Use of social knowledge in tacit coordination: Social focal points

Organizational Behavior and Human Decision Processes 123 (2014) 23–33

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Use of social knowledge in tacit coordination: Social focal points Susanne Abele ⇑, Garold Stasser, Christopher Chartier 1 Miami University, Department of Psychology, Patterson Avenue, Oxford, OH 45056, USA

a r t i c l e

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Article history: Received 29 December 2012 Accepted 14 October 2013 Available online 14 November 2013 Accepted by Eric Van Dijk Keywords: Social decision making Tacit coordination Group processes

a b s t r a c t Social focal point theory predicts that, in matching, people search for a shared characteristic that makes one decision option salient whereas, in mismatching, they search for complementary characteristics that make different options salient for each of the coordinating parties. In two studies, participants learned about a partner’s activity preferences and then tried to either match or mismatch choices on a series of pictures that were remotely associated with one of these preferences. Being the same on a relevant preference facilitated matching whereas being different facilitated mismatching. In the second study, participants also used overall perceived similarity to supplement specific trait information. Coordination performance also affected interpersonal impressions: successful matching increased interpersonal attraction whereas successful mismatching did not. These downstream effects were obtained even when participants had considerable prior social information about their partners. Tacit coordination is compared with mimicry and synchrony, and the implications for coordinated team performance are discussed. Ó 2013 Elsevier Inc. All rights reserved.

Introduction Social interdependence theory (Kelley & Thibaut, 1978; Kelley et al., 2003; Thibaut & Kelley, 1959) asserts that the consequences of one’s actions frequently depend on what others do. Two broad categories of interdependencies are those that afford a coordinated solution and those that do not. In coordination, the interacting parties’ interests are correspondent for at least some combinations of choices. Focal points are emergent solutions to coordination problems (Mehta, Starmer, & Sugden, 1994; Schelling, 1960). Although focal points are often characterized as conspicuous, prominent, or salient options in the decision space, we will argue that emergent solutions to coordination problems often depend on the relationship between characteristics of the actors and of the decision options. Even though interests are correspondent, successful coordination can be difficult to achieve, particularly when people cannot or do not explicitly communicate – that is, when coordination is tacit. Whether negotiating traffic, collaborating with colleagues, or completing household chores, coordination is essential to successful interactions. We first review the distinction between matching and mismatching problems (Abele & Stasser, 2008). Next we review the concept of a focal point (Schelling, 1960) as it applies to both matching and mismatching coordination. We then outline a theory

⇑ Corresponding author. E-mail addresses: [email protected] (S. Abele), [email protected] (G. Stasser), [email protected] (C. Chartier). 1 Present address: Ashland University, Department of Psychology 0749-5978/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.obhdp.2013.10.005

of social focal points and summarize the supporting evidence for the theory from existing studies. The current research examined critical features of the theory when applied to repeated interactions in which actors have extensive knowledge about each other. Study 1 examined the proposition that social actors search for useful cues from an array of social information even when they could rely on repeated interactions with feedback to develop coordination. In short, they identify a focal point based on shared social knowledge. The second study contrasted two kinds of social knowledge that could be used in defining focal points: a generalized impression of similarity versus knowledge of a specific trait that is associated with choices on a coordination task. Both studies also address the idea that coordination affects subsequent social knowledge in the form of interpersonal impressions (Abele & Stasser, 2008). In this sense, there is a two-way street between social knowledge and coordination.

Distinction between matching and mismatching Abele and Stasser (2008) distinguished two types of coordination problems (see also, Bramoullé, 2007). Matching problems require actors to choose the same action for successful coordination, such as two friends trying to meet in a mall. Mismatching problems require actors to choose different actions for successful coordination. Past research has used primarily matching games (e.g., Mehta et al., 1994) but mismatching problems are often encountered in life. For example, a cleaning crew is more efficient if members avoid dusting the same desk and domestic

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partners benefit if one, but not both, stop at the store to buy milk on the way home from work. Social knowledge about preferences, attitudes, and past behavior can affect expectations of future behavior. However, the usefulness of social knowledge depends on coordination requirements – whether to match or to mismatch. Focal points as social constructs – social focal point theory When trying to meet a friend in the mall, the fountain in the center of the mall is more likely to be chosen than other options (see Schelling, 1960, for other examples). The fountain is uniquely different from other structural features of the mall (shops, multiple entries and parking lots). However, for many coordination problems, one alternative is not structurally unique from other possibilities. Indeed, if there are two or more fountains in a mall, meeting at a fountain loses its effectiveness as a focal point. Moreover, if trying to mismatch, a uniquely prominent option does not provide a focal point. If two adversaries want to avoid meeting each other at the mall (a mismatching problem), the prominence of the fountain does not provide a focal point. In this case, individuating and shared social knowledge is needed to infer where each is likely and not likely to go in the mall. Whereas matching focal points can be defined by common social knowledge, we claim that mismatching focal points often require common social knowledge (see, Abele & Stasser, 2008, for further elaboration of this argument). By common social knowledge, we mean knowledge that is known by each of the actors, and each is aware that it is commonly known. Additionally, relevant social knowledge can be of two types: group membership or individuating. Group membership information tells whether the actors are members of the same or different social categories (e.g., nationality, political affiliation and gender). To be useful in identifying focal points, category membership needs to inform the expectations of each other’s responses. Individuating information conveys specific information about the actors (e.g., preferences, past behavior, and abilities). In the foregoing example of two adversaries wanting to avoid each other in the mall, suppose one likes to browse in bookstores and the other frequents clothing boutiques. If these inclinations are known to each, a simple strategy for successful mismatching is for each to go to their favorite shops. A fundamental assumption of a theory of social focal points is that actors look for a pattern of social information that satisfies two requirements. First, the information makes one solution to the coordination problem more prominent than other solutions. Second, the social knowledge and the indicated solution are assumed to be common knowledge (see also, Van Dijk, de Kwaadsteniet, & de Cremer, 2009). We summarize the theory in two postulates and one hypothesis.  Trait selection postulate: When faced with a coordination task, people search for relevant social information either in the form of category membership or individuating information about the actors involved.  Relevance postulate: To be relevant, the social information must suggest a strategy (focal point) for solving the coordination problem. Specifically, for the types of binary choice problems used in the subsequent studies, matching social focal points are defined by a shared characteristic of the actors that is associated with the same response expectation. Mismatching social focal points require that the actors are different on a characteristic and that this difference is associated with different response expectations.  Social focal point hypothesis: The foregoing postulates lead to the following prediction regarding coordination

