1
Reaping the Benefits of Informational
Dissimilarities in a Post-Merger Context:
The Role of Factional Faultlines
By Annelies Dussel
s1766929 University of Groningen Faculty of Economics and Business
Msc. Business Administration Change Management
2
ABSTRACT
This empirical study examines the information exchange activities of post-merger teams in the framework of group faultline theory. Faultlines are hypothetical lines that may split a team into subgroups based on one or more attributes. Organizational changes trigger these faultlines, resulting in increased team member awareness of the presence of subgroups. Faultline theory proposes that the perception of subgroups negatively affects team processes. A cross-sectional descriptive design was used to test the model with a sample of 18 post-merger newly created teams. The analysis showed no support for the negative consequences of subgroup formation. The perception of subgroups based on the personal attribute concerning pre-merger organizational membership affects intra-team information exchange in a positive manner. Factional affiliations pave the way for team reflexivity and encourage team members to share information for improvement of team performance. As a result, innovative capabilities are increased. The degree of psychological safety experienced within the post-merger teams does not moderate the relationship between intra-team information exchange and team innovativeness. Mergers are shown to entail strong positive consequences on team performance by information recombination, and provide proper means for fostering viability in fast-changing industries. This study contributes to the positive view of diversity in stating that factional diversity perceptions increase team performance by the exposure to new information. To determine the processual effects of factional faultlines longitudinal analysis is needed.
3 CONTENT ABSTRACT ... 2 INTRODUCTION ... 4 Conceptual Model ... 6 LITERATURE... 7 Objective Faultlines ... 7 Faultline Activation ... 10
Mergers and the Potential of Factional Groups ... 11
Faultlines and post-merger intra-team information exchange ... 12
Post-merger intra-team information exchange and the innovative capability of groups ... 14
Psychological Safety and information utilization ... 16
METHODOLOGY ... 17
Participants and Procedure ... 17
Measurements ... 19 Factor Analysis ... 22 Control variables ... 23 RESULTS ... 26 Correlation Analysis ... 27 Hypothesis testing ... 28 DISCUSSION ... 30
Mergers and the value of factional groups ... 30
Post-merger Integration and In-group Bias between Factional Groups ... 32
In-Group Psychological Safety and the Merger Context ... 34
Practical implications ... 35
Limitations and future research ... 36
CONCLUSION... 38
REFERENCES ... 39
Appendix I – Managerial Grid ... 50
4
INTRODUCTION
The rapid pace of technological change in current economies drives organizations to be creative in increasing their innovative potential to stay competitive (McCarthy, 2011). The ability of a firm to anticipate at opportunities for change is one of the most important means in which viability is ensured (Wiersema and Bantel, 1992). One of the key activities that becomes more and more represented is the stimulation of diversified teams to generate innovative ideas. The exposure to different perspectives, approaches, and attitudes is expected to stimulate explorative and flexible thinking (Granovetter, 1973).
Current empirical research on the effects of diversity on team performance has however produced mixed results (Williams and O’Reilly, 1998; Jehn, Northcraft and Neale, 1999). Whereas the pessimistic view states that diversity creates more difficulties for team coordination and team performance, the optimistic view demonstrates that diversity leads to value creation and increased team output (Mannix and Neale, 2005). Because of this inconsistency, Williams and O’Reilly (1998) argued for a more complex framework concerning team diversity, which also counts for contextual aspects and the types of diversity addressed.
A measure of diversity that also includes complexity is group faultlines research, as proposed by Lau and Murnighan (1998). Faultlines are “hypothetical lines that may split a team into subgroups based on one or more attributes“ (Lau and Murnighan, 1998: 328). For instance, a clear faultline exists when the sales agents within a team are recent college graduates and their team mates are designers close to retirement (Bezrukova, Thatcher, Jehn and Spell, 2012). In this team personal attributes overlap can be found in terms of age and functional background. The strength of the existing faultlines depends on the amount of aligned characteristics among team members, and is found to have implications for political processes, communication and coordination in decision-making processes (Lau and Murnighan, 1998; Pearsall, Ellis and Evans, 2008; Bezrukova, Jehn, Zanutto and Thatcher, 2009). Hence, faultlines research allows for team dynamics as a result of multiple attributes, and takes the belonging to multiple subgroups into account (Bezrukova et al., 2009).
According to Nishii and Goncalo (2008), the emergence of subgroups influences the patterns of social interaction that unfold within a team. As a consequence, the degree to which a team is able to capitalize on the different perspectives and skills the diversity offers, is affected by these processes (Nishii and Goncalo, 2008).
5 related to social interactions irrelevant to the task. Lau and Murnighan (2005) support the finding that faultlines directly affect team processes and outcomes, however add that triggering the faultline-related aspects of tasks increases their influence in decision-making processes. Hence, they continue, organizational practices that highlight faultlines might increase polarization, and as a consequence induce more detrimental results (Lau and Murnighan, 1998). As a consequence, faultlines might be more dominant in these situations, and organizations have to count for these effects.
Because the proposed trigger effect is little investigated, this study contributes to diversity theory by analyzing the consequences of stimulation of group faultlines. The analysis combines the examination of group faultlines and their effect on intra-team information exchange, in the context of merger. As mentioned earlier, organizations nowadays search for opportunities to increase their knowledge and capabilities to innovate due to the rapid pace of technological change. A means by which knowledge-intensive firms increase their technical capabilities and enhance strategic renewal is initiating a merger to combine existing information and create synergies between two firms (Cloodt, Hagedoorn & van Kranenburg, 2006; Graebner, Eisenhardt & Roundy, 2010). The success of these explorative initiatives however depends on the actual expertise transfer between newly formed organizational teams (Bouty, 2000). The merger activity as described here can be seen as a trigger of faultlines: new members enter teams, and awareness of personal demographics related to their prior organization might influence the emergence of subgroups (Li and Hambrick, 2005). As a consequence, communication and coordination processes are disturbed or reformed which may complicate the desired information exchange. Analyzing the effect of this a merger on the perception of team faultlines and consequently the intra-team information exchange processes, this quantitative study contributes in the understanding of faultline activation and provides managerial implications for the management of post-merger newly created teams and the subsequent intra-team processes.
The field study concerns merger activity initiated by seventeen firms. A merger is defined as “the combination of two or more separate organizations, with overall management control coming under a single governing body and single chief executive” (Harman & Harman, 2008, p. 100). The organizations under study share one post-merger objective, namely value creation due to recombination of information. A shared characteristic to achieve this goal is the post-merger team member mix-up of members of both former organizations to stimulate intra-team information exchange. Hence, instead of entailing just a ‘formal’ combination of the managing board, the mergers induced the creation of new functional teams to take advantage of expertise dissimilarities.
