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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