performance. Being the same on a relevant trait facilitates matching but not mismatching. Conversely, being different on a relevant trait facilitates mismatching but not matching. The results of de Kwaadsteniet, Homan, van Dijk, and van Beest (2012) provide preliminary evidence for the specific predictions in the social focal point hypothesis. They showed that when students were told to match another’s choice of three colors (pink, blue, or yellow), they tended to choose the stereotypical color preference for their gender when they thought they were of the same gender (e.g., males chose blue and females chose pink). When they thought they were of opposite genders, they chose the stereotypical neutral color of yellow (Study 1).2 Conversely, when participants were told to mismatch color choices (Study 2), their choices were distributed almost equally across the three colors when they thought the partner was of the same sex. However, when they thought the partner was of the opposite sex, they choose the color stereotypically associated with their own gender (presumably because they thought the partner would do likewise resulting in different choices). These results illustrate two points. First, when no other information is available, people will use category membership (gender in this case) to identify a solution to a one-shot coordination problem. Second, this attempt will be successful when behavioral expectations derived from the category memberships (gender stereotypes in this case) make a solution to the coordination problem prominent. This one-shot color selection task simulates a situation in which strangers having limited knowledge of each other have to coordinate only once. However, most social contexts present a more complex situation. First, actors often know several things about each other and most of this knowledge is not useful for solving tacitly any particular coordination problem. Thus, to be successful in solving a novel coordination problem, each actor must search for relevant social information and assume that the other will do the same. Second, coordination problems often repeat, if not exactly then thematically. Thus, actors can often rely on past experience to guide their current behavior. If the current problem repeats a theme of an already solved problem, this experiential information can suggest a focal point for the current problem. We extended the work by de Kwaadsteniet et al. (2012) in four ways. First, participants completed a series of coordination problems with feedback. Second, the instances in the series repeated a theme. Thus, as with many coordination problems faced in social life, our participants could develop a coordination strategy by trial and error and thereby avoid searching for and using social knowledge. One question that we wanted to address is whether people use individuating social information to identify focal points when they can develop coordinated behavior without doing so. Third, before completing the coordination tasks, our participants knew several things about their partner, namely the social category information of gender plus individuating information consisting of preferences for various activities (five in the first study and ten in the second study). Fourth, the information relevant to forming behavioral expectations for the coordination task was always one item of the individuating information, not the more salient social category information (gender). 2 Although the overall pattern of results across the studies reported in de Kwaadsteniet et al. (2012) support the patterns predicted by the social focal point hypothesis, some of the findings are not as strong as one would expect if searching for social cues were a dominant strategy in solving coordination problems. For example, in Study 1, only 56% of participants choose the sex-typical choice when they were told they were playing with a same-sex partner. Thus, they would have matched on the sex-typical choice only 31% of the time with another randomly selected same-sex partner. Given that gender was the only social information available in this study and they had one chance to match, one would expect active use of social information to yield a much higher success rate.

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Successful matching and mismatching and interpersonal impressions Coordination is a social activity and we have argued that focal points are frequently defined partly by social information. Abele and Stasser (2008) showed that coordination is a social activity in another sense – coordination success and failure affect interpersonal impressions. Partners are seen as smarter after, than before, successful coordination. Moreover, their results further underscored the difference between matching and mismatching tasks. Partners were rated as more similar to oneself and more likeable after successful matching than after successful mismatching. However, the participants in Abele and Stasser (2008) had limited prior information about each other. Thus, these effects could be described as impression formation because the participants had virtually no prior information about others before the task and their impressions had to be based primarily on how they performed collectively on the coordination task. An open question is how coordination success modifies impressions when partners already have prior knowledge about each other. Indeed, social focal points are based on prior knowledge and some of that knowledge may become salient because of its relevance to the coordination problem. For these more information rich situations, the following two hypotheses are considered. The relevant trait hypothesis predicts that ratings of similarity and liking will increase when the partners are the same on the relevant trait and decrease when they are different. The rationale for this hypothesis is that the coordination task makes the partner’s standing on a task-relevant trait salient and the standing on this trait will determine whether impressions of similarity and liking increase or decrease over the course of the task. That is, whether the coordination task is matching or mismatching does not matter but the standing on the relevant trait does; having to coordinate simply underscores the similarity or dissimilarity on the relevant trait. The coordination requirement hypothesis asserts that the type of coordination – matching versus mismatching – affects similarity and liking ratings. Consistent with Abele and Stasser’s (2008) findings, this hypothesis asserts that choosing the same option(s), as successful matching requires, increases the perception of being alike and subsequently liking. In contrast, successful mismatching does not increase interpersonal liking and perceived similarity because it requires making different choices.

Study 1 We created a coordination situation, in which the coordinating parties had knowledge about each other in the form of preferences for various activities. The preference for one of these activities was relevant to the ensuing coordination task although the participants were not forewarned of its relevance. One purpose of Study 1 was to see whether participants spontaneously identify and use prior information about their partner when it can potentially define a focal point. In order to test the social focal point hypothesis, participants attempted to match or to mismatch the choices of a partner who was ostensibly either the same or different on a relevant trait. Another purpose was to test how prior knowledge may moderate the effects of coordination on interpersonal impressions. Recall that the relevant trait hypothesis presumes that the coordination task draws attention to the relevant trait and makes salient whether the partner is the same or different. The coordination requirement hypothesis states that matching conveys a sense of being alike and liking whereas mismatching does not. In order to test these ideas, participants rated their partners on a number of

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traits prior to playing the coordination game (but after learning their activity preferences) and again after the game was completed. Method Participants and design One hundred twenty undergraduate students (57 females and 63 males) from Miami University participated. They were randomly assigned to a 2 (Coordination Requirement: Match versus Mismatch)  2 (Relevant Trait: Same versus Different) factorial design. Two of these conditions – namely, matching when the same on the relevant trait and mismatching when different on the relevant trait – created a correspondence between the trait information and the coordination requirement. The trait information was noncorrespondent with the coordination requirement in the two remaining conditions. In the main design stated above, a participant’s partner was simulated by programming the computer to respond on the first trial assuming that the participant would choose the option associated with her activity preference (hereafter referred to as a compliant partner). When the trait information was noncorrespondent with the task, an equally realistic option would be to program the simulated partner to play the option associated with its preference (noncompliant partner). This distinction is elaborated below. To assess whether this procedural variation in simulating partner play made a difference in coordination success, an additional sixty-one participants (25 females and 36 males) participated in two external control conditions. As was explained above, the difference between a compliant and non-compliant partner would only be apparent when there is noncorrespondence between trait and task. Hence, the two external control conditions were: (a) matching with a noncompliant partner whose preference on the relevant trait was different from the participant’s preference, and (b) mismatching with a noncompliant partner whose preference on the relevant trait was the same as the participant’s preference. Procedure and task Between four and eight participants were invited to each session. Upon arrival, participants were seated in individual cubicles of a computer lab. All instructions were given on the computers. Participants reported demographic information (e.g., sex, year in school, major) and then completed an Activity Preference Questionnaire (APQ) eliciting their preference for each of five pairs of activities: indoor or outdoor exercise, arts or sports events as entertainment, studying in the library or in the dorm/apartment, drinking coffee or juice/pop, and going to the bars or the movies on a Saturday night. After completing their APQ, participants learned the responses of their partners to the APQ items. Whereas participants thought that they were playing with a partner, the ostensible partner’s choices were programmed so that the partner had either indicated the same preference as the participant on the relevant trait (same on relevant trait) or the other preference (different on relevant trait). To assess possible extraneous effects of the content of the relevant trait, entertainment preference (arts versus sports) was the relevant trait for half of the participants and exercise preference (indoor versus outdoor) was relevant for the remaining half in each of the conditions. Overall, the feedback indicated that the partner was the same sex as the participant and that they agreed on two of the five preference items. Participants then received the instructions for the coordination task via the computer terminal. The experimental task was a twoperson coordination game with two decision options. On each trial, the two players chose simultaneously one of two options without

