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Consistency Matters! The Effects of Group and Organizational Culture on the Faultline-Outcomes Link

Katerina BezrukovaDepartment of Psychology

Rutgers University311 N. 5th Street

Camden, NJ 08102Phone: 856-225-6120Fax: 856-225-6602

E-mail: bezrukov@camden.rutgers.edu

Sherry M.B. ThatcherManagement Information Systems Dep't

University of ArizonaTucson, AZ 85721

Tel: 520-621-2255 Fax: 520-621-2433E-mail: sherryt@bpa.arizona.edu

Karen A. JehnSocial and Organizational Psychology

Leiden UniversityWassenaarseweg 52

Leiden 2333 AKThe Netherlands

E-mail: jehnka@fsw.leidenuniv.nl

Consistency Matters! The Effects of Group and Organizational Culture on the Faultline-Outcomes Link

ABSTRACT

We explain how two types of group and organizational culture (e.g., cultures about the

importance of careers and acceptance of diversity) moderates the relationships between group

faultlines and individual outcomes. Group faultlines are defined as hypothetical dividing lines

that split a group into relatively homogeneous subgroups based on the group members’

alignment along one or more attributes (adapted from Lau & Murnighan, 1998). We extend the

group composition literature by showing how different faultline bases (informational and social

category) have different effects on employee’s performance and turnover rates under different

cultural conditions (consistent vs. inconsistent). We test our hypotheses using data from 110

groups consisting of 671 individuals in a Fortune 500 information processing company. Our

results revealed that members of groups with social category faultlines had lower levels of

performance and a higher rate of turnover. Members of groups with informational faultlines were

awarded higher bonuses in groups with a diversity-focused group culture, but lower levels of

performance ratings and higher rates of turnover in groups with a career-focused group culture.

Three-way interactions between faultlines, group cultures, and organizational cultures were also

found and are discussed.

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Consistency Matters! The Effects of Group and Organizational Culture on the Faultline-Outcomes Link

Recent research in the area of group composition has moved away from studying the

direct effects of heterogeneity (or diversity) on outcomes due to the mixed and contradictory

results relating to the effects of diversity and performance (Milliken & Martins, 1996; Williams

& O’Reilly, 1998). Group composition researchers have responded to these findings in two

ways. First, some researchers grouped diversity variables based on similar attributes (e.g., social

category diversity and informational category diversity) (Jehn, Chadwick, & Thatcher, 1997;

Jehn, Northcraft, & Neale, 1999; Polzer, Milton, & Swann, 2002) and investigated their

relationship to outcomes. The second, and most recent, response has been to focus on the issue of

demographic alignment as put forth in the group faultlines theory introduced by Lau &

Murnighan (1998). A recent paper by Bezrukova, Thatcher and Jehn (2004) combined these two

approaches and found that faultlines based on social categories did indeed predict different group

processes and outcomes than faultlines based on informational categories.

Since group composition may interact with a variety of other group and organizational

factors (Williams & O’Reilly, 1998), another way to explain the inconsistencies in empirical

results is to look at the relationship between group composition and performance in a more

complex framework and consider the role of contextual variables (Chatman, Polzer, Barsade, &

Neale, 1998; Jehn, et al., 1999; Rousseau & Fried, 2001). According to Johns (2001), the context

of individuals and groups often works in such a way as to encourage or impede behavior and

attitudes in organizational settings. Recent research on diversity has suggested that group and

organizational cultures may be of great importance when considering the effects of group

diversity (Chatman et al., 1998; Jehn, 1994; Mannix, Thatcher, & Jehn, 2001). Furthermore,

recent work on organizational climate has suggested that the strength of organizational cultures

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may also influence outcomes important to organizations (Schneider, Salvaggio, & Subirats,

2002).

There are three objectives of this paper. First, we will explain how two different types of

group culture (e.g., cultures about career advancement and diversity) represent a contextual

variable that moderates the relationships between group faultlines and individual outcomes. We

propose that these group cultures may serve as moderators of the relationships in which a

phenomenon at one level (e.g., group faultlines) has an impact at another level (e.g., individual

performance, turnover rates) (Klein & Kozlowski, 2000; Rousseau, 1985). Second, we will

contribute to theory on culture by investigating the cross-level effects of both group and

organizational culture. In effect, we show that cross-level integration of culture enables us to

understand culture consistency. Third, we show how group and organizational culture

congruency (or cultural consistency) can be a strong contextual variable when understanding the

effects of group faultlines on individual outcomes. We then test these relationships empirically.

Social Category and Informational Faultlines

We define group faultlines as hypothetical dividing lines that split a group into subgroups

based on two or more characteristics (Lau & Murnighan, 1998). Most research on diversity in

groups and organizations has looked at diversity as a composite of an individual’s various

demographic characteristics (Thatcher & Jehn, 1998; Williams & O’Reilly, 1998). From this

perspective diversity has been considered as a group-level variable defined as the degree to

which there is dispersion of a particular demographic characteristic in a specific population

(Blau, 1977). We advance the traditional understanding of diversity by utilizing a group

faultlines approach (Lau & Murnighan, 1998; Thatcher, Jehn, & Zanutto, 2003) that takes into

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account more than one demographic characteristic at a time, the way the characteristics align,

and the number of possible subgroupings that emerge.

Recent work has demonstrated how one can measure group diversity with a combination

of characteristics. Jehn and her colleagues (1997; 1999) have stressed the value in distinguishing

between forms of heterogeneity (e.g., those based on social categories and those based on

informational categories). Bezrukova, et al. (2004) have applied the same logic to faultlines as

described below.

Social category characteristics are observable attributes such as race/ethnic background,

nationality, sex, and age (Cummings, Zhou & Oldham, 1993; Jehn, et al., 1999; 1997). Social

category diversity is dispersion across members of a group on social category characteristics that

are easily observed by others and used for categorization purposes. While social category

diversity may not be relevant to the given task, it does shape people's perceptions and behaviors

(Pelled, 1996) through mechanisms of categorization and prejudice. Age, race, and sex prejudice

reflect the same categorization process of distinguishing between similarity and dissimilarity,

leading to stereotyping and misinformation. These categorizations may or may not be accurate,

and may lead to conflict if individuals are not living up to the expectations of others which

coincide with these categories. The same logic used to develop social category diversity can be

applied to faultlines. Thus, social category faultlines are hypothetical dividing lines that split a

group into subgroups based on social category demographic characteristics (e.g., age, race,

gender) (Bezrukova, et al., 2004).

Informational characteristics are underlying attributes of individuals (such as work

experience and education) which, although not immediately detectable, are important in the

completion of a task (Jehn et al., 1997). The information/decision-making perspective suggests

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that diversity will have positive implications on workgroup outcomes, since the group will have

access to a wider array of views, skills, and information (Gruenfeld, Mannix, Williams, & Neale,

1996). Educational background, functional background, and industry experience are all linked to

the set of skills one employs when undertaking a task. However, different backgrounds can lead

to fundamentally different preferred ways of completing a task. Therefore, informational

faultlines are hypothetical dividing lines that create subgroups based on informational

demographic characteristics (e.g., work experience, tenure) (Bezrukova, et al., 2004).

