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Mapping the field of virtual work 1
MAPPING THE FIELD OF VIRTUAL WORK: A CO-CITATION ANALYSIS
Sumita Raghuram Pennsylvania State University
125 Willard Hall, University Park State College, PA 16803
Philipp Tuertscher Vienna University of Economics
and Business Administration 1090 Vienna, Austria
Raghu Garud Pennsylvania State University
Smeal School of Business, University Park State College, PA 16803
Forthcoming in Information Systems Research
Sep 15, 2008
The study was funded in part by a grant from Society for Human Resource Management. The conclusions, interpretations and recommendations, however, are those of the authors and do not necessarily represent those of the foundation. We thank three anonymous reviewers and the Associate Editor of ISR for their inputs.
Mapping the field of virtual work 2
MAPPING THE FIELD OF VIRTUAL WORK: A CO-CITATION ANALYSIS
ABSTRACT
Interest in the area of virtual work continues to increase with articles being written from
different disciplinary perspectives – e.g. information systems (IS), management, psychology and
transportation. In this paper, we map research on virtual work to (a) understand the intellectual
base from which this field has emerged, (b) explore how this field has evolved over time, and (c)
identify clusters of research themes that have emerged over time and the relationships between
them. Specifically, we use co-citation analysis of research published in all social science
disciplines to map the field at three points in time – 1995, 2000 and 2006. Our results show that
the field has grown from nine research clusters in 1995 to sixteen in 2006. A comparison across
these maps suggests that research in the cluster of “virtual teams” has gained significance even
as research within some earlier clusters such as “urban planning and transportation” has lost
ground. Our longitudinal analysis identifies relevant concepts, theories and methodologies that
have emerged in the field of virtual work. This analysis can help interested researchers identify
how they may want to contribute to the field of virtual work – by adding to popular clusters,
enriching emerging smaller clusters or by acting as bridges across clusters.
Mapping the field of virtual work 3
MAPPING THE FIELD OF VIRTUAL WORK: A CO-CITATION ANALYSIS
With advances in information technology, ‘virtual work’ in the form of global virtual
teams, telecommuting and distributed work is now being embraced by most organizations (The
Telework Advisory Group, 2007). Reasons for its growing popularity range from productivity
gains that can be realized from such a work mode to an ability to harness talent that lies
distributed across time and space (Gajendran & Harrison, 2007). Consequently, it is not
surprising to note that academicians from disciplines as diverse as information systems (IS),
management, psychology and transportation have become interested in researching this new
work form.
How can we tap into the insights that these diverse literatures have to offer?
Unfortunately, this is not a straightforward task. Given its multi-faceted nature, there are several
meanings associated with the term ‘virtual work’. For instance, terms such as computer-mediated
work, telecommuting, and distributed work, all have a bearing on our understanding of this new
work mode. Given this proliferation of terms, it is difficult to identify the connections across the
different contributions and to take full advantage of the accumulated knowledge.
To address these issues, we use IS tools to conduct a bibliometric study to map the field
of virtual work. This approach allows us to uncover underlying connections between the
contributions on virtual work from different disciplines. Scientific research is a social activity
with researchers building upon the efforts and insights of many (Karuga, Lowry & Richardson,
2007; Oh, Choi & Kim, 2006). The mapping process that we apply in this paper to study the field
of virtual work is premised on such an understanding. Specifically, we use co-citation analysis to
(a) understand the intellectual base from which this field has emerged, (b) explore how this field
Mapping the field of virtual work 4
has evolved over time, and (c) identify clusters of research themes that have emerged over time
and the relationships between them.
The approach that we have used and the outcome of our analysis is of value to those
directly engaged in the area of virtual work. By understanding the genesis of the field and where
it has reached as of today, such a map helps us find fruitful avenues for future research. At the
same time, the method that we use here can be applied to study other important areas in IS,
complementing other methods that have been used to track a field.
BACKGROUND
Virtual Work Reviews
With advances in information technologies, individuals are no longer constrained by time
and space. It is therefore not surprising to note that virtual work has grown along with advances
in technologies such as broadband communication (that allows for easy transmission of data) and
groupware (that enables decision making and problem solving from distributed locations).
Correspondingly, researchers from different disciplines have become interested in examining this
new work mode and the body of literature in this area has grown significantly. This may be an
opportune time for both academicians and practitioners to take stock of the developments in this
growing field to determine future courses of action.
To conduct such a review, several methodologies such as meta-analysis, descriptive
review and bibliometric approaches can be used. Insights from science and technology studies
suggest that the methods that we use critically shape our understanding of a field and our
subsequent research (Latour & Woolgar, 1979). Each method is “a way of seeing and a way of
not seeing” (Poggie, 1965: 284) and, for this reason, we briefly review meta-analysis and
Mapping the field of virtual work 5
descriptive reviews as approaches that can be used to review a field before proceeding to offer
greater details about co-citation analysis.
Meta Analysis. Meta-analysis is an approach designed to statistically summarize the
relationships found significant between variables across multiple studies so as to arrive at an
overall estimate of the coefficients involved (Gajendran & Harrison, 2007). To conduct a meta-
analysis, researchers access both published and unpublished large sample studies (i.e. no case
studies or theoretical articles are included). Typically a meta-analysis requires that the
researchers choose the articles to be included based upon the specific relationships that they
would like to explore.
Different studies may have used different participant samples, methodologies and
measures, and a meta-analysis aggregates all these findings into one overall finding (Cooper,
2003). This is both its strength and its weakness. By bringing together various findings into one
study, it provides researchers with a “bird’s eye view” of some of the more robust relationships
between a set of predictors and outcomes that have been found in the literature. For instance,
Gajendran and Harrison’s (2007) recent meta-analysis of 46 studies on virtual work identified
perceived autonomy of individuals as an important variable that mediates the relationship
between virtual work and beneficial outcomes such as job satisfaction, performance and
turnover. At the same time, however, such a macro perspective is often gained at the expense of
the micro processes constituting the phenomenon including the specific context of each study.
Descriptive Literature Review. In contrast to meta-analysis, with a descriptive literature
review, researchers can more readily include case studies, field studies and theoretical articles.
With such an approach, researchers access and read relevant articles to summarize findings,
often guided by an overall framework. For instance, in a review of virtual work, Baruch (2001)
Mapping the field of virtual work 6
summarized the definition, antecedents (such as information technology, employee/employer
willingness) and the outcomes (such as benefits and shortcomings) of virtual work. In a similar
vein, Fjermestad and Hiltz (2000) reviewed 79 papers on Group Support Systems and
categorized the methodology and results into four factors – contextual, intervening, adaptation
and outcomes. Through this review, the authors offer the GSS researchers and managers an up-
to-date descriptive evaluation of GSS research in organizations.
As may be apparent, conducting a descriptive literature review requires considerable
attention on the part of those conducting the review. And herein lies this method’s strength and
weakness. On the one hand, such reviews offer in-depth analyses of articles (the seminal ones, in
particular) and provide a more nuanced understanding of the contextual issues involved as to
how and why new work modalities such as virtual work may succeed. On the other hand, though,
conducting a comprehensive and exhaustive review can be demanding. Such a review is
constrained by the time and energy of the researchers involved who have to choose the articles
that they can review, often based on their specific research interests. Consequently, there is a real
possibility that several bodies of work can easily be excluded.
Biblometric analysis. A bibliometric approach uses IS tools to conduct a comprehensive
search of relevant articles that appear in multiple databases. Such an analysis is different from a
typical research review in that researchers’ priors do not limit the review. This is because
software tools can help categorize research into clusters by extracting information from
bibliographic records (Schneider, 2006).
Citation analysis is a major bibliometric approach that can be used to identify underlying
patterns of relationships between articles based on the references that these cite (Osareh, 1996).
Advances in information technologies for indexing and searching scholarly work have made this
Mapping the field of virtual work 7
method all the more possible. Indeed, with the availability of the database from the Institute for
Science Information (ISI), citation analysis has developed as an important method for the study
of developments in scientific communities (Garfield & Welljams, 1992; Gmür, 2003).
This approach is premised on citations being key indicators of past and present scientific
activities (Braam, Moed & van Raan, 1991; Garfield, Malin & Small, 1983; Small & Griffith,
1974) and the method allows for the inclusion of research articles from different disciplines. For
example, Karuga, Lowry and Richardson (2007) have used citation analysis to define the
maturity of the IS discipline by examining the impact of 879 articles on IS and non-IS research
(such as, management, engineering and organizational behavior). Manually reviewing this vast
literature is a daunting task and is possible only because of the availability of software tools.
