handbook of new media2

8/12/2019 Handbook of New Media2

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HANDBOOK

OfNEW MEDIA

Social Shaping

and Consequences of ICTsEdited by

LEAH A. LIEVROUW

and SONIA LIVINGSTONE

SAGE PublicationsLondon !Thousand Oaks !New Delhi


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13

New Media and Organizingat the Group Level

A N D R E A B . H O L L I N G S H E A D

andNOSHIR S . C O N T R A C T O R

sma l l groups have been de f ined by as collectives ranging from a minimum

IXI and in most cases three, to a maximum of 15 \ I rneinbcrs (cf. McGrath, 1984). Members of

have interdependent goals, are acquainted and interact with one another and have a sense

of hslon;ing. Recent developments in digital com-technologies have brought about a

change in our collective notion of what con- a group. Members of groups no longer need

IO hc formally constituted or to be co-present (in or place) to collaborate, share information or

Ins t ead new t echnologie s f ac i l i t a t e theinaintenance and dissolution of groups individuals who use different devices (such

~)hones. mobiles, laptops, personal digital assis- lo interact over one or more of a variety of

(audio, video, text and graphics) offered

~~eral forums (such as Internet newsgroups,chat sessions via Instant Messenger, and cor-

int ranets) . These developments have trig-t a shift in conceptualizations of groups from

traditional notion of same time, same place toany [inrc. anywhere and, some would argue apocry-phally. all the time, everywhere. In addition to

phys ica l and t empora l cons t r a int s , develop-meats in new media have a lso e l iminated con-sIr;llnts on the size of groups. In traditionalface-to-face groups, the size of the group is likely tobc rrlatiwly small and its membership is by defini-~OI :Iclosed set. This is also true for some geo-pphically distributed work teams that collaborateucmf communication technologies such as videoand ~oniputer confercncing. However, that is not

the case in many Internet-based newsgroups,

where the re a re l i t e r a l ly hundreds of pa r t i c ipant s(Alexander et al., in press). These participants maycoalesce as a group because of a common prac-

t i c e , such a s col l abora t ing on the deve lopment of a software program, or because of a common in t e re s t , such a s the i r conce rns about the use of

s w e a t s hop labour pr ac t i ce s or the i r i n t e re s t i ndownloading a particular genre of music. As aglobal community of consumers and producers we

are grappling with the opportunities and challengesof these new fluid group forms of organizing.

As researchers, we are challenged to redefine thetheoretical and methodological apparatus to studyhow new media shape , and a re in turn shaped by,the ways in which we organize in groups . Be fore

the deve lopment of the Wor ld Wide Web and theInternet, research on groups with technological sup-por t was dr iven by three bas i c goa l s : t o examine

how adequately new media could permit groups toovercome t ime and space constra ints , to evaluatethe impac t of t e chnologie s on the r ange and speed

of members access to information, and to evaluatethe impact of technologies on the groups task per-formance (McGrath and Hollingshead, 1994).

Much of the theory and r e sea rch addre s sed whenand how the structure, interaction and performanceof t e chnologica l ly enabled groups were s imi l a r to

and different frotn face-to-face groups. As such, thefocus of this research was on examining the ways inwhich new media s e rved to subs t i tu t e and enla rge

communicat ion among group members (Contractorand Bishop, 2000). With the surge in digital com-munica t ion t echnologie s , r e sea rche r s s t a r t ed to


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222 NEW MEDIA AND ORGANIZING

reckon with the idea that most technologicallyenabled groups were inherently different from face-to-face groups, and that they were worthy of study

as entities in their own right rather than simply to bebench marked against equivalent face-to-facegroups. Many of the premises of exist ing theories

were be ing cha l lenged by technolog ica l deve lop-ments and risked becoming less relevant at best, andobsolete at worst. Researchers are currently rethink-

ing their definitions of groups and are developingnew theories to explain and predict their behaviour,and are designing new methods to study them.

This chapter examines the role of new media atthe group level of analysis. Its emphasis is on howtechnology shapes and is shaped by the behaviour

of groups, rather than on issues relating to thedesign of hardware and software systems forgroup collaboration. The organization of this

chapter reflects the evolution in theory and researchon groups and new media. As we shall see, thetheory and research also reflects our evolving de5nitions of new media starting with early experi-ments in teleconferencing (audio and videoconferencing) in the 197Os,and continuing withproprietary computer-mediated communication

sys tems in the 19SOs, the r ise of the Internet andthe web as open communica t ion ne tworks in the199Os, and the ub iqu i tous , pe rvas ive and mobi lecommunication environment that ushers us into thetwenty-first century. The chapter begins with a brief

description of an early, but influential, classificationof technologies that support group interaction. Thesecond and third sections examine the theory andempirical findings of research that investigated howtechnolog ica l ly enab led group co l labora t ions a re

similar and different from face-to-face collabora-tions. As will become evident, most of this research

was conducted, or at least premised, on conceptual-izations of groups prior to recent developments in*@h,t m fx@~ Th~~f~~~ cP~~~~~~~~~

reconceptualization of groups that takes intoaccount the new forms of organizing enabled bynew media. This reconceptualizat ion al lows for a

more f luid, dynamic and activi ty-based defini t ionof groups and technology, and is drawn from a net-

work perspective. It presents a knowledge networkapproach to the study of groups and technology.

A CLASSIFICATION OFT HNOLOW ST H A T SU P P O R T GR O U P S

Collaboration among group members entails cogni-

tive as well as emotional and motivational aspectsof communication. Group members transmit, receiveand store information of various kinds, from eachother and from various other sources. Theseexchanges were viewed as distinct functions carried

out by group members. Hence, not surprisingly,

schola rs conceptua l ized the technolog ies th

support these functions to also be distinct. Witheye towards retrospective synthesis of research this area, McGrath and Hollingshead (1993; 1presented a classification system for communicasystems based on the functional role of technologto support group collaboration. The four categoof the classification system are based on whetthe technology: (1) provides within-group commnication (i.e. group communication support syste

or GCSS); (2) supplements information available the group or i ts members by information drafrom databases (i.e. group infonnation support

terns or GISS); (3) supports communication wthose outside the group (i.e. group external supp

systems or GXSS); and (4) s tructures group taperformance processes and task products (i.e. grperformance support systems or GPSS). The cla

fication system was developed in the early 19when the World Wide Web was in i ts infancy.was later updated to include communication tenologies available on the Internet (Hollingshe

2001). While the classification system was deoped at a time when distinct technologies supporthese different functions, it continues to be a via

framework to organize and examine contemporatechnologies that typically support more than onethese four functions.

