Tacit Coordination in Anticipation of Small Group Task Completion

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     32, 129—152 (1996)  . 0006

Tacit Coordination in Anticipation of Small Group Task Completion G M. W, G S,  C J. M Miami University Received: February 10, 1995; revised: August 16, 1995; accepted: August 23, 1995 Group members may tacitly coordinate their actions by predicting others’ behaviors and adjusting their own behavior accordingly to meet the perceived demands of their collective task. Subjects read and recalled political candidate statements while anticipating either a group decision-making or collective recall task. When anticipating collective recall, they remembered more statements about topics outside of other members’ expected expertise, whereas they recalled more statements associated with others’ expected expertise when anticipating group choice. In a follow-up study, the bias toward duplicating others’ expected expertise under a choice set occurred when participants anticipated discussion followed by private choice but not when they anticipated having to satisfy an explicitly assigned group decision rule. These results are discussed in terms of a model of anticipatory tacit coordination.  1996 Academic Press, Inc.

When groups work together on a task, members must coordinate their activities to perform efficiently. Such coordination is often tacit in that members do not explicitly discuss strategies for performing the task (Hackman & Morris, 1975). Stasser and Wittenbaum (1995) identified this phenomenon as tacit coordination, defined as the synchronization of members’ actions based on unspoken assumptions about what others in the group are likely to do. This research was supported by Grant N00014-90-J-1790 from the Office of Naval Research awarded to the second author and a fellowship awarded to the first author from the National Science Foundation (DIR-9113599) to the Mershon Center Research Training Group on the Role of Cognition in Collective Political Decision Making at The Ohio State University. Portions of Study 1 were presented at the sixty-sixth annual meeting of the Midwestern Psychological Association, May, 1994, Chicago, IL. Portions of Study 2 were presented at the sixty-seventh annual meeting of the Midwestern Psychological Association, May, 1995, Chicago, IL. We thank Sandy Vaughan and Erin Wilson for help in creating the research materials, Stacey Seiber for assisting with data collection and creating materials, Candace Ferrell, Amy Hallal, and Amanda Nilsson for long hours of data collection and coding, and Lauren Katz, Melissa Layman, and Alyssa Piljan for coding and data entry. Correspondence and reprint requests should be addressed to: Garold Stasser, Department of Psychology, Miami University, Oxford, Ohio 45056. E-mail : gs4apsyf=miamiu.acs.muohio.edu. 129 0022-1031/96 $18.00

Copyright  1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

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Group action may often involve some degree of tacit coordination. For example, when making hiring decisions in an academic department, selection committee members must process a large body of information about many job applicants. Complete examination of all applicants’ materials is infeasible. So, committee members often make assumptions about the kinds of information to which other members will attend : Bob always examines the letters in great detail, Ann thinks teaching experience is important, and Jim judges success by the number of publications. Given other members’ past behavior, expertise, and interests, committee members can adjust their own behavior to facilitate the group’s task completion. If members correctly anticipated others’ attention to information, then the group has coordinated itself tacitly without explicit discussion of who should remember what. Despite the apparent pervasiveness of tacit coordination in small task-oriented groups, it has not been systematically studied. Although group members may tacitly coordinate their behavior during interaction by mutually adjusting their plans and expectations without discussion, the purpose of the current research is to examine the anticipatory processes of tacit coordination. Several lines of research support the notion that group members’ attempts to coordinate tacitly begin prior to interaction. In the groups that they observed, Hackman and Morris (1975) found that task-oriented groups rarely discussed plans for how to go about performing their task unless explicitly instructed to do so. Instead, groups seemed to implement existing strategies that were socially shared before discussion. Gersick (1988) observed task forces in natural settings and found that behavioral patterns were established early during each team’s first interaction. She assumed that the sheer speed with which behavioral patterns emerged suggests that they are the result of processes operating before groups convene, such as ‘‘members’ expectations about the task, each other, and the context and the repertoires of behavioral routines and performance strategies’’ (p. 33). Wegner (1986) proposed, in his theory of transactive memory, that group members form expectations about others’ likely contributions to the group’s task, where the task is to encode, store, and retrieve information. In his theory, groups act as memory units whereby members develop a shared system for managing information over time as members learn about each others’ areas of expertise. However, members begin to create the transactive system by initially making assumptions about what others will remember based on others’ presumed abilities, personal interests, access to information, past behavior, or stereotypes. According to Rouse, Cannon-Bowers, and Salas (1992), team mental models partly consist of shared knowledge about the team (e.g., roles of team members, relationships between team members, functioning of team members) and the task (e.g., evaluative criteria, procedures and strategies for completing the task). From this general knowledge, members form expectations about what each other will do in the given situation. Lastly, Bowers, Morgan, Salas, and Prince (1993) showed that active-duty military pilots hold general expec-

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tations about the degree and type of coordination needed for various routine and nonroutine flight operations. Taken together, the foregoing literature suggests that task-oriented groups implicitly coordinate their actions and develop ways of approaching the task by forming hypotheses about other members, the task, the environment, and the coordination requirements for the given situation before the group convenes. Instead of explicit discussion of how to go about performing a task, it seems that group members adopt strategies based on what they expect others to do given their presumed knowledge, abilities, interests, and access to resources. That is, members may make assumptions about the expertise domains of other group members, assume what others are likely to do based on their presumed expertise, and consequently adjust their own behavior to fit with the anticipated actions of others. This process is delineated further in a model of anticipatory tacit coordination. ANTICIPATORY TACIT COORDINATION: A MODEL As depicted in Fig. 1, anticipated tacit coordination of group action requires at least three components : member expectations, task assessment, and resource allocation. Member expectations include expectations about other members’ talents and actions. Members form hypotheses about others’ knowledge domains, interests, special skills, and performance abilities often based on a limited set of cues. According to expectation states theory, group members form expectations about others’ task competence based on task- relevant characteristics, such as members’ task experience, personal interests, and knowledge, as well as diffuse status characteristics such as age, race, and