Co-citation analysis is a specific type of citation analysis used to identify clusters of
references “co-cited”1 by subsequent articles (Small, 1973). This approach is particularly well
suited to gaining an understanding of a research trajectory by studying relationships that exist
across prior work because it is based on the inputs of those who are the most knowledgeable in a
research field, i.e. those contributing articles to the field. Specifically, by co-citing references in
their bibliography, contributing authors establish connections between two or more references
that have been published in the past. The assumption is that two co-cited references are related,
either because they are part of the same research cluster or because their foci are similar
(Garfield et al., 1983; Peters, Braam & van Raan, 1995).
The presence of a sufficiently large number of citing articles in a field makes it possible
to identify systematic co-citation patterns while ignoring random connections. These systematic
patterns can be visualized in a co-citation network diagram (what we call as a ‘map’ in this
1 In other words, when two or more references (such as Nilles, 1988 and Mokhtarian, 1991) co-occur in the reference lists of articles, a link is established between these co-cited references.
Mapping the field of virtual work 8
paper) where the more frequently co-cited references can be placed in close proximity in
Euclidian space (Small & Griffith, 1974). Clustering by co-citation is a self-generating, dynamic
classification system because relationships between the different contributions (indicated by the
contributors) are continually being updated by ongoing scholarly work.
A co-citation analysis of virtual work offers several advantages. It makes it possible for
us to understand the structure of the intellectual base underpinning virtual work; one that is
constituted through the contributions of scholars from different disciplines. Specifically, it
enables the identification of connections across a large number of articles based on their
references. Researchers can use co-citation analysis as a complement to other review methods.
For example, researchers can choose to conduct a more in-depth review of cited references that
the co-citation analysis demonstrates as being central in the network. They can also use co-
citation analysis to see how seminal citations included in a traditional descriptive literature
review connect with others.
METHODOLOGY
Data source
We used the Social Sciences Citation Index (SSCI) of the ISI Web of Science to identify
our sample of articles for this analysis. The SSCI is a multidisciplinary index covering multiple
journals across social science discipline. It indexes individually selected, relevant articles from
over 3,300 of the world's leading scientific and technical journals. Each week, on average 2,900
new records and 60,000 new cited references are added.
To reduce the possibility of drawing too narrow a search boundary (Chen, 2006), we
contacted 7 researchers in the IS and management disciplines and identified the terms that they
would most readily associate with virtual work. Our queries resulted in the following words:
Mapping the field of virtual work 9
‘telework’, ‘telecommute’, ‘virtual work/team’, ‘distance work/team’, ‘distributed work/team’,
‘computer mediated work/team’. To ensure that our search was comprehensive, we truncated
search terms and used wildcards to include words that were different from the word-stem. We
considered all articles from the SSCI containing at least one of the search terms in their titles,
abstracts or keywords.
SSCI contains some data that have been entered manually or have been scanned from
hardcopies of articles. Consequently, there is a small possibility that errors may have crept in.
Also, differences in the use of initials or mistakes in the spellings of authors can result in
different names appearing for the same author. To rationalize such inconsistencies, we checked
all the references in the sample for potential spelling errors. In some obvious cases (e.g., same
journal, year, volume, page but different spelling of author name), the record was corrected to its
most frequently used form. In the less obvious cases, we used Google scholar2 to verify whether
references with similar names represented different publications.
Some articles included multiple citations to a reference (e.g., references to different pages
of the same publication). These references were investigated to verify whether the record indeed
cited two different references published in the same issue of a journal. If the records were merely
referring to different pages of the same article, duplicate references were removed to avoid a
distorted citation count and co-citation pattern.
Analyses
Our search yielded 490 articles on virtual work in the ISI Web of Science that had been
published between the period 1976 and 2006 and we included the complete set of 490 articles.
These 490 articles cited 12,759 references. The inclusion of such a large number of references in
the analyses would have resulted in a very fine-grained map. For this reason, it is desirable to 2 Google scholar was used for convenience. It has information about books in addition to articles that SSCI contains.
Mapping the field of virtual work 10
exclude references with low citation counts from a co-citation analysis (Mane & Börner, 2004).
Such exclusion does not significantly impact the structure of the resulting map.
We used the freely available Sitkis (Schildt, 2005) software package to construct a co-
citation network. From the 12,759 references cited by the articles on “virtual work” in our
sample, we initially selected those that had been cited by at least 15 articles in our sample (Chen,
2006). We then incrementally lowered this citation-threshold until the map was at a level of
granularity that was sufficient for us to visualize the evolution of major clusters in the field3.
Eventually, we arrived at a list of 140 references that had been cited by at least 10 articles i.e.,
2% of the 490 articles in our sample. These 140 references served as the basis for drawing the
connections across the 490 articles.
In the next step, to identify research clusters from the overall co-citation network we
clustered the frequently co-cited references (Small & Griffith, 1974). Clustering is a process of
rearranging references through the use of an iterative algorithm such that related references
appear close to one another. Traditional clustering approaches such as hierarchical clustering,
agglomerative clustering, and iterative partitioning (McCain, 1990) appear to be suboptimal for
bibliometric research because these algorithms assign every cited reference to a cluster even if
they are not relevant to any specific cluster (Schildt & Mattsson, 2006).
To overcome this problem we utilized the dense sub-network grouping algorithm
suggested by Schildt and Mattsson (2006). This algorithm forms a cluster of co-cited references;
the formation of a cluster is initiated by first selecting two references from the sample that are
most similar to one another. This similarity is determined by the Jaccard index4 (Small &
3 A similar approach has been used by Leydesdorff (2004) who progressively lowered thresholds to find “articulation points” between different network components that can be considered as sub-disciplines. 4 The Jaccard index is defined as the size of the intersection divided by the size of the union of two sample sets:
Mapping the field of virtual work 11
Greenlee, 1980). The Jaccard index is the ratio between (a) the intersection of two sets, and (b)
their union. The Jaccard value between two references can be calculated by dividing the number
of articles that co-cite these references by all the articles citing any of the two references. The
figure can range from 0 (representing a situation where these two references were not co-cited
even once by these articles) to 1 (representing a situation where these references were co-cited
by all these articles).
A cluster of references emerges as the algorithm, after seeding the process, iteratively
adds additional references from the remaining pool that have the highest average similarity score
with the references already in the cluster. This process continues until the average similarity of
the remaining references is below a pre-selected cutoff Jaccard value when a new cluster is
formed. A low cutoff Jaccard value results in few but relatively large sized clusters with some
overlaps between references. Conversely, a high cutoff value generates more distinct but smaller
sized clusters and some references may not belong to any cluster at all.5 Selecting an appropriate
cutoff value requires the judgment of researchers in evaluating the trade-off between assigning
maximum possible references to a cluster while generating several distinct clusters (Schildt,
Zahra & Sillanpää, 2006).
Using an iterative process, we experimented with different cutoff values for generating
the clusters. We used Jaccard index values of 0.05, 0.10, 0.15, 0.20, 0.25 and 0.30 for this
exploration. Each time, after changing the index values, we evaluated the effect on the number
and size of clusters that emerged. After testing different alternatives, we selected a cutoff value
of 0.10. This parameter setting resulted in a sufficient number of distinct clusters for visualizing
the evolution of research clusters on virtual work.
5 The relationships between the different clusters are structurally similar across the different parameter settings. The results are therefore robust for different settings of this parameter.
Mapping the field of virtual work 12
RESULTS
We present two kinds of maps based on the approach that we described. First, to provide
the reader with a macro-level understanding of the field, we present overview maps of the field
depicting the various research clusters and their connections at three different points in time.
Second, to provide the reader with micro-level details, we zoom into the major clusters
comprising the most recent map of the field (as of 2006) and show the most influential scholarly
works and how these are related. Both types of maps are important as it is difficult to understand
the complete picture without understanding its nuances and vice versa. The possibility of going
back and forth between macro-level understanding and micro-level detail helps generate a
holistic understanding of the field.
Longitudinal Co-citation Networks
To trace the evolution of research on virtual work, we generated three snapshots of the
field – as they appeared in 1995, 2000 and 2006 (Figures 1 a, b and c).
---- Figures 1 a, b and c here ----
A visual comparison of the networks across panels a, b and c suggests that the field has
emerged from a disparate set of nine clusters as of 1995 (Fig 1a) to one exhibiting small world
characteristics among sixteen clusters as of 2006 (Fig 1c). By small world, we mean that the
connections between two or more densely connected networks is established by relatively short
paths (Watts & Strogatz, 1998). In 2006, for instance, there appear to be two such networks (in
dotted lines, representing two major research domains) connected by a cluster related to
references on “work-family/review” and a cluster related to “practitioner focus”.
