Computer Mediated Communication in Negotiations: The Effect of Intragroup Faultlines on Intergroup Communication and Outcomes

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Virtual Negotiations between Collocated Diverse Teams: The Effect of
Intragroup Faultlines on Intergroup Communication
Keivan Bahmani
Electrical and Computer
Engineering
Clarkson University
bahmank@clarkson.edu
Zhaleh Semnani-Azad
Reh School of Business,
Electrical and Computer
Engineering
Clarkson University
zsemnani@clarkson.edu
Wendi L. Adair
Department of
Psychology
University of Waterloo
wladair@uwaterloo.ca
Katia Sycara
Robotics Institute
Carnegie Mellon
University
katia@cs.cmu.edu
Abstract
This work examines the effect of faultlines in
virtual computer mediated communications of two
collocated negotiation teams. We expand upon prior
diversity literature by considering the effect of both
surface and deep-level faultlines on the intergroup
computer mediated communications in virtual
negotiations. Faultlines are hypothetical lines that
divide teams into multiple subgroups based on
diversity attributes. We confirm that the effect of
team diversity on intergroup computer mediated
communications can be better captured through
faultlines. Our results suggest that faultlines mediate
the effect of diversity on teams’ computer mediated
intergroup communication and that deep-level
faultlines significantly lower the frequency and
quality of intergroup communication of virtual
negotiations.
1. Introduction
Today’s organizations are highly dependent on
Computer Mediated Communication (CMC) systems
to foster cost and time effective interactions between
members from different geographic regions [1]. CMC
systems foster person-to-person communications,
often in text or graphic form, over computer networks
such as electronic mail, voice mail, and computer or
video conferencing [2], [3]. CMCs are particularly
useful in organizations with high member diversity in
terms of surface-level characteristics (i.e. visible
features such as age, gender, and ethnicity) and deep-
level elements (i.e. invisible features such as cultural
norms, values, and personality dimensions) [4], [5].
Interactions over CMC are frequent among
geographically dispersed virtual teams, where each
member is in a different location [3]. Such teams are
quite diverse and CMC can solve some aspects of the
communication and process problems in diverse
teams, particularly miscommunication and conflict.
Yet, in many organizations, CMC connects two or
more collocated teams based in different locations
[6], [7]. Collocated teams are more traditional
organizational teams, where members interact face-
to-face [6]. These collocated teams can also be highly
diverse. One critical process that requires the
connection of collocated teams via CMC is
negotiation. Negotiation is a social process where
two or more parties try to resolve conflict or
distribute resources [8]. Negotiations occurring over
CMC are known as virtual negotiations [8].These
types of negotiations occur frequently between
collocated teams where the bargaining and exercise
of negotiation strategies take place virtually.
Prior diversity and communication research has
heavily studied interactions and in some cases,
negotiations in geographically dispersed, virtual
teams [7]–[10]. There are also many studies
comparing communication or negotiation processes
between virtual and collocated teams [6], [8]. While
these studies shed light on how diversity and CMC
interact to influence team communication and
performance, there is limited research on virtual
negotiations between collocated teams [11]–[13].
Given that many organizations adopt diverse or non-
homogenous teams composed of members varying in
cultural or demographic characteristics, there is a
need to understand how within team, i.e. intragroup,
interactions in collocated diverse teams impact
communication process and interactions between
teams, i.e. intergroup.
Accordingly, in our study we examine interaction
processes in an intragroup context and its impact on
virtual negotiations in an intergroup context.
Extending on prior literature that show intragroup
problems developing because of diversity, we
speculate that collocated diverse teams face similar
Proceedings of the 51st Hawaii International Conference on System Sciences |2018
URI: http://hdl.handle.net/10125/49975
ISBN: 978-0-9981331-1-9
(CC BY-NC-ND 4.0)
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issues. Yet, extending on prior literature we predict
that intragroup issues in collocated diverse teams
spill over in the intergroup context, negatively
influencing virtual negotiations and intergroup
communications.