F. 1 Model of anticipatory tacit coordination.

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gender (Berger, Conner, and Fisek, 1974; Berger, Fisek, Norman, & Zelditch, 1977; Berger, Rosenholtz, & Zelditch, 1980). Based on these assumptions, members infer what others are likely to do (i.e., how they will approach the task and the likely usefulness of their contributions). T ask assessment involves an assessment of the task demands as perceived by group members (i.e., what is to be accomplished by the collective action). This includes an estimation of the criteria used to judge successful task performance and the procedures and strategies that will likely facilitate it. Several group task typologies have been advanced (e.g., Hackman & Morris, 1975; McGrath, 1984; Steiner, 1972), but all classify collective tasks according to characteristics and procedures that seem inherent in the task. However, the ‘‘objective’’ rules and procedures for successful task completion may not be synonymous with group members’ ‘‘subjective’’ perceptions of task demands. One important distinction between tasks is whether they are viewed as primarily cooperative or competitive. The nature of coordination may change depending on whether group members see successful task completion as involving working together toward a common goal, or seeking to benefit individual goals at the expense of other members’ successful goal completion. Examples of cooperative tasks, according to McGrath (1984), include brainstorming, collective recall, problem-solving, and intellective tasks. Brainstorming and collective recall are maximizing tasks according to Steiner’s (1972) task typology. That is, success is a function of how much is accomplished. In these cases, members may realize that contributing diverse input maximizes the group’s collective output. Other tasks may not be maximizing tasks but their successful completion may be facilitated by diverse input. For example, problem-solving and intellective tasks (Laughlin & Ellis, 1986) possess a demonstrably correct solution that is most likely to be discovered with different input. Decision-making tasks can potentially be either cooperative or competitive. That is, members may view reaching a mutually satisfying consensus as the important goal or they may feel that getting the group to adopt one’s own position (i.e., advocacy) is the primary goal. Similar input may facilitate preference agreement whereas unique knowledge and arguments may facilitate advocacy in a group with conflicting preferences. Resource allocation refers to the allocation of one’s own resources to actions that facilitate successful completion of the group’s task given what others are expected to do. First, members must determine what the resources are. Depending on the task and what others are expected to do, members may judge their relevant resources as effort, time, information, strength, or talent. Second, members need to make a subjective assessment of the utilities of their possible contributions. If the task calls for diverse input, then members should try to focus on subtasks that others will not likely complete because duplication adds relatively little value to the group product. Conversely, if members view the task as one that requires common action, then members should try to duplicate others’ actions. Finally, every action entails a cost. By contributing

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one type of resource, members may be giving up their ability to contribute in another way. Thus, members need to determine which of their contributions would be the most beneficial and least costly for successful group task completion. TACIT COORDINATION: A CONSCIOUS PROCESS? The tone of the foregoing discussion suggests that group members engage in effortful calculations about other members, the task, and how to allocate their own resources to the group. However, the process of tacit coordination may not be a highly deliberate process, given the relative ease and speed with which some groups develop collective action patterns (e.g., Gersick, 1988). Other theories have speculated that expectations guide interaction patterns in groups in an automatic manner. In reference to the process by which members form expectations about others’ task competence based on their perceived status, Berger, Wagner, and Zelditch (1985) admit, ‘‘we believe that interactants, while engaging in interaction, typically are not aware of how expectation states are formed, what states are formed, or how these states are translated into behavior. The process... is, in all likelihood, largely outside the individual’s awareness’’ (p.36). In the learning literature, practice has been shown to increase performance. Although both individuals and group members may acquire knowledge about rules for task completion through practice, they seem to lack the ability to articulate such knowledge (Argote, 1993). Knowledge acquired through learning is often tacit, disorganized, inaccessible, and hence difficult to measure directly (Berry & Broadbent, 1984). Thus, we consider the possibility that group members will exhibit behaviors indicative of anticipatory tacit coordination without being able to report accurately that they have done so. STUDY 1 A major objective in Study 1 was to demonstrate that group members use cues about other members’ likely actions to guide their own behavior in anticipation of small group task completion. Moreover, we wanted to determine if group members are responsive to variations in task demands when reacting to expectations about others’ behaviors. Given that coordination is defined relative to something to be done, varying task demands (as perceived by members) seems essential to demonstrating that members attempt to coordinate tacitly their activities. Therefore, for Study 1, we wanted two group tasks that involve the same materials, but placed different demands on the group. Collective recall and group decision-making are two tasks that place distinctly different demands on the group but can be based on identical sets of information. In addition, these tasks represent common cognitive tasks faced by organizational, political, and social groups. For a collective recall task, the group goal is to remember collectively as much information as possible. In order to maximize the amount of recall

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produced by the group, members should try to remember information that others will not likely remember. Focusing on information that others will likely remember risks duplication of effort, whereas focusing on information that others are not expected to recall increases the chances that one’s efforts will add to the collective performance. Results from Giuliano and Wegner (1985, cited in Wegner, 1986) support the notion that group members attempt to maximize collective recall by remembering information that others probably will not recall. They found that when a member of an intimate couple was assigned responsibility for remembering particular items of information while working on a collective recall task, the member did recall more of those items only when he or she believed the partner would not recall them (i.e., the partner was not presumed to be expert in that domain). We suspected that a similar effect would occur for members of adhoc groups. Group decision-making tasks implicitly demand that members integrate information to form individual preferences and then pool information and preferences (usually, via discussion) to obtain a collective decision. As mentioned earlier, the manner in which members prepare for a decision-making task may depend on whether they perceive the goal as facilitating the emergence of a cooperative agreement or as persuading others to adopt one’s own preference. In the former case, the pressures are to identify a shared set of information that will yield a consensus or, at least, justify the groups’ ultimate choice. Thus, the collective information processing goal for cooperative decision-making tasks is not to minimize information output but may, in fact, be to reduce the set of available information to a subset that facilitates consensus-seeking. Thus, members may tend to focus on information that they anticipate others will also remember. By focusing on the same information as others, members can operate from a shared set of knowledge and, by doing so, may more easily and comfortably reach a consensus. However, if members perceive the decision-making task as conflictual, then being well-informed may prepare members to argue their position and sway others’ judgments. In this case, members may prepare for a group decision-making task by considering both common and unique information to an equal degree. Common information may allow them to anticipate others’ arguments and form counterarguments whereas unique information permits them to advance novel arguments (Vinokur & Burnstein, 1974). In addition to ascertaining members’ sensitivity to task demands, we were interested in determining members’ sensitivity to cues about others’ likely actions. More specifically, we were interested in exploring how impoverished social cues can be and still evoke coordination attempts by members. Are members willing to base allocation of effort on member expectations formed from remote social cues or do they attempt to coordinate their actions only when given relatively proximal and direct predictive cues about others’ actions? Group members often have rather limited information about what other members are likely to do in a given situation. Thus, if tacit coordination

