The effects of top management team size and interaction norms on cognitive and affective conflict

Journal of Management 1997, Vol. 23, No. 4.495516

The Effects of Top Management Team Size and interaction Norms on Cognitive and Affective Conflict Allen C. Amason University of Georgia

Harry J. Sapienza University of South Carolina

There is mounting evidence that effective top management teams engage in cognitive conflict but limit affective conflict. Cognitive conflict is task-oriented disagreement arising from differences in perspective. Affective conflict is individual-oriented disagreement arising from personal disaffection. This study of 48 TMTs found that team size and openness were positively related to cognitive conflict. While team size was also associated with greater affective conflict, when teams had high levels of mutuality, greater openness led to less affective conflict. The findings have implications for improving strategic decision making through the use of conflict.

Built upon a rich tradition, a new agenda of strategic decision making research is beginning to emerge (Eisenhardt Jr Zbaracki, 1992; Rajagopalan, Rasheed & Datta, 1993). This new agenda focuses on the normative issues at “the heart of strategic management” by examining the antecedents of strategic decision-making effectiveness (Eisenhardt & Zbaracki, 1992, p. 33). Many have observed that the various components of strategic decision-making effectiveness do not peacefully coexist (Cosier & Rose, 1977; Nemeth & Staw, 1989; Sqhweiger & Sandberg, 1991). Thus, a central issue for research is how such outcomes as decision quality, consensus, and affective acceptance can be realized simultaneously (Amason & Schweiger, 1994; Eisenhardt & Zbaracki, 1992). The problem is that many of the factors that enhance decision quality appear also to undermine consensus and affective acceptance. At the same time, factors that enhance consensus or positive affect appear to also curtail decision quality. A dilemma results where teams must choose between pursuing higher quality decisions which cannot be implemented versus implementing lower quality decisions (Gaenslen, 1980; Guth & MacMillan, 1986). For example, researchers have noted Direct all correspondence 30602.

to: Allen C. Amason, Terry College of Business, The University of Georgia, Athens, GA

Copyright 0 1997 by JAI Press Inc. 0149-2063 495

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that team heterogeneity can have both positive and negative effects on strategy making (e.g., Cho, Hambrick & Chen, 1994; Priem, 1990). While heterogeneity improves decision quality, it can also make decision implementation more difficult (Nemeth & Staw, 1989). Conflict may be the key to unlocking this conundrum (Amason, Thompson, Hochwarter & Harrison, 1995; Jehn, 1994; Tjosvold, Dann & Wong, 1992). In a recent article, Amason and Schweiger (1994) explain that while conflict is essential for effective strategic decision making, it is also a dangerous force that can wreck a team’s efforts to share information and reach consensus. The traditional view has been that conflict obstructs decision making (Hickson et al., 1986; Mintzberg, Raisinghani & Theoret, 1976). More recently, however, researchers have found that conflict can improve decision quality and enhance understanding (Schweiger, Sandberg & Ragan, 1986; Schwenk, 1990). Amason and Schweiger (1994) argue that conflict can be both beneficial and detrimental because conflict appears in different forms. Cognitive conflict is task-oriented and arises from differences in judgment or perspective. Affective conflict is emotional and arises from personalized incompatibilities or disputes (Brehmer, 1976; Jehn, 1994; Pinkley, 1990). The premise of our study is that the ability to manage these two types of conflict is a key to effective strategic decision making. Cognitive conflict appears to improve strategic decision making because it facilitates the exchange of information among the top management team members. Team members disagree because their different perspectives cause them to “see different environments” (Mitroff, 1982, p. 375). Yet, these differences and the cognitive conflicts that they produce can enhance decision quality and shared understanding. Bantel and Jackson, for instance, argue that complex decisions are best solved by teams with “a variety of skills, knowledges, abilities and perspectives” (1989, p. 109). Schweiger and colleagues (1986, 1989) also found that interaction techniques that force team members to disagree and debate the merits of different alternatives produce superior decisions. Thus, cognitive conflict appears to be altogether functional with respect to the quality of strategic decisions. Affective conflict, on the other hand, can produce suspicion, distrust, and hostility among team members (Brehmer, 1976; Guetzkow & Gyr, 1954; Faulk, 1982). By so doing, affective conflict can obstruct the exchange of information between team members and erode the commitment team members have for one another and for their decisions. Teams whose members avoid one another share little information and produce poor decisions. Team members who are not committed to their decisions are unenthusiastic about seeing those decisions implemented (Guth & MacMillan, 1986). Finally, team members with residual anger and bitterness may be unwilling to work together in the future (Korsgaard, Schweiger & Sapienza, 1995). Thus, affective conflict appears to be altogether dysfunctional with respect to team member attitudes toward the strategic decision making process. The crux of the dilemma is that these two types of conflict can be aroused by similar conditions. Thus, as teams stimulate cognitive conflict, they may inadvertently trigger affective conflict. As a consequence, well-intentioned efforts to improve decisions may produce undesirable results. For example, research on deciJOURNAL OF MANAGEMENT.

