A bird eye view of m commerce vương thanh sơn

A Bird-Eye View of M-Commerce
Prof. Dr. Son Vuong
Director, Networks and Internet computing Laboratory (NICLab)
Computer Science Department
University of British Columbia
Vancouver, BC Canada
Email: or

Hoi Thao ve TMDT, DH Kinh Te Luat
HCMC, 30/11/2012


Prof. Dr. Son Vuong’s Bio Sketch
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BSEE Cal State U, Sacto, MEng CarletonU, PhD, U. Waterloo
Lecturer/Assistant Professor, U Waterloo, 1980-82
Joined UBC/CS since 1982
Director of Networks and Internet Computing Lab (NICLab)
(Co)Author over 200 papers, Supervise 80 MSc/PhD theses

Co-edited three books, including “Recent Advances in Distributed
Multimedia Systems” published in 1999
Co-Leader of $30M CAD GISST NCE Proposal (2000)
(Co)chair and (Co)organizer of 10 international conferences
(NCAS’11, Multimedia’08, DMS’08, NOMS’06, DMS'97, ICDCS'95,
PSTV'94, FORTE'89, IWPTS'88).
Consultant for the Canadian Government: Department of
Communications (DOC), Department of Industry (DOI)
Board of Directors for companies, including Confederal Networks
(ConfedNet) and LIVES Mobile Corp.

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A Bird-Eye View of M-Commerce

Outline
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M-Commerce: Introduction
Key Issues/Concerns
LIVES as applied to M-Commerce
Video Clip.
Conclusions

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Mobile Commerce (M-Commerce)
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A form of e-commerce

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performed on the internet using wireless
devices such as
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Handheld computers (tablets), cell phones
(smartphones), dashtop computers (embedded in
automobile dashboards)

Presents unique opportunities and challenges


Popular M-Commerce Uses
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Mobile Banking

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Mobile stock trading

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Mobile ticketing

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Digital Wallet

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Mobile Coupon


M-Commerce Value
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Convenience
Anytime and anywhere access
Personalization and localization
Flexibility
Ubiquity

Who is using it?
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USA, Canada
Europe (France, Austria, Germany, Finland,
United Kingdom, etc.)
Asia (Japan, etc.)
Now, worldwide (China, etc. )


M-Commerce Hurdles
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Technical Challenge
Security and Privacy
Demography
Usability
Governmental policies and regulations


M-Commerce Hurdles (in the past)
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Screens too small and difficult to read
Slow internet speeds
Difficult text entry
Cost of mobile services


The Mega Trends for Internet
Interaction

Connected Group
Reed Law (2n)

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Level of Interaction

Individual
Metcalfe Law (n2)

Smart
Content
Content
User

0

Information

User Generated
Content

12 Consumer products
8
9 10
710
11
10
Industrial
Vehicular
telemetric
10
10
Residential
Computers
&
commercial buildings
Shipping automation
logistics

50 Years

Time


The End State of Connectivity
Ubiquity and Mobility

Connected Mobility 24/7

3 Billions

200 Millions
(5B
downloads)


The Rise of Mobile Broadband
To enable x10 (speed) x10 (devices) x10 (industries)
Connected Devices

Tablet and Smartphone
Laptop and Cellphone

Anything that can be connected
will be connected


Mobile Broadband Landscape
Cellular Wireless Law of Speed vs. Decade

1T
100G

5G
10G

4G
Gbps

?

Mobile device
for everything

Cell size shrinks
Ce
count increases

3G

50
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Mbps

2G

kbps

1G

bps

AMPS

4

1

30 Years
1980

1990

2000

2010

2020

Time


E-Commerce Business Model

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E-Commerce: Business Models Issues
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Possible Models:
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Slotting fees
Wireless advertising (text)
Pay per application downloaded
Pay per page downloaded
Flat-fees for service & applications
Revenue share on transactions

Trust issues between banks, carriers, and
portals
Lack of content / services


Types of M-Commerce Applications

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Methods for delivering M-Commerce services
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Directly from cell phone service providers
Via mobile Internet or Web applications
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Location-based m-commerce applications

Using Short Message Service (SMS) text
messaging or Multimedia Messaging Service
(MMS)
Using short-range wireless technology, such as
RFID


Kinds of business models
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Brokerage: market makers bring together
buyer and sellers
Advertising: web advertising providing
advertising messages
Infomediary: collecting and disseminating
information

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Assessing a business model

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Can be assessed by looking at the
marketing strategy
Can also be assessed by technology
- imitation
- complementary assets
Financial measures
Competitor benchmarking
Market analysis
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Traditional vs. New Business Models
Traditional

New Business

Distribution

Mass
Manufactures push
Middleman

Personalized
Customer Pull
Direct

Communications

Closed

Open

Finance

Slow
Difficult
Local
Mass
Physical

Fast
Easier
Global
Niche
Virtual

Production

Markets
Assets

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Consumer Decision Process

Consumer Decision Process
Problem - Recognition

PRE-PURCHASE

Information Search
Evaluation of Alternatives

PURCHASE

Purchase Decision

Satisfaction
POST-PURCHASE

Loyalty
Disposal

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Consumer Decision Process — Flower
Example
Flowers
Problem - Recognition

Pre-Purchase

Need recognition, potentially triggered by a
holiday, anniversary or everyday events

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Search for ideas and offerings, including:
– Available on-line and off-line stores
– Gift ideas and recommendations
– Advice on selection style and match

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Evaluation of alternatives along a number of
dimensions, such as price, appeal, availability, etc.

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Purchase decision
Message selection (medium and content)

Information Search

Evaluation of Alternatives

Purchase

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Purchase Decision

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Post-sales support
– Order tracking
– Customer service

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Education on flowers and decoration
Post sales perks

Satisfaction

PostPurchase

Loyalty

Disposal

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Metrics
 Metrics: If it moves, measure it!
 Measures of performance; may be quantitative
or qualitative
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Response times
Site availability
Download times
Timeliness

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Security and privacy
On-time order
fulfillment
Return policy
Navigability
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Some Specific M-Commerce Issues

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Electronic Payment System (Smartcards)

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Marketing/Advertisement and Hospitality
(LIVES)

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Electronic Payment System
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proximity payment system
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allows customers to transfer funds wirelessly between their
mobile device and a point-of-sale terminal

Electronic cash (e-cash or digital cash)
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Provides a private and secure method of transferring funds from
a bank account or credit card to online vendors or individuals
PayPal
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E-cash benefits
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Privacy - hides account information from vendors
Convenient if seller cannot process a credit card

Smartcards
–

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Best-known e-cash provider

Credit cards with embedded microchips that can store and
process data and can be used as electronic wallets


Learning Through Mobile Technologies

Prof. Dr. Son Vuong

Networks and Internet Computing Laboratory (NICLab)
Computer Science Department
University of British Columbia
Vancouver, BC CANADA
In parnership with
the Commonwealth of Learning (COL)


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