perceived individual collaboration know-how development through information technology–enabled...

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Perceived Individual Collaboration Know-HowDevelopment Through Information Technology–EnabledContextualization: Evidence from Distributed TeamsAnn Majchrzak, Arvind Malhotra, Richard John,

To cite this article:Ann Majchrzak, Arvind Malhotra, Richard John, (2005) Perceived Individual Collaboration Know-How Development ThroughInformation Technology–Enabled Contextualization: Evidence from Distributed Teams. Information Systems Research16(1):9-27. http://dx.doi.org/10.1287/isre.1050.0044

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Perceived Individual Collaboration Know-HowDevelopment Through Information

Technology–Enabled Contextualization:Evidence from Distributed Teams

Ann MajchrzakInformation and Operations Management, Marshall School of Business, University of Southern California,

Los Angeles, California 90089, [email protected]

Arvind MalhotraInnovation and Entrepreneurship, Kenan-Flagler Business School, University of North Carolina at Chapel Hill,

Chapel Hill, North Carolina 27514, [email protected]

Richard JohnDepartment of Psychology, College of Letters, Arts and Sciences, University of Southern California,

Los Angeles, California 90089, [email protected]

In today’s global market environment, enterprises are increasingly turning to use of distributed teams toleverage their resources and address diverse markets. Individual members of structurally diverse distributedteams need to develop their collaboration know-how to work effectively with others on their team. The lackof face-to-face cues creates challenges in developing the collaboration know-how—challenges that can be over-come by communicating not just content, but also context. We derive a theoretical model from Te’eni’s (2001)cognitive-affective model of communication to elaborate how information technology (IT) can support an indi-vidual’s communication of context to develop collaboration know-how. Two hundred and sixty-three individualsworking in structurally diverse distributed teams using a variety of virtual workspace technologies to supporttheir communication needs were surveyed to test the model. Results indicate that when individuals perceivetheir task as nonroutine, there is a positive relationship between an individual’s perceived degree of IT supportfor communicating context information and his collaboration know-how development. However, when indi-viduals perceive their task as routine, partial IT support for contextualization is associated with lower levels ofcollaboration know-how development. This finding is attributed to individuals’ misunderstanding of the con-veyed context, or their struggling to utilize the context conveyed with partial IT support, making a routine taskmore prone to misunderstanding and leaving the user worse than if she had no IT support for contextualization.We end the paper by drawing theoretical and practical implications based on these findings.

Key words : knowledge management; collaboration; virtual teams; distributed teams; knowledge sharing; groupsupport systems

History : Robert Zmud, Senior Editor; Carol Saunders, Associate Editor. This paper was received on September18, 2003, and was with the authors 12 months for 2 revisions.

IntroductionFaced with an increasingly global work environ-ment, managers are concerned about developingemployees’ know-how to collaborate in distributedteams (Brown and Duguid 1998, Hinds and Bai-ley 2003, Saunders 2000, Straus and Olivera 2003).Distributed teams (DTs) are defined as groups ofpeople who interact through interdependent tasks

guided by a common purpose, and who work acrossspace, time, and organizational boundaries primarilythrough electronic means (Maznevski and Chudoba2000). Employees are increasingly asked to work notonly in DTs, but also in structurally diverse DTs thatcross geographic locations, functional assignments,reporting managers, and business units (Cummings2004) to afford a broader representation of perspec-

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Majchrzak, Malhotra, and John: Perceived Individual Collaboration Know-How Development10 Information Systems Research 16(1), pp. 9–27, © 2005 INFORMS

tives to spark innovation and speed implementa-tion of new ideas across space and time (Majchrzaket al. 2004). Individuals working in DTs are oftenchallenged by nonroutine tasks. Under these condi-tions, individual members of DTs need to developcollaboration know-how to work effectively in theDT (Cramton 2001). Even when the tasks being per-formed by individuals in DTs are routine, membersof DTs need to have the know-how to integrate theirwork and collaborate with other members of the team.In this paper, we describe how IT can be used tosupport the development of collaboration know-howamong individuals in structurally diverse DTs.

Theoretical DevelopmentThe Need for Collaboration Know-HowFor individuals to work effectively in structurallydiverse DTs, collaboration know-how is required.Know-how has been defined as knowledge of cur-rent practices required to transform inputs into out-puts as effectively as possible (Brown and Duguid1998, Finholt et al. 2002). Blackler (1995), relying onRyles’s (1949) concept of “knowledge how,” describesknow-how as action oriented, partly tacit, acquired bydoing, and, as such, hard to circulate and needing tobe developed individually (Brown and Duguid 1998).An individual’s collaboration know-how refers

specifically to knowledge about how to communi-cate one’s own ideas and integrate it with others’ideas, including how to coordinate one’s actions andwork with others on the team. This notion of collab-oration know-how builds on Grant’s (1996) conceptof knowledge integration. A variety of virtual teamresearchers have chronicled the problems individu-als face in knowledge integration, such as differentcommunication practices and interpretations of mean-ing (Cramton 2001, Hinds and Bailey 2003, Maznevskiand Chudoba 2000, Majchrzak et al. 2000).Malhotra et al.’s (2001) description of the lead engi-

neer in a structurally diverse new product develop-ment DT offers an example of the need for individualsworking in DTs to develop collaboration know-how.The lead engineer was responsible for integrating ana-lytic results into new design iterations and leadingdesign discussions around each iteration. His exist-ing collaboration know-how involved asking each

engineering specialist on the team to send him hisanalytic results, which he would then privately inte-grate to produce a new version of the design thatwould be the focus of the team’s next design discus-sion. However, the members of the DT complainedthat this practice violated the team norm that allinformation (including analytic results, evaluations ofdesign ideas, and suggestions for new ideas) shouldbe posted in the virtual workspace for everyone tosee. Yet, from the lead engineer’s perspective, hav-ing team specialists post their results to the virtualworkspace yielded chaotic and unproductive designdiscussions because members focused only on thelatest analytic results, failing to consider the impactof the analytic results from all the specialists, espe-cially the results that were shared earlier. After severalweeks of frustrating design discussions, the engi-neer finally proposed a new practice for collabora-tion: a hyperlinked cross-team matrix in which eachspecialist would link his results (in a predeterminedformat) to each posted design drawing so that theteam members could easily find, examine, and discussall the specialists’ results during design discussions.This suggestion was adopted and helped to make thedesign discussions more productive. At the end ofthe project—eight months after coming up with thematrix idea—the lead engineer attributed the team’screation of a radically new product design to thedevelopment of his collaboration know-how for man-aging the team.

Need for Contextualization to DevelopCollaboration Know-HowIndividuals in DTs face great difficulties in develop-ing their collaboration know-how due to a lack offace-to-face sharing of nonverbal cues to help pri-oritize messages and content, repair communicationmisunderstandings, and learn communication norms(Clark and Brennan 1991, Finholt et al. 2002, Hindsand Bailey 2003). Because structurally diverse teamsare rarely brought together in face-to-face meetings(Majchrzak et al. 2004), members must rely on ITto support their collaboration know-how develop-ment (Malhotra et al. 2001, Malhotra and Majchrzak2004). Finally, structural diversity poses additionalchallenges because the diversity of perspectives cre-ates greater opportunities for misunderstanding (Fin-holt et al. 2002, Maznevski and Chudoba 2000).