A further examination of these maps shows that there were two major domains of
research as of 1995 (Figure 1a) – a larger, denser one focusing on “urban planning and
Mapping the field of virtual work 13
transportation” and “early theory” (research domain A) and a smaller one focusing on “virtual
teams” and “computer mediated communication” (research domain B). Research in domain A
offered descriptions of the virtual work phenomenon, initial empirical evidence for its emergence
and early theoretical models to explain the changes in work modes that were occurring. This
research served as a platform to spawn subsequent empirical explorations and conceptual
developments (as the map of the field in 2000 shows). Research in domain B was very small and
distinct. There were no crossovers between research topics in the two domains.
The map of the field as of 2000 shows that research domain B, drawing upon a theory
base that advanced understanding of virtual team processes, grew by encompassing research on
virtual organizations and global virtual teams (Figure 1b). Two clusters, in particular, bridged
research domain A with research domain B. One had a “practitioner focus” and another
examined “organizational structures” such as network organizations. Although connecting the
two research domains, the “work-family” cluster was in the periphery.
The 2006 map (Figure 1c) shows re-emergence of the partition between the two research
domains that had almost come together in 2000. Domain B has evolved to become larger and
denser in comparison to domain A. The “work-family” cluster has moved from its status of a
connector across the two research domains and has established stronger ties with research
domain A. Within research domain B, the “virtual teams” cluster has grown denser and has
become more prominent. The “practitioner focus” cluster remains as a major bridge across the
two research domains. The “literature review” cluster is another bridge connecting the two
research domains through its link with the research in practitioner-oriented cluster.
Network Composition
Mapping the field of virtual work 14
We can examine the structure of knowledge generation within and across research
clusters by probing deeper into the network composition. For simplicity, we focus only on the
2006 map and then allude to the networks in the other two maps as required. Rather than provide
a cluster-by-cluster description of all the 16 clusters comprising the 2006 map (Figure 1c), we
focus our description on the larger clusters that account for 73% of all citations.6 The clusters
marked “early theory” and “urban planning and transportation” are the two largest clusters
within research domain A. “Virtual teams” and “computer mediated communication” are the two
largest clusters within research domain B. To understand the composition of these 4 clusters
please see Figures 2 a-d.
---- Figures 2 a-d here ----
In these graphs, the size of the circles is proportional to the number of citations each
reference has received. The thickness of the lines represents the extent to which these references
were co-cited by the 490 articles as measured by the Jaccard index that we explained earlier. In
our description we provide a general sense of the cluster’s characteristics, common theories and
research methodologies used by the group of researchers.
The “urban planning and transportation” cluster (Figure 2a) represents research
examining the impact of virtual work on job-housing balance and travel patterns in urban and
suburban areas. Research in this cluster predicts the spread of telecommuting by examining (a)
individuals’ decision to telecommute based on their perception of constraints and their
motivations (Mokhtarian, 1998; Mokhtarian & Salomon, 1994), (b) occupations conducive to
telecommuting (Handy & Mokhtarian, 1995), and (c) the impact of telecommuting on travel
distances and travel times (Pendyala, Goulias & Kitamura, 1991).
6 The entire network resulting from this analysis is available on request from the authors.
Mapping the field of virtual work 15
Most of the research in this cluster originated in the state of California, known for its
heavy traffic patterns, rising cost of urban living and disruption of transportation due to possible
earthquakes (e.g., Mokhtarian, 1991a). The region is also known for most of the innovations in
communications technology. The research examines the impact of virtual work on decreasing
automobile congestion, traffic diversions, energy consumption and air pollution. Some of the
research is directed towards developing public policy changes for mass transit and urban
planning (e.g., Mahmassani, Yen, Herman & Sullivan, 1993). Interestingly, research in this
cluster offers definitions and nuanced understandings of virtual work that can be found even
today. For example, Nilles (1991) defined telework and telecommuting as:
“Telework is the substitution of telecommunication technology for work related travel. Telecommuting, a subset of teleworking, is the partial or total substitution of telecommunication and or computer technology for daily commute to work”.
Further, research from this cluster distinguished between home based work and tele-
center based work (Mokhtarian, 1991b; Stanek & Mokhtarian, 1998). Telecommuting, according
to this research, is not an all-or-nothing approach. Consequently, telecommuting should be
viewed along a continuum, thus broadening the potential base of telecommuters (Mokhtarian,
1991b). A notable difference between this cluster and the other clusters was the consistent use of
the terms ‘telework’ and ‘telecommute’ rather than ‘virtual work’.
Distinct from a public policy perspective, the “early theory” cluster (Figure 2b) adopts an
employee-centric approach to focus primarily on home-based work. It draws upon theories from
sociology, psychology and organizational behavior such as Hackman and Oldham’s (1976) task
characteristic model and Maslow’s need hierarchy to explain the effects of reduced socialization
and increased identity conflicts (Salomon & Salomon, 1984; Shamir & Salomon, 1985). The
outcomes explored include work family balance, organizational identification, employee
Mapping the field of virtual work 16
productivity, stress and job satisfaction. The determinants examined include an individual’s
ability to manage social isolation, self-determination, the availability of information technology
and family structure (Kraut, 1989; Venkatesh & Vitalari, 1992).
This “early theory” cluster represents some of the initial empirical research utilizing the
theoretical bases described earlier. The prevalent research methodology in this cluster consists of
interviews, case studies and small sample surveys (DeSanctis, 1984; Olson & Primps, 1984)
because of the difficulties in identifying large samples of home workers (Kraut, 1989). The
viability of virtual work is an undercurrent that runs through a number of articles in this cluster
(e.g., Kraut, 1989; Shamir & Salomon, 1985). Overall, this cluster can be credited for identifying
many constructs central to virtual work that have been examined in greater depth by researchers
belonging to the other clusters.
The “computer-mediated communication” (CMC) (Figure 2c) cluster builds upon Social
Presence theory, Social Information Processing theory and Media Richness theory (e.g., Daft &
Lengel, 1986) to offer a socio-technical lens in understanding the impact of communication
technology (Sproull & Kiesler, 1986). A critical evaluation of the theories and research on CMC
by Walther (1992) provides insights into the core ideas of this cluster. A common understanding
was that CMC, because it lacks non-verbal cues, would result in an exchange of messages that
would be impersonal and task-oriented. Walther (1992), however, suggested that this might be
true for only certain situations. In many cases, CMC may facilitate those involved in developing
deeper relationships, especially if communications are allowed to unfold within an expanded
time frame. Specifically, given enough time, computer supported groups will exchange enough
information to form social and emotional bonds (Chidambaram, 1996). Likewise, electronic mail
can prove to be an effective communication medium if an organization encourages and supports
Mapping the field of virtual work 17
its use (Markus, 1994). Most empirical studies in this cluster compare computer-mediated groups
with face-to-face groups in laboratory settings and evaluate participants on the use of technology
in accomplishing specific tasks.
The “virtual teams” cluster (Figure 2d) focuses on geographically distributed teams and,
in many cases, globally dispersed teams that transcend time, space and culture (e.g., Jarvenpaa &
Leidner, 1999; Lipnack & Stamps, 1997). The cluster identifies the benefits as well as the
challenges related to trust, cohesion and technology that virtual teams may confront (Townsend,
DeMarie & Hendrickson, 1998). Adaptive Structuration (DeSanctis & Poole, 1994) is a
dominant theory within this cluster. This theory describes the interplay between advanced
technologies, social structures and human interactions that forms the basis for an understanding
of processes associated with virtual teams (DeSanctis & Poole, 1994; Maznevski & Chudoba,
2000).
Within the “virtual teams” cluster, there is a sub-cluster focused on global virtual teams
(Cramton, 2001; Jarvenpaa, Knoll & Leidner, 1998; Jarvenpaa & Leidner, 1999; Maznevski &
Chudoba, 2000) that is becoming important given the rise of multinational firms. Global virtual
teams consist of people who are distributed across international boundaries and who deal with
issues that are global in nature (Maznevski & Chudoba, 2000). In addition to the challenges that
virtual teams confront, global teams have to deal with challenges related to working across
international time zones, cultures and geography. Research in this cluster frequently uses
grounded theorizing from in-depth case studies (Glaser & Strauss, 1967) because researchers
have limited access to global virtual teams while requiring rich data to understand this relatively
new work form. Some of the issues examined include: (a) the temporal pattern of interaction
incidents (face to face versus on-line) as it relates to decision-making processes and relationship
Mapping the field of virtual work 18
building (Maznevski & Chudoba, 2000), (b) the development of trust (Jarvenpaa et al., 1998;
Jarvenpaa & Leidner, 1999) and, (c) the failures in developing mutual knowledge and
consequently collaboration (Cramton, 2001).
Other research in this cluster focuses on answering questions central to virtual teams.
