1 prentice hall, 2002 (class5 29.01.02) information rules - chapter 1: the information economy...

Prentice Hall, 2002 1

(Class5 29.01.02) Information Rules -

Chapter 1: The Information Economy

Shapiro & Varian

modifications by J.Molka-Danielsen


Overview for Class 5

Chapter 1 from Shapiro and VarianGroup 1 Presentation (Nordang, Hovden, Bjerkvik, Tomren)Group 2 Student Presentation (Valderhaug, Golka, Kristensen)Chapter 4 from Tuban (begin 4.2-4.5)

Consumer behavior onlineDemographicsConsumer purchasing decisionMatching products and customers: Personalization


The Information Economy

Carl ShapiroHal R. Varian


Systems of Products

Complementary productsHardware/softwareClient/serverViewer/content

Product linesHigh fixed cost, low incremental costLeads to value based pricing


Unique Features

ComplementsDifferent manufacturersStrategy for complementors as well as competitorsCompatibility as strategic choiceStandards and interconnection

Product linesLower quality may be more expensive


Information

Anything that can be digitizedText, images, videos, music, etc.a.k.a. content, digital goods

Unique cost characteristicsUnique demand characteristics


Cost structure

Expensive to produce, cheap to reproduceHigh fixed cost, low marginal cost

Not only fixed, but sunkNo significant capacity constraints Particular market structures

MonopolyCost leadershipProduct differentiation (versioning)


Rights Management

Low reproduction cost is two-edged sword

Cheap for owners (high profit margin)But also cheap for copiers

Maximize value of IP, not protectionExamples

Library industryVideo industry


Consumption CharacteristicsExperience good

BrowsingAlways newReputation and brand identity

Overload Economics of attention Hotmail example Broadcast, point-to-point, hybrid


Technology

Infrastructure to store, retrieve, filter, manipulate, view, transmit, and receive informationAdds value to information

Web = 1 terabyte of text = 1 million booksIf 10% useful = 1 Borders BookstoreValue of Web is in ease of access

Front end to databases, etc.Currency


Systems Competition

Microsoft-Intel: WintelIntel

Commoditize complementory chips

MicrosoftCommoditize PCs

AppleIntegrated solutionWorked better, but lack of competition and scale led to current problems


Lock-In and Switching Costs

Example: Stereos and LPsCostly switch to CDs

Systems lock-in: durable complements

Hardware, software, and wetwareIndividual, organizational, and societal


Network Effects

Value depends on number of usersPositive feedback

Fax (patented in 1843)Internet (1980s)

Indirect network effects Software

Expectations managementCompetitive pre-announcements


Compatibility

ExamplesBeta v. VHSSony v. Philips for DVD

Role of 3rd partiesRead v. write standards

Backwards compatibility?Windows 95Windows NT


Basic Strategies

Go it alonePartnerships (Java)Formal standard setting

Widespread use Licensing requirements

Competition in a market or for a market?


Policy

Understand environmentIP policyCompetition policy

Regulation Antitrust

Electronic commerce Contracts Privacy


Information is Different…but not so different

Key conceptsVersioningLock-inSystems competition, Network effects

Statistics on eCommerce growthStatistics on eCommerce growth

Gruppe 1Gruppe 1

Nils Einar Nordang, Karl Johan Hovden, Nils Einar Nordang, Karl Johan Hovden, Jan Tore Bjerkvik, Nils Kristian TomrenJan Tore Bjerkvik, Nils Kristian Tomren

Internet Exercise 3, page 35Internet Exercise 3, page 35

eCommerce er veksande, og framtida ser lys ut for e-businesses

• Mellom 2000 og 2001, vil andelen av Internett-brukarar som handlar online øke med 50%. Globalt vil andelen av Internett-brukarar øke frå 10% til 15% .

• Integrert offline og online shopping aktivitetar fører stadig til økte inntjenings-moglegheiter for bedrifter: heile 15% av alle Internett-brukarar har handla offline som et resultat av informasjon dei har funne online.

• Online-sikkerheit er den største bekymringa for brukarar som ikkje har handla online.

