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The Role of Virtual Distance in Innovation and Success
Karen Sobel Lojeski
Stevens Institute of
Technology
Howe School of Technology
Management
Email: klojeski@stevens.edu
Richard Reilly
Stevens Institute of
Technology
Howe School of Technology
Management
Email: rreilly@stevens.edu
Peter Dominick
Stevens Institute of
Technology
Howe School of Technology
Management
Email pdominic@stevens.edu
Abstract
Although prior research has tended to
dichotomize work teams as virtual or non-
virtual, most project teams today involve some
mix of face-to-face and virtual interaction. We
develop a construct called Virtual Distance
®
that includes temporal, spatial and relational
facets and apply it to 115 project teams. We
propose that virtual distance will influence trust,
goal clarity and organizational citizenship and
will indirectly have an influence on
innovativeness and project success. Our results
showed that virtual distance had significant
influences on trust, goal clarity and OCB and
indirectly influenced innovation and success.
The results have implications for the selection
and management of teams that are
geographically dispersed and interact virtually.
Introduction
The rapid acceleration of networked
organizations has led to a rise in global and
virtual teams (Stough, 2000). An organization’s
success is highly dependent on the use of such
teams in projects focused on new product
development (Barczak & McDonnough, 2003),
application software development (Powell,
Piccoli, & Ives, 2004), supply chain integration
(Bal, 1999), and many other activities. In
addition, globalizing the innovation process
using virtual resources has become an important
way to access diverse sets of knowledge and has
become an imperative for companies that seek to
succeed in a global market (Santos, Doz &
Williamson, 2004). Advances in communication
technology have reshaped the manner and
frequency of daily interactions between
coworkers and customers. Telephones,
videoconferencing, e-mail, and groupware tools
have made it possible for people to collaborate
without meeting face-to face (FTF) (Zaccaro &
Bader, 2002).
Research on virtual teams has identified
three basic characteristics: members are
geographically and/or organizationally dispersed,
collaboration and communication occur through
the use of information technologies, and
interactions are more likely to be temporally
displaced or asynchronous (e.g. Townsend,
deMarie, & Hendrickson, 1998; Zigurs, 2002).
Much of the literature assumes that teams are
either virtual or FTF. Although some (e.g.,
Arnison, 2002), contend that it is virtually
impossible to distinguish a virtual team from a
traditional team due to the pervasive nature of
technology and communications. We have taken
an expanded perspective in our research. First,
“virtualness” is not necessarily a dichotomous
phenomenon (Pauleen, 2003). Most teams
today, whether they are global, virtual or co-
located, can be described by a mix of virtual and
FTF interactions. The key characteristics used to
define a “virtual team” are best thought of as
contributing to a continuum (Zigurs, 2002,
Watson-Manheim, Chudoba, & Crowston, 2003,
Griffith, Sawyer & Neale, 2003) of virtualness.
For example, many co-located teams use e-mail
or web-based collaboration or design tools.
Second, the commonly cited characteristics of
virtual teams are not the only factors influencing
the attitudes, behavior, and innovativeness of
team members. For example, global virtual
teams engaged in new product development and
other innovative activities are challenged by a
number of different issues including building
trust and motivating one another, cultural
diversity and lack of goal clarity (Barczak &
McDonough, 2003). Collaboration, whether it is
FTF or computer mediated, occurs within a
much broader context or climate, which includes
interpersonal, social, organizational and
technical factors, all of which have important
implications for the attitudes and behavior of
team members and their ability to succeed and
innovate (O’Leary & Cummings, 2005).
To be effective, leaders must promote a
climate that supports innovation and business
success (Harborne, 2003). This can only be
accomplished when managers understand the
issues that virtual team members face in the
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
1
0-7695-2507-5/06/$20.00 (C) 2006 IEEE
globalized workplace. Although there are clearly
new sets of issues that present themselves to the
21
st
century networked workforce, the virtual
team research to date has reported relatively few
outcome differences between virtual teams and
FTF teams (Powell, Piccoli and Ives, 2004). In
most cases, these studies have treated virtualness
as a dichotomous phenomenon, with FTF or
“traditional” teams as a control group or
comparator (e.g. Arnison, 2003; Aubert &
Kelsey, 2003). Moreover, they have looked at
the defining constructs of temporal,
technological and geographic displacement in
isolation from other potentially important
variables (e.g. Montoya-Weiss, Massey & Song,
2001; Jarvenpaa & Leidner, 1998).