GCSS: Technologies that Mediate orAugment Within-Group Communicatio

The signature feature of GCSS is its ability to p

mit group members to communicate usingmedia. In some cases GCSS may mediate comnication among members spatial ly separated

each other while they are communicating. Exampwould include video conferencing, or textls~~,~~Q~,~~~e~~~~~~~~~.~~~ \p WJ , .~n .er cx

GCSS may augment face-to-face communiutwby the use bf overhead projectors for communicatinggraphics or document-sharing software over worked computers. Some GCSS support asynchnous communication for group members interact

in different time periods; others require that gromembers interact synchronously. As these c~pies illustrate, GCSS vary in the communicatl~~channels that are available to group mcmbevisual, auditory, text and graphics.

Most research on GCSS has been based onpremise that the fewer modalities afforded bj Inologically mediated communication would liout some of the cues in face-to-face communicnlio(Culnan and Markus, 1987). Based on this as~tion, the research agenda sought to examine hog performance of groups using GCSS was moderaby the particular task(s) and activities in which group was engaged, the experience of tht gwith the technology, and the degree to which pro


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ORGANIZING AT THE GROUP LEVEL 223

Table 13.1 A typologyofgroup communication support systemsModalities available Svnchronous AsvnchronousVisualA u d i o

Text, graphics

I n t e r n e t

Video conference

Phone conference

Computer conference

N e w s g r o u p sChat rooms

Videocassette exchange

Voice mail

Audiotape exchange

E-mail

Fa x

Home pages, websites

members have a shared conceptualization of management programs that organize schedules,

relative expertise (Hollingshead, 1998a; 1998b; files, contacts and other information on desktops to

Hollingshead et al., 1993). In addition to examining facilitate information exchange with other members.the performance of groups using GCSS, some Microsoft Outlook, which comespreloaded onresearch has focused on the interaction process many PC-compatible computers, is one such

among group members. This research McGrath information management program. More recentand Hollingshead, 1994) has found evidence that exampl es includ e softwa re agents such as web-the sequencing, synchrony and timing of messages bots, or web-based robots, that assist group

a mong group members using GCSS is moderated members by providing them, in some cases pro-by the size and nature of the groups, as well as the actively, with rel evant info rmation sca nned from

level of ambiguity among group members. digital repositories.

Table 13.1 provides examples of GCSS organi-

zed by the communication channels provided by thetechnology (video, audio, text/graphics) and thetemporal distribution of members, i.e. whether theyare communicating synchronously or asynchro-nously. As noted at the start of this section, GCSS

can support communication between members whoare co-present or are geographically distributed.However, as we shall see in the review of empirical

research, the preponderance of research on GCSShas been among geographically distributed groups.

Culnan and Markus (1987) a rgue tha t th i s b iasreflects an early preoccupation with the role of GCSS to mediate rather than to augment face-to-face communication. The organizing scheme alsoinc ludes ca tegor ies fo r In te rne t t echnolog ies ,

although World Wide Web browsers can supportvideo conferencing, audio conferencing and docu-m e n t s h a r i n g o n t h e I n t e r n e t .

GXSS: Supporting External

Communication

ISS Supplementing InformationAvailable to the Group

The GXSS function is a special case of both theGCSS function and the GISS function. Com-munication between group members and key exter-

nal human agents can be done with any of theGCSS systems described above. At the same t ime,one can consider interaction with non-human

agents (such as webbots) external to the group asaccessing yet another kind of information database,thus making it a special case of GISS. Organi-

zations are increasingly able to interconnect seam-lessly the human agents and non-human agents on

their intranets with those of their clients, partners,suppliers or subcontractors, via secure web-basedextranets (Barr et al . , 1998). As such, extranets

serve as a unified infrastructure for GXSS thatreaches beyond the traditional organizationalboundary or its digital analogue, the corporatefirewall.

iroup members have access to many repositoriesof information or knowledge besides other group

members. These repositories include databases,archives and intranets. Intranets are web-basedtechnologies that support knowledge distribution

among networks of teams within organizations. Thetypes of knowledge that are available to groupmembers on intranets can include: (1) human

resources, (2) sales and marketing activi t ies ,I!) financial information, and (4) design and manu-facturing specifications and innovations (Bar et al.,

1098). Other examples of GISS are information

GPSS: Modifying the Groups Task

Performance

For several decades, researchers have designed andeva lua ted s t ra teg ies to s t ruc ture the in te rac t ionamong group members in order to enhance their

effectiveness. These strategies, often under thestewardship of a facilitator or supervisor, constrainand structure the communication, the task informa-

tion available, and/or the form and sequence of taskresponses permitted and required of the group


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2 2 4 NEW MEDIA AND ORGANIZING

Some examples of such strategies are brainstorming,the Delphi method and the nominal group technique

(NGT) (for a summary, see McGrath, 1984) .More r ecent ly , t e chnologica l ly enabled group

performance support sys tems (GPSS) have beendeployed to assist with these strategies. An influential

effor t has focused specif ica l ly on technological lyenabled strategies to enhance decision-makingamong groups. These GPSS are a lso cal led GDSS

or group decision support systems (see Jessup andVa lac ich, 1993, for d i s cus s ion) . In the l a t e 1980sand early 1990smost GPSS were in the form ofdecision rooms specially equipped computer labssuppor t ing synchronous groups wi th co- loca ted

members . Most groups used these systems to aug-

ment their face- to-face decis ions . These systemsva r i ed a s to the type of t a sk suppor t provided to

groups, the size of groups that could use thesystem, and whether a t ra ined faci l i ta tor was nec-e s sa ry to augment the GPSS. Those tha t provided

direct task support for groups usually incorporatedan a r r ay of module s , each of which st ruc ture s adifferent subset of a groups tasks or different por-t ions of the group proces s on a g iven projec t . For

example , a GPSS might include tools or modulesfor electronic brainstorming; for structuring variousforms of evaluation and voting (rating, ranking,

weighing, pick one, pick any, etc.); for identifyingstakeholders and bringing their assumptions to thesurface; or for exchanging anonymous or identified

comments on any or a l l topics . Effor ts are underway to develop these systems to support asynchro-nous and synchronous groups on the Internet. More

recent ly , GPSS have been des igned to encompassmore than jus t decis ion-making. Current effor ts inthe area of workflow management, enterpriser e source planning and compute r - suppor t ed coope r -ative work (discussed by Star and Bowker andothers elsewhere in this volume) underscore efforts

to enhance group performance beyond simplydec i s ion-making.