2. Collocated Diverse Teams and
Faultlines
Diverse teams can be quite beneficial to
organizations [14]. Well-managed diverse teams out-
perform culturally homogeneous teams because of
enhanced information processing and multiple
perspectives, which improve group decision-making
and creativity [15]–[17]. Yet, diverse teams face
many challenges such as lower social integration and
ineffective communication [18], [19]. This is because
members differ on surface-level characteristics.
According to categorization and social identity
theories, in-group bias emerges in this context. This
is when people categorize themselves and others
based on shared demographic attributes as in-group
members, and other members that do not share these
features as out-group members [20], [21]. The higher
the in-group/out-group distinction the more conflict
diverse teams experience, which hinder team unity
and performance [20]–[22]. In addition, differences
in deep-level diversity can lead to discrepancies in
information processing within the team. This often
results in misunderstanding and communication
distortion in diverse teams [19], [23]–[26].
One of the main issues associated with diverse
teams is the formation of faultlines or hypothetical
dividing lines in a team, based on the alignment of
diversity attributes that lead to subgroups [27].
Depending on the diversity composition of the team,
there may be multiple faultlines and subgroups. For
instance, a four-member team of diverse gender
composition may split by a gender faultline into two
subgroups of men and women. These potential and
un-perceived faultlines are dormant faultlines, which
may or may not lead to subgroup formation. Such
faultlines can enhance categorization in the team,
reduce cross sub-group communication and lower
team performance [27]. Activated faultlines, or
faultlines perceived by team members that generate
subgroups, contribute more to team processes such as
conflict, satisfaction and performance than dormant
faultlines [28].
Prior research shows a significant relationship
between activated faultlines and conflict, which
subsequently leads to attenuated team performance
[22], [29]–[31]. For instance, Lau et al. investigated
the influence of faultline from surface-level attributes
on team learning and satisfaction via FTF and CMC
modes of communication. The authors found that
faultlines reduce intra-team communication,
measured by the frequency of task related intra-team
communications [22]. If collocated diverse teams
need to interact and plan for an intergroup virtual
negotiation, there may be a possibility of faultline
activation and subgroup formation on an intra-team
level. Thus, we investigate the extent to which
diversity attributes contribute to faultline activation
in collocated diverse teams, before any intergroup
interaction.
Hypothesis 1a. Surface diversity attributes (e.g.
gender, age, and ethnicity) contribute to faultline
activation in collocated diverse teams.
2.1 Deep-level Diversity in Collocated Teams
While both surface and deep-level diversity
features can contribute to faultline formation, the
majority of faultline research heavily focused on the
alignment of surface-level diversity [27], [31], [32].
Diversity literature illustrates the importance of deep-
level attributes and their impact on collocated diverse
teams. For instance, deep-level diversity attributes
have significant effects on team learning, creativity,
decision making and outcome, above and beyond
surface-level diversity features [15], [33].
Accordingly, we examine faultline activation based
on both surface and deep-level diversity elements in
an intragroup context.
While there is a dearth of work on the
contribution of deep-level diversity to faultline
activation, there are several studies examining the
role deep-level diversity on various team processes
[33]. Prior work on deep-level diversity heavily
focused on characteristics such as values, attitudes
and culture, with a lot of emphasis on cultural values
and norms. Culture reflect a set of unique profiles of
society, incorporating characteristics from observable
behaviors to psychological values and norms [34].
For instance, cultural attributes have a more
prominent impact on team processes [33]. Cultural
attributes fuel diversity categorization and sub-group
formation through shared values and norms among
members of the in-group, and negative stereotypes
toward the out-group. In a diverse team context,
culture can negatively impact communication, even
via CMC, due to unrealistic cultural expectations or
communication distortion due to cultural
misunderstanding and biases [19], [35].
Accordingly, we examine the impact of surface-
level diversity such as gender, age and ethnicity on
faultline formation. We also examine the influence of
deep-level diversity, specifically culture, on faultline
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activation. We primarily focus on cultural norms, or
the the appropriate behavior in interactions
prescribed by a culture [36]. We examine the
influence of tight versus loose cultural norms,
reflecting the extent to which societies have tight
rules and structures, and the level of patience and
acceptance of deviant or non-normative actions [37].