Group and Organizational Cultures

The essential core of culture consists of traditional ideas and especially their attached

values and the extent to which these ideas and values are accepted by a group (Kroeber &

Kluckhohn, 1963). There are different levels of analysis from which to study culture. For

example, culture exists at societal, national, and regional levels (DiMaggio & Powell, 1983).

Within organizations, culture can exist at an organizational, business unit, department, or group

level (Chatman & Jehn, 1994; Mannix et al., 2001).

Group culture is defined as the extent to which group members have consensus on values,

norms, and appropriate behaviors related to work (adapted from Chatman & Jehn, 1994; Mannix,

et al., 2001; Rousseau, 1990; Triandis & Suh, 2002). Group culture is an important variable to

look at when investigating group composition because one of the most often studied moderators

in group composition research is group values (Jehn, 1994; Probst, Carnevale, & Triandis, 1999).

Group values refer to the individuals’ fundamental beliefs regarding the desirability of behavior

choices (Enz, 1988; Rokeach, 1973). They reflect, for example, preferred ways to perform

individual and group tasks such as being innovative, task-oriented, or career-oriented (Jehn,

1994; Jehn, et al., 1997; O'Reilly, Chatman, & Caldwell, 1991). Two primary concerns become

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relevant when researchers conceptualize group values: (1) the extent to which members care

about values (value strength), and (2) the extent to which these values differ across settings

(value content) (Flynn & Chatman, 2001; Mannix, et al., 2001). The content of values, and

sequentially, the norms and the behaviors they support (thus, group culture), vary widely across

groups in an organization (Bettenhausen & Murnighan, 1991; Jehn, 1994). The content of values

we are interested in revolves around those important for work groups (i.e. values about career

advancement and diversity). Thus, we examine how different group cultures shape the way in

which group faultlines affect performance. In fact, past research on diversity suggests that strong

group cultures may be “a powerful way for managers to use informational and social influence

processes to encourage solidarity rather than divisiveness” (Williams & O'Reilly, 1998).

Following Reichers and Schneider’s (1990) definition of organizational culture, we

define organizational culture as a common set of shared meanings or understandings about an

organization. As in our discussion of group culture, the impact of organizational culture comes

from the content and the strength of the shared meanings. Previous research has found that

organizational culture affects group-level actions (O’Reilly, Williams & Barsade, 1998; Thomas

& Ely, 1996). O'Reilly, et al. (1998) found that organizational cultures that supported ethnic

diversity reported positive effects on performance. Similarly, Thomas and Ely (1996) found that

organizations that have cultures in which diversity is viewed as an opportunity to learn rather

than as a legal requirement tend to perform better. However, we argue that it is not merely the

content or strength of the organizational culture that influences group-level relationships; it is the

resulting impact of shared group values and organizational culture (cultural consistency) that

influences the relationship between group faultlines and individual outcomes.

Group- and Organizational Culture Consistency

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By exploring how group and organizational cultures simultaneously interact in

moderating the relationships between group faultlines and individual outcomes, we are

essentially talking about a congruency or consistency effect between group and organizational

cultures. The general notion of congruency, or fit, has attracted much research attention in

psychology and organizational behavior (Nadler & Tushman, 1980). This body of research draws

on the interactional psychology literature; both an individual and the situation combine to

influence an individual’s response in a given situation (Chatman, 1991). Although the majority

of person-environment fit literature has focused on the fit between an individual and the

individual’s job, researchers recently suggested that this focus is no longer appropriate due to the

changes in the nature of work, organizations, and employer-employee relationships (Carson &

Stewart, 1996; Kulik, Oldham & Hackman, 1987).

More recent studies have attempted to look at the fit between an individual and some

measure of the organization’s environment (Werbel & Gilliland, 1999). Original person-

environment fit literature proposed that good matches between environments and individuals

would result in high performance, high levels of satisfaction, and low levels of stress (Pervin,

1968). Individuals who have a poor person-environment fit were more likely to be injured on the

job than those who were more suitably matched to their environment (Sherry, 1991). Some of the

organizational components that are used when conducting a study of person-organization fit are

expectations or demands as well as the climate, culture, norms, values and strategic needs (Chan,

1996). Previous research on person-organization fit has focused on employee variables such as

values, goals, interests and cognitive styles (O’Reilly, et al., 1991; Vancouver & Schmitt, 1991;

Holland, 1985; Chan, 1996). O’Reilly, et al. (1991) found that person-organization fit on values

was a predictor of satisfaction, commitment, and turnover. Vancouver and Schmitt (1991) found

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that person-organization goal congruence was negatively correlated with intent to leave and

Chan (1996) found that cognitive misfit predicted actual turnover.

Person-workgroup fit is the most recent addition to this body of literature but as teams

become more of a workplace reality, workgroups are becoming an increasingly important part of

the workplace context (Chan, 1996; Werbel & Gilliland, 1999; Kristof, 1996; Judge & Ferris,

1992). Jehn (1994) examined the fit between group values and supervisor values and found that

more conflict existed when there was a misfit between the values of the groups and the values of

the supervisor. Person-group fit is especially important in organizations where teams play a

strong role in the organization and employees interact with their team members on a regular

basis. What has not been examined thus far is the impact of the “fit” between group and

organizational cultures on group and individual behavior.

Although research on organizational culture views the “strength” of the culture as

important, it is a difficult concept to measure. Recent work in the area of organizational climate

(Schneider, et al., 2002) adapted and tested a conceptualization of culture strength from Chan

(1998). This conceptualization of culture strength, in effect, measured the consistency of the

culture (reliable and stable) within a group by looking at within-group variability in climate

perceptions. We are attempting to bridge work in the areas of culture, congruence, and

organizational climate by showing how the congruence of group and organizational cultures (the

similarity across these two levels of culture) represents cultural consistency (a measure of

strength as determined in the climate literature). We argue that cultural consistency is important

because it can create extremely positive effects (in the case where the group and organizational

cultures align) or extremely negative effects (in the case where group and organizational cultures

do not align).

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Therefore, we add to the literature on culture and fit in two ways. First, we look at group-

organization culture consistency which extends the literature by examining the fit between two

entities that has not been previously examined. Very little research has studied culture in settings

involving multiple group boundaries, a serious gap when one considers the frequency of

organizational decisions involving the interests of multiple groups (Polzer, 2002). Second, we

draw from recent organizational climate literature to show how group-organization cultural

consistency provides a strong context under which individuals and groups work.