THEORETKAL PERSPECTIVES

Most pr ior theory and r e sea rch have focused pr i -marily on how groups using technology accom-plished their tasks differently from groups withoutaccess to technology. More specif ica l ly, much of

the early theory relevant to the study of groups andtechnology addressed how the interaction and per-

formance of groups that were separated in spaceand time differed from face-to-face groups. Thisresearch centred on those technologies classified asGCSS. One se t of theor i e s dea l t wi th the topic of media choice or media se lect ion: how people makechoices about dif ferent media to use in their com-munication with others. Another set dealt with the

topic of media effects: how technologies can impact

group interaction processes and group outcomes. thi rd s t ream of theor iz ing explored the intcrrdtions between technologies and group interactionattempting to integrate the arguments ofl~by media choice and media effects thcorlSpec i f i ca l ly , adapt ive s t ruc tura t ion theory Xexamined how the s t ructures that are imptechnologies recursively shape and in turn shaped by group interaction. Most of the empmi nves t iga t ions of th i s pe r spec t ive were conducrwith technologies classified as GPSS. Finally.most current theory that relates to group s

technology deals with the complexity of grprocesses, and suggests that technology is onl) of many factors that can inf luence group proccand outcomes .

Media Choice

Some of the earliest theoretical work on IWchoice was conducted before computer usewidespread, and hence dea l t wi th cornrnunicall~llsystems other than computers . Short e t a l . 117 proposed the sociul presence model to prcwhich media individuals will use for certain ~of interactions. Social presence refers to the depof salience of the other person involved in the itIlaction, and was therefore assumed to be an ohltive dimension that could be calibratedresearcher independent of the users. They hyporhs ized that media dif fered in their socia l preseilcand that individuals are aware of and agree ondifference and use it as a basis of their mchoice. For instance, they argued that on an oqt ive scale , text-based communicat ion has a losocial presence than video conferencing, which

turn has a lower soc ia l pre sence than face-to-lcommunicat ion. Further they argued that indivlals would select a communication medium thata social presence commensurate with the task

were t rying to accomplish. Specif ica l ly, theydieted that individuals avoid a given medium fisgiven type of interaction if they perceive

medium as not providing a high enough degreesocia l presence for that type of interact ion. Talso predicted that communication using mediain socia l presence would be more appropria tetask-re la ted communicat ion while media highsocia l presence, such as fac t- to-face communit ion, were more appropria te for t ransact ing ipersonal (or socioemotional) content,

Daft and Lengel (1986) extended the idembodied in the social presence model intheory of media richness. They proposed thatferent forms of communication differ in the ness of the information that they provide, Richnwas def ined as the abi l i ty of a medium to provmultiple cues (verbal and non-verbal), and immate (or quick) feedback, us ing mult iple modali


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ORGANIZING AT THE GROUP LEVEL ,>i--_

(text, video, audio and graphics). Based on these

criteria they arrayed the various media from verylean (company policy manuals for rules and regula-t ions) to lean (formal information systems) tosomewhat rich (direct contact) to very rich (group

meetings). Further, they argued that the variousinfonnation processing tasks conducted by group

members could also be objectively arrayed in termsof their equivocality and uncertainty. Some com-

munication tasks, such as finding the latest salesfigures, entailed reducing uncertainty (that is, find-

ing the right answer to a question). Other tasks,such as crafting a sales strategy, required reducingequivocality (that is, determining what is the right

question to answer). Media richness theory pro-posed that rich media were more appropriate to

reduce equivocali ty and lean media were moreappropriate to reduce uncertainty. Daft and Lengelargued that managers use (and should use) differentcommunication methods of appropriate degrees ofrichness to deal with situations that differ in equivo-cality and uncertainty. Hence, different communi-

cation media, or s tructural mechanisms in theirterminology, need to be used for different types of organizational tasks. The more equivocality a situ-ation involves, the richer the information requiredto dea l wi th i t . They presen ted seven s t ruc tura lmechanisms ordered along an information richness

continuum based on capacity for resolving equivo-cality versus reducing uncertainty. The sevenmechanisms included: group meetings, integrators,

direct contact , planning, special reports , formalinfonnation systems, and rules and regulations.

At the time media richness theory was first pro-

posed, e-mail was not widely available in organiza-t ions ; however , th i s theory was fea tured qu i teprominently in early empirical research that

addressed predictors of e-mail usage in organiza-tions. It was argued that managers whose choice ofmedia reflected the equivocality or uncertainty of

the task were perceived to be more competent .Some researchers (Trevino et al., 1990) found sup-port for this argument, but many others did not (e.g.El-Shinnawy and Markus, 1997). One of the earlycriticisms of the model was that, like social pres-

ence theory, it assumed that media richness wasconsidered to be an objective dimension; that is,each medium provided the same amount of rich-

ness, predetermined by the inherent attributes of thetechnology, regardless of who was using it (Culnanand Markus, 1997). Other scholars proposed thatmedia r ichness was a subjective dimension. Forexample, e-mail may be perceived as a richermedium by people experienced with that techno-

logy than by those who are not. Still others notedthat most tasks involved varying degrees of uncer-tainty and equivocality and that it was often not fea-

sible to parse the task into subtasks that wereunifonnly high or low in terms of their uncertaintyor equivocality. As such, for these unbundled tasks

it did not make much sense to dictate the use of leanor r ich media.

Social presence theory and media richness theorywere influential early attempts to understand media

choice among group members. The lack of consis-tent empirical support for these theories was attri-

buted to the theories assumptions about ascribingobjective attributes (social presence or media rich-ness) to different communication technologies. As

a result , al ternative media selection theories wereput forward that could account for these inconsis-tent findings.

One such theoretical formulation was the social

irEfluerlce model. Fulk et al. (1990) contended thatthe media r ichness model is more normative thandescriptive of communication patterns in organiza-

t ions . They a rgued tha t ind iv idua l percep t ions o f the information richness of various media can vary,and that it was important to measure those percep-

tions rather than to rely solely on an objectiveassessment. They contended that objective featuresof media r ichness can and do influence individual

perceptions of media r ichness, but there are othersources of such influence, such as social inter-

action. Drawing upon earlier research on sociallearning theory and social information processingtheory , they a rgued tha t soc ia l in te rac t ion in theworkplace shapes the creation of shared meanings.

and that those shared meanings provide an impor-tant basis for shared patterns of media selectionFulk et al., 1990; Schmitz and Fulk, 1991).