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is a prevalent phenomenon, it seems that members must be willing to base member expectations on rather distal (and, perhaps fallible) cues. More specifically, in the present study, university students anticipated either a collective recall task or a group decision-making task. In either case, they were required to process an extensive set of task-relevant information about three candidates for student body president. Individually, they could reduce the processing demands by coordinating their effort with the anticipated actions of others. On the one hand, if they were explicitly told that another member had personal expertise in an identifiable domain of the information (e.g., he or she is interested and knowledgeable in minority issues), they could easily use this social knowledge to focus their own cognitive activities. On the other hand, if they were given only general social information about another person (e.g., major, extracurricular activities), they would first have to infer from these social cues that the individual has personal expertise in a given area before they could use this social knowledge to guide their own information processing. Given the apparent prevalence of tacit coordination, we expected that group members would not only use direct information to form expectations about others’ action but also use general social knowledge to form these expectations. University students individually read descriptions of three hypothetical candidates for student body president with the expectation that their future five-person group would be asked either to decide on the best candidate, or to recall collectively as many candidate statements as possible. Before reading the candidate statements, participants reviewed bogus questionnaires ostensibly completed by the other four group members. These questionnaires suggested that the others collectively were ‘‘experts’’ on three of the five topics covered in the candidate descriptions. Others’ expertise was either explicitly indicated on the questionnaire or implicit in the questionnaire content. After reading the candidate statements, subjects were unexpectedly given 6 min to individually recall the candidate statements. Free recall was coded for statements associated with free topics (areas not associated with other members’ expertise) and taken topics (areas of other members’ expertise). We expected that subjects who anticipated collective recall would remember more free than taken topic statements whereas subjects who anticipated a group decision would remember more taken than free topic statements if they perceive the task as cooperative. However, those anticipating a group decision may recall taken and free topic statements to the same extent if they perceive the task as conflictual. Also, we expected that these effects would occur both when others’ expertise was implicit in the questionnaire content and when others’ expertise was explicitly indicated. Method Subjects and Design Eighty-nine introductory psychology students at Miami University participated in partial fulfillment of a research experience requirement. The design of the study was a Task Set (decide vs

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recall)]Expertise Salience (explicit vs implicit)]Topics (free vs taken) mixed factorial with the topics factor being a repeated measure. Nine subjects were suspicious of the manipulations and so their data were excluded from the analyses presented here, leaving a total of 80 subjects.1 The paticipants were assigned to experimental conditions randomly with the restriction of maintaining equal sample sizes in each of the four experimental conditions defined by task set and expertise salience.

Materials Candidate profiles. Each candidate made fifteen statements—three statements in each of five different topic areas related to campus issues : academic issues (e.g., advising, course scheduling and offerings, class evaluations), campus crime and safety (e.g., escort service, rape awareness, substance abuse), dorm life (e.g., roommate assignments, room decoration restrictions), minority issues (e.g., University affirmative action policies, cultural awareness), and social life (e.g., campus activities, Greek policies). On the basis of an independent sample’s (N\50) preexperimental ratings of candidate policy statements, we constructed each of the three candidates’ profiles to include six positive, four negative, and five neutral items of information. Positive items are those that were rated, on the average, as moderately to highly desirable for a candidate by pretest participants, whereas negative items were rated as moderately undesirable. (In order to avoid unrealistic profiles, extremely undesirable attributes were not used.) Neutral items received neutral desirability ratings. College life questionnaires. The College Life Questionnaire requested information such as students’ major, college-related extracurricular activities, favorite class, and features about the University that they like. Bogus profiles of ‘‘experts’’ in each of the five topic areas were created by fabricating a series of responses to this questionnaire. Others’ expertise was either implicit in the questionnaire content, or explicitly indicated on the questionnaire as the response to the additional question, ‘‘Which of the five topics related to college life do you know most about? (check one)’’. Two profiles for each of the five topic areas were chosen for use in the study based on a separate sample’s (N\36) preexperimental ratings of the implicit versions of 24 bogus profiles. All of the chosen expert profiles were rated as highly knowledgeable in their target area of expertise and moderately knowledgeable in the other four areas. For example, one ‘‘social life’’ expert was a member of a sorority/fraternity, worked on the ‘‘Greek Week’’ committee and as a rush guide, and reported liking going uptown with friends and the ‘‘Greek atmosphere’’ at Miami. As

TABLE 1 N  E T  E  E F Expert Folder A B C D E

Academic

Crime

Dorm

Minority

Social

0 2 1 1 0

0 0 2 1 1

1 0 0 2 1

1 1 0 0 2

2 1 1 0 0

1 At the end of each experimental session, the experimenter asked subjects if they knew, before assembling in groups, that the anticipated group members were fictitious. We eliminated those subjects who claimed to definitely know that the other members, as described in the questionnaires, were bogus. We did reanalyze the data for all measures with the nine suspicious subjects included in the analyses. None of the results changed as a consequence of adding these subjects.

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summarized in Table 1, the College Life Questionnaires, as ostensibly completed by other participants in the study, were compiled into five folders representing five different group compositions. Each folder contained four bogus questionnaires that were chosen so that a participant would anticipate interacting with four other individuals who were collectively expert in three of the five topic areas. Two of the questionnaires in a folder suggested overlapping expertise in one topic area, and the other two suggested unique expertise in two other topic areas. In other words, three of the five topics covered in the candidate descriptions were taken by others (i.e., others possessed expertise in these topics) and two of the topics were free (i.e., not areas of others’ expertise). We constructed the folders to have two members with redundant expertise so that the manipulation would seem more realistic and less contrived or obvious. Any one participant received only one pattern of other expertise (i.e., folder type A, B, C, D, or E in Table 1). However, to control for extraneous variables associated with particular topic areas, each folder type occurred equally often within each of the four conditions defined by the task set and expertise salience factors.2

