Research Note —Continued Participation in Online Innovation Communities: Does...

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Research Note—Continued Participation in OnlineInnovation Communities: Does Community ResponseMatter Equally for Everyone?Chen Zhang, Jungpil Hahn, Prabuddha De

To cite this article:Chen Zhang, Jungpil Hahn, Prabuddha De (2013) Research Note—Continued Participation in Online Innovation Communities:Does Community Response Matter Equally for Everyone?. Information Systems Research 24(4):1112-1130. http://dx.doi.org/10.1287/isre.2013.0485

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Information Systems ResearchVol. 24, No. 4, December 2013, pp. 1112–1130ISSN 1047-7047 (print) � ISSN 1526-5536 (online) http://dx.doi.org/10.1287/isre.2013.0485

© 2013 INFORMS

Research Note

Continued Participation in Online InnovationCommunities: Does Community Response

Matter Equally for Everyone?Chen Zhang

Fogelman College of Business and Economics, The University of Memphis, Memphis, Tennessee 38152,[email protected]

Jungpil HahnSchool of Computing, National University of Singapore, Singapore 117417, [email protected]

Prabuddha DeKrannert Graduate School of Management, Purdue University, West Lafayette, Indiana 47907, [email protected]

In this study, we focus on the factors that influence online innovation community members’ continued partici-pation in the context of open source software development (OSSD) communities. Prior research on continued

participation in online communities has primarily focused on social interactions among members and benefitsobtained from these interactions. However, members of these communities often play different roles, whichhave been examined extensively, albeit in a separate stream of research. This study attempts to bridge thesetwo streams of research by investigating the joint influence of community response and members’ roles oncontinued participation. We categorize OSSD community members into users and modifiers and empiricallyexamine the differential effects of community response across these roles. By analyzing a longitudinal data setof activities in the discussion forums of more than 300 OSSD projects, we not only confirm the positive influ-ence of community response on members’ continued participation but also find that community response ismore influential in driving the continuance behavior of users than that of modifiers. In addition, this researchhighlights the importance of modifiers, a key subgroup of OSSD participants that has been largely overlookedby prior research.

Key words : online innovation communities; open source software development (OSSD); continuedparticipation; member roles; community response

History : Elena Karahanna, Senior Editor; Amrit Tiwana, Associate Editor. This paper was receivedSeptember 21, 2010, and was with the authors 17 months for 3 revisions. Published online in Articles inAdvance May 28, 2013, and October 22, 2013.

1. IntroductionInnovative users sharing common interests often par-ticipate in online innovation communities. Thesecommunities consist of “individuals or firms inter-connected by information transfer links which mayinvolve face-to-face, electronic, or other communica-tion” (von Hippel 2005, p. 96) and are character-ized by “voluntary participation, the relatively freeflow of information, and far less hierarchical con-trol and coordination than seen in firms” (Shah 2005,p. 343). Examples of online innovation communitiescan be found in such diverse domains as sports equip-ment (e.g., windsurfing gear; Shah 2005) and opensource software (e.g., Apache web server; von Hip-pel 2007). More recently, many forward-thinkingcompanies are supporting/sponsoring online inno-vation communities, drawing consumers and other

stakeholders together to generate ideas for newproducts/services, provide suggestions for enhancingexisting ones, or collaboratively design and developnew ones (e.g., Di Gangi and Wasko 2009, Jeppsenand Fredriken 2006).

Recognizing people as the most important factor inonline communities, several studies have found thatmany community initiatives are unsuccessful becausethey fail either to attract a critical mass of members orto muster the sustained participation of their existingmembers (e.g., Deloitte 2008, Ren et al. 2012, Worthen2008). This is true for both online communities in gen-eral and online innovation communities in particu-lar. Empirical evidence shows that the majority of themembers of these communities only make few contri-butions and leave quickly. For example, in a Pythonopen source software project, more than half of the

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Zhang, Hahn, and De: Continued Participation in Online Innovation CommunitiesInformation Systems Research 24(4), pp. 1112–1130, © 2013 INFORMS 1113

community members did not make any further con-tributions after their first one (Ducheneaut 2005).

It is important to understand which factors drivemembers’ continued participation in online innova-tion communities for several reasons. First, devel-oping innovative products often requires a highlevel of domain knowledge and experience. As theproduct evolves and becomes more complex, onlythose members who have participated actively over along period of time may possess a sufficiently thor-ough understanding of the product and the domain(von Krogh et al. 2003). The communities better atretaining the existing experienced and knowledgeablemembers are more likely to ensure continued high-quality inputs from these members, which facilitatesuccessful, uninterrupted development and enhance-ment of the products/services. Secondly, communitymembers frequently receive assistance and advicefrom other members (Franke and Shah 2003), whichrequires effective transfer of product- and domain-specific knowledge. Retaining members who alreadypossess a significant amount of such knowledge helpsinnovation communities provide assistance to othermembers, especially to newcomers who typicallyexperience steep learning curves (Ducheneaut 2005,von Krogh et al. 2003).

The growing literatures in online communitiesand online innovation communities contribute to ourunderstanding of continued participation in onlineinnovation communities. One stream of research high-lights the importance of social interactions and ben-efits obtained from social interactions as the maindrivers of continued participation (e.g., Fang andNeufeld 2009, Joyce and Kraut 2006). Another streamrecognizes that members participating in the commu-nities exhibit significant heterogeneity with respectto the roles they play within the communities (e.g.,Crowston and Howison 2006, Lakhani and von Hippel2003, Lee and Cole 2003, Morrison et al. 2000, Waskoet al. 2009). However, the joint effects of both socialinteractions and members’ roles have not been exam-ined to date. Filling this gap in the literature is evenmore important in the context of online innovationcommunities, in which social interactions are ofteninseparable from members’ roles in relation to theinnovation artifact. By bridging the two streams ofresearch on social antecedents of continued partici-pation as well as members’ roles, we can develop anuanced understanding as to why some members par-ticipate for a long period of time, whereas others haveonly sporadic participation even when they are undersimilar social influence in the same community. In thispaper, we focus on community response to a mem-ber’s participation, an important aspect of social inter-actions, and the specific role that the member plays in

relation to the innovation artifact. The research ques-tion we seek to answer is whether and how the influ-ence of community response on members’ continuedparticipation differs among members playing variousroles in the community. More specifically, we distin-guish between two roles—users and modifiers—andexamine the impact of community response on theircontinued participation.1

We address this research question in the context ofopen source software development (OSSD) user communi-ties, which refer to the online communities surround-ing OSSD projects that consist of a large communityof users who are not formally a part of the coredevelopment team. Although the core developmentteam has been recognized as a key component ofOSSD and extensively studied by prior OSSD research(e.g., Grewal et al. 2006, Hahn et al. 2008, Lakhaniand Wolf 2005), the participation of the communityof users outside of the core team is also crucial tothe success of OSSD projects (Bagozzi and Dholakia2006, von Krogh and von Hippel 2006). They helpmotivate the members of the core development teamto work on the project via community identification(Hars and Ou 2002), peer recognition (Lerner andTirole 2002), and other community-related intrinsicmotivational factors. In addition, they provide feed-back and code contributions to the core developmentteam; their inputs and criticisms drive the evolution-ary process of learning (Lee and Cole 2003). How-ever, such user communities surrounding the projectdevelopment team have been under-investigated inthe existing OSSD literature.

To empirically investigate our research question, weuse longitudinal data from online discussion forumsof OSSD communities to capture members’ actual par-ticipation over time. Content analyses of the mes-sages posted on these online discussion forums allowus to identify the roles members play (i.e., usersversus modifiers) within the online innovation com-munity, which we use to test whether the impactof community response on continued participationvaries by members’ roles. Our findings highlightthe need to consider not only the social aspectswithin communities but also the inherent differencesacross community members. In addition, identify-ing the antecedents to members’ continued participa-tion in OSSD user communities sheds light on howto improve the sustainability and long-term viabilityof OSSD projects, a practical concern of many opensource entrepreneurs and commercial software com-panies interested in investing in OSSD projects.