The social influence model hypothesized that

media perceptions and use: (1) are subject to socialinfluence; (2) may be subjectively or retrospec-

t ively rat ionalized; (3) are not necessari ly aimedat maximizing eff iciency: and (4) may be designed

to preserve or create ambiguity to achieve strategicgoals. Schmitz and Fulk (1991) found that per-ceived (as distinct from objectively defined) e-mailrichness predicted individuals e-mail assessments

and usage and that the opinions of colleaguesinfluenced others media assessments. These results

supported the notion that other group memberscan in f luence how ind iv idua ls perce ive and usetechnology.

The social influence model of media selection

explici t ly recognized the role of group memberscommunication networks in shaping their percep-t ion of media r ichness. An important implication,

not addressed by the social influence theory, washow media selection in turn influenced the subse-quent structure of the communication network itself

(Contractor and Eisenberg, 1990). For instance,group members may be socially influenced by othermembers in their primarily face-to-face communi-

cation network to begin using e-mail. However.once these members begin to use e-mail , the new

contacts available through this new medium mayenlarge and possibly modify their pre-existing com-munication network. That is, it is possible that the


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22 6 NEW MEDIA AND ORGANIZING

networks that socially influence individuals mediachoices may in turn occasion a restructuring in theircommunication network. In essence, this observa-

tion points to a media effect resulting from amedia choice. The following section describes aninfluential stream of research on the effects of

media use on groups.Media choice theories may be rendered less rele-

vant today by developments in technologies.

Increasingly, the convergence to a unif ied mult i-modal (audio, video, text and graphic) forum forcommunication makes interest in the dist inctions

between media, and hence the question of mediachoice, obsolete. Unlike the context in which mediaselection theories were developed, today it is

increasingly plausible - even probable ~ for groupmembers to simultaneously communicate viamultiple modalities through a single device. An

example would be the use of the web page tosimultaneously communicate via audio and video,whi le shar ing a document , and jo in t ly execu t ing a

graphic s imula t ion .

Media Effects

Hiltz and Turoff (1978) were among the first to

describe differences between face-to-face andcomputer-mediated interaction in terms of social andpsychological processes, and to discuss the impor-

tance of task-media contingencies. Hiltz and Turoffargued that groups communicating via computerhad access to a narrower band of communication

than groups communicating face-to-face. For exam-ple, non-verbal communication and paralanguageeither were not available or were substantially

reduced in computer-mediated communication. Insome si tuations, such narrowband communicationallowed information to be communicated with more

precision and less noise, and afforded the opportu-nity for rational judgement processes to operate inthe group with less intrusion of non-rational consid-

erations. In other situations, computer conferencingneeded to be supplemented by other media in whichnon-verbal communication and paralanguage were

available. They were also among the first to presentempirical findings that explored the effects of com-puter conferencing on the distribution of participa-

t ion among members, on the amount of task andsocial communication, and on user responses to theava i lab i l i ty and the i r sa t i s fac t ion wi th the sys tem(Hiltz et al., 1986).

Kiesler et al. (1984) provided a theoretical ration-ale as to why and how groups will differ when they

use computer-mediated as compared with face-to-face communication. They proposed that computer-mediated communication depersonalizes thein te rac t ion process , with several concomitant

effects. Individuals tend to lose mental sight of theirinteraction partners. At the same t ime, they lose

access to a variety of cues that provide feedback to

members regarding the impact of their behaviour oninteraction partners, their status and their indivi-duali ty. Thus, computer-mediated communication

removes substantial social infomlation and elimi-nates much of the feedback that people ordinarilycommunicate to one another face-to-face. This can

have both positive and negative influences on theinteraction processes, task outcomes and responsesof users (Sproull and Kiesler, 199 1).

People feel less inhibited when interactingthrough a computer network as a result of the reduc-tion in social cues that provide information regard-

ing ones status in the group. Therefore, participantsconcentrate more on the messages and less on thepersons involved in the communication. Individuals

feel less committed to what they say, less concernedabout it, and less worried about how it will be

received by their communication partners. Becausepeople communicating electronically are less awareof social differences, they feel a greater sense of

anonymity and detect less individuality in others.As a consequence, individuals engaged in computer-mediated group interaction tend to:

1 feel more anonymous and detect less individual-ity in their communication partners;

2 part icipate more equally (because low-statusmembers are less inhibited);

3 focus more on task and instrumental aspects and

less on personal and social aspects of interaction(because the context is depersonalized);

4 communicate more negative and more uninhibi-ted messages (because they are less concernedwith politeness norms that tend to regulate com-

munication in face-to-face groups); and5 experience more difficulty in attaining group

consensus (both because of elimination of much

interpersonal feedback, and because of reducedconcern with social norms).

All of these effects have been demonstratedempirical ly (for review, see Kiesler and Sproull ,

1992), and will be revisited in greater detail later inthis chapter.McGrath and Hollingshead (1993; 1994) build-ing on the work described above and applying it towork groups, maintained that group interaction andperformance are greatly affected by the type and

difficulty of the task that the group is performing,and that the effects of technology on group inter-action and performance interact with task type.They hypothesized that the effectiveness or5 groupon a task will vary with the fit between the richnessof the information that can be transmitted using thatsystems technology and the information richnessrequirements of the groups task. However, asgroups developed more experience with a givencommunication technology, the r ichness of the

information that could be transmitted effectively VIIthat technology would increase.


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McGra th and Hol l ingshead pos i ted tha t g roup

tasks differed in their information richness require-ments. Information richness referred to how muchthe information contains surplus emotional, attitu-

dinal, normative and other meanings, beyond theliteral cognitive denotations of the symbols used toexpress it. They also posited that communicationmedia differed in the r ichness of the information

that they can and do convey. Face-to-face commu-

nication among interpersonally involved humanswas the richest medium; communication in written

form among strangers was the least rich. Computercommunication among group members inexperi-enced with the technology is at the low-richness

end of that continuum.Drawing from McGraths (1984) task typology,

McGra th and Hol l ingshead hypothes ized tha t

groups work ing on genera te t asks (e .g . s implebrainstorming tasks) do not require the transmission

of evaluative and emotional content. As a result,computer-supported groups may brainstorm moreeffectively than face-to-face groups. At the otherend of the con t inuum, groups negot ia t ing and

resolving conflicts of views or interests may requirethe transmission of maximally r ich information,including not only facts but also values, attitudes,

emotions, etc. As a result, groups interacting face-to-face should perform such tasks more effectivelythan groups interacting via computer. In between

the two ends of the continuum are intellective tasksthat have a correct answer or decision-making tasksthat do not have a correct answer, which may

require some intermediary level of informationrichness. The predict ions for generate tasks and

negotiation tasks received empirical support(Gallupe et al., 1991; Hollingshead et al., 1993;Valacich et al., 1994), but not those for intellectiveand decision-making tasks (Hollingshead et al.,1993; Straus and McGrath, 1994).

