‘Faultlines in organizational teams’ A study about perceived faultlines affecting team processes and outcomes. By Lisan Keijzer

‘Faultlines in organizational teams’

A study about perceived faultlines affecting team processes and outcomes.

By Lisan Keijzer

University of Groningen Faculty of Economics and Business

ABSTRACT

In this study, the influence of perceived faultlines on team processes and outcomes in the organizational teams is examined. The study explores how perceived faultlines in teams affect the degree of conflict and behavioural integration, and the consequences for team performance within this teams in the context of change. This quantitative field study is conducted in 44 teams, with 226 respondents, representing 16 organizations in the Netherlands. Faultlines which are triggered because of organizational change, are called change related faultlines. Due to experience of organizational change, team members can actual perceive faultlines within their team based on various change related bases. The results show that perceived change related faultlines affect emotional conflict and task conflict in a positive manner. This indicates that when faultlines are perceived due to organizational change, emotional conflict and task conflict within this team increases. Furthermore, a significant negative relation is found between perceived change related faultlines and team performance. This indicates that the more faultlines are perceived within a team, the lower the degree of team performance. Findings of this study indicate that organizational managers must ensure that they notice consequences of faultlines within their teams and try to minimize process losses and maximize team outcomes.

Key words: Organizational change, Diversity, Subgroups, Faultlines, Change-related faultlines, Organizational teams, Team conflict, Behavioural integration, Team performance.

Research theme: Managing Diversity

1st supervisor: Dr. J. Rupert 2nd supervisor: Dr. C. Reezigt

Acknowledgement

TABLE OF CONTENT

1. INTRODUCTION ... 4

1.1 Initial motive ... 5

1.2 Problem Statement ... 6

2. THEORETICAL FRAMEWORK... 7

2.1 Diversity and the concept of faultlines... 7

2.2 Organizational change ... 10 2.3 Team conflict ... 12 2.4 Behavioural integration ... 13 2.5 Team performance ... 15 2.6 Conceptual Model ... 17 3. METHODOLOGY ... 18 3.1 Research method ... 18 3.2 Data collection ... 18 3.3 Data source ... 19 3.4 Measurements ... 20 3.5 Factor analysis... 23 3.6 Control variables ... 27 3.7 Reliability analysis ... 28

3.8 Multiple regression analysis ... 28

4. RESULTS ... 30

4.1 Correlation analysis ... 30

4.2 Hypothesis testing conflict ... 32

4.3 Hypothesis testing behavioural integration ... 33

4.4 Hypothesis testing performance ... 34

5. DISCUSSION ... 37

5.1 Key findings ... 37

5.2 Theoretical implications ... 40

5.3 Managerial implications ... 42

5.4 Research limitations and further research ... 43

1. INTRODUCTION

Today’s organizations make extensive use of teams for their work projects, whereby the prevalence of teams in modern organizations is constantly increasing (Tost, Gino, and Larrick, 2013). Given the prevalence of this increased use of teams, it makes maximizing a group’s ability to meet challenges and minimize process losses a key challenge for any organization (Thatcher and Patel, 2012). Next to this trend, diversity in the workplace is a central issue for contemporary organizational management (Choi and Rainey, 2010). In today’s world, diversity is an integral part of teamwork. Significant demographic changes and an increasingly globalized (labour) market have lead to a more heterogeneous workforce (Williams and O’Reilly, 1998). It is important to understand how group diversity relates to group processes and performance and to understand the impact of diversity on organizational outcomes (Martins and Milliken, 1996), since teamwork has become one of the most common forms of organizational collaboration (Cooke, Rosen, and Salas, 2008). Diversity refers to “differences between individuals within a team that may lead to the perception that another person is different from themselves” (van Knippenberg, de Dreu, and Homan, 2004: 1008). Diversity is generally classified by its characteristics: task-related variables; such as tenure, education and functional expertise (Webber and Donahue, 2001), demographic variables; such as gender and ethnicity, and non-demographic variables; such as abilities, attitudes and values (Harrison, Price, and Bell, 1998).

According to Van Knippenberg and Schippers, (2007), diversity can have a significant effect on the functioning of teams and therewith on team performance. Knippenberg et al. (2004), summarize that research on diversity often show findings of inconsistent effects on team processes and outcomes. Influence of diversity on performance can be both positive and negative and the direction of this influence is attributed to the type of diversity. Two general types of diversity are informational/dysfunctional diversity and social category diversity (Williams and O’Reily, 1998). The first type, informational/dysfunctional diversity concerns invisible, work-related characteristics; such as education and functional background. The second type, social category diversity concerns all visible characteristics; such as gender, age and ethnicity. Arising from these divisions, diversity research is mainly based on the following two common perspectives (Jehn, 1995; Knippenberg et al., 2004). First, the informational/decision-making perspective assumes that diversity in education and functional background influences team performance in a positive way, due to a wider range of task-relevant knowledge, expertise and skills. Secondly, the social categorization perspective assumes a negative influence of diversity on performance, due to social categorization. Team members use differences and similarities to categorize others and themselves. Subgroups arising from this categorization have a negative influence on performance.

team, which can lead to diversity faultlines (Bezrukova, Jehn, Zanutto, and Thatcher, 2009). In this research, diversity will be approached from a group dynamic perspective; looking at the role of diversity during team collaboration. Faultline theory describes the process of coalition formulation within organizational teams (Duxbury and Gover, 2012). As groups develop, the variety and potential salience of each member's more subtle characteristics become more likely sources for the alignment of faultlines (Newcomb, 1961). Depending on the similarity and salience of team members' attributes, teams may have many potential faultlines, each of which may activate or increase the potential for particular sub groupings (Lau and Murnighan, 1998). Lau and Murnighan (1998), state that the concept of faultlines opens up the consideration of, for example, demographic differences between subgroups within an overall group. The imaginary line that divides a heterogeneous team into homogenous sub-groups is called a dormant faultline (Lau and Murnighan, 1998). For example, a team with both men and women could have an imaginary split between the two genders. A faultline is activated when these divisions into subgroups are actually perceived by the members of the overall group. Lau and Murnighan (1998) call this perception and awareness of the subgroups by team members the result of the activation process of faultlines.

1.1 Initial motive

1.2 Problem Statement

This study attempts to explore the role of activated faultlines in organizational change context. One of the most compelling insights of previous studies in the area of diversity research is that of group faultlines, the alignment of demographic attributes that lead to hypothetical dividing lines, may affect group processes and performance (Thatcher and Patel, 2012). This research will identify how group faultlines affect team conflict and behavioural integration in context of change. After that, their influence to team performance will be examined. To achieve this, the following research question need to be answered:

Research question:

2. THEORETICAL FRAMEWORK

In this section a literature review of the research is shown. This theoretical framework includes a review of existing research about faultlines, organizational change as possible trigger, team conflict, behavioural integration and team performance. Finally, this literature review results in a conceptual model for this research.