We speculate that in collocated diverse teams,
tight cultural norms heighten the categorization effect
of faultlines compared to that of loose cultural norms.
Team members that endorse tight cultural norms are
more likely to pay attention to the transgression of
other members in their team. This will result in the
categorization of those transgressors as out-group
members. This categorization potentially results in
subgroup formation based on transgressors (out-
group) and members who follow the rules and
regulations (in-group) and activate faultlines based
on the alignment of tight/loose cultural norms in the
team. As a result, we predict that:
Hypothesis 1b. Deep-level diversity attributes (e.g.
tight cultural norms) contribute to faultline activation
in collocated diverse teams.
3. Faultlines and Communication
As we expect surface and deep-level diversity
attributes to give rise to faultlines in collocated
diverse teams, we further predict that active
intragroup faultlines will negatively influence
intergroup interactions between collocated teams
when negotiating virtually over CMC. We speculate
this because if a team’s faultline and subgroups
contribute to lower unity, cohesions, communication,
and performance, it will be difficult for this team to
effectively communicate and negotiate with another
team. This will be even more challenging when the
negotiation is occurring virtually.
Overall, there is a dearth of work on the effect of
faultlines on interterm CMC of collocated teams.
However, there are few studies on the effect of
faultlines on communication process of virtual teams
[12], [30]. For example, Polzer et al. examined the
contribution of faultline in geographically dispersed
virtual teams communicating via a text-based CMC.
In this case, geographical differences of the team
members lead to faultline and subgroup formation.
The authors found that faultlines fuel intragroup
conflict, lower trust, and reduce the frequency of
communication in these virtual teams [12].
Other studies also illustrate that faultlines reduce
the frequency and quality of subgroup
communication in an intragroup context [21], [38].
According to Larkey and colleagues [38], when
subgroups are formed, an inclusion/exclusion process
gets activated, in which in-groups will communicate
more within their subgroups and communicate less
with the out-groups. This pattern of
exclusion/inclusion leads to lower frequency and
quality of communication between subgroups, on an
intragroup level [22]. Specifically, as team members
in subgroups increase their communications among
each other, and decrease it with the out-group, they
can generate shared communication patterns [39].
Team members in same subgroups are more likely to
adjust and match each other’s communication style,
i.e. convergence, and have a distant communication
pattern from the out-group, i.e. divergence, thereby
lowering communication quality across subgroups
[38].
We speculate that the relationship between lower
frequency and quality of intragroup communication
in collocated diverse teams can negatively influence
communication process in virtual negotiations
between teams, because of the lack of mutual
knowledge [40], [41]. Mutual knowledge is a
knowledge that team members share in common and
are aware that they share [40]. Prior research shows
that in teams, mutual knowledge or “common
ground” is integral for coordination of any action,
decision making and performance [40].
Communication quality and frequency in a team
heavily contribute to the team’s mutual knowledge. If
the mutual knowledge of a collocated diverse team is
low because of faultline, this lack of cohesive
understanding and coordination can spillover to
intergroup interactions, lowering quality and
frequency of communication in intergroup virtual
negotiations [40]. As a result, we predict that:
Hypothesis 2. Faultlines lower quality (H2a) and
frequency (H2b) of intergroup communication in
virtual negotiations.
Hypothesis 3. Faultlines mediate the effect of
diversity on the quality and frequency of
communication in virtual negotiations.
4. Theoretical Model
Figure 1 illustrates our conceptual model and
hypotheses for this study.
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Figure 1. The relationship between diversity attributes, faultline and communication.
5. Methodology
5.1 Participants
Participants were 97 undergraduate management
students (52.6 % female, Mean age= 21.48, S.D.
=1.54) organized into 24 four-person teams from two
North American universities where negotiations takes
place between teams from different universities.
Participants received course credit for participation.
Most participants were Caucasians (68.1%). We also
had East Asian (16.5%), Middle Eastern (7.2%),
African American (4.1%), Latin American (2.1%)
and South Asian (2.1%) participants.