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Majchrzak, Malhotra, and John: Perceived Individual Collaboration Know-How DevelopmentInformation Systems Research 16(1), pp. 9–27, © 2005 INFORMS 11

To overcome these difficulties of communicatingacross boundaries, some have suggested that indi-viduals should communicate not just the content ofa message, but also its context (Brown and Duguid1998). Based on Habermas’ theory of communicativeaction, Te’eni (2001) elaborates a cognitive-affectivemodel of communication, which highlights the shar-ing of contextual information in the development ofknow-how. His model proposes three facets of orga-nizational communication:(1) Inputs to the communication process (i.e., the

organizational setting of the individuals involved inthe communication);(2) Communication impact (i.e., mutually agreed

purposeful action, encompassing our narrower con-cept of collaboration know-how development); and(3) A cognitive-affective communication process

(i.e., the choice of communication strategy and IT sup-port for that strategy).Examining the communication process, Te’eni pro-

poses contextualization as one communication strat-egy. Contextualization is defined as the presentationof context information about a message structuredfor easy absorption, with context defined as infor-mation about the situation, intentions, and feelingsabout an issue or action, as owned, evolved, andrepresented by each individual involved in the com-munication process. Weick and Meader (1993) sim-ilarly describe context for a decision as the explicitpresentation of multiple perspectives and preferencesregarding cause-effect links, definitions and scope ofdecisions, and understandings about whether there isa need for a decision at all. The communication ofcontext can lead to more effective thinking (Tyre andvon Hippel 1997) because it helps to prioritize infor-mation and interpret cues (Cramton 2001), share andframe issues and decisions (Mark 2002), and engage insense making about alternative views on cause-effectlinks and preferences for effects (Weick and Meader1993). In doing so, communication of context helps toensure that the content influences know-how devel-opment (Sussman and Siegel 2003).The virtual team literature identifies the sharing of

context as a major need of individuals in distributedteams (Cramton 2001, Hinds and Bailey 2003, Jar-venpaa and Leidner 1999, Weisband 2002). However,in this literature, the definitions of context are var-

ied and include: organizational or geographic affilia-tion (Hinds and Bailey 2003, Maznevski and Chudoba2000, Sproull and Kiesler 1986), situational aware-ness such as information about each person’s milieuor environment (Cramton 2001, Weisband 2002), andindividual differences (Walther 1995). In contrast,Te’eni’s (2001) model, as well as Weick and Meader’s(1993) sense-making framework, stresses the cogni-tive context associated with communication—identi-fication of alternative perspectives on, details about,and the nature of changes over time in the communi-cated content. Because our focus is a cognitive modelof communication, we adopt the concept of cognitivecontext.In addition to these primarily cognitive elements,

Te’eni (2001) argues that another critical element thatinfluences organizational communication is the rela-tionship or affective element. Relationship, for Te’eni,includes trust and commitment. When trust and com-mitment are high, communications are more effective.In this paper, we specifically focus on the cognitiveelements proposed in Te’eni’s model, with trust andteam size in our model as controls for the affective ele-ment. Although Te’eni only focuses on trust and com-mitment, team size has been strongly associated withparticipation and the nature of interaction in teams(Gladstein 1984, Yeatts and Hyten 1998). As team sizeincreases, the relationships among teammembers tendto suffer (Lichtenstein et al. 1997). Team size can alsoinfluence the teammembers’ motivation to collaborate(Huberman and Loch 1996). Similar issues related toteam size have been observed in DTs (Riopelle et al.2003). Therefore, we include team size as an addi-tional control for affective influences in DTs.

IT Support for ContextualizationWhen individuals are geographically distributed,communication is mediated through a variety of ITsystems. Boland et al. (1994) develop a theory of howIT can be designed and used to facilitate a contex-tualization strategy. Their theory elaborates on fiveaspects of a contextualization strategy1 that IT can

1 Boland et al. (1994) suggest a sixth property, mixed form. We didnot operationalize this property because our preliminary interviewswith the DT leaders indicated that the technologies in use across allteams in our sample were equally capable of including all mediaformats such as text, pictures, graphs, and so on.

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support: (1) ownership (the IT system allows users toeasily identify who authored a message), (2) easy travel(the IT system enables individuals to move effort-lessly among messages to examine historical, analytic,motivational, and situational layers), (3) multiple per-spectives (the IT system enables comparisons of per-spectives conveyed in a message against alternativeperspectives on the issue), (4) indeterminancy (the ITsystem allows for partial and tentative messages), and(5) emergence (the IT system allows for the emergenceof new categories, constructs, and levels of abstrac-tion for describing and organizing messages). IT func-tionalities that support each of the five aspects of anindividual’s contextualization strategy were proposedto help organize and present context information in away that facilitates sense making.Preliminary support for the Boland et al. (1994)

theory was found in qualitative research on a struc-turally diverse DT (Majchrzak et al. 2000, Malhotraet al. 2001). Individuals in the team reported theimportance of indeterminancy (allowing for incom-plete entries), ownership (highlighting authorship ofentries in repositories), and easy travel (hot-linking ofindividual workspaces with team workspace) as theyused their IT system to discuss their work with oth-ers. However, this qualitative research did not relatethe type of IT support the individuals used for theircollaboration know-how development. Moreover, thetheory has not been tested in large samples of individ-uals engaged in DTs who use a variety of alternativeIT systems to coordinate their work. In this study, ourintent is to submit this theory to such a test.Simply providing functionalities in a technology

does not suggest that the technology is either appro-priate for the situation (Goodhue and Thompson1995), used as intended (DeSanctis and Poole 1994,Majchrzak et al. 2000), or deemed useful for contextu-alization by individuals of a DT (Malhotra et al. 2001,Mark 2002). The actual use and perceptions of useful-ness are driven by the team’s norms in use for the IT(Majchrzak et al. 2000, Mark 2002). Examples of normsinclude e-mails preceded by key words to indicateurgency, entries dropped into folders that represent ateam-defined taxonomy of terms, and clearly identi-fied annotations so that anyone not attending a vir-tual meeting would know who said what. However,it is hard to disentangle the impact of functionalities,

the use of those functionalities, and the team normsthat influence use (Majchrzak et al. 2000). Therefore,we do not try to disentangle these facets related totechnology use, but rather adopt the notion of fit pro-posed by Goodhue and Thompson (1995), Goodhue(1998), and Goodhue et al. (2000) that integrates thesevarious facets. Accordingly, our notion of fit focuseson an individual’s assessment of the degree to whichthe IT supports the five aspects of a contextualiza-tion strategy. Individuals in DTs are likely to perceivethe IT system as providing varying levels of supportfor contextualization, with support ranging from none(none of the five aspects enabled) to high (most or allenabled).

Influence of Task Type on the RelationshipBetween IT Support and CollaborationKnow-How DevelopmentThus far we have argued, following Boland et al.(1994), Te’eni (2001), and Weick and Meader (1993),that individuals in a DT will experience greater col-laboration know-how development when they usea contextualization strategy supported by IT. How-ever, Te’eni (2001) proposes that contextualizationas a communication strategy is needed, particularlyin situations that individuals perceive as nonroutinebecause of the higher potential for misunderstandingarising from confusion over conflicting and multipleinterpretations of causation. Individuals in DTs mayperceive tasks as nonroutine for several reasons: Theyhave a new role to perform, they are new to work-ing in DTs, or the task the group faces is entirelynew. Weick and Meader (1993) also argue that tasksthat have the potential for misunderstanding havea greater need for contextualization. Thus, the morea contextualization strategy is supported by IT, thegreater collaboration know-how is developed, partic-ularly for individuals engaged in tasks perceived asnonroutine.For individuals performing tasks they perceive as

routine, the issue may be different. In routine tasks,the problem is already defined, causal linkages areevident, the nature of the decision needing to bemade is known, disagreements over preferences areless prominent (Weick and Meader 1993), and thesolution requires knowledge aggregation rather thansynthesis and integration (Hatano and Inagaki 1991).

