Download Fundamental components of network effects Expectations

university of Aegean
Value creation mechanisms
in Web environments
SDP in Web Science, Oxford
Michalis Vafopoulos, 2008
contents
•Digital goods: definition/characteristics
•How Web is related to digital goods
•Limit the plethora of opportunities & threats
•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
•Conclusions
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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
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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
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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
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Web creates “unlimited” options
“unlimited” opportunities, i.e.
•innovative technologies
•social inclusion
•regional development
•collaborative research…
and “unlimited” threats:
•identity theft
•frauds
•addictions…
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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
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How can we limit this chaos?[2]
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.
•utility derived from consumption of these goods/services
increases as additional consumers purchase the same
goods/services.
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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
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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)
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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
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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
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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 (userdefined 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.
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Reed’s Law: Group Forming Networks [2]
•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
Beanies
www.eBay.com
Pez
13
What about the Web?
eras
description
basic value source
Pre Web
The desktop is the platform
1980’s
Web1.0:90’s “Surfing” Web:
documents The browser is the platform
Computations
[no network effect]
hyper-linking of
documents
Web2.0: 00’s Social Web:
The Web is the platform
people
social dimension of
linkage properties
Web3.0:10’s Semantic Web:
The Graph is the platform
data
URI-based semantic
linkages
Web4.0:20’s Metacomputing:
+ processing power
abilities The network is the platform hyper-linking
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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/management.
•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?
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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.
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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
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Fundamental value components of the Web
•Which are the “competitive” networks?
• in document “storage” and “exchange” i.e. libraries and
paper
eras
Expectations
Coordination
Compatibility
Switching Costs
Web 1.0
Very low
Low
Very low
Very high
Web 2.0
High
High
High
Low
Web 3.0
Very high
Very high
Very high
Very Low
Web 4.0
Very high
Very high
Very high
Very Low
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The same comparison can be done for…
1. Communication
i. Mobile phones
ii. Language
iii. …
2. knowledge representation
3. Learning
i. e-learning =failure (high switching costs)
4. Selection process
i. e-voting =failure (high switching costs)
…
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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?
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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 new definition of utopia?
21
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]
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Thanks for your attention.
Michalis Vafopoulos
[email protected]