5.2 Task
The participants engaged in a supply-chain
management dispute negotiation task by [42]. The
task involved a pet food producer and its major
supplier in a dispute about product quality, delay on
payments and potential of lawsuit. Both parties were
asked to negotiate about issues associated with the
delivery of product, percentage of fat content of the
meat flour, percentage of water content of the meat,
flour, outstanding bill payment, lawsuit, and future
relationships. The exercise required teams to first
coordinate and manage their negotiation approach,
decide on strategies, and plan implementation among
themselves, i.e. within team interaction. Then teams
negotiated with the opposing team about the different
issues, i.e. between team interactions. The task
provided opportunities for integrative solutions by
incorporating the interests of all parties.
5.3 Procedure
A week before the negotiation exercise,
participants read about their roles and prepared for
their first, intra-group interaction about planning and
implementation of strategies. The team interaction
was face to face and lasted around two hours. During
this meeting team members needed to discuss their
goals, approach for the upcoming negotiation, and
assign roles among themselves. For instance, teams
could have assigned a leadership role to a member.
Teams had the flexibility to plan their own approach
and role coordination. A few days after the planning
phase, teams were given information about their
counterparts. Teams were asked to contact their
counterparts and schedule a two hours session for the
virtual negotiation with another team from the
opposing university. This negotiation was conducted
using a CMC employing video conferencing. Upon
the completion of the negotiation, teams were asked
to record their negotiation deals and provide
information on their final outcomes. Throughout the
entire study, participants completed three sets of self-
report surveys individually. The first survey was
given a week before the distribution of the
negotiation case. This survey included demographic
measures and items about the endorsement of tight
cultural norms. The second survey was given right
after the first team meeting and included measures
about their intragroup experience and faultline
activation. The third survey was given right after the
negotiation and included self-report faultline
activations measure as well as measures about their
intergroup experience, quality of communication,
negotiation outcome.
5.4 Measures
Most of our self-report measures asked
participants to rate their agreement with each
statement on a 6-point Likert scale (1, Strongly
Disagree and 6, Strongly Agree).
5.4.1 Surface-level Diversity. We examined
gender, age, and ethnicity as surface-level diversity
Intergroup
Communication
Surface and Deep-level
Diversity
Faultlines
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attributes and calculated faultline strength that
combines these attributes in a team to determine the
potential strength of a dormant faultline [31], [43]–
[45]. We adopted the Average Silhouette Width
(ASW) model due to the algorithm’s ability to
consider up to six simultaneous subgroups and
mitigating the negative effect of correlation between
the input data [44]. We used the ASW Cluster
package and calculated the surface-faultline strength
of each team based on age, gender and ethnicity
attributes with equal weights.
5.4.2 Deep-level Faultline: Tight versus Loose
Cultural Norms. We used the endorsement of tight
cultural norms as a characterization of deep-level
faultline. We employed the six-item tightness-
looseness scale by Gelfand et al. [37], measuring the
strength of social norms and tolerance of deviance
across individuals. The cultures with tight cultural
norms has strong norms and low tolerance for deviant
behaviors. These cultures score higher in the measure
than the loose cultures with weaker norms and higher
tolerance for norm violations. As a result, higher
scores indicates higher endorsement of tight cultural
norms.
5.4.3 Faultline Activation. We measured activated
faultlines in two instances: 1) after the within group
planning, and 2) after the between group
negotiations. We used the four-item activated group
faultline measures implemented in [28]. The measure
captured the extent to which individuals noticed
subgroup formation in the teams based on diversity
elements.
5.4.4 Frequency of Communication: Information
Exchange. We examined perceived frequency of
communication after the negotiation exercise. We
used information exchange as a proxy of
communication frequency. This was an eight-item
scale adopted from prior negotiation research [46]–
[48]. These items asked about the extent to which
teams shared information about priorities, interests,
and needs during the negotiation.
6.4.5 Quality of Communication. We measured
quality of communication after the negotiation
simulation. We adopted the quality of communication
experience measure by Liu and et al. [49]. This
fifteen-item measure included items associated with
three dimensions of quality of communication:
clarity, responsiveness, and comfort.
