Anti-rival good
Anti-rival good” is a neologism suggested by Steven Weber. According to his definition, it is the opposite of a rival good. The more people share an anti-rival good, the more utility each person receives. Examples include software and other information goods created through the process of commons-based peer production.
An anti-rival good meets the test of a public good because it is non-excludable (freely available to all) and non-rival (consumption by one person does not reduce the amount available for others). However, it has the additional quality of being created by private individuals for common benefit without being motivated by pure altruism, because the individual contributor also receives benefits from the contributions of others.
Free open-source software
Lawrence Lessig described Free and open-source software as anti-rivalrous: "It's not just that code is non-rival; it's that code in particular, and (at least some) knowledge in general, is, as Weber calls it, 'anti-rival'. I am not only not harmed when you share an anti-rival good: I benefit."[1]
Network effects
The production of anti-rival goods typically benefits from network effects. Leung (2006)[2] quotes from Weber (2004), "Under conditions of anti-rivalness, as the size of the Internet-connected group increases, and there is a heterogeneous distribution of motivations with people who have a high level of interest and some resources to invest, then the large group is more likely, all things being equal, to provide the good than is a small group."[3]
Although this term is a neologism, this category of goods may be neither new nor specific to the Internet era. According to Lessig, English also meets the criteria, as any natural language is an anti-rival good.[4] The term also invokes reciprocity and the concept of a gift economy.
Data sets
Nikander et al. insist that some data sets are anti-rivalrous. This claim rests on three observations:[5]
  1. It's cheaper to share than exchange data, because exchange requires erasing in addition to transferring data.
  2. If the cost of copying is negligible, then the Pareto optimal allocation of any such data set is (near) universal availability.
  3. The value of many data sets increases with the number of users, because the shared knowledge tends to reduce the barriers to understanding and collaboration. This contrasts sharply with material goods, where consumption by one reduces and may eliminate the value to another.[6]
Of course, this assumes that the data shared does not involve uses that would likely harm humans.[7]
See also
  1. ^ Lessig, L. "Do You Floss?". London Review of Books. Archived from the original on 10 December 2006. Retrieved November 14, 2006.
  2. ^ Leung, T. "(Review) The Success of Open Source". Sauria Associates. Retrieved November 15, 2006.
  3. ^ Weber, S. (2004), The Success of Open Source, Harvard University Press, ISBN 978-0-674-01292-9
  4. ^ Lessig, L. "Do You Floss?". London Review of Books. Archived from the original on 10 December 2006. Retrieved November 14, 2006.
  5. ^ Pekka Nikander; Ville Eloranta; Kimmo Karhu; Kari Hiekkanen (2 June 2020), Digitalisation, anti-rival compensation and governance: Need for experiments, Wikidata Q106510738.
  6. ^ The comic strip Pogo featured in one strip a retailer, who would rent a sandwich. It was funny, because a sandwich obviously rivalrous.
  7. ^ See, e.g., Siva Vaidhyanathan (12 June 2018). Antisocial Media: How Facebook Disconnects Us and Undermines Democracy. Oxford University Press. ISBN 978-0-19-084118-8. Wikidata Q56027099., and Spencer Graves (18 July 2014), Restrict secrecy more than data collection, San José Peace & Justice Center, Wikidata Q106512569.
Last edited on 15 April 2021, at 23:19
Content is available under CC BY-SA 3.0 unless otherwise noted.
Privacy policy
Terms of Use
HomeRandomNearbyLog inSettingsDonateAbout WikipediaDisclaimers