Teigland, di gangi, & yetis setting the stage sunbelt

For presentation at INSNA Sunbelt XXXII, Redondo Beach, CA, March 2012

SETTING THE STAGE:
EXPLORING THE SUSTAINABILITY OF A PRIVATE-COLLECTIVE COMMUNITY

Robin Teigland
Department of Marketing and Strategy
Stockholm School of Economics
Stockholm, Sweden
e-mail: robin.teigland@hhs.se

Paul M. Di Gangi
Department of Information Systems and Operations Management
Loyola University Maryland
Baltimore, MD
e-mail: pmdigangi@loyola.edu

Zeynep Yetis
Department of Marketing and Strategy
Stockholm School of Economics
Stockholm, Sweden
e-mail: zeynep.yetis@hhs.se

March 2012

Please do not quote or cite without permission from the authors.

Acknowledgement: We would like to sincerely thank the OpenSimulator Community for their
openness and helpfulness in conducting this study. It has been a real pleasure and extremely
interesting to work with all of you! We would also like to thank Tomas Larsson and Christina
Huitfeldt for their support in our data collection and analysis.

Setting the Stage – Teigland, Di Gangi, & Yetis

SETTING THE STAGE:
EXPLORING SUSTAINABILITY OF A PRIVATE-COLLECTIVE COMMUNITY

ABSTRACT
While private-collective communities, such as open source communities engaging

directly with firms, are argued to provide the “best of both worlds” for knowledge creation, a

fundamental question is how can a community built using private resources and operating with

the ideals of a collective, sustain its operations and continue to produce attractive rewards for

all parties involved? In this study, we propose that a stakeholder perspective using resource

dependence theory might shed light on this question, and as such, we develop three research

questions: RQ1) What are the resources necessary to sustain a private-collective community?,

RQ2) Who are the stakeholders of a private-collective community and what resources do they

contribute to the community?, and RQ3) What characterizes the structure among the different

stakeholders of a private-collective community? To investigate these questions, we conducted

an exploratory case study of OpenSimulator, an open source community comprising a

multitude of different actors developing a multi-platform, multi-user 3D application server that

enables individuals and firms to customize their virtual worlds based on technology

preferences. Analyses using semi-structured interviews, longitudinal archival data, word bursts

of mailing list messages, and social network data of the community for the period August 2007

to October 2011 revealed how the interrelations among the various stakeholder groups

influence the community’s sustainability over time, thus enabling us to come closer to

fulfilling our ultimate aim of understanding the dynamics of a private-collective community.

Keywords: private-collective, online community, emergent forms of organizing, social
network analysis, resource dependency, stakeholders, open source software, virtual worlds

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INTRODUCTION

Knowledge creation is one of the fundamental drivers of value creation in society and the firm-

based model has generally been heralded by practitioners and researchers alike as the primary

source of knowledge creation. However, researchers have increasingly turned their attention

towards challenging this assumption and have begun to explore models that focus largely on

collective environments as a means to create knowledge (e.g., Lee & Cole, 2003). These

models have been juxtaposed with one another as they differ in their underlying assumptions.

The firm-based model assumes support by private investors who expect to receive returns from

private goods through efficient regimes of intellectual property protection while the community

model is based on "collective action" in which innovators collaborate to produce a public good

characterized by non-excludability and non-rivalry (von Hippel & Von Krogh, 2003).

von Hippel & von Krogh (2003) proposed a hybrid model labeled the “private-

collective” model, which is characterized by 1) private individuals investing resources but

forgoing any potential returns by freely revealing their innovation to the community and 2)

firms that base some or all of their profits on the products or services developed by the

community (Dahlander & Magnusson, 2008). While von Hippel & von Krogh suggest that

private-collective communities provide the “best of both worlds” for knowledge creation, their

sustainability is dependent upon the ability of the different community actors to strike a

balance between their often conflicting values, norms, and goals - a process that may be

especially difficult when the community is faced with an external environment characterized

by turbulent change.

While research and industry demonstrate that firms organize value creation activities

through formalizing their organizational boundaries and acquiring resources to develop

commercially attractive products and/or services for consumers, we know relatively little about

how a community comprised of numerous actors with divergent interests is able to adapt its

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organizing practices to sustainably achieve its goals. Understanding how private-collective

communities sustain themselves adds a layer of complexity to a relatively unknown model of

organizing. How can a community built using private resources and operating with the ideals

of a collective achieve benefits that are attractive to all parties in order to sustain its operations

and continue to produce rewards for all? Thus, the overarching question guiding this research

is the following: how do private-collective communities sustain themselves despite the

divergent interests within the community? The purpose of this study is to explore the

relationships between different sets of private-collective community actors and investigates the

structures and resources by which different actors influence decision making, share power and

resources, and self-organize in order to achieve sustainability, i.e., in order “to continue

providing benefits for members over the long term” (Butler, 2001: 347).

In this article, we propose that a stakeholder perspective using resource dependence

theory might shed light on the sustainability of a private-collective community, and we apply

this perspective and theory in an exploratory study of the OpenSimulator Community. The

next section briefly summarizes the relevant literature on the private-collective form of

organizing and identifies three core questions that will be the focus of our investigation.

Following this summary, an introduction of the research site and methods is presented before

we discuss our analysis and findings. We conclude with contributions and future directions of

this research.

THEORETICAL BACKGROUND

During the past two decades, the widespread global adoption of internet-based communication

technologies has led to the development of numerous online communities. Many of the more

well-known and researched communities include those within the open source software (OSS)

arena, such as LINUX, MySQL, Apache, and GNOME. However, communities are also

developing within other knowledge-intensive industries, such as pharmaceuticals, e.g.,

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PinkArmy; the physical goods industries, e.g., sports equipment (Franke & Shah; 2003; Shah,

2000); and farm machinery, e.g., Jakubowski, 2011. As the number of communities grow so

does participation by firms within them, and these firms are becoming significant players in the

economy. For example, in 2006 a sample of 158 firms contributing to open source had a total

of 530,000 employees and total annual revenue of €231.4 billion (Mehra et al., 2010; UNU-

MERIT, 2006).

Within these communities, individuals from across the globe self-organize around a

shared interest and common practices to create value through sharing knowledge and

innovating. Innovations can take many forms, such as idea generation, realization, prototyping,

transfer, and diffusion. The challenge to these communities is that the knowledge produced is

often described as a privately produced public good (Kollack, 1998, 1999; Lerner and Tirole,

2002; Johnson, 2001; Bessen, 2001; Weber, 2000; Hars & Ou, 2000; O’Mahony, 2003; von

Hippel & von Krogh, 2003). First, this knowledge is the product of private collective efforts

by individuals. Second, the knowledge is nonexclusive, i.e., it is available to all, and it is joint

in supply, meaning its availability to others does not diminish when consumed by one

individual (Snidal, 1979). Thus, the market for this knowledge is not necessarily someone

buying a product or service but instead is peers in the community interested in using the

knowledge (Dahlander & Frederiksen, 2011; von Hippel, 2005). As a result, the community is

a “very rich and fertile middle ground where incentives for private investment and collective

action can coexist and where a ‘private-collective’ innovation model can flourish" (von Hippel

& von Krogh, 2003: p. 213). However, as we will see below, these communities are also ripe

with paradoxes and challenges.