1 User role and modifier role will be discussed in detail in §2.2and 2.3.

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Zhang, Hahn, and De: Continued Participation in Online Innovation Communities1114 Information Systems Research 24(4), pp. 1112–1130, © 2013 INFORMS

2. Literature Review andTheoretical Development

2.1. Participation and Continued Participation inOnline Communities

The factors that influence members’ participationintention or behavior in online communities havebeen extensively investigated. These factors include,among others, informational benefits (e.g., Butler et al.2007), relational benefits such as a sense of belong-ing (e.g., Ridings and Gefen 2004), reputational ben-efits (e.g., Wasko and Faraj 2005), enjoyment (e.g.,Wasko and Faraj 2005), social identity (Dholakia et al.2004), and community commitment (e.g., Batemanet al. 2011). The antecedents of initial adoption may,however, be different from those of continued adop-tion because the factors that emerge after the initialuse may influence subsequent decisions related tocontinued use (e.g., Karahanna et al. 1999). Hence,prior research has also examined the antecedents ofcontinued participation in online communities andfound that members’ intentions toward continuedparticipation are influenced by such factors as socialinteraction ties, post-usage satisfaction (Chen 2007),members’ reputation and relational capital (Tiwanaand Bush 2005), community size and interaction withcommunity leaders (Johnson 2008), and the existenceof a response from the community to the initial par-ticipation (Joyce and Kraut 2006).

However, there has been less research focusing oncontinued participation in online innovation commu-nities. In the OSSD context, members may reducethe level of their participation when their motivationschange or the values they obtain from their partici-pation decrease; hence, it is important to understandhow and why people join and leave a particularproject (von Hippel and von Krogh 2003). Priorresearch has found that OSS developers’ initial moti-vations and initial access privileges fail to explaintheir continued participation (Fang and Neufeld2009). Instead, their continued participation emergesfrom successful social interaction with the commu-nity (Fang and Neufeld 2009) and is highly influ-enced by their satisfaction with prior participation(Wu et al. 2007).

Table 1 summarizes these studies of the factorsinfluencing members’ participation in online commu-nities by identifying the focus, theoretical lens, datasource, participation behavior, online community con-text, and findings of each. Overall, they emphasizethat social interactions and the benefits obtained fromsocial interactions drive the continuance behavior ofcommunity members. A key antecedent of continuedparticipation identified in the literature is communityresponse to members’ participation (e.g., Joyce andKraut 2006). However, because individual differences

are often not considered in this stream of research, animplicit general assumption is that social interactionssuch as community response influence all communitymembers in a similar manner. Nevertheless, extensiveresearch has found that not all members in onlinecommunities are the same and that members oftenplay different roles. And in online innovation com-munities, the differences in members’ roles are evenmore common (Morrison et al. 2000). Next, we reviewthe existing research that identifies the various rolesmembers play in online communities and particularlyin OSSD user communities.

2.2. Members’ Roles in Online Communities andOSSD User Communities

Several studies suggest that not all members in anonline community are the same because their atti-tudes (Bagozzi and Dholakia 2006) and expertise(Wasko and Faraj 2005) often differ, leading to dif-ferent motivations and behaviors in the community.Researchers have analyzed the contents and patternsof interactions among community members to iden-tify the different roles that these members play suchas information seeker, information provider (Lakhaniand von Hippel 2003, Wasko et al. 2009), debaters,spammers (Turner et al. 2005), infrastructure main-tainers, member recruiters, social managers, and con-tent generators (Butler et al. 2007).

Likewise, in the OSSD context, recent research hasinvestigated the roles played by members and thestructure of OSSD communities (e.g., Crowston andHowison 2006, Lee and Cole 2003, Nakakoji et al.2002, Xu et al. 2005) because “understanding theseroles is critical in order to grasp the complexitiesand intricacies of innovation in OSS” (von Kroghand von Hippel 2006, p. 979). It is well recognizedthat OSSD communities consist of individuals withdifferent interests and capabilities. These individu-als participate with various levels of intensity andplay different roles in the innovation process (e.g.,von Krogh and Spaeth 2007). OSSD projects and theirsurrounding communities usually have a layered,“onion” shaped structure of organization (von Kroghand Spaeth 2007, Crowston and Howison 2006). Thepeople in the inner layers tend to have more con-trol over and be more involved in the software devel-opment process than those in the outer layers, eventhough the outer layers tend to have more partici-pants than the inner ones do. Table 2 summarizes theroles identified in the OSSD literature.

In terms of the criteria adopted in the literature,some studies (e.g., Crowston and Howison 2006)adopt a larger set of criteria—such as project adminis-trative status, project team membership, type of con-tribution, and extent of contribution—to develop amore fine-grained classification than other studies do.

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Table 2 Members’ Roles in OSSD

Study Member roles Criteria

Hertel et al. (2003) Developers actively engage in the development process by acting as active developers or asmaintainers of a module. Interested Readers are subscribers of the project mailing list whoalso spend some time on the project development.

Active engagement in thedevelopment process

Lee and Cole (2003) The core consists of a project leader and many maintainers, who select which bug fixes andsoftware patches to retain in the next official release. The periphery consists of thedevelopment team and the bug reporting team. The development team produces codevariations by fixing bugs, adding features, and creating software patches. The bug reportingteam generates bug reports.

Involvement in generation andreview of code variations,selection and retention ofcode variations in projectrelease

von Krogh et al. (2003) Nondevelopers/list participants are subscribers to the mailing list and do not contribute any codeto the repository. Joiners are on the mailing list and did not initially have access to the coderepository but later submitted source code to the repository. Newcomers are those who havejust started making changes to the code repository. Developers have moved beyond thenewcomer stage and are making code contributions to the project.

Access and code contributionto the project repository

Xu et al. (2005) Project leaders guide the vision and direction of a project. Core developers are formally listed ineach project. They extensively contribute to projects, manage concurrent versions system(CVS) releases, and coordinate other developers. Co-developers irregularly or regularly fixbugs, add features, provide support, write documents, and offer other information. They arenot formally listed in the project. Active users discover and report bugs, suggest new features,and exchange other information by posting messages to forums or mailing lists.

Extent of guiding the projectdirection, formalassociation with theproject, extent of codecontribution, bug reporting,and feature suggestion

Ye et al. (2005) Project leaders oversee the project and make most of the decisions about it. Core memberscollectively guide and coordinate the development of the project. Active developers regularlydevelop new features, fix bugs, and help improve the code contributed by less recognizeddevelopers. Peripheral developers occasionally contribute code by developing new features orfixing bugs. Bug reporters discover and report bugs but typically do not fix bugs or read code.Readers use the software and read the source code to understand how it works. Passive usersuse the system in a similar way as the users of proprietary software.

Extent of guiding the projectdirection, coordinating theproject, developing newfeatures and bug fixes,reporting bugs, and readingcode

Crowston and Howison(2006)

Project leaders make key decisions about a project. Core developers make strong contributionsto the project and have earned commit privileges on the source code repository.Co-developers contribute code but have not gained commit privileges to the source coderepository. They usually submit code patches for review by core developers. Active users testnew releases; submit bug reports; write documentation; and help answer questions aboutsetup, configuration, and build. Passive users use the code without contributing.

Extent of overseeing theproject, commit privilege tothe project repository,extent of code contribution,document writing, andanswering questions

Shah (2006) Need-driven participants’ code creation is driven by their needs. They contribute code for variousreasons such as reciprocity, norms, product improvements, desire to integrate own code intosoftware, and career concerns. Hobbyists create code for fun and enjoyment. They contributecode to obtain feedback.

Developers’ reasons forcreating and contributingcode

Fang and Neufeld (2009) Core participants have contributed at least one CVS commit (per quarter), representing the mostcritical development activity. Active participants may not have not contributed CVS commitsbut have contributed more than 10 email or tracker messages, which representsabove-average participation. Peripheral participants have not contributed any CVS commits,and have contributed fewer than 10 messages, which represents below-average participation.