We sought to operationalize a broader set
of variables that might more fully explain
behavior, success, and innovation in workplace
teams. We drew from both the recent virtual
team research, which stresses computer-mediated
interaction along with temporal and geographic
displacement as well as more general concepts
related to group dynamics and social interaction.
We tried to understand how these variables,
when considered together, impacted trust, goal
clarity and organizational citizenship behavior
(OCB); all of which should be predictors of
project success and innovation performance.
Most global virtual team research considers
geographic distance as a fundamental
characteristic. But distance can also be used to
describe the emotional or psychological gap
between team members who work in the same
building and regularly meet FTF. For a team
that is working primarily in virtual space the
socio-emotional “distance” may be a function of
other factors, in addition to the obvious ones of
geography and computer mediation.
Factors Influencing Distance
The socio-emotional distance between one team
member and another can be influenced by a
variety of factors. These include spatial,
temporal, technical, organizational and social
factors that shape the perceptions of individuals
engaged in collaborative work. In the present
investigation we explore how these factors
collectively impacted work related attitudes,
behavior and performance
. Based on a review
of management, information systems and
psychological literature and interviews with
senior executives managing virtual work we
identified eleven factors that were likely to
influence the perception of distance between
team members.
Spatial (geographic) Distance – Research
suggests that the closer one is physically to
another the greater the chance to form social ties
(Latane, 1996). Physical distance also impacts
the tendency to deceive, ability to influence and
the likelihood of cooperation. (Bradner et al.,
2002).
Temporal Distance – Differences in time zones
amongst virtual team members is often cited as
one of the factors that play a role in virtual team
interactions (Montoya-Weiss, Massey, & Song,
2002, Jarvenpaa 1998). It has also been
suggested that temporal distance be considered
when structuring organizations (Orlikowski &
Yates, 2002), globalizing an organization
(Boudreau, Loch, Robey, & Straud, 1998), and
assessing team boundary issues (Espinosa,
Cummings, Wilson, & Pearce, 2003).
Relational Distance - Relational distance refers
to the difference between team members’
organizational affiliations. For example, an
employee of a company is relationally closer to
another employee of the same company versus
an outsourced employee. Relational distance has
been shown to play a key role in social cohesion
(Moody & White, 2003), information systems
networks, as well as leader effectiveness (Klagg,
1997).
Cultural Distance - Cultural differences have to
date, been a focus of some of the research in
virtual environments and innovation; virtual
teams (Dube & Pare, Jarvenpaa & Leidner,
1999,Massey, Montoya-Weiss, Hung, &
Ramesh, 2001, new product teams (Barczak &
McDonough, 2003), risk mitigation(Grabowski
& Roberts, 1999), virtual societies (Igbaria,
1999), consensus building using group support
systems (Mejias, Shepherd, Vogel, & Lazaneo,
1997), majority influence (Tan, Wei, Watson,
Clapper, & McLean, 1998), software
development (Tellioglu & Wagner, 1999) and
more. Cultural distance has also been used to
study foreign investment expansion, entry mode
choice, and the performance of foreign invested
affiliates, among others (Shenkar, 2001).
Cultural distance is also used to interpret
network ties amongst managers (Stevenson,
2001).
Social Distance - Social distance has been
studied in a number of contexts including
economically defined class or status differences
(Akerlof, 1997), feelings of social closeness and
distance based on social interactions in social
space (Bottero & Prandy, 2003), as a factor in
direct and networked exchanges (Buchan,
Croson, & Dawes, 2002), as a function of
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
2
management (Fox, 1977), a dimension of the
Systematic Multiple Level Observation of
Groups (SYMLOG) management behavior
assessment (Jensen, 1993), as a perceived
measure contributing to the concept of leader
distance (Antonakis & Atwater, 2002), and as a
factor in friendship networks (Krackhardt &
Kilduff, 1999).