2.1 Diversity and the concept of faultlines

(Lau and Murnighan, 2005; Li and Hambrick, 2005; Bezrukova et al., 2009). A faultline can be distinguished between dormant and activated faultlines (Jehn and Bezrukova, 2010). The following sections will clarify this distinction of dormant faultlines; not (yet) perceived by team members, and activated faultlines; perceived by team members.

Dormant faultlines

dormant faultlines are not activated, they can be present without having any influence on performance (Lau and Murnighan, 1998). The following section will explain what this activation means.

Activated faultlines

Dormant faultlines can be triggered by an event that makes them more visible which results to activating them. Team members realise that their team is split into several homogenous subgroups due to some sort of trigger. Chrobot-Mason, Ruderman, Weber, and Ernst (2009: 1770) define a trigger as “an event involving two or more people from different social identity groups that ignites a replication of societal-based identity threat in an organization”. Lau and Murnighan (1998) mention this activation process as the process results in perception and awareness of the subgroups by team members. Bezrukova and Jehn (2010), further submit that faultline activation occurs when members actually perceive subgroups based on demographic attributes. Summarized, activated group faultlines exist when members perceive two of more separate subgroups in their team. An example is as follows; when a work team exist of members with a different age and experience, there can be a faultline based on age, gender, nationality, education, etc. These faultline can become visible after a discussion how an organization’s intranet should be used to communicate with one another. Opinions could differ due to a person’s age, education etc, and subgroups may show themselves on the basis of these differences. When the members perceive these subgroups, this trigger makes the faultline active.

are actually activated by organizational change and are perceived by team members. Organizational change as a trigger of activated faultlines will be elaborated in following section.

2.2 Organizational change

In modern organizations there is a high rate of continuous occurrence of organizational change (Fedor and Herold, 2008). Organizational change is defined as alterations of existing work routines and strategies that affects a organization as a whole (Fedor and Herold (2008). According to Caldwel et al., (2012) organizations initiate, implement and consolidate changes on a daily basis. Organizational change is an empirical observation in an organizational entity of variations in shape, quality or state over time (Poole and van de Ven, 1995), after the deliberate introduction of new ways of thinking, acting and operating (Campbell, Freese, and Schalk, 1998).

Duxbury and Gover (2012) found that social identities and intergroup dynamics can influence the way that individuals experience organizational change. Intergroup dynamics refer to the system of behaviours and psychological processes occurring between social groups, such as subgroups within a team. While looking at change processes such as a merger, acquisitions, organizational restructurings or employee turnover, these are processes that expand, extinguish or consolidate formal group boundaries (Bartel and Wiesenfeld, 2013). Such contexts often change the way a team performs and who is in a group, which defines and differentiates team members in a new context. When a team is changed due to organizational change, there is a natural tendency that diversity in the team increases, whether that diversity is based on work activities, values and attitudes or demographic characteristics (Bartel and Wiesenfeld, 2013). This increase in diversity within the team, reduces the perceived similarity that creates a coherent unit for group members (Ashforth and Johnson, 2001). For example, when a certain group becomes larger, the ‘new’ members may have different expertise and experience which increases the diversity of members in the team, which results in changed intergroup dynamics and is a certain basis for faultlines.

change may have activated latent faultlines. Furthermore, the scale of organizational change resulted in increased contact between teams, which changed teams and increased diversity. In other words, it would appear that the experience of organizational change in this case activated the existing faultlines. For individuals, it can be very difficult to cope with organizational change. When employees experience organizational change, they often feel a loss of territory, uncertainty about what the future holds, and when they are faced with new change, they may fear failure (Coch and French, 1948). Wanberg and Banas (2000) state that some employees are not bothered by organizational change at all and see this as a chance to grow and learn, whereas others react negatively to even the smallest changes. Therefore, it is not surprisingly that individuals respond to organizational change in many ways. Some embrace it, while others are ambivalent, they can feel (un)comfortable, (dis)advantaged; have a positive or negative opinion about the change and they can resist or participate to the change (Cawsey, Deszca and Ingols, 2012).

refers to the personal consequences of organizational change for employees and if they are disadvantaged or if the change has a small or a positive impact.

Faultlines could be activated during organizational change, and these change related faultlines may be perceived by team members based on one of these four change bases. Previous faultline research shows that activated faultlines are likely to have a negative impact on team processes and team performance (Lau and Murnighan, 1998; Jehn et al., 2003; Bezrukova et al., 2009). In the following section existing literature about team performance, behavioural integration and team performance will be discussed. Furthermore, the relation between perceived faultlines and these team processes and performance will be elaborated, followed by the hypotheses of this research.

2.3 Team conflict

Team conflict refers to the friction, disagreement or discord arising within a group due to beliefs and action of one or more members, which are perceived as unacceptable by the team. It is the process by which people or teams distinguish that actions taken by others have negative effects on their interest (Levi, 2013). In previous literature, conflict is distinguished in three types of conflict, namely: emotional-, task-, and process and conflict (Jehn and Mannix, 2001). These specific types of conflict in combination with faultlines are examined in previous research. Several scholars have explored the relation between subgroups and emotional conflict (O’Reilly and Tsui, 1989; Li and Hambrick, 2005); task conflict (Hennan and Perlmutter, 1986; Kitayama and Markus, 1991); and process conflict (Beersma, Harinck, and Gerts, 2003; Goyal, Maryping, and Robert, 2008). Existing literature shows that perceived faultlines have the following potential effects on these three types of conflict. First, following from the well-known tendency for people to be drawn to, like, and trust others like themselves, and to avoid, distrust, and dislike those who are dissimilar (O’Reilly and Tsui, 1989), abundant evidence exists that demographic differences engender emotional conflict (Li and Hambrick, 2005). Second, as a result of differing experiences and backgrounds, members bring in divergent experience and frames of references and may therefore disagree, for example, on matters encompassing supervisory policies, risk taking, control systems, and urgency, which causes task conflict (Hennan and Perlmutter, 1986; Kitayama and Markus, 1991). And third, as the degree of diversity as variety increases to moderate levels, every subgroup is likely to see issues and opportunities associated with the task from their own vantage point (Eisenhardt, Kahwajy, and Bourgeois, 1997) and these vantage points differ based on their functional backgrounds and their training (Goyal, Maruping, and Robert, 2008). Because of these differences, it is likely that subgroups would disagree with each other on resource allocation within the team, and place their own sub goals above those of the team (Milton, Polzer, and Swann, 2000), resulting in process conflict (Beersma, Harinck, and Gerts,2003).