According to [49] quality and effectiveness of
communication is captured through three dimensions
of clarity, responsiveness and comfort. Clarity
reflects the cognitive aspect of communication or the
level of understanding of the meaning in messages
[50]. Responsiveness is the behavioral aspect of
communication, specifically, synchronization in
speech patterns and responsiveness to information
inquiries or emotion expression [51]. Comfort is
associated with the affect, ease and pleasantness in
interactions [49].
6. Results
We conducted individual level analyses to
examine the effects of surface-level (age, gender, and
ethnicity) and deep-level (tight cultural norms)
demographic characteristics on activation of
faultlines. We also examined how activated and
perceived faultlines influence the frequency and
quality of intergroup CMC. We conducted analyses
on direct effects using hierarchical linear regressions
and mediation analyses using the PROCESS macro
for SPSS (Hayes, 2013) specifying Model 4.
Unstandardized indirect effects were computed for
each of 1000 bootstrapped samples, and the 95%
confidence interval was computed by determining the
indirect effects at the 2.5th and 97.5th percentiles.
In H1a and H1b, we posited that surface and
deep-level diversity attributes lead to activation of
faultlines in collocated diverse teams. Contrary to our
prediction, surface-level diversity were negatively
related (β = -.22, SE = .46, t = -2.09, p = .04) to
faultline activation in time 1. However, in time 2, (β
= .28, SE = .17, t = 2.32, p = .02), deep-level
diversity, i.e. tightness cultural norm, was
significantly and positively related to perceived
faultlines. We also found a significant and strong
relationship between activated faultlines in time 1
and faultlines in time 2, (β = 438, SE = .08, t = 4.18,
p < .01). Thus, H1a is not supported while, H1b is
supported.
For H2, we expected that faultlines lead to lower
quality (H2a) and frequency (H2b) of intergroup
CMC in virtual negotiation. In support of the first
part of our hypothesis (H2a), we found a significant
negative relationship between faultlines based on the
alignment of deep-level attributes and clarity, (β = -
.29, SE = .11, t = -2.74, p < .01), responsiveness, (β =
-.24, SE = .11, t = -2.19, p = .03), and comfort, (β = -
.27, SE = .15, t = -2.53, p = .01) dimensions of the
intergroup CMC. For the second part of the
hypothesis, in order to investigate the frequency of
communication, we examined information exchange
during the virtual negotiations. Supporting the second
part of our hypothesis we found that that faultlines in
time 2 were negatively related to frequency of
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communication, (β = -.25, SE = .08, t = -2.26, p =
.03). As a result, both H2a and H2b are supported.
We conducted additional analyses to examine
whether faultlines mediates the relationship between
deep-level characteristics associated with cultural
norms and the quality and frequency of
communication. Our analyses illustrated that
faultlines in time 2 mediated the relationship between
tight cultural norms and quality of intergroup CMC
in terms of clarity, (β = -.12, SE = .07, LLCI: -.31,
ULCI: -.01), responsiveness, (β = -.11, SE = .07,
LLCI: -.31, ULCI: -.02) and comfort (β = -.17, SE =
.09, LLCI: -.38, ULCI: -.02). Moreover, faultlines
mediated the relationship between tight cultural
norms and frequency of communication, (β = -.07,
SE = .04, LLCI: -.17, ULCI: -.01). In addition, we
conduct the sobel test using the PROCESS macro for
SPSS for the mediations between the cultural norms,
deep-level faultlines and clarity (z = -1.66, p = .096),
responsiveness (z = -1.56, p = .118), comfort (z = -
1.65, p = .097) and frequency of communication (z =
1.40, p = .158). Even though the result of our sobel
test doesn’t indicate a significant mediation, we
believe this might be due to our limited sample size
and the confidence interval obtained through the
bootstrapping process to be more trustworthy [52].
As a result, H3 is partially supported.
