The provision of online public goods: Examining social structure in an electronic network of practice

Decision Support Systems 47 (2009) 254–265

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Decision Support Systems

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The provision of online public goods: Examining social structure in an electronicnetwork of practice

Molly McLure Wasko a,⁎, Robin Teigland b,1, Samer Faraj c,2

a MIS, College of Business, Florida State University, Tallahassee, FL 32306, United Statesb Institute of International Business, Stockholm School of Economics, Box 6501, Stockholm, 113 83 Swedenc 1001 Sherbrooke St. W., McGill University, Montreal, Quebec Canada H3A 1G5

⁎ Corresponding author.E-mail addresses: [email protected] (M.M. Wask

(R. Teigland), [email protected] (S. Faraj).URL: http://www.teigland.com (R. Teigland).

1 Tel.: +46 8 755 2172; fax: +46 8 31 99 27.2 Tel.: +1 514 398 1531; fax: +1 514 398 3876.

0167-9236/$ – see front matter © 2009 Elsevier B.V. Adoi:10.1016/j.dss.2009.02.012

a b s t r a c t
a r t i c l e i n f o
Available online 11 March 2009

Keywords:Online communitiesDigital social networksComputer-mediated communicationElectronic networks of practice

Electronic networks of practice are computer-mediated social spaces where individuals working on similarproblems self-organize to help each other and share knowledge, advice, and perspectives about theiroccupational practice or common interests. These interactions occur through message postings to produce anon-line public good of knowledge, where all participants in the network can then access this knowledge,regardless of their active participation in the network. Using theories and concepts of collective action andpublic goods, five hypotheses are developed regarding the structural and social characteristics that supportthe online provision and maintenance of knowledge in an electronic network of practice. Using socialnetwork analysis, we examine the structure of message contributions that produce and sustain the publicgood. We then combine the results from network analysis with survey results to examine the underlyingpattern of exchange, the role of the critical mass, the quality of the ties sustaining participation, theheterogeneity of resources and interests of participants, and changes in membership that impact thestructural characteristics of the network. Our results suggest that the electronic network of practice chosenfor this study is sustained through generalized exchange, is supported by a critical mass of active members,and that members develop strong ties with the community as a whole rather than develop interpersonalrelationships. Knowledge contribution is significantly related to an individual's tenure in the occupation,expertise, availability of local resources and a desire to enhance one's reputation, and those in the criticalmass are primarily responsible for creating and sustaining the public good of knowledge. Finally, we find thatthis structure of generalized exchange is stable over time although there is a high proportion of memberchurn in the network.

© 2009 Elsevier B.V. All rights reserved.

1. Introduction

Recent advances in internet communication technologies have ledto the rapid growth of electronic social networks. Participants in thesenetworks leverage the connectivity of the internet with a variety ofweb-based tools to communicate, collaborate and participate in theco-production of information goods and services. This new mode ofvalue creation has been termed “peer production”, describing howmass collaboration is changing how people organize, share knowl-edge, innovate and create value [53]. Popular forms of these networksinclude open source software communities, interactive blog sites, P2Pnetworks, wikis, tagging sites and discussion forums. One of the most

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famous examples is www.wikipedia.org, where tens of thousands ofindividuals making relatively small contributions have created anencyclopedia of everything, available to everyone. One of the keyenablers of this change is that once digitized, information becomes apublic good. In tangible form, an encyclopedia has significant costsassociated with manufacturing, distributing and updating content.Additionally, if an individual lends the tangible encyclopedia to afriend, they cannot both read it unless they are collocated. In contrastto tangible goods, digitized information goods have the critical publicgood characteristic of nonrivalry — meaning that these goods are notused up or diminished with consumption. This has fundamentallychanged how people think about, contribute to, value and makepurchasing decisions regarding information goods.

Despite the growing interest in mass collaboration and virtualorganizing, surprisingly little theoretical and empirical research hasinvestigated the communication and organizing processes in electro-nic social networks. As management in many organizations hasdiscovered, the creation of a virtual social space for collaboration andknowledge exchange is no guarantee that knowledge sharing will

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255M.M. Wasko et al. / Decision Support Systems 47 (2009) 254–265

actually take place [2,44]. The availability of communication technol-ogy to sustain group interactions does not necessarily translate intoco-production of knowledge and information, and it seems irrationalthat individuals want to voluntarily contribute their time, effort, andknowledge to help strangers [57]. What is missing is an understandingof the social and structural characteristics that underlie interactionsand knowledge creation within active, sustainable electronic socialnetworks.

For this research, we focus on one of the most pervasive forms ofelectronic social networks — the online discussion forum. Theseelectronic social networks, often in the form of listservs or electronicbulletin boards, create electronic links between individuals regardlessof physical location or personal acquaintance, and have the potentialto support computer-mediated communications between thousandsof people [52]. In these networks, individuals are able to engage inknowledge sharing, problem solving and learning through postingand responding to questions on professional advice, storytelling ofpersonal experiences, and debating relevant issues [56]. Individualsbenefit from these networks since they gain access to new informa-tion, expertise, and ideas that are often not available locally. Public andprivate sector organizations are also attempting to leverage electronicsocial networks to promote knowledge sharing between employeesboth within and across organizational boundaries, and to provideonline support for customers [11,19].

We refer to these informal electronic communication networks as“electronic networks of practice”. Electronic networks of practice aresimilar to communities of practice in that they are a social spacewhere individuals working on similar problems self-organize to helpeach other and share perspectives about their occupational practice orcommon interests [6]. Thus, following Brown and Duguid [6] in theiruse of the term “networks of practice”, we add the term “electronic” tohighlight that communication within this type of network of practiceoccurs through asynchronous computer-based communication tech-nologies, such as bulletin boards, listservs and Usenet newsgroups.

The goal of this research is to examine the structural and socialproperties of an active, ongoing electronic network of practice.Building upon work by Fulk and colleagues [17], we extend collectiveaction and public goods theories to examine participation in anelectronic network of practice as a form of collective action. Thecollective action is exhibited through the interactive posting andresponding of messages to the network. This interaction produces andmaintains the public good of a continuous stream of relevant practiceknowledge that is stored and made available to anyone with aninterest in the practice. Additionally, we have chosen to anchor ourinvestigation in the field of social network analysis, an area in whichresearchers have been paying increasing attention in recent years.Social network theories focus on how the interactions betweenindividuals within emergent groups create patterns of relationshipsthat in turn constitute the structure of the network. From a socialnetwork viewpoint, individuals and their actions are interdependentbecause individuals are embedded in networks of relationships(Berkowitz, 1988; Wasserman and Faust, 1994).

The paper develops as follows. First, wedefine the key characteristicsof public goods and compare different electronic social networks acrossthese dimensions. Next, we define electronic networks of practice, andthen describe how theories of collective action are relevant forunderstanding the social and structural characteristics of these electro-nic networks. We then develop and test five hypotheses related to thestructure of social interaction and participation within electronicnetworks of practice: 1) the overall pattern of interactions that producesand sustains the public good of knowledge, 2) the relationship betweenthe critical mass and knowledge creation, 3) the quality of therelationships sustaining participation, 4) the relationship between theheterogeneity of resources and interests of network participants andparticipation, and 5) how changes occur in the network structure overtime. To investigate these hypotheses, we collected two sources of data

from one electronic network of practice: 1) message postings over afour-month period and 2) a paper-based survey administered to allactive network participants. The shared practice of the network was USfederal law, where participating lawyers actively engaged in theexchange of legal advice. The paper concludes with a discussion of ourfindings and areas for future research.

