Like other nonexcludable goods, content
lends itself to FREE RIDING.
Here, we compare
these contexts using the
GARN prism, identify
the threats associated Nonexcludable High
with the GARN phe- Low
nomenon, and discuss
ways to counter the
threats. We provide a
unified framework to
phenomena that were previously viewed in isolation.
Our aim is to unravel the common thread among
Internet-facilitated contexts and consequently examine how lessons from one context may be used in others. Before exploring specific GARN phenomena, we
turn to the economics literature and present several
types of goods, as they are useful in our analysis.
Goods can be classified into four categories across
the dimensions of nonexcludability and nonrivalry
(see Table 1) [ 3]. For example, it is difficult to prevent
nonexcludable goods (such as public parks) from
being consumed by nonpayers; a nonrival (or nonconsumable) good (such as a TV show) can be consumed without diminishing its availability for future
consumption. Unlike physical goods, information
goods (such as software and content) are typically
nonrival [ 11].
OSS development is a growing phenomenon [ 12],
evident in the number of users registered at Source-forge.net (a host for open-source projects,
www.sourceforge.net) that increased from around
500,000 in 2003 [ 6] to more than 1. 8 million in
2008. A growing variety of software applications are
developed in the open-source model; more than
170,000 are registered at Sourceforge. Contributions
are made by individuals independently deciding to
donate time and effort to produce software that is
freely available to all (a pure GARN) or by software
companies actively supporting OSS development.
The availability of high-speed networks allows the
sharing of computer resources via grid computing,
Table 1. Types of
goods [ 3].
enabling better allocation
and use of computing
High resources within and
Public good among organizations.
Collective good Grids may be closed (to
members of a certain
community) or open (accessible to all); they may also
be one-way (contributors lack access to the pooled
resource) or two-way (contributors are also receivers).
A well-known example of a grid-computing project is
SETI@home, a volunteer-based grid comparable to
the strongest computer available today, for searching
for “extraterrestrial intelligence.” Computing grids
can be viewed as grids of computers and primarily
represent an architectural issue. However, our focus
here is the wider issue of grids of computer users and
owners, including their social and organizational
Increasing use of wireless broadband computing is
accompanied by the emergence of wireless commons,
whereby participants provide Internet access to other
participants through their WLAN access points [ 2].
Like computing grids, wireless commons may be
either closed or open to all [ 2]. If the latter, which represents a pure GARN mechanism, individuals must
not password-protect their access points.
Content GARN often manifests itself as contribution of content produced by others (such as media
files shared via P2P systems). However, in many P2P
networks, contributing and consuming are technically almost inseparable for users. Therefore, we won’t
analyze P2P networks here further. A clearer example
of content GARN is knowledge-based, self-created
content, such as Wikipedia, a free online encyclopedia with 1. 4 million entries in English alone, written
and edited by volunteers [ 7].
The GARN mechanism carries with it a number
of threats that can be categorized using the goods
typology (see Table 2); these are analyzed in the next
sections. Given the common GARN mechanism