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knowledge of the other player’s choice. The two options consisted of two pictures. There were two picture sets of ten pairs. The first picture set consisted of pairs in which one was associated with an arts event and the other was associated with a sports event. Examples of pairs in this set include: a Grammy trophy versus a sports trophy; an open-air concert pavilion versus a sports arena; and a microphone versus a basketball. The second picture set consisted of pictures associated with outdoor or indoor exercise activities. Examples of pairs in this picture set include: skaters in an indoor rink versus inline skaters on an outdoor trail; an indoor soccer game versus an outdoor soccer game; and a swimmer in an indoor pool versus a swimmer in a lake. As mentioned, two different picture sets were included to ensure that results were not linked to the particularities of the specific pictures. Participants saw pictures from one of these sets in their game. The relevant trait from the APQ was the entertainment preference for participants who were given the first picture set and the exercise venue preference for participants who were given the second picture set. Under matching requirements, players won 1 US$ on each trial that they chose the same picture and lost 50 cents if they chose different pictures. Under mismatching requirements, players won 1 US$ on each trial that they chose different pictures, and lost 50 cents on each trial that they chose the same picture as their partner. If players failed to coordinate on a pair, the pair was presented to them again later. Thus, the participants ultimately experienced coordination success on all ten pairs of pictures. The measure of coordination performance is based on the number of coordination failures experienced en route to the ten successes. Feedback after each trial reported the partner’s choice. Also included were the amounts won by the participant on that trial and a cumulative summary of the number of trials on which they had chosen the same or different picture depending on whether they were trying to match or mismatch, respectively. In the experimental conditions, the partner’s decisions were modeled by having the simulated partner play the first trial assuming that the participant would opt for the picture associated with her preference. The simulated partner continued that strategy on subsequent trials unless there were three consecutive failures at which point the computer would switch. Thus, the simulated partner played a compliant and stable strategy of staying in the event of one or two consecutive failures in the experimental conditions. In the two external control conditions, a noncompliant stable strategy was modeled. The simulated partner initially chose the option associated with the simulated partner’s reported preference on the APQ feedback. As in the model of the compliant strategy, the simulated partner continued that strategy on subsequent trials unless there were three consecutive failures, at which point the computer would switch. As pointed out previously, this distinction between compliant and noncompliant strategy only made a difference when the standing on the relevant trait was the same under mismatching or different under matching. Thus, the external control conditions were only implemented for these two conditions. Before and after completing the coordination task, participants rated their partners on a series of items that measured interpersonal liking, similarity to self, and intelligence. All items were answered on a nine-point rating scale, with ‘1’ indicating strong disagreement with a statement and ‘9’ indicating strong agreement. Intelligence was a composite of responses to the following items: ‘‘My partner is smart’’ and ‘‘My partner is intelligent’’ (a = .87 for pre-task and a = .94 for post-task ratings). Similarity was measured with the following two items: ‘‘My partner is similar to me’’ and ‘‘My partner and I have much in common’’ (a = .88 for pre-task and a = .88 for post-task ratings). Rated interpersonal liking consisted of the responses to: ‘‘I would like my partner if we were to get to know each other’’ and ‘‘I would enjoy spending time

with my partner’’ (a = .84 for pre-task and a = .91 for post-task ratings). Our hypotheses regarding person perceptions made the same predictions for ratings of liking and similarity and these measures were highly correlated, r(N = 120) = .78. Thus, for the analyses, we averaged the similarity and liking ratings to form an aggregate interpersonal attraction measure. This measure had high internal consistency – a = .88 for pre-task and a = .92 for post-task ratings. The initial ratings were obtained after participants had received their partners’ responses to the APQ and read the instructions and the rules of the coordination game but had not yet played the game. The final interpersonal ratings were taken after the coordination task was completed and the final performance feedback given. Results Coordination performance The social focal point hypothesis predicts that being the same on a relevant trait facilitates matching whereas being different on a relevant trait facilitates mismatching. Conversely, when the trait information was not congruent with the required coordination, we expected coordination failures on the early trials and improving coordination over trials as participants adjusted their choices based on feedback. We first examined performance on the first trial which occurs before the participant received any information about the partner’s play. Then, we examined performance across trials. First-trial performance strongly supports the social focal point hypothesis. When the partners’ standings on the relevant trait corresponded to the coordination requirement (i.e., same/match and different/mismatch), 85% succeeded whereas, when the relevant trait and coordination requirement did not correspond, only 49% succeeded, v2(1, N = 120) = 17.07, p < .0001. Note that 50% success is expected by chance. To assess performance over time, we analyzed coordination failures in two trial blocks – first five trials versus the remaining trials. Recall that participants had to coordinate successfully on each of 10 picture pairs. If they failed on a pair, it was presented later. Thus, the number of trials in the second trial block varied depending on the number of times that picture pairs were repeated. Because the number of trials varied, we analyzed the proportion of trials that were coordination failures in each trial block. Note that chance performance on this proportion measure would be .5 and perfect performance would be zero. Proportion of coordination failures were analyzed in a 2 (coordination requirement: match versus mismatch)  2 (relevant trait: same versus different)  2 (trial block) ANOVA treating the trial block as a repeated measures factor.3 As expected, there is a significant interaction of coordination requirement and standing on the relevant trait, F(1, 116) = 49.74, p < .0001, g2 = .26.4 Also, there is a significant decrease in the proportion of coordination failures from the first (M = .19) to the second (M = .04) trial block, F(1, 116) = 40.45, p < .0001, g2 = .30. However, both of these effects are qualified by a three-way interaction of coordination requirement, standing on relevant trait, and trial block, F(1, 116) = 19.81, p < .0001, g2 = .15. As illustrated by Fig. 1, the interaction of coordination requirement and standing on the relevant trait is much more pronounced in the first than in the second trial block. The simple interaction in the first trial block is strong, F(1, 116) = 59.56, p < .0001, g2 = .34, but only marginally significant in the second trial block, F(1, 116) = 3.65, p = .056, g2 = .03. Decomposition of the interaction 3 The coordination performances were nearly identical for the two picture sets (indoor versus outdoor exercise venue and sports versus cultural entertainment). Thus, we omit picture set as a factor in the reported analyses. 4 Reported eta-squared values are partial.