6 (education, tenure, expertise) in determining the social patterns within a team during the early stages of cooperation. However, they point out, an organizational change that entails uncertainty concerning the resulting opportunities can create faultline activation on other attributes. Especially in the context of a merger, the post-merger combination of organizational members might induce the perception of factional subgroups (Li and Hambrick, 2005). In this sense, the former membership of a particular pre-merger organization might form a faultline base for team split up. This faultline activation in turn can influence the newly formed communication patterns (Tuggle, Schnatterly, and Johnson, 2010). Therefore, in this research demographics as well as less visible team member attributes are analyzed, together with the activation effect of a merger on the perception of intra-team attribute differences. Summarizing, the theoretical gap addressed by this study is the potential activation of factional faultlines by means of a merger and its effect on intra-team information exchange. Furthermore, the effects of this intra-team member information exchange and the corresponding team innovativeness are investigated to gain a better understanding of post-merger team integration.
Conceptual Model
A conceptual model concerning the expected relationships between the independent variables and the dependent variables of this study is provided in figure 1.
Figure 1: Model of the effects of perceived faultlines on team processes, adapted to a post-merger research context
The purpose of this paper is to contribute to existing diversity theory in two ways. First, the triggering role of merging activity on factional subgroup formation is analyzed. Secondly, the interplay between post-merger factional faultline activation and intra-team information exchange activities is examined, which is predicted to influence the innovative capabilities of the teams under study. The research question comprises the following:
To what extent do perceived factional faultlines affect intra-team information exchange and subsequent team innovation in the context of a merger?
7
LITERATURE
Objective Faultlines
Faultline theory is a relatively new approach to team processes, however is argued to provide a very sophisticated conceptualization of the dynamics of team processes (Lau and Murnighan, 1998; Choi and Sy, 2010). Faultlines can be seen as “hypothetical lines, that may split a team into subgroups based on one or more attributes” (Lau and Murnighan, 2005: p. 645). A key assumption of the faultline framework is the discontinuity effect. This effect yields that the internal competitiveness between subgroups is stronger than is the case with interactions between individuals within a team. The intra-team interactions are predominated by the interactions between subgroups (Insko, Schopler, Hoyle, Dardis, and Graetz, 1990; McGlynn, Hardy and Cottle, 2009), which yields that subgroup interactions form the main predictor for work team dynamics.
The conceptualization of subgroups by individuals based on intra-team diversity is largely captured by social identity theory as proposed by Tajfel and Turner (1986). Social identity can be defined as “the individual’s knowledge that he belongs to certain social groups together with some emotional and value significance to him of this group membership” (Tajfel, 1972, p. 292). This definition yields that the identification of individuals with certain group members results in the perception of in-group and out-group members.
Intra-team stereotyping results from a team members’ personal inclination to create a sense of belonging and to foster self-esteem (Williams and O’Reilly, 1998; Nishii and Goncalo, 2008). The social identity theory proclaims that subgroup formation results in the internalization of norms and behaviors of in-group members which become part of the individual’s social identity (Hogg, 2004). The similarity-attraction paradigm entails that increased similarity on demographic attributes with an individual is associated with certain behaviors and in is likely to increase interest in this person (Byrne, 1997). Moreover, the composition of group members can be perceived as a measure of information present in this team (Homan, Greer, Jehn and Koning, 2010). Demographic attributes like education and tenure are regarded by co-members as indicators for the knowledge base and mind-sets of others (Jehn, 1995). Therefore, team members are motivated to gather with team mates who possess the most relevant information for their activities. Furthermore, as a consequence of the in-group attraction, team members perceive dissimilar co-members as being less trustworthy and capable (Williams and O’Reilly, 1998). This leads to more frequent communication and collaboration with the in-group members (Bezrukova, Thatcher and Jehn, 2007). Because of the consequences of in- and out-group perceptions on team processes, diversity issues have to be considered when analyzing team performance.
8 rage or personality are ignored. Picture a team consisting of two female sales assistants of 38- and 40-year old, a 52-year old male IT engineer, and a 49-year old male IT manager. The application of established diversity theories to this case would result into the assumption that the functional knowledge of female sales assistants would not differ from that of male IT service members, or the neglect of age as a base for subgroup formation. These dispersion theories focused solely on the presence of diversity on individual attributes (Bezrukova, Thatcher and Jehn, 2007). Faultline theory is however captured in the alignment approach to diversity. This approach entails that instead of analyzing separate demographics of team members, the interaction between these characteristics should be taken into account (Bezrukova, Thatcher and Jehn, 2007). When applying the alignment approach to the sample team, all personal characteristics like age, gender, and functional background are incorporated in the analysis of team diversity and the resulting subgroup formation. Because the faultline measures take into account cumulative proportions of variance across demographic attributes, it enables to estimate the extent to which group process variability can be explained by the alignment of team members (Bezrukova, Thatcher, and Jehn, 2007).
Faultline bases: social and informational categorization
9 these categories. Hence, social and informational faultline bases are both included for measuring objective faultlines in this study.
Faultline strength and faultline distance
Two specific components contributing to the explanatory power of the faultline model are faultline strength (Fau) and faultline distance (Thatcher et al., 2003; Lau and Murnighan, 2005; Bezrukova et al., 2009). Faultline strength deals with similarities within teams, and refers to “the number of demographic attributes that align within a team” (Zanutto et al., 2010). Picture the earlier mentioned team consisting of two female young salespersons, and two male IT group members. Obvious attribute overlap can be found in the personal characteristics concerning functional backgrounds, gender and age. If, however, the male employees were both IT-engineers, the hypothetical dividing line based on work experience becomes more evident, and as a consequence the strength of the faultline concerning work experience is increased. The example of this team shows that group heterogeneity is a precondition for faultline measures (Meyer and Glenz, 2013). The concept of faultline strength furthermore stresses the proposition of Lau and Murnighan (2005), who argue that teams characterized by moderate diversity are likely to show the most obvious faultlines. This results from the finding that subgroup homogeneity is not likely to be measured when team member diversity is too high. This degree of diversity can for instance be found in a team consisting of a 25-year old female sales assistant, a 52-year old male IT engineer, a 58-year old female project manager and a 32-year old male IT manager. If subgroups were formed on the faultline base of functional background within this team, the alignment of demographic attributes within these subgroups will be less clear compared to the earlier described team (Bezrukova et al., 2009; Meyer and Glenz, 2013). Faultline strength is a relevant determinant, because stronger faultlines are likely to result in strengthened in-group identification, which in turn influences team functioning (Gibson and Vermeulen, 2003).