Relationship History - One indicator of social
distance is relationship history. This includes
both the extent to which members have had a
prior relationship or relationships with some of
the same people. Relationship history has been
shown to be important in mentoring (Siegel,
2000) and trust building (Rousseau, Sitkin, Burt,
& Camerer, 1998). Relationship history has also
been found to positively impact openness, trust,
and information sharing in computer-mediated
teams. (Alge, Wiethoff, & Klein, 2003).
Task Interdependence – Interdependent tasks
require more communication (Bishop & Scott,
2000), which should lead to decreased distance
between team members. Task interdependence
has also been related to both organizational
commitment and team commitment and
organizational citizenship behavior (Pearce &
Gregerson, 1991; Bishop & Scott, 2000)
FTF interaction – The notion of social presence
has been used in research on virtual work to
describe the extent to which team members feel
the presence of other group members and the
feeling that the group is jointly involved in
communicating (e.g., Venkatesh, Johnson, 2002;
Andres, 2002). One end of the continuum of
social presence is FTF so frequency of FTF
interaction should be related to perceptions of
distance.
Team Size – Group or team size has been shown
to affect one’s sense of belonging (Williams,
1993). A sense of belonging is critical to the
development of organizational identity, which
has been shown to have a direct influence on
organizational citizenship behaviors (Pratt, 1998;
Shamir, 1990). Group size in virtual
environments has also been shown to effect team
decision making (Baltes, Dickson, Sherman,
Bauer, & LaGanke, 2002) and satisfaction
(Dennis & Wixom, 2001).
Multi-Tasking – Multi-tasking, a term used to
describe a person working on more than one task
at a time, can create significant stress and can
lead to less efficiency and productivity (Brillhart,
2004). Cognitively distancing oneself from the
stress created by multi-tasking and information
overload is known as absent presence, “the idea
that we may be physically on a street corner, but
our distracted minds are not.” (Berman, 2003).
Technical Skill - One’s comfort level with
technology plays a role in interactions with
distant team members (Staples, Hulland, &
Higgins, 1999). Less technically competent
members may be less inclined or able to
communicate and form relationships that would
decrease social distance. Major corporations
have found that technical and interpersonal skills
are key to the selection of virtual team members
who are likely to be committed to the project and
to each other (Kirkman, Rosen, Gibson, Tesluk,
& McPherson, 2002).
The factors described above were taken
together to form the multi-dimensional construct,
Virtual Distance®.
Virtual Distance enabled us to look more closely
at the combined effect
of actual physical and
temporal issues (as
noted in much of the
literature as the primary
building blocks upon
which virtual teams are
formed) as well as the
socio-emotional issues
that are often missed. Subsequently, we could
then measure Virtual Distance as an independent
variable against the key performance drivers of
project success and innovation.
In addition to the distance variables we
included several other key variables in a tentative
model: these were: vision or goal clarity, trust
and organizational citizenship behavior (OCB).
Clarity of Vision and Goals
The relationship between group goals and
group performance has been well documented
(e.g., O’Leary-Kelly, Martocchio & Frink,
1994). As teams become more virtual, however,
the absence of experiences gained from FTF
interactions may lead to difficulties in creating
and maintaining a shared vision and commitment
to goals (e.g., Handy, 1995; Seo, Barrett,
Bartunek, 2004, Kezsbom, 1999). Among team
members who are geographically or temporally
distant, individual goals may become less clear if
they are not directly attached to some sort of
organizational mandate (Manzevski & Chudoba,
2000), potentially leading to less collaborative
effort. We expect that virtual distance will
influence the extent to which team members
understand goals and objectives clearly.
Trust
Trust has received considerable attention,
especially in relation to virtual teams and
Cultural Distance
Social Distance
Relationship History
Interdependence Distance
Face to Face
Multi-tasking
Technical Skill
Team Size
Geography
Time Zone
Relational Distance
Virtual
Distance
+
+
+
-
-
+
-
+
+
+
+
VIRTUAL DISTANCE MODEL
™
Cultural Distance
Social Distance
Relationship History
Interdependence Distance
Face to Face
Multi-tasking
Technical Skill
Team Size
Geography
Time Zone
Relational Distance
Virtual
Distance
+
+
+
-
-
+
-
+
+
+
+
VIRTUAL DISTANCE MODEL
™
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
3
innovation. Research has found that perceptions
of physical distance impacted individuals’
willingness to trust counterparts in computer-
mediated interaction (e.g. Moon, 1999, Bradner
& Mark, 2002). Jarvenpaa & Leidner, (1999)
reported that that timely and consistent
communication (especially task-oriented) was
likely to engender trust within virtual teams.
