20-751 ECOMMERCE TECHNOLOGY FALL 2003 COPYRIGHT © 2003 MICHAEL I. SHAMOS eCommerce Technology...

20-751 ECOMMERCE TECHNOLOGY

FALL 2003

COPYRIGHT © 2003 MICHAEL I. SHAMOS

eCommerce Technology20-751

Lecture 1: Overview


FALL 2003


Course Administration

• Instructor: Michael Shamos ([email protected])

• Teaching assistant: Jie Hu ([email protected])

• Course web page: through Blackboard or http://euro.ecom.cmu.edu/program/courses/tcr751/official.shtml

• Slides posted on web page the night before lecture• 14 lectures, 4 homeworks, 1 final exam• Grading

– Homework 40% (10% each)– Class participation 10%– Final exam 50%


FALL 2003


Working Together• You may (and should) study together and discuss homework

• You should surf the Web to learn more about course topics

• BUT: ALL WORK YOU SUBMIT MUST BE YOURS ALONE• You must list the names of the people you worked with

• You must give credit for any material that is not yours

• If you need to include material from another source, state exactly where it came from (give URL, etc.)

• DO NOT ATTEMPT TO COPY MATERIAL FROM WEB PAGES AND SUBMIT IT AS YOUR HOMEWORKYou will be caught. Your career will end. Fast.

• Penalties for violation: zero credit, course failure, expulsion

• See University Policy on Cheating and Plagiarism


FALL 2003


What is Commerce?

• Middle French, from Latin commercium, fromcom- (together)+ merc- (merchandise) (1537) “The exchange or buying and selling of commodities on a large scale involving transportation from place to place.”

• Buying and selling ( transactions )• Large scale ( scalability )• Transportation ( supply chain )• Every business process in the world must be

re-engineered: “Can it be made electronic?”

NEED TECHNOLOGYTO SUPPORTALL OF THESE


FALL 2003


Commerce (8000 B.C.)

BUYERFINDS

SELLER

NEGOTIATION

PAYMENT

SALE

DELIVERY

POST-SALEACTIVITY

SELECTIONOF GOODS

INFORMATION

PHYSICAL+INFORMATION


FALL 2003


eCommerce

BUYERFINDS

SELLER

NEGOTIATION

PAYMENT

SALE

DELIVERY

POST-SALEACTIVITY

SELECTIONOF GOODS

SEARCH ENGINE

SHOPPING BOT

AGGREGATOR

ON-LINE CATALOG

AUTOMATED AGENTS

TRACKING AGENT

ON-LINE HELP

INTERNET TELEPHONY

CUSTOMER PREFERENCES

BARGAINING STRATEGIES

PRICE SENSITIVITIES

CREDIT/PAYMENT INFORMATION

ON-LINE PROBLEM REPORTS

FOLLOW-ON SALES OPPORTUNITIES

SOME TECHNOLOGIES USED: SOME INFORMATION GATHERED:

BROWSING BEHAVIOR

DELIVERY REQUIREMENTSE-PAYMENT SYSTEMS

CONFIGURATOR

RECOMMENDER AGENT

TRANSACTION PROCESSOR

DATA INTERCHANGE

CRYPTOGRAPHY

BROWSER SHARING

MARKET BASKET

PERSONAL DATA

CUSTOMER SATISFACTION

SEARCH BEHAVIOR

EFFECTIVENESS OF PROMOTIONS

INFORMATION

PHYSICAL+INFORMATION

Voice(IVR, ACD)

Voice(IVR, ACD)

E-MailE-Mail

Direct Interaction

Direct Interaction

SalesAuto.SalesAuto.

MarketingAuto.

MarketingAuto.