faultlines, and as the two sides become aware of one another, negative processes such as conflict are likely to arise (Li and Hambrick, 2005). These perceived faultlines may lead to conflict due to team members who break into subgroups and behave in ways consistent with the in-group or out-group (Ashforth and Mael, 1989; Hogg and Terry, 2000). According to several scholars, it is likely that members of subgroups experience frustration, discomfort, hostility, and anxiety between subgroups, which mostly result in team conflict (Gaertner, et al., 1999; Lipponen, Helkama, and Juslin, 2003; Polzer, 2004; Polzer et al., 2006). Lau and Murnighan (1998) propose that perceived faultlines promote processes such as potential conflict and are therefore inherently detrimental. These conflicts are perceived incompatibilities or discrepant views among team members of different subgroups (Jehn and Bendersky, 2003). Conflict, due to perceived faultlines within teams, can cause extreme negative process problems (Brewer, 1996; LaBianca, Brass, and Gray, 1998). Furthermore, Lau and Murnighan (1998) explicitly state that formation of subgroups along faultlines makes a team vulnerable to a variety of conflict-increasing forces. They conclude that greater diversity also tends to provide fertile ground for disputes (Lau and Murnighan, 1998). So, when faultlines emerge, it seems to happen that team members perceive more conflict between team members and their subgroups.

The three types of intra-group conflict most often examined in team research are emotional conflicts, which are disagreements over non-work-related interpersonal issues (Jehn, 1997; Pelled, 1996), task conflicts that are disagreements over work-related issues, and process conflicts that are disagreements over how work gets done. In sum, subgroups within a team foster stereotyping, distrust and in-group/out-group dynamics (Li and Hambrick, 2005), which generates more coordination problems and intra-group conflict, and thus, that group outcomes will decrease (O’Leary and Mortensen, 2010). If faultlines are perceived within teams, it seems to be likely that this results in the formation of one of the three types of conflict. The combination of perceived faultlines and conflict suggest the following set of hypotheses:

Hypothesis 1a: the more faultlines are perceived in a team, the higher the degree of emotional conflict within this team.

Hypothesis 1b: the more faultlines are perceived in a team, the higher the degree of task conflict is present within this team.

Hypothesis 1c: the more faultlines are perceived in a team, the higher the degree of process conflict is present in this team.

2.4 Behavioural integration

Roberts and Weick, 1993; Heo et al., 2007). Hambrick (1994) explained the three components of behavioural integration as follows: joint decision-making, refers to the degree to which members make decisions as a team about key issues (Lin, Hsu, Cheng, and Wu (2011); information exchange is described by Ahuja, Dennis and Robert (2008) as the synthesis of individual team members’ information and expertise through social interactions; and collaborative behaviour belongs to the social dimension of behavioural integration (Lin et al., 2012), as ‘helping each other’ and ‘making things easier for each other’ Dino et al. (2005). When one of these three components is absent, the level of difficulty increases with respect to achieving high performance (Hambrick, 1994).

The specific three concepts of behavioural integration in combination with faultlines are examined in previous research. Several scholars have explored how subgroups affect joint decision making (Kameda and Sugimori, 1995), information exchange (Phillips, Mannix, Neale, and Gruenfeld, 2004), and collaborative behaviour (Cramton and Hinds, 2005; O’Leary and Mortensen, 2010). When a team breaks into factions due to activated faultlines, it has negative repercussions to the joint decision making. These factions are formed for strategic gain, such as dominance over other factions, and represent subgroups within the team. This dominance lead to greater power in team decision making (Ulmer,1965) and members use it in favour of their own subgroup to acquire resources they cannot gain individually. Information exchange is influenced by faultlines during discussion when team members do not exchange all the decision-relevant information they hold, while this should help the team to resolve differences in opinions (Larson, Sargis, and Bauman, 2004). It is likely that the members who are not exchanging all possessed information are doing this in favour for their subgroup, to achieve the best solution for their subgroup instead of the team. Close examination of teams of Gratton, Voigt and Erickson (2007), revealed in many cases a direct result of faultlines within teams, namely failures in collaborative behaviour. Subgroups tend to collaborate only within their own subgroup instead of collaborating with other subgroups. So when faultlines emerge, it seems to happen that team members rarely behave collaborative within their team.

Hypotheses 2a: the more faultlines are perceived in a team, the lower the degree of collaborative behaviour within this team.

Hypotheses 2b: the more faultlines are perceived in a team, the lower the degree of information exchange within this team.

Hypothesis 2c: the more faultlines are perceived in a team, the lower the degree of joint decision making within this team.

2.5 Team performance

Existing team performance literature and the relation between perceived faultlines and team performance will be discussed in this section. Furthermore, there will be elaborated how team conflict and behavioural integration could mediate the relation between perceived faultlines and team performance.

Perceived faultlines and team performance

Activated faultlines within teams are likely to sharpen the boundary salience around faultline subgroups and to increase in- and out-group distinctions of these subgroups (Bezrukova et al., 2009). Jehn et al. (1999) and Pelled et al. (1999) state that members who perceive subgroups, categorize their team members into in- and out- groups. This stereotyping of team members, in-group favouritism and out-group hostility causes conflict and dislike to surface and lead to a decline of cohesion and social integration within the team. (Tajfel and Turner, 1986; Mackie et al., 2000; Webber and Donahue 2001). Within these teams the ‘us versus them’ attitude is likely to arise, and may facilitate fragmentation of subgroups which causes mismanagement, process-, and performance loss (Li and Hambrick, 2005) Lau and Murnighan (2005) state that necessary for accomplishing a task in a common-goal team will be limited in groups with cross-subgroup interactions and information exchanges between subgroups. Perceived faultlines are likely to result in tension and personal attacks and may also decrease efforts to share critical information with the whole team (Sawyer et al., 2006). Team performance is likely to decline due to these deteriorated team processes. When perceived faultlines within teams affect team processes, it seems logical that team performance will decrease. Therefore, perceived faultlines and team performance combined suggest the following hypothesis:

Hypothesis 3a: the more faultlines are perceived in a team, the lower the degree of team performance.