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In such situations, partial IT support may generateconfusion that hurts collaboration know-how devel-opment. Partial IT support refers to the case whenindividuals perceive that some of the five aspectsof the contextualization strategy are not supported,such as when information is conveyed with histor-ical referents but without the ownership needed toassess source credibility. Incomplete representationsof context due to partial IT support may lead to adecreased ability of individuals to make sense of a sit-uation that is thought to be known or well understood(Mark 2002, Weick and Meader 1993). As such, theindividual receiving this incomplete representation ofcontext must now not only perform the task, butmust also simultaneously expend cognitive resourcesto resolve and reconcile the implications of the miss-ing context—a process that an individual perform-ing a nonroutine task would be doing anyway. Forthe individual performing a routine task, this needto resolve and reconcile missing context may cre-ate confusion that causes the individual to reconsiderthe problem statement, preferences, and causal link-ages to solutions. For example, an individual in aDT responsible for routine help desk support maybe assigned the task of putting together a frequentlyasked questions (FAQ) list for global customers fromsuggestions posted in the virtual workspace by teammembers, a task she may perceive as routine, requir-ing collaboration know-how that involves simplyaggregating and organizing posted suggestions fromother members. However, if suggestions have somenotes assigned but no rationale, ownership, or his-torical context, or some suggestions have some con-text information and others have none, the individualis unable to determine which suggestions are dupli-cates, how to organize and link the suggestions, andhow to present the suggestions for easy customer use.As such, the collaboration know-how she was expect-ing to use through the virtual workspace would beinsufficient for aggregating the posted suggestions inthe virtual workspace, leading her to either returnto e-mail or phone, or to redefine the problem. Ineither case, perceptions of collaboration know-howdevelopment through the virtual workspace would beharmed.For nonroutine tasks, the opportunity for mis-

understanding already exists, thus the incremental

improvement in understanding by knowing even par-tial context may outweigh any confusion caused bypartial context support. In other words, partial andfragmented communication about context may be bet-ter than none when individuals perceive the task asnonroutine. For example, in the Malhotra et al. (2001)case study research on team members performingwork they considered nonroutine (new product devel-opment in a distributed setting), members reportedthat even when only six out of the eight distributedmembers used annotations, the partial annotationswere better than no annotations. Thus, when individ-uals are engaged in nonroutine tasks, even partial ITsupport for contextualization may facilitate their col-laboration know-how development.In sum, we argue that the opportunities for mis-

understanding when performing nonroutine tasks areso great that collaboration know-how developmentwill benefit from any IT support for contextualiza-tion even if the support is partial. When individu-als perform routine tasks, however, partial IT supportwill lead to reduced collaboration know-how devel-opment because individuals not only must performthe task, but must also expend cognitive resources atthe same time to resolve and reconcile the implica-tions of the missing context.In Figure 1, we summarize our arguments into

a hypothesized model. Because our focus is on thecognitive elements of contextualization, we haveincluded two controls for the affective relationship

Figure 1 Research Model

Perceivedcollaboration

know-howdevelopment

PerceivedIT support for

contextualization

Perceivedtask

nonroutineness

Trust inteam members

Teamsize

Control variables

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among team members: team size and trust. In sum,we hypothesize the following.

Hypothesis. For individuals that are performing non-routine tasks, there is a linear positive relationship bet-ween their perceived collaboration know-how developmentand their perceptions of the degree of support providedby IT for their contextualization needs. There is a curvi-linear relationship between the development of collabora-tion know-how and the perceived degree of contextualiza-tion support provided by the IT system for individualsengaged in routine tasks in distributed teams.

Research MethodsThe study involved a cross-sectional survey of 263individuals working in 54 structurally diverse DTs.We identified the 54 DTs through solicitation by DTconsultants, professional organizations, collaborationtool providers, and personal contacts. The solicitationpromised a benchmarking report in exchange for par-ticipation. After the initial contact, e-mail exchangesor interviews were conducted to confirm that theteam was structurally diverse and virtual. Of the90 contacts, 54 teams met the criteria.The 54 teams were generally international: 75%

included members from more than one national cul-ture, with 60% including members three or more timezones apart or with different native languages. Halfof the teams included members from more than onecompany; 60% of the teams included members frommore than one organization and function; some teamscame from multinational companies, and other teamscame from small firms. In the sample, 33 companies in15 different industries were represented (e.g., telecom-munications, consumer products, engineering design,medical device manufacturing). The DTs in our sam-ple were performing a variety of tasks (e.g., consult-ing, corporate mergers, new product development).Once a team was identified, a one-hour semistruc-

tured interview with the team leader was conductedto ask about the team’s objective and background, thepractices used in the team to manage its distributednature, and the capabilities of the IT tools being uti-lized by the team to collaborate. The team leader wasalso asked to nominate the manager to whom theteam reported who could complete an evaluation ofthe team outputs and process to date (using a scale by

Ancona and Caldwell 1992). We used this team eval-uation to confirm that the team was judged by othersin the company to be successful. We wanted to studyonly high-performing teams, because this allowed usto control for poor performance as a possible fac-tor influencing collaboration know-how development.Finally, the team leader was asked to encourage teammembers to complete a 35-minute online survey. Forsmaller teams (6–10 members), all members of theteam filled out the survey. For larger teams (more than10 members), we received responses from 50% of theteam members, on average. Team members receiveda summary report that compared their team (aggre-gated across team members) to the aggregate statisticsof all teams in our sample.Surveyed members reported spending only 2.5% of

their time on the team in face-to-face meetings withall other members, and only 15% of their time inface-to-face meetings with any other member. Thus,the individuals could not use face-to-face meetings tosupport their contextualization needs. Members wereasked if they had worked with none, few, half, most,or all of the other members of the team prior to thisteam. On average, members reported working withonly a few of the other team members. In addition,they reported being highly dependent on each otherto perform their task (measured using the scale byKirkman and Shapiro 2000). Thus, the strategic diver-sity of the team coupled with interdependence andlow familiarity among team members suggested con-textualization needed to be conveyed during discus-sions.The 54 teams used a wide variety of IT applica-

tions to support their virtual collaboration, includingLotus Notes, Groove, Livelink, Microsoft products,NetMeeting, Webex, and E-Room. A variety of func-tionalities integrated into the virtual team room tech-nologies was used, ranging from application-sharingsoftware to calendaring, from intelligent search toolsto expert directories, from instant messaging to dis-cussion threads. All teams used telephone conferenceson a regular basis in addition to their repositories.Thus, the DTs in our sample used a range of IT appli-cations to support contextualization.