• Yngre Internett-brukarar brukar ikkje so mykje pengar som eldre brukarar.

Key numbers 2001...Country average

2001

Country average

2000

Year on year

changeLowest Highest

Internet users 31% 27% + 4% 4% 63%Indonesia Norw ay

Online shoppers 15% 10% + 5% 1% 33%Philappines/

Turkey USA

Online dropouts 15% 15% no change 0% 34%Hungary Korea

Offline shoppers 15% 13% + 2% 0% 31%Hungary Hong Kong

Future online shoppers 17% 14% + 3% 0% 41%Hungary Japan

Prosentvis økning:

Internet brukarar i verden 2000/2001

4 4

911

13 1315 15 16 16 17

19

2426 26

3033 33 33 34

3639 40 40

4345

48 4851 52

5760

62 63

0

10

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30

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Prosentvis andel av befolkninga som personlig har brukt Internett den siste månaden.

Landsgjennosnitt (31%)

Online shoppers 2000/2001

1 12 2

3 3 3 3 34

56 6 6

7 78

9 9 910

1214

1617 17

18 18 18 18 1819 19

24

28

33

0

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Prosentvis andel av internett-brukarar som har kjøpt varer/tenester online den siste månaden

Future online shoppers

0

34 5 5

7 7 79 10 10

11 11 12 12 13 1314 15 15 15

16 16

19 20 2022

23 23 23 2425 26

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Prosent av Internett-brukarar som planlegg å kjøpe dei neste 6 månadane

Country average (17%)

56 %

44 %

Internet user Non user

96 %82 % 78 %

69 %

15 %

69 %57 %

0< 20 20-29 30-39 40-59 60+ Male Female

%

Prosent av befolkninga som bruker Internett

63 %

37 %

Internet user Non user

20002000 20012001

VekstVekst2000 - 12000 - 1

+ 7%

Prosentvis andel av spesifikke aldersgrupper og kjønn som er Internett-brukarar (2001)

Norge

B2B handel

• B2B handel vil i USA auke veldig raskt dei neste 5 åra. Frå $336 billionar i 2000 til $6.3 trillionar i 2005.

• I dag utgjer Online B2B aktiviteter 3 % av det totale markedet, men innan år 2005 vil det utgjere 42%.

B2C handel

• B2C handel over internett utgjorde i år 2000 $ 39 billionar. I løpet av 2003 vil dette tallet auke til $143 billionar. (Forrester Research Inc)

Kjelder:

• Tala er henta frå Taylor Nelson Sofres som er det 4 største foretaket innanfor markedsinformasjon på Internett

• Vi har også henta statistikk frå eMarketer.com


Group 2

Anita Helene Valderhaug, Katrin Elisabeth Golka, Bjørn O. KristensenInternet Exercise 7, page 79.

Packetvideo.com

• The company

• Technology

• Potential use of PVPlatform

• Use of M-commerce

The company

• Exists since 1998

• First company in the world to demonstrate MPEG-4 video images streaming to mobile devices

• Leading Edge Company of the Year 2001

Technology

• PVPlatform including:

-PVAuthor (encoding)

-PVServer (serving)

-PVPlayer (decoding)

• Runs on all wireless systems, e.g. GSM

• PVAirguide

Potential Use of PVPlatform

Transmission of e.g.:

-Financial news and online trading.

- Sports highlights

- SMS/video email

- Movie trailers and tickets

- Multiplayer role-play games

Use of m-commerce

• Targeted Advertisement

• Two-way video communications

• Instant e-commerce

Prentice Hall, 2002

Chapter 4(begin)- 4.2 to 4.5

Internet Consumers, E-Service, and

Market Research

Prentice Hall, 200236

Figure 4-1EC Consumer Behavior Model

Source: Zinezone, c/o GMCI Co.


Consumer Behavior Online (cont.)

Consumer typesIndividual consumers

Commands most of the media’s attention

Organizational buyersGovernments and public organizationsPrivate corporationsResellers Consumer behavior viewed in terms of:

Why is the consumer shopping?How does the consumer benefit from shopping online?