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Fig. 1. Proportion of coordination failures for matching and mismatching coordination by relevant trait congruency in Study 1.

in the first trial block showed that partners who were the same on the relevant trait experienced virtually no matching errors (M = .06) but several mismatching errors (M = .23), F(1, 116) = 14.92, p < .0001, g2 = .11. Conversely, partners who were different on the relevant trait experienced proportionally fewer mismatching errors (M = .07) than matching errors (M = .39), F(1, 116) = 48.76, p < .0001, g2 = .30. Using the external control groups, we also examined the effects of a compliant and noncompliant partner on coordination success. We analyzed the proportion of coordination failures in a 2 (Coordination Requirement: Match versus Mismatch)  2 (Partner Strategy: Compliant versus Noncompliant)  trial block ANOVA, treating trial block as a repeated measures factor. In this design, participants in the matching condition were different on the relevant trait and those in the mismatching condition were the same on the relevant trait. That is, compliant (playing the option consistent with the partner’s preference) and noncompliant (playing the option consistent with one’s own preference) strategies are distinguishable only when the standing on the relevant trait does not correspond to the coordination requirement. Because trait information was incongruent with the coordination task for all conditions in this design, performance was poor in the first trial block (M = .30) and improved with experience in the second trial block (M = .06), F(1, 118) = 92.09, p < .0001, g2 = .44. There is virtually no overall effect of partner strategy, F(1, 118) = 0.35, p = .56, and the interaction of partner strategy with coordination requirement is not significant, F(1, 118) = 2.16, p = .14. Thus, participants did no better or worse playing with a compliant as compared to a noncompliant partner. The difference between the two partner strategies emerged in the relative frequencies that the participants chose the picture associated with their preference. Against a noncompliant partner when trait information and coordination requirement are incongruent, one is forced to choose a preference-inconsistent choice in order to coordinate. Thus, participants played the option consistent with their preferences in the noncompliant control conditions on only 17% of the trials (as compared to 84% for the corresponding experimental conditions with a compliant partner).

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Interpersonal attraction. We predicted one of two possible patterns of results for interpersonal attraction as measured by ratings of similarity and liking. The relevant trait hypothesis states that the coordination task makes salient a relevant trait. If partners are the same on the relevant trait, the hypothesis asserts that attraction would increase but not when they were different. The coordination requirement hypothesis predicts that matching, but not mismatching, increases interpersonal attraction. We conducted a 2 (coordination requirement match versus mismatch)  2 (relevant trait: partners same or different)  2 (time: pre- versus post-play) ANOVA treating the time factor as a repeated measure. There are main effects of relevant trait, F(1, 116) = 4.96, p < .03, g2 = .04, and time, F(1, 116) = 15.96, p < .0001, g2 = .12. The partner was rated as more similar and likeable (M = 6.12) when s/he expressed the same preference on the relevant trait than when expressing a different preference (M = 5.66). However, inconsistent with the relevant trait hypothesis, the effect of relevant trait did not interact with time, F(1, 116) = 1.34, ns. In support of the coordination requirement hypothesis, the main effect of time is qualified by a significant coordination requirement by time interaction, F(1, 116) = 5.87, p < .02; g2 = .05. When matching, rated attraction was greater after (M = 6.18) than before (M = 5.57) the task, F(1, 57) = 16.98, p < .0001, g2 = .23. However, ratings of attraction did not change significantly when the coordination task involved mismatching (Mpre = 5.84; Mpost = 5.99), F(1, 59) = 1.55, ns. Compliance and impressions We noted above that the strategy of the simulated partner did not affect coordination efficiency, but the noncompliant strategy forced participants to play choices inconsistent with their activity preferences. One would expect that interpersonal impressions would also be affected and they were. Overall, compliant partners were rated as more similar and likeable (M = 5.91) than noncompliant partners (M = 5.40), F(1, 118) = 5.39, p < .03, g2 = .04. More telling are the changes from pre- to postgame. Participants expressed more positive attraction for compliant partners after the game (M = 6.10) than before (M = 5.73), F(1, 60) = 6.15, p < .02, g2 = .09. Participants who experienced a noncompliant partner did not change their attraction ratings, F(1, 60) = 0.06, ns. Partner strategy also affected perceptions of intelligence. Overall, partners were rated as somewhat smarter after (M = 7.04), than before (M = 6.79), completing the coordination task, F(1, 118) = 4.63, p < .04, g2 = .04. More to the point, however, this time affect was qualified by an interaction with partner strategy, F(1, 118) = 8.25, p < .005, g2 = .06. When the partner followed a compliant strategy, the partner was seen as smarter after (M = 7.30), than before (M = 6.69), completing the coordination task, F(1, 60) = 15.86, p < .0002, g2 = .21. Rated intelligence of noncompliant partners did not change over the course of the coordination task, F(1, 60) = 0.32, ns. Discussion

Partner perceptions Smartness. Abele and Stasser (2008) found that perceptions of partner’s smartness were affected by coordination success but not by the type of coordination required. In the current study, participants repeated instances of failures so that ultimately everyone experienced 10 coordination successes. Moreover, as illustrated in Fig. 1, coordination improved with experience and the incidents of failures was low in the second trial block. Thus, we expected that there would be an increase in perceived partner smartness from pre- to post-play. Indeed, a 2 (coordination requirement)  2 (relevant trait) X 2 (time: pre- versus post-play) ANOVA revealed only a main effect of time, F(1, 116) = 28.22, p < .0001; g2 = .20. Mean smartness ratings increased from 6.80 to 7.31 on a 9-point scale.

Results of Study 1 support the social focal point hypothesis. Social knowledge about the interacting partner improves coordination when a relevant social trait is available and the partners’ standing on the relevant trait corresponds to the requirement of the coordination problem. Being the same on the relevant trait reduced coordination failures under matching, whereas being different on the relevant trait reduced coordination failures under mismatching. This pattern was prominent in the first five trials before participants gained experience working with their partner. When social information was not helpful, participants adjusted their choices based on feedback and performance after the first five trials and coordination was nearly perfect in all conditions on the final block of trials. This pattern of performance means that they

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quickly learned to generalize from one picture pair to the next based on the theme (indoor versus outdoor exercise venues for half of the participants and sports versus cultural entertainments events for the other half). It also shows that participants in the study did not need to use social information to perform moderately well on the coordination task. Nonetheless, when social information was helpful, they clearly used it to avoid coordination failures. In regards to the effects of coordination performance and coordination requirement on feelings of similarity and liking, our findings support the coordination requirement hypothesis: successful matching increased perceived similarity and liking ratings whereas successful mismatching did not. This pattern of effects on partner perceptions extends the findings of Abele and Stasser (2008) in that participants in the current study had other social knowledge about their partner prior to the coordination task. That is, the effects of matching and mismatching on partner impressions do not occur solely when there is no prior information about the partner.