MeasuresTable 1 shows the items that comprise the constructs.Standardized instruments for most of the constructs

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Table 1 Measurement of Constructs

PrenormalizedConstruct and items MEAN (SD)

Dependent variableCollaboration know-how development 3�6 �0�7�“Working in this distributed team is helping me learn: � � �”

1. How to streamline the team’s internal processes 3�7 �0�8�2. How to reduce redundancy of information and knowledge in the team 3�5 �0�9�3. How to coordinate the efforts of everyone on the team 3�7 �0�9�4. How to rapidly implement new team ideas 3�6 �0�9�

Independent variableDegree of IT support for contextualization

(OWN, TRAVEL, etc. refer to the Boland et al. (1994) contextualization needs; these labels were not 4�1 �3�5�shown to the respondents.)

“The virtual workspace or repository used by the team enabled me to: � � �”(strongly disagree to strongly agree response scale—1 to 5; scale was created as a count of the

following items in which 4 or 5 were marked)1. Easily know who contributed a piece of knowledge to the team repository (OWN) 3�2 �1�7�2. Easily find specific entries in repositories that have been contributed by specific individuals (OWN) 2�9 �1�6�3. Easily link my team’s repository with other knowledge sources and applications (TRAVEL) 2�7 �1�6�4. Easily identify historical connections between entries (TRAVEL) 2�4 �1�5�5. Easily allow different people to find summaries as well as details in the repository (TRAVEL) 2�4 �1�5�6. Easily interweave notes, chat, e-mail, and documents in the repository (INDETERM) 2�6 �1�5�7. Easily know rationale behind the decisions made by team members so that decisions and rationale 2�5 �1�5�

can be revisited later (INDETERM)8. Easily label an entry with multiple key words it pertains to (MULTIPLE) 2�5 �1�5�9. Easily view annotations and comments on knowledge in team’s repository made by other team 2�7 �1�6�

members (MULTIPLE)10. Be informed when knowledge in repository changes (EMERGENT) 2�7 �1�6�11. Easily change identifiers on knowledge in repository as team’s ideas evolve over time (EMERGENT) 2�5 �1�5�

ModeratorTask nonroutineness 3�6 �0�7�To what extent do you agree with these statements?(Scale: 1= strongly disagree to 5= strongly agree)1. The team is dealing with a nonroutine problem 3�7 �1�0�2. The team is using a nonroutine process to address the problem 3�4 �0�8�3. The team is addressing questions that have never been asked in quite that form before 3�6 �0�9�

ControlsTrust 4�2 �0�6�To what extent do you agree with these statements?(Scale: 1= strongly disagree to 5= strongly agree)1. Most people on this team are basically honest and can be trusted 4�4 �0�6�2. Team members in my distributed team are always interested only in their own welfare (reverse) 3�9 �0�8�3. Members in this team are always trustworthy 4�2 �0�7�4. In this team, one has to be alert or someone is likely to take advantage of you (reverse) 4�1 �0�8�5. Team members in my distributed team are willing to help if you need it 4�2 �0�6�

Group size (completed by team leader)“What is the number of core members on your team?” 13�4 �8�9�

do not exist and thus needed to be created for thisstudy. In light of this, we paid particular attentionto pilot-testing and the verification of discriminantvalidity among the constructs to avoid biases result-ing from common method variance. We return to thisissue later in the Construct Validity section.

Perceived Collaboration Know-How Develop-ment. To develop our measure of individual collabo-ration know-how development, following the proce-dure used by Cummings (2004), we first conductedinterviews with a sample of 15 managers involvedin managing structurally diverse DTs to identify the

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different types of collaboration know-how that needto be developed if individuals are to effectively per-form in these teams. We supplemented these inter-views with a review of earlier qualitative research(Majchrzak et al. 2000, Malhotra et al. 2001). Further-more, we examined available instruments for mea-suring knowledge sharing effectiveness (e.g., Goldet al. 2001). Together, these sources suggested that,in structurally diverse DTs, four areas of collabora-tion know-how are particularly useful to an individ-ual performing in such teams: (1) how to stream-line the team’s internal processes, (2) how to reduceinformation redundancy within the team to optimizediversity of opinions, (3) how to coordinate individ-ual members’ efforts, and (4) how to rapidly imple-ment new team ideas. We preceded these items withthe stem, “Working in this distributed team is helpingme learn � � � �” and used a five-point agree to disagreeresponse scale. We pilot-tested the scale on eight indi-viduals who were members of different structurallydiverse DTs. A reliability (alpha) coefficient of 0.83was obtained on the full sample for the four items,indicating strong interitem covariance.

Degree of Perceived IT Support for Contextualiza-tion. To develop the scale for the degree of IT sup-port for contextualization, we used the Boland et al.(1994) five aspects of a contextualization strategy thatcan be supported by IT: ownership, easy travel, multi-plicity, indeterminacy, and emergence. We conductedexploratory interviews with 12 individuals not in oursample who used a variety of virtual workspaces, toidentify ways in which they used the workspaces tomeet each contextualization need. This led to a listof 15 items (3 items for each aspect). Piloting of the15 items on 8 individuals engaged in different dis-tributed groups not in our sample led to the drop-ping of 4 items (1 for each of 4 aspects) that did notapply equally across different types of groups andworkspaces. Preceding the 11 remaining items was thequestion: “Does your team use a virtual workspace orcentralized repository to communicate and coordinatetheir work?” If the respondents reported no use ofsuch a workspace, they skipped all 11 questions. Weincluded this question to ensure that individuals’ per-ceptions of support for contextualization needs were

directed at the virtual workspace and not at othertechnologies or tools (e.g., e-mail, audioconferencing)they might have available to them.As indicated in the theory section, we wanted

our items to simultaneously capture the use (ratherthan mere presence) of technology functionalities andimplicit group norms that influence use. For this rea-son, using the notion of fit proposed by Goodhueand Thompson (1995), we prefaced each of the itemswith the stem, “The virtual workspace technology (ordata repository) used by the team has enabled meto� � � �” We felt that the word “enabled” encouragedrespondents to consider how the technology func-tionalities and enabling norms surrounding the useof the technology helped them perform their work.Response scale choices were 1 (strongly disagree) to5 (strongly agree). Across the sample of 263 individu-als, we obtained a reliability (alpha) coefficient of 0.89for the 11 items.We had argued that confusion associated with

partial support might lead to less collaborationknow-how for individuals performing routine tasks.Therefore, average support across items could not beused because higher averages might result from afew needs being highly supported even though otherneeds were not supported at all. To avoid this, wecreated an index based on a count of the numberof contextualization needs that individuals marked 4(“agreed”) or 5 (“strongly agreed”). This index repre-sents a conservative assessment of support because itcounts even modestly supportive technology as non-supportive. Nevertheless, the correlation between thismore conservative count and an average of the itemmeasures’ full response scale was 0.88 �p < 0�001�.This indicates that, although our index may have beenmore conservative, it also captured a general assess-ment of support.

Perceived Task Nonroutineness. Perrow’s (1967)task routine-nonroutine continuum is an aggregationof two underlying task characteristics—task varietyand task analyzability. We sought a scale that concep-tually integrated both characteristics in as few itemsas possible. The scales reviewed by Withey et al.(1983) measure variety and analyzability separatelyand use a larger number of items. For these reasons,we decided to use the three-item scale developed byGoodhue and Thompson (1995) that was intentionally

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structured to combine both analyzability and variety.We adopted Zigurs and Buckland’s (1998) definitionof task to refer to the group’s problem as it is pre-sented to the individual. Thus, we asked individu-als to assess the degree to which they perceived thegroup’s problem to be nonroutine. We expected signif-icant individual variation even within groups, becausethe structural diversity within the team meant thatsome people may have performed the task previouslywhereas others would find the same task to be novel.The three-item scale demonstrated adequate measure-ment qualities (Cronbach’s alpha of 0.76).