The Effects of Information and Social Category Faultlines on Outcomes

Much research has been done to investigate the effects that different group composition

variables have upon group performance (Milliken & Martins, 1996; Williams & O’Reilly, 1998).

However, the reality of work life is that an employee works in a group but tends to be rewarded

individually (Beersma & De Dreu, 2002). Thus, we hypothesize the effects of social category

and informational faultlines on individual-level outcomes. Following Hackman’s (1987) model

of effectiveness, we consider several performance outcomes: (1) individual performance ratings

as determined by a group manager based on performance standards set by the company, (2) stock

options and bonuses as drawn from individual, group, business unit, and company performance

history, and (3) turnover rates, defined as the extent to which individuals leave their job.

We argue that faulty group processes, emerging from the negative categorization across

subgroups formed by social category faultlines, may lead to severe losses in individual

performance outcomes. The alignment of demographic attributes based on similarity of group

members on gender, race and age is a sufficient condition for divisive social categorizations to

come to play (Jehn, et al., 1999). The negative effects of stereotyping, in-group favoritism and

out-group hostility can further sharpen the boundary salience around emerging subgroups, cause

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conflict and dislike to surface, and lead to decreased cohesion and social integration (Mackie,

Devos, & Smith, 2000; Tajfel & Turner, 1986; Webber & Donahue, 2001). This lessens the

frequency of interactions and information exchanges between members of different subgroups

formed by social category faultlines, which in turn, may lead to individual productivity losses

because both the amount of information and the access to the resource pool is reduced (Clement

& Schiereck, 1973; Freidman & Podolny, 1992).

Hypothesis 1 (H1): Members of groups with strong social category faultlines will have lower levels of individual performance outcomes.

Literature on minority influence suggests that information sharing in diverse groups

depends on the extent to which group members are provided with social support (c.f. Allen &

Levine, 1971; Bragg & Allen, 1972). When a group has strong informational faultlines, its

members may find support and validation for their knowledge (e.g., opinions, assumptions,

information) in their subgroups due to mutual liking, shared experiences and perceived similarity

of aligned members (Phillips, Mannix, Neale, & Gruenfeld, 2003). In such groups with strong

informational faultlines, members may freely express their ideas and actively engage in open

discussion of divergent perspectives across subgroups because they have support from within

their own subgroup (Lau & Murnighan, 1998; Phillips, 2003). We further propose that in

common-goal groups with informational faultlines, members are forced to integrate the divergent

opinions into their view of the decision problem. As a result, synthesis of ideas that are superior

to the individual solutions themselves (Schweiger & Sandberg, 1989; Schwenk, 1990) may

emerge and thus reinforce individual performances of its members. Similar processes are

highlighted by the literature on minority influence: minorities who argue consistently and

flexibly are shown to promote a thorough, intensive elaboration of the problem (De Dreu &

West, 2001; Moscovici, 1980; Phillips, 2003). Thus, we predict,

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Hypothesis 2 (H2): Members of groups with strong informational faultlines will have higher levels of individual performance outcomes.

We further argue that dissatisfaction arising from either conflict or faulty processes

(social category faultlines) or debating divergent opinions (informational faultlines) (Amason,

1996; Jehn, 1997) may impact an employee’s decision to leave his or her group. More

specifically, the “us versus them” mentality of subgroups formed by social category or

informational faultlines is likely to make it easy for one subgroup to blame the other subgroup

for mistakes and create stressful and unpleasant environments. Tension and personal attacks

within a group resulting from these processes can further escalate dissatisfaction among group

members (e.g., Amason & Schweiger, 1994; Jehn, 1994) causing employees to leave. Thus, even

though the two types of faultlines may have differential performance effects, we argue that the

tension and conflict caused by having strong faultlines may lead to an environment that makes

some individuals unhappy and uncomfortable. This, in turn, may lead to high levels of turnover.

Furthermore, once the boundaries around subgroups become salient, some subgroups can

be automatically placed on the status hierarchy relative to the dominant subgroup (Asante &

Davis, 1985). The status differentials between subgroups resulting from social category and

informational faultlines may restrict access to important resources, deprive lower-status

subgroup members (Mannix, 1993; Sherif, 1967) and create pay dispersion. Because pay

dispersion influences an employee’s decision to leave or to stay with a group (Lazear & Rosen,

1981), we further propose that members in groups with strong social category and informational

faultlines may feel less satisfied and thus, have stronger desire to leave.

While both types of faultlines may trigger an employee to quit his or her job, we predict

that informational faultlines will contribute to employees’ turnover to a lesser degree than will

social category faultlines. Members of groups with strong informational faultlines differ on

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demographic attributes that are directly job-related and pertinent to the task in hand. Members of

such groups tend to have a stronger impact on perceptions of work group tasks and exhibit

stronger attachment to their group as they know that the tension that may exist has positive

implications for performance. These feelings are crucial determinants of people’s willingness to

collaborate and stay with the group (Mitchell & Lee, 2001). Thus, we hypothesize:

Hypothesis 3 (H3): While individuals in groups with strong social category and informational faultlines will both have higher rates of turnover, social category faultlines will have a stronger effect on turnover rates than will informational faultlines.

The Moderating Effects of Group Culture and Group-Organization Culture

There are a number of facets of group and organizational culture that are relevant for

individuals working in a group. We focus here on two of these facets: career advancement, and

diversity (Jehn, 1994; O’Reilly, Chatman & Caldwell, 1991). We define career-focused group

culture as the degree to which group members believe that career advancement opportunities are

important to in their group (adapted from Riordan & Shore, 1997). Career-focused group culture

provides a sense of career opportunities by sending messages to employees about design and

implementation of group-level initiatives, such as selection, socialization and training (Higgins,

2001). Diversity-focused group culture refers to the extent that group members value differences

(with regard to experiences, backgrounds, and work) and believe that diversity is important in

their group (Richard & Johnson, 2001). Diversity-focused group culture sends messages to

employees about the group’s values regarding diversity (Nemetz & Christensen, 1996) such as

the acceptance and accommodation of various religious practices in the workplace (e.g., allowing

days off for various religious holidays and special times for prayer).

Because group members’ differences in informational characteristics are directly related

to the jobs that they perform, we argue that groups with informational faultlines may be more

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impacted by having a career-focused culture than groups with social category faultlines. Hence,

we are specifically interested in looking at the effects of career-focused group culture with

respect to informational faultlines. We argue that a career-focused group culture will have a

positive influence on groups with informational faultlines because it reinforces members’ desire

to succeed professionally. Kozlowski and Farr (1988) emphasized that work environment

characteristics such as beliefs about career opportunities are key determinants of employees’

interest, engagement in career exploration, and rate of participation in development activities.