Code contribution to projectrepository and messagecontribution to mailing listsor trackers

However, the common criterion used in all of thesestudies is whether or not an individual is engagedin software code development and/or modificationactivities. Whether or not members engage in theseactivities aptly differentiates their motivations for par-ticipating in the community as well as the level ofinnovation-specific knowledge they must possess tocarry out these activities. Accordingly, we parsimo-niously categorize members of OSSD user communi-ties into users and modifiers based on the activities theyperform with regard to the software code.2

2 Our classification of the roles of OSSD user community mem-bers overlaps with the classifications of OSSD participants pro-posed in other studies but is not completely identical for the

By users, we refer to those individuals in the OSSDuser community who plan to adopt or have adoptedthe software, typically with no intention as yet ofmodifying the software themselves. They may postrequests for information related to the general usage,

following reason. We are interested in the continuance behavior ofOSSD user community members, those individuals who participatein the project in various ways (e.g., contribute bug fix, report bugs,request features, etc.) but do not belong to the project team. In con-trast, Shah (2006) focuses on developers who have made code con-tributions to the project, and these developers may or may not bepart of the project team. The communities examined by Crowstonand Howison (2006) consist of not only people who actively con-tribute to the project (e.g., contribute code, report bugs, requestfeatures, etc.) but also those who only use the software without anyactive participation.

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download, setup, and configuration of the software(e.g., Crowston and Howison 2006, Xu et al. 2009), butthey do not contribute directly to the developmentand enhancement of the software product. Users’ con-tribution may, nonetheless, be indirect—e.g., by usingthe software in its currently developed state; test-ing new releases; submitting bug reports; suggest-ing additional features; and helping answer questionsfrom others regarding the setup, configuration, anduse of the software (e.g., Crowston and Howison 2006,Lee and Cole 2003, Xu et al. 2009).

Modifiers refer to those individuals in the OSSD usercommunity who have modified (or plan to modify)the software code. They are not formally affiliatedwith the project development team and do not havecommit privileges to the code repository. They notonly create and modify code to fit their own use con-texts and needs but also sometimes voluntarily con-tribute their modifications to the core developmentteam for review and possible incorporation into theproject’s subsequent software release (e.g., Crowstonand Howison 2006, Ye et al. 2005).

Along with the differences in the activities ofusers and modifiers, there are additional differencesbetween these two roles of OSSD user communitymembers. First, they have different motivations forparticipating in the community (Shah 2006). Users aremostly interested in how to make the most of usingthe current version of the software product to sat-isfy their needs, whereas modifiers are also interestedin extending and customizing the software productusing their expertise and creativity. Secondly, in orderto perform the associated activities (that fulfill thedifferent motivations of members), users and modi-fiers typically possess different amounts of software-specific and domain-specific knowledge. Users tendto have a limited to moderate amount of knowledgeabout how to set up the software and how to usethe various features of the software. Modifiers oftenhave some technical knowledge and programmingskills because software development is a knowledge-intensive activity that requires a significant amountof domain knowledge and experience (Fichman andKemerer 1997). Having examined the software code,they not only are familiar with the software’s featuresand functionalities but also have some understandingof the inner workings of the various components ofthe software.

2.3. Community Response, Members’ Roles, andContinued Participation in OSSD UserCommunities

As summarized above, the various roles of OSSDcommunity members are based on not only theirsocial interactions with other members but also theirinteractions with the innovation artifact—the software

(i.e., using the software, providing feedback aboutthe software, improving the software, etc.). Further-more, the subject of communications among membersis often related to members’ interactions with the soft-ware. Therefore, in this study, we integrate these tworelated, yet disconnected, streams of research investi-gating the social antecedents of continued participa-tion and members’ roles, respectively, to propose thatthe social antecedents to continued participation inonline innovation communities may depend on com-munity members’ roles with respect to the innovationartifact. Specifically, we focus on community responseto members’ participation, a key social antecedent ofcontinuance behavior identified in the existing litera-ture (e.g., Joyce and Kraut 2006), and propose that itsimpact varies depending on the members’ roles.

Community response is critical because communi-cation exchanges among community members allowthe community to function properly; without commu-nication, members cannot interact with one anotherand, consequently, communities cannot exist (Ridingset al. 2002). As aptly put by Applbaum et al. (1974,p. 9), “[C]ommunication is the glue that holds thegroup structure together; it is the enzyme that allowsthe group process to function.” In online commu-nities, members are often strangers who have notmet face-to-face; interactions are mainly throughonline channels in the form of written communica-tion (Ridings et al. 2002) that involves “generatingmessages, responding to messages, organizing discus-sions, and offering other online activities of interest tomembers” (Butler et al. 2007, p. 174).

Such communication exchanges not only promotethe development of a sense of attachment to othermembers and the community as a whole (Sassenberg2002), but also facilitate the establishment of trustamong members (Ridings et al. 2002). More specif-ically, researchers (e.g., Joyce and Kraut 2006) haveidentified community response as a critical factor thathelps maintain members’ trust in the community’sability to provide benefits—community response notonly helps an individual build his belief in othermembers’ ability, skills, and competencies (Ridingset al. 2002) but also increases the individual’s percep-tion of the cooperative intention of the community(Gefen and Ridings 2002).

Furthermore, an individual posting a message ina community often expects some response (Ridingset al. 2002). The response that this individual seekscannot be generated unless other members engage incommunications with him by reading and respondingto his message. It is through these interactions that themember obtains informational, emotional, and otherbenefits from the community. When communicationstake place among members and members receive thedesired benefits from the community, their needs are

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satisfied (Moreland and Levine 2000), strengtheningtheir intentions toward continued participation (Chen2007). In the context of online newsgroups, Joyce andKraut (2006) find that a newcomer who has received aresponse to his initial post is more likely to post again.

Likewise, in the OSSD context where members col-laborate with others in the community to develop andenhance software products, interactions with the com-munity in the form of posting messages and receivingresponses play an important role in driving members’continued participation. When an individual partic-ipates in the community by posting a message, hehopes that others in the community will read his mes-sage and react to it in appropriate ways. For instance,if he posts a request for information or technical sup-port, he expects to receive assistance from the com-munity. If he reports a bug or requests a new featureto be added to the software, he hopes that his par-ticipation will receive attention from the project com-munity and, if possible, some members will take itinto consideration in future versions of the software.If he develops a solution to a known bug or cre-ates a new feature for the software and shares it withthe community, he anticipates feedback from oth-ers acknowledging the usefulness of his contributionor comments toward further improving the software(Shah 2006). Regardless of the purpose of the partic-ipation, online interactions are important for OSSDcommunity members to develop a sense of belong-ing, provide support to one another, facilitate learn-ing, gain recognition for their contributions, etc. Thesebenefits are unlikely to be realized unless other mem-bers engage in communications with a member byreading his message and responding to his participa-tion. When the member does receive responses andthe associated benefits from the community, whichresult in a positive experience interacting with thecommunity, he is satisfied with his participation andhis intention toward continued participation will bereinforced (Wu et al. 2007). Therefore, based on theexisting literature on continuance behavior in onlinecommunities, we expect that members who receiveresponses from the community are more likely to con-tinue their participation.

However, because of the different characteristics ofusers and modifiers in OSSD user communities, weargue that the impact of community response on con-tinued participation will be different for users andmodifiers. Users participate in the OSSD user com-munity primarily to gather information, request assis-tance with the setup and use of the software, reportproblems with it, and provide feedback about it. Theirdecision to use the software is driven by their soft-ware needs for work-related and other purposes aswell as specific task-oriented goals (Fang and Neufeld2009, Shah 2006). In order for users to obtain such use

value from the software, they often seek informationalbenefits as well as support when they encounter prob-lems with setting up and using the software (Bagozziand Dholakia 2006, Franke and Shah 2003). Interac-tions with the community not only help the userobtain software-related information and support butalso help improve his perception of the cooperativeintention of the community. Furthermore, given thediverse needs of users, they often perceive a need foradaptations to the current version of the software tobetter fit their specific use contexts. When they pro-pose such adaptations that may entail bug fixes andimplementation of additional features, they expectothers to acknowledge them and hope that those whohave the requisite technical capability will becomemotivated and make corresponding changes to thesoftware code. Community responses to users’ pro-posals for software adaptations provide confirmationof their participation and may lead them to expectgreater utilitarian value from future versions of thesoftware. In short, community responses help usersobtain informational benefits, user support, and ulti-mately software use value.

In contrast, modifiers have knowledge about notonly the functionalities but also the inner workingsof the software. They seek to customize the softwarecode to satisfy their software need (Roberts et al. 2006,Shah 2006), obtain personal enjoyment from perform-ing an intellectually challenging activity (Lakhani andvon Hippel 2003, von Hippel and von Krogh 2003),and improve their skills (Lakhani and von Hippel2003, von Krogh et al. 2003) and/or status and rep-utation (Lerner and Tirole 2002, Roberts et al. 2006).Although community response helps modifiers obtainfeedback confirming that their contributions are use-ful and important to others (Shah 2006), comparedwith users, modifiers are likely to obtain greater sat-isfaction and benefits from interacting with the soft-ware, writing code, and solving challenging softwarepuzzles.