Procedure Participants met in small rooms at the beginning of the session. In the introduction to the experiment, subjects were told that the study concerned the coordination of activities in a group, however, for the first part of the experiment, they would be working independently in small rooms. The experimenter explained to subjects that they would have the opportunity to share information about themselves with their future group members before their group actually convened. Subsequently, they would be asked to read and discuss hypothetical student body president candidates in small groups composed of other participants scattered in the various small rooms. Participants were told that often group members know ‘‘surface information’’ about each other before the group convenes. So, in order to simulate these types of ‘‘real-world groups,’’ participants completed the College Life Questionnaire, either the implicit or explicit version, and expected that this questionnaire would be shared with the future group members. While working on a filler task (i.e., writing a short essay), subjects were told that the experimenters would be compiling the College Life Questionnaires of others in their group. The questionnaire was printed on four-layer carbon sheets so that it was apparent that the experimenter could easily rip out the copies and distribute them among group members. After completing the filler task, the experimenter gave subjects a folder containing the College Life Questionnaires ostensibly completed by the other group members. The task set manipulation was first introduced at this point. Subjects were told that they would eventually read descriptions of three hypothetical student body president candidates and that their group would be asked either to decide on the best candidate (decide set), or collectively recall as many candidate statements as possible (recall set). Subjects were then given as much time as they needed to examine the folders. Following the perusal of the bogus questionnaires, subjects were again reminded of their anticipated group task, and then individually read descriptions of the three hypothetical candidates. Subjects anticipated convening in their groups immediately after reading the candidate statements. Instead, they were unexpectedly given 6 min to individually recall the candidate statements. Additional questions were asked after the individual free recall task to assess the effectiveness of the manipulations and subjects’ own attention, interest, and knowledge in the five topics as well as their group’s knowledge of these topics. Although the experiment was functionally complete after obtaining the additional questions, subjects were nevertheless placed into groups with other subjects in nearby rooms to engage in their expected group task. After groups

2 Folder was included as a control factor in all of the reported analyses for Studies 1 and 2. Although there were sporadic interactions of folder with other factors, inclusion of folder did not materially qualify any of the reported findings. Therefore, we reran all of the analyses without the folder factor and, in the interest of space, have reported only those analyses.

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completed their task, members were thanked, fully debriefed regarding the deception and the purpose for its use, and invited to complete a mailing label to obtain a copy of the results once the study was completed.

Results and Discussion Manipulation Check T ask set. After the free recall task, participants were asked to rate individually how much attention they devoted to trying to remember the candidates’ statements (recall rating) and how much attention they devoted to deciding on the best candidate (decide rating). Ratings were made on a tenpoint scale ranging from 0 (very little attention) to 9 (very much attention). A 2]2]2 (Task Set]Expertise Salience]Rating) mixed factorial ANOVA revealed two effects : a main effect of rating, F(1,76)\4.98, p\.05, and an interaction between task set and rating, F(1,76)\26.35, p\.0001. Overall, subjects reported giving more attention to determining the best candidate (M\5.64) than to remembering candidates’ statements (M\4.89). However, as intended, only decide set subjects reported giving significantly more attention to deciding on the best candidate (M\6.63) than to remembering the candidates’ statements (M\4.15), F(1,76)\27.12, p\.0001. Recall set subjects reported devoting more attention to remembering the candidates’ statements (M\5.63) than to deciding on the best candidate (M\4.65), F(1,76)\4.21, p\.05. Others’ expertise. Participants rated the amount of knowledge they thought their group had about each of the five topic areas addressed by the candidates. Ratings for each of the five topics were made on a ten-point scale ranging from 0 (very little knowledge) to 9 (very much knowledge). A 2]2]2 (Task Set]Expertise Salience]Topics) mixed factorial ANOVA revealed a main effect of topics, F(1,76)\ 60.99, p\.0001. As intended, participants rated their group as having more knowledge about the taken topics (M\6.68) than the free topics (M\5.49). The topics effect did not vary with the level of expertise salience, F(1,76)\2.00, ns, suggesting that subjects accurately inferred others’ knowledge both when their expertise was made explicit on the College Life Questionnaire and when it was not. Free Recall Two independent coders, who were blind to each subject’s experimental condition, recorded the code for each item of candidate information correctly recalled. For an informational item to be counted as correctly recalled, the statement had to convey the essence of the correct position advocated on the issue. However, the item did not have to be correctly attributed to the candidate who actually espoused the position. For our purposes, it was more important to determine whether the content of a position was or was not remembered even if the position was attributed to the wrong candidate. The

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proportion of correctly recalled candidate statements within free topics (the two topics not associated with other members’ expertise) and taken topics (the three topics of other members’ expertise) was computed for each subject from each of the two independent codings. The coder reliability estimates were obtained by correlating the measures taken from the two independent codings across the 80 subjects. Because the following analyses used the average of the measures taken from the two codings, these correlations were adjusted (via the Spearman—Brown prophesy formula) to obtain the estimated reliability of the average. The resulting reliability estimates for correctly recalled free topic statements and taken topic statements were .98 each. On average, participants remembered nearly 15 items of candidate information out of the possible 45 items. The proportion of correctly recalled statements was analyzed in a 2]2]2 (Task Set]Expertise Salience]Topics) mixed factorial ANOVA, with the topics factor being a repeated measure. Results showed a main effect of task set : Participants who anticipated collective recall (M\.36) individually remembered more candidate statements than those who anticipated a group decision (M\.31), F(1,76)\9.38,p\.01. This main effect was qualified by a significant two-way interaction between task set and topics, F(1,76)\9.86, p\.01. As suggested by Fig. 2, recall set subjects remembered more statements that were associated with free rather than taken topics, F(1,76)\5.09, p\.05. Conversely, decide set subjects remembered more statements that were associated with taken rather than free topics, F(1,76)\4.78,p\.05. The three-way interaction between task set, expertise salience, and topics was not significant, F(1,76)\0.77, ns, suggesting that subjects made assumptions