2. Digital public goods

Public goods are resources that are typically generated andmaintained voluntarily by a collective, which contrasts to privategoods that are typically produced for profit and consumed by anindividual. Public goods are characterized along the dimensions ofnonrivalry, non-excludability, the production function and jointness ofsupply, which we further describe below. These dimensions areimportant for understanding the collective pattern of individualactions required to create and sustain the good.

2.1. Nonrivalry

The most basic definition of a public good is a good that isnonrival. Nonrival means that the good is not used up or depleted inits consumption [50]. Paul Samuelson [48] first examined the nonrivalcharacteristic of a public good, and claimed that although perfectlycompetitive markets could bring about the optimal solution forprivate goods, no such market mechanisms existed for public goods,thus public sector intervention would be necessary to avoid theunderproduction of public goods. Classic examples of public goodsare public parks, public television/radio, and lighthouses. Theinformation goods and services created through online masscollaboration are nonrival since the use of these goods and servicesby one individual does not consume the good or service, nor diminishthe ability of other individuals to access and use them as well. Thisdefining characteristic is commonly shared by all digitized informa-tion goods, regardless of the form of collective action required tocreate and maintain the good.

2.2. Nonexcludablility

A second characteristic that is often associated with public goods isnonexcludability [22]. Nonexcludability is the inability to excludenoncontributors from consumption of the public good. Thus,nonexcludable public goods are resources from which all individualsin a collective may benefit, regardless of whether they havecontributed to providing the good. Public goods are generallyconsidered to evidence both characteristics since public goods arenot used up in their consumption due to nonrivalry, there is noincentive to add costs by controlling access to the good throughexclusion [38]. However, a connection between the two characteristicsof nonrivaly and nonexlcludability does not necessarily exist: anonrival good can be excludable while a nonexcludable good can beeither rival or non-rival [50]. Depending upon the electronic socialnetwork, there are different ways to limit participation and access tothe information good. For instance, an electronic social network mayrequire that members pay a fee and use a password to gain access. Insome networks, only certain members are allowed to post or developcontent. Electronic social networks may designate a moderator toreview and potentially remove individual contributions to the good.Typically, however, when one participant contributes to the electronicsocial network, then all members may benefit from this knowledgeeven if they have not contributed as well.

2.3. The production function

Another critical aspect of public goods relates to the costsassociated with providing the good, which is referred to as the

3 A second type of social dilemma is the social trap or the tragedy of the commonsand involves the consumption or replenishment of a joint good. The commonsdilemma differs from the provision of public goods dilemma because the joint good isnot a public good. Rather the common good is subtractable, the opposite of non-rival.In other words, the use of the common good by one individual diminishes theavailability of the good to another individual, resulting in the “tragedy of thecommons” [28]. Kollock, P. and Smith, M.A. Managing the virtual commons:Cooperation and conflict in computer communities. in Herring, S. ed. Computer-Mediated Communication: Linguistic, Social and Cross Cultural Perspectives, JohnBenjamins, Amsterdam, 1996, 109–128.

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production function [34]. The production function is the relationshipbetween inputs to outputs, specifying the relationship between thequantity of resources contributed to the collective and the amount ofthe public good that is realized. For purely nonrival public goods, theproduction costs are fixed, i.e., the cost of providing the good is thesame regardless of the number of people benefiting from the good[23], and the same quantity is available for each member of thecollective [7]. Thus, the public good costs just as much to produce foruse by one individual as for use by thousands of individuals. What ismore relevant to electronic social network dynamics is that when thecosts of production are fixed, the public good may be supplied byequal participation of all individuals in the collective, or throughefforts by only a small subset of individuals. Using an electronicnetwork of practice as an example, the costs to an individual posting amessage to the network are the same, regardless of the number ofindividuals that benefit from that message. In addition, the messagesposted to an electronic network of practice may occur through equalparticipation of all participants, or sustained through the efforts ofonly a few.

2.4. Jointness of supply

Jointness of supply was introduced to the study of public goodsoriginally by James Buchanan [8]. In joint supply, the unit ofproduction embodies two or more final product components,which are jointly produced or supplied. The classis example ofjoint supply is the steer that jointly produces or supplies bothmeat and hides. In order for joint supply to occur, the costsassociated with supplying multiple goods/services must be lessthan the costs associated with supplying these same goods/services separately [8]. An example of a jointly supplied service is atheater performance, where the performance occurs in the theateritself, but then jointly supplies a television or digital broadcast thatviewers can watch at home. While producing these servicesseparately is possible, joint supply oftentimes is far more efficient.This is a critical component for understanding how electronicsocial networks are sustainable. Some digital goods can be jointlysupplied through other activities. For instance, software developedfor private use may then be made open source. Since the individualhas already incurred the costs of codification for his or her ownneeds, the costs of then jointly supplying this program to othersare very low. In contrast, the public good of knowledge created inan electronic discussion forum is not jointly supplied. Eachmessage is unique, thus to post a response to a request for helprequires a unique solution for each situation. The exception to thiswould be the cross-posting of a discussion thread across manyelectronic forums.

When a public good is purely non-rival and nonexcludable, aparadox exists. If the public good is produced for one, then it isproduced for all, and all members of the collective are free to enjoythe benefits of the collective good, regardless of their owncontribution towards its creation or maintenance. Thus, the rationalindividual behavior would be to enjoy the public good for free,without contributing in return. This is referred to as free-riding, byindividuals who are described as free-riders. Free-riding is espe-cially difficult to prevent when contributions can be sustained by asmall minority of active participants. Additionally, as the costs ofcontributing increase — such as when the activities cannot be jointlysupplied with alternative/private activities, then the incentive tofree-ride also increases. Members of a collective must often makedecisions that balance the benefits of maximizing self-interest withthe collective's interests. Free-riding is a rational behavior for anindividual, but results in collective irrationality. If everyone were tofree-ride on the efforts of others, then the public good would neverbe created. This is a special case of problems referred to as a socialdilemma, and more specifically, the provision of public goods

dilemma.3 In the provision of public goods dilemma, the optimalindividual decision is to free-ride and enjoy the public good withoutcontributing anything to its creation or maintenance. Thus, whywould rational individuals take the time and effort to help strangers,when they could simply free-ride on the efforts of others? From theabove analysis, electronic social networks characterized by jointnessof supply, such as P2P music sharing networks and tagging sites (egdel.icio.us), and to some extent open source software, should havelower costs of production, thus a higher likelihood of succeeding. Incontrast, electronic social networks that require unique contribu-tions and also relatively equal participation by all, such as electronicdiscussion forums, will be the most costly to produce. Wikis andother forms of electronic repositories (such as end user feedbackand review systems), can fall either way. The content may have beenproduced for another purpose and jointly supplied for relatively lowcost (eg slideshare), or require a unique contribution (Amazon bookreviews).