Purchasing types and experiences2 dimensions of shopping experiences

Utilitarian—to achieve a goalHedonic—because it’s fun

3 categories of consumersImpulsive buyers—purchase quicklyPatient buyers—make some comparisons firstAnalytical buyers—do substantial research before buying



Direct sales, intermediation, and customer relations

Companies that sell only through intermediaries still need good relations with the end-usersExample: Ford Motor Company

Do not sell directly to consumersRecognize that drivers of Ford vehicles think of themselves as having a relationship with the company


Personal Characteristics and Demographics of Internet Surfers

Environmental variablesSocial variablesCultural variablesPsychological variablesOther environmental variables


Personal Characteristicsof Internet Surfers

Personal characteristics and differences

Consumer resources and lifestyleAge and genderKnowledge and educational levelAttitudes and valuesMotivationPersonality


Demographics of Internet Surfers

Major demographics presented include

GenderAgeMarital statusEducational levelEthnicityOccupationHousehold income


Demographics of Internet Surfers (cont.)

The more experience people have on the Web, the more likely they are to buy onlineTwo major reasons people do not buy online

SecurityDifficulty judging the quality of the product


Figure 4-2Amount of Money Spent on the Web


Consumer Purchasing Decision Making

Roles people play in decision-makingInitiator—suggests/thinks of buying a particular product or service

Influencer—advice/views carry weight in making a final buying decision

Decider--makes a buying decision or any part of it

Buyer—makes the actual purchase

User—consumes or uses a product or service


Consumer PurchasingDecision Making (cont.)

Purchasing decision-making model5 major phases of a general model

Need identification—actual and desired states of needInformation searchAlternatives evaluation—research reduces number of alternatives, may lead to negotiationPurchase and delivery—arrange payment, delivery, warranties, etc.After-purchase evaluation—customer service


Table 4-2Purchase Decision Making Process & Support System

Source: O’Keefe and McEachern, 1998.


Figure 4-3 Model of Internet Consumer Satisfaction

Source: Lee (2001)


Matching Products with Customers: Personalization

One-to-one marketingRelationship marketing

“Overt attempt of exchange partners to build a long term association, characterized by purposeful cooperation and mutual dependence on the development of social, as well as structural, bonds”

“Treat different customers differently”No two customers are alike


Figure 4-4The New Marketing Model

Source: GartnerGroup


Matching Products with Customers: Personalization (cont.)

Issues in EC-based one-to-one marketingCustomer loyalty—degree to which customer stays with vendor or brand

Important element in consumer purchasing behaviorOne of the most significant contributors to profitability

Increase profitsStrengthen market positionBecome less sensitive to price competitionIncrease cross-selling successSave costs, etc.



Issues in EC-based one-to-one marketingMeeting customers cognitive needs—organize customer service to meet needs of each skill set

NoviceIntermediateExpert

E-loyalty—customer’s loyalty to an e-tailerLearn about customers’ needsInteract with customersProvide customer service



Issues in EC-based one-to-one marketingTrust in EC

Deterrence-based trust—threat of punishmentKnowledge-based trust—grounded in knowledge about trading partnersIdentification-based trust—empathy and common values between partners

Value of EC referralsWord-of-mouthDelivery of good or service sparks other users


Figure 4-5The EC Trust Model

Source: Lee and Turban (2001)



PersonalizationProcess of matching content, services, or products to individuals’ preferencesAlternative methods

Solicit information from usersUse cookies to observe online behaviorUse data or Web mining

Personalization applied throughRule-based filteringContent-based filteringConstraint-based filteringLearning-agent technology



Personalization (cont.)Collaborative filtering examples

Backfilp.com—recommends restaurantsC5solutions.com—personalized messages via cell phonesMysimon.com—assists in purchase decision-making process based on user information

Legal and ethical issuesPrivacy issuesPermission-based personalization tools

1 prentice hall, 2002 (class5 29.01.02) information rules - chapter 1: the information economy...

Documents

prentice hall

varian slide

expensive slide

norge slide

hybrid slide

personalization slide

societal slide

currency slide