F. 2 Mean proportion of correctly recalled candidate statements for Study 1 as a function of task set and topics.

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about what others were likely to remember whether the others’ areas of expertise were made explicit or not.3 These results suggest that group members tacitly coordinate their activities differently depending on the group’s task. Subjects apparently made assumptions about what information other members were likely to remember based on others’ presumed expertise, and adjusted their own strategy to facilitate their group’s task completion. When anticipating a collective recall task, they increased recall diversity by supplementing others’ expected recall. When anticipating a decision task, they increased the amount of shared recall by duplicating what they expected others to know. Presumably, this effect in the decide set indicates that subjects viewed the decision task as primarily cooperative and did not feel the need to be generally well-informed in order to defend their own preferences. Moreover, the recall effects held both for situations where others’ expertise was made explicit and for situations where others’ expertise needed to be inferred from social characteristics. Thus, remote social cues were potent enough to evoke anticipatory efforts to coordinate. Reported Attention Participants remembered information using a strategy that would likely facilitate the group’s task completion. However, did subjects accurately report the information to which they actually attended? Subjects rated their attention to candidate statements in each of the five topics on a 10-point scale ranging from 0 (very little attention) to 9 (very much attention). Subjects’ attention ratings were analyzed in a 2]2]2 (Task Set] Expertise Salience]Topics) mixed factorial ANOVA, with the topics factor being a repeated measure. All of the effects for this analysis were nonsignificant, suggesting that subjects did not accurately report the strategy that they used in anticipation of group task completion. This lack of significance may have occurred because subjects lacked awareness of their strategy use. That is, anticipatory attempts to coordinate may have been an automatic process that occurred without the awareness of group members. Of course, subjects may have simply avoided reporting attention bias because they thought that a ‘‘good’’ subject would not evidence such bias, or they may have felt that attention bias may reflect negatively upon themselves. Alternatively, subjects may not have biased their attention to information but rather biased their retrieval of information when asked to recall. If this was the case, then subjects may be accurate in their reported attention. In sum, these results are consistent with the notion that 3 Because proportions may possess properties that violate the formal assumptions of the general linear model (Cohen & Cohen, 1983), the arcsine transformation (A\2 arcsine Jp) was performed on the proportion of correctly recalled candidate statements. The free recall analyses for Studies 1 and 2 were rerun with the transformed proportions and no changes in the reported results were found.

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anticipatory tacit coordination can occur out of awareness, but they are not definitive evidence for an unconscious process. Participant Expertise To determine if participants’own expertise presented a confound in the data, such that recall set subjects possessed greater expertise in free topics and decide set subjects possessed greater expertise in taken topics, subjects’ own expertise was examined in relation to the independent variables. Participants rated the amount of personal interest and knowledge they had in each of the five topic areas on a 10-point scale ranging from 0 (very little interest, knowledge) to 9 (very much interest, knowledge). A composite measure of subject expertise was created by adding each subject’s interest and knowledge ratings for free and taken topics. Subject expertise was analyzed in a 2]2]2 (Task Set]Expertise Salience]Topics) mixed factorial ANOVA, with the topics factor being a repeated measure. All of the effects for this analysis were nonsignificant, suggesting that participants’ own areas of interest and knowledge were unrelated to the independent variables. To determine whether subjects recalled candidate statements in topics congruent with their own expertise, we examined subjects’ expertise in relation to their free recall. A measure of expertise bias was created by subtracting subjects’ expertise in taken topics from their expertise in free topics. Likewise, we created a measure of recall bias by subtracting the proportion of correctly recalled statements for taken topics from that for free topics. A positive bias value would indicate greater expertise or recall for free compared to taken topic statements, whereas a negative bias value would indicate greater expertise or recall for taken compared to free topic statements. The zero-order correlation between subjects’ expertise bias and their recall bias was not significant, r(80)\.18, ns, indicating that subjects’ report of interest and knowledge in the topic areas was unrelated to their recall. Thus, subjects apparently assumed that others in their group would recall candidate statements correspondent with their areas of expertise, however subjects themselves did not do so. This result suggests an interesting paradox : if every member of a group engaged in such a strategy of tacit coordination, the group interaction would be uncoordinated. STUDY 2 The results of Study 1 suggest that group members anticipate other members’ likely task contribution and adjust their own behavior to facilitate their group’s task completion. When members anticipate collective recall, they remember information that they expect others will not remember. In this way, the group can maximize its collective recall output. Conversely, when members anticipate a group decision, they duplicate others’ expected recall. We have suggested that this duplication of recall may occur when members perceive the decision-making task as cooperative and facilitate preference agreement among members by focusing on commonly recalled information.

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Thus, consensus pressures seem to promote a common focus. In Study 2, we manipulated the amount of agreement required by the group task to determine whether consensus pressures predispose subjects to focus on presumably common information. As in the first study, university students individually read descriptions of three hypothetical candidates for student body president with the expectation that they would interact in a five-person group. However, in the second study, they expected either to decide by unanimity rule on the best candidate, to decide by majority rule on the best candidate, or to discuss the candidates before reaching a final private decision. Before reading the candidate statements, participants reviewed bogus questionnaires ostensibly completed by the other four group members. These questionnaires were designed to suggest that the others collectively were ‘‘experts’’ on three of the five topics covered in the candidate descriptions. Others’ expertise was explicitly indicated on the questionnaire.4 After reading the candidate statements, subjects unexpectedly recalled candidate statements individually for 6 min. Free recall was coded for statements associated with free and taken topics. If subjects focus on information that they think will be widely shared in order to facilitate agreement, then increasing pressures to agree should increase the recall of common information. In other words, unanimity rule participants should show the strongest bias toward remembering information that they think others will also remember. Because majority rule allows for some disagreement within the group, these subjects should show less bias toward remembering taken topic information. Lastly, participants who are merely asked to discuss the candidates with other members have the least pressure to agree with each other, and should thus be least biased toward remembering taken information. However, discuss-only participants may still have a desire to agree with others in order to make the interaction go smoothly or to validate their opinions (Festinger, 1950). Therefore, these participants may also be predisposed to duplicate others’ expected recall. Method Subjects and Design Sixty-six introductory psychology students at Miami University participated in partial fulfillment of a research experience requirement. The design of the study was a Decision Rule (discuss-only vs majority vs unanimity)]Topics (free vs taken) mixed factorial with the topics factor being a repeated measure. Six subjects were suspicious of the manipulations and so their data were excluded from the analyses presented here, leaving a total of 60 subjects.5 The subjects 4 Because there were no differences between the implicit and explicit expertise salience conditions in Study 1, we chose only one level for the second study. The explicit condition is conceptually a more potent manipulation; subjects do not have to make an inference about others’ anticipated expertise. Therefore, we chose the explicit condition for Study 2. 5 Suspicious subjects were detected in the same manner as in Study 1. Also, we reanalyzed the data for all measures with the six suspicious subjects included in the analyses. None of the results changed as a consequence of adding these subjects.