2.5. Collective action and public goods

Despite the pessimistic conclusions of the Logic of CollectiveAction [42] and the N-person Prisoner Dilemmas games, it is widelyrecognized that collective action and the creation of public goodsoccurs, despite rational self-interest and the ability to free-ride. Ofimportance is that in contrast to theories of social dilemmas, theoriesof collective action focus on how social dilemmas are avoided. Inelectronic social networks, the obvious evidence that individualsforego free-riding is the active participation exhibited through theposting of content. Thus, we apply theories of collective action toexamine why individuals forego the tendency to free-ride in thesenetworks, and actively engage in collective action to create a publicgood. We propose that individual participation in electronic socialnetworks is a form of collective action. Collective action is typicallydescribed as being based solely on the voluntary cooperation ofindividuals [34], and involves the production of a public or semi-public good [23]. In the formal language of collective action theory, wesuggest that the participants in an electronic social network form thecollective, while the digital content produced and archived by thevoluntary contributions of participants becomes a public good. For ourinvestigation, we focus on one particular electronic social network,the electronic network of practice. Given that activities in thesenetworks are unique and not jointly supplied, the collective actionunderlying these networks is likely more difficult to sustain.

3. Development of hypotheses

3.1. Defining electronic networks of practice

To begin our discussion, we define an electronic network ofpractice as a self-organizing, open, activity-system focused on practicethat exists through computer-mediated communication. This defini-tion highlights four characteristics that are essential for under-standing how collective action results in an archive of collectiveknowledge that is created and maintained as a public good. First,participation in an electronic network of practice is self-organizing


and voluntary. Individuals choose whether or not they want toparticipate in the electronic network, as well as how often theyparticipate — ranging from simply observing or lurking to becomingan active participant posting messages. Individuals decide forthemselves about how they participate, voluntarily choosing whetheror not to post questions, replies, comments, announcements, or amixture of all. Finally, individuals voluntarily determine theirparticipation, choosing the knowledge they are willing to disclose(which can be either constructive or destructive) and the length of themessage, influencing the quality and helpfulness of the knowledgeexchanged. Thus, knowledge seekers have no control over whovoluntarily responds to their questions, or the helpfulness orrelevance of the responses to the current problem at hand. It isimportant to note that this characteristic of self-organizing, voluntaryparticipation distinguishes an electronic network of practice fromother forms of virtual work, such as virtual teams, where individualsare expected to coordinate efforts to deliver a specific outcome.

The second defining characteristic of an electronic network ofpractice is that participation is open to anyone, anywhere who has adesire to interact in the network, as long as the individuals have accessto the required technology. Typically, participation is available toanyone with an internet connection, regardless of physical location,demographics, organizational affiliation or social position. Participa-tion occurs between people regardless of personal acquaintance,familiarity or proximity, thereby eliminating the need for people tohave an established personal acquaintance in order to share knowl-edge. As a result, participants are typically strangers, boundaries aredifficult to create and enforce in the network, and there are practicallyno limits to network size. Thus, electronic networks of practicefacilitate the creation of weak electronic links between like-mindedindividuals who are physically dispersed yet who are willing and ableto help. This characteristic of open participation between strangerssharply contrasts with the personal acquaintance and often tightlyknit relationships in communities of practice. This characteristic alsofurther distinguishes electronic networks of practice from virtualteams or groups where members are generally assigned, typicallyknow one another and interact over time to create some type ofdeliverable, which results in individuals having expectations aboutappropriate behavior and developing reciprocal obligations that areenforceable through social sanctions.

Third, in an electronic network of practice knowledge exchangeoccurs through mutual engagement in practice. Similar to commu-nities of practice, electronic networks of practice are activity systemswhere individuals interact with one another to help each other solveproblems related to their practice. By posting a request to the network,individuals requiring help with a practice-related problem mayquickly reach out to others who then provide valuable knowledgeand insight in response. This posting of and responding to messages issimilar to a conversation, representing active mutual engagement inproblem solving. This mutual engagement in practice results in dyadiclinks between the individuals posting messages, creating an onlinesocial network. In addition, mutual engagement results in the creationof relationships, between individuals and between an individual andthe network as a whole. Therefore, this characteristic of mutualengagement distinguishes electronic networks of practice from morestatic forms of electronic communication, such as content deliveringwebsites, document repositories, or other types of databases.

Finally, electronic networks of practice are created and sustainedthrough computer-mediated communication and exist primarily inelectronic space. Thus, knowledge is exchanged through asynchro-nous, text-based, computer-mediated communication. This distin-guishes electronic networks of practice from other types of networksbased on face-to-face communication, mixed face-to-face andelectronic communication, or other forms of communication. Inaddition, this has a profound influence on how knowledge is actuallyshared and exchanged. For example, in face-to-face interactions,

individuals may perceive a variety of social and visual cues and haveaccess to immediate feedback. However, in asynchronous, computer-mediated communication, these cues are filtered out and feedback isdelayed, influencing interactions in an electronic network of practicedue to the lean medium of exchange [12]. Since conversations areavailable to all participants in the network, the likelihood of newcombinations and the creation of new knowledge potentiallyincreases. Individuals do not have to anticipate the specific informa-tion needs of other participants, nor do they have to identify thesynergistic possibilities that arise from the potential combinations ofinformation from multiple sources [17]. Finally, and most important,the messages posted to an electronic network of practice are saved,creating an archive of collective knowledge that is made available toall participants in the network. This in effect creates an on-linereference manual or help desk, cataloging questions and answers thatcan be referred to later by any interested individual, regardless of hisor her participation in the original interactions.

The creation of knowledge through the posting of messages resultsin the ongoing creation and repository of collective knowledge, openlyavailable to all individuals regardless of their own contribution.However, similar to other public goods, creating knowledge byincurring the personal costs of contributing to a network of practicerepresents a paradox. For individuals who post answers to otherpeople's questions, as suggested above, prior research suggests thatthe giving away of knowledge eventually causes the possessor to losehis or her unique value relative to what others know [54] and thusbenefits all others except the contributor [55]. For individuals whopost questions, there are no assurances that their efforts of posting aquestionwill be rewarded with a reply. Therefore, in the context of anelectronic network of practice, it seems irrational that individualswould voluntarily contribute their time, effort, and knowledgetowards the collective benefit, when individuals could easily free-ride on the efforts of others. Thus, the nonrival nature of a public goodallows the benefit to be offered to everyone in the collective, and thenonexcludability characteristic allows individuals to free-ride on theefforts of others without contributing to the creation of knowledge inreturn.

3.2. Pattern of exchange in electronic networks of practice

The first key issue for examination is the pattern of contributionsthat create the public good. In electronic networks of practice, thepublic good of knowledge is created bymembers contributing throughthe posting of questions and replies that take the form of aconversation. This interaction creates social ties between participants,thus we define a social tie in an electronic network of practice as thetie created between two individuals when one person responds toanother's posting. While it has been argued that social ties areimportant for the achievement of collective action, it is less wellestablished as to exactly how and why social ties are important [35].Initial research proposes that the overall frequency or density of socialties within a group is related to the achievement of collective action.When networks are dense, consisting of direct ties between allmembers, collective action is relatively easier to achieve. Thisargument goes back to Marx, who reasoned that the more individualsare in regular contact with one another, the more likely they willdevelop a “habit of cooperation” and thus act collectively [35]. Thus,one view is that electronic networks of practice may be characterizedby a dense network structure, where all members have social ties withall other members. An alternative view suggests that the pattern ofcontributions is more like a reciprocal gift exchange. This viewsuggests there is a dyadic exchange between a help provider and ahelp seeker, with the expectation that the gift of help will bereciprocated some time in the future [27]. Thus, the nature ofexchange in an electronic network of practice may be structured asreciprocal dyadic exchanges between individuals, where the


motivation to help others stems from the expectation of obligationand reciprocity from the receiver.