Mediators of perceived faultlines and performance

acceptance of a specified output. However, team performance is not always tangible and an alternative assessment of performance is the inquiring of the team’s perception on their performance trough specific mediating processes. The mediators used in this study to predict performance are conflict and behavioural integration. According to Marks, Mathieu, and Zaccaro (2001), organizations expect that performance of their members is developed through dynamic processes of team interaction. Ideas which would not exist prior to a team’s interactions are produced by these team processes (De Dreu, and West, 2001; Mathieu et al., 2000). The duality of subgroups within a team may provide complementary perspectives that can be valuable, for example, for group problem solving (Jackson, 1992). However, this existing partition also causes process losses (Lau and Murnighan, 1998). Li and Hambrick (2005) state that demographic differences between subgroups aggravate these process losses. Stereotyping, distrust, and discord are a result of large demographic differences between subgroups and all cause raising levels of behavioural integration and conflict (Brewer, 1979; Brewer and Kramer, 1986; Pelled, 1996). Li and Hambrick (2005) state that conflict and behavioural disintegration were both strongly, negatively related to performance.

Conflict and team performance

Lau and Murnighan (1998) and Williams and O’Reily (1998) examined in their research that one common group process that is indicated in the original theory as key to performance losses in teams with perceived faultlines, is conflict. As mentioned before, conflict refers to friction, disagreements and discord within teams. These difficulties are mostly caused by beliefs and actions of other team members, which are seen as unacceptable according to the rest of the team. De Dreu and Weingart (2003) found that negative results from conflict, such as anxiety, affiliation and disgust lower working efficiency and therewith performance of team members. Jehn (1995, 1997) and Amason (1996) also state that interactions are harmed by conflict and this impedes decision quality and performance. Disagreements within a team lead to difficulties in reaching agreements. This lack of consensus reduces team performance, due to the team’s inability to find integrative solutions (Lovelace, Shapiro and Weingart 2001). In short, there can be concluded that conflict within a team have negative repercussions for their performance. When perceived faultlines within teams lead to formation of conflict it seems a logical result that the group will not perform well as a team. Therefore, perceived faultlines, conflict and performance combined suggest the following hypothesis:

Hypothesis 3b: when perceived faultlines promote process conflict within teams, team performance will decrease within this team.

Behavioural integration and team performance

understanding through a joint decision making process (Cockburn and Highsmith, 2001; Staples and Webster, 2008) of members within the group. If any of these three elements is missing, project success will be compromised. Li and Hambrick (2005) found in their research that behavioural disintegration is strongly predictive of poor performance, because while considerable task interdependence exists, groups that do not function as a collective will not perform well. Furthermore, Li and Hambrick (2005) believe that behavioural disintegration provokes breakdowns in team effort and therefore causes poor performance. From field interviews Hambrick (1995) concluded that behavioural disintegration generally causes group problems, including difficulty in formulating and implementing responses to environmental shifts, failure to exchange key information, and poor coordination of activities. When faultlines affect behavioural integration in a negative way, causing behavioural disintegration, it seems to be likely that the group will not perform well as a team. Perceived faultlines, behavioural integration and performance combined suggest the following hypothesis:

Hypothesis 3c: when perceived faultlines deteriorates behavioural integration within teams, team performance will decrease within this team.

2.6 Conceptual Model

Based on this literature review, a conceptual model is set up, which is shown in figure 1. This conceptual model concerns the expected relation between the independent variables, the mediators, and the dependent variable of this study. Duxbury and Gover (2012) found that the experience of organizational change is a certain trigger event for the activation of faultlines. Therefore, this study focuses on team conflict, behavioural integration, and team performance within teams that have experienced organizational change. Perceived faultlines can influence these team processes and team outcomes.

3. METHODOLOGY

This section presents the methodology of this research. First, the research method, data collection and data source is described. After that, measurements will be shown and used analyzing techniques are described. This section is dedicated to show how the reliability and validity of the study is ensured.

3.1 Research method

This study is conducted through quantitative research to quantify opinions, attitudes, behaviour and to find out how the participants feel about subgroups and team processes. Quantitative study offers the opportunity to find out the exact number of team members who think in a certain way. During this quantitative study, a large and sufficient dataset is primary collected through a questionnaire within organizations in the Netherlands. This cross-sectional survey is partly descriptive, but mainly explanatory, and used to assess the consequences of faultlines within teams. The survey tested the theory outlined before and measured all the relevant constructs of this research. This cross-sectional method is relatively quick and easy to conduct which enables it to assess multiple teams in a short period. Furthermore, strengths of this cross-sectional method are; the gathered data on all variables is collected only once, multiple outcomes and exposures can be studied, and it gives the ability to measure prevalence for all investigated factors.

3.2 Data collection

than six members, due to their preference of groups composed of two or three members. Therefore, participating teams should preferably consist of 3 to 7 persons, because there is a higher probability that any faultlines that are present within these teams will be perceived by the members due to their integration preferences. Finally, the third and last criteria; participating teams must have experienced an organizational change that occurred no longer than two years ago. When they are exposed to change within this period, their memories about the change project will still be fresh. These criteria are necessary to enhance the validity and reliability of the research. The population of this research includes all team members of a team. It is rather important to collect data from every single team member of the participating team to get insight in the cooperation within the whole team. Because of the importance and achievement of a high response rate, the surveys were taken hard copy whenever possible and were explained in detail before distribution. Next to that, wherever possible the research was announced within participating organizations via email and newsletters, in order to encourage the cooperation of every team member.

3.3 Data source

To collect data for this research, a questionnaire is set up for the team members of participating teams. The final data set consists of data from two versions of this questionnaire. The second version is improved and elaborated with extra items concerning perceived faultlines. The questionnaire started with a short introduction about the research objective, in order to explain to the participants that the survey concerned team collaboration in a change context. Within this introduction the individual anonymity for participants is also mentioned to enlarge the participants confidentiality. The hard copy questionnaires are taken in a quiet and enclosed room whenever possible, this is to give respondents the opportunity to be anonymous and fill in the survey calm and truthfully. While completing the questionnaire, participants had the opportunity to ask questions if there were ambiguities. Which made their response more reliable and valuable. When the organization preferred to online examination of their team, the online questionnaire was emailed to the respondents. This was also convenient for the respondents, because they could complete the questionnaire in a place and time of their own choosing. This offered the opportunity to collect sensitive information, because it provided anonymity for the respondent.

16 organizations. The team composition of participating teams in the final sample consists of 62% male participants and 38% females, with an average age of 41 years ( ). The education level is relatively high, 65% of the participants completed university. Furthermore, the major nationality of the participants is Dutch (97.8%) and 67% is full-time and 33% is part-time employed.