In summary, users obtain informational benefits,support, and software use value primarily from inter-actions with community members, whereas modifiersobtain benefits such as software use value, enjoyment,and learning benefits from both interactions withcommunity members and interactions with the soft-ware code. Because of the greater importance of com-munity response in benefit provision to users than tomodifiers, the impact of community response on con-tinued participation is likely to be stronger for usersthan for modifiers.

A similar argument can be made by consideringwhether a lack of community response will havethe same effect on a member’s decision not to con-tinue participating. Compared with users, modifiers’experience with one software product and thorough

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knowledge of its source code create greater cognitivelock-in (Shapiro and Varian 1999) and lead to higherlearning costs associated with acquiring new knowl-edge regarding how to use and modify another soft-ware product effectively (Alba and Hutchinson 1987).Hence, because the user’s participation involves lesslearning and cognitive lock-in and because it is easierfor the user to switch to another project’s community,a lack of community response will more likely causethe user to discontinue his participation in the focalcommunity and switch to another OSSD user com-munity than it will cause the modifier to switch. Inother words, the impact of community response onthe user’s continued participation is more likely to begreater than its impact on the modifier’s continuedparticipation.

In summary, given the relative importance of ben-efits provided by the community and the amountof learning costs and cognitive lock-in for users andmodifiers, we hypothesize the following:

Hypothesis 1 (H1). Community response is more likelyto lead to continued participation for users than it is formodifiers.

3. Research Methodology3.1. Empirical ApproachThe research hypothesis is empirically tested in thecontext of OSSD user communities by investigatingwhether the influence of community response on amember’s continued participation is contingent onhis role. We identify his participation and continuedparticipation in the community based on his mes-sage posting behavior in an OSSD project’s discussionforums, whereas we determine his role based on theactivities he performs, which are inferred from thecontent of his messages. Since we are interested inwhether and when a member continued his partici-pation, survival analysis is the appropriate approachhere. Because of the existence of censored data in ourdata set, the empirical approach needs to not onlyfocus on the event but also consider the time to anevent. In addition, the values of some of the explana-tory variables in our empirical model may changeover time; survival analysis is able to include thesetime-varying covariates in the analysis. We employthe Cox semi-parametric model (Cox 1972), whichmakes no assumptions about the form of the base-line hazard function, to identify the factors influenc-ing the hazard rate that an individual will continuehis participation in the future. The model has the fol-lowing form: h4t3X5 = h04y5 × e�1X14t5+�2X24t5+···+�pXp4t5.Here, h4t3X5 represents the hazard function of anindividual at time t, with p time varying covariates

X14t51 0 0 0 1Xp4t5, where �11 0 0 0 1�p are regression coef-ficients and h04y5 is an unspecified nonnegative base-line hazard function.3

3.2. DataOur data come from online discussion forums asso-ciated with a sample of OSSD projects hosted atSourceForge.net, the world’s largest host of OSSDprojects. Although SourceForge.net hosts a large num-ber of OSSD projects, the distribution of projects interms of project size, development activity, commu-nity size, volume of discussion in online forums,etc., is quite skewed (Howison and Crowston 2004).In order to ensure that our data set is representa-tive of the wide range of OSSD projects, we adopt astratified sampling strategy in selecting the projectsto investigate. We first obtain a stratified sample bydividing all projects into nonoverlapping bins basedon the volume of discussion activity in the projects’discussion forums and randomly selecting a propor-tion (3%) of projects from each bin. Projects whoseonline forums contained only discussions initiated byproject members or by anonymous individuals areexcluded from the sample. Finally, to ensure thatour sampling approach is not unduly biased towardprojects of certain application domains or targeted atcertain classes of users, we check the representative-ness of the project sample by comparing the samplewith the population of projects on SourceForge.net.Overall, the distribution of discussion activity, projectapplication domains, and target audience of our sam-ple of projects (N = 312 projects) remains highly rep-resentative of the overall population of projects onSourceForge.net.

As mentioned earlier, the online discussion forumsof OSSD projects are the main source of data for ourempirical analysis.4 These forums are used by many

3 We have also considered the possibility of estimating a fixedeffects survival model to control for unobserved heterogeneityamong individuals. However, one of the data requirements for esti-mating fixed effects models is that the dependent variable needs tobe measured at least twice (Allison 2005). As a result, the analy-sis would exclude the observations associated with the individualswho only participated once (i.e., did not continue their participa-tion). This results in the loss of 2,529 observations (48.3%) that rep-resent nonoccurrence of the continuance event. Consequently, wewould include only the observations from those individuals whoare more likely to continue participating in the community, creatinga sample selection bias. Even for the remaining observations, thefixed effects model uses information about variation within indi-viduals and discards information about variation across individu-als. If a covariate varies mainly across individuals but rarely overtime for each individual, the coefficient for that covariate tends tobe poorly estimated (Allison 2005). Because of these reasons, thefixed effects model is not really appropriate for our analysis.4 We note that most prior studies on IS continuance have relied onprimary data collection. Our study deviates from this tradition by

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OSSD projects not only for communicating and col-laborating among developers but also for interactingwith current and potential users. In fact, in manyOSSD communities, the discussion forum is the maininterface between the project team and the project’suser community. An individual with a question, arequest, or other communication needs may post amessage to a relevant discussion forum. By observingmembers’ communication activities in the discussionforums, we are able to infer whether these membersare participating (and continuing to participate) in thecommunity.

Although participation in discussion forums cantake the form of initiating discussion threads orresponding to messages, we examine members’ par-ticipation in the form of posting thread-initiating mes-sages (i.e., the first message in a discussion thread).Because we are interested in the members in theuser community (and not of the development team),thread-initiating messages posted by developmentteam members are discarded, resulting in a total of5,641 thread-initiating messages in the sample.5 Foreach project, we identify, based on the usernames onSourceForge.net, all user community members whoposted at least one thread-initiating message. Our unitof analysis is member participation represented byposting a thread-initiating message on one of the dis-cussion forums.61 7

We also collect all responses (i.e., follow-up mes-sages) to the thread initiating messages in our

utilizing a rich archival data set collected from OSSD user commu-nities, which allows us to unobtrusively observe the actual behav-iors of community members over a period of time.5 In rare instances, a message was posted to multiple forums of thesame project. Such duplicates are discarded.6 837 individuals (24% of all individuals associated with our mes-sage sample) contributed at least two observations to our data set.In situations where two or more observations are from the sameunit (e.g., a person), these observations may be more alike thantwo randomly selected observations. Allison (1995) points out thatfailure to adjust for the possible dependent error terms may causeunderestimated standard errors and p values. One way to assesswhether the dependence among observations is substantial andwhether correction for such dependence is necessary is to estimatea model for the second interval with the length of the first as acovariate (Allison 1995). We find that in our data set, the first inter-val is not a significant coefficient, indicating that the degree ofdependence is not problematic.7 It is likely that some unobserved heterogeneity or omitted vari-ables that influence a member’s likelihood of receiving responsesfrom the community also influence his continued participation inthe community. In other words, there may be a correlation betweenthe independent variable and the error term, leading to biased andinconsistent estimates (Wooldridge 2009). We use the instrumentalvariable (IV) approach to assess the potential bias due to the influ-ence of unmeasured factors on the dependent variable. The resultindicates that the potential endogeneity bias does not significantlyalter our major findings.

sample. Thread-initiating messages typically have aclearly identifiable purpose (e.g., requesting generalinformation, asking a specific question, suggestinga new feature, proposing code modifications, etc.).By observing the content of the follow-up mes-sages, we can check whether a valid response to thecommunicative purpose has been obtained. Of the5,641 thread-initiating messages, 1,231 (21.8%) didnot have any follow-up messages from others dur-ing the observation period. The remaining 4,410 mes-sages received a total of 8,448 follow-up messagesfrom others.