However, an individual contributor must have both the ability andwillingness to post an answer in order to contribute knowledgethrough a response. In addition and as discussed above, the open, fluidmembership in electronic networks of practice makes it difficult tocreate and enforce boundaries, and the individuals participating aretypically strangers, making it difficult to create and enforce socialsanctions for non-reciprocation. Thus, participation in an electronicnetwork of practice by posting messages to the network occursthrough the process of connecting seekers and responders throughknowledge, rather than personal familiarity or physical location.Seekers cannot predict potential knowledge sources, nor cancontributors know beforehand what knowledge is most likely tobenefit certain seekers.

We predict that this leads to a specific type of exchange patternthat is generalized in nature rather than dense or reciprocal. Ageneralized exchange takes place when one's giving is notreciprocated by the recipient, but by a third party ([13]. Generalizedexchange emerges in electronic networks of practice because peopletypically do not know each other and participation is discretionary.For example, in an electronic network of practice, individual A postsa question that is answered by individual B. When individual B inturn posts a question, an unspecified individual C responds. Onereason for the development of generalized exchange is thatindividual A may not have the requisite knowledge to answer B'srequest, while C may be able to easily formulate an effective answer.Thus, exchange patterns that are generalized develop from indirectreciprocation and interest-based contribution. This leads to our firsthypothesis:

Hypothesis 1. The creation of the public good of knowledge inelectronic networks of practice is characterized by a pattern ofgeneralized exchange.

3.3. The presence of a critical mass

Previous research has often found that group size is the bestpredictor of collective action since larger groups have more peopleand potential resources for action [49]. However, theoretically it hasalso been suggested that it is more difficult to sustain collective actionin large groups since contributions are more likely to go unnoticed orseen as unnecessary [21]. The Oliver-Marwell studies [35,40,41]suggest that the effect of group size depends on the costs of providingthe collective good. If the costs of the good rise with the number whoshare it, then they propose that larger groups are less likely to engagein collective action than smaller ones. However, when the costs ofproviding the good are fixed or the same regardless of the number ofpeople benefiting from the good [23], then larger groups are morelikely to attain a sufficient subset of interested individuals. In otherwords, under conditions of pure nonrivalry, free-riders are not aburden to those who contribute, thus it is not necessary to have theparticipation of all members [33]. Thus, public goods may be suppliedby equal participation of all individuals in the collective or throughefforts by only a small subset of individuals. To provide an example,the costs associated with creating a lighthouse are fixed, regardless ofthe number of individuals using the lighthouse. Thus, the lighthousemay be created and sustained equally by all users through the use of afee or tax or may be erected and maintained by a few wealthymerchants.

Borrowing from nuclear physics, this sufficient subset of con-tributors has been labeled “critical mass”, referring to the idea that acertain threshold of participation or action has to be obtained before asocial movement may come to exist [40]. Oliver andMarwell [51: 524]define the critical mass as “a small segment of the population thatchooses to make big contributions to the collective action while the

majority do little or nothing”. Thus, one key aspect of collective actionand the creation of public goods relates to the cost of the creation ofthe public good and the distribution of contributions among themembers of the collective. Similar to the lighthouse example,production costs are fixed in electronic networks of practice, i.e., thecost of posting a message to the network is the same, regardless of thenumber of individuals who may benefit. The knowledge created costsin terms of individual efforts just as much to produce for use by oneindividual as for use by thousands of individuals. Additionally, sincethe knowledge created in an electronic network of practice is not usedup or consumed when accessed and shared, free-riders are not aburden to the network. Thus, the knowledge created by interactions inan electronic network of practicemay occur through the efforts of onlya few members who respond to all postings and thus who form acritical mass. Therefore, theoretically we can expect that collectiveaction in an electronic network of practice is sustained through theefforts of a minority of individuals who constitute a critical mass.

Within the field of social capital, researchers suggest that theconnections between individuals, in other words the structural linkscreated through social interaction between individuals in a network,are important predictors of collective action and knowledge exchange[9,39,45]. These social ties have been referred to as a collective'sstructural social capital [39], and this structural view of social capitalreflects an individual's position in the network and is measured by thetype and number of ties linking a focal individual to others.

Network ties linking individuals have been shown to be importantdeterminants of helping behaviors and knowledge sharing inorganizations [4]. Studies in informal organizational structuresindicate that central individuals have been perceived to be moreinnovative [24], had a higher degree of work reputation andperformance [57], and interpersonal influence [16]. Individualsforming the critical mass of a collective have by definition a highernumber of ties and thus in the formal language of social networktheory have a higher degree of centrality.

In an electronic network of practice, individuals who have a highdegree of centrality and make up the critical mass are those whoactively participate in posting and responding to others, thus creatingmultiple social ties and building the majority of the structural capitalin the network. Research has indicated that the effect of networkcentrality may be even more pronounced in electronic networks ofpractice since formal structures are weak or nonexistent. In one of thefew investigations, Ahuja et al. [1] found that an individual's networkcentrality in an electronic R&D group was positively associated withhelping behavior and performance. Thus, we propose that individualswho form the critical mass in an electronic network of practice arethose who actively participate in posting and responding to others,creating multiple social ties and thus building the majority of thestructural capital in the network. We suggest then that whenelectronic networks of practice have a critical mass of activeindividuals, these individuals sustain the network by activelyparticipating and creating knowledge. This leads to our secondhypothesis:

Hypothesis 2. Knowledge is primarily created by the critical mass inelectronic networks of practice.

3.4. The relational strength of ties

The relational strength of ties in a network refers to the nature andthe quality of relations between the network's members [39, p. 244].The structure of ties provides the foundation for the development ofthe relational strength of the ties since network structures determinethe spread of information about network members and theirinteractions. The relational strength of ties is important to understandsince it influences the development of common understandings andnorms [16], which in turn influence cooperative behaviors and


collective action among the network's members [18,25]. Priorresearch indicates that network structures characterized by dense,reciprocal ties are likely to create strong, relational ties betweenindividuals [25,29]. When individuals in a network know one other,dyadic exchanges result in expectations of future reciprocity anddirect returns between individuals [3].

Collective action may be easier to achieve in networks where theties are characterized by a high degree of goodwill, collective bonds,and expectations of pro-social behavior [10,46]. Additionally, trust isanother characteristic of network ties that is commonly associatedwith collective action [36,39,47]. Other relational attributes ofnetwork ties include obligation to and identification with thecollective [39], affiliation [31], commitment [37], and organizationalcitizenship [43].

However, in electronic networks of practice where the networkstructure is characterized by generalized exchange, ties are basedon the distribution of knowledge rather than personal acquain-tance. This results in ties where seekers and responders aretypically strangers and there are no assurances or expectationsthat help will be directly reciprocated. This is in sharp contrast tothe direct, reciprocal ties that develop through face-to-faceinteractions and personal acquaintances. Therefore, we predictthat the relevant ties providing relational strength within electro-nic networks of practice are not the ties between each individualand other individuals within the network. Rather, the relevant tiesare those that develop between each individual and the collectivenetwork as a whole.