As mentioned before, the participating teams represent 16 organizations in the Netherlands. Table 1 shows an overview in which sectors these organizations operate. The subject of the experienced change varies from mergers or acquisitions (42%), relocation of organization (20.8%), changes in collaborative teams or organizations (8.7%), reorganisation or centralization (6.6%), to modified procedures or routines (3.1%), reconstructions of building (2.6%), expansion of organization (2%), forced resignations (1%), and establishment of new departments (1%). The reason for the organizational change which the teams experienced ranges from improving the internal collaboration and communication (35%), to ensure continuity of organization (16.6%) and cost-reductions (15.2%), to fostering growth (8.1%), required change by law or external stakeholders (7.2%), and to stay competitive within the market (3.6%). The phases in which these organizational changes were present are distributed as follows: starting phase (4%), middle phase (15.5%), end phase (11.9%) or closed (6.2%), whereby 62.4% of the respondents didn’t know in which phase the change was. When the change started or ended was somewhat unclear for 63.7% and 83.6% of the respondents. However, most of these changes started four months (8.4%) and 24 months (6.6%) before December 2013 and will end within one to four months (both 1.8%) from January 2014, or are never ending changes (6.2%).

Organization Frequency Percent Government 65 30.7 Healthcare 50 23.6 Industry 41 19.4 Consultancy 16 7.5 Education 16 7.5 Hospitality 12 5.7 Supermarket 8 3.7 Entertainment 4 1.9 Table 1. Overview sectors

3.4 Measurements

indicate their answers on a 7-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (7) to respond to the items about the independent variables of this study. While comparing a 5-points and 5-points Likert scale, a greater diversification in the dataset is received with the use of a 7-point scale. Due to this greater diversification, the data provides a more nuanced and comprehensive overview of the results. The answer options for participants are more stretched out when using this scale, whereby neural answers are minimized. For this reasons, the 7-point scale is chosen over the 5-point scale. With this measurement method one person’s score can be compared with a distribution of scores from the sample and the response rate per question will be higher (Cooper and Schindler, 2008), which provides more and reliable data.

Perceived faultlines

A perceived faultline can only be measured with a faultline basis, therefore a scale with multiple bases is used. Since this research is in context of change, this scale consists of eight change-related items. These scales reflect the period where foundations for change-related faultlines have been laid. It reflects the period of experiencing organizational change by the team members, which may be the basis of the formed subgroups. These items give respondents the opportunity to determine on which faultline base they perceive their team split up. The change-related measurement consist of four two item-scales to measure at which change-related basis faultlines are perceived. All questions of these items started with ‘since the change, my team split into subgroups based on..’. First, resistance faultlines are measured with

two

based on Wanberg and Banas’s (2000) modified version of Miller et al.’s (1994)

scale.

all change-related items is shown.

use both datasets for this variable. Therefore, the two items from the second version are

computed into one by taking the mean of these items. There is a slight possibility that this

could bias the results of the two-item scales from the second version. However, it was the best

option to compare the change related items from both questionnaires. This was the only way

to use all gathered data, what resulted in a dataset which is large enough to enhance reliability

and validity for this items.

Team conflict

The three most examined types of conflict within groups are task-, process-, and emotional conflict (Jehn, 1997; Pelled, 1996). These three types of conflict were measured with the intra-group conflict scale (Jehn and Mannix, 2001). Questions as ‘how much conflict of ideas was there in your team?’ and ‘how often are there disagreements within you team about the content of your work?’ measured task conflict. Process conflict was measured by questions such as, ‘how much conflict is there in your team about task responsibilities?’ and ‘how often are there disagreements about the distribution of money and resources?’. Emotional conflict is measured by questions such as, ‘how much relational tension is present in your team?’ and ‘how often do people get angry during work in your team?’.

Behavioural integration

The three components of behavioural integration as explained by Hambrick (1994): collaborative behaviour, information exchange, and joint decision making are measured using the measure of Simsek et al. (2005). The survey consists of eleven items measuring the degree of behavioural integration. Questions as ‘team members are flexible in changing responsibilities to make things easier for each other’ and ‘team members are willing to help each other to complete tasks or to meet deadlines’ measure the first dimension: collaborative behaviour. Secondly, information exchange is measured by a three-item scale of Jiang et al. (2012), which consist of questions such as ‘we maintain a high exchange of ideas in our group’ and ‘when discussing an issue, group members provide plenty of information to help in making a decision’. The third dimension joint decision making is measured with questions as ‘team members fully understand the common problems and needs of other team members’ and ‘team members discuss mutual expectations’. Further questions concerning these dimensions can be found in Appendix A.

Team performance

3.5 Factor analysis

A factor analysis is conducted to gain insight into the dataset, while determining the extent to which measurement overlap among a set of variables exists. Purpose of this analysis is to examine the latent or underlying relations between the variables and to produce the scales earlier described. This factor analysis is a statistical tool used for reduction of dimensions and identifying latent variables inherent in the total set of observed variables Pal and Bhattacharya (2013). The factor analysis increases validity of this research, by controlling whether the measured variables, actually are distinguishable as different variables.

The following criteria are used for all factor analyses concerning this research. First, the analysis are performed based on Eigenvalue greater than one. Second, to minimize complexity of component loadings a Varimax rotation is applied to the analysis. Third, for all items a minimal loading of 0.45 forms criterion is used based on Comrey and Lee’s (1992) criteria. Comrey and Lee (1992) suggest the greater the loading, the more the variable is a pure measure of the factor, whereby loadings higher than 0.45 are considered fair and lower than 0.45 are considered poor. Furthermore, an in-between difference of 0.2 had to be shown to become accepted for double loadings. And finally, the Kaiser-Meyer-Olkin (KMO) score indicates the proportion of variance in the variables that might be caused by underlying factors. A score of at least 0.6 is required to indicate the usefulness of the factor analyse. The Bartlett’s Test of Sphericity tests the hypothesis that the correlation matrix is an identity matrix and indicates that the variables are unrelated, this test requires a score of less than 0.05 of the significance level to indicate that the factor analysis is useful for this data. Besides this factor analyses, a reliability analysis is conducted as well, to examine whether or not the content of the items and questions in the questionnaire are actually measuring that variable. A Cronbach’s Alpha is preferred at 0.70 or higher to show reliable results and a Cronbach’s Alpha of 0.60 is the absolute minimum.