3.3. Measures

3.3.1. Dependent Variables. Our research hypo-thesis involves one key aspect of members’ behaviorin innovation communities—continued participation.In order to determine whether a member continuedhis participation in the user community, we retrieveall subsequent messages the member posted to thesame discussion forum after the thread-initiating mes-sage and before the end of the observation period.Recognizing that some members may return to thecommunity by providing answers and respondingto others’ messages besides starting another discus-sion,8 the subsequent messages include both thread-initiating messages and follow-up messages to othermessages. Based on whether and when these subse-quent messages were posted, we are able to observewhether and when the member continued his partic-ipation in the community.9

We capture the timing of a member’s continuedparticipation using the variable Time to Return, whichtakes the value of the time (in days) from a member’sposting of a thread-initiating message to his post-ing of the next message. If the member did not postanother message (i.e., the continuance event did notoccur during the observation period), Time to Returnrepresents the length of the time interval between his

8 We would like to thank an anonymous reviewer for highlightingthis point.9 We notice that OSSD communities encourage members to post amessage containing only one topic or question to improve the mes-sage clarity and to facilitate communication with others in the com-munities. Hence, when members have multiple concurrent requeststhat they need answers for, they tend to post multiple messages toinitiate a discussion for each of their requests within a very shortperiod of time. If we count all such messages as participation, wewould unduly over-count continued participation. In order to avoidthis problem, we identify all messages posted by the same mem-ber to the same community within one hour, keep only the first ofthese messages, and omit the others from our consideration. Therewere 204 such omitted messages in our data set (out of a total of5,641 thread initiating messages; i.e., 3.6% of the data). We havealso conducted robustness checks using different thresholds for thetime interval between messages and obtained similar results.

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posting of the focal message and the end of the obser-vation period. Although some members might nothave repeated their participation during the data col-lection period, they might have done so after the datacollection had ended; in such cases, we are unable toobserve their continued participation. These cases arecommonly referred to as right censoring, where theoccurrence of the continued participation event maybe outside the measurement window. To distinguishwhether a given member’s Time to Return representsthe time to the continuance event or the time until theend of the study, we have a censoring indicator vari-able Censor which takes the value of 1 for censoredobservations and 0 otherwise. The analysis incorpo-rates both the time-to-event variable (Time to Return)and the censoring indicator variable (Censor) in orderto use the information contained in both the censoredand the uncensored observations.10

3.3.2. Independent Variables. Community Response.We capture two aspects of community response expe-rienced by the member. The variable Recent Responseis a binary variable capturing whether the focal mes-sage had received a valid response before the mem-ber posted a subsequent message or before the endof data collection (if he did not return to the com-munity). Although thread-initiating messages mayreceive replies, not all replies are necessarily validresponses that satisfy the member’s communicativeneeds. For example, a reply to the thread may sim-ply be an acknowledgement of receipt, which may notsatisfy the poster’s initial intent. In order to identifyvalid responses, content analysis is conducted on allof the follow-up messages (n= 81448) to code whetherthe follow-up messages satisfied the communicativeintent of the original post. Building upon past studiesof face-to-face and online communications (e.g., Chenand Chiu 2008, Schegloff 1996), we categorize follow-up messages as valid or invalid responses based ontheir information content (i.e., whether the informa-tion contained in the message offers a novel contri-bution with regard to the original message). Validresponses are those follow-up messages that directlyprovide the information requested by the originalposter, evaluate the content in the original message,or provide a confirmation or promise that progressis being or will be made to fulfill the request by theoriginal poster. Two coders (a domain expert and oneof the authors) have independently examined a ran-dom subset of 100 follow-up messages as well as theoriginal thread-initiating messages they responded toand coded the follow-up messages into valid andinvalid responses. The two coders have agreed on

10 Although the hypotheses are stated in likelihood terms, we usethe timing of the continued participation event rather than merelyits occurrence to provide richer interpretations of the data. As dis-cussed in §3.1, we analyze the data using survival analysis.

the coding of 92 responses. Given the high inter-raterreliability with the sample of follow-up messages,we have deemed it unnecessary to have two inde-pendent coders—one of the authors has proceededwith the evaluation of the remaining 8,348 follow-upmessages.111 12

However, whether the member’s most recentthread-initiating message received a valid responsefrom the community may not fully capture the inter-action between the member and the community. Forexample, consider a member who had posted threethread-initiating messages with the third messagebeing the focal message and by the end of the obser-vation period did not receive a valid response to thefocal message (i.e., variable Recent Response has thevalue of 0) but received valid responses to his firsttwo messages. If Recent Response were used as theonly measure of community response, it would indi-cate that no interaction between the member and thecommunity occurred, but in fact the community pro-vided responses to the member twice. Therefore, wealso use the variable Cumulative Response Rate to cap-ture the cumulative replies that the member receivedfrom the community in response to his past thread-initiating participations. We compute the ratio of thenumber of messages that received a valid responseto the total number of thread-initiating messages thatthe member had posted before the event of continuedparticipation occurred (or before the data collectionended) as an indicator of the overall responsivenessof the community as experienced by the member.

11 The content analysis procedure we follow has been adopted inprior studies (e.g., Wasko and Faraj 2005). Although the majorityof the coding being completed by one of the authors opens up thepossibility of a conflict of interest in the coding, the process throughwhich the content coding has been conducted renders this possi-bility rather unlikely. First, the follow-up messages are coded withthe identities of the poster masked, making it virtually impossibleto detect any recurring instances of repeat behaviors. Second, thecoding of all the follow-up messages (i.e., responses) are completedwithout the knowledge of the dependent variable (i.e., whether ornot the individual who had posted the original message returnedto the community by participating again), making it difficult toassociate valid responses with continued participation behaviors.12 It is possible that some participants are satisfied even when theresponses they receive do not contain valid responses that fulfillthe communicative intent of their posts. For example, although amessage “I am having the same problem. How can we solve it?”merely repeats the issue raised in the original message, it mayshow to the original poster that his message has captured oth-ers’ attention, which may offer some social support to him. Hence,it is likely that the messages categorized as invalid responses byour coding scheme are important to study as well. Therefore, weinclude a binary variable, Any Response, indicating the existence ofany follow-up message, in addition to Recent Response and Cumu-lative Response Rate. The results show that Any Response does notsignificantly influence the likelihood of a member’s continued par-ticipation (�= −00023, n.s.), which offers support for our claim thatnot all responses provide the benefits that members are seeking.

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Member Role. A member’s role in relation to thesoftware being developed (i.e., user versus modifier)is identified in two steps. First, we examine the con-tent of each thread-initiating message in our sampleto identify the type of activities associated with themessage. These activities include information gather-ing prior to adopting the software product (e.g., willthis software help him accomplish a task or is thisan interesting project that is worth his involvementand participation in the community); requesting assis-tance related to obtaining, installing, and configuringthe software product; providing feedback during theusage of the software product; seeking help on how touse a specific functionality of the software; contribut-ing extensions of the code to enhance its functionalityor improve its quality; and asking questions related tomodifying the code. We infer the member’s role basedon the activities associated with the messages heposted. The user role is associated with general ques-tions about the software/project and requests for helprelated to download, setup, configuration, and compi-lation of the software; requests for information aboutsoftware details; feature suggestions with no imple-mentation details; and problem/bug reports with nosuggestions about solutions because these activitiesdo not relate to modifying the software code. Themodifier role is associated with activities such as con-tributing code and asking questions about modifyingcode. The member’s role is coded using a dummyvariable Modifier indicating whether the member whoposted the focal message is a modifier.

It is possible that members engage in various activ-ities over time. For example, an individual may firstseek help with functionalities of the software but maystart to contribute code extensions to the commu-nity after he becomes more familiar with the soft-ware. Therefore, in the second step, we examine allthe activities that the member performed, which areinferred from the member’s messages coded duringthe first step, up to the posting time of the focal mes-sage, and determine his role as represented by theseactivities. In other words, we aggregate the message-level activities to the individual level by identify-ing whether the individual had been a modifier inthe past.

3.3.3. Control Variables. We also control for thefactors related to the OSSD project, its community,the message itself, and the member who posted thefocal message that may influence members’ continuedparticipation.

