t-109.4300 network services business models of innovation • new or improvedproduct, service or...

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Agenda © Sakari Luukkainen 1 14.1. Introduction, Sakari Luukkainen 21.1. Theoretical frameworks, Sakari Luukkainen 28.1. Business model design, Sakari Luukkainen 4.2. ICT in business process, Sakari Luukkainen 11.2. STOF cases, Olli Mäkinen 25.2. Cloud computing, Sakari Luukkainen 4.3. Green ICT, Sakari Luukkainen 11.3. Mobile cloud computing, Sakari Luukkainen 18.3. Mobile ecosystems, Juha Winter 25.3. ICT start-up development, Aaltoes & Android Aalto 1.4. Summary, Sakari Luukkainen 10.4. Examination

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Agenda

© Sakari Luukkainen

1

14.1. Introduction, Sakari Luukkainen21.1. Theoretical frameworks, Sakari Luukkainen28.1. Business model design, Sakari Luukkainen4.2. ICT in business process, Sakari Luukkainen11.2. STOF cases, Olli Mäkinen25.2. Cloud computing, Sakari Luukkainen4.3. Green ICT, Sakari Luukkainen11.3. Mobile cloud computing, Sakari Luukkainen18.3. Mobile ecosystems, Juha Winter25.3. ICT start-up development, Aaltoes & Android Aalto1.4. Summary, Sakari Luukkainen

10.4. Examination

© Sakari Luukkainen Sources: Distimo, Foresman, 2010; Sristava, Lara, 2006;Shapiro & Varian, 19992

ICT innovation growth

Characteristics of innovation• New or improved product, service or process from a

market point of view, which contains newtechnological solutions based on R&D investmentsand has been commercially successfully introducedto the market.

• Ultimate commercial success requires innovation inthe whole value network of companies.

• The innovator gets competitive advantage throughtiming advance and IPR protection by patents – shortmonopoly.

• Monopoly will loosen through trade of patents andlicenses or knowledge spillovers when competitorscopy the technology and proprietary technology getscommon to all players in the industry.

R&D investment

Product innovation

Service innovation

Process innovation

© Sakari Luukkainen

3

Incremental change

Discontinuous change- competence, product, market

Mag

nitu

deof

chan

ge

TimeSource Tushman, 1997

New entrant

Technology evolution and revolution

Technology competitionM

arke

tSha

re(%

)

Time

100

50

Winner

Loser

Battle zone

5

© Sakari Luukkainen

Source: Shapiro & Varian 1999

Positive feedbackmakes the stronggrow the stronger andthe weak weaker.

Technology competition

© Sakari Luukkainen

6 Source: Shapiro & Varian 1999

Valu

eto

Use

r

Number of Compatible Users

Virtuouscycle

Viciouscycle

Dominant design is a technology thatwins the allegiance of the market place. Itusually takes the form of a new product orservice synthesized from technologicalinnovations.

Innovation over time

© Sakari Luukkainen

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cost of changes

information

degrees of freedom

market uncertainty

Time

Market uncertainty

• Market uncertainty refers to the inability of vendors andservice providers offering new communications solutions topredict the latent end user needs.

• The uncertainty exists partly also because users do not knowwhat they want until they see and use it.

• When users are first introduced to a new technology theytend to view it in the context of the older technology. They donot know enough about the new technology to understand itspossibilities.

• Users’ needs evolve hierarchically from basic features tomore sophisticated ones along with the technology evolutionas they become more educated about its benefits.

© Sakari Luukkainen

8 Source: Gaynor, 2003

Managing market uncertainty

• Rather than analyzing the market and selecting the best alternative,new services should be developed by successive approximations,that is, by introducing early versions of the product into the initialmarket, learning from the experience, modifying the product andapproaching the market on the basis of better new information incircumstances of lower uncertainty.

• A successful convergent technology and market vision is oftenfound by technology- and business-oriented individuals who workedclosely together from early on.

• In conditions of high market uncertainty, competition is feature-based differentiation and price-based in low market uncertainty.

• When market uncertainty is high, being lucky with a correct guessabout the market is likely to produce more revenue than being rightin markets with low uncertainty.

© Sakari Luukkainen

9 Source: Gaynor, 2003

Managing market uncertainty

• The usage of a flexible, modular system architecture in theintroductory phase of a new communications platform, when themarket uncertainty is high, enables experimentation of suitable newservices especially when they are targeted at latent end users’ needs.