Component Component

1 2 3 4 1 2 3 4

Performance1 0.33 -0.10 -0.06 0.61 Emotional conflict3 -0.25 0.78 0.08 0.05

Performance2 0.32 -0.08 -0.01 0.58 Task conflict1 0.18 0.80 -0.02 -0.23

Collaborative behaviour1 0.40 -0.03 -0.08 0.66 Task conflict2 0.09 0.79 0.03 -0.22

Collaborative behaviour2 0.45 -0.10 -0.02 0.64 Task conflict3 0.02 0.81 0.07 -0.20

Collaborative behaviour3 0.66 -0.02 -0.08 0.53 Process conflict1 -0.22 0.76 0.02 0.06

Information exchange1 0.73 -0.16 -0.01 0.30 Process conflict2 -0.21 0.78 0.02 0.01

Information exchange2 0.77 0.03 0.04 0.16 Process conflict3 0.09 0.53 0.01 -0.16

Information exchange3 0.85 -0.02 -0.07 0.06 Resistance1 -0.02 0.01 0.72 -0.13

Information exchange4 0.77 -0.21 -0.08 0.17 Resistance2 -0.04 0.02 0.71 -0.01

Information exchange5 0.87 -0.05 -0.02 0.10 Resistance behaviour1 0.02 0.01 0.80 0.04

Joint decision making1 0.84 -0.09 -0.07 0.13 Resistance behaviour2 -0.02 0.08 0.77 0.05

Joint decision making2 0.66 -0.19 0.05 0.20 Information1 -0.13 -0.02 0.76 0.08

Joint decision making3 0.63 0.08 0.09 0.11 Information2 -0.09 -0.08 0.76 0.07

Emotional conflict1 -0.18 0.81 0.06 0.09 Personal impact1 0.18 0.26 0.70 -0.29

Emotional conflict2 -0.15 0.79 0.13 0.14 Personal impact2 0.16 0.25 0.63 -0.30

Table 2. Factor analysis dependent and independent variables

Table 3. Factor analysis behavioural integration and conflict

This second factor analysis concerning behavioural integration and performances shows a KMO score of 0.910 and a significant score for Bartlett’s Test of Sphericity of 0.000 and is appropriate for included items. Information exchange1 is loading on both the component collaborative behaviour as well as on the component information exchange with an in-between difference less than 0.20. While considering this item in the questionnaire: ‘almost everyone contributes with good ideas, during cooperating in our team’, the content of this item clearly overlaps with collaborative behaviour. The Cronbach’s Alpha decreased from 0.908 to 0.903 due to elimination of the item, but is still particularly high. Therefore, it is theoretically and statistically supported to exclude this item. Furthermore, all items are loading on their own component, except for joint decision making1, this item is loading on component information exchange. While concerning the question from the questionnaire (i.e. ‘team members would inform each other when their own work influences the work of one another’), there can be assumed that there is some overlap with the variable information exchange. The question is clearly about informing other team members and therefore it is reasonable to accept the combination of the information exchange items and joint decision making1 at this component. The Cronbach’s Alpha of the variable information exchange increases to 0.918 with this addition and is therefore statistically accepted as well. Finally, this factor analysis shows that there is no measurement overlap between performance and collaborative behaviour as well, and therefore belonging items are computed into the variable of the component they are loading at.

Theoretically, the variable conflict consists of three concepts; emotional conflict, task conflict and process conflict. To determine the extent to which these concepts overlap each other, a factor analysis is conducted with all the items of the variable conflict. In the first factor analysis of conflict

Component 1 2 3 4 Collaborative behaviour1 0.18 0.82 0.22 0.13 Collaborative behaviour2 0.25 0.87 0.15 0.09 Collaborative behaviour3 0.40 0.71 0.21 0.30 Information exchange2 0.62 0.25 0.16 0.40 Information exchange3 0.80 0.25 0.09 0.22 Information exchange4 0.82 0.23 0.17 0.11 Information exchange5 0.85 0.19 0.14 0.24

Joint decision making1 0.73 0.16 0.24 0.32

(shown in Appendix B-3) the items are loading on the components of emotional conflict and task conflict, while they should on three different components. Therefore, the factor analysis is theoretically not appropriate and forced into three components.

Component 1 2 3 Emotional conflict1 0.31 0.84 0.24 Emotional conflict2 0.26 0.78 0.36 Emotional conflict3 0.26 0.87 0.24 Task conflict1 0.80 0.35 0.16 Task conflict2 0.79 0.25 0.27 Task conflict3 0.81 0.23 0.33 Process conflict1 0.18 0.29 0.91 Process conflict2 0.19 0.32 0.88

Table 4. Factor analysis conflict

The factor analysis of conflict is now theoretically and statistically appropriate for the included items of the variable, with a KMO score of 0.855 and a significant score for Bartlett’s Test of Sphericity of 0.000. Item process conflict3 is deleted from the analysis, because it is loading on the component task conflict. When considering the question in the questionnaire of this item: ‘how often do you disagree about resource allocation in your work group?’, there can be assumed that this was a difficult question to answer for team members who have had different or minimal knowledge about resources and the allocation of it. Therefore, elimination of this item it theoretically supported. The reliability is increased from 0.907 to 0.913 due to this elimination and therefore statistically supported. As can be seen in table 4, the three concepts of conflict load clearly on three different components, these results are in line with the findings of Jehn and Mannix (2001), and therefore computed in three different variables.

are computed into one variable. The Cronbach’s Alpha of these four items faultlines is 0.836 and therefore it is statistically supported to compute them into one variable. Since information- and disadvantaged are loading on the same component in the factor analysis, these items are computed into one variable as well. This variable is reliable due to a Cronbach’s Alpha of 0.838 and therefore statistically accepted.

3.6 Control variables

Control variables are added to this research to foster internal validity. The control variables task type, goal similarity and team interdependency are often used in faultline literature and therefore also included in this study. Due to the use of this control variables, the analysis of causality between dependent and independent variables can be done more exhaustively. This is a result of the isolation of the variance in the independent variable attributed to the control variables (Malhotra and Grover, 1998). The control variables are measured with three scales. First, task type is measured with a four-item scale to measure this variable. Questions as: ‘how diverse is your job?’ and ‘how predictable is your job?’ are used in this scale. Second, a three-item scale from Jehn (1995) is applied to measure goal similarity. Following question is used for this scale: ‘team members are dependent of each other for information or material in order to fulfil their tasks’. Third, team interdependency is measured with a three-item scale which concerns following questions: ‘this teams has common goals’ and ‘this team knows what is important for our team’ and ‘within this team performed tasks are all inter-related’, based on Campion, Medsker, and Higgs (1993).

