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
2
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
3
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
4
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
LevelofInteraction
Interaction
Content
User
Individual
Metcalfe Law (n2)
User Generated
Content
Connected Group
Reed Law (2n)
Smart
Content
??
0 50 Years
107 Computers108 Vehicular telemetric109 Residential & commercial buildings1010 Industrial automation1011 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
20202010200019901980
AMPS
?
AMPS
? Cell size shrinks Ce
count increases
1
4
16
50
Mobile device
for everything
Time
10G
100G
1T
14
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
16
17
Kinds of business models
 Brokerage: market makers bring together
buyer and sellers
 Advertising: web advertising providing
advertising messages
 Infomediary: collecting and disseminating
information
18
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
19
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
20
Consumer Decision Process
Disposal
Loyalty
Satisfaction
Purchase Decision
Evaluation of Alternatives
Information Search
Problem - Recognition
PRE-PURCHASE
PURCHASE
POST-PURCHASE
Consumer Decision Process
21
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
22
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)
23
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
24
25
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) 1
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

A bird eye view of m-commerce Vương Thanh Sơn

  • 1.
    A Bird-Eye Viewof M-Commerce Prof. Dr. Son Vuong Director, Networks and Internet computing Laboratory (NICLab) Computer Science Department University of British Columbia Vancouver, BC Canada Email: [email protected] or [email protected] Hoi Thao ve TMDT, DH Kinh Te Luat HCMC, 30/11/2012
  • 2.
    2 Prof. Dr. SonVuong’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.
  • 3.
    Outline 1. M-Commerce: Introduction 2.Key Issues/Concerns 3. LIVES as applied to M-Commerce 4. Video Clip. 5. Conclusions 3 A Bird-Eye View of M-Commerce
  • 4.
    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 4
  • 5.
    Popular M-Commerce Uses Mobile Banking  Mobile stock trading  Mobile ticketing  Digital Wallet  Mobile Coupon
  • 6.
    M-Commerce Value  Convenience Anytime and anywhere access  Personalization and localization  Flexibility  Ubiquity
  • 7.
    Who is usingit?  USA, Canada  Europe (France, Austria, Germany, Finland, United Kingdom, etc.)  Asia (Japan, etc.)  Now, worldwide (China, etc. )
  • 8.
    M-Commerce Hurdles  TechnicalChallenge  Security and Privacy  Demography  Usability  Governmental policies and regulations
  • 9.
    M-Commerce Hurdles (inthe past)  Screens too small and difficult to read  Slow internet speeds  Difficult text entry  Cost of mobile services
  • 10.
    The Mega Trendsfor Internet Information Time LevelofInteraction Interaction Content User Individual Metcalfe Law (n2) User Generated Content Connected Group Reed Law (2n) Smart Content ?? 0 50 Years 107 Computers108 Vehicular telemetric109 Residential & commercial buildings1010 Industrial automation1011 Shipping logistics 1012 Consumer products
  • 11.
    The End Stateof Connectivity Ubiquity and Mobility Connected Mobility 24/7 200 Millions (5B downloads) 3 Billions
  • 12.
    Connected Devices Tablet andSmartphone Laptop and Cellphone The Rise of Mobile Broadband To enable x10 (speed) x10 (devices) x10 (industries) Anything that can be connected will be connected
  • 13.
    Mobile Broadband Landscape CellularWireless Law of Speed vs. Decade 30 Years 1G 2G 3G 4G 5G Mbps kbps bps Mbps kbps bps Gbps 20202010200019901980 AMPS ? AMPS ? Cell size shrinks Ce count increases 1 4 16 50 Mobile device for everything Time 10G 100G 1T
  • 14.
  • 15.
    E-Commerce: Business ModelsIssues  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
  • 16.
    Types of M-CommerceApplications  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 16
  • 17.
    17 Kinds of businessmodels  Brokerage: market makers bring together buyer and sellers  Advertising: web advertising providing advertising messages  Infomediary: collecting and disseminating information
  • 18.
    18 Assessing a businessmodel  Can be assessed by looking at the marketing strategy  Can also be assessed by technology - imitation - complementary assets  Financial measures  Competitor benchmarking  Market analysis
  • 19.
    19 Traditional vs. NewBusiness 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
  • 20.
    20 Consumer Decision Process Disposal Loyalty Satisfaction PurchaseDecision Evaluation of Alternatives Information Search Problem - Recognition PRE-PURCHASE PURCHASE POST-PURCHASE Consumer Decision Process
  • 21.
    21 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
  • 22.
    22 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!
  • 23.
    Some Specific M-CommerceIssues 1. Electronic Payment System (Smartcards) 2. Marketing/Advertisement and Hospitality (LIVES) 23
  • 24.
    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 24
  • 25.
    25 Prof. Dr. SonVuong Networks and Internet Computing Laboratory (NICLab) Computer Science Department University of British Columbia Vancouver, BC CANADA In parnership with the Commonwealth of Learning (COL) 1 Learning Through Mobile Technologies http://lives.cs.ubc.ca
  • 26.
    Dr. Son Vuong LIVESMobile Corp. Spin-off from University of British Columbia
  • 29.
    LePlaza: A Location-Based SocialNetwork System = Facebook + Lattitude (Google) • Location–based • Distance-based search • Event-centered with Location Based Personalized Recommendation Service (dining recommendation)
  • 30.
  • 31.
  • 32.
    Visions on M-commerce Is it happening?  Will it meet expectations?  Predicted to boom !?
  • 33.
    M-Commerce Future  Willsucceed 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
  • 34.
    M-Commerce Future  Likelyto 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.
  • 35.
    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”
  • 36.
    The best wayto predict the future is to invest it 
  • 37.