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sion-making techniques, such as Dialectical Inquiry (Mason, 1969) and Devil’s Advocacy (Cosier, 1978) has shown that these techniques promote critical evaluation of alternatives and thorough consideration of assumptions (Schweiger et al., 1989; Schwenk, 1990). This research has also shown, however, that these techniques can produce bitterness and lingering resentment. Research has also shown that techniques that can reduce these negative feelings by restricting disagreement tend to reduce decision quality (Cosier & Rose, 1977; Schweiger et al., 1986; Schwenk, 1990). Research on the Nominal Group (Hegedus & Rassmussen, 1986; Frankel, 1987) and Consensus (Schweiger et al., 1986, 1989) techniques, for instance, suggests that while these techniques produce fewer negative feelings, they also produce less creative decisions. Similarly, some contend that greater TMT heterogeneity can improve decision quality by applying divergent perspectives to complex problems (Hoffman, 1959; Nemeth, 1986). The evidence supports this contention. Bantel and Jackson (1989) found that innovative banks were run by heterogeneous TMTs and Eisenhardt and Schoonhoven (1990) found heterogeneity contributed to the success of new firms. Heterogeneity, like the techniques described above, produces conflict (Eisenhardt & Schoonhoven, 1990; Wagner, Pfeffer & O’Reilly, 1984). This conflict often yields higher quality decisions. At the same time, however, researchers have noted that this conflict can be harmful. Smith et al., (1994) observed that heterogeneous teams may require greater coordination and monitoring. Similarly, Cho, Hambrick, and Chen observed that heterogeneous teams are hampered by dissimilar “perspectives and vocabulary” (1994, p. 13). According to Priem (1990), these dissimilarities are helpful when they provide a diverse pool of perspectives from which creative decisions can emerge. They become harmful, however, when they obstruct communication and undermine a team’s ability to act collectively. Thus, TMTs face a dilemma. To improve decision quality, teams must encourage cognitive conflict by building heterogeneity and by fostering confrontational interaction. Of course, this conflict may undermine the harmony and commitment among the team members. Must teams sacrifice decision quality to gain team member satisfaction? Does pursuing consensus reduce decision quality by eliminating all but those few alternatives that can be readily agreed upon? Recent conceptual and empirical research of these questions suggests not (Amason et al, 1995; Amason, 1996; Jehn, 1994, 1995; Tjosvold, Dann & Wong, 1992). These studies suggest that when conflict remains task-focused, not only does decision quality improve but so does team member commitment and satisfaction. When conflict becomes individual-oriented, however, decision quality, commitment, and team member satisfaction decline. Thus, TMTs that can stimulate cognitive conflict while avoiding affective conflict are likely to produce high quality strategic decisions while also building the commitment, coordination, and trust necessary to effectively implement those decisions (Jehn, 1994; Mohr & Spekman, 1994; Tjosvold, Dann & Wong, 1992). TMTs that avoid all conflict or that are unable to avoid affective conflict are likely to produce poor decisions that attract little consensus and that undermine team member satisfaction. JOURNAL OF MANAGEMENT,

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Of course, managing conflict is easier said than done. Researchers have found that cognitive and affective conflict are often correlated (Cosier & Rose, 1977; Jehn, 1994; Pinkley, 1990), and little is known about how one can be encouraged while the other is restrained. Thus, we designed this study to answer the question: How can top management teams gain the benefits of cognitive conflict while avoiding the costs of affective conflict? While we do not directly examine decision-making effectiveness, we do examine the antecedent conditions of cognitive and affective conflict, which have been shown to be key elements of strategic decision-making effectiveness. Gaining the Benefits, Avoiding the Costs Researchers have found that teams are often unable to separate cognitive and affective conflict. Torrance (1957), one of the earliest researchers to make the distinction between task-related and person-related conflict, expressed doubt that decision makers could recognize the difference between the two. In a review of the social judgment theory-based conflict research, Brehmer (1976) explained that even purely cognitive disagreements may arouse affective conflict because decision makers can never fully justify their preferences. As a consequence, distrust and suspicion develop between decision makers who hold different opinions. As distrust and suspicion creep into the process, cognitive differences can produce “full-scale emotional conflict” (1976, p. 986). This explanation is supported by the findings of Baron, who reports that, “often, what starts as a rational exchange of opposing views deteriorates into an emotion-laden interchange . . . in which strong negative feelings are aroused” (1984, p. 272). The same pattern can be seen in the research on Devil’s Advocacy and Dialectical Inquiry. These techniques were designed to stimulate cognitive conflict; that decision quality improves with their use suggests that at least some of the conflict that they provoke is, in fact, cognitive. However, that these techniques also lower commitment and satisfaction among team members suggests that they may inadvertently provoke affective conflict as well. Similarly, distilling a decision from the diverse perspectives of a heterogeneous team will inevitably involve conflict (Mitroff, 1982). While some of this conflict is cognitive and contributes to decision quality, the decreased commitment and cohesion often observed in heterogeneous teams suggests the presence of some affective conflict as well. Indeed, Jehn (1994) found that the type of conflict a team experienced mediated the relationship between the team’s value similarity and its overall performance and member satisfaction. This all suggests that, once engaged in a decision, decision makers have trouble distinguishing cognitive disagreements from personal assaults. As a result, when faced with different opinions and perspectives, decision makers often respond as if they are being personally attacked. By so doing, they incite affective conflict. Once aroused, the affective conflict tends to escalate, reducing the effectiveness of the decision-making process. As Baron states, “conflict can quickly JOURNAL

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move from a constructive mode, capable of generating positive outcomes, to a destructive one, much more likely to yield negative results” (1984, p. 272). In spite of this, however, we believe that effective top management teams are able to consciously promote cognitive conflict and, at the same time, limit affective conflict. Eisenhardt (1989) reported that the most effective TMTs in her study were those that engaged in the “aeration” of opinions without arousing acrimony and political gamesmanship. These teams actively used their differences and disagreements to produce more thorough and well thought out decisions. Yet, their disagreements remained task focused and did not degenerate into personalized, affective conflict. Tjosvold, Dann, and Wong (1992) also found that effective teams were those that could openly discuss their opposing views without undermining their cooperative orientation and collective focus. Finally, Amason and colleagues (1995) reported that successful strategic decisions resulted when TMTs used conflict to stimulate discussion and creativity, but were able to keep their disagreements from provoking anger and personal animosity. The conflict a team experiences is likely a function of its structural and social context. As discussed earlier, team heterogeneity and interaction processes can both influence conflict. In addition, Eisenhardt and Schoonhoven (1990) argued that collective tenure among a team’s members can affect their ability to focus on issue-related differences without getting bogged down in personal disagreements. Eisenhardt and Bourgeois (1988) found that the presence of a powerful CEO can affect conflict by forcing team members to resort to covert coalition building to accomplish their purposes. Clearly, there are a number of factors that can affect the level and type of conflict a team can experience. We chose to focus on three such factors: team size, openness, and mutuality. Team size was chosen because it parsimoniously represents a team’s structural and compositional context. As Hambrick and D’Aveni state, “at a basic level, the resources available on a team result from how many people are on it” (1992, p. 1449). Openness was chosen because it captures the propensity of teams to share information; communication and information exchange are keys to the success of group effort and task accomplishment (Barnard, 1938; Galbraith, 1973). Based on the literature on communication in organizations (Redding, 1972) we define openness as the TMT’s propensity to tolerate, encourage, and engage in open, frank expression of views. Mutuality captures the extent to which diverse members of a team feel joint responsibility and share goals. We define mutuality as the extent to which TMT members believe that they are mutually accountable and responsible and will share in the consequences of their strategic decisions. Teams with greater mutuality are analogous to the “cooperating” groups in Deutsch’s experiments (1949). Deutsch created mutual responsibility and accountability in “cooperating” experimental groups by compensating (with grades) members according to the individual and collective outcomes of members; he also created “competitive” experimental groups by differentially rewarding group members according to their output relative to others in the group. By focusing on these constructs, we can examine the composition, dynamics, and goal structure of team effort. JOURNAL