The teams comprised in this research had to meet several criteria, as mentioned before in the methods section. These teams must comply with the following definition: “a team is a collection of individuals who are interdependent in their tasks and who share responsibility for outcomes” (Cohen and Bailey, 1997: 241). To control whether participating teams actually meet the terms of this definition the control variables are used. The mean of team interdependency within teams is 4.88 ( ), which shows that the team members of these teams consider themselves as interdependent of other team members. Next to that, the mean of goal similarity is 5.45 , whereby it becomes clear that team members see their team goals similar, as common goals. Therefore, it can be concluded that participating teams are actual teams as required.

3.7 Reliability analysis

In Appendix B-5 is the reliability per variable is shown. In summary, the Cronbach’s Alpha of almost all variables is between and which is higher than the minimum of 0.6. This means that the items of these variables can be summed into one variable. Except for variable task type whereby the Cronbach’s Alpha is . As mentioned before, this variable is not reliable and must be deleted from the dataset.

3.8 Multiple regression analysis

One of the most commonly used statistical models and routinely used in research to gather validity evidence or develop theories is a multiple regression (Skidmore and Thompson, 2010). It is a statistical tool to determine the linear relation between the variables of this research. The general purpose of the multiple regression is to learn more about the relation between the independent or predictor variables and the dependent variable. These multiple regression analysis are shown in the result section of this research. When conducting a multiple regression analysis, the cases-to-independent variables ratio is ideally twenty cases for every cases-to-independent variable in the model (Nimon

Component 1 2 3 Task type1 -0.15 -0.20 0.72 Task type2 -0.13 0.12 0.78 Task type3 0.19 -0.16 0.56 Team interdependency1 -0.08 0.83 -0.22 Team interdependency2 0.02 0.90 -0.07 Team interdependency3 0.37 0.67 0.11 Goal similarity1 0.86 0.10 -0.04 Goal similarity2 0.90 0.12 0.03 Goal similarity3 0.85 0.10 -0.07

4. RESULTS

The results of this study are presented in this section. This presentation of results starts with a correlation analysis of the control-, dependent- and independent variables. After that, this section continues with the testing of hypotheses.

4.1 Correlation analysis

Before conducting the correlation between the variables, first the available data from individual team members is aggregated into group level data. All the constructed variables are aggregated to group level in order to make a correlation analysis at group level possible. The means, standard deviations, and correlation of all variables of the conceptual model and the control variables are shown in the following table. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. Goal similarity 5.45 0.69 2. Team interdependency 4.88 0.87 0.38* 3. Resistance faultlines 2.53 0.68 -0.22 -0.32* 4. Impact faultlines 2.58 0.71 -0.32* 0.23 0.38* 5. Emotional conflict 2.28 0.92 -0.10 0.45** 0.08 0.27 6. Task conflict 2.86 0.97 0.09 0.36* 0.09 0.35* 0.43** 7. Process conflict 2.41 1.08 -0.45** 0.12 0.16 0.31* 0.67** 0.31* 8. Collaborative behaviour 5.03 0.86 0.59** 0.22 -0.13 -0.33* 0.06 0.11 -0.23 9. Information exchange 4.99 0.70 0.54** 0.24 -0.09 -0.02 -0.02 0.28 -0.23 0.53**

10. Joint decision making 4.66 0.64 0.48** 0.19 0.01 0.02 0.07 0.05 -0.07 0.44** 0.66**

11. Performance 5.21 0.72 0.62** 0.19 -0.07 -0.19 -0.11 0.01 -0.33* 0.53** 0.47** 0.40**

Table 6. Means, standard deviations and correlations of the variables ( teams) (*

p < .10; **p < .05; ***p < .01)

The means and standard deviations

faultlines are not strongly perceived by the participants. The three variables concerning conflict have a mean below average as well, whereby the highest mean is 2.86 and refers to task conflict. These means show that there is seldom an emotional, task or process conflict within the participating teams. The three concepts of behavioural integration have a mean above average, whereby the lowest mean is 4.66 and belongs to joint decision making. These means above average indicate that participants agree with the items concerning behavioural integration. Therefore, there can be concluded that team members are willing to help each other to complete tasks or to meet deadlines, maintain a high exchange of ideas, and discuss mutual expectations within their team. Finally, performance has a mean of 5.21 , whereby participants agree with the effectiveness and good performance of the team.

Correlations

In the correlation table it is shown that expected correlations arise between the independent and dependent variables. Three negative correlations can be found between goal similarity and process conflict ; between process conflict and performance ; and between goal similarity and impact faultlines . The strongest correlation is found between emotional conflict and process conflict . Followed by a correlation between information exchange and joint decision making ; and between goal similarity and performance . Cooper and Schindler (2008) point out that interpretations could be impeded by collinearity between variables. These collinearity can entail strong fluctuations of estimated regression coefficients between data samples. According to Cooper and Schindler (2008), coefficients are only acceptable if to avoid multicollinearity amongst variables. The strongest correlations of this research are acceptable because they score below 0.8 and consequently there is no multicollinearity detected.

The focus of this research is to find the association between perceived faultlines at conflict and behavioural integration, therefore correlations are expected between the independent and dependent variables. While looking at the different perceived faultlines and these team processes, the table shows significant correlations between resistance faultlines and task conflict ; process conflict ; and collaborative behaviour . Although only task conflict, process conflict and collaborative behaviour have a significant relation with perceived faultlines, the other variables are nevertheless included in the hypotheses testing based on theoretical relevance as shown in the theoretical framework of this research.

making Although only process conflict correlates with performance, the variables emotional- and task conflict are also concluded in the following regressions based on theoretical relevance.

The control variables goal similarity and team interdependency have correlations with all the variables of the conceptual model. Therefore, the regression analysis is also used to verify these correlations and incorporate goal similarity and team interdependency as control variables, next to the independent and dependent variables.

4.2 Hypothesis testing conflict

In this section it will be tested whether the multiple independent variables influence the dependent variable and whether this is positive or negative. The first set of hypotheses predicts the formation of conflict within a team when faultlines are perceived by team members. A multiple regression analysis is used to examine the influence of perceived faultlines on conflict and to analyze whether or not perceived faultlines lead to a higher degree of conflict. This multiple regression is shown in the following table.

Emotional conflict Task conflict Process conflict

Predictor variable Model 1a Model 1b Model 1 Model 1a Model 1b

Control Team interdependency 0.50** 0.36** 0.34** 0.34** Goal similarity -0.31** -0.06 -0.45*** -0.58*** Independent variable Resistance faultlines 0.24* 0.21 0.23 0.07 0.16 Impact faultlines 0.18 0.06 0.28* 0.19 0.06 0.20 0.29 0.13 0.20 0.30 Adjusted 0.18 0.25 0.11 0.18 0.27 10.59 8.17 6.04 10.70 8.96

Table 7. Multiple regression analysis perceived faultlines on conflict (*p < .10; **p < .05; ***p < .01)

. The multiple regression revealed that the relation between these variables is positive, which predicts a higher degree of conflict when faultlines are perceived. Therefore, hypothesis 1a is accepted, since the regression confirms that more perceived faultlines by team members, result in a higher degree of conflict within teams.