Control Measures. We included two controls inour analysis: trust and team size. Trust was measuredwith five items from the Krishna and Shrader (1999)scale used by the World Bank and academic schol-ars (e.g., Paldam 2000, Paldam and Svendsen 2003).The scale was developed by the World Bank basedon a review of 26 studies conducted in 15 countriesworldwide. We replaced the words “trust in commu-nity” in the scale with “trust in the distributed team.”We used this instrument because it had been vali-dated in the context of globally diverse respondents(multiple countries and cultures)—a context typical ofthe individuals included in our sample. A reliability(alpha) coefficient of 0.81 was obtained for the scale.Team size was obtained from the team leader, andvaried from 6 to 50 members (with a median of 10and mean of 13).

Construct ValidityWe assessed construct validity by confirming the four-factor structure of the 23 items, by assessing discrim-inant validity, and by examining common methodvariance. We conducted a confirmatory factor analy-sis (CFA) using the Bentler-Weeks model (Bentler andWeeks 1979, 1980) and EQS 4.02 (Bentler 1993) withelliptical reweighted least squares (ERLS) estimation.A four-factor model was estimated, restricting each ofthe 23 items to be an indicator for one and only one ofthe four latent factors, including collaboration know-how development (4 items), degree of IT supportfor contextualization (11 items), task nonroutineness(3 items), and trust among group members (5 items).Covariances among the four factors were allowed tobe freely estimated, and all covariances among residu-als were constrained to zero. The factor loadings from

this model were all large (above 0.60), and estimatedfactor intercorrelations were all small, ranging fromto 0.04 to 0.36. (See the appendix for the detailsof CFA model parameters.) Overall, the four-factormodel fit well (Bentler 1990, Bentler and Bonett 1980),as indicated by the Bentler-Bonett normed fit index(NFI= 0�91), the Bentler-Bonett nonnormed fit index(NNFI= 0�96), the comparative fit index (CFI= 0�97),the average absolute covariance residual (0.017), andthe average off-diagonal absolute covariance residual(0.018). This simple four-factor model (with uncorre-lated residuals) yielded a �2 = 342�0. Compared witha complete independence model of the data ��2 =3�958�7�, this simple four-factor model provided a sig-nificant �p < 0�001� reduction in �2.To establish discriminant validity (following Sird-

eshmukh et al. 2002), an analogous confirmatoryfour-factor model was also estimated using EQS andrestricting the correlations among the four latent fac-tors to 1.0, which represents an extreme case of no dis-criminant validity among the four factors. All three fitindices were considerably attenuated compared withthe four-factor model with factors allowed to correlatefreely (both NFI and NNFI= 0�59 and the CFI= 0�63),and the average absolute covariance residuals weregreatly inflated (0.084 and 0.091 off-diagonal). In addi-tion, the reduction in chi-square test comparing themodel with all factor intercorrelations set to 1.0 ��2 =1�605�3� to the model described above with freely esti-mated factor intercorrelations ��2 = 342�0� was alsosignificant �p < 0�01�.Following the Podsakoff et al. (2003) evaluation

of techniques to control common method biases andrecommendations for selecting appropriate remedies,we adopted their recommendations and assessedthe extent of common method variance by estimat-ing a confirmatory five-factor model, including afifth unmeasured latent methods factor. Each of the23 items was allowed to load on one of the four theo-retical factor constructs, and all were allowed to loadon the fifth methods factor, which was constrainedto be uncorrelated with the other four factors. The fitindices for this five-factor model were barely greaterthan the original four-factor model described above(NFI = 0�93, NNFI = 0�97, and CFI = 0�98), and theaverage absolute covariance residuals actually dou-bled in size (0.033 and 0.036 compared with 0.017

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Table 2 Correlations Among Constructs �N = 263�

Collaboration know-how Degree of IT support Task Trust amongdevelopment for contextualization nonroutineness group members

Degree of IT support 0�27∗∗

for contextualizationTask nonroutineness 0�12∗ 0�12∗

Trust among group members 0�30∗∗ 0�02 0�14∗

Group size 0�08 0�01 −0�14∗ −0�07

∗p < 0�05; ∗∗p < 0�01.

and 0.018 for the four-factor model). The reduction inchi-square test comparing the four-factor model ��2 =342�0� with the five-factor model including a commonmethods factor ��2 = 290�7� was not significant, sug-gesting little or no common methods variance.We then examined the correlation coefficients

among the four main constructs and group size, whichare shown in Table 2. Apparent from the table arethe relatively low correlations, further indicating boththat common method variance is unlikely to be anissue, and that the variables are measuring differentconstructs. Following Szulanski (2000), discriminantvalidity was further demonstrated by forming a 95%confidence interval (CI) for each of the intercorrela-tions above (not involving group size) and comparingthe upper bounds of each 95% CI to the maximumpossible correlations between the scales, given mea-surement error. For each construct pair, discriminantvalidity is demonstrated if the 95% CI upper bound isless than the maximum possible correlation betweenthe construct pair. The upper bounds on the 95% CIranged from 0.14 to 0.41. The maximum possible cor-relation between each pair of measures is calculatedas the square root of the product of their correspond-ing reliability coefficients, as reported above. The fouralphas ranged from 0.76 to 0.89, and the six maximumpossible correlations ranged from 0.78 to 0.86. All sixconstruct pairs easily passed this test of discriminantvalidity.

Analysis StrategyOur first step was to determine whether our expec-tations for an individual-level analysis were appro-priate, by evaluating the extent to which individualson the same team agreed. For each variable, we cal-culated an intraclass correlation. Small values of theintraclass correlation (below 0.70) would suggest low

agreement among team members and would con-firm that an individual-level analysis was appropriate(Shrout and Fleiss 1979). Three individuals were ran-domly selected from the 48 teams with three or moreresponses to assess the reliability of any randomlyselected team member. All intraclass correlations werewell below George’s (1990) suggested criterion of 0.70:collaboration know-how development (0.15), degreeof IT support for contextualization (0.47), task non-routineness (0.29), and trust (0.15). These low valuesof the intraclass correlations confirm that a team-levelanalysis was not viable, and that the dependenciesamong individual team members are small enoughfor an individual-level analysis. Moreover, the smallcorrelations suggest that the social forces that act ongroup members to create similar psychological statestoward trust, IT fit, and tasks in a team may be lesspowerful in structurally diverse DTs.Our hypothesis proposed an interaction effect of

collaboration know-how on task nonroutineness andIT support, which we tested using hierarchical moder-ated multiple regression (HMMR). We chose HMMRover structural equation modeling (SEM) and par-tial least squares (PLS) approaches: (a) to include inthe analysis the continuous nature of the modera-tor variable, (b) to avoid Carte and Russell’s (2003)Error 9 in which differences in path coefficients acrosssubsamples are confounded with differences in themeasurement model estimated for latent constructs,and (c) because if we followed the Chin et al. (2003)recommendations for an integrated PLS model andcomputed interaction terms among the 11 items forIT support and the 3 items for task nonroutineness,the number of interaction terms would have beenimpractical for our sample size.The HMMR strategy allowed us to estimate and test

the linear effects of IT support for contextualizationand task nonroutineness on collaboration know-how

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development, controlling for the linear effects of trustand group size. In addition, the HMMR approachallowed us to test for the hypothesized quadraticeffect of IT support for contextualization on collab-oration know-how development moderated by tasknonroutineness. All of these analyses are based oncorrelations using a sample size of N = 263. As indi-cated by Algina and Olejnik (2003), this sample pro-vides power (0.90) adequate to detect correlations assmall as 0.20 (alpha= 0�05, two tailed). With a proba-bility less than 10% of missing a correlation as smallas 0.20, this study utilizes an adequate sample size.For all analyses, predictor variables were standard-ized to have a sample mean of 0 and a sample stan-dard deviation of 1.0. All product variables (quadraticterms and interaction terms) were computed usingstandardized components, as suggested by Aiken andWest (1991).