Development opportunities include courses, workshops, seminars, and challenging assignments

that enhance self–efficacy and influence professional and personal growth (London, 1989; Noe

& Wilk, 1993). Self–efficacy includes employees’ beliefs that they can successfully cope with

challenging situations (Bandura, 1977), and is positively related to task performance (Gist,

Schwoerer, & Rosen, 1989) and the increased perceptions of career-related benefits (Noe &

Wilk, 1993). As previously discussed, members of groups with strong informational faultlines

enhance their self – efficacy due to social support provided by their subgroup members (Phillips

et al., 2003). Thus, we argue that such a double effect of self-efficacy in groups with strong

informational faultlines and career-focused group culture will produce positive effects.

Hypothesis H4 (H4): Career-focused group culture will moderate the relationship between informational faultlines and outcomes (performance and turnover) such that members of group with strong informational faultlines will have higher levels of performance and lower levels of turnover when their group culture emphasizes career advancement opportunities.

Groups with informational and social category faultlines and a culture of diversity will

see the value of having members from different backgrounds, experiences, or demographic

groups despite the difficulties. These groups should be able to focus on appreciating their

members’ differences rather than focusing on differences in a negative way. Diversity group

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cultures may foster cooperation and a desire to solve problems collectively, thereby creating

norms of tolerance and open communication (Hopkins & Hopkins, 2002). Employees in such

environments may consider diversity as a valuable asset of their workgroup and embrace

differences that can enhance effectiveness through creativity and innovation (Richard & Johnson,

2001). Workgroup environments in which employees believe that their group fairly values each

group member’s contribution, may eventually result in their greater commitment and

productivity due to common fate, shared values, and a sense of in-group membership facilitated

by such cultures (Hicks-Clarke & Illes, 2000). Therefore, groups with cultures of diversity will

have a moderating influence on the relationship between social category and informational

faultlines and outcomes.

Hypothesis H5 (H5): Diversity-focused group culture will moderate the relationship between informational and social category faultlines and outcomes such that members of group with strong informational or social category faultlines will have higher levels of performance and lower levels of turnover rates when their group culture emphasizes diversity.

High congruence between group culture and organizational culture suggests that there is a

consistent view of the culture across organizational levels. When cultures are consistent their

effects are strong and thus, group-organizational career culture consistency should merely

strengthen the results predicted in Hypothesis 4. More specifically, high consistency between

shared members’ beliefs about career advancement opportunities existed within their group and

within their organizational department should promote feelings of predictability, coherence and

control (Schneider, Salvaggio, & Subirats, 2002). Such consistency between career-oriented

group values and a higher-level organizational culture should produce positive responses because

members of groups with strong informational faultlines will perceive uncertainty as more

threatening to their relative stability and reliability. Thus, we argue that individuals in groups

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with strong informational faultlines will have high performance outcomes but this relationship

will be strengthened in groups with strong group cultures on career achievement, and will be

strengthened even further when there is strong group-organizational culture on career

achievement. Thus,

Hypothesis H6 (H6): A three-way interaction between informational faultlines, career-focused group culture, and career-focus organizational culture is expected, such that members in groups with strong informational faultlines and career-focused group culture will have higher levels of performance and lower levels of turnover rates in departments that emphasize career advancement opportunities than in departments without such emphasis.

Similar to the rationale for Hypothesis 6, diversity-focused group-organization cultural

consistency should strengthen the results predicted in Hypothesis 5. Individuals in groups with

strong social category and informational faultlines will have higher levels of performance and

lower turnover rates when they have strong diversity-focused group cultures and this relationship

will be strengthened even further when there is strong group-organizational culture consistency

on diversity. Thus,

Hypothesis H7 (H7): A three-way interaction between informational and social category faultlines, diversity-focused group culture, and diversity-focused organization culture is expected, such that members in groups with strong informational or social category faultlines and diversity-focused group culture will have higher levels of performance and lower levels of turnover in organizations that focus on diversity than in departments without such emphasis.

METHODS

Research Site

Our sample includes 110 groups from a Fortune 500 Corporation within the information

processing industry. This company is truly global with business facilities in 130 countries and a

World Headquarters in the United States. We identified the workgroups using a reporting system

developed by the company, and information about the structure of the divisions and departments

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provided by key senior staff. We verified that these were actual working groups (i.e., they

interacted on a day-to-day basis, were task interdependent, identified each other as group

members, and were seen by others as workgroups) by interview and observation. Our groups

included top- and middle-level managers who were responsible for monitoring the development

and production, sales, marketing and distribution of the company’s products in their respective

markets. Many groups were cross-functional and included representatives from corporate

administration, finance, sales and marketing, product development and manufacturing divisions.

We were informed by key senior staff and employees that “groups” of one or two employees or

groups with over fourteen employees were not actual working groups. This is consistent with

our definition of a group and with group process theories regarding group size. Therefore, we

eliminated such “groups” from our analysis leaving a sample of 110 groups and 671 individuals

with complete demographic and performance data. The age of employees ranged from 27 to 68

years with a mean of 45.6 years. Seventy two percent of the employees were male. The majority

of employees (86.4%) were white; 7% were African American, 2.4% Asian, 3.9% Hispanic. The

level of education ranged from grade school to the Ph. D. level; the modal level was a Bachelor’s

degree. Tenure with the company ranged from less than one year to 44 years with a mean of 14

years. Work functions included four distinct categories (i.e., administrative, customer service,

finance, and marketing).

Measures

Faultlines. We used the company’s personnel records and other archival data to locate

employees’ demographics on age, gender, race, function, education, and tenure. Gender was a

categorical variable coded as female = 0 and male = 1. Race was a categorical variable coded as

white = 1, black = 2, Asian/Pacific Islander = 3, Hispanic = 4, Native American = 5. Age and

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tenure were continuous variables measured in years. Level of education was a continuous

variable ranging from some grade school to doctorate degree on a 1-8 scale. Functional

background was a categorical variable coded as administrative = 1; marketing and customer

service = 2; finance = 3; operations = 4.

As past research showed the importance of distinguishing between the effects of faultline

strength (how cleanly a group splits into subgroups) and faultline distance (how far apart

subgroups are from each other), we operationalize group faultlines in terms of faultline strength

and faultline distance. We use a faultline algorithm and rescaling procedure to calculate faultline

strength and faultline distance scores for each work group (Bezrukova, Jehn, & Zanutto, 2004;

Thatcher, et al., 2003).

Faultline strength was measured along informational (level of education, tenure with the

company, and functional background) and social category (race, age, gender) faultlines using a

faultline algorithm and a rescaling procedure developed by Thatcher, et al. (2003). This faultline

strength measure calculates the percent of total variation in overall group characteristics

accounted for by the strongest group split, in other words, the faultline strength score indicates

how a group splits cleanly into two subgroups.

where denotes the value of the characteristic of the member of subgroup k, denotes

the overall group mean of characteristic j, denotes the mean of characteristic j in subgroup k,

and denotes the number of members of the subgroup (k=1,2) under split g. The faultline

strength is then calculated as the maximum value of over all possible splits

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Possible values of faultline strength scores ranged from .369 (weak faultline strength) to 1 (very

strong faultline strength) for informational faultlines and .427 (weak faultline strength) to .996

(very strong faultline strength) for social category faultlines.

