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Prentice Hall, 2002 1
(Class5 29.01.02) Information Rules -
Chapter 1: The Information Economy
Shapiro & Varian
modifications by J.Molka-Danielsen
Prentice Hall, 2002 2
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
Prentice Hall, 2002 3
The Information Economy
Carl ShapiroHal R. Varian
Prentice Hall, 2002 4
Systems of Products
Complementary productsHardware/softwareClient/serverViewer/content
Product linesHigh fixed cost, low incremental costLeads to value based pricing
Prentice Hall, 2002 5
Unique Features
ComplementsDifferent manufacturersStrategy for complementors as well as competitorsCompatibility as strategic choiceStandards and interconnection
Product linesLower quality may be more expensive
Prentice Hall, 2002 6
Information
Anything that can be digitizedText, images, videos, music, etc.a.k.a. content, digital goods
Unique cost characteristicsUnique demand characteristics
Prentice Hall, 2002 7
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)
Prentice Hall, 2002 8
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
Prentice Hall, 2002 9
Consumption CharacteristicsExperience good
BrowsingAlways newReputation and brand identity
Overload Economics of attention Hotmail example Broadcast, point-to-point, hybrid
Prentice Hall, 2002 10
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
Prentice Hall, 2002 11
Systems Competition
Microsoft-Intel: WintelIntel
Commoditize complementory chips
MicrosoftCommoditize PCs
AppleIntegrated solutionWorked better, but lack of competition and scale led to current problems
Prentice Hall, 2002 12
Lock-In and Switching Costs
Example: Stereos and LPsCostly switch to CDs
Systems lock-in: durable complements
Hardware, software, and wetwareIndividual, organizational, and societal
Prentice Hall, 2002 13
Network Effects
Value depends on number of usersPositive feedback
Fax (patented in 1843)Internet (1980s)
Indirect network effects Software
Expectations managementCompetitive pre-announcements
Prentice Hall, 2002 14
Compatibility
ExamplesBeta v. VHSSony v. Philips for DVD
Role of 3rd partiesRead v. write standards
Backwards compatibility?Windows 95Windows NT
Prentice Hall, 2002 15
Basic Strategies
Go it alonePartnerships (Java)Formal standard setting
Widespread use Licensing requirements
Competition in a market or for a market?
Prentice Hall, 2002 16
Policy
Understand environmentIP policyCompetition policy
Regulation Antitrust
Electronic commerce Contracts Privacy
Prentice Hall, 2002 17
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
20
30
40
50
60
70
Indo
nesi
a
Ukr
aine
Lith
uani
a
Phi
lippi
nes
Indi
a
Latv
ia
Por
tuga
l
Pol
and
Turk
ey
Arg
entin
a
Hun
gary
Thai
land
Mal
aysi
a
Spa
in
Cze
ch
Italy
Fra
nce
Bel
gium
Japa
n
Est
onia
Gre
at B
ritai
n
Ger
man
y
Irela
nd
Isra
el
Taiw
an
Hon
g K
ong
Fin
land
Sin
gapo
re
Aus
tral
ia
Kor
ea
Net
herla
nds
US
A
Can
ada
Den
mar
k
Nor
way
2001 2000
Pro
sen
t av
den
tot
ale
vok
sne
befo
lkni
ng
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
5
10
15
20
25
30
35P
hili
pp
ine
s
Tu
rke
y
Ind
ia
Th
aila
nd
Arg
en
tina
Hu
ng
ary
Ind
on
esi
a
La
tvia
Lith
ua
nia
Ma
lays
ia
Po
lan
d
Ch
ina
Est
on
ia
Ukr
ain
e
Ho
ng
Ko
ng
Italy
Ta
iwa
n
Be
lgiu
m
Sin
ga
po
re
Sp
ain
Cze
ch
Fra
nce
Po
rtu
ga
l
Isra
el
Fin
lan
d
Jap
an
Au
stra
lia
Ca
na
da
De
nm
ark
Ire
lan
d
Ne
the
rla
nd
s
Ko
rea
No
rwa
y
Gre
at
Bri
tain
Ge
rma
ny
US
A
2001 2000
Pro
sen
t av
Int
ern
ett-
bruk
ara
r
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
2830
41
0
5
10
15
20
25
30
35
40
45
Hu
ng
ary
Lith
ua
nia
Po
lan
d
Po
rtu
ga
l
Th
aila
nd
Es
ton
ia
La
tvia
Ukr
ain
e
Ho
ng
Ko
ng
Be
lgiu
m
Ind
ia
Arg
en
tina
Sin
ga
po
re
Gre
at B
rita
in
Ta
iwa
n
Fin
lan
d
Tu
rke
y
Ma
lays
ia
Ca
na
da
Ind
on
es
ia
Ph
ilip
pin
es
Ch
ina
Isra
el
Italy
De
nm
ark
Sp
ain
Fra
nce
Ne
the
rla
nd
s
No
rwa
y
US
A
Ko
rea
Cze
ch
Ire
lan
d
Au
str
alia
Ge
rma
ny
Jap
an
Pro
sen
t av
Int
ern
ett-
bruk
ara
r
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
Prentice Hall, 2002 28
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.
Prentice Hall, 200237
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?
Prentice Hall, 200238
Consumer Behavior Online (cont.)
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
Prentice Hall, 200239
Consumer Behavior Online (cont.)
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
Prentice Hall, 200240
Personal Characteristics and Demographics of Internet Surfers
Environmental variablesSocial variablesCultural variablesPsychological variablesOther environmental variables
Prentice Hall, 200241
Personal Characteristicsof Internet Surfers
Personal characteristics and differences
Consumer resources and lifestyleAge and genderKnowledge and educational levelAttitudes and valuesMotivationPersonality
Prentice Hall, 200242
Demographics of Internet Surfers
Major demographics presented include
GenderAgeMarital statusEducational levelEthnicityOccupationHousehold income
Prentice Hall, 200243
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
Prentice Hall, 200244
Figure 4-2Amount of Money Spent on the Web
Prentice Hall, 200245
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
Prentice Hall, 200246
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
Prentice Hall, 200247
Table 4-2Purchase Decision Making Process & Support System
Source: O’Keefe and McEachern, 1998.
Prentice Hall, 200248
Figure 4-3 Model of Internet Consumer Satisfaction
Source: Lee (2001)
Prentice Hall, 200249
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
Prentice Hall, 200250
Figure 4-4The New Marketing Model
Source: GartnerGroup
Prentice Hall, 200251
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.
Prentice Hall, 200252
Matching Products with Customers: Personalization (cont.)
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
Prentice Hall, 200253
Matching Products with Customers: Personalization (cont.)
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
Prentice Hall, 200254
Figure 4-5The EC Trust Model
Source: Lee and Turban (2001)
Prentice Hall, 200255
Matching Products with Customers: Personalization (cont.)
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
Prentice Hall, 200256
Matching Products with Customers: Personalization (cont.)
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