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were assigned to experimental conditions randomly with the restriction of maintaining equal sample sizes in each of the three experimental conditions defined by decision rule.

Materials and Procedure The same candidate profiles and explicit version of the College Life Questionnaires were used from Study 1. The procedure was identical to Study 1 with the exception that decision rule was manipulated instead of task set and expertise salience. Participants were reminded of their anticipated group task once before and once after perusing others’ College Life Questionnaires. Both unanimity rule and majority rule participants anticipated making a collective choice. Participants in the unanimity rule condition were told that every member of their group would be required to agree for the group to reach a decision. It was emphasized that no member could disagree with the final group decision. The majority rule subjects were told that only a majority of members in their group would be required to agree with the group decision for the preferred candidate, therefore some disagreement would be allowed. Discuss-only participants were asked to discuss their opinions regarding the best candidate to get a better feeling for the candidates. In this condition, the experimenter stressed that their group did not have to agree on the best candidate. These subjects anticipated indicating their candidate preference on a private ballot after discussion.

Results and Discussion Manipulation Check Decision rule. After the free recall task, participants were asked to report how much their group was required to agree by indicating 0 (not at all), 1 (a majority must agree) or 2 (all must agree). All participants correctly remembered the decision rule instructions except for two participants in the discussonly condition who incorrectly indicated that majority agreement was required. To assess whether we successfully manipulated subjects’ desire to agree with other group members, they were asked to rate how much they wanted members of their group to agree with one another and how much they wanted to agree with most of the others in their group. Ratings were made on a 10-point scale ranging from 0 (very little) to 9 (very much). For the following analyses, we used a composite agreement measure consisting of the average of the two ratings because of their conceptual relatedness and their positive correlation, r(58)\.79, p\.0001. A one-way between subjects ANOVA revealed a decision rule main effect, F(2, 57)\9.96, p\.001. Unanimity rule subjects (M\6.58) reported wanting more agreement than discuss-only subjects (M\4.15), F(1, 57)\18.67, p\.0001. Also, majority rule subjects (M\5.93) reported wanting more agreement than discuss-only subjects, F(1, 57)\10.02, p\.001. However, the amount of desired agreement did not differ for majority rule and unanimity rule subjects, F(1, 57)\1.34, ns. In order to determine if we also manipulated subjects’ desire to avoid disagreement with each other, they indicated firstly how concerned they were about the possibility that members of their group would disagree with one another and secondly, how concerned they were about the possibility that they would have a different opinion from others in their group. Ratings were made

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on a 10-point scale ranging from 0 (very little concern) to 9 (very much concern). For the following analyses, we used a composite disagreement measure consisting of the average of the two ratings because of their conceptual relatedness and their positive correlation, r(58)\.70, p\.0001. The one-way between subjects ANOVA yielded a nonsignificant main effect of decision rule (discuss-only\2.00; majority\2.45; unanimity\2.83), F(2,57)\0.64, ns. Therefore, it seems that the decision rule manipulation functioned to change participants’ desire to agree with others in their group and for the group to agree with each other. However, we were unsuccessful at discriminating the desire to agree between the majority and unanimity rule conditions. It appears that all participants wanted agreement within their groups because even the discussion group members reported desiring a moderate amount of agreement. Despite wanting agreement, subjects in all of the decision rule conditions reported little concern over potential disagreement in the group. The lack of a significant decision rule effect for disagreement may reflect a general expectation that disagreement would be minimal and thus members were unconcerned about it. Or, members may have felt that any conflict could be dealt with cooperatively and successfully. Others’ expertise. Subjects’ ratings of their group’s knowledge in the five topic areas were analyzed in a 3]2 (Decision Rule]Topics) mixed factorial ANOVA, revealing a main effect of topics, F(1, 57)\31.01, p\.0001. As intended, participants rated their group as having more knowledge about the taken topics (M\6.40) than the free topics (M\5.45). This main effect suggests that subjects accurately noted others’ areas of expertise. Free Recall Two independent coders, who were blind to each subject’s experimental condition, recorded the code for each item of candidate information correctly recalled. The criteria for identifying correct recall were the same as in Study 1. The proportion of correctly recalled candidate statements associated with free topics and taken topics was computed for each subject from each of the two independent codings. The coder reliability estimates were obtained by correlating the measures taken from the two independent codings across the 60 subjects, and a Spearman—Brown adjustment was made to obtain the estimated reliability of the average. The resulting reliability estimates for correctly recalled free topic statements and taken topic statements were .98 and .99, respectively. On average, participants remembered 13.7 items of candidate information out of the possible 45 items. The proportion of correctly recalled statements was analyzed in a 3]2 (Decision Rule]Topics) mixed factorial ANOVA, with the topics factor being a repeated measure. Results showed a main effect of decision rule, F(2, 57)\4.28, p\.05. Participants who anticipated a unanimity rule (M\.33) remembered more candidate statements than those who anticipated only discussion (M\.26), F(1, 57)\8.42, p\.01. The amount of recall did not

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differ between subjects who anticipated unanimity rule or majority rule (M\.31), F(1, 57)\3.21, p[.05. Also, majority rule and discuss-only subjects did not differ in the amount of recall, F(1, 57)\1.23, ns. This main effect was qualified by a significant two-way interaction between decision rule and topics, F(2, 57)\3.68, p\.05. As depicted in Fig. 3, discuss-only subjects remembered more statements that were associated with taken than free topics, F(1, 57)\6.50, p\.05. However, neither majority rule nor unanimity rule subjects differed in their memory for taken and free topics, F(1, 57)\0.35, ns and F(1, 57)\0.86, ns, respectively. A Tukey HSD test performed on the marginal means for each level of topics revealed that both unanimity and majority rule subjects recalled more free topic statements compared to discuss-only subjects (discuss-only\.23; majority\.32; unanimity\.35), but none of the conditions differed for their recall of taken topic statements (discuss-only\.29; majority\.30; unanimity\.33). These results suggest that group members tacitly coordinate their activities differently depending on the decision rule, but not in the way that we expected. We predicted that subjects anticipating a unanimity rule decision would show the strongest preference for recalling taken over free candidate statements, and those anticipating a majority rule decision or only a discussion of the candidates would show less recall bias toward taken information. Actually, the opposite occurred. Only subjects who anticipated a discussion followed by private choice showed the pattern obtained for the decision-making set in Study 1 (i.e., remembering more taken than free information). In fact, when anticipating group choice under an assigned majority or unanimity rule, subjects showed a trend toward reversing that pattern. We did expect that discussion subjects may remember more taken than free information because,