The implications of trust perceptions for team
performance are less clear. Lynn & Reilly (2002)
found that members of virtual teams reported
lower levels of trust and that these lower levels
of trust correlated with lower levels of
innovation and collaborative behavior. In their
investigation of trust on levels of commitment
and innovation, Ruppel and Harrington write,
“He (Hosmer) suggests that trust and
commitment result in enthusiastic cooperative
and innovative effort beyond that gained from
simple financial incentives or contracts. Only
trust can assure people that they will not be
overly penalized for new ideas that fail or that
they are free to try improvisations leading to
competitive innovations in products, markets,
methods, and technologies.” (Ruppel &
Harrington, 2000, p. 319).
A recent survey of top innovators (Milton, 2003)
found that trust people was the single most
significant factor in differentiating successful
innovators. Others have reported that trust
perceptions can impact performance when
cultural distance is considered (Yadong, 2002).
Organizational Citizenship Behavior
There is strong support for the relationship
between trust and OCB (e.g. Yoon & Suh, 2003,
Deluga, 1995) and also for relationships between
trust and organizational commitment (e.g.
Knight & McCabe, 2003). To date however, no
studies have attempted to link this relationship to
individuals’ perceptions of distance. Moreover,
discussion of OCB and commitment are
conspicuously absent from the growing body of
virtual team research.
We proposed that team members’ perceptions of
distance would collectively impact attitudes and
perceptions that have implications for team
effectiveness and performance (See Figure 1).
Specifically, we proposed the following:
a) Individuals’ perceptions of distance would be
inversely related to the levels of trust they felt
toward members of their teams.
b) Distance perceptions would be inversely
related to the clarity of vision and goals for the
team.
c) Lower levels of trust would lead to lower
levels of reported commitment to the team and
willingness to engage in organizational
citizenship behaviors (OCB).
d) OCB and goal clarity would be positively
related to innovation and success within a
project.
Innovation
The study of innovation is varied and
encompasses many different areas of focus
including but not exclusive of diffusion,
adoption, “innovating” and “innovativeness”
(Damanpour, 1991). We sought to uncover
some of the relationships between distance and
innovation activities involving project teams that
had a virtual component. It has been argued that
virtual proximity, connectedness facilitated by
the use of ICT, cannot completely substitute for
physical proximity when it comes to innovation
and learning (Meister, 2004). Quinn argues that
services companies (the majority of firms
represented in our sample) are particularly
dependent on software innovations (Quinn,
2002). For example, the banking industry is
becoming more dependent on innovations
derived from information and communication
technology (Eika & Reistadbakk, 1998).
Interestingly, Hedlund (1996) points out that
much of the management literature does not
generally look closely at innovation activities in
these environments.
We sought to understand innovation
activities in these environments by analyzing
how team members’ perceived their ability to
express and share innovative and creative ideas
with other team members in order to solve
problems and achieve project goals. We used
this as a proxy for innovation at the project team
level. Our approach is supported by other
research in which the authors show that
companies with the highest levels of innovative
performance exhibit certain characteristics; one
of them being that people perceive the innovative
climate as open and they are free to express new
ideas and take creative risks (Milton, 2003).
Thus, we expect that virtual distance should have
both direct and indirect effects through trust and
goal clarity.
Project Success
Project success can be influenced by many
different factors. Barczak, et.al. assert that FtF
frequency can impact project success, in part
because keeping a project on schedule is
dependent on a certain focus and discipline that
is difficult to maintain with geographically
dispersed team members (Barczak, McDonough
III, 2003). Smith contends that the perception of
project success can also be affected by the
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
4
“distance” from ownership of the project (Smith,
2002) which, as we have discussed so far, may
be linked to our measure of Virtual Distance and
its’ influence on goal clarity, trust, and
organizational citizenship behavior. Loo (1996)
asserts that physical proximity is also a key
variable for project success regarding
cooperation, communication, and a clear set of
performance standards and goals. We measured
project success using team member ratings on
three project outcomes: 1) On-time delivery; 2)
On-budget delivery; and 3) Customer
Satisfaction.