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Hypotheses The Effects

of Size, Openness,

and Mutuality

on Cognitive

Conflict

For many researchers, team size is synonymous with cognitive capability (Halebian & Finkelstein, 1993). Larger teams generally have greater cognitive resources than smaller teams (Bantel & Jackson, 1989). At the same time, larger teams have greater potential for dissimilarity because their members are more diverse and represent more specialized skills and opinions (Bantel & Jackson, 1989; Smith et al., 1994; Wiersema & Bantel, 1992). For this reason, Eisenhardt and Schoonhoven (1990) argued that larger teams are better equipped to process large amounts of diverse information than smaller teams. This cognitive diversity should produce cognitive conflict. Thus, we offer our first hypothesis: Hla: The larger the TMT, the more cognitive conjlict the TMT will experience.

Consistent with social identity theory (Tajfel, 1979; Turner, 1982), members of TMTs respond to what others expect of them. Thus, the norms that teams establish affect how they will interact (Bettenhausen & Murnighan, 1985). Specifically, when team members feel they are free to honestly air their views and challenge the status quo, they are more likely to express their concerns and opinions. Cosier (1978), Schwenk (1990) and Schweiger et al. (1986, 1989) all found that cognitive conflict could be induced through techniques that legitimize disagreement. These techniques established norms of open and frank discussion. To increase taskoriented disagreement, Janis suggested that teams establish norms that “give high priority to airing objections and doubts” (1982, p. 262). Finally, Faulk states that “one of the necessary conditions for the emergence of task [cognitive] conflict is an atmosphere in which all group members can freely express their opinions” (1982, p. 1124). We expect norms of open and frank discussion to lead to greater cognitive conflict. Thus, we advance the following hypothesis: Hlb: The greater the TMT’s openness, the more cognitive conji!ict the TMT will experience.

The extent to which TMT members believe they share in the consequences of their strategic decisions should also affect the level of cognitive conflict they experience (Deutsch, 1968; Tjosvold & Deemer, 1980). In its extreme form, mutuality may manifest itself as a desire to accommodate other team members for the “good’ of the team. In such groups, individuals may exercise restraint rather than fight for positions or views which could be construed as self-serving. Indeed, mutuality has at times been associated with less conflict (Ring & Van de Ven, 1989) and less thorough examination of alternative solutions (Janis, 1982). Deutsch (1949), too, found that groups in which rewards were shared were less apt to question the views of team members than were those in which individual rewards for superior performance were offered. This all suggests that greater mutuality JOURNAL OF MANAGEMENT,

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will be associated with low levels of cognitive conflict. Thus, we offer the following hypothesis: Hlc: The greater the mutuality among TMT members, the less cognitive conflict the TA4T will experience.

In addition to these direct relationships, we expect that the joint configuration of openness and mutuality will affect the level of cognitive conflict a TMT experiences. More specifically, we expect the effects of openness on cognitive conflict to increase as mutuality increases. When mutuality is low, TMT members are less likely to be responsive to the efforts or views of others on the team. In such cases, even when team members are willing to share openly and frankly, others on the team may be less inclined to truly “engage” one another in strategic decision making. On the other hand, when mutuality is high, if openness leads to cognitive conflict, TMT members will see it as their joint responsibility to contribute to the dialogue and to more carefully evaluate others’ views and to offer views of their own. If team members do not trust that their interests are mutually linked, they will be suspicious of the motives behind one another’s criticisms (Brehmer, 1976). Tjosvold and Deemer (1980), for instance, report that competitive group members tend to perceive cognitive disagreements as threats and, therefore, respond to them with avoidance and rigidity. Team members who believe that criticism of their ideas is in some way insincere are likely to respond with cynicism or anger, rather than with cognitive debate. So, the ability to encourage cognitive conflict through the development of open interaction norms will depend in part upon the degree to which mutuality has been established. Thus, we offer the following hypothesis: Hld: Mutuality and openness will interact such that the greater the level of mutuality, the stronger the positive association between openness and cognitive conflict. The Efsects

of Size, Openness,

and Mutuality

on AfSective

Conflict

We expect that team size will influence affective conflict in much the same way that it influences cognitive conflict. All other things being equal, TMTs with a greater number of members will encompass a greater number of divergent feelings, views, and personal goals. As Wiersema and Bantel observed, “large groups have more potential for dissimilarity . ..” (1992, p. 100). This dissimilarity produces many of the cohesional and communicational difficulties often associated with large groups (Shaw, 1981; Smith et al., 1994). As the number of individuals in a group or team increases, the chance of reaching a true consensus will naturally decrease. Further, the difficulty of resolving any one conflict will increase as the number of individuals involved increases. The possibility that further contention will be interpreted as “payback” rather than honest discussion also increases (Tjosvold, 1985). Thus, because larger teams have more potential for dissimilarity and because the ability to resolve conflict diminishes as numbers JOURNAL OF MANAGEMENT,

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rise, affective conflict is likely to occur more frequently in larger teams. Thus, we offer the following hypothesis: The larger the TMT, the more affective H2a: experience.