10 Although faultline theory is a relatively young research area, faultlines have shown to affect intra-team interactions, processes and outcomes. This might be especially the case when faultlines become triggered by external events.
Faultline Activation
Lau and Murnighan (2005) argue that group members can become more aware of existing faultlines when events occur that trigger these faultlines. Authors have investigated the effects of potential faultline-based subgroup formation in relation to team processes and outcomes, like group conflict (Thatcher, Jehn and Zanutto, 2003) decision-quality (Rico, Molleman, Sánchez-Manzanares and Van der Vegt, 2007; Yong-Kwan Lim, Busenitz and Chidambaram, 2012) and group creativity (Bezrukova and Uparna, 2009), and proved significance of the demographic dissimilarity effects. However, Jehn and Bezrukova (2010) show that triggering the faultlines induces even stronger subgroup formation. They define faultline activation as the process by which a potential faultline “is actually perceived by group members as the division of the group into separate subgroups based on demographic alignment” (Jehn and Bezrukova, 2010, p. 24). Stated differently, if organizational events activate the awareness of coworkers of their differences and similarities subgroups are more likely to form (Lau and Murnighan, 2005).
Pearson, Ellis and Evans (2008) investigated the activation of gender faultlines by providing the participants under study with gender-biased or gender-neutral tasks. The team task concerned the development of a new design for an electric razor for men. They found that teams faced with the gender-biased task became divided in gender-based subgroups, with lower levels of team participation and creativity as a result. Homan, van Knippenberg, van Kleef and De Dreu (2007) made faultlines even more evident by communicating the differences between team members before the team work took place. Clear differences in team performance were measured, dependent on the attitude of the team members towards this diversity. Hence, instead of a focus on the degree of diversity within a team, the awareness of participants of this categorization has to be investigated to measure the effects of intra-team diversity (van Knippenburg, Dawson, West and Homan, 2011). A third research, undertaken by Gover and Duxbury (2012) showed that organizational changes can also figure as an external trigger to faultline activation. Their analysis indicated that a large-scale change by means of employee relocation results in increased competition between the in-group – the affected employees, and the out-group – the decision-makers concerning the movement. In this particular case, increased inter-subgroup conflict resulted in minimized change commitment (Gover and Duxbury, 2012).
11 these faultlines by a triggering contextual event. However, in the case of a merger, new teams are formed and hence dormant faultlines are not present. Therefore, to analyze the activated faultlines, objective demographic characteristics of the affected employees and the strength and distance of these faultlines are taken into account as control variables. The potential occurrence of faultline activation is analyzed among 18 teams of four distinct organizations that have been affected by a merger in the past two years.
Mergers and the Potential of Factional Groups
Li and Hambrick (2005) recognize the existence of subgroups before a team is organized. Although this sounds contrary to reasoning, this phenomenon can occur when new teams consist of team members of whom several have collaborated before. An example can be found in the formation of joint venture teams (Li and Hambrick, 2005). Common in this process is the equal assignment of employees of both parent organizations for the management of the JV. Inevitably, collaboration between the new JV members is required to achieve the goals of the newly created venture. The combination of members of both former organizations is argued to result in implementation of best practices (DePamphilis, 2011). Unique to this team formation is that this process can be described as the combination of factional groups (Li and Hambrick, 2005). Li and Hambrick (2005, p. 794) define factional groups as “groups in which members are representatives, or delegates, from a small number of social entities and are aware of, and find salience in, their delegate status”. This entails that the members of both firms entering the new team already perceive themselves as constituting a group.
Picture, for example, the recent television joint venture created by Philips and TPV Technology in April 2012. As stated on their website, the collaboration is initiated to combine the innovative and design capabilities of Philips with the strong production capacity of TPV (Philips, 2012). The employees assigned to this new venture are likely to have invested socially in their former organizations (Li and Hambrick, 2005), may have experienced organizational successes together (Forbes, Borchert, Zellmer-Bruhn, and Sapienza, 2006; Yong-Kwan Lim et al., 2012), and as a natural consequence constitute existing groups. However, the newly created joint venture induces a new organizational identity to be adopted by the affected employees. As a result, the very existence of an embedded identity related to the prior organization is likely to stimulate stereotyping (Terry and Obrien, 2001). The pre-existing faultlines between prior employees of TPV and Philips might result in members’ activities purely targeted at improvement of the in-group power within the new venture (Terry and Obrien, 2001; Li and Hambrick, 2005). Hence, factional affiliations between team members lead to in-group and out-group perceptions between pre-merger organizational members, with inhibited team processes as a result.
12 (Veltrop, Hermes, Postma and De Haan, 2012). The existence of clear organizational differences might increase the in-group bias (Li and Hambrick, 2005). In the case of the Dutch Philips and the Chinese TPV, the work-related knowledge team members possess and the capabilities related to their work experience might form a base of subgroup formation. Differences in those specific organizational attributes are likely to result in dissimilarities in relevant employee capabilities and their daily operations. When translating those organizational characteristics to daily organizational life, post-merger team members are likely to perceive different behaviors in terms of working practices and routines, area of expertise, and the mere fact of ‘originally belonging to the other organization’ (factional groups).
As mentioned, the higher the degree of dissimilarity between the merging factional groups, the higher the likelihood that they will perceive each other as ‘opponents’ which inhibits team collaboration. Li and Hambrick (2005) however did not investigate whether the team members became more aware of the demographic differences specifically due to the new team formation in the joint venture. Hence, actual faultline activation is not yet analyzed in this context. Furthermore, a merger between two firms is likely to affect a higher degree of employees compared to a JV, because instead of affected departments, the whole organization is likely to experience post-merger consequences. This increase of employee involvement might hence induce diverging results (Li and Hambrick, 2005). In this analysis for both objective and perceived faultlines the factional faultline base are incorporated.
Faultlines and post-merger intra-team information exchange
Informational diversity is one of the main benefits of diversified teams. Informational diversity refers to “differences in knowledge bases and perspectives that members bring to the team” (Jehn, Northcraft and Neale, 1999, p. 743). A higher degree of intra-team differences based on information-related characteristics induce a higher degree of task-related information and relevant mixture of skills present in that team (Bezrukova et al., 2009). The suggested benefit entails that differences in tenure, education and expertise result in improved team performance (Schippers, Den Hartog, Koopman and Wienk, 2003), due to innovative recombination of information (Bresman, Birkinshaw and Nobel, 2010).
Some authors, like Nonaka and Takeuchi (1995), argue that mastering the diverse perceptions and opinions within a workgroup is key in tomorrow’s marketplace. This is also in line with the positive view of diversity, as defined by Mannix and Neale (2005). This theory suggests that team diversity provides high potential for value creation, even though it might challenge intergroup interaction. Hence, coordinating subgroup information exchange processes is of main interest of current managers.
