Value creation mechanisms in Web environments

1. Value creation mechanisms in Web environments university of Aegean SDP in Web Science, Oxford Michalis Vafopoulos, 2008

2. contents • Digital goods: definition/characteristics • How Web is related to digital goods • Limit the plethora of opportunities & threats that Web creates • network effects • definition/fundamental components • sources of positive network effects • Metcalfe’s Law • Reed’s Law • criticism • negative network effects • fundamental value components of the Web • more questions from economics • Conclusions 1

3. Digital goods – definition [Quah] • bitstrings, sequences of 0s and 1s, which have economic value or • a set of economically valuable instructions • examples • Ideas and knowledge, computer software, visual images, music, databases, videogames, blueprints, recipes, DNA sequences, codified messages etc 1

4. Digital goods - characteristics • nonrival • use by one agent does not degrade its usefulness to any other agent [ideas, mathematical theorems, S/W, opposite: water] • infinitely expansible • its quantity can be made arbitrarily large arbitrarily quickly at (almost) no cost [mp3 songs, digital pictures] • discrete • instantiate only to quantity 1 - indivisibility • aspatial • they are both nowhere/everywhere at the same time [Virtualization, Lévy] • recombinant • cumulative and emergent/ new digital goods that arise from merging antecedents have features absent from the original 1

5. Web widens these characteristics… • by promoting the following activities at low cost: • Communication • Collaboration • Knowledge Representation • Reasoning & inference(?) • The result is changes in: • Time • Space • Quantity & quality of options 1

6. Web creates “unlimited” options • “unlimited” opportunities, i.e. • innovative technologies • social inclusion • regional development • collaborative research… • and “unlimited” threats: • identity theft • frauds • addictions… 1

7. How can we limit this chaos? [1] • impose hypotheses… starting by • What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. • Herbert Simon, Nobel economics 1978 • micro foundations of consumer’s & firm’s behavior in the Web 1

8. How can we limit this chaos? [2] • Network effects 1

9. Network effects • Some goods/services create more value when more users consume the same goods and services. • They have little or even no value if they are used in isolation. • The consumers using these products constitute networks in which the utility derived from consumption of these goods/services increases as additional consumers purchase the same goods and services. 1

10. Fundamental components of network effects • Expectations • when we choose BlueRay format we believe that it will become a standard • Coordination • reduce the risk of choosing the wrong network. • Difficult in big networks. • Compatibility • two products are compatible when the cost of combining them to generate services is free • Switching Costs • barriers to transfer from a network to another 1

11. Sources of positive network effects • Producer economies of scale & learning curves • Economies of scale • Benefits of cumulative experience “Learning-by doing” (Brian Arrow) • Learning-by-using • Informational increasing returns • As technology gets used, the whole community • figures out how best to apply it • “The Dynamo and the Computer” (Paul David) 1

12. Metcalfe’s Law [1] • Robert Metcalfe, inventor of Ethernet - founder of 3Com • rule of thumb • the value of a network can be measured by the number of connected objects • where “n” is the number of machines (PCs, phones, people) connected, the value of the network is “n” squared • is supported from the data in • semiconductor industry 1

13. Metcalfe’s Law [2] • After critical mass the benefits of a network grow larger than its costs [C*N=A*N^2 , N=C/A is critical mass] • N: network size, C:cost per connection, A: value per connection • The value of a network can not always grow. It may actually starts going down after some size N'>N 1

14. Reed’s Law: Group Forming Networks [1] • GFNs have functionality that directly enables & supports affiliations (i.e. interest groups, clubs, meetings, communities) among subsets of its customers. • Group tools/technologies with common theme (user-defined mailing lists, chat rooms, discussion groups, market makers & auction hosts etc) • aggregate value of a GFN is proportional to the number of non-trivial groups that can be constructed from N nodes (users or members). • N users, construct a total of 2N−N−1 non-trivial groups of sizes between 2 to N members. 1

15. Reed’s Law: Group Forming Networks [2] Beanies www.eBay.com Pez • total network value according to Reed’s Law scales exponentially with N (2N) • Example eBay.com • online auction market site where any subset can form an auction 1

16. What about the Web? 1

17. Criticism • In real life, Reed’s Law means that the total value of a large network doubles every time a new person joins! • No theory behind them • This kind of valuation model ignores key factors—competition/saturation/complexity-burocracy. • Each new connection or GF with same N adds the same value [false assumption] • the smaller network gains considerably more than the larger one. This produces an incentive for larger networks to refuse to interconnect without payment, a very common phenomenon in the real economy [Odlyzko &Tilly] • What about negative network effects? 1

18. Negative network effects [1] • General • digital divide is becoming more expensive both in social and economic terms for people out of the network generating: • new democratic deficit [Vafopoulos]: a metastasis of digital divide which possesses two dimensions: • (a) the lack of effortless and free access to information and communication for all citizens and • (b) unauthorized and no voluntary access to personal data from third parties. 1

19. Negative network effects [2] • security, trust • privacy, identity theft, fraud • personal data aggregation and exploitation from governments • congestion externality • “overuse” of network resources lowers performance (i.e. bandwidth) • challenge • identify & model network effects in social, economic and policy terms 1

20. Fundamental value components of the Web • Which are the “competitive” networks? • in document “storage” and “exchange” i.e. libraries and paper 1

21. The same comparison can be done for… • Communication • Mobile phones • Language • … • knowledge representation • Learning • e-learning =failure (high switching costs) • Selection process • e-voting =failure (high switching costs) • … 1

22. more examples from economics • Transaction cost (Coase) occurs when a good/service is transferred across a technologically separate interface • explains positive network effect in Web environments • Research questions • Are there upper limits to the utility of the freedom that decentralisation has produced? • How easy will it be to describe the Web in game theoretic/rational choice terms? 1

23. more examples from economics • As the number of users increases, will the chances that the choices that one makes impinge on the range of choices available to others increase, or is that an illegitimate extrapolation from the real world with fixed spatial parameters? 1

24. and a philosophical question… • It is not just information that must be free, but the knowledge of how to use it. • The test of a free society is not the liberty to consume information (Web 1.0), nor to produce it (Web 2.0), nor even to implement its potential in private world of one's choosing (Web 3.0 and 4.0). • The test of a free society is the liberty for the collective transformation of the world through abstractions freely chosen and freely actualised. • M. Wark, the manifesto of a hacker • Could be the definition of utopia after digital revolution?

25. review • A research framework • Digital goods, Web • how we limit the chaos of opportunities and threats • Research tools • Laws for value creation in networks • Fundamental value components in networks • [Expectations, Coordination, Compatibility, Switching Costs] • which applies to any kind of analysis 1

26. Thanks for your attention. Michalis Vafopoulos