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: vuong@cs.ubc.ca or stvuong@gmail.com

Hoi Thao ve TMDT, DH Kinh Te Luat

HCMC, 30/11/2012

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Prof. Dr. Son Vuong’s Bio Sketch 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.

Outline

1. M-Commerce: Introduction

2. Key Issues/Concerns

3. LIVES as applied to M-Commerce

4. Video Clip.

5. Conclusions

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A Bird-Eye View of M-Commerce

Mobile Commerce (M-Commerce)

A form of e-commerce

performed on the internet using wireless

devices such as

Handheld computers (tablets), cell phones

(smartphones), dashtop computers (embedded in

automobile dashboards)

Presents unique opportunities and challenges

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Popular M-Commerce Uses

Mobile Banking

Mobile stock trading

Mobile ticketing

Digital Wallet

Mobile Coupon

M-Commerce Value

Convenience

Anytime and anywhere access

Personalization and localization

Flexibility

Ubiquity

Who is using it?

USA, Canada

Europe (France, Austria, Germany, Finland, United Kingdom, etc.)

Asia (Japan, etc.)

Now, worldwide (China, etc. )

M-Commerce Hurdles

Technical Challenge

Security and Privacy

Demography

Usability

Governmental policies and regulations

M-Commerce Hurdles (in the past)

Screens too small and difficult to read

Slow internet speeds

Difficult text entry

Cost of mobile services

The Mega Trends for Internet

Information Time

Level of In

tera

ction

Interaction

Content

User

Individual Metcalfe Law (n2)

User Generated

Content

Connected Group Reed Law (2n)

Smart

Content

? ?

0 50 Years

107 Computers 108 Vehicular telemetric 109 Residential & commercial buildings 1010 Industrial automation 1011 Shipping logistics 1012 Consumer products

The End State of Connectivity

Ubiquity and Mobility

Connected Mobility 24/7

200 Millions

(5B

downloads)

3 Billions

Connected Devices

Tablet and Smartphone

Laptop and Cellphone

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

Anything that can be connected

will be connected

Mobile Broadband Landscape

Cellular Wireless Law of Speed vs. Decade

30 Years

1G

2G

3G

4G

5G

Mbps

kbps

bps

Mbps

kbps

bps

Gbps

2020 2010 2000 1990 1980

AMPS

?

AMPS

? Cell size shrinks Cell

count increases

1

4

16

50

Mobile device

for everything

Time

10G

100G

1T

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E-Commerce Business Model

E-Commerce: Business Models Issues

Possible Models: 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

Methods for delivering M-Commerce services

Directly from cell phone service providers

Via mobile Internet or Web applications

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

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Kinds of business models

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

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

Production Mass Personalized

Manufactures push Customer Pull

Distribution Middleman Direct

Communications Closed Open

Finance Slow Fast

Difficult Easier

Markets Local Global

Mass Niche

Assets Physical Virtual

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Consumer Decision Process

Disposal

Loyalty

Satisfaction

Purchase Decision

Evaluation of Alternatives

Information Search

Problem - Recognition

PRE-PURCHASE

PURCHASE

POST-PURCHASE

Consumer Decision Process

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Consumer Decision Process — Flower

Example Flowers

Disposal

Loyalty

Satisfaction

Purchase Decision

Evaluation of Alternatives

Information Search

Problem - Recognition

Pre-Purchase

Purchase

Post-

Purchase

Need recognition, potentially triggered by a

holiday, anniversary or everyday events

Search for ideas and offerings, including:

– Available on-line and off-line stores

– Gift ideas and recommendations

– Advice on selection style and match

Evaluation of alternatives along a number of

dimensions, such as price, appeal, availability, etc.

Purchase decision

Message selection (medium and content)

Post-sales support

– Order tracking

– Customer service

Education on flowers and decoration

Post sales perks

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Metrics

Response times

Site availability

Download times

Timeliness

Security and privacy

On-time order

fulfillment

Return policy

Navigability

Measures of performance; may be quantitative

or qualitative

Metrics: If it moves, measure it!

Some Specific M-Commerce Issues

1. Electronic Payment System (Smartcards)

2. Marketing/Advertisement and Hospitality

(LIVES)

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Electronic Payment System • proximity payment system

– allows customers to transfer funds wirelessly between their mobile device and a point-of-sale terminal

• Electronic cash (e-cash or digital cash) – Provides a private and secure method of transferring funds from

a bank account or credit card to online vendors or individuals

– PayPal • Best-known e-cash provider

• E-cash benefits – Privacy - hides account information from vendors

– Convenient if seller cannot process a credit card

• Smartcards – Credit cards with embedded microchips that can store and

process data and can be used as electronic wallets

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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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Learning Through Mobile Technologies

http://lives.cs.ubc.ca

Dr. Son Vuong

LIVES Mobile Corp.

Spin-off from University of British Columbia

LePlaza: A Location-Based Social Network System = Facebook + Lattitude (Google) • Location–based • Distance-based search • Event-centered with Location Based Personalized

Recommendation Service (dining recommendation)

LePlaza

EVENT

LePlaza – Location-based recommendation

Visions on M-commerce

Is it happening?

Will it meet expectations?

Predicted to boom !?

M-Commerce Future Will succeed as part of an integrated business

model.

Will not replace traditional commerce but will complement it. New business via mobiles.

New way of marketing, customer care (hospitality)

Will most likely be successful with small transactions rather than big ticket items Ring tones

Games

Food

Media

M-Commerce Future

Likely to succeed if

Internet speeds are increased

Text input becomes more convenient

e.g. Voice activated

Security concerns are addressed

Payment systems become more convenient

Younger generation most likely to adapt

As proliferation of people (farmers) becomes

exposed to Internet and Web access.

They believed it… (Schoemaker, 1995)

Thomas J. Watson, chairman of IBM, 1943

“I think there is a world market for about five computers”

Ken Olson, President, Digital Equipment Corporation, 1977

“There is no reason for any individual to have a computer in their home”

The best way to predict the

future is to invest it

Questions and Discussions