MAPPING THE FIELD OF VIRTUAL WORK: A CO …test.scripts.psu.edu/users/r/u/rug14/1.Mapping the field of virtual... · ... in all social science disciplines to map the ... by acting

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

[email protected]

Philipp Tuertscher Vienna University of Economics

and Business Administration 1090 Vienna, Austria

[email protected]

Raghu Garud Pennsylvania State University

Smeal School of Business, University Park State College, PA 16803

[email protected]

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.



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.



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


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


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)


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


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.


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:


‘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.


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:


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.


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


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


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.


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


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


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


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


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.


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


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’ –


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


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


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


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.


REFERENCES

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.

Banker, R. D., Bardhan, I. & Asdemir, O. 2006. Understanding the impact of collaboration software on product design and development. Information Systems Research, 17(4): 352-373.

Baruch, Y. 2001. The status of research on teleworking and an agenda for future research. International Journal of Management Reviews, 3(2): 113-129.

Bell, B. S. & Kozlowski, S. W. J. 2002. A Typology of Virtual Teams - Implications for Effective Leadership. Group & Organization Management, 27(1): 14-49.

Bianconi, G. & Barabasi, A.-L. 2001. Bose-Einstein condensation in complex networks. Physical Review Letters, 86: 5632-5635.

Braam, R. R., Moed, H. F. & van Raan, A. F. J. 1991. Mapping of science by combined co-citation and word analysis. I. Structural aspects. Journal of the American Society for Information Science, 42(4): 233-251.

Briggs, R. O., Nunamaker, J. F. & Sprague, R. H. 2006. Crossing Boundaries in Information Systems. Journal of Management Information Systems, 22(4): 7-11.

Cascio, W. F. 2000. Managing a Virtual Workplace. Academy of Management Executive, 14(3): 81-90.

Chen, C. 2006. CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature. Journal of the American Society for Information Science and Technology, 57(3): 359-377.

Chidambaram, L. 1996. Relational Development in Computer-Supported Groups. MIS Quarterly, 20(2): 143-165.

Cooper, H. 2003. Editorial. Psychological Bulletin, 129: 3-9.

Cramton, C. D. 2001. The Mutual Knowledge Problem and Its Consequences for Dispersed Collaboration. Organization Science, 12(3): 346-371.

Crane, D. 1969. Social structure in a group of scientists: a test of the "invisible college" hypothesis. American Sociological Review, 34: 335-352.

Daft, R. L. & Lengel, R. H. 1986. Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32(5): 554-571.

DeSanctis, G. 1984. Attitudes Toward Telecommuting: Implications for Work-at-home Programs. Information & Management, 7(3): 133-139.


DeSanctis, G. & Poole, M. S. 1994. Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory. Organization Science, 5(2): 121-147.

Fiol, C. M. & O'Connor, E. J. 2005. Identification in Face-to-Face, Hybrid, and Pure Virtual Teams: Untangling the Contradictions. Organization Science, 16(1): 19-32.

Fjermestad, J. & Hiltz, S. R. 2000. Group Support Systems: A Descriptive Evaluation of Case and Field Studies. Journal of Management Information Systems, 17(3): 115-159.

Gajendran, R. S. & Harrison, D. A. 2007. The Good, the Bad, and the Unknown About Telecommuting: Meta-Analysis of Psychological Mediators and Individual Consequences. Journal of Applied Psychology, 92(6): 1524-1541.

Garfield, E., Malin, M. V. & Small, H. 1983. Citation Data as Science Indicators. Essays of an Information Scientist, 6: 580.

Garfield, E. & Welljams, D. 1992. Citation data: Their use as quantitative indicators for science and technology evaluation and policy-making. Science & Public Policy, 19(5): 321-327.

Glaser, B. G. & Strauss, A. L. 1967. The Discovery of Grounded Theory: Strategies for Qualitative Research. Hawthorne: Aldine de Gruyter.

Gmür, M. 2003. Co-citation analysis and the Search for Invisible Colleges: A Methodological Evaluation. Scientometrics, 57(1): 27-57.

Golden, T. D. 2006. The role of relationships in understanding telecommuter satisfaction. Journal of Organizational Behavior, 27(3): 319-340.

Hackman, J. R. & Oldham, G. R. 1976. Motivation Through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance, 16: 250-279.

Handy, C. 1995. Trust and the Virtual Organization. Harvard Business Review, 73(3): 40.

Handy, S. & Mokhtarian, P. L. 1995. Planning for Telecommuting: Measurement and Policy Issues. Journal of the American Planning Association, 61(1): 99-111.

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.

Jarvenpaa, S. L. & Leidner, D. E. 1999. Communication and Trust in Global Virtual Teams. Organization Science, 10(6): 791-815.

Karuga, G. G., Lowry, P. B. & Richardson, V. J. 2007. Assessing the Impact of Premier Information Systems Research over Time. Communications of the Association for Information Systems, 19: 115-131.

Kraut, R. E. 1989. Telecommuting: The Trade-offs of Home Work. Journal of Communication, 39(3): 19-47.