These ties are characterized by the strength of an individual'srelationship to the entire network [31] and are a collective good thatbenefits network members regardless of personal acquaintance [39].For example, prior research suggests that networks characterized bygeneralized exchange are sustained by generalized trust, solidarity,and other higher order concepts such as citizenship, especially amongactive network members [13]. These network-level ties are also likelyto include a strong identification with the network [30,32], and aperceived obligation to the network [5,10]. Thus, we predict thefollowing relationship:

Hypothesis 3. The relational strength of the ties is determined bythe quality of the tie between each individual and the network as awhole.

3.5. The relationship between heterogeneity of resources and interestsand participation

Continuing our discussion of critical mass, one stream of researchin collective action focuses on the attributes of the individuals withinthe collective and argues that the distribution of individual attributeswithin the collective has important implications for whether or notcollective action is successful. More specifically, it is proposed that thepopulation's heterogeneity of interests and resources is argued toaffect collective action [21,41,42]. In other words, the more hetero-geneous a group is, the more likely there is a critical mass or subset ofmembers who have a high enough level of interests and/or resourcesto produce the public good. However, heterogeneity can also hindercollective action even when the mean levels of heterogeneity appearsufficient. As such, the distribution of heterogeneity of interests andresources is important in terms of achieving collective action, i.e., themore positive skew and deviation from the mean, the more likely acritical mass may result [41].

In most collectives, individuals have differing levels of interest orunderlying motivation in seeing the public good realized, and thesediffering levels affect an individual's potential degree of contribution[35]. Individuals with higher interest levels are thosewho tend to gainmore from additional contributions to the public good. Interests mayinclude social and/or professional motives [56], and it has been

argued that individuals with a high interest level are those who lackprivate alternatives [21].

In addition to interests, individuals also possess differing levels ofresources, such as money, time, expertise, energy, and influence [41].For a public good to be produced and maintained, it is argued thatthose forming the critical mass are more likely to have access to therequired resources. In electronic networks of practice, since indivi-duals may participate regardless of their demographic backgrounds,members may differ in terms of their levels of interests and resourcesand thus the likelihood that they may contribute to the creation of thepublic good. Previous research is in line with these arguments withone study indicating that people who had higher levels of professionalexpertise and organizational tenureweremore likely to provide usefuladvice on computer networks [11]. Additionally, since electronicnetworks of practice connect individuals regardless of organizationalaffiliation, participants may come from organizations ranging fromsmall independent operations with few employees to large multi-national conglomerates. As such, we would expect that individualsalso have differing levels of interest in seeing the creation of the publicgood. Thus, the fourth hypothesis examines the role of individualinterests and resources underlying the provision of online publicgoods.

Hypothesis 4. Individuals forming the critical mass in electronicnetworks of practice will have a significantly higher level of resourcesand interests in seeing the good realized.

3.6. The dynamics of exchange over time

The contribution of knowledge to the network will also affect thestructure of ties since the patterns of exchange that generateknowledge in the network also serve to recreate the networkstructure. This sequence of exchanges creates and recreates thenetwork structure, reflecting a dynamic process of network organiz-ing. This dynamic process enables the network to change over time,reflecting the new patterns of relationships that develop. To theextent that the collective action underlying knowledge contributionremains knowledge-based, we expect that the pattern of knowledgecontributions creating the network structure to remain generalized.However, the pattern of interactions that generate knowledgecontribution may also create personal relationships, based onpersonal familiarity, acquaintance, or even strong friendshipsbetween network members. The social network becomes moreattractive and more successful if it is able to gain more membersand these members continue to return, providing a sense ofcommunity [20,58]. Returning members provide a sense of familiarity[15], and there is the conception of some permanence among themembership of the community, with continuing frequency of visits[51] and long term interaction [14]. This has the potential to changethe network structure from a pattern of generalized exchange, to apattern of direct reciprocity among members who begin to developinter-personal ties and a sense of familiarity with one another.Therefore, we predict that if the majority of members are retainedover time, the pattern of exchange will change from generalizedexchange, based on knowledge and interests, to dyadic, based on thedevelopment of interpersonal relationships among members. Thisleads to our last hypothesis:

Hypothesis 5. Asmoremembers return and participate over time, theoverall pattern of generalized exchange will change.

4. Study design and data collection

Conducted in a field setting, this study examines a single inter-organizational electronic network of practice of a US professional legalassociation. All association members have electronic network of

Table 1Summary of exchanges (April–May).

Number of unique participants 533Number of messages posted 2,538Average participation rate 4.76 messages/personNumber of seeds 1,200 by 460 individualsNumber of unanswered seeds 475 by 89 individualsNumber of answered seeds, (threads) 725, average length 1.85 messagesDyadic exchanges 1,338 response messagesGeneralized exchanges 905 messages or 83%Reciprocal exchanges 433 messages or 17% between 182 dyadsDyads directly reciprocating help 6


practice access as part of their membership benefits, yet participationis voluntary. This electronic network of practice is supported by“bulletin board” technology, similar to that of Usenet newsgroupswhere questions and responses are connected in a “thread”,resembling a conversation.

Data were collected using two different means. The first meansconsisted of downloading all messages posted to the bulletin boardduring two different time periods: i) April 1 to May 31, 2001 and ii)June 1 to July 31, 2001. These messages were organized into threadswith the first message being the seed message, and each message'sheader contained the first and last names of the individual posting themessage, thus indicating who had responded to whom. During timeperiod 1, there were 2538 messages posted by 533 distinct individualsand during time period 2, there were 2496 messages posted by 540distinct individuals.

The second means was through a survey. Individuals were chosento take part in the survey based on their participation in the electronicnetwork of practice during time period 1 (posting at least onemessage to the network). Each participant was sent a survey and wereceived 155 valid responses for a response rate of 29%. To assessresponse bias, we compared the participation rates of surveyresponders with those of non-responders and found that theparticipation rates of the two groups were not significantly different(F=.823, ns). We used both the objectively collected messagepostings as well as survey results to examine our research questions.The coding of the messages was performed by one of the authors. Thefollowing section examines our hypotheses as well as the specific dataand methods used to explore each question.

5. Results

5.1. Hypothesis 1 — generalized exchange

To determine the extent of generalized exchange in the network,we analyzed themessages posted to the network during time period 1.Asmentioned above, therewere 2538messages posted by 533 distinctindividuals during the time period 1, or an average of 4.76 messagesposted by each individual. Of these 2538 messages, 1200 were seedmessages and 1338 were response messages. The 1200 seed messageswere posted by 460 individuals, while 73 individuals posted onlyresponses. Of the original 1200 seed messages, 89 individuals posted475 (40% of total seeds) messages that did not receive a response fromanyone. However, the remaining 725 seeds initiated threads with anaverage length of 1.85 messages in response (1,338 messages/725messages).

We further analyzed the direct reciprocal interactions in order todetermine whether individuals helped those who had helped thempreviously by performing content analysis of the messages. Theinteractions were coded as 1) whether the reciprocal messageoccurred in the same thread, 2), the purpose of the reciprocalmessage, e.g., thank you, clarification of an earlier message, thank youwith a clarification of an earlier message, or other, and 3) whether thedyad directly reciprocated help to each other, i.e., individual A posted aquestion that was answered by individual B, and then B posted aquestion that was answered by individual A.