These include questions such as – do face-to-face teams have higher performance, information
exchange and relational links than virtual teams (e.g., DeSanctis & Poole, 1994; Jarvenpaa et al.,
1998; Walther, 1995)? The cluster, as a whole, makes significant contributions to our
understanding of the critical issues that drive virtual team processes. Much of this work
represents the theoretical and empirical foundations for current virtual team research.
In addition to these four major clusters, 12 additional smaller clusters define the virtual
work domain. For the sake of brevity we do not describe these clusters in detail here and, instead,
provide a brief description of all the 16 clusters in Table 1 along with examples of references
cited by researchers.
---- Table 1 here ----
These clusters show some overlaps in research topics, concepts and problem-sets. However,
a closer look at each individual cluster reveals that the different research clusters build upon
different literature bases. For instance, they examine relatively distinct aspects of virtual teams,
such as, technological facilitators, organizational outcomes or cross-cultural issues (Figure 1c).
DISCUSSION
Through our analysis, we have tracked the progress made in the field of virtual work over
time and have offered our readers with maps of the field on three different occasions. Tracking
the development of a dynamic field can be useful to see how early ideas shape emerging
discourses around the field and to draw implications for future research. Such an analysis has
Mapping the field of virtual work 19
become all the more feasible because of developments in information systems. For example, the
ISI Web of Science makes it possible to explore scholarly work produced over decades and to
identify relevant articles with little effort. Clearly defined data structures and cross linkages
between references that they cite make it possible for us to identify underlying connections
between articles that could otherwise have remained obscured if we had been dealing with paper
copies. From this perspective, the approach we have taken can be easily used to map and track
other fields of interest to IS researchers.
Our analysis helps us understand developments in virtual work at several levels. At one
level, the map shows a network of research topics and ideas in the field. Specifically, the map
identifies key research themes as well as the themes that are most influential in connecting
clusters. At another level, the maps provide a processual account of the emergence of new topics
in scientific fields. For example, in the case of virtual work, the map of the field as of 2006
(Figure 1c) shows that the “virtual teams” cluster is not only highly cited but that it is also
densely connected with other clusters, a situation that results in the development of a platform to
which researchers may like to preferentially attach themselves (Newman, 2001). In comparison
the “urban planning” cluster seems to be growing slower than the “virtual teams” cluster and it is
not as densely connected with other clusters (Figures 1c). Barring exogenous changes that may
once again bring urban planning to the fore, this cluster appears to be losing in relative
importance. The broader principle of preferential attachment (Bianconi & Barabasi, 2001;
Newman, 2001) is that the growth of a cluster will be determined by a combination of two
factors – the presence of a critical mass as well as the existence of critical connections with other
clusters.
Mapping the field of virtual work 20
We also note that the clusters that connect others in the map as of 2006 are not the ones
from which the field emerged as captured by the map in 1995. The co-citation analysis
demonstrates that few will attribute the origins of the field of virtual work to early contributions
from literatures such as urban planning and information technologies. These maps show that the
emergence of the field has been far from a linear process. The early map of the field (Figure 1a)
makes these origins transparent and shows that early theoretical developments and definitional
attempts are related to transportation rather than to the now dominant topic of distributed/virtual
teams. An understanding of the historical development of the field offers insight into the current
continuing use of concepts and terminology such as ‘tele-commuting’, the etymology of which
would have remained obscured if we were to focus only on more recent research. It also tells us
why certain concepts may have been forgotten.
IMPLICATIONS FOR RESEARCH ON VIRTUAL WORK
One of the most important contributions of an analysis of this kind is the
comprehensiveness with which a search is conducted. In this regard, the method we have used
allows us to analyze a broad range of literature bases: e.g. transportation, management, IS and
organization behavior. Consequently, we can identify multiple themes that are related to different
facets of virtual work. Examples of these themes that cut across different facets of this work
phenomenon include, (a) conflict, isolation, communication ambiguities and trust - drawing
attention towards the dynamics of behavior and attitudes, (b) family, team members and co-
workers - drawing attention towards interpersonal relationships and, (c) performance and identity
- drawing attention towards outcomes. The very fact that these themes span different bodies of
literature signals to researchers the broader impact of this work mode. In this way, our analysis
Mapping the field of virtual work 21
generates options for researchers rather than prescriptions for specific relationships that they
ought to explore.
Our longitudinal analysis suggests that some of the constructs that early theorists had
identified have set the seeds for future research. For instance, in the early years, researchers were
curious to learn how distance would impact the organizational identity of individuals who no
longer came in contact with their peers or organizational symbols on a regular basis (Shamir &
Salomon, 1985). In later years, this question was fleshed out both through empirical research as
well as theoretical modeling (Fiol & O'Connor, 2005; Thatcher & Zhu, 2006; Wiesenfeld,
Raghuram & Garud, 1999). Interest in identities continues as users adapt communication
technologies to contemporary work patterns. Examples include, research on self-presentation and
on-line identities in virtual communities (Golden, 2006; Shumate & Pike, 2006). The underlying
assumption of this research cluster is that some individuals shape their on-line identities to create
desirable relationships with their virtual communities (such as customers or virtual team
members). Likewise, examples can be found in the research examining the impact of media
richness on collaboration in virtual teams (Banker, Bardhan & Asdemir, 2006; Majchrzak,
Malhotra & John, 2005). A historical review of this kind highlights the resilience of issues such
as organizational identity and conflict/collaboration. Thus, researchers interested in examining
these issues in the virtual work context can utilize historical developments across clusters to
deepen their research and expand the theoretical lenses available to them. Further, a historical
perspective allows them to better identify the significance of their own contributions in a far
more nuanced fashion.
Another area that research on virtual work may benefit from is in defining virtual work.
These maps show that researchers have grappled not only with the question of what is ‘virtual’ –
Mapping the field of virtual work 22
is it geographic distance, technology used for work, frequency of face-to face contact, (Fiol &
O'Connor, 2005) – but also with how such ‘virtualness’ may be labeled. Accordingly, terms such
as telework, telecommute, distance work, all referring to some of the same underlying dynamics
of dispersion also reflect the fact that they have distinct origins. For instance, geographically
distributed teams are referred to as ‘virtual teams’ (Cluster 3, Figure 2c) rather than as ‘tele-
teams’ or ‘telework teams’ that would be consistent with terminologies used in Clusters 1 or 2
(Figure 2a and 2b). Given that language and labels constitute how we theorize (Whorf, 1956), it
is useful for researchers and reviewers alike to be aware of the roots of this new work mode, a
facet that can be easily forgotten.
By examining the clusters in Figure 1, we not only discover unique interests that
researchers may like to pursue, but also the possibilities for bridging research clusters in the
future. For instance, there may be an opportunity to bridge the more recent research on virtual
teams with ideas developed in earlier work on urban planning and transportation. The
transportation research has focused on the ways in which objectives such as reducing commute
times and increasing cost efficiency may be achieved. Virtual teams and CMC have focused on
objectives related to balancing technological and relational facets of communication. Research
targeted at accomplishing objectives that are relevant to both clusters (i.e. achieving efficiency of
work, while enhancing effectiveness through relational and technological facets of
communications) is one such possibility. In this regard, both the “practitioner focus” and the
“literature review” clusters may have some interesting perspectives to offer as they act as
bridges. The “practitioner focus” cluster provides research on (a) the benefits that businesses can
derive from virtual work, (b) the conditions under which such work will be appropriate (Cascio,
2000), (c) the role of managerial trust (Handy, 1995), and (d) design and task delegation to
Mapping the field of virtual work 23
virtual teams (Bell & Kozlowski, 2002). The “literature review” cluster, on the other hand, draws
upon “initial empirical research” as well as “European research” to identify relevant issues. This
cluster proposes a link with existing organizational theories to better understand the impact of
telework (Bailey & Kurland, 2002; Kurland & Egan, 1999).
However, it is possible that authors who are “trans-disciplinary” (Stokols, Harvey, Gress,
Fuqua & Phillips, 2005) may find that their contributions are not readily embraced by others who
sqauarely belong to any one discipline. It is here that an appreciation of the network structure
and the specific issues constituting each cluster become useful. Specifically, the map of the field
in 2006 suggests how researchers might position their research to address productive tensions
and complementarities between clusters. In this sense, the map of virtual work from our analysis
serves as a boundary object for researchers from the different clusters so that they might connect
their research with ideas from other research clusters. A boundary object is a ‘flexible epistemic
artifact that inhabits several intersecting social worlds and satisfies the information requirement
of each of them’ (Star & Griesemer, 1989). The map of the field in 2006 and our understanding
of the various clusters offer a perspective as to where the gaps exist in literature. It also suggests
which clusters can be more productively integrated to yield new insights in the field of virtual
work. Additionally, these maps can be invaluable to journal editors and reviewers in identifying
referees and possible literature that can help authors.