Challenges to the Private-collective Model

Private-collective communities can be both sources of significant value and of potential pitfalls

to firms interested in leveraging them. For example, IBM invests resources into the Apache

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community to ensure its continued success so that IBM can turn community outputs into

service offerings for their corporate clients that produce significant benefits for IBM. eZ

Systems, a Norwegian-based IT multinational, leverages a vast ecosystem of more than 41,000

partners, clients, entrepreneurs, and hobbyists across the globe to support its eZ Publish web

content management system, and as a result it continues to receive accolades from both

organizations and media about its innovation process. However, not every firm’s partnership

with a private-collective is a success story, and there are an equal if not higher number of

failures where a firm expends resources with little return on investment or where the

community has disbanded due to unsustainable demands or divergent interests (Gartner, 2010).

While the initial research in this area focused on individual motivations for community

participation, recently the field has begun to investigate the sustainability of online

communities and in so doing has identified several factors such as the community’s

governance system (O’Mahony & Ferraro, 2007), technology infrastructure (Ma & Agarwal,

2007), and community design (Ren et al., 2007). However, in order for any community to

sustain itself through providing valued benefits to its members, the community must ensure

continued access to a pool of resources, such as time, energy, money, human capital, and

material (Butler, 2001; Rice, 1982). This line of reasoning stems from resource dependence

theory as Pfeffer and Salancik (1978: 43) have argued, “because organizations are not self-

sustained or self-sufficient, the environment must be relied upon to provide support.” Pfeffer

and Salancik (1978) further articulated three characteristics of the environment that influence

resource dependence: 1) structural concentration of power and influence, 2) munificence, i.e.,

scarcity of resources held by stakeholders, and 3) interconnectedness or the patterns of

communication and network linkages.

While online communities such as support groups or special interest groups require

resources such as members willing to spend time and energy sharing their experiences and

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knowledge with one another, private-collective communities may require a more complex set

of resources. As noted above, private-collective communities are increasingly being discussed

as an alternative to the firm-based model for knowledge and value creation. Thus, we would

expect that similar to a firm, a private-collective community would need continuous access to a

set of tangible and intangible resources such as raw materials, financial resources, equipment

and fixed assets, technologies, human capital, and social capital to ensure its sustainability.

While previous research has touched on this issue (e.g., Bergquist & Ljungberg, 2001;

O’Mahony & Ferraro 2007), research has not yet focused on investigating the resources

required for the sustainability of a private-collective community from a stakeholder and

resource dependency perspective. This leads us to our first research question: RQ1: What are

the resources necessary to sustain a private-collective community?

Similar to firms or other organizations, private-collective community members have

interests in and are active to varying degrees in the community’s activities and as such can

affect or are affected by the achievement of the community’s objectives through their

willingness to contribute unique and valuable resources. Organizational researchers define such

actors as “stakeholders” (Freeman, 1984: 46). The concept of stakeholders has become

embedded in management scholarship (Mitchell et al., 1997) as an approach to help managers

understand how they could better manage the firm’s various investors, employees, and

interested parties. What is noteworthy is that the term is not synonymous with individuals but

also refers to groups or organizations that have an interest in the outcome of an organization’s

work processes. In other words, the stakeholder approach is about “groups and individuals who

can affect the organization” (Ramirez, 1999: 102). From a resource dependence view, the firm

is dependent on environmental actors, i.e., stakeholders, for resources; however, it is this

dependence that gives those actors leverage over a firm (Frooman, 1999). As Pfeffer and

Salancik (1978) note, resources come with contingent environment considerations that may

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influence the direction of the community as well as its sustainability. If a specific subset of the

community (e.g., a group of individuals or organizations with a shared attribute or affiliation)

maintains specific control over key resources, it can significantly influence the productivity of

the collective – thereby shaping the direction of the community. Thus, the basic principle of

stakeholder management is to understand who the stakeholders are and how they can be

managed strategically such that the organization can achieve its interests (Freeman 1984). In

recent years, stakeholder theory has been extended by researchers and practitioners alike

beyond that of firms to organizations in general, such as NGOs within the area of natural

resource management (Ramirez, 1999). Clearly a private-collective community is not a firm,

which tends to be the focus of a stakeholder approach, yet these communities are organized as

networks dependent upon the resource contributions of their diverse individual and

organizational members, i.e., stakeholders.

Additionally, the traditional form of organizing economic value creation is

characterized by a structured hierarchical form of governance that remains static over time with

different personnel assuming pre-defined roles of decision-making authority. In contrast,

collectives (as seen in the OSS environment) are characterized by an organic form of

governance that emerges through the fluid social relationships and contributions over time.

When combined, the private-collective community tends to demonstrate an emergent

governing structure, with some formal governing structures and processes, e.g., the OSS

Debian community (O’Mahony & Ferraro, 2007), to manage the interests of their various

stakeholders.

To date, research has identified two larger groups of stakeholders in private-collective

communities: individuals participating on their own behalf and firms whose employees

participate in the community on behalf of the firm (e.g., Dahlander & Wallin, 2006). On the

one hand, there are individuals who volunteer their free time or are self-employed, and their

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motivations have been categorized based on self-determination theory (SDT) (e.g., Deci &

Ryan, 1985; Gagné & Deci, 2005): intrinsic (e.g., fun, enjoyment); internalized extrinsic (e.g.,

reputation, reciprocity, learning, and own-use), or extrinsic (e.g., career and pay) (for a review

of this literature, see von Krogh et al., Forthcoming). On the other hand, these communities

include individuals who participate and contribute code on behalf of their employers seeking to

obtain private benefits (Lakhani & Wolf, 2005; Mehra et al 2010). Firms view communities as

potential complementary assets that can be combined with a firm’s internal resources to

develop competitive products and services (Dahlander & Wallin, 2006), yet their interests may

diverge from the community despite several convergent interests (see O’Mahony & Bechky,

2008 for a review).

With the exception of a few studies (e.g., O’Mahony & Ferraro, 2007), research on

private-collective communities has primarily focused at the individual level – while not

addressing sustainability at the community level. As such, we have a poor understanding of

who the various stakeholder groups are as well as what resources they contribute to the

community. This leads us to our second research question: RQ2: Who are the stakeholders of

a private-collective community and what resources do they contribute to the community?

A community’s access to a pool of resources contributed by its stakeholders must then

be transformed into benefits relevant for the community’s various interests through social

processes (Butler, 2001). In OSS communities, research has found that a two-tiered structure of

a core and a periphery tends to emerge that characterizes these social processes on a higher

level (Bergquist & Ljungberg, 2001; Lee & Cole, 2003). The core developers are responsible

for writing most of the code related to functionality, reviewing and approving code submitted

by the periphery, and making most of the decisions about new releases while individuals in the

periphery add features and detect, report, and fix bugs (Bergquist & Ljungberg, 2001; Lee &

Cole, 2003; Mockus et al., 2000). For example, the core group of developers in the Apache

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case accounted for more than 80% of the contributions (Mockus et al., 2000). Individuals in the

core group are generally nominated and approved by the community in a democratic process.

Contrary to bureaucratic organizations with a formal hierarchy in which individuals progress

“up the company ladder” through gaining authority over more employees, individuals in open

source communities tend to “progress towards the center” initially due to their technical

contributions and then through their ability to coordinate project tasks (Dahlander &

O’Mahony, 2011).

A considerable challenge, however, to the community’s ability to sustain these social

processes is the fact that they are not static entities. Communities are highly fluid – members,

interests, and needs fluctuate over time due to the actions of others within the community as

well as personal or external events (Faraj et al., 2011). For example, the outcomes that

originally motivated an individual’s behavior upon entering a community are not always the

same as the outcomes subsequently generated. Some individuals may attain a high status

within a community and a select few may even leverage their efforts into high-paying jobs,

consulting fees, or public-speaking events - rewards that generally were not among their

original motivations (Shah, 2006; Author Blinded, Under Review). As such, resources ebb and

flow into, within, and out of the community at a continuous and rapid pace (Faraj et al., 2011).

