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A bird eye view of m-commerce Vương Thanh Sơn


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A bird eye view of m-commerce Vương Thanh Sơn

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A bird eye view of m-commerce Vương Thanh Sơn

  1. 1. 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
  2. 2. 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.
  3. 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. 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. 5. Popular M-Commerce Uses  Mobile Banking  Mobile stock trading  Mobile ticketing  Digital Wallet  Mobile Coupon
  6. 6. M-Commerce Value  Convenience  Anytime and anywhere access  Personalization and localization  Flexibility  Ubiquity
  7. 7. Who is using it?  USA, Canada  Europe (France, Austria, Germany, Finland, United Kingdom, etc.)  Asia (Japan, etc.)  Now, worldwide (China, etc. )
  8. 8. M-Commerce Hurdles  Technical Challenge  Security and Privacy  Demography  Usability  Governmental policies and regulations
  9. 9. M-Commerce Hurdles (in the past)  Screens too small and difficult to read  Slow internet speeds  Difficult text entry  Cost of mobile services
  10. 10. 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
  11. 11. The End State of Connectivity Ubiquity and Mobility Connected Mobility 24/7 200 Millions (5B downloads) 3 Billions
  12. 12. 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
  13. 13. 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. 14. 14 E-Commerce Business Model
  15. 15. 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
  16. 16. 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. 17. 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. 18. 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. 19. 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. 20. 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. 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. 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. 23. Some Specific M-Commerce Issues 1. Electronic Payment System (Smartcards) 2. Marketing/Advertisement and Hospitality (LIVES) 23
  24. 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. 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
  26. 26. Dr. Son Vuong LIVES Mobile Corp. Spin-off from University of British Columbia
  27. 27. 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)
  28. 28. LePlaza EVENT
  29. 29. LePlaza – Location-based recommendation
  30. 30. Visions on M-commerce  Is it happening?  Will it meet expectations?  Predicted to boom !?
  31. 31. 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
  32. 32. 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.
  33. 33. 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”
  34. 34. The best way to predict the future is to invest it 
  35. 35. Questions and Discussions