Mobile Sales(Prod. CFG)

Mobile Sales(Prod. CFG)

FieldServiceField

Service

Portal/Portal/ExtranetExtranetPortal/Portal/

ExtranetExtranet

EDIEDIEDIEDI

E-MailE-MailE-MailE-Mail

Financ.DM

Financ.DM

HRDMHRDM

Prod.DM

Prod.DM

DWDW

Closed-Loop Processing(EAI Toolkits, ETLM Tools, Embedded Mobile Agents)

Closed-Loop Processing(EAI Toolkits, ETLM Tools, Embedded Mobile Agents)

Cust.DM

Cust.DM

OrderDM

OrderDM

S2SS2SS2SS2S

Co

llab

ora

tive

SC

M

Co

llab

ora

tive

CR

M

Operational

SCMSCM ERPERP CRMCRM

Conf.Conf.

WebStorefront

WebStorefront

Collab.Collab.PlanningPlanningCollab.Collab.

PlanningPlanning

Conf.Conf.Conf.Conf.

Mfg.Mfg.Exec.Exec.Mfg.Mfg.

Exec.Exec.

WHWHMgmt.Mgmt.

WHWHMgmt.Mgmt.

Trans.Trans.Mgmt.Mgmt.Trans.Trans.Mgmt.Mgmt.

Demand Demand PlanningPlanningDemand Demand PlanningPlanning

Trans.Trans.PlanningPlanningTrans.Trans.

PlanningPlanning

Distrib.Distrib.PlanningPlanningDistrib.Distrib.

PlanningPlanning

SupplySupplyPlanningPlanningSupplySupply

PlanningPlanning

Mfg.Mfg.PlanningPlanning

Mfg.Mfg.PlanningPlanning

KM/CMKM/CM

Analytical

Svc.Auto.Svc.Auto.

LogisticsLogisticsLogisticsLogisticsHRHRHRHRMfg.Mfg.Mfg.Mfg. FinanceFinanceFinanceFinance

EmployeeEmployeeSystemsSystems

EmployeeEmployeeSystemsSystems

Industry-Industry-Specific Specific SolutionsSolutions

Industry-Industry-Specific Specific SolutionsSolutions

Strategic Strategic PlanningPlanningStrategic Strategic PlanningPlanning

LegacyLegacySystemsSystemsLegacyLegacy

SystemsSystems

Employee Employee SSSS

Employee Employee SSSS

Fact. HH Fact. HH DevicesDevices

Fact. HH Fact. HH DevicesDevices

ProductProductMgmt.Mgmt.

ProductProductMgmt.Mgmt.

OrderOrderMgmt.Mgmt.OrderOrderMgmt.Mgmt.

Web/Web/IntranetIntranet

Web/Web/IntranetIntranet

SOURCE: META GROUP

THE ELECTRONIC ENTERPRISE

ACD = AUTOMATIC CALL DISTRIBUTORCFG = CONFIGURATIONDM = DATA MININGDW = DATA WAREHOUSEETLM = EXTRACT, TRANSFORM, LOAD & MANAGEHH = HAND-HELDIVR = INTERACTIVE VOICE RESPONSE

SUPPLY CHAINMANAGEMENT

ENTERPRISE RESOURCEPLANNING

CUSTOMER RELATIONSHIPMANAGEMENT


FALL 2003


Manufacturers

Customers

LogisticsProviders

WholesaleDistributors

Suppliers

LogisticsProviders

ContractManufacturers

VirtualManufacturers

SupplierExchanges Logistics

ExchangesCustomerExchanges

Information Flow

Goods Flow

SOURCE: AMR RESEARCH (2000)

Internet-Connected Supply Chain


FALL 2003


Why eCommerce? Why Now?