One of the primary concerns of the stakeholder perspective using resource dependence

theory is how a focal organization gains access to the resources it needs through its ability to

influence key stakeholders. Those stakeholders who control the resources needed by the

organization are argued to accrue power, thus creating imbalances among the parties (Mitchell

et al., 1997). Initially, research focused on the dyadic relationships between the focal

organization and its stakeholders. However, recent research suggests that it is not merely the

relationship between the focal organization and its stakeholders that is important to investigate.

Rather the overarching network structure among all the stakeholders and the focal organization

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should be investigated since an organization’s stakeholders are likely to have direct

relationships with each other in addition to the focal organization (Rowley, 1997). In essence,

it is the concentration of power as well as the structure of the network within which a

stakeholder resides that determines both the ability for the stakeholder to achieve a return on its

investment and the community to sustain itself over time (Pfeffer & Salancik, 1978).

This approach builds on the social network perspective, which is primarily concerned

with the interdependence of actors and how their positions in the network influence their

opportunities, constraints, and behaviors (Wasserman & Galaskiewicz, 1994). “Instead of

analyzing individual behaviors, attitudes, and beliefs, social network analysis focuses its

attention on how these interactions constitute a framework or structure that can be studied and

analyzed in its own right” (Galaskiewicz & Wasserman, 1994: xii). One benefit of a social

network perspective is that it enables the investigation of the multiple and interdependent

interactions that exist within the stakeholder environments (Rowley, 1997). Examining

structural characteristics of the overarching stakeholder network can provide insight into the

organization’s ability to influence stakeholders in its quest to gain access to necessary

resources. While some studies examining private-collectives do apply social network analysis

(e.g., Dahlander & Wallin, 2006; Dahlander & Frederiksen, 2011), these tend to be at the

individual level and do not take a stakeholder perspective to investigate how the various

stakeholder groups embed themselves within the network. This leads to our third and final

research question: RQ3: What characterizes the structure among the different stakeholders of

a private-collective community?

In summary, research on private-collective communities has clearly identified the

benefits of firms engaging with collectives for private benefits. However, a complex set of

resources, actors, and social structure must develop and evolve based on emergent conditions

in order to remain sustainable and beneficial to all stakeholders. Using a well-established

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private-collective community based on virtual worlds, we investigate our three research

questions to identify potential factors influencing private-collective community sustainability.

RESEARCH SITE

The OpenSimulator project (http://opensimulator.org) is an online virtual world community

that brings together organizations and individuals and as such represents a private-collective

community. We chose to use the OpenSimulator community as a focal community for our

research for a number of reasons: 1) continuous activity since its foundation in 2007 thus

indicating it has been sustainable to date, 2) a private-collective community with well-

established firms participating (e.g., IBM and Intel), 3) diverse membership in terms of

demographics (e.g., age, educational and professional background, nationality, geographical

location), 4) exhibiting a number of characteristics raised in the literature on private-collective

communities that can accentuate the development of conflict, e.g., anonymity, intellectual

property, and 5) existing within a highly uncertain external environment due to the relative

immaturity of the 3D internet industry that can then impact the supply of resources to the

community.

OpenSimulator is an open source multi-platform, multi-user 3D application server

operating under the Berkeley Software Distribution license that enables individuals and firms

across the globe to customize their virtual worlds based on their technology and use

preferences. The project is powered by the efforts of the community members, who devote

their time and energy to the development processes. From its inception in 2007 to December

2011, 101 developers have committed 16,056 submissions to the OpenSimulator project

resulting in 338,467 lines of code and an estimated cost (based on the COCOMO model) of

$4.99 million dollars (USD). The project has a global reach, crossing 22 time zones, and the

community hosts a diverse group of members. The OpenSimulator project has a 3D aspect that

facilitates a strong sense of immersion for both its developers and users, setting the project

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apart from traditional open source projects. Since the project develops around such a strong

communication medium, there are many contributing to and using OpenSimulator, who are

very passionate about virtual environments and its power as a platform for social exchange.

There are many ways to participate in and contribute to the OpenSimulator project: via

IRC (Internet Relay Chat), mailing lists, the Twitter hashtag (#OpenSim), and the

OpenSimulator Wiki as well as through individual members’ websites or blogs. Another way

to participate is to create an OpenSimulator-related project hosted on SourceForge

(http://forge.opensimulator.org/gf/) or elsewhere. With regard to the mailing lists, the

community members can participate based on two generic roles. First, members who are users

of the OpenSimulator platform can join the Users mailing list that can be used to pose

questions on usage, report bugs, and engage in conversation with likeminded individuals

interested in utilizing OpenSimulator either personally or professionally. Second, members

who are developers can participate in the Developers mailing list that discusses technical issues,

project updates, news announcements concerning modules and company actions as well as

social communication to embody a sense of community among the developers that is separate

from the users. In many open source projects users are the developers of the project itself. For

OpenSimulator, however, there is a clearer distinction between users and developers. Most

noticeably, the developer to user ratio is relatively low in OpenSimulator compared to other

open source projects. This is due to the fact that the potential users of the project are already

developed by Linden Lab (through their use of Second Life); therefore, from the start they

have a good understanding of how to use OpenSimulator and what to expect from it. In general,

users can start using OpenSimulator without necessarily having to expend a lot of development

effort.

METHODOLOGY

Several data collection approaches were used to gather data on the OpenSimulator community.

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First, we conducted 10 unstructured and then 10 semi-structured interviews with members of

the OpenSimulator Community. These interviews were all conducted virtually through the

virtual world of Second Life or OpenSimulator (figure 1) or via Skype. Using the snowballing

technique, we conducted interviews with core developers and members of the OpenSimulator

ecosystem while asking each interviewee to identify additional individuals to interview.

Questions concerning the roles, resources, and motivations for contributing to the community

were included in the interview questionnaire to ensure a rubric to assess motivation and

resource contributions in further analysis.

FIGURE 1
Conduc'ng)an)interview)
Conducting an Interview through OpenSimulator

In addition, we scraped the relevant online sites (e.g., OpenSimulator wiki, Ohloh

commit website, SourceForge site, and social networking sites) and mailing lists for textual

analysis and relational tie data for the first four years and three months of the community- from

the emergence of the community in August 2007 to the end of October 2011. We divided the

data into two periods: 1) August 2007 to September 2009 and 2) October 2009 to October 2011.

Not only did this division represent relatively equal periods, but it also was in line with two

aspects relevant to our analysis: 1) an internal change in which the code reached a relatively

stable development level at the end of September 2009 and 2) an external change in which

much of the hype and interest surrounding virtual worlds had faded.

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Combining the textual analysis with the relational tie data collected throughout the four

years enabled us to perform social network analyses using UCINET version 6.181 with

attribute data to determine the overall network structure of the OpenSimulator community as

well as the structural positioning of different groups of stakeholders within the community

during the two different time periods. Lastly, we validated the results of our analysis by

interviewing the most central member of the community in both time periods to determine

whether the observations made by our research team align with the historical context of the

community. However, as an ongoing research study, we will use the results from the social

network analysis to further identify individuals to interview who may possess a unique

perspective of the community due to his or her social interactions. This will allow additional

validation of the archival data and provide additional descriptive and contextual information

that can add depth to our findings.

RESULTS

RQ1: What are the resources necessary to sustain a private-collective community?