13 effectively use their knowledge base (Boone and Hendriks, 2009). As mentioned in the introduction, information exchange is most likely to happen among those who know what each other knows (Yuan et al., 2009). This concept is often referred to as transactive memory, which consists of two components: (1) “an organized store of information that is contained entirely in the individual memory systems of the team members, and (2) a set of information-relevant transactive processes that occur among team members” (Wegner, Giuliano, and Hertel, 1985, p. 256). In other words, transactive memory deals with the awareness of employees on the information available within the team, and the capability to access and use this information when required. The presence of a transactive memory system enables a team to integrate the available information quickly, which facilitates the application of relevant information to team activities (Lewis, 2003). Because the main objective of the merging firms studied here is synergy creation by recombining information present in both firms, intra-team information exchange is an important precondition.
The information exchange process depends strongly on the willingness of individuals in a team to share the information they have acquired or created (Bock et al., 2005). Szulanski (1996) refers to the difficulties of information transfer in terms of ‘stickiness’. He argues that the tacit nature of information hinders the exchange process internally, because the knowhow cannot be easily articulated (Teece, 1986). Hence, to overcome this stickiness, active participation in information exchange of the members that possess the relevant information is required. For instance, employees reluctant to share their information in concern of their own power base increase the stickiness (Bock et al., 2005). Other drivers of stickiness can be found in characteristics of the context of information exchanging initiatives (Szulanski, 1996).
Consider the occurrence of faultline activation after initiating a merger. A merger affects the degree of resources available for an organization, in terms of processes, products and information (Barney, 1986). As a consequence, existing information exchange structures are likely to become inappropriate, and new connections between organizational members have to be created to foster collaboration (Yoo, Lyytinen and Heo, 2007). This large-scale organizational change results in high uncertainty among employees, who might feel anxious about the consequences for their work, and experience high levels of stress (Terry and Callan, 1998).
14 the duration of employees’ collaboration history increases their trust levels significantly. As a consequence, information stickiness is increased. The in-group is likely to be perceived as more credible and trustworthy, and hence reliance on out-group information becomes less obvious. Team members might question the accuracy of the out-group knowledge or may aim at increasing the in-group power by only making use of information from in-group members for decision-making (Rau, 2005).
Factional faultlines weaken transactive memory systems of teams in two ways: first of all, the awareness of the information available is decreased due to new membership, and secondly, the willingness of exchanging this information is also decreased due to high uncertainty present in the new formed group (Easterby-Smith, Lyles and Tsang, 2008). Therefore, the existence of diversified subgroups based on factional faultlines is likely to impede intra-team information exchange. Hence, the hypothesis derived comprises the following:
H1: The perception of factional faultlines negatively influences the degree of intra-team information exchange in post-merger created teams.
Post-merger intra-team information exchange and the innovative capability of groups
A current trend in global markets is the increased reliance on information for value creation, and these knowledge-driven industries require organizations to constantly reinvent themselves to stay competitive (Liu and Philips, 2011). Many industries become characterized by increased connectedness between firms, to facilitate the exploration and exploitation activities within these industries (Auh and Menguc, 2005; Mom, Van den Bosch and Volberda, 2007; Colombo, Laursen, Magnusson and Rossi-Lamastra, 2011). The firms in this study undertook a horizontal search for external knowledge to increasing their capabilities and knowledge base, by means of a merger. Whereas internal information transfer is already mentioned as one of the desired outcomes of these collaborations, the shared long-term aim is synergy creation in terms of innovative thinking and the generation of new ideas.
15 The process of capturing and applying knowledge is a first step in organizational learning. Organizational learning is defined as “the process of improving actions through better knowledge and understanding” (Fiol and Lyle, 1985, p. 803). In any organizational learning process two aims can be distinguished, namely exploitative and explorative learning. Whereas the first refers to single-loop-learning and is more a kind of incremental, adaptive learning, explorative learning concerns the external discovery of new, alternative practices (Liao, Fei and Liu, 2008). Hence, initiating a merger can be seen as a strategy of explorative learning, because external knowledge sources will become accessible to the merging firm, and innovative practices can be intensified.
Collaboration of organizations with significant differences in skills, information, and organizational cultures provides a unique explorative learning opportunity for both parent organizations (Inkpen, 1998). Many firms already showed increased performance as a result of external knowledge acquisition, whether by means of a merger, alliance or network. For instance, the merger between Disney and Pixar resulted in the creation of innovative and successful movies, due to the combination of information concerning animation technology and marketing capabilities. Furthermore, the merger between General Dynamics and Anteon in 2006 induced a fast introduction of new, improved products, by combining knowledge on old and new technologies for military vehicles. Both firms refer to bridging the prior existence of knowledge gaps between them as being the basis for their post-merger success (Disney Post, 2013; General Dynamics Information Technology, 2013). Many academic authors endorse this finding, by stating that the external knowledge acquisition contributes to the innovative potential of merging firms (Inkpen, 1998; Prabhu, Chandy and Ellis, 2005; Liu and Zou, 2008), especially for innovation-driven firms (Wagner, 2011). Moreover, from an exploration perspective, increased diversity between merging partners will increase the opportunity of cross-fertilization effects (Dittrich, Duysters, De Mand, 2007). Hence, mergers provide the perfect condition for organizational learning, with improved innovative activities as a highly potential result.
16 products or procedures, new to the relevant unit of adoption, designed to significantly benefit role performance, the team, the organization or the wider society” (West and Far, 1989, p. 16). Whereas collective information exchange does not automatically result in perfect team information repositories (Yuan et al., 2010), communication is a necessary precondition for innovative initiatives.
The above arguments show that a merger provides many opportunities for the creation of innovative capabilities, due to the exposure to new information, ideas and resources. Post-merger intra-team information exchange is likely to lead to cross-fertilization, experimentation, and new idea implementation, which are all characteristics of team innovativeness. Therefore, the following hypothesis can be derived:
H2: The degree of merger intra-team information exchange is positively related to the post-merger innovative performance of teams.
Psychological Safety and information utilization
One particular supporting mechanism of new idea implementation in teams is a positive team atmosphere that promotes creativity and risk taking (Lee, Swink, Pandejpong, 2011). Voicing new ideas is a risky endeavor, because new practices are more likely to fail than embedded practices. This phenomenon can be characterized as ‘psychological safety’, which is defined as ‘a shared belief held by the members of a team that the team is safe for interpersonal risk taking’ (Edmondson, 1999, p. 354). Psychological safety is recognized as a prerequisite for a team to reflect critically on current practices and ideas of co-members (Rupert and Jehn, 2008).