conflict the TMT will

On the surface, it may seem that openness would increase affective conflict. After all, teams that invite diverse opinions are going to experience more disagreements than teams that suppress their differences. With more disagreements, the potential for at least some of them to be misinterpreted as personal attacks increases. Research, however, suggests just the contrary. Eisenhardt and Bourgeois (1988) reported that cynicism and covert politicking were less common in teams where open expression was encouraged. It may be that as norms of openness are established, TMT members begin to more fully understand one another and begin to empathize with and accept others’ feelings. This logic is consistent with Deutsch’s (1949) finding that groups that more freely shared ideas among members judged each other more positively. It may also be that as group members become more experienced with exchanging ideas, they value the exchange itself and appreciate those contributing to it. In summary, we expect that, as teams encourage open discussion and become comfortable with disagreement, they should experience less affective conflict. Thus, we offer the following hypothesis: H2b: The greater the TMT’s openness, TMT will experience.

the less affective conjlict the

Researchers have found that discrepancies between the goals sought by team members can kindle affective conflict (Deutsch, 1968; Pinto, Pinto & Prescott, 1993; Pondy, 1967). Long ago, theorists such as Barnard (1938) and Selznick (1957) recognized that a central function of top management is to create superordinate goals that unite action and to reward cooperative behavior toward those goals. Deutsch (1968) found that groups with mutual responsibility and incentives developed stronger feelings of attachment to the group, agreement among group members and positive evaluations of other members than groups with individual responsibility and incentives. Similarly, Pinto et al. (1993) showed that mutuality among members of cross-functional management teams led to positive affective responses among team members. Finally, Tjosvold and colleagues (1980, 1983) found that mutuality influenced the acceptance and understanding group members had of their decisions. It appears that norms of mutuality are associated with greater feelings of attachment and trust, and diminished experiencing of disharmony and affective conflict. In the absence of mutuality, even sincere disagreement can arouse affective conflict because it is likely to be misinterpreted and seen as a personal attack (Brehmer, 1976; Baron, 1984). Mutuality reduces affective conflict by reducing the likelihood that disagreements will appear sinister or self-serving. Thus, we advance the following hypothesis: JOURNAL OF MANAGEMENT,

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H2c: The greater the mutuality among TMT members, the less afsective conjlict the TMT will experience.

Finally, we expect that the level of mutuality will impact the extent to which openness reduces affective conflict. The reason for this is that the degree of mutuality is likely to color how TMT members interpret the open exchange of ideas. TMT members who share the rewards and responsibilities for outcomes are likely to appreciate other members’ willingness to openly share their ideas (and the credit for such ideas). On the other hand, when mutuality is low, TMT members may be relatively unaffected by or may even be resentful of attempts at frank, open discussion. This logic is consistent with Tjosvold who maintains that teams must “argue, debate, and disagree, but must also create facilitative interpersonal conditions: namely, cooperative goal interdependence . . .” (1985, p. 32). We expect that high levels of mutuality will affect a team’s response to openness such that openness reduces affective conflict more than would be the case when TMT members feel little mutual responsibility and accountability. Thus, we offer our final hypothesis: H2d: Mutuality and openness will interact such that the greater the level of mutuality, the stronger the negative association between openness and affective conjlict.

Methodology Our study employed a modified version of Flanagan’s (1954) Critical Incident Technique. We measured the openness and mutuality of 48 top management teams and then measured the cognitive and affective conflict those teams experienced during the consideration of a single strategic decision. We chose this technique because our study dealt with top management teams and, thus, required that data be collected from multiple individuals in each organization. By focusing the recollections of each team’s members on a specific incident, we controlled much of the recollection bias that would otherwise have contaminated the responses (Podsakoff & Organ, 1986). This technique also allowed us to measure true team dynamics for a particular decision and, thus, produce a realistic picture of conflict during strategic decision making. In the first step of the data collection, 260 food processing firms were identified from an industry publication, and a letter introducing the study was sent to the CEO of each. A short time later, each CEO was called. During the ensuing conversations, 94 CEOs agreed to participate and 68 declined. The other 98 CEOs could not be reached. Each of the 94 CEOs who agreed to participate was asked to describe a strategic decision that his or her top management team had made. A definition along with examples of a “strategic decision” was given to the CEOs to ensure comparability of decision types across businesses; the restriction of the sample to a single industry also helped ensure comparability of environmental context. To randomize the selection of decisions and minimize bias, the CEOs were asked to identify the most recent strategic decision that they had actually made and implemented. JOURNAL

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These decisions involved new product introductions, major purchases, relocations, and new market entry. While the details of the decisions were specific to each particular firm, all of the decisions involved high degrees of complexity and consequentiality and, thus, were strategic in nature (Hickson et al., 1986; Mason & Mitroff, 1981). To operationalize the teams, we asked each CEO to name the key managers who had actively participated in the decision that he or she had identified’ This operationalization has been used in previous TMT research (Dess, 1987; Judge & Miller, 199 1; Wooldridge & Floyd, 1990) and is based on the premise that the outcomes of a strategic decision are largely a function of who participates in the decision-making process (Jackson, 1992; Hickson et. al., 1986). We then sent surveys to all of the members of each TMT, including the CEO, in each of the 94 firms. Attached to each survey was a letter, mentioning the CEO (by name) and instructing each participant to complete his or her survey independently and return it in the provided envelope. Each survey had two parts. The first part referenced the decision described by the CEO and consisted of seven questions asking the participants about the conflict that they experienced during this particular decision-making process. The second part was on a separate page and consisted of a series of statements with which the managers were instructed to either agree or disagree. These statements were designed to measure the team’s norms of openness and mutuality and, thus, were not referenced to a particular decision. Attached to each CEO’s survey was a supplemental information sheet that the CEO was to complete and return with his or her survey. This supplemental sheet requested basic descriptive information on the firm and the team. A total of 323 surveys was sent to the 94 firms. We also sent survey packets to the 98 CEOs who were not reached by phone. Along with the surveys was a letter requesting that the CEO distribute one survey to each member of his or her “top management group.” The letter explained that, for the responses to be usable, they had to be completed individually by those top managers who actually participated in the particular strategic decision that the CEO would identify. Each questionnaire then referenced “the important decision identified by the CEO.” Attached to each survey was a letter instructing that the surveys be completed independently and returned in the provided envelopes. A total of 294 surveys was sent to these 98 firms. To be usable, a team had to provide at least two individual responses along with the supplemental information. From the 94 firms whose CEOs agreed to participate, usable responses were received from 45 teams, a response rate of 47.8%. Usable responses were received from just three of the firms that had not previously agreed to participate, a response rate of 3.1%. Clearly, prior contact with the CEO was important. Data on the nonrespondents were limited. However, based upon an examination of the listing of the geographic scope and product categories for each firm provided by the industry publication, we concluded that there were no obvious differences in the size or locations of the responding and nonresponding firms. Table 1 contains the team sizes, reported by the CEO, and the distribution of responses received from each team. The average team consisted of 3.44 managers, with the largest having seven and the smallest team having two JOURNAL OF MANAGEMENT,