ResultsIn preparation for testing our hypothesis, we firstexamined the presence of a quadratic effect of thedegree of IT support for contextualization on collabo-ration know-how development for the complete sam-ple, regardless of the presence of a moderator effect oftask nonroutineness. We included in Step 1 the con-trols (team size, and trust in team members) and thelinear main effect of degree of IT support for contex-tualization. In Step 2, we included the quadratic termfor degree of IT support for contextualization. Theresults are shown in Table 3. The quadratic effect wasnot significant, indicating that the dip in collaborationknow-how development due to partial IT support isnot experienced by all individuals in the sample. Theresults also indicate a significant linear effect for ITsupport. This suggests that regardless of task type, ITsupport is an important predictor of know-how devel-opment.We then tested the interaction effect of task non-

routineness and the quadratic effect of degree of ITsupport for contextualization. We included the lin-ear interaction effect as a control. To calculate thequadratic interaction effect, we standardized the sco-res for task nonroutineness and the quadratic effect fordegree of IT support and multiplied them. We thenincluded the variables from the previous analyses as

Table 3 Regression of Collaboration Know-How Development onSquared IT Support for Contextualization

Collaborationknow-how development

Model 1 Model 2

Independent variables � t � t

ControlsTrust in team members 0�30 5�39∗∗∗ 0�31 5�49∗∗∗

Team size 0�10 1�78 0�10 1�80

Linear main effectDegree of IT support 0�26 4�68∗∗∗ 0�22 3�62∗∗∗

for contextualization

Quadratic effect(Degree of IT support — — 0�10 1�74

for contextualization)2

Adjusted R-squared 0�16 0�17Change in R-squared — 0�01F 17�88∗∗∗ 3�03DF 3 & 260 1 & 259

∗p < 0�05; ∗∗p < 0�01; ∗∗∗p < 0�001. The betas reported are standardizedbeta coefficients, N = 263.

Step 1, with the quadratic interaction effect as Step 2.The results are shown in Table 4.Following Aiken and West (1991) to determine if

the precise nature of the interaction effect was ashypothesized, we conducted a split sample regres-sion. We split the sample at the mean of task nonrou-tineness, yielding a sample of 147 respondents withhigh nonroutine tasks and 116 with low nonroutinetasks. There were 30 ties at the mean; three differ-ent ways of distributing the ties yielded the sameresults. Regressions were conducted on each sampleseparately. The results of the split sample are shownin Table 5 below. As with Tables 3 and 4, trust, notteam size, was found to have a significant relationshipwith collaboration know-how development.The results in Table 5 provide support for our

hypothesis. With routine tasks, there is a curvilinearrelationship between individuals’ perceptions of ITsupport for contextualization and collaboration know-how development (i.e., the quadratic effect is signif-icant). When the task is perceived to be nonroutine,however, this relationship is linear (i.e., a significantlinear effect). As suggested by Aiken and West (1991,p. 12), it is important to probe any significant inter-action effects to fully understand their meaning. Oneof the most powerful means of probing is to plot therelationship between the predictor variable and the

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Table 4 Regression of Collaboration Know-How Development on ITSupport for Contextualization Squared Moderated by TaskNonroutineness


Model 1 Model 2


ControlsTrust in team members 0�29 5�09∗∗∗ 0�28 4�99∗∗∗

Team size 0�10 1�84 0�09 1�70

Direct effectsDegree of IT support 0�21 3�45∗∗ 0�23 3�78∗∗∗

for contextualization(Degree of IT support 0�10 1�65 0�10 1�67


Task nonroutineness 0�08 1�97 0�07 1�14

Moderating linear effectDegree of IT support 0�07 1�20 0�09 1�64

for contextualization×Task nonroutineness

Moderating quadratic effect(Degree of IT support — — −0�12 −2�12∗


×Task nonroutineness

Adjusted R-squared 0�17 0�18Change in R-squared — 0�01F 9�77∗∗∗ 4�51∗

DF 6 & 256 1 & 255


Table 5 Regressions of Collaboration Know-How Development on ITSupport for Contextualization Squared


Low task High tasknonroutineness nonroutineness

�N = 116� �N = 147�


ControlTrust in team members 0�41 4�99∗∗∗ 0�22 2�86∗∗∗

Team size 0�14 1�74 0�05 0�67

Direct effectDegree of IT support 0�14 1�7 0�30 3�38∗∗

for contextualization(Degree of IT support 0�22 2�54∗∗ 0�10 0�12


Adjusted R-squared 0�22 0�13F 8�99∗∗∗ 6�33∗∗∗

DF 4 & 111 4 & 142


Figure 2 Graph of Quadratic Interaction Effect of IT Support forContextualization on Collaboration Know-How Development

3.3

3.4

3.5

3.6

3.7

Perceived degree of IT support for contextualization

Low Medium High

High tasknonroutineness

Col

labo

rativ

e kn

ow-h

ow d

evel

opm

ent

3.8

3.9

4.0

Low tasknonroutineness

dependent variable for different levels of the mod-erator variable. In Figure 2, we plotted collaborationknow-how development as a function of IT supportfor contextualization for the two levels of task non-routineness. In addition, as called for by Aiken andWest, to graphically visualize the complex interactionwe partitioned degree of IT support for contextual-ization into thirds. This categorization was done onlyfor the graph, not for the analysis. The plot clearlydemonstrates that when individuals perceive they areperforming routine tasks, the quadratic relationshipfound in the regression shows a dip in collaborationknow-how development for moderate levels of IT sup-port for contextualization. In contrast, when individ-uals perceive they are performing nonroutine tasks,there is no such dip, resulting in the complete absenceof any quadratic (nonlinear) relationship between ITsupport for contextualization and collaboration know-how development.

DiscussionWe predicted that IT support for contextualiza-tion would affect individual collaboration know-howdevelopment in structurally diverse DTs. Based ona survey of 263 individuals engaged in structurallydiverse distributed teams, we found that the degree of

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IT support for contextualization was related to indi-viduals’ collaboration know-how development mod-erated by task nonroutineness. That is, the posi-tive linear relationship was found particularly amongindividuals performing nonroutine work. For individ-uals performing routine work, a curvilinear relation-ship was found, in which partial levels of IT supportwere associated with less collaboration know-howdevelopment.