Study 2 One feature of the first study is that the prior social knowledge about the partner was neutral in terms of overall similarity. The partner matched the participant on gender and two of the five activity preferences, regardless of condition. In the second study, we provided a stronger test of social focal point theory by increasing the amount of prior information and creating partner profiles that were distinctly similar or dissimilar to a participant’s profile of preferences. Increasing the amount of social information makes identifying the relevant trait more difficult (thus, examining the robustness of the trait selection postulate) and manipulating overall similarity provides a readily available heuristic as a substitute for searching a specific trait that is relevant – namely, ‘‘similar partners will act as I do and dissimilar partners will not.’’ Thus, in Study 2, we manipulated perceptions of overall similarity, which was operationalized by varying the degree of overall preference agreement between the partners on the APQ, independent of whether they agreed or disagreed on their preference most relevant to the coordination task.

Coordination performance In terms of coordination performance we consider two versions of the social focal point hypothesis. The relevant trait version of our social focal point hypothesis is the one considered in the first study. This hypothesis presumes that people identify and use the relevant trait even when it is only a small part of what is known about the other. It predicts being the same on a relevant trait will facilitate matching and being different on a relevant trait will facilitate mismatching. We also considered an alternative version of the social focal point hypothesis based not on identifying a relevant trait but on knowing that actors are globally similar or dissimilar. When actors have an impression of overall similarity or dissimilarity, they might take a cognitively frugal approach and use the overall impression rather than searching for information about the partner’s standing on a relevant trait. Hence, this version of the social focal point hypothesis assumes that impressions of overall (dis)similarity affect expectations of a partner’s response tendencies. That is, having the impression that the partner is similar leads to the expectation that she will respond similarly. Conversely, an overall impression of dissimilarity fosters the expectation that the partner will respond differently. If one were to use overall similarity as a coordination cue in our experimental task, an overall

impression of similarity would facilitate matching whereas an overall impression of dissimilarity would facilitate mismatching.5

Person perceptions Study 1 and Abele and Stasser (2008) showed that successful matching increases the perception of being similar to one’s partner and expressing more liking for the partner. These social inclusion effects do not follow successful mismatching. Additionally, coordination success, whether matching or mismatching, increases the impression that one’s partner is smart. However, in Abele and Stasser (2008), partners had little prior information about each other and thus had to form their impressions mostly based on the task performance. In Study 1, we found the same pattern when partners had prior information but the information was designed to convey neutral impressions of similarity. In Study 2, participants received more prior information that conveyed the impression that their partner was either predominantly the same or different in their preference profile (high or low preference agreement). Thus, we expected that participants would see their partner as highly similar or dissimilar at the onset of the task. Against this backdrop of high or low overall preference agreement, we examined whether matching coordination would impact perceptions of similarity and liking.

Method Participants and design One hundred eighty-seven undergraduate students (113 females and 74 males) from Miami University participated. They were randomly assigned to a 2 (Coordination Requirement: Match versus Mismatch)  2 (Similar on Relevant Trait versus Dissimilar on Relevant Trait)  2 (Overall Preference Agreement: High versus Low) factorial design.

Procedure and task Procedure and task were both identical to the ones used in Study 1, with two exceptions. First, the Activity Preference Questionnaire was extended from five to ten activity items. Second, we used only one trait (entertainment preference) as the relevant trait. The additional items were preferences for: computer (Mac versus PC); living arrangements after graduation from college (in the country versus in a big city); an elective course (photography versus scuba diving); a leisure activity (reading a book versus watching TV); and a community service activity (Habitat for Humanity versus Big Brother/Sisters). The greater number of preference items allowed us to vary overall preference agreement independent of standing on the relevant trait. In the high preference agreement condition, participants learned that their partner chose the same option as they did on eight out of ten items. Conversely, participants in the low preference agreement condition chose a different option than their partner on eight out of ten items. Whether partners chose the same or different option on the relevant trait (preference for sports or cultural/arts event for entertainment) was varied within the overall preference agreement factor. That is, expressing the same or different preference on the relevant trait counted as one of the eight agreements or disagreements in the manipulation of overall preference agreement. 5 The heuristic not only works for the task we used but has considerable ecological validity. For example, if partners know that they are highly similar across a wide range of traits or preferences, it is more likely that they would have the same, rather than different, response inclinations in most situations demanding coordinated responses.

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Results Coordination performance The relevant trait version of the social focal point hypothesis states that people search for trait information that can be used as a coordination cue. As in Study 1, this hypothesis would be supported by an interaction of standing on the relevant trait and coordination requirement. In this study, we also considered an alternative version of the hypothesis which assumes that people do not search for a specific relevant trait when they think they are generally similar or dissimilar. Rather they use overall similarity to form an expectation of having the same or different response tendencies. In our task, this hypothesis would be supported by a preference agreement by coordination requirement interaction. Coordination performance was the proportion of coordination failures en route to coordinating successfully on all 10 pairs of pictures. First-trial performance was examined using log-linear analysis of coordination requirement (match versus mismatch), relevant trait (same versus different), preference agreement (high versus low) and performance (success versus failure). Two interactions emerged as significant: coordination requirement by relevant trait by first trial performance, LL(1, N = 187) = 18.37, p < .0001, and coordination requirement by preference agreement by first trial performance, LL(1, N = 187) = 5.26, p = .022. The first interaction is consistent with the results of Study 1. When the partners’ standings on the relevant trait corresponded to the coordination requirement (i.e., same/match and different/mismatch), 82% succeeded whereas, when the relevant trait and coordination requirement did not correspond, only 56% succeeded, LL(1, N = 187) = 15.22, p < .0001. The second significant interaction suggests that at least some participants also used overall similarity of partner as a cue. When the partners’ overall similarity corresponded to the coordination requirement (i.e., similar/match and dissimilar/mismatch), 76% succeeded whereas, when overall similarity and coordination requirement did not correspond, only 61% succeeded, LL(1, N = 187) = 5.22, p = .022. These first-trial patterns were also observed in performance over trials. A 2 (coordination requirement: match versus mismatch)  2 (relevant trait: same versus different)  2 (preference agreement: high versus low)  2 (trial block) ANOVA yielded support for both hypotheses. The relevant trait version of the social focal point hypothesis is supported by a significant relevant trait by coordination requirement interaction, F(1, 179) = 35.79, p < .0001, g2 = .17. The overall similarity version of the social focal point hypothesis was supported by a significant preference agreement by coordination requirement interaction, F(1, 179) = 17.91, p < .0001, g2 = .09. However, both of these two-way interactions are qualified by a three-way interaction with trial block. As is evident in Fig. 2, coordination improved with experience as revealed by a sizeable trial block main effect, F(1, 179) = 106.54, p < .0001, g2 = .37. In addition, the relevant trait by coordination requirement by trial block interaction is significant, F(1, 179) = 30.06, p < .0001, g2 = .14. Likewise, the preference agreement by coordination requirement by trial block interaction is significant, F(1, 179) = 11.36, p < .001, g2 = .06. Inspection of Fig. 2 suggests that the effects of the experimental conditions are, as expected, most pronounced in the first trial block and relatively small in the second trial block where performance improved with experience and feedback. Simple interaction analyses support this visual impression. In the first trial block, both the relevant trait by coordination requirement and the preference agreement by coordination requirement are significant, F(1, 179) = 65.47, p < .0001, g2 = .27 and F(1, 179) = 29.29, p < .0001, g2 = .14, respectively. In the second trial block, neither interaction is significant, F(1, 179) = 1.84, p = .17 and

Fig. 2. Proportion of coordination failures for matching (top panel) and mismatching coordination (bottom panel) by relevant trait congruency and overall preference agreement in Study 2.