IMPLICATIONS FOR RESEARCH METHODOLOGY
Co-citation analysis as a method leverages the availability of IS tools and data bases to
explore the emerging structures of a scientific field. It helps to capture conceptual and
methodological changes that have taken place over time by adopting a historical approach
(Cooper, 2003). Compared to alternative approaches such as descriptive literature reviews or
Mapping the field of virtual work 24
meta-analysis, this method has its own advantages but, at the same time, certain limitations as
well. The primary limitation stems from the very vantage point of such an approach – it offers an
overview perspective of the literature. By itself, it cannot offer readers an in-depth understanding
of the field that traditional reviews can generate. Thus, co-citation analysis is not an alternative
to a careful reading of the articles of potential interest. Instead, the goal of co-citation analysis is
to generate an understanding of the underlying structure of a field and its dynamics (Braam et al.,
1991) that can then motivate a more nuanced reading of articles considered to be important. Such
facility becomes all the more useful in a field such as virtual work that is increasing rapidly
overtime.
Indeed, co-citation analysis lets us interact with the results. As we mentioned earlier, the
map is a boundary object that makes it possible for different researchers to draw relevant
inferences for themselves. The degrees of freedom that this mapping process affords, renders this
technique all the more powerful. Specifically, it is in a researcher’s control to generate a
representation of the field at the level of granularity that is most informative. At the macro level,
for instance, it is possible to plot the data longitudinally or represent the state of a scientific
domain as it has evolved up to a specific point in time. At the micro-level, it is possible to zoom
into any cluster to explore the dynamics and to identify individual actors and groups that form
invisible colleges (Crane, 1969) as well as the specific topics they are pursuing. The availability
of common IS data sources such as the Web of Sciences or CiteSeer makes it possible to zoom
out of a map and to look at the connections a particular field of interest has with other
disciplines. This possibility may be particularly useful for IS researchers as one of the strengths
of this discipline is its ability to cross boundaries and to connect and contribute to research from
Mapping the field of virtual work 25
other disciplines such as psychology, management and operations research (e.g., Briggs,
Nunamaker & Sprague, 2006; Karuga et al., 2007).
CONCLUSION
The advent of information technologies has resulted in a world that is rapidly changing
and one that is being driven by the convergence of boundaries. These dynamics are manifest in
the emergence of organizational forms and work modes such as virtual work that we have
explored in this paper. Given the fluidity of boundaries and dynamics of change, researchers
need a way to tap into emerging insights offered by existing literature as well as to also tap into
what may have been forgotten over time. Mapping of a field using co-citation analysis is one
such way. Not only is it an easy-to-use tool for tracking developments in a field, but it also
provides researchers with a way to understand its underlying structure so that they can more
mindfully locate themselves and their contributions.
When we applied this mapping process, we found that the field of virtual work is robust
and dynamic, as new strands of research on this phenomenon are being realized in different ways
and with different terminologies. We found that topics such as virtual teams are gaining in
strength at the expense of some of the earlier framings around the need to transcend physical
distance. But, insights from the sociology of science (Mane & Börner, 2004) suggest that
researchers often re-visit earlier insights as a field matures to develop more robust and holistic
understandings. We believe that this may be true of virtual work as researchers become once
again become interested in concepts related to physical distance given current concerns about the
environment. And, the mapping process that we have explored will certainly be useful.
Mapping the field of virtual work 26
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Mapping the field of virtual work 31
FIGURE 1
a. Co-citation network across research clusters until 1995
b. Co-citation network across research clusters until 2000
c. Co-citation network across research clusters until 2006
Urban planning and transportation
Urban planning and transportation
Urban planning and transportation
Early theory
Early theory
Early theory
Definitional
Definitional
Definitional
Initial empirical work
Initial empirical work
Initial empirical work
European research group / Definitional
European research group / Definitional
European research group / Definitional
Literature review
Literature review
Literature review
IT and theoretical modeling on teams
IT and theoretical modeling on teams
IT and theoretical modeling on teams
Virtual teams
Virtual teams
Virtual teams
Computer-mediated communication (CMC)
Computer-mediated communication (CMC)
Computer-mediated communication (CMC)
Practitioner focus Virtual organization
Virtual organization Practitioner focus
Theory base for remote work
Theory base for remote work
Organizational structures
Organizational structures
Cross cultural teams
Cross cultural teams
Distributed teams and technology
Distributed teams and technology
Work family / Review
Work family / Review
Research Domain B
Research Domain A
Research Domain B
Research Domain A
Research Domain B
Research Domain A
Mapping the field of virtual work 32
FIGURE 2
a. Co-citation network of the research cluster on urban planning and transportation
b. Co-citation network of the research cluster on early theory
Mapping the field of virtual work 33
FIGURE 2 (continued)
c. Co-citation network of the research cluster on computer mediated communication
d. Co-citation network of the research cluster on virtual teams
Map
ping
the
field
of v
irtua
l wor
k 34
TA
BL
E 1
: 16
mos
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d cl
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of M
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enka
tesh
, Man
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ce, 1
992;
Yap
, In
form
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n M
anag
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t, 19
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3.
Com
pute
r m
edia
ted
com
mun
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Impa
ct o
f com
mun
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ion
tech
nolo
gy. T
heor
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se in
clud
es S
ocia
l Pre
senc
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ocia
l In
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, Med
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Daf
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t Sci
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, 198
6; M
cGra
th, G
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s, 19
84;
Org
aniz
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999.
Mar
kus,
Org
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1994
; Spr
oull,
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agem
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986;
Chi
dam
bara
m,
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Qua
rterly
, 199
6; S
trau
s, Sm
all G
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6.
4.
Virt
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s Te
ams t
rans
cend
ing
time,
spac
e an
d cu
lture
s. U
se o
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e st
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ion
theo
ry. A
sub-
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ter o
f glo
bal v
irtua
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ms u
tiliz
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nded
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s. O
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rfor
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rmat
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exch
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and
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tiona
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T
owns
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dem
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ent E
xecu
tive,
199
8;
Jaar
venp
aa, O
rgan
izat
ion
Scie
nce,
199
9; M
azne
vski
, O
rgan
izat
ion
Scie
nce,
200
0; J
arve
npaa
, Jou
rnal
of M
anag
emen
t In
form
atio
n Sy
stem
s; 1
998;
Lip
nack
, Virt
ual T
eam
s Res
earc
h,
1997
; O’H
ara-
Dev
erea
ux, G
loba
l wor
k, 1
994.
5.
Euro
pean
re
sear
ch /
Def
initi
onal
Expl
anat
ions
and
def
initi
ons o
f tel
ewor
k.
Gen
esis
of v
irtua
l wor
k in
Eur
ope
whe
re it
ga
ined
pop
ular
ity b
efor
e U
SA. T
he im
petu
s m
ay h
ave
com
e fr
om E
urop
ean
need
to d
evel
op
wor
k lif
e ba
lanc
e.
Hoc
hsch
ild, T
he T
ime
Bin
d, 1
997;
Gra
y, T
elew
orki
ng
Expl
aine
d, 1
993;
Nill
es, M
anag
ing
Tele
wor
k, 1
998;
Bar
uch,
Jo
urna
l of G
ener
al M
anag
emen
t, 19
97; J
acks
on, T
elew
orki
ng:
Inte
rnat
iona
l Per
spec
tives
, 199
8; D
anie
ls, J
ourn
al o
f M
anag
emen
t Stu
dies
, 200
1.
6.
Wor
k fa
mily
/ R
evie
w
A re
view
of v
irtua
l wor
k lit
erat
ure
and
focu
s on
the
wor
k-fa
mily
bal
ance
. K
urla
nd, O
rgan
izat
iona
l Dyn
amic
s, 19
99; H
ill, P
erso
nnel
Ps
ycho
logy
, 199
8; H
ill, F
amily
Rel
atio
ns, 1
996;
Apg
ar,
Har
vard
Bus
ines
s Rev
iew
, 199
8.
7.
Lite
ratu
re
revi
ew
A li
tera
ture
revi
ew fr
om m
anag
emen
t dis
cipl
ine
pers
pect
ive.
H
uws,
Tele
wor
k, 1
990;
Bai
ley,
Jour
nal o
f Org
aniz
atio
nal
Beh
avio
r, 20
02; B
aruc
h, N
ew T
echn
olog
y W
ork
and
Empl
oym
ent,
2000
; Kur
land
, Org
aniz
atio
n Sc
ienc
e, 1
999.