Results indicate that of the 1,338 responses, 905 responses (83%)were of a generalized nature and only 433 responses (17%) were of adirect reciprocal nature between 182 directly reciprocal dyads (forexample John replied to Sue and then Sue replied to John). Due to 23blank posts (potentially mistakes), there were 163 remaining dyads inwhich the reciprocal exchange occurred in the same thread. Of these,82 responses consisted of a “thank you” message, 53 consisted of a“thank you with a clarification” to a prior message, and 23 containedjust a “clarification”. Thus reciprocal exchanges within a thread werefor clarifying questions, seeking more information and thanking theresponder. Only 6 dyads engaged in reciprocal exchanges across

different threads. In other words, the exchange pattern of Sue answersJohn's question and then John answers Sue's question is very rare. Thisindicates that very few people helped each other in a “tit for tat”manner, providing strong support for Hypothesis 1 (Table 1).

5.2. Hypothesis 2 — critical mass

Our next step was to further investigate the structure of the socialnetwork for evidence of a critical mass. We created a square socialmatrix including everyone who posted a message in April and May torepresent dyadic interactions. Themessagematrix data are directionaland valued; the rows (i) are individuals posting responsemessage andthe columns (j) are the individuals receiving them. The values in thematrix, xij, are count totals of the number of messages sent andreceived by participants. From this matrix, we calculated indegreescores for each individual, indicating how many responses anindividual received. We then calculated outdegree scores for eachindividual, indicating howmany responses he or she posted to others.We categorized individuals into four categories based on their patternof participation: 1) outsiders — individuals who posted one or moreseeds but never received a response to these and who posted noresponses to others, 2) seekers— individuals who posted one or moreseeds and who received responses to these seeds, but who neverposted a response to others, 3) professionals — individuals whoresponded to others between one and ten times, and 4) critical mass—individuals who posted to others more than ten times.

The results of this analysis are presented in Table 2.This analysis indicates that people are not participating equally in

the network. The 259 outsiders and seekers (49% of participants) wereonly seeking help without ever helping anyone in return, and theyreceived 348 responses from the network (26% of total messages). Agroup of 251 professionals provided 50% of the 1,338 responses, andthey received 53% of the total number of responses. Thus, profes-sionals provided advice to others, but they also drew from networkresources by asking questions. The remaining 50% of the responseswere posted by 23 an active critical mass. Therefore, half of theresponses on this network came from a critical mass consisting of only4% of the network's participants.

Finally, we compared the number of total messages posted by eachindividual with their degree centrality to find evidence of generalizedexchange. In contrast to indegree and outdegree centrality whichcalculate the number of messages originating from and going to anindividual, degree centrality assesses the number of unique others(alters) to whom an individual (ego) is connected. Degree centralitywas calculated by taking the message postings social network matrixand dichotomizing and symmetrizing the matrix: 1 represents that amessage was exchanged between two individuals and a 0 indicatesthat these individuals did not exchangemessages. Comparing the totalnumber of messages posted by each individual with that individual'sdegree centrality indicates the extent to which this individual isconnected to a variety of unique others. A high positive correlationbetween message posting and degree centrality indicates thatindividuals are engaged with many others. A high negative correlation

Table 2Categorization of individual centrality (T1 responses posted only).

Category Individuals Total messages Average indegree Range indegree Total messages Average outdegree Range outdegree

Outsiders 89 0 0 n/a 0 0 n/aSeekers 170 348 2.04 1–18 0 0 n/aProfessionals 251 704 2.80 1–18 674 2.7 1–10Critical mass 23 286 12.40 4–33 664 28.9 11–114


would indicate that individuals simply post and respond to a selectfew, indicating high levels of participation, but ties to only a fewindividuals. The correlation between the number of messages postedand degree centrality is .98. This indicates that as an individual postsmore messages, he or she becomes linked to more unique individuals.

The above analysis supports Hypothesis 1 since it provides strongevidence of a) unequal participation within the network and b)demonstrates a pattern of generalized exchange sustaining thenetwork. This analysis also indicates that this electronic network ofpractice is structured as a star, with a critical mass of active gurussurrounded by a layer of professional helpers who are thensurrounded by a layer of seekers and then by one of outsiders. Thegurus actively respond to many unique individuals, and the profes-sionals engage in both receiving and providing advice to many others.Fig. 1 shows the network structure.

5.3. Hypothesis 3 — relational ties to the network

To investigate our third hypothesis, we use the survey data. Wefirst examined the extent towhich participants in the exchanges knewone another, representing strong relational ties between individuals inthe network. To measure this, we asked respondents the followingquestion (5 point Likert scale): “The last time you posted a question tothe Message Board, indicate a) how well you know the person whoresponded to you (1, stranger — 5, close colleague), and b) thehelpfulness of the response (1, not helpful— 5, very helpful)”. We alsoasked the following question: “The last few times you posted ananswer to the Message Board, please indicate a) how well you knowthe person who requested help (1, stranger — 5, close colleague), and

Fig. 1. Pattern of exchange represents a

b) the helpfulness of your response, (1, not helpful— 5, very helpful)”.Respondents had space to rate up to four messages.

Results indicate that for the most part, individuals receiving helpdid not know their helpers (μ=1.36, sd=.81), and they rated theresponses they received as helpful (μ=4.19, sd=.96). Similarly,individuals who posted responses were not acquainted with theindividuals whom they were helping (μ=1.23, sd=.71), and theygenerally felt that they were posting helpful advice (μ=3.74,sd=.88). This provides evidence that the participants in the networkhad not developed strong relational ties with other individuals.

We further investigated the strength of the ties betweenindividuals and the network as a whole through multi-item scaleson the survey, indicating the extent of trust of other networkmembers, commitment to the network, and intentions to continueparticipation in the network. We also examined whether anindividual's level of participation in the network correlates withthese relational measures of network ties. See Table 3 for items,reliabilities and factor loadings. See Table 4 for results.

In general, there is some support that participants in the networkhave strong relational ties to the network. Individuals whoparticipate more in the network are more likely to feel committedto the network and intend to continue their participation in thenetwork; however, they are not more likely to have a generalizedfeeling of trust for others in the network. This analysis providessome evidence that strong relational ties may develop in electronicnetworks of practice and that the tie that is significant is the onecreated between an individual and the network as a whole and notthe dyadic ties that develop between individuals, thus providingsupport for Hypothesis 3.

star with ties emanating outwards.

Table 3Relational tie items, reliabilities and factor loadings.

Construct Item wording Reliability Factor loading

Trust I trust the quality of information provided by active members .93 .87Active members are trustworthy in terms of the accuracy of their information .88I can rely on the accuracy of the information provided by active members .89Overall, the people who actively participate are trustworthy .79

Commitment I would feel a loss if the Message Boards were no longer available .85 .79I really care about the fate of the Message Boards .77I feel a great deal of loyalty to the Message Boards .71

Continue participation I intend to continue participating on the Message Boards .89 .77I intend to use the Message Boards for the foreseeable future .72I intend to use the Message Boards at least as regularly as I do now .87

Table 5


5.4. Hypothesis 4 — heterogeneity of interests and resources

Our next hypothesis examines the heterogeneity of resources andinterests of the electronic network of practice participants and therelationship with the network's critical mass. In order to perform thisinvestigation, we analyzed the correlations between the networkcentrality data collected from the posted messages and the resourceand interest data collected from the survey. Our survey assessed twotypes of resources: 1) electronic network of practice expertise asmeasured by the number of months an individual was a member ofthe professional association (objective measure from associationmember database) and 2) professional expertise measured by self-rated expertise. We assessed four types of interests: 1–2) professionalmotivations of reputation, and a desire to learn and challenge oneself,3) social motivation of sustainability of participation, and 4) lack ofprivate alternatives. Alternatives were assessed by examining the typeof law firm (sole practitioner=1, associate=2, partner=3), indicat-ing that a lawyer in a sole partnership would have fewer privatealternatives for professional discussion than a lawyer in a law firmwith more colleagues. The multi-item constructs collected via surveydemonstrated adequate reliability, convergent and discriminantvalidity, and were calculated by taking the average of the items.Actual items, reliabilities and factor loadings are reported in Table 5.Table 6 presents the correlations between constructs.