Kurland, N. B. & Egan, T. B. 1999. Telecommuting: Justice and Control in the Virtual Organization. Organization Science, 10(4): 500-513.

Latour, B. & Woolgar, S. 1979. Laboratory Life: The Social Construction of Scientific Facts. Beverly Hills: Sage Publications.

Leydesdorff, L. 2004. Top-down decomposition of the Journal Citation Report of the Social Science Citation Index: Graph- and factor-analytical approaches. Scientometrics, 60(2): 159-180.

Lipnack, J. & Stamps, J. 1997. Virtual teams: Reaching across space, time and organizations with technology. New York, NY: John Wiley and Sons, Inc.

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.

Majchrzak, A., Malhotra, A. & John, R. 2005. Perceived individual collaboration know-how development through information technology-enabled contextualization: Evidence from distributed teams. Information Systems Research, 16(1): 9-27.

Mane, K. K. & Börner, K. 2004. Mapping Topics and Topic Bursts in PNAS. Proceedings of the National Academy of Science, 101(1): 5287-5290.

Markus, M. L. 1994. Electronic Mail As the Medium of Managerial Choice. Organization Science, 5(4): 502-527.

Maznevski, M. L. & Chudoba, K. M. 2000. Bridging Space Over Time: Global Virtual Team Dynamics and Effectiveness. Organization Science, 2000(11): 5.

McCain, K. W. 1990. Mapping Authors in Intellectual Space - A Technical Overview. Journal of the American Society for Information Science, 41(6): 433-443.

Mokhtarian, P. L. 1991a. Telecommuting and Travel: State of the Practice, State of the Art. Transportation, 18(4): 319-342.

Mokhtarian, P. L. 1991b. Defining Telecommuting. Transportation Research Record, 1305: 273-281.

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. 1998. A Synthetic Approach To Estimating the Impacts of Telecommuting on Travel. Urban Studies, 35(2): 215-241.

Newman, M. E. J. 2001. Clustering and preferential attachment in growing networks. Physical Review E, 64: 025102.


Nilles, J. M. 1991. Telecommuting and Urban Sprawl - Mitigator or Inciter. Transportation, 18(4): 411-432.

Oh, W., Choi, J. N. & Kim, K. 2006. Coauthorship Dynamics and Knowledge Capital: The Patterns of Cross-Disciplinary Collaboration in Information Systems Research. Journal of Management Information Systems, 22(3): 266-292.

Olson, M. H. & Primps, S. B. 1984. Working at Home with Computers: Work and Nonwork Issues. Journal of Social Issues, 40(3): 97-112.

Osareh, F. 1996. Bibliometrics, Citation Analysis and Co-Citation Analysis: A Review of Literature I. Libri, 46: 149-158.

Pendyala, R. M., Goulias, K. & Kitamura, R. 1991. Impact of Telecommuting on Spatial and Temporal Patterns of Household Travel. Transportation, 18(4): 383-409.

Peters, H. P. F., Braam, R. R. & van Raan, A. F. J. 1995. Cognitive resemblance and citation relations in chemical engineering publications. Journal of the American Society for Information Science, 46(1): 9-21.

Poggie, G. 1965. A main theme of contemporary sociological analysis: Its achievements and limitations. British Journal of Sociology, 16: 283-294.

Salomon, I. & Salomon, M. 1984. Telecommuting: The Employees' Perspective. Technological Forecasting and Social Change, 25: 15-28.

Schildt, H. A. 2005. Sitkis - A Bibliometric Software Tool. Espoo, Finland: TKK.

Schildt, H. A., Zahra, S. A. & Sillanpää, A. 2006. Scholarly Communities in Entrepreneurship Research: A Co-Citation Analysis. Entrepreneurship Theory and Practice, 30(3): 399-415.

Schildt, H. A. & Mattsson, J. T. 2006. A Dense Network Sub-grouping Algorithm for Co-citation Analysis and its Implementation in the Software Tool Sitkis. Scientometrics, 67(1): 143-163.

Shamir, B. & Salomon, I. 1985. Work-at-Home and the Quality of Working Life. Academy of Management Review, 10(3): 455-464.

Shumate, M. & Pike, J. 2006. Trouble in a geographically distributed virtual network organization: Organizing tensions in continental direct action network. Journal of Computer-Mediated Communication, 11(3): 24.

Small, H. 1973. Co-citation in the Scientific Literatures: A New Measure of the Relationship Between two Documents. Journal of the American Society for Information Science, 24(4): 265-269.

Small, H. & Griffith, B. C. 1974. The Structure of Scientific Literatures I: Identifying and Graphing Specialties. Science Studies, 4(1): 17-40.


Small, H. & Greenlee, E. 1980. Co-citation Context Analysis of a Co-citation Cluster: Recombinant-DNA. Scientometrics, 2(4): 277-301.

Sproull, L. & Kiesler, S. 1986. Reducing social context cues: The case of email. Management Science, 32: 1492-1512.

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: 53-74.

Star, S. L. & Griesemer, J. R. 1989. Institutional Ecology, `Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Social Studies of Science, 19(3): 387-420.