F(1, 179) = 1.61, p = .20. Thus, our decomposition of the two-way interactions is based on the first trial block results. In support of the idea that participants used relevant trait information when it was congruent, being the same on the relevant trait lead to proportionally fewer matching errors (M = .06) than mismatching errors (M = .27), F(1, 179) = 43.77, p < .0001, g2 = .20, whereas being different on the relevant trait resulted in proportionally fewer mismatching errors (M = .09) than matching errors (M = .25), F(1, 179) = 29.20, p < .01, g2 = .14. In support of the use of overall similarity, partners who had high preference similarity made proportionally fewer matching errors (M = .12) than mismatching errors (M = .27), F(1, 179) = 23.15, p < .0001, g2 = .12. Conversely, low preference agreement resulted in proportionally fewer mismatching errors (M = .09) than matching errors (M = .20), F(1, 179) = 14.35, p < .0001, g2 = .07. These results suggest that participants were using two kinds of information as coordination cues: one was overall similarity as indicated by the number of shared preferences and the other was the standing on a highly associated trait. When both kinds of social information were congruent with the coordination requirement, participants experienced virtually no coordination failures. For example, high overall preference agreement and being the same on the relevant trait resulted in nearly perfect matching coordination (only 3% of unsuccessful trials in the first trial block: cf., Fig. 2). In contrast, when the both types of social information were incongruent with the coordination demands performance was relatively poor. For instance, high overall preference agreement and being the same on the relevant trait resulted in very poor mismatching performance in the first five trials (38% of unsuccessful trials where 50% is chance performance).

Partner perceptions Ratings of partner were analyzed using a 2 (coordination requirement)  2 (relevant trait)  2 (preference agreement)  2

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(time) ANOVA with the time factor represented as a repeated measure. When decomposing interactions involving time into simple effects of time, we partitioned the data and computed new error terms for each simple effect of time (see, Howell, 2010). Smartness. In Study 1, we observed an overall increase in rated smartness of the partner and expected to see the same pattern in this study. Mean smartness ratings increased from 6.90 before the coordination task to 7.57 after completion of the task, F(1, 179) = 66.28, p < .0001; g2 = .27. We also obtained a main effect of preference agreement in that partners were rated as smarter (M = 7.38) when they agreed on most of the preferences items than when they disagreed (M = 7.11), F(1, 179) = 5.02, p < .03, g2 = .03. No other effects in the model were significant. Interpersonal attraction. As for Study 1, we combined the similarity and liking measures in a composite attraction measure (a = .90 for pre-task and a = .87 for post-task ratings). We were interested in two types of effects. First, the manipulation of preference agreement should have affected overall attraction ratings. The main effect of preference agreement is strong, F(1, 179) = 239.44, p < .0001, g2 = .57. Partners were perceived as more similar and likeable (M = 7.16) when preference agreement was high than when it was low (M = 4.75). There is also a main effect of time with an increase in rated attraction over time, F(1, 179) = 18.13, p < .0001, g2 = .09. The main effect of time is qualified by the interaction of preference agreement with time, F(1, 179) = 85.47, p < .0001, g2 = .32. When agreement was high, interpersonal attraction decreased from before (M = 7.35) to after (M = 6.96) the task, F(1, 83) = 15.95, p < .0001, g2 = .16. Conversely, when agreement was low, interpersonal attraction increased from before (M = 4.25) ratings to after the task (M = 5.25), F(1, 96) = 79.21, p < .0001, g2 = .45. Thus, working on the coordination task moderated perceptions of similarity and liking due to overall preference agreement on the APQ. Nonetheless, the effects of the preference agreement were still quite strong after the task, F(1, 179) = 92.60, p < .0001, g2 = .34. Thus, the manipulation of perceived similarity by proportion of agreement on the preference items was highly efficacious. We were also interested in the effects of the task, especially the type of coordination required on interpersonal attraction. We obtained significant main effects of coordination requirement, F(1, 179) = 4.36, p < .05, g2 = .02; of time, F(1, 179) = 18.13, p < .0001, g2 = .09; and of relevant trait, F(1, 179) = 4.51, p < .05, g2 = .02. Overall, rated attraction was slightly higher for the matching (M = 5.95) than the mismatching task (M = 5.79), after (M = 6.04) than before completing the task (M = 5.69), and when partners were the same (M = 6.13) rather than different (M = 5.63) on the relevant trait. As in Study 1, the coordination requirement hypothesis was supported but the relevant trait hypothesis was not. That is, the relevant trait by time interaction was not significant, F(1, 179) = 1.20, p = .27, whereas the coordination requirement by time interaction was, F(1, 179) = 7.12, p < .01, g2 = .04. Interpersonal attraction increased for the matching task from 5.65 to 6.24, F(1, 88) = 28.43, p < .0001, g2 = .24. However, there was no significant increase for the mismatching task, F(1, 91) = 1.11, ns. Discussion Social information can be global and convey an overall impression of how similar another person is to oneself, or it can be specific and suggest a cue relevant to the social situation. The impact of the combination of global and specific social information on coordination performance was one interest of the second study. Another goal was to see whether and to what degree initial