Development Stage of Project. A member’s decisionto remain in a community may be influenced bythe maturity of the project. Some members may pre-fer staying in the community when the project isless developed because the code is easier to under-stand and extend (von Krogh et al. 2003). Others

may prefer contributing to the community when theproject is more established and its software is morestable and functional. The development stage of theproject is operationalized using the variable ProjectStage, which is a categorical variable ranging from 1 to6 representing the various stages of software projects,namely, (1) planning, (2) pre-alpha, (3) alpha, (4) beta,(5) production, and (6) mature (Stewart and Ammeter2002). However, because Project Stage was actuallyself-reported by the project administrator, it may notaccurately capture the actual stage of development ofthe project. Hence, we also control for the calendarage of the project as an additional proxy for the devel-opment status of the project. The variable Project Agecaptures the number of months since the project’s reg-istration at SourceForge.net when the focal messagewas posted.

Target Audience of Project. Software intended fordevelopers and system administrators has a “strongcommunity appeal,” especially for OSS (Lerner andTirole 2005, Stewart et al. 2006). As a result, mem-bers may be more likely to return to the communityand remain active over time. To control for this, weinclude a dummy variable (Developer Target Audience)(1 if the project was targeted at developers and systemadministrators and 0 if it was targeted at end users).

Software License Choice. The choice of software li-cense, especially relating to how restrictive the licenseis, has been found to influence user perceptions ofOSSD projects (Stewart et al. 2006). Therefore, theOSS license may also influence how likely mem-bers will continue their participation in the project’scommunity. We include Restrictive License, a variableindicating whether the project’s license was restric-tive. Consistent with prior research (Lerner and Tirole2005), licenses such as the GNU GPL license and theLGPL license are categorized as restrictive, whereaslicenses such as the BSD license are categorized asnonrestrictive.

Market Success of Project. OSS projects producingsuccessful software products may be more responsiveto their members’ requests and suggestions. Success-ful projects may also be considered more favorablywhen members decide whether or not to remain in thecommunity. The variable Downloads, operationalizedas the natural log of the number of times the softwarewas downloaded in the month prior to the posting ofthe focal message, measures the market success of thesoftware at observation time.

Software Domain. The domain of the software mayinfluence the perceived popularity of the project and,consequently, may impact members’ continued par-ticipation. Following the categorization scheme usedby SourceForge.net at the time of our data collec-tion, we represent the domain using a number of

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Table 3 Descriptive Statistics and Correlations

Variable Mean StDev (1) (2) (3) (4) (5) (6) (7) (8)

(1) Recent Response 0054 00499(2) Cumulative Response Rate 0009 00266 −0036∗∗

(3) Modifier 0019 00351 −0001 0014∗∗

(4) Project Stage 5035 00920 −0007∗∗ −0005∗∗ −0002(5) Developer Target Audience 0071 00454 −0006∗∗ −0002 −0012∗∗ 0010∗∗

(6) Restrictive License 0064 00480 −0012∗∗ −0006∗∗ −0002 0014∗∗ −0030∗∗

(7) Downloads 6087 20061 −0005∗∗ 0002 0000 0018∗∗ 0032∗∗ 0000∗∗

(8) Community Size 15074 140622 0006∗∗ 0014∗∗ 0003∗ −0001 0028∗∗ −0046∗∗ 0036∗∗

(9) Project Age 37027 190644 −0009∗∗ 0001∗∗ 0003∗ 0036∗∗ 0024∗∗ 0007∗∗ 0000∗∗ 0014∗∗

(10) Internet 0003 00156 0001 −0001 0005∗∗ −0008∗∗ 0006∗∗ −0014∗∗ 0041∗∗ −0015∗∗

(11) SwDev 0054 00498 0000 0008∗∗ −0006∗∗ −0018∗∗ 0051∗∗ −0033∗∗ 0019∗∗ 0048∗∗

(12) System 0008 00265 0001 −0006∗∗ −0004∗∗ −0001∗∗ −0004∗∗ −0002 −0019∗∗ −0026∗∗

(13) Game 0004 00198 0003∗ 0002 0014∗∗ −0022∗∗ −0028∗∗ 0014∗∗ 0004∗∗ −0008∗∗

(14) Communication 0005 00225 −0008∗∗ −0006∗∗ −0005∗∗ 0007∗∗ 0009∗∗ 0018∗∗ 0017∗∗ −0017∗∗

(15) Multimedia 0000 00069 0001 −0002∗ 0000 −0005∗∗ 0001 0005∗∗ −0007∗∗ −0007∗∗

(16) Prior Message 1073 40122 0001 0025∗∗ 0043∗∗ −0003∗ −0017∗∗ −0008∗∗ 0002 0019∗∗

(17) Message Length 6014 00901 −0003∗ 0003∗ 0006∗∗ 0003∗ 0007∗∗ −0008∗∗ 0002 0008∗∗

(18) Prior Return 0007 00250 −0002 −0002∗∗ 0003∗ −0003 0005∗∗ −0002 −0005∗∗ −0008∗∗

Variable (9) (10) (11) (12) (13) (14) (15) (16) (17) (18)

(10) Internet −0016∗∗

(11) SwDev −0001 −0002(12) System −0017∗∗ 0021∗∗ −0007∗∗

(13) Game 0001 −0003∗ −0021∗∗ −0005∗∗

(14) Communication 0019∗∗ −0004∗∗ −0015∗∗ −0001 −0003∗

(15) Multimedia −0005∗∗ −0001 −0006∗∗ 0001 −0001 −0002(16) Prior Message 0007∗∗ −0005∗∗ 0000 −0005∗∗ 0004∗∗ −0003∗ −0003∗

(17) Message Length 0004∗∗ 0001 0010∗∗ −0001 −0006∗∗ 0000 0000 −0004∗∗

(18) Prior Return −0005∗∗ 0001 −0001 0002 −0003∗ 0001 0001 0000 −0002

Note. Significance levels: ∗p < 0005, ∗∗p < 0001.

binary variables: Internet, S/W Development, System,Game, Communication, and Multimedia.

Community Size. Prior research has found that mem-bership size in online communities has both posi-tive and negative effects on the benefits obtained bytheir members (e.g., Butler 2001). To control for theseeffects, we operationalize the size of the user commu-nity using the variable Community Size, which is mea-sured by the number of non-project members whoposted at least one message during the month prior tothe posting of the focal message. Anonymous postersare counted as one member.13

Length of Message. We control for the length of thefocal message because longer messages typically con-vey more detailed information. Furthermore, a mes-sage with more detailed content may be easier tounderstand and respond to. Consistent with priorresearch (e.g., Hahn et al. 2008), the variable MessageLength, operationalized as the natural log of the num-ber of characters contained in a message, is includedas a proxy for the amount of information in the focalmessage.

Participation History of Member. The more discus-sions a member has initiated in the past, the more

13 In our sample, only 371 messages (or on average 1.19 messagesper project) were from anonymous posters.

familiar he is with the community and the project; asa result, he may be more likely to continue to par-ticipate in the community. The variable Prior Message,which represents the number of thread-initiating mes-sages that the member had posted to the project’sonline discussion forum prior to the focal message, isincluded to capture the level of experience that themember had with the specific project. In addition, themember may also exhibit similar continuance patternsacross different projects. For example, if the memberhas a general tendency to remain in OSS project com-munities by contributing multiple messages over aperiod of time, he may be more likely to continue hisparticipation in the focal community as well. We con-trol for this possibility with the variable Prior Return,operationalized as the ratio of the number of otherprojects where he posted at least two thread-initiatingmessages to the total number of other projects wherehe contributed at least one thread-initiating message.

4. Results4.1. Descriptive StatisticsDescriptive statistics and pairwise correlations arepresented in Table 3. Continued participation oc-curred for 64% of the participation instances during

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the observation period. For those observations wherecontinuance occurred, the average Time to Return is11.4 days. 54% of the participation instances hadreceived a valid response before the next participa-tion instance by the same message poster or beforethe data collection ended. The correlation matrixshows that the pairwise correlations between theindependent variables and the control variables areall below 0.50. We also check the variance inflationfactor (VIF) values for all the predictor variables inthe regression model. The highest VIF value is 2.1,well below the threshold value of 10, indicating thatmulti-collinearity is not a concern (Belsley et al. 1980).