Limitations of the StudyThis study suffers from four significant limitations.First, although we have statistically demonstratedthat common method variance is not likely to bea major issue for our study, we acknowledge thatin cross-sectional studies using perceptual measuresthere is always the potential for common methodvariance. Future studies should minimize the com-mon method variance by collecting data on moreobjective measures of collaboration know-how devel-opment. Coding of the entries in a team’s reposi-tory to assess an individual’s unique contribution asthe team progresses through its life cycle may pro-vide a proxy for collaboration know-how develop-ment. Alternatively, if coworkers or team leaders aresufficiently knowledgeable about their team mem-bers, they could be asked to rate individual teammembers’ growth in collaboration know-how dur-ing the team’s life cycle. Moreover, IT support canbe measured objectively through log files indicat-ing the extent of use of technology functionalities.Ideally, follow-on research will explore the relation-ship of collaboration know-how development withobjective technology features, as well as their sub-jectively assessed fit. Task nonroutineness was alsoassessed attitudinally because individuals were per-forming different aspects of the group’s task andhad varied past experiences. Exploring the correspon-dence between subjective and objective measures ofthe task that individuals perform and how that affectsthe moderator role of task type is a worthwhile focusof future research.Second, causation has not been demonstrated. Be-

cause earlier case study research of a single team’sprogress through its life cycle demonstrated causalitybetween the use of technology and individuals’ abilityto contribute to the team’s outputs (Majchrzak et al.

2000, Malhotra et al. 2001), our effort in this studywas focused on exploring the relationship betweenIT support for contextualization and collaborationknow-how development across a large sample of indi-viduals. Future studies should attempt to assess cau-sation by following individuals in a set of diverseteams through their life cycles to study how theiruse of IT to support contextualization influences theirdevelopment of individual collaboration know-how.In addition, we did not examine the link between col-laboration know-how development and team perfor-mance. Future research should examine the link thatcollaboration know-how development in individualteam members leads to more effective team processes,which then leads to a better team performance. Such astudy would also provide the opportunity to explore ifIT support for contextualization is able to correct inad-equate team processes, leadership, or composition.Another limitation of this study is that we restricted

our sample to high-performing teams. It may bethat the relationship between IT support for con-textualization and collaboration know-how develop-ment found for high-performing teams is not thesame in teams that have lower levels of performance.Future research studies should explore the relation-ship between IT support for contextualization andcollaboration know-how development over a widerange of teams—including low-performing and high-performing teams in the sample.A fourth limitation is that our measures were

developed specifically for this study. Further researchneeds to be conducted with these measures to deter-mine their validity and reliability. The fact that theintraclass correlations were so low despite theseindividuals being members of an identifiable andhigh-performing team with a team leader and teamdeliverables is an interesting finding in and of itself.At the very least, this finding suggests that, for DTs—especially structurally diverse DTs—the individualsin a team may not provide sufficient influence on eachother to affect some psychological attitudes (such astrust). For such attitudes, treating the individuals asa group may overstate the relational impact of otherteam members. This raises the interesting question:In structurally diverse DTs, do team members sharethe same types of psychological attitudes as typicallyfound in collocated teams?

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Finally, our study is limited to the specific criteriaof our sample: structurally diverse distributed teams.Such a limitation is an advantage for empirical test-ing because of the criticality of collaboration know-how development and the reliance on IT support forknowledge sharing in such teams. However, furtherresearch is needed to determine if the relationshipbetween IT support for contextualization and collab-oration know-how development found here extendsto hybrid teams or to teams that are less diverse. Thisrelationship may not be observed in hybrid teamsbecause members are not as dependent on technologyto share context. In less structurally diverse teams,however, members may already share sufficient con-text to interpret others’ knowledge content withouthaving to use IT support to share context explicitly.This would suggest that IT support for contextual-ization may be of particular benefit only to a subsetof the entire population of DTs: those that are struc-turally diverse, primarily virtual, and composed ofmembers performing what they perceive to be non-routine tasks.

Theoretical ImplicationsOur study follows recommendations by Markus et al.(2002) to develop theories of principles for design-ing IT systems. We suggest that the five aspects ofa contextualization strategy supported by IT consti-tute five design principles. The advantage of thesedesign principles is that they are generalizable acrossIT applications. Moreover, they may be applica-ble, beyond communication-oriented technologies, toinclude knowledge management systems that supportindividual ongoing sense-making processes (Fanieland Majchrzak 2003).Having shown an empirical link between IT sup-

port for contextualization and collaboration know-how development, alternative theories for why con-textualization helps should be explored. We relied ontheory offered by Te’eni (2001) and Weick and Meader(1993) to argue that contextualization helps to developcollaboration know-how. Communicated context pro-vides people with the memory and metaphors fordescribing cause-effect links, exploring preferences forsome effects over others, and constructing moderatelyconsensual definitions of whether there is a need for adecision and what the decision is about. However, an

alternative perspective on contextualization focuseson communication of social rather than cognitive con-text (Sproull and Kiesler 1986). This perspective pro-vides an equally viable explanation for the value ofcontextualization. For example, Cramton (2001) andWalther (1995) suggest that a lack of social contextcues in communication creates a lack of individuat-ing information about other team members, whichleads to stereotypical misattributions. Comparing thesocial versus cognitive context explanations may lead,in some situations, to different hypotheses. For exam-ple, when team members are familiar with each otherand have a strong group identity, the individuatingexplanation would hypothesize that less misattribu-tion occurs even without much IT-supported cogni-tive contextualization. In contrast, the cognitive per-spective would argue that even with social contex-tual cues made apparent during interactions, cogni-tive context information (such as alternative perspec-tives on an issue) is still needed. Therefore, furtherresearch should explore the differential value of eachperspective of contextual information.In an effort to develop generalizable design prin-

ciples for effective communication among individu-als in a DT, we have examined IT support of dis-tributed teams through the lens of contextualization.An alternative to the contextualization lens is that thevalue of IT support for DTs is in the coordinationbenefits it provides by increasing visibility into oth-ers’ work (Olson et al. 2002), enabling cocreation andmanipulation of boundary objects (Star 1989, Carlile2002), allowing easy movement between subactivities(Olson et al. 2002), and evenly distributing informa-tion among team members (Cramton 2001). The rela-tionship between support for contextualization andcollaboration know-how development suggests thatIT support for contextualization provides value aboveand beyond enabling coordination. This hypothesisdeserves testing in future research.Our study represents an initial attempt at empir-

ically demonstrating the value of ideas developedby Boland et al. (1994) and Hedberg and Jonsson(1978) that IT systems and work practices that supportthe exchange of contextual information are relatedto knowledge development. These researchers incor-porated contextualization support within a broader

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concept of support for an active inquiry and sense-making process. Although our intention in this studywas simply demonstrating a variance-based relation-ship between IT support for contextualization, taskroutineness, and collaboration know-how develop-ment, the model by Te’eni (2001) for organizationalcommunication and work by Weick and Meader(1993) suggest that future research should explorethe relationship in more detail with a process-basedmodel. In Figure 3, we show a process-based modelthat summarizes a proposed process by which acontextualization strategy is selected, enabled by ITsupport, results in sense making moderated by tasknonroutineness, and leads to collaboration know-howdevelopment. Having demonstrated the relationshipamong the three shaded constructs, we encouragefuture research to explore this complete process.Our study also has implications for task-technology

theories as they apply to individuals in distributedgroups. Information richness theory (Daft and Lengel1986), TIP theory (McGrath 1991, McGrath andBerdahl 1998), and the theory of task-technology fitin group support system environments (Zigurs andBuckland 1998) collectively present a set of contin-gencies that drive individuals’ media choices basedon the ambiguity or equivocality of the message theyare sending and the objective richness capacities ofthe media. Using these theories, the virtual team lit-erature has argued that, for conveying very simple