impressions of similarity moderate or eliminate the impact of coordination on the perceptions of the interacting partner. We examined two versions of the social focal point hypothesis. The first version is based on the idea that people look for specific trait information that is useful as a cue for coordination. The second version presumes that people use impressions of overall similarity as a cue. Even though participants were given considerable information about their partners, most of which was irrelevant to the task, they experienced fewer coordination failures in matching when the partner was the same on the relevant trait and fewer failures in mismatching when the partner was different on the relevant trait. This finding implies that participants identified and used the relevant social trait out of a wide range of information. However, another finding is that participants with a high overall preference agreement had fewer coordination failures in matching, whereas participants with a low overall preference agreement had fewer coordination failures in the mismatching task. These findings together imply that people can and do use both the standing on the relevant trait and the overall preference agreement as coordination cues. The degree of preference agreement had strong effects on perceptions of partner similarity, likability and intelligence. Specifically, high agreement on the preferred activities resulted in the partner being seen as similar to the participant, likeable and intelligent. These findings are consistent with the general idea that similarity leads to attraction (Byrne & Griffit, 1973). More specifically, our preference items resembled the activity items that Jamieson, Lydon, and Zanna (1987) used to manipulate similarity. They found that high agreement in preference for activities leads to judging another more positively on both social and intellectual desirability. Pertinent to our interests is that the coordination task modified these perceptions. Replicating the findings from Study 1, we found an increase in rated intelligence from before to after the task. In regards to perceptions of social closeness as measured by perceived similarity and liking, the effects of the coordination task are more complex. The experience of working together moderated the extreme impressions invoked by the preference agreement manipulation. Perceived similarity and liking increased in the lowpreference agreement conditions, accompanied by the corresponding decreases in the high preference agreement conditions. In addition to this overall moderating effect, we found that participants’ ratings of social closeness to their partner increased over the course of the matching task but changed little as a result of performing the mismatching task. This finding replicates the results of Study 1 and Abele and Stasser (2008) even when participants had considerable information about their partners and already saw their partners as similar or dissimilar to themselves. General discussion The current work builds on prior research on coordination by matching versus by mismatching and extends it by examining the role of social knowledge in coordination. The extension is twofold. Firstly, we examined how social knowledge affects coordination efficiency and secondly, we explored whether prior knowledge moderates or eliminates the effects of coordination performance on subsequent impressions of one’s partner. Social focal point theory We predicted and showed that social knowledge interacts with coordination requirement on coordination performance. When people are trying to coordinate their actions, they search for information that suggests what others might do. This information is

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often social in nature and is associated with the social attributes of the actors. We summarized our ideas about how social information affords coordination solutions in social focal point theory. The theory presumes that actors attempt to identify relevant social information that suggests the action expected of others in the situation (Trait Selection Postulate). Moreover, for the social information to be useful, the coordinating parties’ relative standing needs to map onto the requirements of the coordination task (Relevance Postulate). Mehta et al. (1994) introduced a similar idea. When it is common knowledge that people are trying to coordinate tacitly, they search for a rule that will identify a unique focal point. The coordination solution identified by this rule is said to have Schelling salience. This label refers to Schelling’s (1960) observation that people are often able to coordinate their choices at well above base rates predicted by their individual preferences or action inclinations. Social focal point theory asserts that Schelling salience is often based on the attributes of the actors. Our task simulated situations in which social actors have equal knowledge about each other and there is nothing in the context that confers privilege or uniqueness to one of the actors. Moreover, the relevant social knowledge was presumably common knowledge. The social focal point hypothesis that we tested incorporates a relevance criterion that distinguishes matching and mismatching tasks. The rule for matching is simple: choose an action that is associated with an attribute that is shared among the actors. The rule for mismatching is somewhat more cognitively demanding: each actor chooses an action that is associated with an attribute that they do not share with the other actors. Our findings yielded patterns of coordination efficiency that are consistent with the use of such rules. The use of relevant trait information in these studies is particularly noteworthy. Our coordination task could be mastered reasonably well by trial and error as evidenced by the rather quick improvement over trials when social information was not helpful. Thus, completion of the task did not demand using social information. Moreover, the relevant trait information was remotely associated with the coordination task, embedded in other social information, and presented before the coordination task was described. In Study 2, we also found evidence for a more general rule for matching based on overall similarity: if others are similar to me, choose the option associated with my preference (as they are expected to choose as I would choose). The version of this general rule for mismatching is: if others are dissimilar to me, choose the option associated with my preference (as the others will likely choose something different). When none of these rules work, the participants in our studies seemingly engaged in a trial and error process. When neither of these rules fit the coordination requirements, coordination success on the first trial was at chance levels (50%) whereas, when both rules fit, participants succeeded 89% of the time on the first trial. The trait selection and relevance postulates together imply that people search for social information that they presume is common knowledge and will yield an effective rule for coordinating. The rules incorporated in our social focal point hypothesis are based on patterns of attributes among all actors, but there are situations in which the focal point is likely to be based on the attributes of one actor. For example, de Kwaadsteniet and van Dijk (2010) showed that people defer to the preference of a higher-status person. The higher-status person chooses her preference and the others assume that she will. We suggest that the higher-status person was focal and, when it was known that she preferred one of the options, that option became the focal point for matching. There are other ways that a person can become focal. For example, some of Schelling’s (1960) examples suggest that an ill-informed person can be focal. Consider two actors, A and B. A knows B’s preference but B does not know A’s and this asymmetry of social information

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is common knowledge. A simple rule is that B will choose his preference and A will select accordingly. Notice that this special-case rule works whether the goal is to match or mismatch. Decision timing is another way of making one actor focal. If the decision environment is structured so that actors decide at different times, decision order can provide a cue for both matching and mismatching. In our experimental task and in many situations, actors decide simultaneously without knowledge of others’ choices. However, in some situations, individuals may decide sequentially and, even though this order of deciding is common knowledge, they may not know each other’s choices until all have decided. Knowing the order of deciding but not the actual decisions until all have decided is often referred to as pseudo-sequential decision-making – pseudo-sequential because the actors are as ignorant of others’ choices as if they were deciding simultaneously. Nonetheless, in coordination problems, pseudo-sequential decisions seemingly underscore the social nature of the interaction (Abele, Bless, & Ehrhart, 2004). Moreover, first-movers seemingly have an advantage in that they act as though others can observe their choices when they cannot, and others seemingly presume that first-movers will choose accordingly (e.g., Cooper, DeJong, Forsythe, & Ross, 1993; Weber, Camerer, & Knez, 2004). Thus, we suggest that the first-mover is focal and the matching rule is: first-mover chooses her preference, and subsequent deciders choose the alternative that they expect the first-mover to choose. Our point is that coordination rules can either be based on commonly-known patterns of attributes among actors or on the attributes of a focal actor. Another point, which is implicit in many of the examples, is that it is often easier to identify and implement a rule for matching than for mismatching. Social consequences We considered several hypotheses in regards to how the social knowledge could affect interpersonal impressions after the coordination task. Based on Abele and Stasser (2008), we proposed the coordination requirement hypothesis, which states that matching increases a sense of being alike and being likeable. We found additional empirical support for this hypothesis. We also examined the possibility that the effects of tacit coordination on partner perceptions would be limited to situations in which partners had little prior information about each other (as in Abele & Stasser, 2008) or the information was neutral (as in the current Study 1). However, this does not appear to be the case. Even when partners had social knowledge about each other that conveyed rather extreme impressions of similarity or dissimilarity, the coordination requirement hypothesis was supported. Successful matching increased similarity ratings and interpersonal liking and successful mismatching did not. Co-regulation According to Semin and Cacioppo’s social cognitive model (2007, 2008), there are three forms of co-regulation, mimicry, synchrony and coordination. The current work looked at the last type of co-regulation. The very basic form is mimicry, which happens largely on a non-conscious level (Chartrand & van Baaren, 2009). The current research on matching versus mismatching coordination has parallels to mimicry and synchrony in that doing the same as opposed to different things fosters rapport and liking. For instance, Chartrand and Bargh (1999) found that people like a person who mimics them more than one who does not. This effect is bilateral. Mimicking another person also leads to greater liking and rapport of that mimicked target (LaFrance, 1979). Furthermore, facial mimicking increases people’s prosocial behavior (Stel, van Baaren, & Vonk, 2008), and even being mimicked engenders more prosocial