McGrath and Hollingshead (1994) also predicted

tha t communica t ion technolog ies cou ld prov ideinformation of increasing r ichness over t ime, asgroups learned how to embed additional emotional,

attitudinal, normative and other meaning throughc o n t i n u e d e x p e r i e n c e .

In summary, the theoretical arguments reviewed

in this section offer three related perspectives onhow technologies may influence the processes andoutcomes of groups. While they vary in their levels

of sophistication and theoretical complexity, allthree theoretical approaches to media effects arebased on the premise that technological attributes

of different media influence key aspects of theinteraction process. These key aspects include theavailability of non-verbal cues, the potential for

anonymous contributions, the ability to communi-cate status differentials, and the information richnessof the medium. These key aspects in turn helped or

hindered the groups interaction process (such asamount of participation, distribution of participation

and negativi ty in communication on f laming) , aswel l a s the g roups ou tcomes ( such as consensus ,accuracy and speed of decision-making).

As such these theoretical perspectives on mediaeffects acknowledge a modicum of technologicaldeterminism. Not unlike the media choice theories

of social presence and media r ichness, discussedin the previous section, the theories of mediaeffects described in this section do not privilege a

socially constructed explanation for understandingmedia effects . The following section offers a theo-retical framework that explicitly recognizes the

social nature of technology and advocates an inex-tricable interrelatedness between media choice andmedia effects.

Adaptive Structuration Theory

Adapt ive strucmration theory CAST), p roposed byPoole and DeSanctis(1990) and inspired by thein f luen t ia l theore t ica l con t r ibu t ions o f Giddens(1984) s t ruc tura t ion theory , s t resses the impor-tance of group interaction processes, both in deter-

mining group outcomes and in mediating theeffects of any given technology. Essentially, asocial technology presents a structure of rules and

operations to a group, but the group does not pas-sively choose the technology in its pre-existingform. Rather, the group actively adapts the tech-

nology to its own ends, resulting in a restructuringof the technology as it is meshed with the groupsown interaction system. Thus, a technology can be

thought of as a set of social practices that emergeand evolve over t ime.

From this point of view, the structure of a group

is not a permanent, concrete set of relationsbetween members and their tasks. Rather, the struc-ture is an evolving set of rules and resources avail-

able to them to produce and reproduce the apparently

s tab le in te rac t ion sys tems tha t we observe . Thus ,there is a recursive process between the structures

(or the rules and resources in a group) and thesystems (the interaction patterns in the groups). Theru les o r resources in the g roup shape the in te rac -

t ions patterns among group members. The interac-t ion patterns among the group members, in turn,reify or subvert the rules and resources in the

group . This recurs ive process i s ca l led adap t ivestructuration.

The ru les and resources tha t g roups use in the

structuration process are sometimes created on thefly by the group, but more often they arejU ul/~~uppropriated by the group based on the social con-text in which it is embedded. Appropriation is the

process by which a group selects features of a tech-nology and socially constructs their meaning. It isthrough such appropriation that a group can chooseto use a new technology. In some cases the groupmay not appropriate a technology in ways that were


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2 2 8 NEW MEDIA AND ORG 3NIZING

in tended by the des igners o f the technology . Thissi tuation is referred to as an irattic uppt opriatiotzFor instance, a group may have access to a groupdecision support system (GDSS) that provides themwith an opportunity to vote on their ideas. The voting

tool is intended by the designers of the technologyto facil i tate democratic deliberat ion among group

members. However, in some instances members ofa group may use the voting tool to prematurelyclose off discussion of an issue. This action would

il lustrate an ironic appropriat ion of the GDSS. Byfaithfully or ironically appropriating a technology,each group invests meaning in, and thereby adapts

for i t s use , the ru les and resources tha t i t d rawsupon. Both technology and context affect group

processes and outcomes because they affect thisappropriation process.

Empirical research has shown that different , butseemingly similar, groups appropriate the same

technology in different ways (DeSanctis and Poole,1997; Poole and DeSanctis, 1992; for a review seeDeSanc t i s and Poole , 1994) . Zack and McKenney(1995) offer a recent example of work in this tradi-

t ion They examined the appropriat ion of the samegroup authoring and messaging computer system by

the managing editorial groups of two morningnewspapers owned by the same parent corporation.Drawing upon Poole and DeSanctis (1990) theoryof adap t ive s t ruc tura t ion , they d i scovered tha t the

two groups appropr ia t ion of the technology , as

indexed by their communication networks, differedin accordance with the different contexts at the two

loca t ions , Fur ther , they found ev idence tha t thegroups performance outcomes for s imilar taskswere mediated by these interaction patterns.

Adaptive structuration theory continues to be anincreas ing ly in f luen t ia l pe rspec t ive to unders tandthe socially constructed ways in which groups

choice of media and the effects of media on groupscoevolve.It provides a powerful analytic frame-work to account for stability and change in a

groups appropriation of new media. While the util-i ty o f a s t ruc tura t iona l pe rspec t ive to the s tudy of groups use of new media is compelling, there con-

tinues to be a debate about the extent to which

empirical s tudies offer a test as opposed to anillustration of structuration theorys ability to

explain the unfolding of complex processes(DeSanctis and Poole, 1994). Indeed, in a review ofempirical studies from a structurational perspective,

one would be hard pressed to identify a single workwhich failed to find support for adaptive structura-t ion theory. Such overwhelming endorsement of

a theory be l ies an under ly ing concern about thepotential falsitiability of the theory. An appropriatechallenge therefore would be to come up with spe-cif ic predict ions from the theory that , i f they were

not empirically validated, would plausibly representa refutat ion of the premises of adaptive structura-t ion theory . Complex i ty theory , d i scussed in the

next section, offers a novel and useful approach totranslate the richly evocative, but highly abbrevi-ated, verbal explications of adaptive structuration

theory into precise, falsiliable hypotheses that canbe empirically validated (Poole, 1997).