We measured how far apart the two subgroups are from each other (faultline distance) on

informational (level of education, tenure with the company, and functional background) and

social category characteristics (race, age, gender,). The faultline distance measure was adapted

from multivariate statistical cluster analysis (e.g. Morrison, 1967; Jobson, 1992; Sharma, 1996)

and calculated as a distance between centroids (the Euclidean distance between the two sets of

averages): , where centroid (vector of means of each variable) for

subgroup 1 = (X , X , X , … , X11 12 13 1P. . . .), centroid for group 2 = (X , X , X , … , X21 2 2 23 2 P. . . .). Faultline

distance can take on values between 0 and with larger values indicating larger distance

between the resulting subgroups. Possible values of faultline distance in our dataset ranged

from .439 (weak faultline distance) to 3.536 (very strong faultline distance) for informational

faultlines and .375 (weak faultline distance) to 3.250 (very strong faultline distance) for social

category faultlines.

The faultline strength and distance measures take into account multiple characteristics of

group members by calculating scores for both continuous and categorical variables

simultaneously. Since there is no theoretical guidance on what differences would become

noticeable, meaningful and reasonable, we assumed an equal importance of all demographic

attributes when calculating these scores (see Thatcher et al., 2003, for more detail on the

rescaling procedure). To account for the joint effect of faultline strength and distance we

standardized both scores and then calculated an overall group faultline score representing the

interaction between the two scores.

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Performance. In this study, we used merit-based performance ratings (individual level)

and bonuses – the most frequently used pay plans for performance in contemporary

organizations (Lowery, Beadles, Petty, Amsler, & Thompson, 2002) – as performance outcomes

variables. Performance ratings are the codes associated with an employees' performance review

(e.g., 5 refers to employee’s outstanding performance, and 1 refers to his or her unsatisfactory

performance). Trained supervisors in this company conduct performance appraisals using pre-

defined criteria and rating scales to gauge actual behavior and worker performance (Drazin &

Auster, 1987). Bonus amounts are the actual bonus amounts paid out for the year. The yearly

bonus is calculated on total base salary for the year and includes multiple performance indicators

determined by the company. Another important outcome variable is turnover, which includes

both employee termination as well as transfer.

Control Variables. We included employees’ gender and tenure as individual-level control

variables and group size as a group-level control variable. Extensive body of literature has

identified the effect of gender on patterns of interaction and status (Ferdi & Wheelan, 1992) and

indicated its substantial impact on various performance outcomes. The effects of tenure (work

experience and competence) have also been shown to affect intragroup communication

(O’Reilly, Snyder & Boothe, 1993) and various performance outcomes (Williams & O’Reilly,

1998). Group size has been shown to be of a great importance for group processes and outcomes

(Goodman, Ravlin & Argote, 1986). All controls were obtained from the archival file data

provided by the company.

Qualitative Data Analysis

Group Culture. To generate measures of our group culture variables, we content-

analyzed company documents that were part of a human resources-sponsored program designed

20

for managers and supervisors of workgroups to assess employee competencies (i.e., values,

goals, skills, and knowledge). In order for managers and supervisors to complete these

assessments, they are provided with a guide that describes multiple competencies. These

competencies define the scope of management’s objectives and values regarding critical aspects

of the workgroup environment. According to Doty, Glick, and Huber (1993), managers and

supervisors translate managerial objectives into the actual context of their departments and

workgroups. Thus, we believe that these data are appropriate to use for specifying the workgroup

culture variables because the competencies assessed in the supervisor reports can serve as

indirect evidence of current group environments regarding certain cultures.

We content-analyzed these supervisor reports based on the following procedure

established in prior research (Abrahamson & Hambrick, 1997; Kabanoff, 1997). First, two raters

blind to the hypotheses and purpose of the study independently reviewed the guide provided by

the company describing each competency. They then sorted the competencies into seven key

phrase lists based on relevant organizational theories regarding group cultures, as well as the

concepts used in the company’s rhetoric (see Appendix 1). The level of initial agreement

between the two raters was 84%. Second, the two raters together reviewed the descriptions and

phrase lists of the context variables for each competency, discussed each definition and phrase

list until they had a common understanding of it, and then refined the key phrase list for each

variable studied. Third, when the key phrase lists were complete, the data were organized by

group. Fourth, these data were searched for the words from the key phrase lists using the

program MonoConc Pro 2.0 (Barlow, 2000) to obtain frequencies of context variable phrase

occurrence. Finally, to arrive at a score for each group culture variable, the percentage of total

relevant hits for a particular variable representing each group were summed. This procedure

21

allowed us to make direct quantitative comparisons of groups within various workgroup

environments using established computer-aided text analysis techniques successfully employed

in past organizational research (e.g., Abrahamson & Hambrick, 1997; Doucet & Jehn, 1997;

Kabanoff, 1997). We rated two group cultures (career-focused and diversity-focused) using the

above procedure. See Appendix 1 for the examples of selected key phrases for each group

culture variable.

Organization Culture. To generate measures of organizational culture, we content-

analyzed company documents that were part of a human resource-sponsored program. In this

organization, the business unit defined the largest entity of culture relevant to the employees;

therefore, we measured the business-unit culture. Employees submitted information regarding

their business unit culture directly over the corporate intranet or via the internet. This

information is confidential and available only to the employee, his or her direct manager and a

selected group of human resource personnel.

We rated these documents by first developing lists of key words characterizing each

variable under study based on relevant group and organizational theories, as well as the concepts

used in the company’s rhetoric. We ran computer-aided text analysis on the company’s textual

data using the program MonoConc Pro 2.0 (Barlow, 2000) and created frequency lists with the

terms mentioned most to least often. To arrive at the key word lists for each variable, three raters

first independently considered all terms from the frequency lists and selected the key words

representing each variable under study. They then discussed their respective lists of key terms

and composed the final lists containing only the words that they agreed upon. Following the

method of Jehn and Werner (1993), two independent raters further conducted the key word

searches on all individual responses, reviewed the surrounding context and coded the text for

22

each variable of interest as defined by theory. The inter-rater agreement ranged from 89% to

97% on the variables and was determined by checking the number of times that the raters agreed

upon the score which they assigned to an individual response. When raters rated a response

farther than 1 point apart, they discussed the response until they reached an agreement and then,

they refined their coding rules.

Two different types of organizational culture (career-focused and diversity-focused) were

identified by content coding the company’s textual data. Examples of career-focused

organizational culture and diversity-focused organizational culture are shown below,

respectively.