Put it differently, the risk of highlighting current errors or new practices, has the potential for personal embarrassment if these are not adopted by the team (Edmondson, 1999). If team members are intimidated by these particular threats, they are less likely to introduce their new ideas. A supporting team atmosphere is more likely to promote innovative practices as an outcome of information combination.
17 likely to result in strong commitment to subgroup goals and feeling safe enough to trust each other with important group activities (Moreland and Levine, 2002). However, due to the perception of in-group and out-in-group members, the same level of safety is unlikely to be encountered within the overarching work team (Lau and Murnighan, 2005). As a consequence, post-merger newly created teams are less likely to be characterized by a supportive atmosphere, and taking risks might be difficult to pursue.
Besides the introduction of new ideas, the actual adoption of these innovations is also influenced by the degree of psychological safety within a team. The quality of information processed in work teams is often associated with the quality of the relationship with the team members offering this information (Baer and Frese, 2003; Subramaniam and Youndt, 2005). Analyzing the source of the information influences the degree to which the earlier shared information is appreciated, and consequently applied for innovative activities. This is supported by the study of Edmondson, Bohmer and Pisano (2003), who found that psychological safety is strongly associated with perceived usefulness of proposed changes. Furthermore, Scheepers, De Jong, Wetzels and De Ruyter (2008) found that psychological safety entails a direct positive effect on group-wide adoption of newly introduced groupware. Taken these considerations into account, it is likely that the innovative output resulting from post-merger information exchange is strongly influenced by the degree of safety experienced within the work team. The following hypothesis can be derived:
H3: Psychological safety in a team moderates the effects of intra-team information exchange on team innovativeness, such that team innovativeness resulting from intra-team information exchange is higher for teams in which psychological safety is perceived as high.
METHODOLOGY
This study entails a descriptive, cross-sectional research design to test the faultline activation model of Jehn and Bezrukova (2010) in the context of a merger. The unit of analysis concerns post-merger newly formed teams. In this quantitative study, primary data is collected by means of a questionnaire for the analysis of faultline theory and its potential consequences in merger contexts. For theory testing, quantitative studies provide benefits. The cross-sectional method provides the opportunity to gather data on multiple teams in a relatively short period. Furthermore, the analysis of multiple teams of seven merged firms supports generalizing the results to a larger sample (Cooper and Schindler, 2008; Myers, 2009).
Participants and Procedure
18 parent firms. A requirement is the combination of at least two members of one parent firm and one of the other merged firm. Team size was determined to be at least three, with a maximum of fifteen team members.
In terms of procedure, the first contact was initiated by email, to explain the research objective and the contribution of, and benefits for the participating organization. Once interested, a round of phone calls was initiated to further explain the procedure of data collection and the content of the questionnaire. After receiving confirmation of participation, the questionnaire was distributed hardcopy and handed out in person to 52 percent of the teams. The remaining sixteen teams received the survey digitally via Google Docs. A short introduction at the questionnaire noted that the research objective concerned team collaborations in a change context and emphasized individual anonymity for the respondents. Two visit rounds per company with the hardcopy version resulted in a high response rate of 93%. For the electronically distributed files, a 57% response rate was achieved. For each team, a response rate of at least 80% was required because of team level data aggregation. Twelve teams were excluded on this base. Two of the 80 completed questionnaires were discarded due to missing data (>30% of the values per respondent). Congruous factional group analysis within merged teams requires the selection of teams consisting of at least two members of one of both pre-merging firms. Due to poor team selection, 8 teams did not meet these requirements, and were excluded from the analysis. Complementary, a team grid comprised of all team members and their demographic features was collected per team to analyze the objective demographics of the missing respondents (see Appendix I). Merger characteristics of the seventeen organizations in the sample were compared to check for nonresponse bias, and no bias was detected.
19 external validity (Van Aken et al., 2007). However, the seventeen organizations involved are all Dutch organizations, and the national culture could result in team collaborations not representative for international institutions
Measurements
Existing scales were used for measurement of the variables included (Appendix II), however translated to Dutch, because of the nationality of the respondents. As mentioned earlier, objective faultline category measures are applied as a control variable, to check for faultline activation.
Objective faultlines. To map the objective faultlines present in the teams, the assigned
team leaders were requested to complete a team grid on team member attributes (Appendix I). Information on objective characteristics of the team members was collected to measure the factional faultlines, and categorized for analysis as presented in table 1. As mentioned, alignment between factional faultlines and the earlier mentioned social and informational faultline bases is likely to produce more detrimental effects on the social dynamics of a team compared to the measurement of solely factional faultlines (Veltrop, Hermes, Postma and De Haan, 2012).
Faultline Category Team member attributes
Factional faultlines Pre-merger organization, tenure
Social faultlines Pre-merger organization, gender, age
Information-based faultlines Pre-merger organization, tenure, educational level, work experience
Table 1 – Categorization of Objective faultlines
For the faultline construct the cumulative proportions of variance across the variables had to be measured (Bunderson and Sutcliffe, 2002; Thatcher et al., 2003), as a base for estimations of attribute clusters present within the teams. These objective faultline measure scores are as a consequence team-level variables. The score was computed with the common used algorithm as developed by Thatcher et al. (2003) (Lau and Murnighan, 2005; Bezrukova, Spell and Perry, 2010). A team can be divided in subgroups based on present faultlines, in a total of S= 2n-1-1 ways. The model is presented in the figure below.
Figure 2: The faultline algorithm as developed by Thatcher et al. (2003)
20 the subgroup is denoted with ̅.jk. Finally, the members per subgroup k are captured in . The Fau represents the strength of faultline divisions, which was calculated as proposed by Bezrukova, Jehn, Zanutto and Thatcher (2009). Fau can have values between 0 and 1, where higher values represent stronger faultlines. Teams with high values of Fau are likely to be divided in very homogeneous subgroups (Thatcher et al., 2003). A clustering algorithm (Jobson 1992; Sharma 1996) was applied in this study to find the strongest split present in teams. Subsequently, faultline distance was measured, which represents the Euclidean distance between the sets of averages within the team and subgroups, or differently stated, the extent to which the subgroups diverge as a result of differences across them (Zanutto, Bezrukova & Jehn, 2010). The distance formula comparing two subgroups comprises the following: √∑ ( ̅ ̅ ) 2. The faultline distance is measured
along the strongest faultline split per team resulting from the Fau analysis, and measures of this variable can represent values on a scale of 0 to ∞. Similar to Fau, a higher faultline distance measure indicates a higher distance among subgroups on the particular attribute. To ensure that all objective information on potential faultlines within a team is analyzed, faultline distance is treated as a moderator of faultline strength in this study (Zanutto et al., 2010). Hence, an interaction term is created to analyze the potential faultlines that split up a team, together with the differences between those teams. When analyzing this interaction term, also the mean effects of the variables are incorporated. Furthermore, teams can potentially divide based on coalitional splits (e.g. subgroups of at least two team members) or token splits (e.g. subgroups consisting of one team member, Zanutto et al., 2010). Hence, for all three faultline base measures (factional, social, information) both coalitional and token Fau and Distance measures were calculated.