Hypothesis 1b refers to task conflict and comprises the following: ‘the more faultlines are perceived in a team, the higher the degree of task conflict is present this team’. The multiple regression analysis is used to examine the influence of perceived faultlines on task conflict. As revealed in table 7, impact faultlines have a significant positive relation with task conflict . The results show a positive relation between these variables and indicate that whenever more faultlines are perceived this results in a higher degree of task conflict. This is in accordance with the formulated hypothesis and therefore hypothesis 1b is accepted.

Hypothesis 1c concerning conflict within teams comprises the influence of perceived faultlines on process conflict and is as follows: ‘the more faultlines are perceived in a team, the higher the degree of process conflict is present within this team’. The multiple regression executed in order to analyze whether or not the perceived faultlines lead to a higher degree of process conflict. Although the correlation analysis showed a correlation between information/personal impact faultlines and process conflict, the multiple regression analysis does not show a significant relations at all. Hypothesis 1c has to be rejected because of the absence of a significance relation.

4.3 Hypothesis testing behavioural integration

Collaborative behaviour Information exchange Joint decision making

Predictor variable Model 1 Model 1 Model 1

Control Team interdependency -0.01 0.03 0.01 Goal similarity 0.59*** 0.54*** 0.48** Independent variable Resistance faultlines 0.01 0.03 0.12 Impact faultlines -0.16 0.17 0.20 0.34 0.29 0.23 Adjusted 0.33 0.28 0.21 21.96 17,35 12.22

Table 8. Multiple regression analysis perceived faultlines on behavioural integration (*p < .10; **p < .05; ***p < .01)

Hypothesis 2a concerns collaborative behaviour and comprises the following: ‘the more faultlines are perceived in a team, the lower the degree of collaborative behaviour within this team’. The results of the multiple regression analysis, conducted to analyze the influence of perceived faultlines on collaborative behaviour, are shown in table 8. These results show no significant negative relation between resistance faultlines or impact faultlines and collaborative behaviour. So, the relation between perceived faultlines and collaborative behaviour, leads not to a lower degree of collaborative behaviour according to the multiple regression analysis. Although the correlation analysis shows a correlation with different values between impact faultlines and collaborative behaviour, hypothesis 2a still has to be rejected since the regression did not result in any significant relations.

Hypothesis 2b refers to perceived faultlines and information exchanges states: ‘the more faultlines are perceived in a team, the lower the degree of information exchange’. The results of the multiple regression revealed no significant relations to show the influence of perceived faultlines on information exchange. Since no significant results could be pointed out, hypothesis 2b is not accepted.

Hypothesis 2c concerning behavioural integration within teams comprises the influence of perceived faultlines on joint decision making and is as follows: ‘the more faultlines are perceived in a team, the lower the degree of joint decision making within this team’. Examination with a multiple regression concerning that perceived faultlines lead to less joint decision making in teams, did not result in any significant negative relations. Therefore, hypothesis 2c is rejected.

4.4 Hypothesis testing performance

performance, while both affected by perceived faultlines. To analyze the relation between these variables, the three step model of Baron and Kenny (1986) is used. These steps specify the requirements that must be met to form a true mediation relation. Prior to this, all variables are centred by calculating the mean and subtracting the variable from its centred variable.

Dependent variable

Predictor variables Performance

Model 1a Control Team interdependency -0.05 Goal similarity 0.65*** Independent Resistance faultlines -0.30** Impact faultlines 0.11 0.46 Adjusted 0.40 8.16

Table 9. Regression analysis perceived faultlines on performance (*_{p < .10;} **_{p < .05;} ***_{p < .01)}

First step consists of a regression analysis of the perceived change related faultlines on performance, and is used to confirm that the independent variable is a significant predictor of the dependent variable. Hypothesis 3a concerns the relation between perceived faultlines and team performance and comprises the following: ‘the more faultlines are perceived in a team, the lower the degree of team performance’. The results of this regression are shown in table 9, The multiple regression analysis shows that resistance faultlines are negatively associated with the dependent variable performance . There can be concluded that whenever more faultlines are perceived, the lower the degree of team performance. This is in accordance with the formulated hypothesis, and therefore, hypothesis 3a is accepted. Due to this significant relation between perceived faultlines and performance, the first condition is fulfilled. Following steps of Baron and Kenny (1986) are executed only with the variable resistance faultlines, to explore if a mediator exist. The following steps are executed per hypothesis.

were positively associated with the mediator of emotional conflict . Therefore, only the variables resistance faultlines and emotional conflict are included in a regression analysis. Due to the fact that previous results show no significant relation between resistance faultlines and task- or process conflict, these two types of conflict are not included in this regression analysis. Also worth mentioning is that, impact faultlines and task conflict have a significant relation. However, impact faultlines are not accepted as significant predictors of performance and are therefore excluded from the following regression analysis. The regression analysis used to see if emotional conflict is a significant predictor of performance . The results show no significant relation between the variables because . Since these results do not show that emotional conflict are a significant predictor of performance, this hypothesis does not have to be further examined and is therefore rejected.

5. DISCUSSION

In this section the discussion and implications of this quantitative examination about the influence of perceived change related faultlines to team processes and team outcomes will be discussed. The study hypothesized a positive influence of perceived faultlines on conflict and negative influence on behavioural integration the team processes, with would decrease the team outcome as a result. Practical implications, limitations and suggestions for further research will be provided in this section. In the concluding section an answer will be given to the proposed research question:

‘To what extent do faultlines, activated by organizational change, influence team conflict and behavioural integration and what is their influence to team performance?’

Previous research about faultlines was merely focussed on dormant faultlines. This study expands literature about perceived faultlines with multiple faultlines bases in the context of organizational change. The study contributes to the current knowledge about the consequences of perceived faultlines. By testing seven hypotheses, this study examined the potential effect of perceived change related faultlines in teams. Conflict and behavioural integration within teams were investigated as constructs to measure the affected group processes, performance is examined as construct to measure group outcomes. Data from a questionnaire was utilized to examine the influence of perceived faultlines on group processes; conflict and behavioural integration, and group outcomes; performance.

5.1 Key findings