Groups as Complex Systems

In the past decade there has been a plethora of scholarship calling for the extension of complexitytheory arguably a mainstay of many disciplines in

the physical and life sciences ~ to social sciences ingenera l , and to the s tudy of g roups in par t i cu la r(Arrow et al., 2000; Contractor and Seibold, 1993;

Contractor and Whitbred, 1997; Gersick, 1991:McGrath, 1991). The motivation for this call stemsfrom a widely shared frustration with extant

theories, which have proven to be inadequate atuntangling with precision the complexity in groupprocesses. The phenomena described in verbal

expos i t ions o f , say , adap t ive s t ruc tura t ion theoryinvoke a multitude of factors that are highly inter-connected, often via complex, non-l inear, dynamic

relationships. Lamenting the failed promise ofear l ie r fo rays in to sys tems theory , Poole no tes ,Most often, systems theory became a metaphor,

rather than an instrument of analysis (1997: 50).Two streams of research that attempt to go beyondthe use of complexity theory as a metaphor

(Contractor, 1999) have been developed to dealwith the complexity of groups use of new media:groups as self-organizing systems (Contractor and

Seibold, 1993; Contractor and Whitbred, 1997) andgroups as complex, adaptive and dynamic systems(Arrow et al., 2000).

Groups as Self-organizing SystemsIn general terms, self-organizing systems theory(SOST) seeks to explain the emergence of patterned

behaviour in systems that are initially in a state of dis-organization. I t offers a conceptual framework toexplicitly articulate the underlying generative mech-

anisms and to systematically examine the processes

by which these mechanisms generate, sustain andchange existing structures or elaborate new struc-

tures (Contractor and Seibold, 1993: 536).llya Prigogine and his colleagues proposed the

theory of self-organization. In an effort that con-

tributed to a Nobel Prize, Prigogine and hiscolleagues (Glansdorff and Prigogine, 1971)mathematically proved that systems that exhibit

emergence of spontaneous order must meet thefollowing logical requirements:

1 At leas t one of the components in the sys tem

must exhibit autocatalysis, i.e. self-referencing.2 A t l ea s t tw o of t h e c o m po n e nt s i n t h e s y s t em

must be mutually causal .


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ORGANIZING AT THE GROffP LEVEL 229

; The system must be open to the environmentwith respect to the exchange of energy andmatter .

4 The system must operate in a far-from-equilibrium condition.

These four requirements offer, at a very abstractlevel, the conditions under which any system canself-organize. Our interests here are in applyingthese concepts to the study of groups using newmedia. Contractor and Seibold (1993) developed a

self-organizing systems model for groups use ofgroup decision support systems (GDSS). Theydeveloped a model based on the theoretical mechan-

isms spec i f ied by adap t ive s t ruc tu ra t ion theory[Poole and DeSanctis, 1990; discussed in the previ-ous section) about the recursive interrelationship

behveen the structures (the rules and resourceswithin the group) and the systems (the interactionpatterns among the group members). Contractor

and Seibold (1993: 537-8) specified four genera-tive mechanisms that were consistent with the theo-retical tenets of adaptive structuration theory and

met the logical requirements of self-organizingsystems theory:

1Members expertise (or resources) with theta sk w i l l re in force the con ten t and pa t te rnof their communication during GDSS-baseddiscussions.

2 The content and pattern of members communi-cation will reinforce their perceptions of thegroups norms for structuring the GDSS-based

discussion.3 Members expertise (or resources) with

GDSS will reinforce their perceptions of the

groups norms for structuring the GDSS-baseddiscussions.

4 Members perceptions of the groups norms

for s t ruc tu r ing the GDSS-based d iscuss ionwill reinforce the content and pattern of their

co mmu n i ca t i o n .

Using simulations, they showed that based on thesefour theoretical mechanisms the groups use ofGDSS would self-organize only under a very speci-ficrange of initial conditions. A group using GDSSwas considered to have self-organized when the

groups structures (that is, its members perceptionsof the rules) were stable and the group membersinteraction patterns were reproducing and reinforc-

ing (rather than subverting) these stable structures.The simulation also provided precise conditionsunder which the groups would 1~01 successfullyappropriate the technology. That is, the group mightinitially attempt to use the technology but wouldthen discontinue its use. These results, theoreticallygrotmded in adaptive structuration theory and logi-ca l ly cons is ten t w i th se l f -o rgan iz ing sys tems

theory, represent plausible occurrences in groupsuse of new media. They also respond to one of the

criticisms levelled against adaptive structurationtheory by making its explanations more amenableto falsification. In general terms, the approach illus-

trates how self-organizing systems theory can offerthe log ica l cond i t ions and the ana ly t ic f rameworkto discover precise, empirically falsifiable hypothe-

ses about the use (and lack thereof) of new mediaby groups.

Groups as Complex, Adaptiveand Dynamic Systems

Arrow et al. (2000) have proposed a general theory

of complex systems, which embeds technology asone aspect of the system. This theory builds on thetime interaction and performance (TIP) theory pro-

posed by McGrath ( 199 1). TIP theory assumes thatgroups pursue multiple functions for multiple pro-

jects by means of complex time/activity paths.

Arrow et al. (2000) extend this theory by proposingthat all groups act in the service of two genericfunctions: (1) to complete group projects and (2) to il il me el needs. A groups success in pursuingthese two fimctions affects and depends on the via-bility and integrity of the group as a system. Thus,mnifztclinillg system ilztegrig, becomes a third func-tion, instrumental to the other two. A groupssystem integrity in turn affects i ts abili ty to com-

plete group projects and fulfil member needs.Groups include three types of elements:

(1) people who become group rnel,lDers; (2) goals thatare embodied in group projects: and (3) resourcesthat get transformed into group technologies.Technologies differ in how much they facili tate or

cons t ra in in te rpersona l ac t iv i ty , ta sk ac t iv i ty andprocedura l ac t iv i ty ; and in how ef fec t ive ly theysupport different instrumental functions (i .e . pro-

cessing of information, managing of conflict andconsensus, and motivation, regulation and coordi-nation of member behaviours).

A group pursues i t s func t ions by c rea t ing andenacting a coordinated pattern of member-task-tool relations, its coor dinntion netw r k Thefu l l coord ina t ion ne twork inc ludes s ix componentne tworks : (1 ) the member network, or pa t te rn o f member-member relations (such as status rela-

tions); (2) the tnsk network, or pattern of task-taskrelations (e.g. the required sequence for completionof a set of tasks); (3) the tool netwol.k or pattern oftoo l - too l re la t ions (e .g . the p rocedure by which atechnology can be used most efficiently); (4) thelabour network, or pattern of member-task rela-tions (i.e. who is supposed to do what); (5) the rolenetwork, or pattern of member-tool relations (i .e .how members do their tasks); and (6) the job netwalk or pattern of task-tool relations (e.g. whatpiece of equipment must be used for a given task).