• This understanding of such a derived demand that is related to thenew telecommunications services has been found to be a successfactor for the vendors in telecommunications.

• Nobody predicted in the early 90´s what Internet is today and itsimpact to society.

• The flexible layer architecture of the Internet enabled new servicedevelopment according to contingent market development withoutlarge changes in the underlying infrastructure.

© Sakari Luukkainen

10 Source: Gaynor, 2003

© Sakari Luukkainen

Innovation diffusion

Num

bero

fUse

rs

Time

Saturation

Launch

Takeoff

Criticalmass

Late majority

Early majority

Early adopters

Source: Rogers, 199511

Innovators

Leapfroggers

Laggards

Innovators

Innovation diffusion

• Relative advantage (price and performance) over competingtechnologies substitutes

• Compatibility with the values, norms, needs, and experienceof the end users

• Low complexity

• Easy trialability of the early adopters

• Observability of innovation, the visibility among the usercommunity

© Sakari Luukkainen

12 Source: Rogers, 2003

Economies of scale

• ICT services have high fixed costs but low marginal costs -they are costly to produce but cheap to reproduce

• Supply-side economies of scale exist when the cost perunit decreases as more units of the good are produced

• The net value of the last produced unit [= (€ amountconsumers are willing to pay for the last unit) - (average perunit cost of production)] increases with the number of unitsproduced

© Sakari Luukkainen

13 Source: Shapiro & Varian 1999

Network externalities

• Demand-side economies of scale exist when the value of asubscription to the network is higher when the network has moresubscribers. This is also known in economics as network effect ornetwork externality.

• Network externalities arise because a typical subscriber can reachmore subscribers in a larger network.

• A network exhibits network externalities when the value of asubscription to the network is higher when the network has moresubscribers.

• Metcalfe´s law: total value of network = n * (n-1) = n2 – n [n peoplein a network]

© Sakari Luukkainen

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Network externalities• Physical networks connect users directly to each other (e.g., railroad,

telephone line), whereas virtual networks connect users indirectly. Virtualnetworks are a collection of compatible goods and services that share acommon technical platform.

• Network externalities arise in virtual networks because larger sales of good Ainduce larger availability of complementary goods B1, ..., Bn, thereby increasingthe value of good A. The increased value of good A results in further positivefeedback.

• Complementary goods are additional products or services that enable orenhance the value of another good. In some markets, it may be important toattract producers of complementary goods in order to attract users.

• The number of units of a platform in actual use is also known as the installedbase of the technology. The installed base can be an effective way of gaugingthe popularity of a platform and, thus, the strength of its network externalities.

© Sakari Luukkainen

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Two-sided networks

• Two-sided networks are platforms that have two distinct usergroups providing each other with network benefits. Benefits to eachgroup exhibit demand-side economies of scale.

• In a two-sided network, members of each group exhibit apreference regarding the number of users in the other group; theseare called cross-side network effects. Each group’s membersmay have preferences regarding the number of users in their owngroup; these are called same-side network effects.

• Consumers, for example, prefer credit cards honored by moremerchants, while merchants prefer cards carried by moreconsumers.

• Two-sided networks are also useful in explaining many free pricingor "freemium" strategies where one user group gets free use ofthe platform in order to attract the other user group.

© Sakari Luukkainen

16 Source: Wikipedia

Cross-side

Same-side

Switching costs

• When there are substantial switching costs in movingfrom one technology or service to another, users facelock-in.

• Investments in varying complementary benefits relatedto the actual ICT investment influence switching costs.

• Sonera & Elisa example: low number of movingcustomers before portability of telephone number.

• iki.fi e-mail solution to reduce switching cost.

© Sakari Luukkainen

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Type of lock-in Switching costs

• Contractual commitments

• Durable purchases• Complementary products• Brand-specific training• Information and db• Specialized suppliers• Search costs• Loyalty programs

• Compensatory or liquidateddamages

• Replacement of equipment• Replacement of equipment• Learning new system• Converting data to new format• Finding of new supplier• Learning about quality of altern.• Lost benefits from existing

supplier

© Sakari Luukkainen

18 Source: Shapiro & Varian 1999

Switching costs

• Existing installed customer base with high switching cost is asignificantly valuable asset

• Acquiring a new customer is much more expensive than keeping anexisting one

• Total switching cost = costs the customer bears + costs the newsupplier bears

• The present discounted value to a supplier of a locked-in customer isequal to total switching costs plus the quality or cost advantage ofcurrent supplier’s product