The strategic management literature classifies resources into 1) tangible, e.g., financial

and physical, 2) intangible, e.g., technology, reputation, and 3) human, e.g., skills, commitment,

loyalty (Grant 2008). Additionally, this literature describes how resources are static and that to

perform a task resources must work together. Organizational capabilities are therefore defined

as the capacity for a set of resources to perform a task or activity in an integrative manner

(Grant 2008). Capabilities can be identified through breaking down value creation activities

into primary, i.e., activities directly related to producing the service or product, and support

activities, i.e., activities that support the primary activities, (Porter, 1985) and through a

functional classification, e.g., marketing, corporate management (Grant, 2008).

Through our analysis of the interviews and secondary data, we identified a range of

primary and support resources and capabilities necessary for the sustainability of the

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community (table 1). First, OpenSimulator is similar to other virtual IT development projects

with regard to the resources and capabilities required for the software development: resources

necessary to complete the work (i.e., the actual project itself) and resources to support the

project team (e.g., code repositories, communication technologies) along with expertise

capabilities to complete the work and capabilities for coordinating the work in a virtual

dynamic environment (PMI, 2008).

Interestingly, our analysis also revealed that OpenSimulator requires the resources and

capabilities of several other types of organizations. First, OpenSimulator in many regards

functions as an overarching firm within which the software development process occurs, and as

such it requires a set of primary and supporting “firm” resources, e.g., computing process,

storage, copyrights, reputation, and corresponding capabilities, e.g., creating awareness of its

products and services, human capital development, attracting resources and talent, and business

intelligence. In many regards, OpenSimulator is competing against other open source software

and other online communities for resources, such as the software expertise needed to fulfill its

main objective, as well as against other virtual world platforms and service providers for

potential users and customers. Second, OpenSimulator is similar to a joint venture since

members come from diverse organizations with significant underlying differences in their

behaviors, values, attitudes, motives, organizational identities, and loyalties (Lerpold, 2003).

This brings with it the need for supporting resources, e.g., dialogue and conflict resolution

skills, and supporting capabilities, e.g., negotiating motives and timeframes and achieving

collective competence, i.e., the group’s ability to work together towards a common goal and

the creation of a collective outcome (Ruuska & Teigland, 2009). Finally, OpenSimulator is

similar to volunteer organizations in terms of its need for commitment and loyalty from its

members as well as its capability to manage external shocks and the fluidity of its resources.

Our analysis thus revealed that OpenSimulator requires not only a set of primary

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resources and capabilities to create the software, but it also requires a complex set of support

resources and capabilities to sustain itself. The question that our analysis thus raises is what

are the sources of these resources and capabilities, which supports our theoretical reasoning

motivating the second research question of our study.

TABLE 1
Resources and Capabilities of the OpenSimulator Community
Activity Resources
Tangible Intangible Human Capabilities
Primary Technology Technology System architecture skills Code development
infrastructure, Copyrights Programming skills Installation
e.g., servers Debugging skills Seamlessness with other
Information Patching skills technologies and applications
archives Implementation skills, e.g., grid Keeping pace with potentially
running competitive developments
Intellectual property skills Creating awareness of
OpenSimulator products and
services
Support Financial Culture Information Complex project management
Reputation management/archival skills Virtual organizing
Legitimacy Communication and Human capital development
collaboration in virtual Cross-cultural management
environment skills Business intelligence
Dialogue skills Energizing
Conflict resolution skills Resolving tensions
Negotiation skills Negotiating motives & timeframes
Intellectual property skills Achieving collective competence
Commitment Attracting resources to community
Loyalty Attracting talent to community
Managing external risks and shocks
Managing fluidity

RQ2: Who are the stakeholders of a private-collective community and what resources do they

contribute to the community?

Within the stakeholder literature, there is an ongoing discussion as to how to identify

stakeholders (see Mitchell et al, 1997 for a review). However, in recent years, stakeholder

attributes have received increased attention (Frooman, 1999). Within the resource dependence

view, it has been proposed that stakeholders can be identified by their power to influence the

organization through the control over necessary resources both in terms of access to the

resource as well as how the resource can be used (Frooman, 1999). In addition, the urgency of

the stakeholder’s claim on the organization is to be considered (Mitchell et al., 1997).

Developers of stakeholder theory have found that classifying stakeholders into useful

categories facilitates the analysis (Rowley, 1997). It is important to note here that since the

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OpenSimulator community is not a formal organization with organizational boundaries

distinguishing external stakeholders from the organization. Consequently, we treat all

community members as stakeholders given the fact that all play an integral role in the success

of the community due to their ability to provide unique contributions.

As noted above, private-collective communities comprise two broad groups of

stakeholders: private individuals and organizations. Our analysis suggests this was too general

a categorization – particularly for the organization category. One aspect that became

particularly apparent during the interview phase is that the individual member’s stakeholder

affiliation, e.g., Hobbyist, Entrepreneur, SME Employee, Academic, plays a role in terms of

the resources that the member can potentially provide. For example, the large company

members provided legitimacy that the SME Employees or entrepreneurs could not.

Additionally, there appeared to be a different sense of urgency or timeframe based upon

stakeholder affiliation - with the Entrepreneurs and SMEs generally having shorter time

horizons than the Large Firm Employees, Hobbyists, or Academics in terms of seeing

developments realized. Finally, we noticed that the issue of intellectual property also played a

role in terms of resource contribution, e.g., with the Hobbyists contributing more freely than

the Entrepreneurs and Large Firm Employees, who in turn contributed more freely than the

SME Employees.

While there may be other ways to identify and classify stakeholders, we decided to

proceed with a stakeholder categorization based on an individual member’s organizational

affiliation. We investigated the OpenSimulator wiki and developer mailing list to identify the

organizational affiliations of individuals by checking these affiliations based on publicly

available information during the two different periods found on 1) signature messages in

electronic communications, 2) postings and profiles on social networking sites, e.g., LinkedIn,

Twitter, facebook, 3) postings and profiles on other mailing lists and online communities, e.g.,

18


SourceForge, Ohloh, 4) official company websites and blogs, and 5) private websites and blogs.

Through this process, we identified the following organizational affiliations: 1) Academic –

employed at a university, 2) Entrepreneur – self-employed or founder of a firm selling services

or products related to OpenSimulator and the 3D internet, 3) Hobbyist – participating in

OpenSimulator on own free time due to personal interests, 4) Large Firm Employee (> 250

employees) 1, 5) Non-profit Employee, 6) Local or Regional Public Sector Employee, 7)

Federal Public Sector Employee, 8) Research Institute Employee, and 9) SME1 Employee

(<250 employees). For the individuals who were employees in groups 4 to 8, these individuals

were participating within OpenSimulator due to their responsibilities assigned by their

employer. While this may be considered a fine-grained categorization, we chose to maintain

this view of stakeholder categories so as not to confound any findings by grouping together

different organizations.

Two researchers conducted this stakeholder coding independently and crosschecked

each other’s work. This coding procedure was considerably tedious as we investigated the

information posted by each individual across various public sites and across the two different

time periods of our study. However, we were surprised at how much information was publicly

available and at how consistent the information was for an individual across sites. For example,

in only 4% of the individuals during period one was there a discrepancy between what people

wrote on the various internet sites. In these cases, we chose to use the stakeholder category that

he/she identified on the OpenSimulator wiki as this was the category under which they chose to

represent themselves to the community. Finally, we were also somewhat surprised at how little

variation there was in terms of individuals changing their stakeholder category. While several

individuals changed jobs during the entire four year period, few actually changed stakeholder

category.