Career-focused: “In the last 3 years I have experienced several positive opportunities. Much of which as to do with people I reported to (name), for example, is a great manager/mentor. Additionally, this is carried over in the [name of the department] which I am now a part of. This is an environment in which efforts are recognized. It is intellectually and personally satisfying.” Diversity-focused: “I like the diversity of my job and the work place. Not only the ethnic, gender etc., but my job gives me the opportunity to deal with a wide range of cross functional fields. I like people and learning new things.”

Quantitative Data Analysis

Given that informational and social category faultlines are multilevel phenomena, with

observations at one level of analysis (individuals) nested within another level of analysis

(groups), we employed two-level hierarchical linear modeling (Bryk & Raudenbush, 1992;

Hofmann, 1997). The basic two-level HLM model is depicted in equation form as follows:

Level 1: yij = β0j + β1jx1ij + rij (1)

Level 2: β0j = γ00 + γ01zj + U0j (2)

β1j = γ10 + U1j (3)

23

where yij is an individual-level outcome measure for person i in group j, x1ij represents an

individual-level independent variable, β0j and β1j are random coefficients representing a within-

group intercept and a within-group slope, respectively, rij is an individual-level error term and is

assumed to be independent and normally distributed with a mean 0 and a variance of 2. zj

represents a group-level variable, γ00 and γ10 are between-group intercepts, γ01 is a between-group

slope, U0j, and U1j are group-level error terms that represent the residual variance for each

equation and are assumed to be normally distributed with mean 0 and variance in intercepts

( and slopes (

We performed a sequence of models using the HLM 5.04 statistical package (Bryk,

Raudenbush, Cheong, and Congdon, 1994). Each HLM analysis was conducted in a hierarchical

fashion that included six steps (Bryk & Raudenbush, 1992; Hofmann, Griffin & Gavin, 2000).

Model 1 estimated within- and between-group variance in our dependent variables. Model 2

included individual-level controls (gender and tenure), model 3 added group-level controls

(group size), and model 4 included the main effects of variables under study. Finally, to test the

moderating effects we specified model 5 which included two-way interactions (e.g.,

informational faultlines x career-focused group culture) and model 6 which included

hypothesized three-way interactions (e.g., social category faultlines x career-focused group

culture x career-focused organizational culture). In addition, because the predicted value of our

turnover variable can only take on one of two values (0 = active employee; 1 =

terminated/transferred employee), and therefore cannot be normally distributed, we conducted a

series of nonlinear analyses.

RESULTS

24

Table 1 displays the means, standard deviations, and correlations, respectively, among all

variables. Social category faultlines were negatively and significantly associated with bonuses.

Informational faultlines were positively and significantly correlated with both career- and

diversity group and organizational cultures while social category faultlines were negatively

related to diversity-focused group culture. We examine the relationships between informational

and social category faultlines, group and organizational cultures, performance and turnover using

hierarchical linear modeling analyses.

---------------------INSERT TABLE 1 ABOUT HERE --------------------

Faultlines, Performance and Turnover

The results of null models for bonuses, performance ratings, and turnover (τ00 = 2.92, df = 85,

= 781.18, p = .000; τ00 = .07, df = 85, = 156.91, p = .000; τ00 = .71, df = 85, = 119.55,

p = .008, respectively) show that there is systematic between-group variance in bonuses and

performance ratings. The results of random coefficients regression models show significant

variance in the intercept parameters for bonuses (τ00 = 3.13, df = 67, = 557.85, p = .001),

performance ratings (τ00 = .07, df = 67, = 106.95, p = .002), and turnover (τ00 = .55, df = 85,

= 65.80, p = .087) models confirming the appropriateness of testing the cross-level

relationships.

Table 2 presents the HLM analyses testing the main effects of informational and social

category faultlines on individual-level outcomes. In support of hypothesis 1, members of groups

with strong social category faultlines had lower levels of performance ratings (γ03 = -.05, p = .09)

and bonuses (γ03 = -.21, p = .07). Hypothesis 2, predicting that members of groups with strong

informational faultlines will have higher levels of individual performance outcomes was not

supported. Hypothesis 3, predicting that while individuals in groups with strong social category

25

and informational faultlines will both have higher rates of turnover, social category faultlines

will have a stronger effect on turnover rates than will informational faultlines, was partially

supported. Members of groups with strong social category faultlines had higher rates of turnover

(γ03 = .36, p = .001).

---------------------INSERT TABLE 2 ABOUT HERE --------------------

The Moderating Effects of Group Culture

We further conducted HLM analyses to test hypotheses 4 and 5 predicting the moderating

effects of career- and diversity-focused group cultures on the relationship between group-level

faultlines and individual-level outcomes. Hypothesis 4 predicted that career-focused group

culture will moderate the relationship between informational faultlines and outcomes

(performance and turnover) such that members of group with strong informational faultlines will

have higher levels of performance and lower levels of turnover when their group culture

emphasizes career advancement. Opposite to what was expected, members of groups with strong

informational faultlines and a career-focused group culture had lower levels of performance

rating (γ05 = -.17, p = .029) and higher rates of turnover (γ05 = .77, p = .004) than groups that did

not have this group culture. Hypothesis 5, predicting that diversity-focused group culture will

moderate the relationship between informational and social category faultlines and outcomes

such that members of group with strong informational or social category faultlines will have

higher levels of performance and lower levels of turnover rates when their group culture

emphasizes diversity, was partially supported. Members of groups with strong informational

faultlines and a diversity-focused group culture were awarded higher amounts of bonuses (γ05

= .27, p = .09).

---------------------INSERT TABLE 3 ABOUT HERE --------------------

26

The Moderating Effects of Group and Organizational Culture

Finally, we conducted HLM analyses to test a more complex relationship between

faultlines, group- and organizational culture, and outcomes (H6 and H7). The main effects HLM

model included faultlines and culture variables (e.g., informational faultlines, diversity-focused

group- and organizational culture). The first interaction HLM model included all the two-way

interactions (e.g. informational faultlines x diversity-focused group culture; informational

faultlines x diversity-focused organizational culture; diversity-focused group culture x diversity-

focused organizational culture). The second interaction HLM model included a three-way

interaction between faultlines, specific group-, and organizational culture.

Hypothesis 6, predicting a significant three-way interaction between informational

faultlines, career-focused group culture, and career-focus group-organizational culture, such that

members in groups with strong informational faultlines and career-focused group culture will

have higher levels of performance and lower levels of turnover rates in departments that

emphasize career advancement opportunities than in organizations without such emphasis, was

not supported. Hypothesis 7, predicting a significant three-way interaction between informational

and social category faultlines, diversity-focused group culture, and diversity-focused group-

organization culture consistency, such that members in groups with strong informational or

social category faultlines and diversity-focused group culture will have higher levels of

performance and lower levels of turnover in organizations that focus on diversity than in

organizations without such emphasis, was partially supported. Members of groups with strong

informational faultlines and diversity-focused group culture had higher levels of performance

ratings (γ10 = 11.32, p = .014) and lower levels of turnover (γ10 = -68.73, p = .001) in departments

that focus on diversity than in departments without such emphasis. Furthermore, opposite what

27

was expected, members of groups with strong social category faultlines and diversity-focused

group culture had lower levels of performance ratings (γ10 = -12.69, p = .056) and higher levels

of turnover (γ10 = 81.69, p = .014) in departments that focus on diversity than in departments

without such emphasis.