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behavior (Van Baaren, Holland, Kawakami, & van Knippenberg, 2004). Moreover, it has been shown that doing a physical action in synchrony fosters liking (Hove & Risen, 2009), and cooperation (Wiltermuth & Heath, 2009). Despite the common theme that doing the same thing engenders positive interpersonal feelings, there are a number of differences among these paradigms. In both mimicry and synchrony, the target action is an embodied action – meaning it has to do with either the body or the face. Moreover, in the mimicry and synchrony paradigms, the interacting agents serve as visual stimuli for each other. This makes the other person, who mimics or moves in synchrony, more salient. In tacit coordination, the target action is often not embodied but is a deliberate choice when actors are explicitly interdependent. That is, the actors are aware that their payoff for choosing a particular alternative depends partly on what the others choose. An open question is whether the interpersonal impressions engendered by these various forms of co-regulation are mediated by similar psychological processes. If so, it may be that tacit coordination involves deliberation and social awareness but that the downstream effect on interpersonal impressions is not deliberative. For example, are people aware that they are more favorably disposed to a partner after successful matching than they are after successful mismatching or are these effects largely sub- or pre-conscious? Similarly, is the increase in judged intelligence after successful coordination, be it matching or mismatching, reasonable given the simplicity of coordination tasks that we have used in our studies or is this impression of enhanced intelligence an automatic response to successful coordination?

Coordination in teamwork Coordination is a fundamental concern in teamwork (Steiner, 1972). Many collaborative tasks are inherently mismatching tasks. Loan managers completing mortgage applications, janitors cleaning a building and scholars coauthoring a paper often need to execute different actions for successful and efficient completion of the task. One implication of the current work could be that coordinated teamwork often underscores differences between the team members. As a consequence, liking and interpersonal affect between the group members would not be promoted. This implication is in stark contrast to what is often expected in teamwork: success breeds group cohesion, strong in-group identification, and enhanced motivation and enthusiasm. However, the evidence for these presumed effects of success is mixed. For example, Mullen and Cooper (1994) concluded, based on their meta-analysis, that team success increases task commitment but not interpersonal liking. It is also possible that the implications for mismatching coordination could unfold differently in teams. Team tasks are typically multifaceted and successful performance often involves a mix of matching and mismatching behaviors. The downstream effects of successful mismatching on impressions of similarity and liking are often small or nonexistent (as in the current studies; see also, Abele & Stasser, 2008). Applying these results to team tasks that involve a mix of matching and mismatching coordination suggests, albeit speculatively, that success on the mismatching components would have little net effect on impressions but that success on the matching components would tend to increase team cohesion. Thus, the aggregate effect of successful completion of a series of matching and mismatching coordination tasks would be to enhance a sense of social inclusion. Additionally, teamwork is often explicitly coordinated whereas our studies have examined tacit coordination. Another open question is whether the downstream effects of coordination that we have observed depend on the tacitness of the process. If roles

and tasks are explicitly assigned or negotiated, would matching lead to interpersonal attraction whereas mismatching would not? Addressing questions about how the current findings scale up to in situ teamwork is limited by the nature of the task that we used. Even though teams often face situations that repeat themes, the options are less constrained and more fluid than in the task that we used. Also, the use of a ‘‘programmed partner’’ in our studies means that the developing coordination was somewhat easier than is often faced in real life contexts. It was easier for at least two reasons. First, by virtue of the program being slow to change after an instance of coordination failure (waiting for three consecutive failures), repeating cycles of failure in which both partners followed a ‘‘fail-switch’’ strategy were largely avoided. Second, the program never inadvertently made a mistake in choice and, thereby, avoided sending misleading signals that could disrupt established coordination. Conclusions The challenge in tacit coordination is to find a shared selection rule that identifies a focal point. Structural focal points are salient solutions to coordination problems, which suggest themselves from the decision set (e.g., chose the biggest or brightest option if matching; see Schelling, 1960, for many examples of structural focal points). The theory of social focal points integrates the concept of focal points from behavioral economics with social categorization theory. The theory identifies several ways that matching and mismatching coordination problems can be resolved by coordination rules that make use of social cues. The findings suggest that people spontaneously use social information if it is relevant (trait selection postulate) and useful (relevance postulate) given the type of coordination required. Moreover, even in the context of considerable social partner knowledge, successful matching coordination promotes social inclusion whereas successful mismatching does not. Acknowledgment We gratefully acknowledge financial support from the National Science Foundation (Grant BCS-0339158 awarded to the first author). References Abele, S., Bless, H., & Ehrhart, K. M. (2004). Social information processing in strategic decision making: Why timing matters. Organizational Behavior and Human Decision Processes, 93, 28–46. Abele, S., & Stasser, G. (2008). Coordination success and interpersonal perceptions: Matching versus mismatching. Journal of Personality and Social Psychology, 95, 576–592. Bramoullé, Y. (2007). Anti-coordination and social interactions. Games and Economic Behavior, 58, 30–49. Byrne, D., & Griffit, W. (1973). Interpersonal attraction. Annual Review of Psychology, 24, 317–336. Chartrand, T., & Bargh, J. (1999). The chameleon effect: The perception–behavior link and social interaction. Journal of Personality and Social Psychology, 76, 893–910. Chartrand, T., & van Baaren, R. (2009). Human mimicry. Advances in Experimental Social Psychology, 41, 219–274. Cooper, R., DeJong, D. V., Forsythe, R., & Ross, T. W. (1993). Forward induction in the battle-of-the-sexes games. The American Economic Review, 83, 1303–1316. de Kwaadsteniet, E. W., Homan, A. C., van Dijk, E., & van Beest, I. (2012). Social information as a cue for tacit coordination. Group Processes and Intergroup Relations, 15, 257–271. de Kwaadsteniet, E. W., & van Dijk, E. (2010). Social status as a cue for tacit coordination. Journal of Experimental Social Psychology, 46, 515–524. Hove, M., & Risen, J. (2009). It’s all in the timing: Interpersonal synchrony increases affiliation. Social Cognition, 27, 949–960. Howell, D. C. (2010). Statistical methods for psychology. Belmont: Wadsworth. Jamieson, D. W., Lydon, J. E., & Zanna, M. P. (1987). Attitude and activity preference similarity: Differential bases of interpersonal attraction for low and high selfmonitors. Journal of Personality and Social Psychology, 53, 1052–1060.

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