1
The official EU definition of an SME is < 250 employees.

19


With the various stakeholder groups identified, we proceeded to identify what resources

and capabilities each group brought to the OpenSimulator community. One of the most

important resources contributed to the community is the development of the underlying source

code of the OpenSimulator platform. On Ohloh, a public directory of open source software,

there were 319,849 lines of code in the project as of September 2009 and 337,458 lines of code

as of October 2011. The project has an Active Core Developers group, which fluctuated around

20 developers during the first period and 12 developers during the second period. These

individuals contributed the most to the code repository and were responsible for deciding

which developers to invite to join the Active Core group. To be invited to join the core

developers group, an OpenSimulator member must demonstrate skills in producing interesting

and useful code within the very large main code base, handling some degree of pressure

gracefully, and functioning within the multi-faceted spirit of the project. The project also

distinguishes between developers who are active and those who are not within the community.

Core developers who do not contribute to the code for six or more months have their status

changed to "Following the white rabbit". However, if a developer starts contributing to the

code again, he/she is moved back into active status. These “white rabbit followers” can also be

moved to a permanently disengaged status at their request, and as such they lose their access to

the OpenSimulator repository server.

Our investigation revealed that a core principle of the OpenSimulator community is that

simple and naive solutions are appreciated as developers aim to make the code as simple,

structured, and readable for newcomers as possible. Introducing new technologies that would

increase thresholds for installing and using the code in different environments are discouraged

in order to facilitate maximum compatibility. The OpenSimulator project aims for better code

reuse and prefers incremental improvements to profound rewriting. This translates into the fact

that the developers try to avoid profound refactoring since it destabilizes the project and the

20


community. However, one of the benefits of OpenSimulator as is generally the case in other

open source communities is that when there is a highly controversial decision about the kernel,

developers have the right to fork the project if they do not agree with the direction the

community decides to take.

During the four years of the project we analyzed, there were a total of 34 developers

who were at one point classified as Active Core Developers: Academics 3 (8.8%),

Entrepreneurs 14 (41.2%), Hobbyists 8 (23.5%), Large Firm Employees 5 (14.7 %), and SME

Employees 4 (11.8%). However, Ohloh identified that there were 87 committers during the

same four years. Of these 5 (5.7%) were Academics, 25 (28.7%) Entrepreneurs, 21 (24.1%)

Hobbyists, 9 10.3%) Large Firm Employees, 6 (6.9%) SME Employees, and 21 (24.1%) were

not identifiable due to lack of information provided by the committer. An analysis of these 21

who were not identifiable revealed that they were minor contributors since during the entire

period all had 15 or fewer commits and on average had only five commits. Among those who

were identifiable, there were no Non-profit, Public Sector, or Research Institute individuals

contributing code. Table 2 provides an overview of the stakeholder affiliation of the Active

Core Developers at the end of each period as well as the top 20 Ohloh committers during each

period.

On the Ohloh site, committers are also relatively ranked on a scale of 1-10 (10 highest

rank). An Ohloh community member can assign “Kudos” to any other member contributor

based on his/her appreciation or respect for the contributor as well as take these Kudos back if

he/she so desires. Of the ten individuals who received the highest ranking of “9” kudos during

the four year period, five were Entrepreneurs, two were Hobbyists, two were Large Firm

Employees, and one was an Academic,

This analysis reveals a clear dominance of Entrepreneurs both in quantity and quality of

code development, indicating the importance of this stakeholder group’s resource contribution

21


to the community. Hobbyists were relatively less active; however, over time they represented a

larger portion of the commits to the OpenSimulator project growing from 10% to 30% of the

top 20 committers during the two time periods. Large Firm Employees were somewhat more

active than Academics, with Large Firm Employees growing somewhat in importance from

period one to two. SME Employees displayed a similar pattern to Hobbyists during the first

period but completely ceased their activity during the second period. Finally, there were no

contributions from the other categories of Non-profit, Local Public Sector, Federal Public

Sector, or Research Institute during either period.

TABLE 2
Overview of OpenSimulator Developers on Wiki and Ohloh
August 2007 - September 2009 October 2009 – October 2011
Active Core Ohloh Top 20 Active Core Ohloh Top 20
Stakeholder Developers Committers Developers Committers
Affiliation # Inds % Total # Inds % Total # Inds % Total # Inds % Total
1-Academic 2 10% 2 10% 1 8% 1 5%
2-Entrepreneur 8 40% 11 55% 7 58% 9 45%
3–Hobbyist 4 20% 2 10% 2 17% 6 30%
4-Large Firm 3 15% 3 15% 2 17% 4 20%
5–Non-profit 0 0% 0 0% 0 0% 0 0%
6-Local Public 0 0% 0 0% 0 0% 0 0%
7–Federal Public 0 0% 0 0% 0 0% 0 0%
8-Research Inst 0 0% 0 0% 0 0% 0 0%
9-SME 3 15% 2 10% 0 0% 0 0%
Total 20 100% 20 100% 12 100% 20 100%

Additionally, there are a considerable amount of community members who contribute

bug reports, patches, testing, and maintenance work to the OpenSimulator project, who listed

themselves on the OpenSimulator Wiki. In the first period, there were 64 people, of which we

coded 62 with an organizational affiliation: Academics 4 (6.5%), Entrepreneurs 21 (34%),

Hobbyists 23 (37%), Large Firm Employees 11 (18%), Federal Public Sector 1 (1.5%), and

SME Employees 2 (3%). In the second period, there were 84 people, of which we coded 81

with an organizational affiliation: Academics 7 (9%), Entrepreneurs 25 (31%), Hobbyists 31

(38%), Large Firm Employees 13 (16%), Federal Public Sector 2 (2%), and SME Employees 3

(4%). In both periods, we found a slightly higher number of Hobbyists than Entrepreneurs

22


with a larger relative increase of Hobbyists in period two. Academics also increased their

participation noticeably from period one to two.

A second important resource to the community is the developer mailing list, which

serves as both a forum for collaboration as well as an information archive. During the first

period, there was a total of 7654 messages posted by 251 unique individuals with an average of

30.5 messages per individual and during the second period 2942 messages posted by 229

unique individuals with an average of 12.8 messages per person. We coded each individual

who had made more than four posts during either of these time periods with his/her stakeholder

affiliation – a total of 138 individuals in period one and 101 individuals in period two. An

investigation of the content of the messages made by people posting four or fewer posts during

both these periods revealed that the majority of questions or posts were either spam or

questions or messages that were not relevant to the community and thus received no response.

Thus, we chose this cutoff as we did not consider those making four or fewer posts during a

two-year time period to be contributing to the community. The resulting number of messages

in period one was 7424 posted by 138 individuals - 54 messages per person, and in period two

2696 posted by 101 individuals in period two - 27 messages per person.

Of note is that during the first period, 119 individuals (86%) of the 138 actively posting

individuals were easily tied to their real life identity while only 19 individuals (14%) acted

anonymously in terms of being able to code them with a “real life” identity. However, we

could code 14 (10%) of these 19 individuals with a stakeholder affiliation since they had well-

established online identities such as in the virtual world of Second Life or through their own

websites, blogs, etc. Several of these even acted as avapreneurs, i.e., entrepreneurs selling

virtual goods or services through their avatars (Teigland, 2010). Thus, only five (3.6%) acted

truly anonymously, and we coded these as Hobbyists since there was no evidence either online

or in their postings to the mailing list that they were affiliated with any kind of organization or

23


had entrepreneurial interests. In the second period, 82 individuals (81%) of the 101 individuals

actively posting were easily tied to their real life identities, eight (8%) had well-established

online identities, and the remaining. 11 individuals (11%) acted truly anonymously and thus

were coded as Hobbyists.

In terms of demographic attributes, the majority of the identifiable individuals were

working age males with a technical background from the Northwestern hemisphere, e.g.,

Europe and North America, and who were capable of communicating in English. However,

there were several members from countries such as Japan, Australia, and Malaysia, thus the

community was spread across 22 time zones. An extra note is that the Active Core Developer

group comprised individuals spread across 18 time zones. Tables 3a and 3b contain descriptive

statistics for participation among the various stakeholder groups during each of the two time

periods.