F. 3 Mean proportion of correctly recalled candidate statements for Study 2 as a function of decision rule and topics.

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as the agreement ratings suggest, such groups still had a moderate amount of desire to agree. However, the results from the majority and unanimity rule conditions are more puzzling and suggestions for their interpretation are offered in the General Discussion. Reported Attention Again, we were interested in whether subjects accurately reported their strategy use in anticipation of group interaction. Subjects’ attention ratings were subjected to a 3]2 (Decision Rule]Topics) mixed factorial ANOVA. All of the effects for this analysis were nonsignificant, suggesting that subjects did not accurately report the strategy that they used in anticipation of group task completion. As in Study 1, this lack of parallelism between recall and reported attention to topic areas suggests that subjects were unaware of, or reluctant to report, their attentional focus in anticipation of group interaction. Participant Expertise As in Study 1, we wanted to determine if subjects’ own expertise was related to the independent variables or to the dependent variable. To this end, we analyzed subject expertise in a 3]2 (Decision Rule]Topics) mixed factorial ANOVA. All of the effects for this analysis were nonsignificant, suggesting that participants’ own areas of interest and knowledge were unrelated to the independent variables. Also like Study 1, the zero-order correlation between subjects’ expertise bias and their recall bias was not significant, r(60)\.18, ns, indicating that subjects’ report of interest and knowledge in the topic areas was unrelated to their recall. GENERAL DISCUSSION Several researchers have noted that, when group members begin working on a collective task, they establish patterns of interaction early and without explicit discussion of how to go about completing the task (Gersick, 1988; Hackman & Morris, 1975). These observations have lead some (e.g., Gersick, 1988) to speculate that the speed with which behavioral patterns emerge stems from members’ preinteraction expectations about the task, themselves and other group members, and the task environment. However, to date there has been little empirical evidence examining the process by which members tacitly coordinate their activities in anticipation of small group task completion. The current studies provide the first demonstration that group members (a) use social cues to form expectations about others’ likely task contributions, (b) are sensitive to perceived differences in task demands, and (c) allocate their own resources to fit with the anticipated actions of others. As shown in Fig. 1, these three components are key ingredients for anticipatory tacit coordination. In Study 1, participants supplemented others’ expected recall when they anticipated a collective recall task, but duplicated others’ expected recall when

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they anticipated a group decision-making task. Presumably, members attempted to maximize the group’s collective recall by remembering information that others likely would not remember, and they tried to facilitate the emergence of a consensus by focusing on commonly recalled information. Study 2 showed that the bias toward duplicating others’ expected recall remained in discussion groups, but was eliminated when a group decision was anticipated and the decision rule (unanimity or majority) was explicitly assigned. Why would participants anticipating a majority rule or unanimity rule decision not show a bias toward recalling taken information as decide set subjects did in Study 1? In retrospect, it seems that the explicit decision rule may have enhanced members’ perceived need for conflict resolution. Without an explicit requirement to agree (decide set subjects in Study 1 and discussonly subjects in Study 2), subjects could focus mostly on similar information as others to make the interaction go smoothly. Conversely, our majority and unanimity rule instructions made it clear to subjects that disagreement in the group must be resolved to meet the rule requirements. These subjects were warned that either no disagreement (unanimity) or only minority disagreement (majority) would be allowed. The explicitly strict requirement to agree may have made it more salient to both unanimity and majority rule participants that they may have to compromise their preference or be prepared to argue their position. Considering more unique (i.e., free topic) information may have been their way to prepare for this argumentation given that conflict resolution is likely best achieved when members are well-informed and can offer novel arguments to persuade others (Vinokur & Burnstein, 1974). Other research supports the idea that anticipated conflict enhances cognitive activity. People who expect a discussion with a disagreeing partner develop persuasive arguments in order to prepare for the anticipated conflict (Cialdini, Levy, Herman, Kozlowski, & Petty, 1976). Also, Levine, Bogart, and Zdaniuk (in press) propose that prospective group members who expect to enter a group with disagreeing members engage in anticipatory cognitive processing to a greater degree when more conflict is perceived, such as when consensus is required. In addition, unanimity rule leads to greater compromise of preference and higher participation rates (Miller, 1989). This research suggests that the amount of agreement required by a group’s task may influence members’ need to engage in cognitive activity, such that the more agreement required (and the less conflict allowed), the more members should prepare for anticipated compromise by formulating arguments. Anticipatory argumentation may result in attention to both common and unique information and a higher amount of recall for both types. In sum, our earlier theorizing suggested that members expecting a cooperative group decision task would recall more presumably common information to facilitate consensus, whereas members expecting a conflictual group decision task would show enhanced recall for unique information in