This analysis suggests that the resources and interests examined inthis study had little correlationwith people receiving help (indegree).The only significant relationships with indegree is a desire to seekchallenges, thus those who receive help are motivated by thechallenge and learning opportunities associated with doing so.Resources and interests had higher associations with responding toothers (outdegree). These results indicate that longer professionalassociation tenure and higher levels of expertise are associated withresponding to others. In addition, individuals who are sole practi-tioners are significantly more likely to respond to others as are thoseconcernedwith enhancing their reputations. Thus, while interests andresources were not as significant for people who receive help, they arereasonably good indicators of why people provide knowledge toothers. This provides support for hypothesis four — individuals in thecritical mass (higher outdegree) will have greater interests in seeingthe good realized and greater resources to contribute.

Table 4Correlations between relational strength of tie and participation.

N=155 Meana Std dev 1 2 3

1. Trust 3.76 0.812. Commitment 3.93 1.00 0.60⁎⁎

3. Continue participation 4.25 0.81 0.54⁎⁎ 0.75⁎⁎

4. Number of messages posted (T1) 4.76 8.90 0.02 0.16⁎ 0.18⁎

a Multi-item scales were averaged to derive a mean score, 1–5 scale.⁎ pb .05.⁎⁎ pb .01.

5.5. Hypothesis 5 — patterns of exchange over time

We analyzed all messages posted during time period (June andJuly) to determine which individuals from time 1 continued theirparticipation in the network. As mentioned above, there were 2495messages posted by 540 unique participants during the second timeperiod. The correlation between participation in time 1 and time 2 is.78, indicating somewhat stable participation. Further analysisindicates that only 311 of the original 533 individuals from time 1participated during time 2, resulting in the loss of 222 individuals(drop-outs) and a gain 229 new individuals (newcomers). The 222drop-outs had posted a total of 474 messages in time 1, of which 322were seeds. Fifty-nine of the original 89 individuals in time 1 whoposted seeds without receiving a reply (outsiders) did not participatein time 2 (66%). Thus, these 59 individuals may have felt that no valuewas generated from their participation in time 1 and did not bother toreturn in time 2.

We examined the survey responses from drop-outs to determinethe motivations and resources of these individuals. We received 62surveys from drop-outs. The only significant differences betweenindividuals who continued their participation into time 2 and drop-outs were that the drop-outs posted fewer seeds and had lower levelsof both out-degree and in-degree centrality in time 1. However, therewere no significant differences between continuing participants anddrop-outs in terms of their motivations and resources. This analysissuggests that although there appears to be a large amount of turnoverin terms of the percentage of individuals who drop out, there is littlechange in terms of the distribution of resources in the network.Individuals who are more structurally embedded in the network interms of in-degree and out-degree centrality are more likely tocontinue their participation. This also suggests that in addition tobeing characterized by generalized exchange, this network is fairlyresilient to high fluctuations in membership.

To determine the extent of generalized exchange in the networkduring time period 2, we created a social network matrix of allmessages posted to the network during this time. To determine thelevel of reciprocity in the network, the social network matrix was

Resources and interests items, reliabilities and factor loadings.

Construct Item wording Reliability Factorloading

Reputation I earn respect from others by participatingon the NOP

0.87 0.87

I feel that participation improves my statusin the profession

0.91

Participating on the NOP improves my reputationin the profession

0.85

Challenge Participating on the NOP gives me the opportunityto learn new things

0.88 0.69

I participate on the NOP to be exposed to complexproblems and issues

0.89

I find participating on the NOP interesting 0.72

Table 6Correlations between resources and interests and type of participation.

1 2 3 4 5 6

1 Months in assoc2 Expertise .44⁎⁎

3 Type of firm .16⁎ .014 Reputation .04 − .01 .055 Challenge − .39⁎⁎ − .23⁎⁎ − .10 .16⁎

6 Indegree − .01 .03 − .09 .12 .15⁎

7 Outdegree .17⁎⁎ .15⁎ − .15⁎ .18⁎ .02 .73⁎⁎

⁎ pb .05.⁎⁎ pb .01.


analyzed to determine which dyads had reciprocal ties. Table 7presents a summary of the findings for time 1 and time 2 forcomparison.

As mentioned above, there were 2496 messages posted by 540individuals during time 2, with an average of 4.62 messages posted byeach individual. There were 1117 seed messages posted by 456individuals. Similar to time 1, this indicates that most participants,84%, continue to ask questions and initiate threads. Of these 1117 seedmessages, 391 or 35% did not receive a response. There were 726threads with an average length of 2.9 messages. This resulted in 1379response messages creating 1169 dyadic links. Of the 1379 responsemessages, there were 491 messages exchanged reciprocally between182 dyads (19% of messages were directly reciprocal). These summaryresults are very similar to the results of time 1.

Once again, to find evidence of generalized exchange we used thesocial network matrix data to examine the network structure throughin-degree and out-degree centrality scores for each individual. Theresults of this analysis are presented in Table 8.

Participation in time 2 follows the same pattern as time 1. Forty-eight percent of the individuals (259) participating in the network areonly seeking help and are not responding to others. These individualsreceived 408 responses (30%). Of the 1379 responses posted, 44% ofthese came from 252 professionals (47%). In time period 2,777responses are posted by 29 very active insiders or only 5% of time 2participants (4% in time 1). One reason for this increase in thepercentage of responses posted by the critical mass may beattributable to gaining another six participants in the critical mass.We find that of the original 23 members of the critical mass in time 1,eight did not continue their very active participation in time 2,indicating that they posted ten or fewer responses. Thus, themembersof the critical mass in time 2 consisted of 15 members from time 1 and14 newcomers. This indicates that there is substantial fluctuationwithin the core of the network, suggesting that this network's core ispermeable and open to those who want to increase their contributionto the network.

6. Discussion and areas for further research

Our results indicate that theories of collective action and publicgoods and the application of social network analysis to electronic

Table 7Summary of exchanges for Time 1 and Time 2.

Time 1

Number of unique participants 533Number of messages posted 2538Average participation rate 4.76 messages/personNumber of seeds 1200 by 460 individualsNumber of unanswered seeds 475 by 89 individualsNumber of answered seeds (threads) 725, average length 1.85Dyadic exchanges 1338 response messagesGeneralized exchanges 905 messagesDirect reciprocal exchanges 433 messages or 17% bet

networks of practice may contribute significantly to our under-standing of these emerging organizational forms. In this particularelectronic network of practice, the public good of knowledge wasproduced through generalized exchange among members. However,this exchange was not evenly conducted by all members, rather it wassustained by a critical mass of individuals who primarily responded toothers, rather than a core of participants participating primarilyamongst themselves. This critical mass was then surrounded by agroup of peripheral individuals who both asked and received advice.Thus, the network is structured as a star with a central critical massand connections radiating outwards. In addition, the heterogeneity ofresources and interests provided good indications of why peoplecontributed to the public good provision. Therefore, we have supportto proceed further with these theories to help us understandelectronic network of practice dynamics.