Map
ping
the
field
of v
irtua
l wor
k 35
8.
IT a
nd
theo
retic
al
mod
elin
g on
te
ams
Focu
s on
theo
rizin
g ab
out v
irtua
l tea
ms u
sing
ac
adem
ic ro
ots i
n in
form
atio
n sy
stem
s and
te
chno
logy
. Fra
mew
orks
dev
elop
ed h
ere
focu
s on
task
func
tions
and
gro
up p
roce
sses
.
Mon
toya
-Wei
ss, A
cade
my
of M
anag
emen
t Jou
rnal
, 200
1;
Kay
wor
th, J
ourn
al o
f Man
agem
ent I
nfor
mat
ion
Syst
ems,
2002
; L
urey
, Inf
orm
atio
n &
Man
agem
ent,
2001
; Nun
nally
, Ps
ycho
met
ric T
heor
y, 1
978.
9.
Th
eory
bas
e fo
r re
mot
e w
ork
Theo
ry b
ase
that
rese
arch
ers i
n vi
rtual
wor
k ha
ve d
raw
n up
on a
nd c
onsi
dere
d im
porta
nt.
Incl
udes
sem
inal
pie
ces i
n kn
owle
dge
crea
tion,
sh
arin
g an
d tru
st.
May
er, A
cade
my
of M
anag
emen
t Rev
iew
, 199
5; N
gwen
yam
a,
MIS
Qua
rterly
, 199
7; M
eyer
son,
Tru
st in
Org
aniz
atio
ns, 1
996;
N
onak
a, T
he K
now
ledg
e, C
reat
ing
Com
pany
, 199
5.
10. P
ract
ition
er
focu
s Th
e pr
os a
nd c
ons o
f virt
ual w
ork
from
a
prac
titio
ner p
ersp
ectiv
e. C
orpo
rate
exa
mpl
es
and
impl
icat
ions
for m
anag
ers o
f virt
ual w
ork
prog
ram
s.
Han
dy, H
arva
rd B
usin
ess R
evie
w, 1
995;
Cas
cio,
Aca
dem
y of
M
anag
emen
t Exe
cutiv
e, 2
000;
Bel
l, G
roup
& O
rgan
izat
ion
Man
agem
ent,
2002
.
11. D
istri
bute
d te
ams a
nd
info
rmat
ion
tech
nolo
gy
Rol
e of
info
rmat
ion
tech
nolo
gy/ c
olla
bora
tive
tech
nolo
gy in
team
s. O
utco
mes
exa
min
ed
incl
ude
inno
vatio
n, c
onfli
ct g
ener
atio
n an
d kn
owle
dge
diss
emin
atio
n. M
ore
cont
empo
rary
st
udie
s.
Maj
chrz
ak, M
IS Q
uarte
rly, 2
000;
Bar
on, J
ourn
al o
f Per
sona
lity
and
Soci
al P
sych
olog
y, 1
986;
Hin
ds, O
rgan
izat
ion
Scie
nce,
20
03; G
riff
ith, M
IS Q
uarte
rly, 2
003;
Gib
son,
Virt
ual T
eam
s th
at W
ork,
200
3.
12. D
efin
ition
al
Con
cept
ion
and
defin
ition
of v
irtua
l wor
k as
a
visi
on o
f mod
ern
soci
ety;
tele
com
mut
ing
vers
us
tele
wor
king
.
Nill
es, T
elec
omm
unic
atio
ns-T
rans
porta
tion
Trad
eoff
:, 19
76;
Tof
fler,
The
Thi
rd W
ave,
198
0; G
illes
pie,
Rev
iew
of T
elew
ork
in B
ritai
n, 1
995.
13
. Ini
tial e
mpi
rical
w
ork
The
effe
cts o
f tel
ecom
mut
ing
on e
mpl
oyee
sa
tisfa
ctio
n us
ing
smal
l sam
ple
size
s and
cas
e st
udie
s.
Nill
es, M
akin
g Te
leco
mm
utin
g H
appe
n, 1
994;
Ols
on, T
elew
ork,
19
88; H
artm
an, J
ourn
al o
f Bus
ines
s and
Psy
chol
ogy,
199
1.
14
. Virt
ual
orga
niza
tion
The
mea
ning
of v
irtua
l org
aniz
atio
ns, a
nd h
ow
thes
e or
gani
zatio
ns m
ay b
e ab
le to
man
age
cust
omer
supp
ort k
now
ledg
e.
Dav
idow
, The
Virt
ual C
orpo
ratio
n, 1
992;
Dav
enpo
rt, S
loan
M
anag
emen
t Rev
iew
, 199
8.
15. C
ross
cul
tura
l te
ams
Team
s tha
t spa
n ge
ogra
phic
bou
ndar
ies.
Team
dy
nam
ics a
re fr
augh
t with
cul
tura
l iss
ues.
Ger
sick
, Aca
dem
y of
Man
agem
ent J
ourn
al, 1
988;
Hof
sted
e,
Cul
ture
's C
onse
quen
ces,
1980
. 16
. Org
aniz
atio
nal
stru
ctur
es
Theo
retic
al b
ase
in o
rgan
izat
iona
l stru
ctur
es
such
as n
etw
orke
d or
gani
zatio
ns. R
ole
of
com
mun
icat
ion
with
in o
rgan
izat
iona
l st
ruct
ures
.
Daf
t, R
esea
rch
in O
rgan
izat
iona
l Beh
avio
r, 19
84; N
ohri
a,
Net
wor
ks a
nd O
rgan
izat
ions
, 199
2.
* Th
is is
a p
artia
l lis
t rep
rese
ntin
g re
fere
nces
with
hig
h nu
mbe
r of c
itatio
ns.
**N
ames
of o
nly
first
aut
hors
are
pro
vide
d du
e to
spac
e co
nstra
ints
.
Mapping the field of virtual work 36
Appendix A
Complete list of references included in each cluster (arranged in order of number of citations received within the cluster)
Cluster 1: Urban Planning and transportation
Mokhtarian, P. L. & Salomon, I. 1994. Modeling the Choice of Telecommuting - Setting the
Context. Environment and Planning A, 26(5): 749-766.
Mokhtarian, P. L. 1991. Telecommuting and Travel - State of the Practice, State-of-the-Art. Transportation, 18(4): 319-342.
Nilles, J. M. 1988. Traffic Reduction by Telecommuting: A Status Review and Selected Bibliography. Transportation Resources, 22(4): 301-317.
Mokhtarian, P. L. & Salomon, I. 1997. Modeling the Desire to Telecommute: The importance of attitudinal factors in behavioral models. Transportation Research Part a-Policy and Practice, 31(1): 35-50.
Mokhtarian, P. I. & Salomon, I. 1996. Modeling the Choice of Telecommuting: Identifying the Choice Set and Binary Choice Models for Technology-based Alternatives. Environment and Planning A, 28(10): 1877-1894.
Handy, S. L. & Mokhtarian, P. L. 1995. Planning for Telecommuting - Measurement and Policy Issues. Journal of the American Planning Association, 61(1): 99-111.
Mokhtarian, P. L. 1991. Defining Telecommuting. Transportation Research Record, 1305: 273-281.
Mokhtarian, P. L., Handy, S. L. & Salomon, I. 1995. Methodological Issues in the Estimation of the Travel, Energy, and Air-quality Impacts of Telecommuting. Transportation Research Part a-Policy and Practice, 29(4): 283-302.
Pendyala, R. M., Goulias, K. G. & Kitamura, R. 1991. Impact of Telecommuting on Spatial and Temporal Patterns of Household Travel. Transportation, 18(4): 383-409.
Nilles, J. M. 1991. Telecommuting and Urban Sprawl - Mitigator or Inciter. Transportation, 18(4): 411-432.
Mokhtarian, P. L. 1998. A Synthetic Approach to Estimating the Impacts of Telecommuting on Travel. Urban Studies, 35(2): 215-241.
Bernardino, A. T., Ben-Akiva, M., and Salomon, I. 1993. Stated Preference Approach to Modeling the Adoption of Telecommuting. Transportation Research Record. 1413, D.C., 22–30.
Mapping the field of virtual work 37
Hamer, R., Kroes, E. & Vanooststroom, H. 1991. Teleworking in the Netherlands - an Evaluation of Changes in Travel Behavior. Transportation, 18(4): 365-382.
Sullivan, M.A., Mahmassani, H.S. & Yen, J. 1993. Choice Model of Employee Participation in Telecommuting under a Cost-Neutral Scenario. Transportation Research Record, 1413, 42-48.