DISCUSSION

Discussion of Results

Consistent with the predictions made by Lau and Murnighan (1998), our results revealed

significant and negative relationships between social category faultlines and outcomes. Members

of groups with social category faultlines had lower levels of performance and a higher rate of

turnover. As theory predicts and our results strongly support, the alignment of demographic

attributes based on similarity of group members on gender, race and age may fire up negative

categorization processes to the extent to which individuals’ tangible outcomes such as bonuses or

performance ratings become affected. Furthermore, in groups with strong social category

faultlines, individuals must truly feel that "us vs. them" distinction negatively colors their group

experience to the point when they are willing to leave.

Consistent with our predictions, we found that members of groups with informational

faultlines were awarded higher amounts of bonuses in groups with an emphasis on diversity. Our

findings suggest that when groups with informational faultlines have a strong diversity-focused

group culture, members of such groups may become more inclusive to different opinions that

arise across subgroups. They may shift their focus from a subgroup towards the larger group and

make their overall information and communication exchanges more inclusive, thereby

minimizing process losses. This also suggests that members of groups with informational

28

faultlines and a culture of diversity may consider diversity as a valuable asset of their workgroup

and embrace differences that can enhance effectiveness through creativity and innovation

(Richard & Johnson, 2001).

Some more puzzling results were obtained with respect to the moderating effects of

career-focused group cultures. Contrary to what was expected, members of groups with

informational faultlines had lower levels of performance rating and a higher rate of turnover in

groups with an emphasis on career advancement. One possible explanation is that such culture in

groups with informational faultlines places an emphasis on individual career achievement, which

may interfere with some patterns of social interactions within subgroups and lead to the decline

in mutual helping behaviors. For example, members of group with strong informational faultlines

and a career-focused culture may suspect that their career advancement opportunities are

mutually exclusive and thus, refuse to assist their peers. Another explanation is that career-

focused group culture may create an environment in which members are constantly under

pressure of “producing” and are judged based on their career achievements. Termination or

transfer may become a feasible solution and one of the possible responses to such frustrating

situations.

We found that while members of groups with informational faultlines and diversity-

focused group culture had higher levels of performance and a lower rate of turnover in

departments that focused on diversity, members of groups with social category faultlines had

lower levels of performance and a higher rate of turnover in such departments. In both cases, the

emphasis on diversity highlights people to think about the way they are different. In the case of

informational faultlines it highlights peoples differences regarding task-related issues (consistent

with what we expected) and suggests that these differences are good. For social category

29

faultlines the emphasis on diversity highlights that people are different on gender, age, and race.

Although the culture may emphasize that diversity is good, individuals still must deal with

subgroups of people who are very different from themselves.

Limitations of the Study

The strengths of the current research (e.g., data collected from an actual workplace

setting, multiple methodologies) are accompanied by potential weaknesses. Some limitations of

this study are common in demography studies that use archival file data. For instance, while we

were able to construct reliable measures of group culture variables using content analysis of

company documents, no direct measures of these variables were available. Future research

should use employee survey data and interviews that allow a more thorough understanding of

how various group cultures shape effects of faultlines and affect employee behavior. We also

realize that our performance measures may have different antecedent predictors. For example,

bonuses can be based on “hard” performance numbers (e.g., sales or customer satisfaction),

while individual performance ratings may indicate a more subjective perception of an

employee’s performance by her or his supervisor. This might be one reason we obtained

different levels of significance in effects when testing our hypotheses.

Contributions of the Study

In this field study, we investigate a more complex relationships between contextual

variables and their effects on groups. Many researchers have proposed to employ a

configurational framework to the study of context and group processes. For example, Richard

(2000) believes that future multilevel research should investigate the backdrop of business

strategies, human resource practices, and cultures as a system of combined contextual factors.

Jehn and Chatman (2000) suggest that the recognition that not one type of conflict but rather that

30

the composition of all conflicts (the type of conflict present in a group relative to the other types

of conflict present) within a group matters. In our study, we draw upon and extend past research

on organizational culture and climate by examining the effects of different workgroup

environments and more importantly, by seeking the most effective alignment of group and

organizational cultures for group diversity to be beneficial. Our findings suggest that we should

look not only at workgroup environments alone where a group operates (organizational cultures),

but also consider the immediate context of groups (group cultures) and the interaction between

the two.

In this study, we further extend the theory of group faultlines (Lau & Murnighan, 1998)

and make our predictions about group interactions based on multiple member demographic

characteristics and their alignment within the group. Past diversity studies have often ignored

individuals’ multiple demographic characteristics (e.g., gender, race, age) and the alignment of

these characteristics across group members. This alignment can be crucial for understanding the

effects of group and organizational context on the group composition-performance relationship.

Based on faultline theory (Lau and Murnighan, 1998), the alignment construct we introduce

conceptually accounts for the interdependence among multiple demographic characteristics. It

suggests that the effects of diversity are most likely a complex function of the various

demographic characteristics aligning rather than working separately and recommends a more

sophisticated consideration of all the potential dynamics that many different characteristics when

aligned can activate (Lau and Murnighan, 1998).

In this study, we also attempt to further the theoretical understanding of group faultlines

in demographically diverse organizations by theorizing about separate effects for social category

and informational faultlines. Recent work has stressed the value in distinguishing between forms

31

of heterogeneity (e.g., those based on social categories and those based on informational

categories) (Jehn, 1997; Jehn et al., 1999), thus we suggest that the same logic can be applied to

faultlines.

32

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Appendix 1. Selected key phrases and descriptions of competencies for group culture variables.

1. Career-focused group culture:Examples of key phrases (competencies):Coach and DevelopChange ChampionContinuous LearnerDescription of a competency:DefinitionProvides challenging assignments and opportunities for development. Behaviors

-Provides challenging assignments to facilitate individual development-Shows interest in employees’ career-Stimulates others to make changes and improvements

2. Diversity-focused group culture:Examples of key phrases (competencies):Valuing diversityEthics & ValuesGlobal PerspectiveDescription of a competency:DefinitionCreates a work environment that reflects respect for everyone’s contributions; demonstrates and fosters respect for each person whatever that person’s backgroundBehaviors

-Values the talents and skills of others-Recognizes and utilizes the contributions of people from diverse backgrounds-Creates an environment in which people from diverse backgrounds feel comfortable-Helps people from diverse cultures/backgrounds/lifestyles succeed

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13296

Table 1. Means, Standard Deviations, and Zero-Order Correlations Among Variables.