Tentative Research Model
Teams defined primarily by geographic and
temporal distance and enabled by information
and communication technology (ICT), are likely
to be influenced by a number of issues in
addition to those that have traditionally been
associated with co-located teams. We propose
a tentative model that links virtual distance and
several key mediating variables to innovation
and success. Our tentative model (shown in
Figure 1) hypothesizes the following
relationships: Virtual distance will negatively
influence members’ trust, perceptions of goal
clarity, OCB and innovation. Goal clarity will
influence innovation and success and will also
influence trust which will in turn influence OCB
and innovation. Finally, innovation and OCB
will influence project success.
Method
The sample included data from 115 projects
For 30 projects we used aggregated data from
multiple respondents. Most of the respondents
worked in technology-related fields in a variety
of organizations with headquarters in the
Northeastern corridor and held positions ranging
from Vice-president to programmer. Seventeen
different organizations were represented and
included financial services, manufacturing,
healthcare, government, software, and
outsourcing industries. The two largest
functional areas represented include Information
Technology (33%) and Engineering (15%).
Respondents’ organizations also varied
considerably in size with half having less than
5,000 employees and half more than 5,000
employees.
Procedure
All respondents were asked to complete a
questionnaire describing their organization,
current position and their experiences with a
recently completed project. Eleven scales
measuring each of the hypothesized distance
components were included in the questionnaire.
Our measure of virtual distance, the VDM Index,
was a simple linear composite of each of the
eleven variables in the Virtual Distance Model.
Each of the variables in the model was first
converted to a standard score and all scores were
averaged with appropriate positive or negative
sign so that higher average VDM Index scores
indicated greater virtual distance. We also
included items to assess five other variables.
Trust was assessed with three items taken from
Jarvenpaa & Leidner (1999), and OCB was
measured with 10 items taken from scales in
Podsakoff, Ahearne & Scott (1997). Two-items
were used to measure goal clarity, five items
were used to assess innovative behavior (White,
2002) and three items measuring project success
were taken from Lynn & Reilly (2000).
Internal consistency reliabilities, means and
standard deviations and intercorrelations were
calculated for all variables. The hypothesized
model was tested with LISREL8.
Results
Table 1 shows the means, standard
deviations, reliabilities and intercorrelations for
the variables in the model.
Table 1: Means, SDs and Correlations
1
Figure 1 shows the hypothesized model with
standardized path coefficients. All coefficients
1
Notes: all coefficients were significant at p<.01
Cronbach’s alpha shown for all variables except VDI. VDI
reliability was estimated as 1 - ΣVE
i
/V
t
; where VE is the
error variance for each of the eight components and V is the
variance for VDI
.
Reliabilities for all variables are shown in the diagonal.
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
5
were significant (p<.01) with the exception of a
non-significant path between innovation and
success. The model had a good fit to the data
(RMSEA = .070, CFI = .99, NFI = .973, NNFI =
.96. In sum the results showed that the VDM
Index has a significant direct effect on Goal
Clarity, Trust, Innovation and OCB. Goal Clarity
has a significant influence on Trust, Innovation
and Success. Trust has a significant direct
influence on OCB and Innovation. OCB and
Goal Clarity have significant direct effects on
overall project success.
Because the path from innovation to success was
non-significant we ran a second model without a
path from innovation to success. The fit was
slightly better (RMSEA = .046, NFI= 97, NNFI
= .98, CFI = .99) with no change in the chi-
square. All path coefficients in the second model
were significant with p<.01. Because
coefficients for the second model showed only
two changes in the third decimal place they are
not shown.
Discussion
As globalization and technology continue
to evolve it is likely that virtual work will
increase. Teams characterized by large cultural,
spatial and temporal differences are likely to
become the norm rather than the exception.