7. Discussion
In this work, we aim to shed light on the impact
of diversity and faultlines on the intergroup computer
mediated communications during virtual
negotiations. This work expands upon previous
virtual team and CMC literate by shedding light on
the relationship between faultlines and intergroup
CMC. Contrary to prior faultline literature that
mainly focused on surface-level characteristics such
as age, gender, and ethnicity, in this work, while we
examined the surface-level demographic attributes
through ASW model [44], we also extend the prior
works by introducing and examining faultlines
derived from deep-level cultural norms.
Our results confirms that the relationship between
diversity and teams’ CMC might not be as
straightforward as proposed in previous literature [5],
[13]. In case of surface-level demographic diversity,
we observed a pattern similar to that of [5], [13].
Contrary to our prediction, surface-level diversity
characteristics were positively related to the
frequency of intergroup communications. Carte et al.
[13] proposed that this relationship is due to the
reductive capabilities of the CMC. However, we
could not observe the similar pattern for more
prominent deep-level diversity attributes.
Another novel aspect of this study is the
confirmation of faultline activation based on both
surface and deep-level diversity attributes,
specifically tight and loose cultural norms.
According to [20], over time due to the interaction
between team members the effect of surface-level
attributes will gradually fade-away while the effect of
deep-level attributes become more prominent. Our
result confirms the same pattern in activation and
persistence of faultlines in negotiation teams. As in
time 1, the surface-level attributes lead to faultline
activation and later in time 2, faultlines were based
on the alignment of cultural norms.
We speculated that in diverse negotiation teams,
people who endorse tight cultural norms might tend
to exclude team members who are deemed as
transgressors. This can result in subgroup formation
within the team: transgressors who are excluded (i.e.
out-group) verses rule-abiding members who are
included (i.e. in-group). This subgroup formation can
further reduce the intra subgroup communications
and hinder the formation of mutual knowledge. Our
findings support this notion by illustrating the
importance of individual-level endorsement of tight
cultural norms in heightening the effect of faultlines
and how faultlines stemmed from these cultural
norms can hinder effective intragroup communication
in virtual negotiations.
Our result also confirms that faultlines based on
the alignment of deep-level attributes mediate the
relationship between cultural norms and teams’
CMCs. This is a novel contribution to the faultline
and culture literature as we show that tight cultural
norms, i.e. low tolerance for deviances from social
norms, can diminish intergroup communication
effectiveness by increasing the divide among
subgroups.
It is worth mentioning that even though we found
a significant relationship between surface-level
diversity (i.e. ASW measure) and activated faultline,
this relationship was inverse, i.e. higher surface-level
diversity was negatively related to faultline activation
in time 1. This surprising effect might be due to the
calculation of faultline strength with ASW model
based on equal weights for all the surface-level
characteristics of age, gender, and ethnicity [44]. We
speculate that the weightage of these elements may
differ depending on the team composition, type of
task, interactions and cultures. These additional
factors can bolster the conscious perception of
subgroups and faultlines in teams. Indeed, after
conducting additional analyses by manipulating the
relative ratio of these weights, we were able to see
different effects on the relationship between ASW
strength and faultline activation.
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8. Conclusion and Future Work
In this study, we investigated the effect of
diversity on intergroup CMC of negotiation teams.
Our study indicates that the relationship between
diversity and intergroup communication in virtual
negotiations can be better captured through faultlines
and we confirm that faultlines mediate the effect of
team diversity on intergroup communications. This
work also identifies the negative effects associated
with endorsement of tight cultural norms on
intergroup communications in virtual negotiations.
For future research, we plan to increase the
sample size of our study to investigate the
inconsistencies of surface-level faultlines. This would
allow us to investigate the effect of demographic
faultline on intergroup CMC of teams. We also aim
to examine the relationship between various degrees
of virtually in the CMC, faultlines and intergroup
CMC.
While we introduced faultlines based on the
alignment of deep-level attributes, we only focused
on tight cultural norms. For future research, we plan
to develop a comprehensive model of deep-level
faultlines that includes other facets of cultural norms.
For example, recent negotiation research show the
importance of honor, face, dignity cultural norms in
predicting social interactions and conflict resolution
[46].
9. Acknowledgment
This research has been sponsored by ARI
FA1130204-374345.
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