4.2. Results of Hypothesis TestingTable 4 presents the results of our hypothesis test-ing. They suggest that community response in termsof the cumulative response rate to the member’s pastparticipations, instead of the response the memberreceives for his latest participation, positively influ-ences the “risk” that he will continue to participatein the future (Cumulative Response Rate: � = 00289,p < 0001). In addition, there is a significant differencebetween the odds of the modifier’s continued partici-pation and those of the user’s continued participation(Modifier: �= 002521 p < 0001). This suggests that whenall other variables are held constant, the rate of contin-ued participation for modifiers is 28.7% higher thanthat for users. More importantly, the results suggestthat the positive impact of Cumulative Response Rateon the hazards ratio of continued participation tendsto be smaller for modifiers than for users (Cumula-tive Response Rate × Modifier: � = −00436, p < 0001).14

The impact of Recent Response on the hazards ratioof continuance also seems to be smaller for modifiersthan for users (Recent Response × Modifier: �= −00280,p < 0005). In other words, the extent to which com-munity response helps attract the member’s futureparticipation depends on the role of the member.Community response in terms of either the cumu-lative response rate or the recent response is morelikely to sustain the user’s participation than the mod-ifier’s participation. Figure 1 shows the interactionplot. Hence, our hypothesis is supported.

In addition, the results suggest that some projectcharacteristics such as license restrictiveness and tar-get audience also play a role in driving members’continued participation. Members are more likely tocontinue their participation in communities develop-ing software products with a less restrictive license or

14 We also test the linear hypothesis about the net impact of Cumu-lative Response Rate on modifiers (i.e., the sum of the main effect ofCumulative Response Rate and the interaction effect between Cumula-tive Response Rate and Modifier). The result suggests that this impactis not significantly different from zero (Wald �2 = 00976, n.s.).

Figure 1 Impact of Response on Continued Participation:Users vs. Modifiers

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Modifier/responseModifier/no responseUser/responseUser/no response

Notes. The interaction plot highlights the impact of receiving a response (i.e.,Recent Response = 0 vs. 1) on the likelihood of continued participation forusers and modifiers. The figure clearly shows that continued participationis significantly affected by the presence of a response for users but not formodifiers.

targeted at end users, possibly because these commu-nities are perceived to be more attractive and morelikely to achieve success. Members’ continued par-ticipation is also influenced by the community size;members are more likely to keep participating inlarger communities than in smaller ones.

4.3. Post Hoc Interviews with Users and ModifiersAlthough the empirical results clearly show that usersare influenced by community response to a greaterextent than modifiers when it comes to continuedparticipation in OSSD user communities, the theoret-ical mechanism underlying our hypothesis is basedon assumptions about differences in benefits soughtand switching costs across users and modifiers. Giventhe secondary nature of our data, it is not possible,however, to ascertain the validity of these assump-tions empirically. In order to provide further empiricalgrounding for these assumptions, we have conducteda number of in-depth interviews with a group ofusers and modifiers in various OSSD user communi-ties to obtain additional insights on the benefits theyseek from participating in these communities and theswitching costs they incur as well as the motivationsfor their continued participation. These intervieweeshave been identified from OSSD user communitiesoutside of the original sample used in the quantita-tive analysis to further support the external valid-ity of the study. We have conducted semi-structuredinterviews with five modifiers and seven users iden-tified through a local open source software commu-nity as well as SourceForge.net. Each interview haslasted approximately 35 minutes. Table 5 summarizesthe main insights and provides some representativequotes from the interviewees.

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Table 4 Results of Hypotheses Testing

Variable Parameter estimate Hazard ratio Parameter estimate Hazard ratio

Recent Response −00029 00971 00004 10004Cumulative Response Rate 00219∗∗ 10245 00289∗∗ 10335Modifier 00252∗∗ 10287Recent Response × Modifier −00280∗ 00756Cum Response Rate × Modifier −00436∗∗ 00647Project Stage −00006 00994 −00004 00996Developer Target Audience −00355∗∗ 00702 −00356∗∗ 00701Restrictive License −00163∗∗ 00849 −00159∗∗ 00853Downloads 00030∗∗ 10030 00030∗∗ 10030Community Size 00014∗∗ 10014 00014∗∗ 10014Project Age 00000 10000 00000 10000Internet 00141 10152 00144 10155SwDev 00109∗∗ 10115 00112∗ 10119System 00074 10076 00076 10079Game 00087 10091 00088 10092Communication −00400∗∗ 00670 −00400∗∗ 00671Multimedia −00419 00658 −00418 00658Prior Message 00040∗∗ 10040 00039∗∗ 10040Message Length 00152∗∗ 10165 00148∗∗ 10160Prior Return 00047 10048 00049 10051Wald �2 639086∗∗ 680019∗∗

ã in-2 log likelihood 9079∗

Note. Significance levels: ∗p < 0005, ∗∗p < 0001.

Consistent with our theorizing, users seem to pri-marily seek informational benefit in the form of usersupport from the community when they participate.They typically asked questions regarding the installa-tion, the configuration, and the use of the software,expecting others to assist by providing the informa-tion that may help solve their immediate problems.They have stressed during the interviews that theuser support offered by the community was a maindriving force for their continued participation. How-ever, modifiers’ participation was motivated more bythe opportunity to pursue their interest in the soft-ware and to improve it, the enjoyment of workingwith the software and learning new skills, and theprospects of giving back to the community. Overall,the primary motivations for modifiers’ continued par-ticipation seem to be more closely related to theirinteractions with the software code.

Furthermore, users and modifiers valued commu-nity responses differently. Users considered it impor-tant to receive timely and helpful responses fromthe community, whereas modifiers contributing codepatches often did not expect to receive confirmationor acknowledgment from the community, but whenthey did receive it, they felt accomplished knowingthat their contributions helped others. When modi-fiers asked code-related questions but failed to receiveany response from the community, often they werenot only able to eventually figure out the answer ontheir own but also willing to share it with the com-munity, which they felt was “the right thing to do.”

Our interview data also confirm the differences inthe amount of time and effort invested in software-specific learning across users and modifiers. Modifierstended to spend more time and effort examining thecode and understanding how to work with it, whereasusers tended to spend less time and effort learninghow to set up and use the software.

In summary, the interviews with users and modi-fiers provide support for our theoretical assumptionsof differences in benefits sought by users and modi-fiers and the sources of benefits. Modifiers have fre-quently alluded to significant switching cost due tothe extensive amount of time and effort spent in learn-ing about the source code.

It is also worth noting that our interviews revealnot only differences between modifiers and users butalso differences between modifiers and formal mem-bers of the OSSD project team. Although both projectteam members and modifiers are usually program-mers and they both have the technical skills requiredto understand and to modify the source code, mod-ifiers often delineate themselves from project teammembers. They have indicated that their involve-ment with the project was much less than that ofteam members because of their time constraints andother obligations. Although prior studies (e.g., Harsand Ou 2002, Lerner and Tirole 2002, Roberts et al.2006) have identified that OSSD participants are moti-vated by reputational benefit and career advancementopportunities, our interviews with modifiers suggestsuch findings are not necessarily applicable to modi-fiers, possibly because this subgroup of OSSD partic-ipants is not formally affiliated with the project and

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Table 5 Participation and Continued Participation in Online Communities

Summary Representative discussion from interviewee

Topic: Benefits sought from participation and continued participationUsers sought informational benefits from the community. “We had a couple of issues when setting it up on our platform. We have posted a couple

of posts on that such as ‘how to go about it.’ 0 0 0 [I posted the questions hoping]maybe they have encountered it before or maybe what I am missing or what waswrong in my configurations, something along those lines 0 0 0 the forum actually helpedin that regard and we were pleased by the response we received because it solvedour problem.” (User 4)

“If I have a question or a problem, I don’t recall any occasion within 24 hours withoutat least a beginning of one answer, sometimes an answer, somebody else commentingon the answer.” (User 5)

Modifiers sought benefits (e.g., enjoyment, learningbenefits) from interacting with the source code of thesoftware itself.

“I get to work on generally the kind of things that I want to work on rather than whatmy boss told me to work on.” (Modifier 2)

“I am really aggressive on this project and that’s the only thing that is keeping me here.[I am] confident enough on my ability to make changes to the code so that I can getit to work. …I’d like to see what other people are developing on top of the projectand the changes they are making to it, I think that’s interesting and would probablybe one of the bigger reasons. If I see something cool they are doing, I might want todo something similar.” (Modifier 5)

Topic: Impact of community response on continued participation

Lack of user support from the community negativelyimpacted continued participation.