However, we examined only one specific type of electronicnetwork of practice, an inter-organizational network using bulletinboard technology. Other types of electronic networks of practiceinteractive technologies exist (such as moderated bulletin boards,listservs and chatrooms), and more recently the advent of web 2.0technologies and virtual works, open new opportunities for theinvestigation of how the use of these different media may affectelectronic network of practice dynamics. For instance, the norms ofthe professional association listserv supporting the ISWorld dictatethat responses should be sent privately to the seeker, not postedpublicly. Thus, this type of exchange may be better supportedtheoretically as a dyadic social exchange, rather than the maintenanceof a public good [3]. In addition, this study was conducted only overfour-months and relied on cross-sectional survey data. Thus, we werenot able to investigate issues such as how the pattern of exchangeschanged over time, how the critical mass formed, or how the publicgood was achieved in the first place. Subsequent studies shouldinclude longitudinal data to better understand electronic network ofpractice lifecycles as well as to increase our understanding of thenature of interdependence of individuals' decisions to contribute tothe public good. It has been argued that reciprocal interdependenceand not sequential interdependence characterizes interactive com-munication systems [17]. However, it has yet to be tested empirically.

A final issue of interest to managers and researchers is the problemof free-riders and how they affect electronic network of practicedynamics. Free-riders are those “who do not contribute sufficiently tothe jointly held body of information while continuing to enjoy itsbenefits” [17: 78]. Two explanations have been provided: 1) individualgreed or the desire to obtain the best possible outcome for oneself and2) the “fear of being a sucker” or the fear that no one else willcontribute even though one wants to [26: 189]. In electronic networksof practice, individuals may free-ride through lurking, reading allmessages to gain access to the network's knowledge without everposting themselves. There is also the issue of whether people whocontinually ask questions, receive help from the electronic network ofpractice, but never bother to help anyone else in the electronicnetwork of practice are free-riders. It can be argued that theseindividuals actually do contribute to the public good since they

Time 2

54024964.62 messages/person1117 by 456 individuals391 by 266 individuals

messages 726, average length 2.90 messages1379 responses creating 1169 dyads985 messages

ween 182 dyads 491 messages or19% between 184 dyads

Table 8Categorization of individual centrality in Time 2 (with time 1 values in parentheses).

Category Individuals Total messages Average indegree Range indegree Total messages Average outdegree Range outdegree

Outsiders 83 (89) 0 0 n/a 0 0 n/aSeekers 176 (170) 408 2.35 1–17 0 0 n/aProfessionals 252 (251) 625 2.48 1–25 602 2.39 1–10Critical mass 29 (23) 345 11.90 1–52 777 26.80 11–162


stimulate the thought processes by other participants. However, thisparticipation only works if there is a critical mass who continueresponding to questions, basically providing a “free help-desk” toothers.

In conclusion, this study's goal was to apply the theoretical lens ofcollective action and public goods to examine online cooperationthrough the provision and maintenance of knowledge in electronicnetworks of practice. Our findings suggest some practical implicationsfor the development and maintenance of electronic networks ofpractice. First, it seems possible that electronic networks of practice donot need equal member participation, but rather can be sustainedthrough the collective actions of a small percentage of members whoform a critical mass. At least in the case of our study, this critical masswas able to provide the public good through generalized exchange ofadvice and solutions. One of the key findings from this study was thatindividuals who make up the critical mass in this electronic networkof practice were concerned with enhancing their reputations in thenetwork, thus technology that supports identifiers of individuals maybe more likely succeed than systems where participation is anon-ymous. In addition, we found in our case that those most likely todevelop the critical mass had longer experience in the profession andwere experts in their area, but did not have easy access to colleagues.This suggests that when a local community of practice is not availablefor face-to face interaction, electronic networks of practice maypresent a viable alternative for sustaining knowledge exchange.

We further propose that in order for knowledge to be created inelectronic networks of practice, generalized exchange should lead tothe creation of a critical mass of active participants that contribute themajority of messages and sustain the network for the benefit of others.However, our theory does not discuss the network structurecharacterizing this critical mass. For instance, individuals in acollective may congregate into “cliques” or small groups of activeparticipants who only engage and respond to each other. Thus, thecritical mass in an electronic network of practice might consist of acollection of smaller social networks with little interaction acrosscliques. Another structure that may emerge is that of a central coresustaining the electronic network of practice. A corewould consist of asmall group of individuals corresponding with each other (oneclique), with little regard to peripheral members. This core ofindividuals would simply interact and debate with each other withoutengaging othermembers of the network, creating a closed inner circle.A third potential configuration of the critical mass is a star structure.Star structures indicate that there is a critical mass of interested andresourceful individuals that interact with all others in the network as awhole, rather than with one another. When an electronic network ofpractice is structured as a star, the critical mass contributes to allindividuals with a need to access knowledge, and we suspect that thisstructure is most likely to lead to the creation of knowledge that isbeneficial to the majority of participants. Thus, an interesting area forfuture research would be to examine the actual network structures ofa variety of electronic networks of practice to determine if a certainstructure (i.e. star) leads to higher benefits than others.

It should be noted that these four characteristics describe anelectronic network of practice in their “purest” form. However, inreality there exist electronic social networks that can be described to avarying extent along these dimensions. For instance, an electronicnetwork may not be open to all, but have a restricted membership

where participants are not strangers to one another. Electronicnetworks may also be used to support physical, face-to-face socialnetworks, such as a neighborhood community bulletin board. Inaddition, electronic networks may have different technical character-istics such as synchronous, non-archived, or based on public questionswith private answers. These hybrid forms of electronic networks ofpractices, and the different underlying technologies that supportinteractions, are interesting new avenues for studying collectiveaction and the provision of online public goods.

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Molly Wasko is an Associate Professor in the department of Management InformationSystems at Florida State University where she teaches primarily strategic informationtechnologies, corporate information security and project management. She receivedher doctorate in MIS from the University of Maryland, College Park. Prior to getting herdoctorate, she spent eight years working in production and operations management.Her research interests include the intersection of digital and social networks, socialnetwork analysis, the development of online communities, and open source softwareprojects. She serves on the editorial boards of MISQ and Organization Science, and is amember of the Academy of Management, AIS and INFORMS.

Robin Teigland is an Associate Professor at the Center for Strategy and Competitivenessat the Stockholm School of Economics in Sweden. Her research interests focus on therelationship between knowledge flows in networks and performance at the individual,organizational, and national levels. More information on her can be found at www.knowledgenetworking.org.

Samer Faraj holds the Canada Research Chair in Technology, Management & Healthcareat the Desautels Faculty of Management at McGill University. Previously, he wasassociate professor at the Smith School of Business at the University of Maryland. Hiscurrent research focuses on how IT transforms work and the provision of health care aswell as the participation dynamics of online knowledge communities. He is currentlysenior editor at Organization Science and serves on the editorial board of the Journal ofAIS and Information and Organization.

http://www.knowledgenetworking.org

http://www.knowledgenetworking.org

Documents

The provision of online public goods: Examining social structure in an electronic network of practice