Salomon, I. 1985. Telecommuting and Travel: Substitution or Modified Mobility? Transport Economics and Policy, (1), 219 -235
Mahmassani, H. S., Yen, J.-R., Herman, R. & Sullivan, M. 1993. Employee Attitudes and Stated Preferences Towards Telecommuting: An Exploratory Analysis. Transportation Research Record, 1413: 31-41.
Stanek, D. M. & Mokhtarian, P. L. 1998. Developing Models of Preference for Home-Based and Center-Based Telecommuting: Findings and Forecasts. Technological Forecasting and Social Change, 57(1-2): 53-74.
Cluster 2: Early theory
Olson, M. H. & Primps, S. B. 1984. Working at Home with Computers: Work and Nonwork Issues. Journal of Social Issues, 40(3): 97-112.
Kraut, R. E. 1989. Telecommuting - the Trade-Offs of Home Work. Journal of Communication, 39(3): 19-47.
Salomon, I. & Salomon, M. 1984. Telecommuting - the Employees Perspective. Technological Forecasting and Social Change, 25(1): 15-28.
Shamir, B. & Salomon, I. 1985. Work-at-Home and the Quality of Working Life. Academy of Management Review, 10(3): 455-464.
Venkatesh, A. & Vitalari, N. P. 1992. An Emerging Distributed Work Arrangement - an Investigation of Computer-Based Supplemental Work at Home. Management Science, 38(12): 1687-1706.
Yap, C. S. & Tng, H. 1990. Factors Associated with Attitudes Towards Telecommuting. Information and Management, 19, 227-235.
Ramsower, R.M. 1985. Telecommuting: The Organizational and Behavioral Effects of Working at Home. Ann Arbor, MI: UMI Research Press.
Duxbury, L. E., Higgins, C. A. & Irving, R. H. 1987. Attitudes of Managers and Employees to Telecommuting. Infor, 25(3): 273-285.
DeSanctis, G. 1984. Attitudes Toward Telecommuting: Implications for Work-at-home Programs. Information & Management, 7(3): 133-139.
Mapping the field of virtual work 38
Pratt, J. H. 1984. Home Teleworking - a Study of Its Pioneers. Technological Forecasting and Social Change, 25(1): 1-14.
Duxbury, L.E., C.A. Higgins, and S. Mills. 1992. After-Hours Telecommuting and Work Family Conflict: A Comparative Analysis. Information Systems Research, (3)2, pp. 173-196.
Goodrich, J. N. 1990. Telecommuting in America. Business Horizons, 33(4): 31-37.
Chapman, A.J., Sheehy, N.P., Heywood, S. & Dooley, SC. 1995. The Organizational Implications of Teleworking. International Review of Industrial and Organizational Psychology, 10, 229-248, John Wiley & Sons.
Olson, M. H., Ives, B., & Baroudi, J. L. 1983. The Measurement of User Information Satisfaction. Communications of the ACM, (26), 182.
Kinsman, F. 1987. The Telecommuters. Chichester: John Wiley and Sons, New York: NY.
Cluster 3: Computer mediated communications
Daft, R. L. & Lengel, R. H. 1986. Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32(5): 554-571.
McGrath, J. E. 1984. Groups: Interaction and Performance. Englewood Cliffs: Prentice-Hall.
Markus, M. L. 1994. Electronic Mail as the Medium of Managerial Choice. Organization Science, 5(4): 502-527.
Sproull, L., & Kiesler, S. 1986. Reducing Social Context Cues: The Case of Email. Management Science, 32, 1492 – 1512.
Chidambaram, L. 1996. Relational Development in Computer-Supported Groups. MIS Quarterly, 20(2): 143-165.
Straus, S.G. 1996. Getting a clue: The Effects of Communication Media and Information Distribution on Participation and Performance in Computer-Mediated and Face-to- Face Groups. Small Group Research. 27: pp 115-142.
Zack, M. H.1993. Interactivity and Communication Mode Choice in Ongoing Management Groups. Information Systems Research, 4, pp. 207-239.
Straus, S.G. 1996. Getting a Clue: The Effects of Communication Media and Information Distribution on Participation and Performance in Computer- Mediated and Face-to- Face Groups. Small Group Research, 27, 115-142.
James, L.R., DeMaree, R.G. & Wolf, G. 1984. Estimating Within Group Interrater Reliability with and Without Response Bias. Journal of Applied Psychology, 69, 85-98.
Mapping the field of virtual work 39
Walther, J. B. 1992. Relational Communication in Computer-mediated Interaction. Human Communication Research, 19 (1), 50-88.
Hollingshead, A. B., McGrath, J. E., & O'Connor, K. M. 1993. Group Task Performance and Communication Technology: A Longitudinal Study of Computer Mediated vs. Face-to-Face Work Groups. Small Group Research, 24, 307-333.
Siegel, J., Dubrovsky, V., Kiesler, S. & McGuire, T. W. 1986. Group Processes in Computer-mediated Communication. Organizational Behavior and Human Decision Processes, 37(2), 157-187.
Kiesler, S., & Sproull, L. 1992. Group Decision Making and Communication Technology. Organizational Behavior & Human Decision Processes, 52, 96-123.
Hiltz, S. R., Johnson, K. & Turoff, M. 1986. Experiments in Group Decision Making. Communication Process and Outcome in Face-to-face versus Computerized Conferences. Human Communication Research, 13(2): 225-252.
Cluster 4: Virtual teams
Townsend, A. M., DeMarie, S. M. & Hendrickson, A. P. 1998. Virtual Teams: Technology and Workplace of the Future. Academy of Management Executive, 12(3): 17-29.
Jarvenpaa, S. L. & Leidner, D. E. 1999. Communication and Trust in Global Virtual Teams. Organization Science, 10(6): 791-815.
Maznevski, M. L. & Chudoba, K. M. 2000. Bridging Space over Time: Global Virtual Team Dynamics and Effectiveness. Organization Science, 11(5): 473-492.
Jarvenpaa, S. L., Knoll, K. & Leidner, D. E. 1998. Is Anybody Out There? Antecedents of Trust in Global Virtual Teams. Journal of Management Information Systems, 14(4): 29-64.
Lipnack, J. & Stamps, J. 1997. Virtual teams: Reaching across space, time and organizations with technology. New York, NY: John Wiley and Sons, Inc.
O'Hara-Devereaux, M., & Johansen, R. 1994. Global Work: Bridging Distance, Culture and Time. San Francisco: Jossey-Bass.
Cramton, C. D. 2001. The Mutual Knowledge Problem and Its Consequences for Dispersed Collaboration. Organization Science, 12(3): 346-371.
DeSanctis, G. & Poole, M.S. 1994. Capturing the Complexity in Advanced Technology Use- Adaptive Structuration Theory. Organization Science, 5, 121-147.
McGrath, J. E. & Hollingshead, A. B. 1994. Groups Interacting with Technology. Newbury Park: Sage.
Mapping the field of virtual work 40
Warkentin, M. E., Sayeed, L. & Hightower, R. 1997. Virtual Teams versus Face-to-face Teams: An Exploratory Study of a Web-based Conference System. Decision Sciences, 28(4): 975-996.
Short, J., Williams, E. & Christie, B. 1976. The Social Psychology of Telecommunications. Wiley, London.
McGrath, J. E. 1991. Time, Interaction, and Performance (TIP): A Theory of Groups. Small Group Research, 22, (2), 147-174.
Glaser, B. G. & Strauss, A. L. 1967. The Discovery of Grounded Theory: Strategies for Qualitative Research. Hawthorne: Aldine de Gruyter.
Walther, J. B. 1992. Interpersonal Effects in Computer-Mediated Interaction Communication Research, 19(1): 52-90.
Daft, R.L., Lengel, R.H., & Trevino, L.K. 1987. Message Equivocality, Media Selection, and Manager Performance. Implications for Information Systems. MIS Quarterly,11, 355-366.
Duarte D. L., & Snyder, N. T. 1999. Mastering Virtual teams: Strategies, tools, and techniques that succeed. San Francisco, CA: Jossey- Bass, Inc.
Walther, J. B. 1995. Relational Aspects of Computer-Mediated Communication: Experimental Observations over Time. Organization Science, 6(2) 186-203.
Strauss, A. L., & Corbin, J. 1990. Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Newbury Park, CA: Sage Publications.
Carlson, J.R., & Zmud R.W. 1999. Channel Expansion Theory and the Experiential Nature of Media Richness Perceptions. Academy of Management Journal, 42 (2) 153-170.
Grenier, R., and Metes, G. 1995. Going Virtual: Moving Your Organization in the 21st Century, Upper Saddle River, NJ: Prentice Hall.
Fulk, J., & DeSanctis, G. 1995. Electronic Communication and Changing Organizational Forms. Organization Science, 6, 337-349
Walther, J.B. 1997. Group and Interpersonal Effects in International Computer-Mediated Collaboration. Human Communication Research, 23, 342-369.