“[I did not post any additional messages on the forum] because I did not receive aresponse to my initial message [from the community].” (User 6)

When modifiers contributed their code patches, they usuallydid not expect confirmation and acknowledgement fromthe community. But when they did receive it, they werepleasantly surprised and felt accomplished.

“[Getting response back from the community] made me feel good and nervous, becauseyou know I haven’t really had a chance to test on anything else, and so I wasn’tentirely sure that if someone else had a different setup and if it wasn’t going to breakanything. But overall it made me feel good. When I got responses back that said‘hey, everything is working great and thanks much,’ that was the fire that made me,you know, really happy that I did what I did.” (Modifier 1)

When modifiers asked code related questions but did notreceive any response from the community, often theywere able to eventually find the solution on their own.They also shared it with the community to help thoseexperiencing similar problems.

“I posted a question to a mailing list and somebody hinted where it was in the code that wasmaking this decision and I looked at it and traced it and found what was doing wrong formy particular case, and chose to work around it, posted it as a patch. 0 0 0 [Putting it upthere] just seemed like the right thing to do; other people are probably going to be havingthat same challenge.” (Modifier 4)

Topic: Learning and setup cost

Downloading and installing the software is easy, especiallywhen the user has experience using similar software.

“Since I have been using other similar software, I personally understand the concept,the concept is similar for everything (project). So if you know the concept, it’s goingto be very easy for you to just download the software, install it. If you ran into aproblem, there is a FAQ already there.” (User 2)

Before modifying the source code, modifiers need to spendmuch time learning about it and understanding how thecode works, especially for more complex projects.

“Every time I open up a piece of software to look at it and try to make a change, thereis usually a good bit of work that goes into trying to figure out how things work andif I go out and make some modifications, am I going to mess up something else.”(Modifier 1)

“There is a significant amount of learning involved when joining the project and becomingpart of community. This project was kind of complex.” (Modifier 5)

because reputation and career advancement opportu-nities may be based on formal affiliation.

4.4. LimitationsBefore concluding, we note some limitations aris-ing from the nature of our data. Our data includeonly community members’ interactions observablefrom the messages posted in discussion forums eventhough they may use alternative communicationchannels such as Internet relay chats and email list-servs. In addition, although our post hoc interviewswith users and modifiers provide qualitative evidence

about the benefits they seek as they continue to partic-ipate in OSSD user communities, the sources of suchbenefits, and the extent of switching costs they incur,our secondary archival data collected from the discus-sion forums does not allow us to directly measure theextent of various benefits or the switching costs.

5. Discussion and ConclusionsThis study looks beyond the motivations of members’initial participation in online innovation communi-ties by focusing on the antecedents of their con-tinued participation, a topic that has been largely

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under-investigated. More importantly, we examinethe joint influence of community response and mem-bers’ roles on their continued participation in thesecommunities. Our findings highlight the need forresearchers to look beyond social interactions amongcommunity members when investigating the motiva-tion and participation behavior of those engaged incommunications and activities around a central prod-uct or service.

Furthermore, from the OSSD perspective, the usercommunity consisting of users and modifiers sur-rounding the project development team has beenunder-investigated in the existing literature, althoughbuilding an active community outside of the coreteam is crucial to the success of OSSD projects(Bagozzi and Dholakia 2006, von Krogh and vonHippel 2006). The results in this study offer insightsto help OSSD project administrators and teams bet-ter identify the members who are more likely toremain in the community based on the roles theyassume. Because community response plays a greaterrole in attracting continued participation of users ofthe software compared to modifiers, if project admin-istrators and teams seek to sustain these members’participation in the community, they may need to bemore actively engaged in communications with themand improve the responsiveness of the community byfocusing on the inquiries and discussions posted bythese members.

In addition, our quantitative and qualitative find-ings not only suggest differences between users andmodifiers in terms of their motivations, switchingcosts, and continued participation behavior but alsoallude to the distinction between modifiers and theformal members of the project team. Developers for-mally affiliated with project teams may be seek-ing reputation and career advancement opportunitiesas compensation for their formal (albeit voluntary)involvement in OSS projects. However, modifiers’participation seems to be primarily motivated by theirsoftware needs, the enjoyment of programming, thedesire to improve the software, the opportunity tolearn about others’ improvements to the software,and the gratification from helping others and giv-ing back to the community. In fact, the extant OSSDliterature on member motivations and participationseems to have overlooked the important distinctionbetween project team members and community mod-ifiers, possibly because of the variety of data sourcesused. For example, some studies use data from mul-tiple archival sources such as project mailing lists(both general purpose and developer-oriented), news-groups, bug tracker systems, and code repositories(e.g., Fang and Neufeld 2009, Hars and Ou 2002) andconsequently focus on all OSSD participants with-out distinguishing among team members, modifiers,

and users. In contrast, some studies adopt a muchmore focused sample such as members of the projectdevelopment team (Grewal et al. 2006, Hahn et al.2008, Roberts et al. 2006); participants of a help dis-cussion forum (Lakhani and von Hippel 2003), mostof whom are developers affiliated with the projectteam; or members of a user group (Bagozzi and Dho-lakia 2006), most of whom are users. Finally, otherstudies focus on participants who have posted mes-sages on developer-oriented mailing lists (Kuk 2006,von Krogh et al. 2003). In these studies, participantscan either be project team members or modifiers,but a clear distinction between the two subgroupshas not been made. Overall, the OSSD research todate has neglected the role of modifiers, an importantsubgroup of OSSD participants who act as a bufferbetween project team members and the broader usercommunity.

Such delineation of roles may help explain someinconsistent findings in recent research on OSSD par-ticipants’ motivations. For example, although bothRoberts et al. (2006) and Shah (2006) identify motiva-tional factors such as software needs, fun, and learn-ing (von Krogh et al. 2012), Roberts et al. highlightthe more extrinsic factors such as reputation, careeradvancement, and pay, whereas Shah draws atten-tion to more intrinsic and relational factors such asideology and reciprocity. A closer look reveals thatRoberts et al. focus on team members who have con-tributed code to the code repository, whereas Shahconducts sampling from all individuals participat-ing in the mailing list of a project, including users,modifiers, and project team members, and does notexplicitly distinguish among these roles. Our studyhighlights the need for OSSD researchers to articulatethe subgroup(s) of OSSD participants they are focus-ing on because their findings are likely to be depen-dent on the specific motivations and behaviors of thesubgroup(s).

From the broader open innovation community per-spective, our study suggests that firms that are host-ing and managing online innovation communities,where consumers are actively involved as co-creatorsof products and services, need to carefully observethe behavior of participants and identify their variousmotivations and roles in the community. In order toinvolve and retain the right participants, firms need topromote the appropriate types of interactions (socialinteractions versus interactions with the innovation)for each role and find the right balance between stim-ulating social connections among participants andencouraging participants’ ideas and suggestions oninnovative products or services. For example, host-ing firms of online innovation communities such asthe BMW Group Co-Creation Lab, MyStarbucksIdea,and LEGO Mindstorms may identify modifiers, who

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are motivated by their involvement in designing andimproving the product or service as well as by inter-actions with other participants, and users, who aremotivated primarily by the opportunity to connectwith others and share experiences. Depending on thetarget group that the community wants to attract andretain, its hosting firm needs to carefully design andmanage the process of engaging the community inorder to fulfill the needs of that group.

Future research may conduct a longitudinal sur-vey of community members about their perceptionsand satisfactions over time and combine such primarydata with secondary archival data such as ours thatcapture members’ actual behaviors. Such combina-tion of longitudinal primary and secondary archivaldata would allow one to identify how the sourcesand the types of benefits that members seek changeover time, how their roles evolve in the community,and how such role evolution impacts their contin-ued participation behavior. Furthermore, it would beinteresting to examine whether and how OSSD usercommunity members’ interactions with project teammembers help sustain the continued participation ofboth community members and project team mem-bers, which plays an important role in the success ofa project.

AcknowledgmentsThe authors thank the senior editor, the associate editor,and the anonymous reviewers for their helpful suggestions.They are also grateful to William Kettinger for his guidanceand help with the qualitative data collection in the laterstages of the study. This research was partially supported bythe New Faculty Summer Research Grant from the Fogel-man College of Business and Economics at the Universityof Memphis.

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