Figure 3 Proposed Model of Virtual Team Communications

Individualsdistributed

acrossboundaries

Managinginterdependent

actionContextualization

IT support forcontextualization

Collaborationknow-how

development

Communication process

Communicationinputs

Communication impact

Communicationgoal Communication

strategySense making

= Constructs explored in this study

Tasknonroutineness

Source. Adapted from Te’eni (2001) and Weick and Meader (1993).

messages, a lean medium (such as e-mail) is most effi-cient because it eliminates communication of extra-neous information (e.g., Hinds and Bailey 2003).For tasks that individuals perceive to be nonroutine(because they have a new role with an old task,or they are new to the group that has performedthis task earlier, or it is an entirely new task), theyare encouraged to communicate their richer infor-mation with multichannel and interactive electronicmedia. When these tasks are nonroutine, the richestof media (i.e., face to face) has been recommended.However, our study findings differ from the tenets ofthe task-technology paradigm presented above in tworespects. First, our sample consisted of structurallydiverse teams whose members did not have the bene-fit of the richest media of face-to-face contact and yeteffectively performed nonroutine work (e.g., strategicplanning, new product development). Moreover, col-laboration know-how development still occurred forthese individuals. This suggests that, in contrast toboth the task-technology theories and virtual team lit-erature that argue for the importance of face-to-facecontact (e.g., Bhappu et al. 2001, Cramton 2001, Hindsand Bailey 2003, Mannix et al. 2002, Maznevski andChudoba 2000), face-to-face contact is not required fornonroutine tasks when IT provides contextualizationsupport. Second, the dip in collaboration know-howdevelopment found with routine tasks when IT sup-port for contextualization was partial suggests that

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it may not be the richness of the media that con-tributes to collaboration know-how development, butrather the level of support for contextualization thatthe media provides.These findings lead us to join calls in the literature

that question the value of media richness models ingeneral (Markus 1994, Carlson and Zmud 1999) andspecifically for explaining how individuals performeffectively in distributed groups (Saunders 2000). Forindividuals in structurally diverse DTs, we suggestreplacing the concept of media richness with a con-cept of contextualization richness, made possiblethrough the alignment of technology support andwork practices. We argue that future research shouldfocus on rich contextualization support for individu-als in DTs. Such research could answer the importantquestion of whether electronically mediated commu-nication can supersede face-to-face communicationwhen IT provides ways for individuals to more effi-ciently learn, organize, retrieve, and compare alterna-tive and emergent perspectives on a problem. Finally,a focus on contextualization support may help to elab-orate why an IT system may have unintended nega-tive effects. We observed a negative effect of partialcontextualization support for individuals performinga routine task, which was ameliorated when higherlevels of support were provided. Thus, a contextu-alization support lens may be helpful, for example,by suggesting that reasonably comprehensive cogni-tive contextualization support may be more importantthan the choice of any one medium.

Practical ImplicationsManagers are struggling to identify ways to effec-tively manage and leverage the opportunity providedwhen a group of diverse individuals—each of whomrepresents different constituencies that cross organi-zational, geographical, and functional boundaries—are brought together to solve a problem (Bhappuet al. 2001, Majchrzak et al. 2004). With this struc-tural diversity comes the potential for conflict andprocess losses (Hinds and Bailey 2003, Mannix et al.2002), but also the potential for increased knowl-edge creation and performance (Bhappu et al. 2001,Cummings 2004).Our results suggest a way of managing the struc-

tural diversity among these individuals. This canbe achieved by facilitating the sharing of contextual

information among individuals that leads to gainingthe collaboration know-how needed to manage theirinterdependent work. Our results also suggest thatby following a set of theoretically derived principleswhen designing IT support and accompanying workpractices, managers of DTs can encourage the sharingof contextual information. These design principles arenot limited to or constrained by specific technologiesor teams, but rather are overarching guidelines. The11 items used to measure IT support for contextual-ization can be used by managers to benchmark anytechnology and the team’s work practices to assessadherence to the spirit of these design principles(DeSanctis and Poole 1994). Managers should assesstheir virtual workspaces not only from a functional-ity perspective (such as hyperlinking, templates, inte-gration of instant messaging, electronic whiteboards,revision history, and synchronous meeting support),but also from the perspective of the contextualizationneeds of the individual members of the DT.Finally, our findings alert managers to the fact that

support is a matter of degree, and that, when indi-viduals perform routine tasks, partial support maybe worse than no support at all. Moreover, the rou-tineness of a task assigned to the team may notcorrespond to the routineness experienced by someindividuals on the team. Managers who plan to pro-vide only partial support for collaboration (e.g., byproviding some technology functionalities but notothers and not establishing norms for the use of thesefunctionalities) and are not aware of how individu-als on the team assess the routineness of the tasksthey are performing, may find that their efforts to pro-vide technology support for their teams fail to achievedesired benefits. It may be better for such managersto not provide any support. However, an even bet-ter strategy may be for managers to consider provid-ing all 11 IT functionalities associated with IT supportfor contextualization found in this study, and thenassess the degree to which these functionalities fit thecontextualization needs of their virtual employees. Ineither case, our results indicate that attention shouldbe paid to IT support if employees are to learn howto collaborate virtually in the 21st century.

AcknowledgmentsThe authors would like to thank the SIM APC, especiallyBob Zmud, for sponsoring and encouraging them to do this

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work; Manju Ahuja, Sabine Hirt, and Claudia KubowiczMalhotra for reading earlier drafts; faculty and Ph.D. stu-dents at the University of Maryland and University ofGeorgia where earlier drafts were presented; Netage andGroove for their help in finding sites; the 53 team leaderswho generously gave their time to the authors; the surveyrespondents who spent time completing the survey; and theeditors and reviewers at ISR who helped the authors enor-mously to clarify the message.

Appendix. Results of CFA

Know-howdevelopment

Tasknonroutineness

Trust

TR1

TR2

TR3

TR4

TR5

NR1

NR2

NR3

IT7

IT8

IT9

IT10

IT11

IT2

IT3

IT4

IT5

IT6

KH1

KH2

KH3

KH4

IT1

E1

E2

E3

E4

E6

E5

E7

E9

E8

E10

E11

E12

E13

E14

E15

E16

E17

E18

E19

E20

E21

E22

E23

0.80

0.69

0.80

0.63

0.68

0.63

0.69

0.65

0.66

0.61

0.67

0.62

0.68

0.57

0.61

0.53

0.62

0.84

0.56

0.68

0.75

0.64

0.76

0.61

0.72

0.60

0.78

0.73

0.77

0.73

0.75

0.74

0.78

0.79

0.73

0.83

0.80

0.76

0.79

0.85

0.66

0.83

0.54

0.66

0.77

0.74

0.18

0.04

0.16

0.21

0.31

0.36

IT support forcontextualization

Notes. ∗KH = know-how; IT = IT support; NR = task nonroutine-ness; TR= Trust; #’s= item #’s in Table 1.

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