Boutellier, R., Gassmann, O., Macho, H., Roux, M. 1998. Management of Dispersed R&D Teams. R&D Management, Vol. 28, No. 1, 13-25.
Cluster 5: European research/ definitional Hochschild, A. R. 1997. The Time Bind: When Work Becomes Home and Home Becomes
Work. New York: Henry Holt.
Mapping the field of virtual work 41
Gray, M., Hodson, N. & Gordon, G. 1993. Teleworking Explained. Chichester: Wiley & Sons.
Nilles, J. M. 1998. Managing Telework: Strategies for Managing the Virtual Workforce. New York: Wiley.
Baruch, Y. & Nicholson, N. 1997. Home, Sweet Work: Requirements for Effective Home Working. Journal of General Management, 23(2): 15-30.
Jackson, P. J. & Van der Wielen, J. M. (Eds.). 1998. Teleworking: International Perspectives. London: Routledge.
Daniels, K., Lamond, D. & Standen, P. 2001. Teleworking: Frameworks for Organizational Research. Journal of Management Studies, 38: 1151-1186.
Qvortrup, L. 1998. From Teleworking to Networking: Definitions and Trends. In P. J. Jackson
(Ed.), Teleworking: International Perspectives: 21-39. London: Routledge.
Cluster 6: Work-family
Kurland, N. B. & Bailey, D. B. 1999. Telework: The Advantages and Challenges of Working Here, There, Anywhere, and Anytime. Organization Dynamics, 28, 2, 53-69.
Hill, E. J., Miller, B. C., Weiner, S. P. & Colihan, J. 1998. Influences of the Virtual Office on
Aspects of Work and Work/Life Balance. Personnel Psychology, 51(3): 667-684.
Hill, E. J., Hawkins, A. J. & Miller, B. C. 1996. Work and Family in the Virtual Office: Perceived Influences of Mobile Telework. Family Relations, 45(3): 293-301.
Apgar, M. 1998. The Alternative Workplace: Changing Where and How People Work. Harvard Business Review, 76(3): 121-139.
Ellison, N. B. 1999. Social Impacts: New Perspectives on Telework. Social Science Computer Review, 17(3): 338-356.
Cluster 7: Literature review
Huws, U., Korte, W., & Robinson, S. 1990. Telework: Towards the Elusive Office. Chichester: Wiley.
Bailey, D. E. & Kurland, N. B. 2002. A Review of Telework Research: Findings, New Directions, and Lessons for the Study of Modern Work Journal of Organizational Behavior, 23: 383-400.
Baruch, Y. 2000. Teleworking Benefits and Pitfalls as Perceived by Professionals and Managers. New Technology Work and Employment, 15(1): 34-49.
Mapping the field of virtual work 42
Kurland, N. B. & Egan, T. B. 1999. Telecommuting: Justice and Control in the Virtual Organization. Organization Science, 10(4): 500-513.
Cluster 8: IT and theoretical modeling on teams
Montoya-Weiss, M. M., Massey, A. P. & Song, M. 2001. Getting it Together: Temporal Coordination and Conflict Management in Global Virtual Teams. Academy of Management Journal, 44(6): 1251-1262.
Kayworth, T. R. & Leidner, D. E. 2002. Leadership Effectiveness in Global Virtual Teams. Journal of Management Information Systems, 18(3): 7-40.
Lurey, J. S. & Raisinghani, M. S. 2001. An Empirical Study of Best Practices in Virtual Teams. Information & Management, 38(8): 523-544.
Nunnally, J. C. (Ed.). 1978. Psychometric Theory. New York: McGraw-Hill.
Cohen, S. G. & Bailey, D. E. 1997. What Makes Teams Work: Group Effectiveness Research from the Shop Floor to the Executive Suite. Journal of Management, 23(3): 239-290.
Turoff, M., Hiltz, S. R. & Bhagat, A. N. F. 1993. Distributed Group Support Systems. MIS Quarterly, 17(4): 399-417.
Furst, S., Blackburn, R. & Rosen, B. 1999. Virtual Team Effectiveness: A Proposed Research Agenda. Information Systems Journal, 9(4): 249-269.
Cluster 9: Theory base for remote work
Mayer, R. C., Davis, J. H. & Schoorman, F. D. 1995. An Integrative Model of Organizational Trust. Academy of Management Review, 20(3): 709-734.
Ngwenyama, O. K. & Lee, A. S. 1997. Communication Richness in Electronic Mail: Critical Social Theory and the Contextuality of Meaning. MIS Quarterly, 21(2): 145-167.
Meyerson, D., Weick, K. E. & Kramer, R. M. 1996. Swift Trust and Temporary Groups. In D. Meyerson & K. E. Weick & R. M. Kramer & T. R. Tyler (Eds.), Trust in Organizations: Frontiers of Theory and Research. Thousand Oaks: Sage Publications.
Nonaka, I. & Takeuchi, H. 1995. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford: Oxford University Press.
Davenport, T. H. & Prusak, L. 1998. Working Knowledge: How Organizations Manage What They Know. Cambridge: Harvard Business School Press.
Cluster 10: Practitioner focus
Handy, C. 1995. Trust and the Virtual Organization. Harvard Business Review, 73(3): 40.
Mapping the field of virtual work 43
Cascio, W. F. 2000. Managing a Virtual Workplace. Academy of Management Executive, 14(3): 81-90.
Bell, B. S. & Kozlowski, S. W. J. 2002. A Typology of Virtual Teams - Implications for Effective Leadership. Group & Organization Management, 27(1): 14-49.
Cluster 11: Distributed teams and information technology
Majchrzak, A., Rice, R. E., Malhotra, A., King, N. & Ba, S. L. 2000. Technology Adaptation: The Case of a Computer-Supported Inter-Organizational Virtual Team. MIS Quarterly, 24(4): 569-600.
Baron, R. M. & Kenny, D. A. 1986. The Moderator Mediator Variable Distinction in Social Psychological Research - Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology, 51(6): 1173-1182.
Hinds, P. J. & Bailey, D. E. 2003. Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams. Organization Science, 14(6): 615-632.
Griffith, T. L., Sawyer, J. E. & Neale, M. A. 2003. Virtualness and Knowledge in Teams: Managing the Love Triangle of Organizations, Individuals, and Information Technology. MIS Quarterly, 27(2): 265-287.
Gibson, C. B. & Cohen, S. G. 2003. Virtual Teams that Work: Creating Conditions for Virtual Team Effectiveness. New York: John Wiley.
Cluster 12: Definitional
Nilles, J. M. 1976. Telecommunications-Transportation Tradeoff: Options for Tomorrow. New York: John Wiley & Sons.
Toffler, A. 1980. The Third Wave. New York: Bantam
Gillespie, A., Richardson, R. & Cornford, J. 1995. Review of Telework in Britain: Implications for Public Policy, Report to the Parliamentary Office of Science and Technology/ESRC 1995. Newcastle.
Cluster 13: Initial empirical evidence
Nilles, J. M. 1994. Making Telecommuting Happen: A Guide for Telemanagers and Telecommuters. New York: Van Nostrand Reinhold.
Olson, M. H. 1988. Organizational Barriers to Telework. In W. B. Korte & S. Robinson & W. J. Steinle (Eds.), Telework: Present Situation and Future Development of a New Form of Work Organization: 77-100. North Holland: Elsevier Science Publishers.
Mapping the field of virtual work 44
Hartman, R. I., Stoner, C. R. & Arora, R. 1991. An Investigation of Selected Variables Affecting Telecommuting Productivity and Satisfaction. Journal of Business and Psychology, 6(2): 207-225.
Cluster 14: Virtual organization
Davidow, W. H. & Malone, M. S. 1992. The Virtual Corporation. New York: Harper Business.
Davenport, T. H. & Pearlson, K. 1998. Two Cheers for the Virtual Office. Sloan Management Review, 39(4): 51-66.
Cluster 15: Cross cultural teams
Gersick, C. J. G. 1988. Time and Transition in Work Teams - Toward a New Model of Group Development. Academy of Management Journal, 31(1): 9-41.
Hofstede, G. H. 1980. Culture's Consequences. Thousand Oaks: Sage.
Cluster 16: Organizational structures
Daft, R. L. & Lengel, R. H. 1984. Information Richness - A New Approach to Managerial Behavior and Organization Design. Research in Organizational Behavior, 6: 191-233.
Nohria, N. 1992. Is a Network Perspective a Useful Way of Studying Organizations? In N. Nohria & R. G. Eccles (Eds.), Networks and Organizations: Structure, Form, and Action. Boston: Harvard Business School Press.