• Collective switching costs (e.g. group pricing of mobile calls)

© Sakari Luukkainen

19 Source: Shapiro & Varian 1999

Openness vs Control

Your

Sha

reof

Indu

stry

Valu

e

Total Value Added to Industry

Control

Open

Your Reward

Optimum

20

© Sakari Luukkainen

Source: Shapiro & Varian 1999

Open innovation

© Sakari Luukkainen

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Source: Chesbrough, H. (2003). Open Innovation: The NewImperative for Creating and Profiting from Technology

© Sakari Luukkainen

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Internet Service Evolution

websitee-commerce

e-businessvalue networks

ecosystems

-Order and payonline

-Reduction oftransactioncosts

-Maximizeaccessibility tonew markets

-Visibility in theglobal market

-Diffusion andgathering ofinformation

-Supply chainintegration

-Economy inthe value chainintegration

-Reduction ofcost

-Portals

- New Internetbusiness modelsbased onorganizationsinternetworking

-Virtualenterprises

-ExampleAmazon,Google/Android,Apple

-Dynamicaggregation ofservices

-Naturalselection andevolutionamongservices

-Examplemashups, opendata and APIs,HTML5

Extent of organizational change and ICT exploitation

Businessbenefits

Adapted from Nachira, F. et. al. (2002)

© Sakari Luukkainen

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Value network Business ecosystem

Structure Organized by one actor,reasonably static

Self-organizing, dynamic

Competition andcooperation

Cooperation Both simultaneously

Role of end users Passive Active role in selectingservices and thus actors in theecosystem

Knowledge Sharing limited tooperational information

Openness of the technologyplatform as the motivator ofcooperation

Control One powerful actor Decentralized decision making

Entry barriers High Low

Managing a value network• Search for consensus with complementors about technical

standards and how they interface with platforms

• Consensus needs to be forged by one company driving theprocess

• Platform leaders should be industry enablers, they shouldhelp others innovate in better ways around the platform

• Platform leaders should not unnecessarily step out of theirsystem boundaries into that of their complementors

• Leaders can reduce external tensions by acting on behalf ofthe entire industry

© Sakari Luukkainen

24

Amazon’s value network

© Sakari Luukkainen

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• Relatively stable• Contractual agreements• Dominant player controls• Physical goods require

expertise in logistics andinventory management

Network Operators/ ISPs

End users

Developers

Data / ServiceProviders

Amazon

Advertisers

AffiliatesVendors

Amazon.com Value NetworkArto Kettula (2009)

Business ecosystems

© Sakari Luukkainen

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dynamic structure which consists ofinterconnected population oforganizations

unclear borders ..

is self-sustaining ..

experimentation…

develops through self-organization,emergence, co-evolution …

contains competition and cooperationsimultaneously

combined knowledge and capabilities Characteristics of business ecosystem.Mirva Peltoniemi (2005)

Dynamics

Coupled withchanging

environment

Businessecosystem

Large numberof participants

Interconnectedness

Interaction

Competition andcooperation

Shared fate

Conscious choice

Aims at innovationsand commercial

success

Open mashup ecosystem

© Sakari Luukkainen

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• Developers make highly customized services which would beunprofitable to create for the API provider

• Combining data from multiple sources allows the developers tocreate more valuable and innovative services for end users

• High level of usage of open source software, data and platforms• Reusing existing services enables faster service development• API providers gain visibility for their brands and more traffic to

their main sites• Brokers decrease switching costs between developers and API

providers

Long Tail of Mobile Services

© Sakari Luukkainen

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IIIOpen Ecosystem

IIApp stores

Serv

ice

Rev

enue

s

AppStore

IOperator services

Number ofServicesCall & Share

Mobile Email

BusinessServices

Voice SMS/MMS

PoC

Mobile TVHomeEntertainment

Windows phonemarket Google Play

Ringtones

APIs, mashup, HTML5

29.1.2013© Sakari Luukkainen

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ICT innovation growth - summaryN

umbe

rofU

sers

Time

Network effectsEconomies of scale – lower cost/priceTwo-sided networks

Switching costs

Revolution - evolution

Value network - ecosystem

Latent needs - Market uncertainty

Critical mass

Cost of changes

Degrees of freedom

Experimentation – innovators - differentiation

Early adopters / majority

Complementarity – virtual networks

Installed base

Dominant design

Technology competition – virtuous cycle

Openness - control

Next time

• Business model design (e.g. STOF model)• 1st half of the exam book

© Sakari Luukkainen

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