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Table

1.

Team Size as Supplied by the CEO

505

Team Sizes & Responses Number of Responses Provided

Teams with 2 members - 10

Teams with 2 respondents

Teams with 3 members - 16

Teams with 3 respondents

- 21 - 16

Teams with 4 members - 17

Teams with 4 respondents

- 6

Teams with 5 members - 2

Teams with 5 respondents

- 2

Teams with 6 members - 2

Teams with 6 respondents

- 2

Teams with 7 members - 1

Teams with 7 respondents

- 1

Number of teams - 48

Number of teams - 48

Number of team members - 16.5

Number of respondents

Average team size - 3.44

Average per team response - 2.98

- 143

members. On average, 2.98 managers per team responded, a within-team response rate of 87%. The companies represented by these 48 top management teams averaged 266 employees and $52 million in sales. It is also worth noting that, in all but a few cases, this supplemental information was supplied by the CEO. Thus, in all but a few cases, the CEO’s response is included in the team responses. Measures Cognitive and affective conflict were measured with items from the Interpersonal Conflict Scale developed by Jehn (1992, 1994). Three items measured cognitive conflict and four items measured affective conflict. The responses were recorded on Likert-type scales ranging from (1) “none” to (5) “a great deal.” Previous research has shown cognitive and affective conflict to be correlated (Jehn, 1992, 1994). Thus, we assessed the measure using factor analysis with Promax rotation, to gauge the interfactor correlation. A positive correlation would be consistent with our supposition that cognitive and affective conflict often occur together. As expected, the analysis produced two factors accounting for just over 70% of the variation in the items. The four affective conflict items loaded on a single factor and produced a subscale reliability coefficient of .86. The three cognitive conflict items also loaded on a single factor and produced a subscale reliability coefficient of .79. None of the items produced meaningful off-loadings and the factors were positively correlated (.388). Openness was measured with four statements consistent with the aeration of ideas (Eisenhardt, 1989) and the encouragement of voice (Folger, 1977). The managers were asked to agree or disagree with the statements, “we thoroughly and sincerely evaluate different alternatives,” “quality improves when all the group’s members participate, ” “dissenting opinions should be encouraged,” and “the group enjoys debating different ideas.” These items loaded on a single factor and produced a coefficient alpha of .72. Mutuality was measured with four statements consistent with a collective orientation towards decision making, as described by Tjosvold (Tjosvold & JOURNAL OF MANAGEMENT,

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Deemer, 1980; Tjosvold & Field, 1983) and Deutsch (1949). The managers were asked to agree or disagree with the statements, “this group tends to cooperate for the overall benefit of the company, ” “rewards are shared equally regardless of whose ideas are used, ” “when we make a decision, we are all focused on achieving the same goal,” and “we all benefit equally when we make a good decision.” These items loaded on a single factor and produced a coefficient alpha of .7 1. Given the perceptual nature of our constructs and the potential difficulty for distinguishing among them with a survey instrument, we conducted a full factor analysis of the data to ensure that we had indeed measured separate constructs. We used Varimax rotation to assess the ability of the items to discriminate between the constructs and used the MINEIGEN function to set the criteria for factor retention at eigenvalue > 1. As shown in Table 2, four factors emerged, meaning that these four factors were the only ones that produced eigenvalues greater than 1. The factor loadings suggest a high degree of within-factor convergence and between-factor discrimination. The affective conflict items all loaded heavily and exclusively on a single factor. Likewise, the cognitive conflict items all loaded heavily and exclusively on a single factor. The openness and mutuality items also all loaded on separate factors. While three of the eight items used to measure openness and mutuality did produce off-loadings greater than .30, none

Table 2. Factor Analysis Results Examining the Convergence and Discrimination of the Measures Items

Factor 1

Factor 2

Factor 3

Factor 4

AFFCON

1

.74187

-.06757

.26938

AFFCON

2

.79663

-. 12584

.07969

.04494

AFFCON

3

.79937

-. 13798

.29397

.02485

AFFCON

4

.73418

-.03883

.25734

-. 12293 .09359

-.06780

COGCON

1

.25996

-. 10698

.81665

COGCON

2

.I4539

-.03048

.83560

.I2472

COGCON

3

.27798

-.023 14

.70416

-.05327

.30254

.00610

S6023

OPENSS 1

-.30079

OPENSS 2

.10464

OPENSS 3

.00392

OPENSS 4

.14029 -.02539

.04998

so740

.04708

.83214

-.407.59

.29380

.23294

.47449

MUTUAL

1

.03101

.70439

-.07522

.03932

MUTUAL

2

-.26835

.76312

.12458

.06837

MUTUAL

3

-.24060

.74531

-.0643 1

.07733

MUTUAL

4

.07252

.61394

-.18648

.32907

2.93270

2.26297

2.21111

2.053343

Eigenvalue

Proportion of Variance Explained Notes:

- 63.07%

* No other factors produced eigenvalues greater than or equal

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of these off-loadings were larger than the corresponding on-loadings, and in only one case was an off-loading greater than .33. All of the factors produced eigenvalues greater than two and together explained just over 63% of the total variation in the fifteen items. Thus, we are relatively confident that the measures captured four distinct constructs. Because we conceptualized TMTs as semi-stable groups that coalesce around particular issues, we measured the size of the teams by asking the CEO to report how many people were actually involved in the decision in question. Additionally, we measured and used team tenure and CEO tenure as control variables. Research has shown that collective experience among a team’s members may affect the level of comfort a team has with expressing conflict (Eisenhardt & Schoonhoven, 1990). So, we asked the president to report, on average, the number of years that the members of the TMT had worked together. Research has also shown that CEO tenure may affect the emergence of conflict by altering the distribution of power within the team (Eisenhardt & Bourgeois, 1988; Finkelstein, 1992). Thus, we asked the president to report the length of time he or she had held the position as the leader of the top management team. Finally, we assessed the level of within-team agreement before combining the individual responses into team level variables (Rousseau, 1985; Smith, 1991). To do this, a one-way ANOVA was run using team affiliation as the independent variable. For each measure, the level of between-team variation was significantly greater (p < .OOl) than the level of within-team variation, suggesting a relatively high level of agreement within the teams. We also calculated eta squareds, which, when above .20, indicate that any two within-team responses are more similar than any two responses from the sample at large (Florin, Giamartino, Kenny & Wandersman, 1990). The h2s for cognitive and affective conflict were .64 and .66, respectively. Openness had an h2 of .62 and mutuality had an h2 of 55. This high level of agreement allowed us to use the mean of the individual responses within each team as the team level variable.

Results To protect against common method variation, we ran two sets of analyses. The first used the full set of responses from all of the team members (the full sample). The second used an engineered, partial sample which was developed by randomly splitting each team in half, the dependent variables were then drawn from the responses from one half of a team’s members and the independent variables were drawn from the other half of the team’s members (see Smith, Organ & Near, 1983). For teams with an odd number of members, the extra person was randomly assigned to provide either conflict or norm information. A high degree of correspondence between the two sets of results will indicate that common method variance does not pose a significant threat to the validity of the findings (Podsakoff & Organ, 1986). We present the results of both the full- and partialsamples in Tables 3 and 4 and will refer to both sets in reporting the results. Table 3 contains the correlations, means, and standard deviations for the variables as developed from both the full and the partial samples. As expected, JOURNAL

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Table 3.

Zero-Order Correlations, Means, and Standard Deviations (N = 48 Teams, partial sample results are reported below the full sample results.)

-

Cognitive Conjlict

Affective Conflict

TMT Size

Openness

Mutuality

TMT Tenure

CEO Tenure

Cognitive Conflict

1.oooo .oooo 1.oooo .oooo

Affective Conflict

0.3795 .0078 0.4310 .0022

1.oooo .oooo 1.oooo .oooo

TMT Size

0.3478 .0156 0.3710 .0094

0.2841 .0503 0.3467 .0158

1.oooo .oooo 1.oooo .oooo

Openness

0.1465 .3203 0.0985 .5055

-0.3558 .0130 -0.1425 .3338

-0.1402 .3417 -0.2005 .1717

1.oooo .oooo 1.oooo .oooo

Mutuality

-0.1943 .1855 -0.2848 .0497

-0.3558 .0131 -0.3319 .0212

-0.3729 .0090 -0.3500 .0147

0.5352 .OOOl 0.493 1 .0004

1.oooo .oooo 1.oooo .oooo

TMT Tenure

-0.3687 .0099 -0.2697 .0637

-0.0495 .7379 -0.0618 .6761

-0.1362 .3559 -0.1362 .3559

-0.0008 .9952 0.0554 .7080

0.3069 .0339 0.1885 .1994

1.oooo .oooo 1.oooo .oooo

CEO Tenure

0.0240 .8710 -0.0816 .5811

0.2457 .0923 0.1287 .3834

-0.1648 .2629 -0.1648 .2629

-0.0058 .9686 0.2288 .1176

0.1929 .1888 0.2094 .1531

0.1591 .2799 0.1268 .3471

Mean

2.515 2.527

1.928 1.927

3.458 3.458

5.540 5.523

5.477 5.624

7.375 7.375

11.020 11.020

Std

0.602 0.756

0.724 0.839

1.166 1.166

0.835 0.952

0.769 1.037

6.463 6.463

7.355 7.355

1.oooo .oooo 1.oooo .oooo

conflict and affective conflict were positively correlated (fs = .3795; ps .4310). This suggests that cognitive and affective conflict did, in fact, often occur together in these teams. Openness and mutuality were also highly correlated (fs = S352; ps = .4931). When combined with the results of the factor analysis, this suggests that, although openness and mutuality are distinct constructs, they appear to occur in conjunction with one another. Again, this is consistent with our supposition that openness should foster trust and reciprocity. Team size was negatively correlated with mutuality (fs = -.3729; ps = -.3500). As the team composi-

cognitive =

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tion literature indicates, increased size may mean greater provincialism, which may make mutual cooperation difficult. It is also interesting to note that TMT tenure was negatively related to cognitive conflict cfs = -.3687; ps = -.2697). This may suggest that as team members grow familiar with one another, they disagree less frequently on matters of substance. CEO tenure was positively related to affective conflict (fs = .2457; ps = .1287). While weak, this relationship is consistent with an implication of Eisenhardt and Bourgeois’s (1988) study that a powerful CEO can produce more covert dealing by the other members of the top management team. Because of the interaction effects predicted in Hld and H2d, we used hierarchical regression to test our hypotheses; thus, two equations were generated with cognitive conflict as the dependent variable, and two with affective conflict as the dependent variable. First, we regressed cognitive conflict against the two control variables and three independent variables to test Hla-Hlc (see under COGNITIVE CONFLICT, Model 1, full sample and partial sample results in Table 4). We then added into the equation the cross product of openness and mutuality to test Hld (Model 2 under COGNITIVE CONFLICT in Table 4). The same procedure was followed to test H2a-H2d for affective conflict (see again Table 4). Because openness and mutuality were correlated, however, we first assessed the degree of multicollinearity by regressing each on the other independent variables. As the R2 for these models approaches 1.00, it indicates severe multicollinearity (Berry & Feldman, 1985). The model for openness produced an R2 of .32 while the model for mutuality produced an R2 of .46. While these R2’s are large enough to suggest some collinearity, that collinearity should not make our hypoth-

Table 4.