Stokols, D., Harvey, R., Gress, J., Fuqua, J. & Phillips, K. 2005. In vivo studies of transdisciplinary scientific collaboration - Lessons learned and implications for active living research. American Journal of Preventive Medicine, 28(2): 202-213.

Thatcher, S. M. B. & Zhu, X. 2006. Changing Identities in a Changing Workplace: Identification, Identity Enactment, Self-verification, and Telecommuting. Academy of Management Review, 31(4): 1076-1088.

The Telework Advisory Group. 2007. Telework Trendlines for 2006. Scottsdale, AZ: WorldatWork.

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.

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.

Walther, J. B. 1992. Interpersonal Effects in Computer-Mediated Interaction Communication Research, 19(1): 52-90.

Walther, J. B. 1995. Relational Aspects of Computer-Mediated Communication: Experimental Observations over Time. Organization Science, 6(2): 186-203.

Watts, D. J. & Strogatz, S. H. 1998. Collective dynamics of 'small-world' networks. Nature, 393(6684): 440-442.

Whorf, B. L. 1956. Language, Thought, and Reality: Selected Writings of Benjamin Lee Whorf. Cambridge: MIT Press.

Wiesenfeld, B. M., Raghuram, S. & Garud, R. 1999. Communication Patterns as Determinants of Organizational Identification in a Virtual Organization. Organization Science, 10(6): 777-790.


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



Early theory

Early theory

Early theory

Definitional

Definitional

Definitional

Initial empirical work



European research group / Definitional



Literature review

Literature review

Literature review

IT and theoretical modeling on teams



Virtual teams

Virtual teams

Virtual teams

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


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


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

t cite

d cl

uste

rs o

f vir

tual

wor

k re

sear

ch*

Clu

ster

D

escr

iptio

n Fi

rst a

utho

r**

of th

e ci

ted

refe

renc

e 1.

U

rban

Pla

nnin

g an

d tra

nspo

rtatio

n

Trav

el p

atte

rns i

n ur

ban

and

subu

rban

are

as;

spre

ad o

f tel

ecom

mut

ing;

eff

ect o

n tra

ffic

co

nges

tion,

ene

rgy

cons

umpt

ion

and

air

pollu

tion

Mok

htar

ian,

Env

ironm

ent a

nd P

lann

ing,

199

4; M

okht

aria

n,

Tran

spor

tatio

n, 1

991;

Nill

es, T

rans

porta

tion

Res

ourc

es,1

988;

M

okht

aria

n Tr

ansp

orta

tion

Res

earc

h 19

97; M

okht

aria

n,

Envi

ronm

ent a

nd P

lann

ing,

199

6; H

andy

, Jou

rnal

of A

mer

ican

Pl

anni

ng A

ssoc

iatio

n, 1

995.

2.

Ea

rly th

eory

Th

eorie

s fro

m so

ciol

ogy,

psy

chol

ogy

and

orga

niza

tiona

l beh

avio

r. O

utco

mes

exp

lore

d in

clud

e w

ork

fam

ily b

alan

ce, o

rgan

izat

iona

l id

entif

icat

ion,

per

form

ance

, stre

ss a

nd jo

b sa

tisfa

ctio

n.

Ols

on, J

ourn

al o

f Soc

ial I

ssue

s, 19

84; K

raut

, Jou

rnal

of

Com

mun

icat

ion,

198

9; S

alom

on, T

echn

olog

ical

For

ecas

ting

and

Soci

al C

hang

e,19

84; S

ham

ir, A

cade

my

of M

anag

emen

t Rev

iew

19

85; V

enka

tesh

, Man

agem

ent S

cien

ce, 1

992;

Yap

, In

form

atio

n M

anag

emen

t, 19

90.

3.

Com

pute

r m

edia

ted

com

mun

icat

ion

Impa

ct o

f com

mun

icat

ion

tech

nolo

gy. T

heor

y ba

se in

clud

es S

ocia

l Pre

senc

e, S

ocia

l In

form

atio

n Pr

oces

sing

, Med

ia R

ichn

ess

Daf

t, M

anag

emen

t Sci

ence

, 198

6; M

cGra

th, G

roup

s, 19

84;

Org

aniz

atio

n Sc

ienc

e, 1

999.

Mar

kus,

Org

aniz

atio

n Sc

ienc

e,

1994

; Spr

oull,

Man

agem

ent S

cien

ce, 1

986;

Chi

dam

bara

m,

MIS

Qua

rterly

, 199

6; S

trau

s, Sm

all G

roup

rese

arch

, 199

6.

4.

Virt

ual t

eam

s Te

ams t

rans

cend

ing

time,

spac

e an

d cu

lture

s. U

se o

f ada

ptiv

e st

ruct

urat

ion

theo

ry. A

sub-

clus

ter o

f glo

bal v

irtua

l tea

ms u

tiliz

ing

grou

nded

theo

rizin

g an

d ca

se st

udie

s. O

utco

mes

exa

min

ed in

clud

e pe

rfor

man

ce,

info

rmat

ion

exch

ange

and

rela

tiona

l lin

ks.

T

owns

end,

Aca

dem

y of

Man

agem

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

.


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.


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.


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.


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.


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.


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.


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.


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.


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.