TABLE 3a
OpenSimulator Mailing List Contributors – Period One
Org. Affil. # Individuals % Total # Messages % Total #Msg/Ind
Academic 12 8.7 857 11.5 71
Entrepreneur 47 34.1 3386 45.6 72
Hobbyist 39 28.3 1396 18.8 36
Large Firm 18 13.0 1191 16.0 66
Non-profit 3 2.2 60 0.8 20
Local Public 2 1.4 29 0.4 15
Federal Public 1 0.7 21 0.3 21
Research Inst 1 0.7 25 0.3 25
SME 15 10.9 459 6.2 31
Total 138 100% 7424 100% 54

TABLE 3b
OpenSimulator Mailing List Contributors – Period Two
Org. Affil. # Individuals % Total # Messages % Total #Msg/Ind
Academic 14 13.9 594 22.0 42
Entrepreneur 39 38.6 1376 51.0 35
Hobbyist 30 29.7 437 16.2 15
Large Firm 11 10.9 177 6.6 16
Non-profit 2 2.0 29 1.1 15
Local Public 1 1.0 14 0.5 14
Federal Public 1 1.0 14 0.5 14
Research Inst 0 0.0 0 0.0 0
SME 3 3.0 55 2.0 18
Total 101 100% 2696 100% 27

24


We find a pattern here similar to the above analysis. The Entrepreneurs dominate in

terms of resource contribution with 34% in period one and 39% in period two of the total

mailing list population and with 46% and 51% of the total body of messages, thus giving them

a relatively high message-to-individual ratio (72 and 35). The second largest group of

individual members, Hobbyists (28% and 30%), generally has a considerably lower message to

individual ratio (36 and 15) while Academics (71 and 42) or Large Firm Employees (66 and

16). Moreover, SME Employees, while just slightly under in number compared to Large Firm

Employees during period one, decreased significantly during period two and have a

considerably lower message to individual ratio (31 and 18). The remaining Non-profit, Public

Sector, and Research Institute individuals participated the least in both absolute and relative

terms with a message-to-individual ratio between 15 and 25 in period one and between 0 and

15 in period two. Noticeable in the comparison across time periods is the universal decrease in

the message per individual ratio across all stakeholder groups indicating that the time period

around October 2009 was a key period where a dramatic shift in the community occurred.

To analyze the content of the messages posted to the mailing list, we conducted a word

burst analysis of the content of the messages posted during the two time periods (tables 4a and

4b). A word burst analysis identifies the words that are most characteristic of a certain person

or group (Kleinberg, 2004). Thus, it does not show absolute frequency but instead identifies

the words that are most overrepresented in a sample or portion of a text compared to the entire

text using the "probabilistic generative model", i.e., more characteristic words rank more

highly than less characteristic words of a person or group compared to the group as a whole. A

comparison of the word burst method with other methods shows that the burst method

produces results that are more refined compared to cruder measures provided by the methods

in the comparison group (Kleinberg, 2004). We generated a word burst for each stakeholder

affiliation group, which identified the words that were most overrepresented in the messages

25


posted by the respective group compared to the sum of all messages by all groups during each

time period. For example, while Academics use the word “user” more frequently in absolute

terms than “inventory”, compared to the average, Academics use “inventory” more often than

“user”. This analysis gives an indication of the type of issues each stakeholder group is

discussing and can be seen as an indication of the type of resource that it is contributing to the

community.

TABLE 4a
30 Most Characteristic Words per Stakeholder Affiliation – Period One
Academics Entrepreneur Hobbyist Large Firm Non-profit Local Public Federal Public Res Inst. SME
inventory state debug availabletype hints stolen currency behaviour portability
user join osg processing help centos money geometry openid
really obscures saving file tested ceo risk states metadata
servers night succeeded worlds internal info losing vehicle asset
think pages osgrid users similar screen chatrooms phantom userserver
server scene shape mathematics correctly sue commerce integer inventoryserver
millions region guest center bitsystem free inworld unit regionserver
region believe functions tree sanded sued owner physics script
addresses physics guests wrote people terminal legal state goods
different prerouting grid next understood ward due appenders class
inventoryserver core value approach router loss educational patch executed
modules currency build computer map svn solutions everybody assets
grid incoming sims rest regions override core body assetbase
agent revision project attachments viewer release monetary collision inform
service opencurrency allow asset computer viewing argument prim cable
hypergrid separate regions respond host wrote implementation options compiler
search model assets corp. precious having corruption geometries plugins
registry propose fatal math programmers urge devolve independant packet
set sounds notions types scripts readable essential zone scriptengine
scenes local logins printing locally confirm. opencurrency logging lock
people joint total machines next current/trunk scope initialrotation service
register application running utilization instances supportinformation immature printstatus private
services assigned plazas dissemination priorities widows plans vehicles lively
session points vehicle prohibited sim file claims hidden neighbours
system tag cba privileged configured immediate software shapes tests
push memory mono separate software copy case cultures hack
cap prim perhaps review part flavored samplemoney initialposition touch
happy think patches emulator holding lends external globally return
regions defaults copyright pervasive website wished dollars flag servicebase
security objects tester vector height bandwidth functions initialization creationdate

During the first period, we found that Academics focus on the development of the

underlying platform and technology infrastructure as the words they use are inventory, servers,

regions, modules, etc. The focus for the Entrepreneurs tends to be more on the development of

the actual use of the OpenSimulator virtual world, e.g., night, scene, region, physics, currency.

The Hobbyists are concerned with testing and debugging the software, e.g., debug, functions,

fatal, patches, etc. For the employees, Large Firm Employees seem to be interested in data

26


processing and visualization while the SME Employees are focused on programming since

their words are very programming oriented. The Non-profits have issues related to installation

and the use of OpenSimulator while both the Public Sector categories discuss legal and

financial issues.

TABLE 4b
30 Most Characteristic Words per Stakeholder Affiliation – Period Two
Academics Entrepreneur Hobbyist Large Firm Non-profit Local Public Federal Public Res Inst. SME
hg we bulletsim updates education research testclient behaviour admin
wifi state wiki sciencesim socket sl bot geometry item
master established pm trust exception project gridclient engine megaregions
info join documents testclient initiative beneficial appearance states prims
scholar never bots queue forums educational avatar vehicle viewer
robust night part adaptive failed hud minutes phantom megarion
timeout pages testclient voice endpoint failed skull integer trees
regionstore scene next dsg debug comfortable enable unit add
freeswitch region kins pronounced respond boxed using physics linkedin
university believe wise bots request declined lot state scalable
version obsolete outfit viewer trace sciland answer appenders names
line physics documentation simian string stupid problem patch inventory
connector core authority appearance inner colleges grey collision root
lgpl modules install packet element develops megaregion prim robot
migration currency users retransmit next maliciousintent position application/ms sequence
offline incoming gravity distance connection medicine simulation options mobilephone
note revision olg packets part newbies opensim api file
resource opencurrency newest priority boolean phenom runned geometries coordinates
branch separate framework algorithm receiving reassuring help zone pinkutus
updating model backup iteration period operator object logging prisonplanet
tiles propose flotsam lgpl unable perspective apperance vehicles next
tracking fields varies infinity portales team stored shapes grass
publications definitively years gpl timeout endlessly assess cultures services
simian local use network int grid/standalone retrieve initialposition part
notes joint display discuss unity speculations disturbing globally archive
userstore application personal bandwidth getfolder luck inherited flag regioninfo
map forge genuine linden stack moving independant initialization sensor
handlers assigned physical graph thanks settings actually settings noticed
licence points kin queuing attempt projectand manipulating logger following
sciences guess patent city sending repeatable figures testavatar opensimbase

During the second period, we found that Academics shifted focus slightly to the

research of virtual worlds and their application to the university environment by using such

words as scholar, publications, Simian, and university, version, info, etc. The focus for the

Entrepreneurs remains relatively stable with a more pronounced tendency towards the

monetization of the OpenSimulator virtual world, e.g., opencurrency, currency, and application

development, e.g., modules, fields, revision. The Hobbyists also seemed to have shifted

slightly with more interest in software use, e.g., documentation, wiki, install, display, backup,

etc. For the employees, Large Firm Employees continue to maintain interest in the technical

27


infrastructure and application of virtual worlds in specific areas, e.g., network, packets,

sciencesim, scisim, etc., while SMEs focused almost exclusively on application development.