Understanding how perceived distance
influences behavior is one of the keys to
developing theories and practices that can help
select, organize and manage virtual teams
effectively. Although our data are preliminary,
results suggest that perceived distance is a
function of technological, social, geographic and
other factors. We proposed the term Virtual
Distance to characterize this variable (Reilly,
Sobel Lojeski & Dominick, 2005). Our data and
other research suggest that Virtual Distance is
different than other types of distance and is a
multidimensional construct that incorporates a
number of distinct factors that create a socio-
emotional state. The notion of distance
described here differs from other notions of
distance (e.g., psychological, cultural, social) in
that it includes very real spatial distance and
temporal factors that make it difficult for
individuals to develop social ties in the same
way that co-workers have for centuries.
Eleven factors made up our virtual distance
measure in this study. An exploratory factor
analysis revealed three factors: Interpersonal
congruence (e.g., similar values, status based on
contribution, and goal interdependence); Social
Relationships (e.g., FtF communication,
relationship history); and Technical Expertise
(e.g., technical skill and multitasking). An
analysis of factor scores showed Interpersonal
Congruence to be the most highly correlated
with key endogenous variables. Social
Relationships had significant correlations with
several endogenous variables. Technical
Expertise had no significant relationships. It
could be argued that the first two factors will
continue to increase in their influence on how
teams function in the future. Differences in
cultural values and relational distance, for
example, are becoming more common as
technology evolves, companies increase off-
shore contracting and markets become global.
Relational distance continues to increase with
both on-shore and off-shore outsourcing.
Relationship History may be one way that
organizations can decrease distance. Selecting
team members with a history of working
together would be a simple way to decrease the
virtual distance within a team. Lynn & Reilly
(2002) found that very high performing teams
generally knew one another and had worked on
similar projects before. In addition to selecting
members with past common experiences
organizations can also plan for the future by
providing opportunities for dispersed co-workers
to build relationships.
Task Interdependence was also found to
decrease distance. Consistent with our results
other research has shown relationships between
task interdependence and commitment (Pearce &
Gregerson, 1991; Bishop & Scott, 2000) as well
as performance (Saavedra, Early & Van Dyne,
1993). Designing projects to ensure
interdependence should increase interactions,
communication and mutual goal setting, all of
which should lead to decreased perceptions of
distance.
Face-to-Face Interaction is one way to
decrease distance but may have limited
application depending upon the spatial distances
involved in the team. The frequency of FTF
should continue to be an important variable in
team research. A recent study (Kirkman, Rosen,
Tesluk, & Gibson, 2004) showed that FTF was a
moderator for the relationship of empowerment
to success in virtual new product development
teams.
Our data suggested that Virtual Distance
has a significant influence on trust of project
team members. Trust is a widely studied
construct with implications for many important
organizational outcomes (e.g., Mayer, Davis &
Schoorman, 1995; Simons & Peterson, 1995).
Thus, evidence that Virtual Distance is related to
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
6
trust, if borne out by future studies, is significant
for the management of virtual teams. According
to a recent model (McKnight, Cummings,
Chervany, 1998) social mechanisms play an
important role in sustaining and increasing trust.
Interaction, they note, tends to increase the trust
between people. Likewise, Mayer, et al., (1995)
suggest that increased interaction in traditional
teams will increase trust. In virtual teams, the
more distant a person is, the less frequent the
interaction and trust becomes lower over time.
One of the outcomes of lower trust is a reduction
in OCB. OCBs can be viewed as voluntary
behaviors that are part of a social exchange
process. Trust characterizes confidence and
beliefs about other team members’ likelihood of
reciprocating OCBs (Soon & Yuh, 2003). Thus,
when trust is low team members are less likely to
engage in OCBs and less likely to define their
role more broadly to include OCBs.
Virtual Distance also has implications for
shared understanding of what is expected both in
the vision for the project and the goals that are to
be achieved. Although empirical studies are
lacking, Keszbom (1999) notes that a common
vision or sense of purpose is more difficult to
achieve with virtual teams. We suggest that it is
more important to understand the Virtual
Distance amongst team members to know
whether a lack of common vision is likely to be a
problem. We focused on two outcomes:
innovation and success. Although Virtual
Distance had direct and indirect influences on
innovation and success the latter two variables
were not related. One reason may be that the
nature of the projects that we studied, most
software development in financial organizations,
were not directly dependent upon innovative
behavior. On the other hand, innovation may
have future benefits in other projects or
applications.