Activated Faultlines. Activated team faultlines are firstly assessed with an 8-item scale to
measure the perceived existence of subgroups within a team, as proposed by Jehn and Bezrukova (2010) (i.e. At meetings of our team subgroups often sit together, during the work the team is divided
into several sub-groups). Participants were asked to indicate their answer on a 7-point Likert scale,
ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (7). For the scale a method of alternate-form reliability is applied (Litwin, 1995). The construct is measured by making use of eight items addressing the same question in similar, but not identical ways. The resulting scale from the factor analysis described below shows high internal consistency with a Cronbach’s alpha of 0.95 (Litwin, 1995), and hence indicates sufficient internal consistency for using the eight items as a measure of activated faultlines.
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into subgroups based on: demographics – e.g. age, gender, functional background, and behaviors – e.g. way of working, personality) (Jehn and Bezrukova, 2010). Relevant to this specific study, another
potential faultline base measuring factional groups was added (i.e., Since the change, my team split into subgroup based on the different partner organizations for which team members were
pre-merger employed). Again a 7-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly
agree’ (7) was provided. The faultline bases concerning working style (M = 4.16), team tenure (M=4.58), and the newly created pre-merger organization base (M=4.32) revealed the highest scores. Furthermore, 26.9% of the respondents indicated the pre-merger organizational background as the most significant base for subgroup formation. Hence, merger effects are measured. Besides the predetermined bases included in the questionnaire, the respondents were able to formulate additional characteristics, on which they perceived subgroup formation was based. However, few additional faultline bases were added, and hence this item was not incorporated in further analysis.
A variable of perceived factional faultlines was created by combining the activated faultlines scale with the merger-related faultline bases as indicated in the theoretical section, namely: way of working, pre-merger organization, team tenure and expertise. The combination of these scales provides a holistic view on the persistence of subgroups and faultline bases within the sample teams.
Dependent variables
For all dependent variables, participants were asked to indicate their answer on a 7-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (7).
Intra-team information exchange. The instrument used for the measurement of
information exchange is developed by Jiang, Jackson, Shaw and Chung (2012). The items cover both quality and quantity of intra-team information exchange. An item selection of the original scale is made to prevent the survey of becoming too exhaustive. To ensure construct validity, only items with a component score of at least 0.7 in the original study were incorporated in the questionnaire (e.g. When discussing an issue, team members provide plenty of information to help in making a
decision; We maintain a high exchange of ideas in our team). The full-item scale passed the threshold
of internal consistency (α = 0.7) (Litwin, 1995).
Team innovativeness. Four items adopted from De Dreu (2006) and Anderson and West
(1998) were used in this study to measure team innovativeness. The items comprise the following:
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this is an innovative team. Item two was reversed for analysis, and the final scale showed high
internal consistency (α = 0.78).
Psychological Safety. Edmondson (1999) provides a 7-item scale for psychological safety
in teams (e.g. “If you make a mistake on this team, it is often held against you” and “It is safe to take a
risk on this team”). Three negatively scored items of the scale were reversed before factor analysis
was conducted. The final scale variable included the first six items, with a Cronbach’s alpha of 0.75 indicating sufficient scale reliability. The analysis concerning the creation of the factors is described below.
Factor Analysis
A factor analysis was conducted to reduce data for analysis, and to produce the above described scales. A general rule is the presence of at least five respondents for each item incorporated in the factor analysis (Hair, Anderson, Tatham, and Black, 1998). Consequently, the limited sample induces separate testing of scales and item loadings. Table 2 shows the rotated scores of dependent variables information exchange and team innovativeness together with independent variable perceived faultlines.
With a KMO of 0.823, and a significant score for Bartlett’s Test of Sphericity, factor analysis was appropriate for the included items. A Varimax rotation method was applied to minimize complexity of component loadings. A minimal loading of 0.4 forms a criterion for all items, and for double loadings an in-between difference of 0.2 had to be shown to become accepted.
Table 2 – Factor analysis IV and DVs Table 3 – Factor Analysis DVs and moderator variable Forced into three factors, Eigenvalue > 1.00 Forced into three factors, Eigenvalue > 1.00
23 The factor analyses resulted in more components than theoretically required, as indicated by the related scree plots and Eigenvalue measures. However, for both cases the additional fourth component solely comprised of the second item measuring team innovativeness (> 0.4). As a consequence, factors were forced at a fixed number to increase interpretability.
First of all, the independent variable measuring the presence of subgroups in the work team clearly showed high loadings for one scale. A Cronbach’s alpha of 0.95 indicates high scale reliability, and hence a factor measuring subgroup formation was created. A difficult issue was present in the items measuring intra-team information exchange. Double loadings were found for two of the five items in both analyses on the team innovativeness component. This intersection is clearly demonstrated by evaluating the measured items. Whereas information exchange is primarily concerned with the exchange of information, implementation of new methods as described by team innovativeness requires information on these procedures to be exchanged. The two specific items of Jiang et al. (2012) are however the only items of the scale particularly focused on the actual exchange of information. The remaining items are more concerned with the specific team members contributing to the information exchange. Excluding them entails low coverage of the actual concept of information exchange. This was also shown by the Cronbach alpha that indicates the reliability of the scale, which decreases from 0.70 to 0.65. Hence, to ensure construct validity, the original scale items were incorporated in the newly created factor measuring intra-team information exchange.
A moderator variable concerning psychological safety was created (α = 0.72). As shown in table three, item7 was excluded due to poor component loading (< 0.4). This exclusion also lead to a better loading of item 2 of Team innovativeness (> 0.4). The item appeared to be more individual-related than focused on team atmosphere, which theoretically supports exclusion. Deletion of this item was also supported by the reliability analysis of the scale, since an increase of internal reliability from α = 0.71 to α = 0.75 is measured. Concluding, all four items of the original team innovativeness scale were used to create the factor variable (α = 0.78).
