Internet Business Economics and Policy
Lee Kuan Yew School of Public Policy26th November 2013
Dr. John Ure Director, TRPC Pte Ltd (Singapore)
Associate Professor and DirectorTechnology Research Project (TRP)
University of Hong Kong
Executive DirectorAsia Internet Coalition
Lipsey’s 24 General Purpose Technologies(Source: http://en.wikipedia.org/wiki/General_purpose_technology)
Also see Richard Harris ‘The Internet as a GPT’ in E.Helpman (1998) GPTs and Economic Growth
Internet as a GPT(Stylized Ecosystem/Supply Chains)
Hardware Software Services
IP standards Algorithms Production (content … 3D printing)Distribution (CDNs; DRM…)Exchange (e-commerce; digital money)
Devices Apps e-Government
Internet of Things Smarts SNS
Infrastructure Business models Digital Society
Standards, interoperability, networks
IPRs, open source, hybrids
Cloud computing, unified communications
Monopoly Quasi-monopolies Competition
Regulation De-regulation Liberalization
The Age of Algorithms
• 1930s – Turing foresaw the progression from HW to SW
mechanical electrical Algorithms (e.g.
punched tape) + solid state electronics
The long decade
Algorithms and computers(1940s)
Moore’s Law = falling marginal costs
Mobile wireless phones(1940s)
Falling costs of ubiquitous access
Cybernetics (1940s)
Feedback loop = learning-by-doing + information enrichment
Increasing returns? (1990s? dot.com bubble, etc.)
Breaks the rules of equilibrium economicse.g. W.Brian Arthur (1994) Increasing Returns and Path Dependence in the Economy
Chris Anderson’s The Long Tail Internet business model
• “Forget squeezing millions from a few megahits at the top of the charts. The future of entertainment is in the millions of niche markets at the shallow end of the bitstream. Increase in capacity and speeds” http://www.wired.com/wired/archive/12.10/tail.html
Network Economics
• (N-1)N = N2-N L known within IT sector as Metcalf’s LawBut note: well-known within telecoms where the “community
of interest” is not infinite – cf. SNS “Friends”?
See also Carl Shapiro and Hal R. Varian (1999). Information Rules. Havard Business School Press.
CostsInternet Exchanges = Example of Network Economics
Kenya IXP (KIXP), opened in Nairobi in 2000 and the second in Mombasa in 2010.
KIXP operates a Multi-Lateral Peering Agreement (MLPA) whereby ISPs are required to interconnect free of charge, but each pays a usage fee to KIXP.
Google Global Cache (GGC) in April 2011 Traffic volumes rose > x 10 within the year Lion’s share = streamed video, for example from YouTube Latency dropped by 20% on top of the initial fall in latency when
the KIXP was first opened from 1,200-2,000 milliseconds (via satellite) to 60-80 milliseconds.
Now 16 African countries hub through KIXP
CostsInternational versus domestic connectivity
Trombone traffic adds to cost and to latency = between 200 to 900 milliseconds in the case of African ISPs
Several major submarine cables now operating in East Africa – e.g. Eastern Africa Submarine Cable System (EASSy) connects South Africa to the East Africa coast
OECD assessment of the voice-equivalent cost of Internet transit traffic in 2013 = USD 0.0000008 per minute – five orders of magnitude lower than typical voice rates.
BUT … local access charges levied by telecom companies consistently account for between 30%-40% of total international transit costs.
Source: http://www.oecd-ilibrary.org/science-and-technology/oecd-digital-economy-papers_20716826
Costs of Entry and Sustainable Growth
Lowers entry costs Something of a myth that costs across the board are lower
Business costs(e.g. eBay staff grown from 76 to 31,500 over 15 years since IPO –http://www.ft.com/intl/cms/s/0/ffd8fa40-5714-11e3-8cca-00144feabdc0.html )
R&D, start-up costs, capex and opex not very different
Funding often different (VCs, Angel capital, etc.)
Costs of compliance International diversity of jurisdictions
Costs of sustainability
Costs of Innovation Upgrades, patches, new
services, form factors, etc.
Revenue models
Utility models (marginal cost pricing = zero?)
Monthly subs, e.g. broadband, IPTVAnnual subs, e.g. software, online journals, MOOCs Consumer markets Enterprise markets
Online sales & services
e-Commerce, e.g. eBay, online retailers, music
Ads and Big Data Volume dependent, e.g. OTT service providers SNS
Laws & RegulationsTrade & Investment Border controls and
procedures – e.g. e-Commerce companies Localization – e.g. data centres, commercial presence Intermediary liability
Data protection Cross-border data flows Confusion with security
issues?
Content controls IPRs and Intermediary liability for breaches of copyright (or other materials considered unlawful)
Good to grow?The environment for Asia’s Internet business (EIU)
1. There is global demand for Asian content and platforms, but few entrepreneurs are thinking globally.
2. Asian Internet businesses typically focus on home markets, either because they are potentially huge or because they feel they need to build scale before venturing abroad
3. Monetization is an uphill battle for many entrepreneurs.
4. Online payment channels are fragmented and under-developed, hindering business.
Source: http://asiainternetcoalition.org/advdoc/2c083eb6cd1ae38cee3826e1ad6a2a6e.pdf
Good to grow?The environment for Asia’s Internet business (EIU)
5. Internet regulation is on the rise, and many governments are focusing more on control than enablement, failing to understand the negative impact on the sector
• Asia’s market for tech talent is being fought over globally. To ensure supply governments need to think strategically, both in letting foreign talent in and building up the local base
• A culture of collaboration is slowly replacing suspicion in Asia.
Source: http://asiainternetcoalition.org/advdoc/2c083eb6cd1ae38cee3826e1ad6a2a6e.pdf
Conclusions1. The digital economy does not do away with any of the basic
economic truths (dare we call them “laws”?)
2. The digital economy does speed up the rate of transformation and in that sense is disruptive
3. Supply chains (intermediaries) and value chains (sources of revenues) are changed, sometimes dramatically
4. All transformations require changes to business models leading to lobby groups pressurizing policy makers and regulators
5. Policy makers and regulators often have only a partial understanding of the digital economy and the way it works
Thank YouThank You
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