 2004; van Knippenberg & Ellemers, 2003)

with the tenets of goal-setting theory (Locke & Latham, 2002) in order to

develop a more complete explanation of a range of motivational phenomena

in groups.

LIMITATIONS AND FUTURE DIRECTIONS

This study has several limitations. In the first instance, caution in

interpreting the results is warranted due to the rather low statistical power

at the group level. However, it should be also noted that the strategy we

developed to cope with some of the problems linked to small samples (e.g.,

using a matched group design) was successful as several important

preconditions (e.g., having a similar baseline performance before interven-

tions are enacted, having constant goal difficulty across conditions) were

achieved. Nevertheless, further replications with a larger number of groupswould of course be desirable.

Caution in generalizing these findings is also warranted due to the fact

that we examined ad hoc groups of students in a laboratory. While

conducting a study in a laboratory context has some advantages (e.g., in

allowing a fine-grained analysis of different group goal-setting procedures),

it also has limitations. We do not know, for example, whether the behaviour

of university students and their temporary supervisor in a short-term

setting can be generalized to the behaviour of employees at the workplace

where career success and promotion are at stake. However, especially in therealm of goal-setting research there is ample evidence that findings from the

laboratory generalize to more realistic conditions (Locke, 1986; Locke &

Latham, 2002). Primarily, this is because this generalization is based on

soundtheorythat is validated in an array of contexts (see Haslam & Reicher,

in press, for a similar argument). Thus, it seems reasonable to assume that

corresponding results to those obtained here could also be obtained in

organizational teams. Nevertheless, as laboratory groups are necessarily

decontextualized relative to applied settings, and because these groups

neither have a common history nor a common future, replication studies in

field settings certainly seem warranted.

Moreover, we should be also aware of the fact that potentially influential

factors were not measured (e.g., perceptions regarding indispensability of


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own efforts, evaluation apprehension) and not manipulated in this study.

Even though the limited evidence we have so far indicates that advantages of

group goal setting are probably task-specific (Wegge & Kleinbeck, 1996;

Weldon & Weingart, 1993), task demands were also not systematically

varied in this study. Future research should address this lacuna by

examining other group tasks and the impact of task interdependence during

teamwork. Of course, it also remains to be seen how effective group

brainstorming might become if the practice of setting challenging group

goals were combined with other interventions (e.g., use of a trained

facilitator, brain-writing techniques, or procedures that ask group members

to build on the ideas of other group members in a round-robin manner).

Moreover, in this study we focused only on thequantity of ideas (checking

and correcting for very similar ideas), not their quality. Because priorresearch has found that there is often a strong association between the

number of ideas and the flexibility and originality of ideas (Thompson, 2003,

p. 98), we did not attempt a more detailed analysis of our data. However, a

more sophisticated analysis in terms of originality or flexibility of ideas

produced by group members could potentially yield additional insights (e.g.,

see Adarves-Yorno, Postmes, & Haslam, in press). Moreover, this might be

another avenue for further research as such an analysis might help to

uncover the cognitive processes that are involved in producing group goal-

setting effects in brainstorming groups.Two further limitations of this study are linked to the procedures we used

for group brainstorming. First, the available time for finding ideas was

rather short (3 minutes). In brainstorming tasks, ideas are generated with

low effort and difficulty in particular at the beginning of the process (Oxley

et al., 1996; Paulus et al., 2002). Thus, the impact of motivational forces is

probably much easier to demonstrate over a longer time period. Future

studies, therefore, should examine whether group goal setting is even more

effective over longer time periods (e.g., 15 minutes). That said, it was notable

that group goal setting significantly improved performance even under therestricted time conditions selected in this studyso in many ways this was a

stringent test of our arguments.

Second, social loafing effects occur mainly in situations where group

members contributions are not identifiable and where performance feed-

back is not available (Karau & Williams, 1993; Paulus et al., 2002). As

group members were asked to read their ideas out loud to the rest of the

group after each trial, group members performance was identifiable and

evaluated by other group members and the experimenter. Thus, social

loafing would not necessarily be expected to have occurred in this context

and, accordingly, it would be interesting to investigate whether group goal-

setting effects are stronger in conditions where social loafing is more likely

(e.g., when ideas generation is anonymous; see Erez & Somech, 1996).


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Again, though, when we consider that social loafing was unlikely to occur in

this experiment and that DYB instructions also motivated groups to

increase their brainstorming performance, the demonstration of a group

goal-setting effect in comparison to DYB groups is nontrivial and all the

more impressive.

Finally, it should be also emphasized that improving group performance

in organizations necessarily involves much more than just using the most

appropriate leadership (goal-setting) technique. To make the use of group

work in organizations a real success, we also have to take into consideration

a range of other factors. These include, for example, effective group task

design (Ulich & Weber, 1996; van Vijfeijken, Kleingeld, van Tuijl, Algera, &

Thierry, 2002), relevant group feedback (Deshon et al., 2004; Kluger &

DeNisi, 1996; Schmidt & Kleinbeck, 1997), group training and groupdevelopment (Kozlowski, Gully, Nasson, & Smith, 1999) and appropriate

group compensation (DeMatteo, Eby, & Sundstrom, 1998; Hertel et al.,

2004). Nonetheless, the preliminary signs are that, added to these factors,

group goal-setting techniques can be a very effective tool in the

organizational psychologists armoury. On this basis, we encourage

researchers as well as practitioners to use these strategies in order to

improve brainstorming and other related forms of performance in teams.

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