Correlations Mean

(N =671 )

S.D.

(N = 671)

Mean

(N = 110)

S.D.

(N = 110)

1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Group Size 7.64 3.37 6.10 3.08 .26** .15 .01 .13 .03 -.03 .06 -.11 .28** .29** .23* .26** -.03

2. Gender .72 .45 .68 .25 .17** .32** .01 .07 .03 -.03 .06 -.11 .28** .29** .23* .26** -.03

3. Tenure 13.97 9.37 13.49 6.46 .13** .23** .13 .06 .19* -.04 -.10 -.12 -.09 -.17 -.11 .05 -.31**

4. Social Category Faultlines .41 1.23 .41 1.49 -.02 -.00 .09* .28** .08 -.15 -.04 .04 -.08 -.07 -.04 -.06 .11

5. Informational Faultlines .11 1.31 .01 1.58 .11** .02 .03 .18** ..03 .12 .16 .07 .06 .07 .05 .09 -.03

6. Career-Focused Group Culture .33 .23 .33 .25 -.00 .06 .15** .05 .10** .11 .17 -.02 -.31** .07 .05 .09 -.03

7. Diversity-Focused Group Culture .55 .31 .56 .33 -.08* -.02 .02 -.11** .16** .09* .09 .28** .01 -.33** -.37** -.18 -.19

8. Career-Focused Org Culture .03 .03 .03 .03 .05 -.11** -.08 -.05 .20** .13** .07 .18 -.05 -.02 -.02 .16 -.12

9. Diversity-Focused Org Culture .03 .02 .03 .02 -.19** -.21** -.12** 02 .09* -.08 .25** .16** .22* .22* .23* .18 .03

10. Bonuses 11920.32 26303.39 10196.11 19588.03 .18** .06 -.06 -.09* .03 -.28** -.04 -.02 .19** .96** .86** .37** .01

11. Options 2086.39 3531.64 1725.59 2670.24 .16** .07 -.12** -.07 .03 -.33** -.07 -.07 .23** .92** .84** .33** .08

12. Change in Salary .01 .03 .01 .02 .14** .07 -.05 -.04 .01 -.27** -.07 -.02 .16** .64** .64** .35** .13

13. Performance Ratings 3.89 .79 3.81 .49 .14** -.01 -.03 -.02 .02 -.12** .03 -.02 .06 .25** .23** .20** -.28**

14. Termination .16 .37 .16 .22 -.03 -.07 -.19** .05 -.01 -.08* -.06 -.04 .04 -.05 -.02 .06 -.11**

*p < .05; ** p < .01

Individual level correlations are reported in the lower triangle. Group level correlations are reported in the upper triangle

13296

Table 2. Results of HLM Estimation for Individual-Level Outcomes (main effects models).

Bonuses Performance Ratings Termination

Model & Variable Coefficient Standard error Coefficient Standard

error Coefficient Standard error

One-way ANOVAGroup variance) 2.924*** .071*** .706**2 (Residual variance) 2.412 .551

Control VariablesRandom-coefficients regressionγ10 (Tenure) -.005 .127 -.054 .057 .618*** .139γ20 (Gender) .383* .157 .001 .067 .464* .220Group variance) 3.134*** .069** .553†

2 (Residual variance) 2.255 .549

Intercepts-as-outcomesγ10 (Tenure) -.004 .127 -.075 .058 .618*** .145γ20 (Gender) .394* .158 .009 .068 .456* .225γ01 (Group Size) .993* .487 .302* .117 .343* .313Group variance) 2.983*** .056* .545†

2 (Residual variance) 2.258 .544

Main Effects Intercepts-as-outcomesγ10 (Tenure) .007 .127 -.067 .057 -.709*** .148γ20 (Gender) .389* .159 -.011 .068 -.456* .229γ01 (Group Size) .943† .484 .287* .118 -.207 .315γ02 (Info Faultlines) -.055 .177 -.015 .046 -.013 .094γ03 (Social Category Faultlines)

-.207† .114 -.054† .036 .357** .106Group variance) 2.998 .058* .4752 (Residual variance) 2.256 .543

† p < .1; *p < .05; **p < .01; ***p < .001

Table 3. Results of HLM Estimation for Individual-Level Outcomes (moderated models).Bonuses Performance Ratings Termination

Model & Variable Coefficient Standard error Coefficient Standard

error Coefficient Standard error

Career Group CultureMain Effects γ10 (Tenure) .024† .142 -.076 .056 -.119 .122γ20 (Gender) .412* .198 .056 .070 -.411† .234γ01 (Group Size) .112† .06 .025† .014 -.066† .038γ02 (Info Faultlines) -.045 .130 -.023 .035 -.033 .081γ03 (Career Group Culture) -3.232*** .784 -.508** .165 -.033 .591Group variance) 2.749*** .038† .6112 (Residual variance) 2.347 .498Interactionsγ10 (Tenure) .011 .141 -.071 .056 -.185 .119γ20 (Gender) .409* .198 .054 .069 -.331 .241γ01 (Group Size) .107† .062 .028† .015 -.061† .036γ02 (Info Faultlines) -.136 .224 .026 .038 -.285** .099γ03 (Career Group Culture) -3.654*** .944 -.465** .157 -.803 .622γ05 (Info Fau x Career Gr Culture) .236 .366 -.171* .078 .769** .266Group variance) 2.758*** .038† .5792 (Residual variance) 2.346 .499

Diversity Group CultureMain Effects γ10 (Tenure) .001 .143 -.097† .057 -.145 .122γ20 (Gender) .367† .199 .046 .072 -.424† .234γ01 (Group Size) .135* .067 .035* .016 -.059 .038γ02 (Info Faultlines) -.105 .193 -.053 .037 -.066 .090γ03 (Soc Cat Faultlines) -.200 .126 -.022 .044 .229† .132γ04 (Diversity Group Culture) .204 .628 .269† .163 .379 .391Group variance) 3.409*** .049† .5972 (Residual variance) 2.352 .498Interactionsγ10 (Tenure) .005 .143 -.082 .059 -.187 .137γ20 (Gender) .356† .198 .044 .071 -.471* .228γ01 (Group Size) .149* .067 .033* .016 -.053 .045γ02 (Info Faultlines) -.389 .294 -.118† .062 .058 .180γ03 (Soc Cat Faultlines) .038 .204 -.083 .065 .340 .219γ04 (Diversity Group Culture) .072 .665 .143 .205 .654 .506γ05 (Info Fau x Diversity Gr Culture) .269† .163 .072 .052 -.137 .140γ06 (Soc Cat Fau x Diversity Gr Culture) -.473 .356 .128 .133 -.248 .642Group variance) 3.393*** .050* .6752 (Residual variance) 2.354 .498

† p < .1; *p < .05; **p < .01; ***p < .001

42