The life course of a group can be characterized

by three logically ordered modes that are conceptu-a l ly d is t inc t bu t have fuzzy tempora l boundar ies :


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2 3 0 NEW MEDIA4 AND ORGANIZING

jbrmation, operation and metamorphosis. As agroup forms, people, intentions and resources

become organ ized in to an in i t i a l coord ina t ion net-work of relations among members, projects andtechnology that demarcates that group as a

bounded soc ia l en t i ty . As a g roup opera tes overt ime in the service of group projects and memberneeds, i ts members elaborate, enact , monitor and

modify the coordination network establishedduring formation. Groups both learn from theirown experience and adapt to events occurring intheir environment. If and when a group undergoes

metamorphosis , i t dissolves or is t ransformed intoa different social entity.

OV E R V I E W OF MA J O R EM P I R I C A L F I N D I N G S

A number of scholars have written literature

reviews that examine communication technologiesand groups (e.g. Benbasat and Lim, 1993;Hollingshead and McGrath, 1995; Kiesler and

Sproull, 1992: Kraemerand Pinsonneault, 1990;McGra th and Hol l ingshead , 1994; McLeod , 1992;1996; Seibold et al., 1994; Williams, 1977). Most of

these reviews have compared the interactionprocesses and outcomes of computer-mediatedgroups with those of face-to-face groups. Several of

those reviews have reached the same conclusions

about the s ta te o f knowledge in th i s a rea : namely ,that more theory-guided and programmatic researchis needed (e .g . Hol l ingshead and McGra th . 1995;

McLeod, 1992).

Interaction Patterns

Many studies have revealed that groups interactingvia computers have more equal participation among

members than groups interacting face-to-face (e.g.Clapper et al., 1991: Daly, 1993; Dubrovsky et al.,1991; George et al., 1990; Hiltz et al., 1986;

McLeod, 1992; Rice, 1984; Siegel et al., 1986;Straus, 1996; Straus and McGrath, 1994; Zigurs

et al., 1988). As described earlier, the general expla-nation for the effect is that people feel less inhibitedwhen in te rac t ing th rough a compute r ne twork as aresu l t o f the reduc t ion in soc ia l cues tha t p rov ide

informat ion regard ing ones s ta tus in the g roup .Because people communicating electronically areless aware of social differences, they feel a greater

sense of anonymity and detect less individuality inothers (Sproull and Kiesler, 1991). It is important tonote some common elements across this set of stud-ies. These studies were conducted during one

experimental session with nd hoc groups consistingof s tudents in a l abora tory se t t ing . However , i t i salso important to note that this finding was observed

across a variety of communication technologies.

Many studies have also showed no evidence ofthe participation equalization effect in computer-mediated groups (Berdahl and Craig, 1996;Hollingshead, 1996b; Lea and Spears, 1991;McLeod and Liker, 1992; McLeod et al . , 1997;Saunders et al., 1994; Spears and Lea, 1992;

Watson et al., 1988; Weisband, 1992; Weisbandet al., 1995). In fact, most showed that status differ-ences among participants were displayed in theirinteraction in the computer-mediated setting. One

explanation for the inconsistency of findings acrossstudies is that s tatus differences among members

within the groups may have been differential lysalient across studies. When members identitieswere known or were available visually, the status

differences in the number of contributions and theperceived influence of those contributions weremaintained in the computer-mediated setting. When

they were not or when members contributions wereanonymous, the part icipation equalizat ion effectwas more likely to occur.

I t i s a l so poss ib le tha t the par t i c ipa t ion equal-izat ion may be an indication of how the mediumreduces the baseline of each members participa-tion rather than how the medium leads to increasedpart icipation of low-status members during thegroup d i scuss ion (McGra th and Hol l ingshead ,

1994; Spears and Lea, 1994). It takes more time totype a message on a computer network than it doesto say that same message verbally. In the experi-ments cited above, the computer sessions were atleast as long as those face-to-face group meetings;however, the amount and the rate of communica-t ion in the computer-mediated set t ing were muchless . Another poss ib le t echnolog ica l exp lana t ionfor greater egalitarian participation patterns in

computer-mediated settings is that electronicgroup members have the ability to participatewithout in te r rup t ion , s ince tu rn- tak ing i s no t a

norm in a computer-mediated environment(Weisband et al . , 1995).

A number of studies have found that computer-

mediated groups exchange less information and areless likely to repeat information in their decisionsthan face-to-face groups (Holl ingshead, 1996a;

1996b; McLeod et al., 1997; Straus and McGrath,1994). In some cases, this reduction can lead topoorer outcomes for newly formed groups (cf.

Hol l ingshead , 1996a; 1996b) .

Performance

Very few studies have demonstrated that groupscommunicating via computer perform better thangroups interacting face-to-face, although many

have demonstrated that computer-mediated groupsperform less well than or equally well as face-to-face groups (for reviews see McGrath and

Hol l ingshead , 1994; McLeod , 1992; 1996) . Even


12/16


though computer-mediated groups generate lesscommunication and use less information in theird ions, they take longer to make themthollingshead, 1996a). They are also less likely toreach consensus (for reviews see Hollingshead andMcGrath, 1995; Kiesler and Sproul, 1992).

As described earlier, there seems to be an inter-action effect of task and technology on the quality

of group performance. Computer groups produce

more ideas of higher quality on idea generationtasks. Face-to-face groups tend to have higher-quality products on intellective and negotiationtasks. However, i t may be the structure that isimposed by the technology rather than the techno-

logy itself that is responsible for this effect(Hollingshead and McGrath, 1995). The task struc-ture may include: procedures that s implify thehandling of complex information; procedures that

explicate agenda, thus making group process moreorganized; and procedures that expose conflict and

help the group to deal with i t . Some researchshowed that a paper and pencil version of the taskstructure imposed by the technology (i.e. without

electronic communication) gave higher-quali tydecisions than the same task structure provided by aGPSS, which in turn was higher than the no-structure face-to-face condition (Hollingshead andMcGrath, 1995; Watson et al., 1988). In some cases,newly formed groups on computers may have prob-

lems with task structure that requires more complexinformation processing (Hollingshead, 1996a).

Longitudinal research comparing the impact of

computer-mediated and face-to-face communica-tion over time has brought into question previousfindings of significant differences in performance

between face-to-face and computer-mediatedgroups. That research has shown that computer-mediated communication hinders the interaction

process and performance of groups initially, butover time, groups can adjust successfully to their

mode of communication (see McGrath et al., 1993and Arrow et al., 1996 for overviews). In addition,work on the interpersonal and relationshipaspects of computer-mediated communication over

time complements this finding. Walther andBurgoon (1992) showed that members ofcomputer-mediated groups felt less connected to

one another initially, but over time, members ofcomputer-mediated groups expressed more posi-tive feelings about one another that approximated

those expressed by members of face-to-facegroups. The transient effects of technology werealso illustrated in a longitudinal study comparing

the developments of norms in groups using GDSSwith groups not using GDSS. Contractor et al.