The Non-profits have shifted towards understanding the more technical aspects of

OpenSimulator while the Public Sector stakeholders are focused on the use and application of

virtual worlds.

Another resource that has been highly noted in the literature and that we confirmed in

RQ1 is passion of individuals, or devoted enthusiasm for the community’s goals, within the

community (Faraj et al., 2011). To identify those who demonstrated passion, we conducted a

degree centrality analysis of the mailing list postings. We chose degree centrality because it

considers the absolute number of times people posted compared to others. Entrepreneurs lead

in terms of contribution as 6-7 of the top 10 and the top two most central individuals were

Entrepreneurs in both periods. Of note is that these top 10 individuals were also among the

highest in quantity and quality committers noted above and nine were Active Core Developers

in the first period and six were Active Core Developers in the second period.

We then took a first step at mapping our findings onto the table in terms of which

stakeholder affiliation groups are involved in contributing which resources to OpenSimulator

in order to begin to understand their influence as stakeholders within the OpenSimulator

community. At this point, we cannot complete the resource and capability table (table 5);

however, this table will be used to guide our research as we proceed with investigating the

sustainability of the OpenSimulator community. We have inserted an X in the box where we

have found support for this stakeholder affiliation group to be the dominant resource

contributor, i.e., other stakeholder affiliation groups may be contributing as well, throughout

the two time periods.

One observation from our analysis is that the valuable intangible resources and support

human resources and capabilities are not easily connected to originating from one stakeholder

28


group. Rather, these resources and capabilities are developed within the community through

everyday interactions between the diverse individuals comprising the community and in

particular within the Active Core Developer Group. One means to better understand these

interactions is through a social network investigation of the structure of the relationships,

which we turn to in the next section.

TABLE 5
Initial Overview of OpenSimulator Resource and Capability Contribution
Acad Entrep Hobby LrgFi NonP FedPub LocPub ResIn SME
Primary Tangible Resources
Technology infrastructure, eg servers X X
Information archives X
Primary Intangible Resources
Technology
Copyrights
Primary Human Resources
System architecture skills
Programming skills X
Debugging skills X
Patching skills X
Implementation skills, e.g., grid running X
Intellectual property skills
Primary Capabilities
Code development X
Installation X
Seamlessness w other technologies & applications X
Keeping pace with potentially competitive X
technology developments
Creating awareness of OpenSimulator X
products/services

Support Tangible Resources
Financial
Support Intangible Resources
Culture
Reputation X
Legitimacy X
Support Human Resources
Information management/archival skills
Communication and collaboration in virtual envts
Dialogue skills
Conflict resolution skills
Negotiation skills
Intellectual property right skills
Commitment
Loyalty
Support Capabilities
Complex project management
Virtual organizing
Cross-cultural management
Human capital development
Business intelligence
Energizing X
Resolving tensions
Negotiating motivations & timeframes
Achieving collective competence
Managing fluidity
Attracting resources to community
Attracting talent to the community
Managing external risks and shocks

29


RQ3: What characterizes the structure among the different stakeholders of a private-collective

community?

To investigate our final question, we turned to social network analyses using the

OpenSimulator Developers mailing list. The interactions taking place on this mailing list

represent the day-to-day interactions that Freeman (2005) refers to as one of the three

stakeholder relationship levels to be investigated; the other two being the organization as a

whole and the organization’s processes or standard operating procedures. Our first analysis was

to generate the overarching network graphs based on an individual’s replies to others in the

community. We included the entire population of both senders and receivers on the mailing

list for the two time periods. Figures 2 and 3 provide four snapshots of the network for the two

time periods: Figures 2a and 3a include all ties, Figures 2b and 3b include those who have ties

with at least two others, Figures 2c and 3c include those who have ties with at least three others,

and Figures 2d and 3d include only those who have ties with 10 or more people.

Figure 2a is a highly connected component with a dense core and loosely connected

periphery. What becomes evident in the first period is that the inner core is composed primarily

of Entrepreneurs and Large Firms, with the Large Firms clustering more on the left hand side

and the Entrepreneurs more on the right hand side of the core. Moving out from the core there

seems to be a pattern of rings based on stakeholder affiliation: first Large Firm Employees,

then SME Employees, then Hobbyists, and then the Periphery, i.e., those who sent four or

fewer messages during either of the two time periods. The Academics seem to be sprinkled

throughout. When reducing the network between Figures 2b and 2c, the Periphery becomes

disconnected. These individuals were not active community contributors, i.e., responding to

other community members’ posts, so even if they did post messages or pose questions to the

community, the community did not respond to them. Figure 2d further reveals that there is a

tightly knit core group driving the network during the first period.

30


FIGURE 2 a-d
Network Structure of OpenSimulator Developer Mailing List – Period One

Turning to the second period, we find quite a different pattern. First, the network itself

is much sparser than the previous time period. Overall interaction among individuals decreases

particularly within the core of the network (comparing Figure 3a to 3d). Figure 3a

demonstrates that the core of the network is primarily composed of Entrepreneurs, Hobbyists,

and Academics versus the previous time period. Entrepreneurs and Hobbyists remain

generally dispersed across the entire network (similar to period one) while Academics disperse

across the lower left side and center of the network. Large Firms have shifted towards the

periphery of the network in period two indicating that Large Firms have decreased their

participation and moved more towards maintaining an awareness of the developments of the

OpenSimulator community versus direct involvement in its direction. In fact, Large Firms

appear to cluster more towards the lower left side of the network suggesting interest in specific

subsets of the community versus the entire community (e.g., focused attention on virtualization

31


in virtual worlds versus the overall virtual world community). Also, Academics and Hobbyists

have taken a progressively more central role within the community serving as connectors

between several Entrepreneurs and Large Firms. The few remaining SME Employees are also

more clustered around the lower right side of the network away from the Large Firms, possibly

indicating a strategic shift for SMEs away from competing directly against Large Firms. The

remaining stakeholder groups appear in pockets of the network; however, they are dispersed

with no discernible pattern.

FIGURE 3 a-d
Overall Structure of OpenSimulator Developer Mailing List – Period Two

A further investigation revealed that member degree and eigenvector centrality are

characterized by a long-tail, further confirming our above analyses of an active core. We

conducted an eigenvector centrality test since this measures the influence of a node in a

network through assigning relative scores to all nodes in the network based on the concept that

connections to high-scoring nodes contribute more to the score of the node in question than

32


equal connections to low-scoring nodes. These tests revealed again the high influence of

Entrepreneurs throughout both time periods (table 6). Noticeable when comparing across time

periods is the sudden decrease in the diversity of the most central community members from

Entrepreneurs, Academics, Large Firms, and Hobbyists in period one to Entrepreneurs,

Academics, and Hobbyists only with Entrepreneurs remaining the most influential and largest

stakeholder group of the most central community members. To fill the void created by the

turnover of the Large Firm Employees, Academics and Hobbyists became more active. This

suggests a key structural pattern for sustaining the community is the participation of multiple

stakeholders with one dominant stakeholder group (e.g., Entrepreneurs) driving the bulk of the

community activity.