Regression Analyses & Hypotheses Tests N = 48 Teams Cognitive Conflict Full Sample

Independent Variables

Ml

M2

Affective Conjlict

Partial Sample

Ml

M2

Full Sample

Ml

M2

Partial Sample

Ml

M2

TMT Tenure

-.0279

-.0315

-.0220

-.023 1

-.OOOl

CEO Tenure

.0128

.0109

.0012

.0005

.0320

.0290

.0269

TMT Size

.1597*

.1562*

.1966*

.1863*

.1397+

.1339+

.2064*

TMT Openness

.2021*

.7599+

.2541*

.6036+

-.2136+

.7915

-.0008

.7136*

.4892

-.2177*

.0985

-.1744+

.7296

-.2260*

.4203

TMT Mutuality

-.1310

-.1097

Openness X Mutuality

-.067 1

R*

.2952

.3129

.2807

F

3.518**

3.111**

3.277**

Notes:

.2975 2.984*

-.0058

-.OOlO

-.1778+

.2962

.3284

3.536**

3.341**

-.0032 .0286 1853*

-. 1372*

.2230

.2802

2.411*

2.661*

+=p<.lO*=p<.O5**=p<.Ol

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esis tests any less conservative (Berry & Feldman, 1985). In fact, if the parameter estimates for openness and mutuality are significant, in spite of any multicollinearity that may be present, our hypotheses will still be supported. The Impact of Size, Openness, and Mutuality on Cognitive Conflict Table 4 indicates that Hla (cognitive conflict increases with TMT size) was supported (p < .05) in both the full and partial sample. Likewise, openness was also significantly related (p < .05) to cognitive conflict in both sets of results, supporting Hlb. Mutuality was negatively related to cognitive conflict as predicted in the full-sample results, but the relationship was not significant; in the partial sample the relationship was negative and significant (p < .05). Thus, Hlc received mixed support. Hypothesis Id stated that the positive impact of openness on cognitive conflict would increase in the presence of greater mutuality. To test this, a multiplicative interaction term was added to the direct effects model (see Model 2). While the interaction term improved the model’s R* to .3129, the increase of .0177 was not significant. The same result was found in the partial sample where the change in R* was .0168. So, Hld was not supported. The Impact of Size, Openness, and Mutuality on AfSective Conflict Table 4 also indicates that H2a (affective conflict increases with TMT size) was supported at p < .l in the full-sample and at p < .05 in the partial-sample. As predicted, openness was moderately related (p < .l) to affective conflict in the full-sample but was not significantly related to affective conflict in the partial sample results. Thus, H2b received mixed, and at best, weak support. Mutuality was negatively related to cognitive conflict as predicted in both the full-sample (p < .l) and the partial-sample results @ < .05). Thus, H2c received support. The significant coefficients for the interaction term in Model 2 (p < .l in the full- and p < .05 in the partial-sample) indicate that the joint effect of mutuality and openness contributes to explaining variation in affective conflict beyond what is explained by either alone. This effect can be observed in the changes in the models’ R* from .2962 to .3284 in the full sample (p = .0845) and from .2230 to .2802 in the partial sample (p = .0319). To interpret this effect, we performed a median split of the sample into high- and low-mutuality groups and examined the correlations between openness and affective conflict in both (Cohen & Cohen, 1983). Consistent with our prediction, for the subgroup high in mutuality, the correlation between openness and affective conflict was much more strongly negative (r = -.59, p < .Ol) than for the low mutuality subgroup (r = .09, n.s.). Thus, H2d was supported: openness had a significantly stronger impact on affective conflict in the presence of mutuality. In summary, of the four hypotheses predicting cognitive conflict, two received strong support (team size and openness), one received mixed support (mutuality), and one was not supported (the interaction of openness and mutuality). Of the four hypotheses predicting affective conflict, three were supported (team size, mutuality, and the interaction of openness and mutuality), and one was not supported (openness). JOURNAL

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Discussion This study examined how TMT composition and norms impact the level of conflict experienced by TMTs during strategic decision making. We argued that because cognitive conflict has been shown to improve decision quality, and affective conflict has been shown to undermine team harmony, effective TMTs would engage in processes that maximized the former and limited the latter. Therefore, the management of conflict appears central to long-term effectiveness. We developed a model predicting that cognitive and affective conflict in a TMT would be affected by its size, the openness of its interactions, and its level of mutuality. As predicted, we found team size positively related to both cognitive and affective conflict. Openness was also positively related to cognitive conflict, as we had hypothesized, and while it appeared negatively related to affective conflict as we had predicted, the results were weak. Mutuality was unrelated to cognitive conflict, either directly or in conjunction with openness. On the other hand, mutuality appeared to have a dampening effect on affective conflict. Further, TMTs with high levels of mutuality appeared especially able to achieve the predicted benefits of openness: for them, higher levels of openness meant significantly lower affective conflict. Recent research seems to suggest that the ability to arouse cognitive conflict without allowing affective conflict is a key to gaining the “benefits of conflict without the costs” (Eisenhardt & Zbaracki, 1992, p. 34). Thus, a better understanding of the conditions that can lead to cognitive and affective conflict is important. Our findings appear to contribute to this emerging discourse. Like others, we found cognitive and affective conflict to be positively related to one another. This is important because it underscores the potential danger of arousing conflict without fully considering its ramifications. Our ability to induce conflict outstrips our ability to manage its effects. Thus, conflict can be like Pandora’s box: once opened, its forces become difficult to control. That cognitive and affective conflict often occur together suggests the need for caution. We found that team size was positively related to both cognitive and affective conflict. This is consistent with our expectations and with extant theory on the effects of group size. Size introduces diversity, and diversity can have conflicting effects (Shaw, 1981; Smith et al., 1994). As Tjosvold (1985) cautioned, some of the conditions that are essential for cognitive conflict may also lead to affective conflict. This seems to be the case with team size. Of course, this presents a practical dilemma since a larger team may both enhance and hinder decision-making effectiveness. Perhaps a key to managing size is recognizing that disagreement is more helpful at some points of the decision-making process than others. Early in the process, when the problem is being defined and solutions are sought, a diverse set of opinions and perspectives is indispensable. Later, however, when the decision has been made and the team begins to focus on the details of its implementation, diversity and disagreement may be less important. However, even this solution is practically problematic as it may be impossible to simply “drop” TMT members at will. Clearly, more research on the double-edged effects of team size is needed. JOURNAL