Control variables
Control variables like goal similarity, task interdependency, task type and team identification are often used in faultline research, and therefore, also included in this analysis to foster internal validity. By including these controls, the variance in the independent variable attributed to these variables is isolated, and hence causality between the independent and dependent variables can be analyzed more thoroughly (Malhotra and Grover, 1998).
24 interdependency. Interdependency in terms of team tasks is argued to increase motivation and subsequently team performance due to an increased sense of shared responsibility (Kiggundu, 1983). Affective commitment with a team can reinforce a feeling of in- and out-group members (Van der Vegt, Van de Vliert and Oosterhof, 2003). Therefore, a variable measuring team identification was added to count for this variance, using a six-item scale. A factor analysis concerning the control variables was used (KMO = 0.68). Results are presented in table 4.
Components 1 2 3 TaskInterdependency1 -0,08 0,85 -0,12 TaskInterdependency2 -0,07 0,89 -0,12 TaskInterdependency3 -0,09 0,70 0,12 Team Identification1 0,29 0,41 0,21 Team Identification2 0,68 0,06 0,28 Team Identification3 0,80 0,07 0,20 Team Identification4 0,68 -0,16 0,19 Team Identification5 0,67 -0,11 -0,07 Team Identification6 0,63 -0,01 -0,04 Goal Similarity1 0,01 -0,05 0,81 Goal Similarity2 0,07 0,03 0,79 Goal Similarity3 0,39 0,02 0,55
Table 4 – Principal Component Analysis control variables Components based on Eigenvalue > 1.00
As shown in table four, the first item of the team identification scale entailed a high loading on the task interdependency component. This particular item (‘I consider the team as important’) might be interpreted in relation to the team tasks performed. Because exclusion of item 1 resulted in an increase in internal scale reliability (Cronbach alpha increases from 0.72 to 0.75), this item was not incorporated in the factor Team Identification.
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RESULTS
As mentioned in the former section, a distinction can be made between objective faultlines measuring coalitional splits, and objective faultlines measuring token splits. For this particular dataset, these distinct split-ups entail important implications. Of the 18 teams incorporated in this study, six teams comprise of three members, and therefore only token splits can potentially be detected within these teams. Relevant differences in Fau and distance measures furthermore occurred for four additional teams, when including or excluding token splits. An example is presented in table 5.
Team
member Gender Age Nationality Educational Level Organizational Tenure Pre-merger organization Subgroup
1 1 52 Dutch 5 16 7 1 2 1 38 Dutch 5 7 8 3 3 1 32 Dutch 6 16 8 2 4 1 52 Dutch 6 16 7 1 5 1 56 Dutch 5 16 7 1 6 1 32 Dutch 6 16 8 2
Factional Fau based on coalitional splits: 0.41, Factional Distance based on coalitional splits: 2.37 Factional Fau allowing for token splits: 0.94, Factional Distance allowing for token splits: 4.54
Table 5 – Example: Demographics of a team indicating the subgroups based on factional faultlines
The team in table 5 consists of six team members, and the pre-merger organization faultline base indicates a coalitional split of two teams of three members. However, the factional faultline measurement also incorporated organizational tenure, which appeared to be the strongest split and results in the occurrence of token splits in this team. Similar results were found for social and informational faultline measures for the sample teams, with the presence of token splits in eight and seven teams respectively.
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Correlation Analysis
Table 6 provides the means, standard deviations, and correlations for all variables of the conceptual model (figure 1) and the control variables. The objective faultline measures are based on subgroup formation allowing for token splits.
Table 6 – Means, Standard Deviations and Correlations of the variables (n = 18 Teams), *p < .10; **p < .05; ***p < .01
As expected, correlations arise between the independent variables and dependent variables. The perception of factional faultlines in a team correlates significantly with information exchange (r = 0.50, p < 0.05). Furthermore, a correlation is found between task-relevant information exchange and team innovativeness (r = 0.56, p < 0.05). Few correlations arise between the Fau and Distance measures and the dependent variable task-relevant information exchange. The informational faultline category incorporating the forms the exception, and entails a negative correlation in terms of faultline strength (r = -0.46, p < 0.10). A negative correlation can also be found between the social distance measure and information exchange (r = -0.49, p < 0.05).
The strongest correlation between independent variables is found for factional faultline strength and social faultline strength (r = 0.64, p <0.01). Collinearity between variables can entail strong fluctuations of estimated regression coefficients between data samples (Cooper and Schindler, 2008), which impedes interpretation. However, the coefficients for this correlation are acceptable (r < 0.8) and expected because the distinct distance measures incorporate similar demographics like pre-merger organization and/or tenure. As a consequence, actual multicollinearity is not detected. Although the control variables task type and team identification show no significant correlations with information exchange, they are nevertheless included in the regression based on the theoretical relevance as depicted in the methodology section. This analysis
28 does not satisfy the sample threshold of twenty teams team-level research (Greer, 1991). Due to this sample limitation, the hypotheses are tested separately the regression.
Hypothesis testing
The first hypothesis comprises the following: Activated factional faultlines as a result of a
merger negatively influence intra-team information exchange. Faultline strength and the interaction
variable distance measures for all three categories of objective faultlines (factional, social and informational) are incorporated in separate regression models as control variables. Subsequently, the perceived faultlines variable is added per model to analyze activation effects as a result of a merger. Findings for the separate regression models are presented in table 7.
Model
1a Model 1b Model 2a Model 2b Model 3a Model 3b Model 4a Model 4b Model 5a Model 5b Model 6a Model 6b Model 7a Model 7b Control variables Task Type -0,02 0,09 0,01 0,13 0,03 0,06 0,00 0,16 0,08 0,02 -0,03 0,13 0,08 Task Interdependency -0,08 0,11 -0,13 0,22 -0,19 0,15 -0,10 0,05 -0,11 0,08 -0,08 0,11 0,01 Team Identification 0,23 0,03 0,20 0,09 0,20 0,08 0,17 -0,04 0,06 -0,02 0,14 -0,05 0,05 Factional Fau 0,86 1,18 Factional Fau* D2 0,24 0,27 Social Fau -0,14 0,45 Social Fau* D2 -1,28 -3,21 Informational Fau -2,50 -1,67 Informational Fau* D2 0,46 -1,35 Independent Variable Perceived Faultlines 0,26 ** 0,34* 0,35* 0,37 0,36* 0,25 0,27 0,20 R2 0,25** 0,32** 0,08 0,04 0,19 0,35 0,06 0,31 0,34 0,43 0,23 0,36 0,58 0,58 F-value 5,23 1,35 0,27 1,15 0,42 0,75 0,21 1,05 0,93 1,09 0,97 1,35 2,14 2,00 Sig 0,02 0,04 0,89 0,39 0,85 0,64 0,92 0,43 0,51 0,44 0,46 0,31 0,13 0,15
Table 7 – Results for multiple regression on dependent variable task-relevant information exchange (N = 18 teams)
*p < .10; **p < .05; ***p < .01
29 specific variables neither appear to significantly influence the dependent variable task-relevant information exchange, both in the basic models (Models 3a, 5a, 6a and 7a) as well as when perceived faultlines is included. The significant beta-coefficients of perceived faultlines (0.26 - 0.36) indicate a positive relationship, which is the opposite of the relationship as hypothesized. As a consequence, h1 is rejected.