Many of the implications of Virtual
Distance have yet to be studied. Some areas that
are potentially interesting and important include
affective variables, selecting and organizing
virtual teams and managing and leading virtual
teams. For example, how does distance
influence the emotional and affective side of
work? Do distant employees have more or less
satisfaction, more or less commitment? Recent
research has confirmed the increased difficulty
of meeting socio-emotional needs of virtual team
members (Chidambaram, 1996; Lurey &
Raisinghani, 2001; Maznevski & Chudoba,
2001). Kock (2004) in a recent paper suggests
that human evolution has designed both our
brains and bodies for FTF communication. It
may be that alternatives to the social interactions
of the workplace will have to be found for many
virtual workers to meet some of the social and
emotional needs required for job and life
satisfaction.
Notions of virtual distance may also have
applications to selecting and organizing virtual
teams. For example, a critical global project
may require understanding and perhaps
minimizing the distances between team members
by selecting individuals with closely aligned
work-related values and organizing the tasks to
provide clear opportunities for interdependence
and frequent communication. A final area for
application of virtual distance notions is in team
leadership. Understanding how distant team
members are from one another and how they
differ on key facets of virtual distance can help
project managers to better lead and manage.
As virtual work proliferates effective
leadership of projects in virtual space will
become an essential competitive weapon. We
are currently collecting more data to further
validate and test our model. The present sample
was limited to one respondent per project but
future data will include multiple respondents
from a variety of multi-national projects. This
will allow us to gain a better understanding of
the within and across team effects of virtual
distance on trust, OCB and other variables.
Several theoretical contributions are possible
from this research. First, although trust has been
extensively explored the notion of distance as a
predictor of trust has not. Likewise there is not
much research on distance as an antecedent of
shared vision. A better understanding of how
Virtual Distance affects the formation of shared
vision and goal commitment could be an
additional contribution. Finally, the data
reported here are preliminary and have some
methodological limitations such as single
response and a relatively small sample. Our
future research will address both methodological
problems and look at an expanded model of
virtual distance and the relationships between
virtual distance and organizational outcomes.
Conclusions and Limitations
The results presented provide evidence that
a multidimensional index of Virtual Distance has
an influence on several important intermediate
and outcome variables in project teams. In
addition, the results offer some preliminary
validation for the notion of Virtual Distance as a
meaningful construct. Our study has two major
limitations. First, some of our data are limited to
Proceedings of the 39th Hawaii International Conference on System Sciences - 2006
7
single respondents, which may have produced
some mono-method bias. Factor analysis of the
VDM Index Variables indicated that 18.7 % of
the variance was accounted for by the first factor.
A second factor analysis of items measuring the
exogenous variables in our model showed
slightly 29.2% of the variance accounted for by
the first factor. Using the Harman test (e.g.,
Podsakoff & Organ, 1986) these results suggest
that single-source bias may not be a serious
problem. For projects for which we had multiple
responses we examined intraclass correlations
for our key variables. Intraclass correlations
ranged from ranged from .58 to .77 with a
median of .67 suggesting a reasonable level of
agreement between independent respondents.
Nevertheless, more multiple response data
would allow us to better understand how virtual
distance operates within and across teams to
influence trust, goal clarity, OCB and other
outcome variables. A second limitation has to
do with the nature of our sample. Most of our
data come from financial institutions in which
the projects tend to be software or service
development potentially limiting our
generalizations. A final limitation was our
relatively small sample size. Opinions as to
minimal sample size vary. For example, Stevens
(1996) argues that samples should be at least 15
times the number of variables. Bentler and
Chou (1987) recommend at least 5 times the
number of parameter estimates (including error
terms). Loehlin (1992) recommends at least 100
and preferably 200 cases. Our study, while
certainly on the low end of these rules of thumb,
meets at least the minimal requirements
suggested by these authors.
We hope to remedy these limitations in the
near future by collecting larger numbers of
multiple responses from a variety of different
kinds of organizations and projects.
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