TABLE 6
Centrality of Top 10 Community Members
Period One Period Two
Aug 2007- Sept 2009 Oct 2009 – Oct 2011
# Eigen Degree Eigen Degree
1 Entrep Entrep Entrep Entrep
3 Entrep Entrep Acad Acad
5 Acad Acad Entrep Hobby
6 Large Large Entrep Entrep
7 Large Large Hobby Entrep
8 Entrep Entrep Entrep Hobby
9 Hobby Hobby Hobby Entrep
10 Entrep Entrep Acad Acad
10 Hobby Hobby Entrep Entrep

Additionally, we examined whether a clustering effect occurred within the community

based on stakeholder affiliation. A hierarchical cluster analysis revealed a low degree of

diverse clustering in both periods. At times issues would be discussed by only two (and in a

low number of cases three) people, indicating that the community is characterized by a high

degree of interaction between all members regardless of affiliation.

Looking at the fluidity of the members from period one to period two (figure 4), we

find a distinct pattern in which active members during both periods (red nodes) cluster together

33


while new members in period two (blue nodes) cluster together. Interestingly, the new

members cluster around one central person who was active in both periods (red node in the

lower right side) suggesting that this individual plays an ambassador role to bridge the “old

guard” of the community to the rising new members. Interestingly, this node is located away

from Large Firms and closer to Hobbyists and Entrepreneurs, which may influence the future

shape of the core of the network as these newcomers will have more direct contact with key

members of the community. Also, the clear separation of active individuals in both periods

and newcomers active in period two suggests that the virtual world community may be

entering a maturity phase where the foundation issues for developing and maintaining a virtual

world (e.g., processor configuration, hosting) have been resolved and the new members are

focused on application and use. Thus, a potential differentiating point between server-side

developers and client-side developers may be emerging which would make the individuals that

connect these two groups increasingly important to sustaining the community and protecting it

from forking.

FIGURE 4
Member Turnover from Period One to Period Two

34


In terms of member turnover by stakeholder affiliation (table 7), we find an overall net

decrease in member participation over time with only three groups slightly increasing.

Entrepreneurs and Hobbyists, the largest two membership groups both lose a large share of

members but also receive a new influx of members resulting in moderate decreases overall

suggesting a healthy turnover of membership may be needed in these groups to sustain the

community, i.e., new ideas and skillsets entering the community through turnover.

TABLE 7
Member Turnover by Stakeholder Affiliation
Stakeholder
Affiliation Member Loss Member Gain Net Change
Academic 4 8 4
Entrepreneur 22 17 -5
Hobbyist 21 20 -1
Large Firm 7 0 -7
Non-profit 0 1 1
Local Public 2 1 -1
Federal Public 0 1 1
Research Inst 1 0 -1
SME 7 1 -6
Periphery 91 83 -8
Total 154 132 -22

Finally, based on Rowley’s discussion (1997) related to the overarching network

structure of stakeholder relations, we collapsed the node graphs based on stakeholder affiliation

for both time periods (figures 5a and 5b). Since OpenSimulator is not an official organization

with a focal organization, we ran two analyses: 1) we collapsed all individual nodes into one

node based on his/her stakeholder affiliation, and 2) we separated out the Active Core

Developers at the end of each period and collapsed these to make a focal organization and then

collapsed the remaining nodes based on stakeholder affiliation.

35


FIGURE 5a
Collapsed Node Structure: Left without Core and Right with Core – Period One

FIGURE 5b
Collapsed Node Structure: Left without Core and Right with Core – Period Two

Both pictures indicate that there is a high degree of density in the overarching structure

with the stakeholder affiliation groups highly connected with one another. Not surprisingly, the

Entrepreneurs are the most central in the left figure for both periods one and two while

Academics become more central in period two. However, what is interesting in the right figure

is the centrality of the Hobbyists in the community. As noted in the figures above looking at

the network at the individual level, we found that while they were not so central, Hobbyists are

well distributed around the network and interacting with a relatively more diverse set of others.

This suggests that each group sustains the community through role specification.

Entrepreneurs and, more recently, Academics assume the role of acting as central points of

36


contact that direct the actions of the community (through code contributions and influencing

the network through maintaining strategic ties) and Hobbyists disperse throughout the

community making them strategically important for developing a holistic view of what work is

being performed in the community. Large Firms remain members of the community to

provide access to key infrastructural resources, e.g., processing, storage, but maintain a loosely

affiliated connection, which allows them to tap into the community when needed, i.e.,

complementary assets.

DISCUSSION

The purpose of our research is to shed some light on the overarching question: how do private-

collective communities sustain themselves despite the divergent interests within the

community? We developed three research questions based on a stakeholder perspective to

resource dependence theory with the intention of raising the level of analysis from that of the

individual, e.g., participation motivations, to the level of the community, i.e., resource and

capability needs of the community. As mentioned earlier, resource dependence theory states

that three environmental conditions may influence a structure: 1) centralization of power and

influence, i.e., stakeholder groups, 2) munificence, i.e., scarcity of resources held by

stakeholders, and 3) connectedness or linkages among individuals, i.e., network structure,

(Pfeffer & Salancik, 1978). The analysis for our first research question RQ1: What are the

resources necessary to sustain a private-collective community?, revealed an extensive list of

resources and capabilities not previously presented in a compiled format in the literature. The

principle finding was that while most primary tangible, intangible, and human resources are

brought to the community by individual members, OpenSimulator’s sustainability is dependent

upon the community’s development of a complex set of support capabilities that exceed those

required of a virtual IT project.

Turning to RQ2: Who are the stakeholders of a private-collective community and what

37


resources do they contribute to the community?, our analysis provided some unexpected

findings. Previous literature has analyzed the different stakeholders of open source

communities by mainly separating them into two groups: firm-sponsored individuals and

hobbyists (e.g., West & Gallagher, 2006; Dahlander & Wallin, 2006) or need-driven and

hobbyist participants (Shah, 2006). While Shah (2006) lists the different motivations and

resources these two different groups bring to the community, this analysis of the need-driven

participants does not consider a deeper or more granularized understanding of the stakeholders

involved. Notable from our research was the dominant presence of Entrepreneurs in this

community across multiple time periods and the relatively weak presence of Hobbyists, which

is counter to traditional open source software communities. Entrepreneurs are the driving

engine of this community and contribute the most in terms of resources – developing code,

helping and sharing with others, energizing, coordinating, etc., while Hobbyists, even though

they were a sizable portion of the community in absolute numbers, contributed with a few

exceptions much less to the community than expected. This is not to say that Hobbyists are not

of value, merely that the collective output of the primary resource that this group provides to

the community may be overrated by practitioners and researchers alike.

Furthermore, Large Firm Employees and Academics were equal or more active in

contributing resources to the community than Hobbyists and SME Employees in period one,

while Academics and Hobbyists were more active in contributing resources in period two.

Surprisingly, SME Employees were the least active in the community, not counting the more

or less unrepresented Non-profits, Public Sector Organizations, and Research Institutes. Thus,

our findings provide support for taking a more fine-grained approach when investigating issues

of resource contribution and community sustainability than the previous grouping of need-

based individuals into one category or dividing members into firms and hobbyists.

An initial mapping of stakeholders to the list of resources and capabilities developed in

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