(1996) found that while members of non-GDSSgroups were initially more likely than members ofGDSS groups to socially influence one anothersperceptions of the groups norms, this difference

dissipated over time. That is, in the long term,

groups using GDSS were no more likely thangroups no t us ing GDSS to soc ia l ly in f luence oneanothers perceptions of the groups norms.

THE RE C O N C E P T U A L I Z A T I O N O F G R O U P S

ANDNEWMEDIA ASKNOWLEDGENETWORKS

While it should be evident that the study of groupsand new media is a vibrant area for research, we

now return to the opening statements of this chapterabout the theore t ica l and ana ly t ic cha l lenges tha t

confront scholars who consider the ways in whichthe new new media of the twenty-first centurywill influence our ability to organize in groups. Inconclusion, we offer a reconceptualization of

groups use of new media from a knowledgenetworks perspective.

From Knowledge Management

to Knowledge Networks

Knowledge management is a critical concern forcontemporary organizations, and i t is expected to

become increasingly important in the future(Nonaka and Takeuchi, 1995). It has long been rec-ognized that computers could increase the range,

depth and speed with which information could beacquired, processed, presented for use and sharedfor collaborative efforts. However, research in this

area has given little attention to theoretical or con-ceptual issues about information acquisi t ion, pro-cessing and integration, and even less attention to

theoretical issues about the antecedents and conse-quences of different patterns of information distr i-bution within work groups, and the conditions

under which information can be and is easily sharedamong group members. Recent developments in

technologies have shown their potential as knowl-edge management systems, although little is knownabout the social challenges and motivations forgroup members to use these systems effectively.

These challenges call for a knowledge networkapproach (Monge and Contractor, 2001) andknowledge-based theor ies to unders tand groups

use of new media

Groups as Knowledge Networks

The proliferat ion of digital technologies has dra-matical ly changed the nature of work in groups.These technologies, as described previously, have

the potential to provide many benefits to groups bylinking people who have common goals and inter-ests but are separated in time and space. They may

enable organizations to develop effective teamsfrom workers who are geographically distr ibuted.


13/16

232 NEW MEDIA AND ORGANIZING

Today, in stark contrast to just a decade ago, virtualteams consider having employees located in t imezones far removed from one another (such asCalifornia, Ireland and India) as a competitive

advantage rather than a disadvantage. Members of distributed work teams can work round the clock inorder to meet the competi t ive demands of a global

marketplace. In some cases the members of theseteams are e-lancers (electronic freelancers) whocoalesce on a short-term project and then disperse.

In other cases, the technologies have the potential toenable the organization to hire and retain the bestpeople, regardless of location (Townsend et al . ,

1996). These changes have led scholars to call for areconceptualizat ion of groups as much more f luid,

dynamic, mult iplex and activi ty based (Goodmanand Wilson, 2000).

Clear ly these new technolog ies have the po ten-t ial to nurture a team by l inking the members not

on ly to one ano ther bu t a l so to a l a rge number o f internal and external knowledge repositories.Conceptually, therefore, it is increasingly useful to

consider the group and its members as a network ofagents, where some of the agents are human agentswhile others are non-human agents (such as knowl-

edge repositories. avatars and webbots) . Humanagents communicate with one another by retrievingand allocating information relevant to their collec-tive tasks. An increasingly vexing question that

group members face in this networked environ-

ment is not which medium to use (as was addressedby earlier theories of media choice), but rather

which agent to use.Groups and the media they use can be usefully

reconceptualized as a lo~o~ ~genetwork. A net-work is made up of a set of nodes and relat ionsbe tween these nodes . The nodes tha t con ta in the

knowledge can be people. databases, computerf i les or other forms of repositories. The relat ionsare the communication relat ions ( that is , publish-

ing, retr ieving, al locating) among the nodes. Thelocation of knowledge within this network ofagents can vary along a continuum from central-ized. where knowledge resides with only one agent,

to distributed, where knowledge exists among

many agents (Farace et al.. 1977). Distributedknowledge may refer to the parts of a larger knowl-edge base, each possessed by separate actors withinthe network. In this form of distributed knowledge,actors bring relatively unique. non-redundant

knowledge which enables a collective to accom-plish complex tasks. Distributed knowledge occursat many levels in the empirical world, including

work groups, large-scale project teams, andin te rorgan iza t iona l s t ra teg ic a l l i ances . Al te rna t i -vely, distr ibuted knowledge may refer to the f lowor diffusion of knowledge, which increases the

level of knowledge among all actors.Communication networks, actual knowledge ner-

works, and cognitive knowledge networks are

different ways of conceptualizing the network ofagents. Communication networks represent thedegree to which individual agents interact with

o ther agen ts in the ne twork . Ac tua l knowledgenetworks represent the actual distribution ofknowledge among the network of agents. Cognitive

knowledge networks represent individuals percep-tions of the distribution of knowledge in the net-work of agents. Knowledge networks are dynamic,

in terms of both agents and linkages. Agents join orleave a knowledge network on the basis of tasks tobe accomplished, and their levels of interests ,

resources and commitments. The links within theknowledge network are also likely to change on the

basis of evolving tasks, the distribution of knowl-

edge within the network, or changes in the agentscognitive knowledge networks. New media, such as

intranets, serve both as the infrastructure that supports the development of relations in the networkand as the nodes in the network. In our own

research, we have applied a knowledge networkperspective to theories that investigate new lnediause in g roups and organ iza t ions (Hol l ingshead

etal., 2001; Monge and Contractor, 2001).We believe there is tremendous potential for the

development and extension of theories which seek

to explain the development of a groups use of media as a knowledge network of human and non-human agents. The knowledge network perspective

is especially well suited to test multiple theories

and their contradictory or complementary influ-ences on the evolution of the groups. Knowledge

networks and their defining characteristics can berepresented and analysed exceptionally well usingtechniques developed within the field of social net-

work analysis (Wasserman and Faust, 1994). Thesetechniques enable researchers to examine thedynamics of relations at multiple sites and across

different levels of analysis ( individual , dyads.group, organizations and industries). It is difficultto predict the types of configurations that groups

with technology will take in the future. Regardlessof their forms, a knowledge network perspectivewill allow future researchers to examine, describe

and evaluate new media and organizing at the

group level.

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