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We also found openness to be an important antecedent of cognitive conflict. Cognitive conflict occurs naturally as teams compare and contrast the diverse perspectives of their members. The literature has shown that diversity is a key to effective strategic decision making (Bantel & Jackson, 1989). Without norms that encourage open discussion, however, teams cannot take advantage of their diversity. As Daft and Lengel (1986) found, open communication facilitates creativity and synergistic learning. Thus, diversity may represent the potential for better decisions, but openness represents the catalyst that unlocks that potential. The mixed results regarding the impact of openness on affective conflict are best understood through an examination of all the results. The negative zero-order correlation between openness and affective conflict is consistent with our expectation, but this direct effect weakens in the presence of the other variables in the regression equations. Nonetheless, openness is shown to have a potent and desirable effect on affective conflict in the presence of high mutuality. Our results suggest that mutuality may be the key to effective conflict management. Mutuality did not fully exhibit the predicted negative impact on cognitive conflict, but it did dampen affective conflict, especially when combined with high levels of openness. On a practical level, this is encouraging. That is, the results suggest that TMTs can reduce affective conflict through taking steps to increase mutuality and that these steps need not necessarily curtail efforts at generating cognitive conflict. This interpretation is consistent with Katzenbach and Smith’s (1993) recent work suggesting that feelings of mutual responsibility and accountability are essential for high performance TMTs. Assurance that team members will share in the outcomes of their decisions may dispel suspicion and create trust. Perhaps this is why Gomez-Mejia and Balkin (1992) recommend team-based rewards for unstructured problems like strategic decisions. Research by Tjosvold and colleagues (1980, 1983) has shown that, in the absence of a mutually cooperative reward system, team members become secretive and opportunistic. Without a sense of mutuality, team members may perceive sinister motives where none exist and feel personally threatened when no threat is present. Under such circumstances, any disagreement will trigger affective conflict. Thus,

Table 5.

Conflict Levels for Teams Based on the Levels of Openness and Mutuality

High Openness

CC = 2.73

cc = 2.44

AC = 2.19

AC = I .60

n=8 Low Openness

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n= 16

cc = 2.55

CC = 2.36

AC = 2.04

AC = 2.09

n= 16

n=S

Low Mutuality

High Mutuality

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if mutuality is established before cognitive conflict is encouraged, cognitive disagreements may be less likely to trigger affective conflict. This explanation is completely consistent with our finding that openness and mutuality work best when practiced together. Table 5 reports the levels of conflict for the 48 teams based on their levels of openness and mutuality. It is interesting to note that the gap between cognitive and affective conflict is the largest in those teams with high levels of both openness and mutuality. More than any other group in the sample, these teams seem able to engage in cognitive conflict without allowing their disagreements to trigger personalized, affective conflict. While taking note of its interesting findings, it is also important to note this study’s limitations. For example, we sampled firms in a single industry in order to control cross-industry, contextual variation. This choice may limit the generalizability of our results. Our sample was relatively small. While we found support for several of our hypotheses, we did not find support for others. It may well be that we failed to detect some significant relationships because of a lack of statistical power. We chose to sample intact top management teams working on real strategic decisions. This allowed uncontrolled variation in the design because each team had, of course, worked on different decisions. Nonetheless, this choice was made consciously because we felt that it was essential to obtain true dynamics and reactions, rather than reactions to a hypothetical problem. The fact that our predictions were largely supported despite this potential confound supports the power of our model. To conclude, many have argued that top management teams should seek diversity and learn to rigorously examine their different perspectives so that they can achieve higher quality decisions. Others have argued that top management teams should seek consensus and strive to maintain interpersonal relationships that will allow them to continue to work together harmoniously. The problem has been that these objectives do not peacefully coexist (Schweiger & Sandberg, 1991). Hence, some have hinted at the need to trade increments of one for the others (Priem, 1990; Van De Ven & Delbecq, 1974). For normative theorists, though, a trade-off is no solution at all. It is not enough to simply acknowledge the apparent incompatibility of diversity, conflict, consensus, and team member affect. As Bettenhausen states, “a concerted effort is needed to explore how diverse perspectives can be shared more effectively” (199 1, p. 356). Effective sharing should allow top management teams to simultaneously improve decision quality, consensus and affective acceptance. Our study provides evidence that effective sharing can occur in an atmosphere where frank and even critical discussion is encouraged, but where team members are assured that their interests are mutually linked. Acknowledgment: We would like to acknowledge mous JOM reviewers for their helpful and constructive of this article.

and thank the two anonycomments on earlier drafts

Notes 1. IIshould

be noted that this operationalization of the TMT will likely product a slightly different team than the more formal. positional indicators recommended by Hambrick (1994) for measuring top management JOURNAL

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groups. specific ics and in fact,

Hambrick (1994) states that these formal top management groups may rarely work collectively on decisions and, thus, are not particularly “team-like.” Because we were focusing on interaction dynamthe emotional responses team members have towards one another, we needed to sample teams that had, worked collectively on a specific decision. Thus, we used this particular operationalization.

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JOURNAL

OF MANAGEMENT,

VOL. 23, NO. 4, 1997