The second hypothesis predicted a positive relationship between post-merger information exchange in a work team, and the subsequent innovative capabilities of a team. Results of the multiple regression can be found in table 8. Task-relevant information exchange appears to explain 32 percent of the variance in dependent variable team innovativeness (β = 0.73, p < 0.05). When isolating the effect by controlling for task type, task interdependency and team identification, this positive relationship remains significant (β = 0.73, p < 0.05), and variance explained increases to 63 percent. This increase can be attributed to the significant predicting roles of type of task performed and the intra-team interdependency for completing tasks, both entailing a positive effect on team innovativeness (β = 0.73; p < 0.05; β = 0.73; p < 0.05). Overall, a positive relationship between intra-team information exchange is found, and therefore H2 is accepted.
Model 8a Model 8b Model 9a Model 9b Control variables
Task Type 0,36* 0,35*
Task Interdependency 0,47** 0,32
Team Identification 0,51 0,72*
Independent variable
Task-relevant Information Exchange 0,93** 0,73**
Moderator variable
Psychological Safety * Information Exchange 0,64 0,23
Information Exchange (I’) 0,82** 0,73**
Psychological Safety (P’) -0,46 -0,66
R2 0,32 0,63 0,45 0,72
F-value 7,48 5,43 3,82 4,73
Sig 0,02** 0,00** 0,03** 0,01**
Table 8 – Results for multiple regression and moderator analysis on dependent variable team innovativeness (N = 18 teams). *p < .10; **p < .05; ***p < .01
The third hypothesis concerns the potential moderating role of psychological safety, and indicates that the causal relation between information exchange and team innovativeness changes as a function of psychological safety (Baron and Kenny, 1986). It is hypothesized that team innovativeness (T) resulting from information exchange (I) is higher for teams in which a high degree of psychological safety (P) is perceived. The derived moderator formula comprises the following: T = b0 + b1I + b2P + b3I*P (Whisman and McClelland, 2005). To analyze this moderating
30 variables entails replacement of the predictor I by I’ = I - ̅ and P by P’ = P - ̅ (Whisman and McClelland, 2005). Subsequently, multiplying the centralized variables results in an interaction term of psychological safety (P’*I’), which is included in the equation. Variables P’ and I’ are also incorporated in the regression, to count for main effects. The outcomes of the regression analysis as presented in table 8 indicate overall model significance (p < 0.05), however no significant moderating role is found (β = 0.23; p > 0.10). The variance of team innovativeness explained appears to result solely from the centralized variable concerning information exchange (β = 0.73; p < 0.10), the core team task (β = 0.35; p > 0.10) and the degree of team identification (β = 0.72; p < 0.10). However, significance of these variables is not relevant conceptually in testing the moderator hypothesis (Baron and Kenny. 1986). As a result, H3 is rejected.
DISCUSSION Key Findings
In this study the perception of factional faultline bases is tested in relation to information exchange in post-merger team collaborations. In faultline research the negative consequences of categorization on team processes have been largely emphasized (Lau and Murnighan, 1998). Accordingly, faultline activation is argued to result in even more detrimental effects on team processes. The significance of the actual perceived faultlines versus the irrelevance of objective factional faultlines in this analysis supports the actual triggering effect of a merger. The results of this study show however that factional faultline activation contribute to the positive view of diversity. The perception of subgroups based on factional faultlines does not inhibit intra-team collaboration as expected, but appears to stimulate the exchange of task-related information. The positive workgroup consequences of factional affiliations contribute to the thesis of Van Knippenburg and Schippers (2007), who argue that different types of faultlines might induce asymmetric effects on team performance.
Task-related information exchange in a post-merger setting entails positive consequences on the innovative capabilities of teams, especially when the core team task concerns integration activities, and task interdependency is high. Although team processes are likely to be uncertain in the post-merger newly created teams, the degree of intra-team psychological safety plays no significant role in predicting team innovativeness.
Mergers and the value of factional groups
31 Mosakowski, 2000; Dahlin, Weingart and Hinds, 2005). Although it is argued that diversity is more likely to negatively impact team processes when team members’ awareness on this diversity is increased (Homan, Hollenbeck, Humphrey, van Knippenberg, Ilgen, and Van Kleef, 2008), salience of intra-team dissimilarities appears to enhance team collaboration in a post-merger setting. The positive, linear relationship shows that the higher the comparative fit between the preexisting subgroups, the more team members become encouraged to share information with the out-group members.
The hypothesis of factional subgroups in post-merger team efforts central in this study entails that the intra-team categorization disrupts work team processes. However, Van Knippenberg, DeDreu and Homan (2004) argue, that instead of this subgroup formation, actual in-group bias forms the major cause. This way, team dynamics are not deteriorated by the mere presence of subgroups, but the variation can be attributed to the actual preference of team members pertaining to one of the subgroups. Hence, the perception of factional subgroups is likely to form a prerequisite for in-group bias, and does not inhibit information exchange itself. Instead, when in-group bias is prevented, subgroup formation based on factional affiliations stimulates information transfer within work teams.
One of the main benefits of diversity in a work team is the variety of opinions and knowledge available to this team. It is argued that factional faultlines weaken transactive memory systems of teams by decreasing the awareness of the information available in the new teams, together with a decrease in the willingness of exchanging information due to high uncertainty present in the new formed team (Easterby-Smith, Lyles and Tsang, 2008). Although diversity is argued to inhibit team practices, diversity actually paves the way for team reflexivity. Team reflexivity refers to ‘the team’s careful consideration and discussion of its functioning’ (Van Knippenberg and Schippers, 2007). As mentioned earlier, diversity indicates the knowledge present in a team, and team members are likely to be motivated to gather with those team mates possessing the most relevant information for their activities (Williams and O’Reilly, 1998). Knowledge gaps in teams due to diversity can create awareness of shortcomings in team functioning, and methods for improvement might be found in the newly available information. In other words, the extent to which diversity is perceived might positively influence the common understanding of the importance of internalizing the new information (Van Ginkel, Tindale and Van Knippenberg, 2009), with activities to foster a strong transactive memory as a result.