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anticipation of compromise.6 The discuss-only condition from Study 2 and nonrule decision condition from Study 1 resemble the expected pattern for a cooperative decision, whereas the majority and unanimity decision rule conditions from Study 2 resemble the expected pattern for a conflictual decision. We suspect that an explicit decision rule enhanced the perceived need to resolve possible conflict, leading those anticipating a majority or unanimity decision rule to focus on more (particularly unique) information in preparation for argumentation. As our model suggests, an assessment of the group task as cooperative or conflictual may influence members’ resource allocation. Given the preliminary nature of this research and the early stage of theory development, any explanation for the aforementioned findings will be speculative. The studies presented herein represent building blocks with which to understand tacit coordination processes. Several future directions will help build the wall toward better understanding. Future Directions Part of the difficulty of predicting and explaining group members’ attention to information in anticipation of small group task completion stems from lack of understanding about how group tasks are perceived by members (i.e., the ‘‘task assessment’’ component of the model depicted in Fig. 1). Such understanding is necessary in order to develop an empirically-grounded theory of tacit coordination. In the current investigation, we did not directly assess members’ perceptions of task demands. Obviously, this represents a limitation of our research paradigm in that we were forced to make assumptions about members’ view of their anticipated task and what strategies they judged as useful. Future research should ask group members directly how they perceive the requirements of their anticipated task. However, given that the processes involved in tacit coordination may not be highly deliberate, there is some question as to whether subjects could accurately report their perceptions and strategy use. Efforts to identify how group members perceive the requirements for successfully meeting various task goals is a necessary next step in clarifying anticipatory tacit coordination. In both Studies 1 and 2, participants did not accurately report the information to which their recall suggests they gave more attention. While other explanations for why members did not accurately report their attention to information are possible, we think it is plausible that they were not sufficiently aware of their attentional bias to report it. However, we do not want to suggest that the process of tacit coordination is never a deliberate process. In fact, it seems likely that deliberate attempts to tacitly coordinate collective action 6 Although consensus and compromise seem similar, they are distinctly different. Consensus refers to agreement, whereas compromise is a process by which consensus can be achieved whereby some members must shift their decision preference. Consensus may be obtained without any conflict, whereas compromise implies that conflict exists and must be resolved to obtain agreement.

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may be a step toward explicit coordination. When members are aware of their attempts to tacitly coordinate but these attempts fail or are recognized as risky, they may explicitly discuss coordination strategies. Gersick and Hackman (1990) suggest a number of events that may prompt groups to recognize and change habitual routines—established behavioral patterns that are exhibited automatically and repeatedly over time when a group is faced with similar situations. Conditions such as experiencing failure, group recomposition, task redesign, reaching a milestone, or encountering novelty, may prompt groups to reconsider their habitual routines. Similarly, coordinating tacitly may be an habitual response to preparing for, and working in, groups. Individuals who have worked in many formal and informal groups may form member expectations and react to these expectations without conscious deliberation. However, events such as failure feedback, external interventions (e.g., planning periods), and unfamiliar or complex tasks may increase members’ awareness of their tacit strategies and, thus, lead them to become more explicit in their attempts to coordinate action. Further research may help to identify the factors that mediate the mode of coordination used: tacit coordination or explicit strategy planning (e.g., see Weldon & Weingart, 1993). Placing tacit coordination within a broader context of other coordination modes, such as planning, will enhance the understanding of how members combine and synchronize their efforts. Participants in these studies showed a bias toward remembering information that would help the group reach its anticipated collective goal. However, we do not know if the discussion content of interacting groups would match the recall bias of subjects anticipating group interaction. If we could effectively manipulate or select other members’ social cues in a way to make the examination of discussion content feasible, what outcome would result? The discussion content may reflect the contents of our free recall task in that attempts to remember diverse information would lead to more unique information discussed by the group, whereas attempts to remember similar information as others would lead to more common information discussed by the group. However, a major theme of previous work is that discussion, other things being equal, enhances the recall of commonly known information (e.g., Gigone & Hastie, 1993; Stasser, Taylor, & Hanna, 1989; Stasser & Stewart, 1992; Stasser, Stewart, & Wittenbaum, 1995; Stasser & Titus, 1985; 1987). Therefore, attempts at the individual level to duplicate others’ expected recall might be enhanced during discussion, whereas attempts to enhance the diversity of recall prior to discussion might be attenuated. Lastly, tacit attempts to coordinate collective action may backfire. In Studies 1 and 2, subjects engaged in strategies based on expectations that others would remember information related to their areas of expertise even though subjects’ interests and knowledge were not related to their own recall. This paradox has implications for coordination in interacting groups. If members try to duplicate or complement others’ anticipated actions, and others do not behave as

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members anticipated, then the group may fail to coordinate their information processing. As a simple thought experiment, consider the following case. Three members (A, B, and C) of a group are motivated to maximize diversity of action (as in a collective recall task). There are four classes of subtasks or actions that are important for the collective performance: a, b, c, and d. Based on social cues or prior knowledge of members’ interests and abilities, others expect both A and B to allocate effort to actions in classes a and b and C to allocate effort to actions in class c. Suppose that each member independently follows the tacit coordination rule, ‘‘Do what others are not likely to do.’’ Under this rule for allocation of effort, A and B will give top priority to actions in class d and will be indifferent to actions in classes, a, b, and c. At the same time, the rule will lead C to pursue actions in c and d and avoid actions in a and b. The end result could easily be that actions in d are duplicated and actions in a and b are left undone. In this case, the group would have performed better if everyone followed their own interests and not attempted to coordinate their actions tacitly. An interesting theoretical and applied question is whether, or under what conditions, group members recognize situations in which attempts at tacit coordination are ineffective and either abandon such attempts or allocate time to explicitly coordinate their actions. As suggested above, experiencing failure may be one condition under which members reevaluate their strategy use and either tacitly adopt new performance strategies or opt to explicitly discuss strategy plans. Moreover, tacit coordination may be an important link in understanding group performance. It may be that the degree of sophistication necessary to recognize when tacitly coordinated actions will and will not work is an important characteristic of effective teams who must perform in a constantly changing task environment. Likewise, poor team performance partially may be the result of members’ inability to implement tacit coordination effectively. In this way, understanding the tacit nature of coordination may help us to predict and explain the interaction process and performance of task-oriented groups. REFERENCES Argote, L. (1993). Group and organizational learning curves: Individual, system, and environmental components. British Journal of Social Psychology, 32, 31—51. Berger, J., Conner, T., & Fisek, M. H. (1974). Expectation states theory: A theoretical research program. Cambridge, MA: Winthrop. Berger, J., Fisek, M. H., Norman, R. Z., & Zelditch, M., Jr. (1977). Status characteristics and social interaction. New York: Elsevier. Berger, J., Rosenholtz, S., & Zelditch, M., Jr. (1980). Status organizing processes. Annual Review of Sociology, 6, 479—508. Berger, J., Wagner, D. G., & Zelditch, M., Jr. (1985). Introduction: Expectation states theory: Review and assessment. In J. Berger & M. Zelditch, Jr. (Eds.), Status, rewards, and influence. San Francisco: Jossey-Bass.

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