• Computers are faster– 1973: 1 million instructions/sec– 2003: 2 billion instructions/sec

• Have more main memory– 1973: 0.125 megabytes– 2003: 512.0 megabytes

• Cost less– 1973: $4,000,000– 2003: $1,000

• Speed/size/cost improvement factor: 32 billion


FALL 2003


Progress of Technology

• Have more disk storage– 1973: 10 MB

– 2003: 120,000 MB (soon 1 terabyte = 1000GB)

• Higher communication speeds– Human speech: 30 bits/sec

– 1973 Modem 300 bits/sec

– 2003 Modem: 56,000 bits/sec

– T1 line: 1,544,000 bits/sec

– DSL (high end) 7,000,000 bits/sec

– Internet 2: 1,000,000,000 bits/sec

– Optical 10,000,000,000,000 bits/sec in 1 fiber (entire U.S. telephone traffic)

IMPROVEMENT: 12000 x

1973-2003IMPROVEMENT:

30 BILLION x


FALL 2003


eCommerce Technology Topics

• Infrastructure • Electronic payments • Wireless • Databases• Web Architecture • Mass personalization, CRM,

Data Mining• Search engines • Privacy Technology• Cryptography • Enterprise Resource Planning • Network security • Intelligent agents

• Data interchange


FALL 2003


eCommerce Infrastructure

• What worldwide structure is required to support eCommerce?

• Network + communications– Required course: Communications and Networking (20-770)

• Machines• Software

– Required course: Core Java for eCommerce (20-753)

• Protocols• Security• Payment

– interface to banking systems


FALL 2003


The Internet

• The fundamental technology linking business and people around the world in less than 1 second– Nothing competes with it

• How does it work?• How big is it?• Who owns it? Who governs it?• How does it grow? How big can it get?• What architecture allows this?• What are the limitations?

• Required course: The Internet (20-755)


FALL 2003


Wireless Technologies & mCommerce

• Can’t get (much) away from radio• Differences between wireless and wired communication• Cells, frequency allocations• Shared medium: SDMA, FDMA, TDMA, CDMA• 1G, 2G, 2.5G, 3G, 4G• Wireless LAN: IEEE 802.11• Bluetooth• WAP, iMode• Universal Wideband (UWB)

• Elective Course: Mobile eCommerce (20-863)


FALL 2003


Web Architecture

SOURCE: INTERSHOP

How are web sites constructed?

TIER 1TIER 2Server

TIER 3Applications

TIER 4Database

Elective Course: eCommerce Web Application Development (20-860)


FALL 2003


Search Engines

• Finding web pages– Crawlers, spiders, bots

• Query interfaces• Retrieval methods

– Indexing– Document ranking– Artificially altering retrieval order

• Document clustering• Multilingual issues• Multimedia retrieval

• Required Course: Web-Based Information Architectures (20-760)


FALL 2003


Cryptography• Secrecy

– Information cannot be used if intercepted

• Authentication– We’re sure who the parties are

• Integrity– Data cannot be altered

• Non-repudiation– Sender cannot deny sending the message

• Cryptography– Symmetric encryption (DES, Rijndael)– Public key cryptosystems (RSA)– Digital signatures & certificates, public key infrastructure (PKI)


FALL 2003


Network Security• Access control

– authorization / authentication• Authentication

– something you know: passwords– something you have: smart card– something you are: biometrics– someplace you are: GPS

• Network protection, firewalls, proxy servers• Intrusion detection• Denial of service (DOS) attacks• Viruses, worms

• Required course: Computer Security


FALL 2003


Data Interchange

• How can sites exchange information without prior agreement?– What do the data fields mean? price, extended price, unit

price, prix, цена, τιμή, 가격 , X’AC12’

– XML: Extensible Markup Language

• How can machines communicate without humans?• How can data formats and structures be

communicated?– XML schemas– Ontologies


FALL 2003


eCommerce Data Exchange Needs

Ship Notices

Bills of Lading Electronic Payments

Purchase Orders

Invoices

RFQs Catalogs Quotations

Letters of Credit


FALL 2003


Electronic Payments• Forms of money

– token (cash), notational (bank account), hybrid (check)

• Credit-card transactions– Secure protocols: SSL, SET

• Automated clearing and settlement systems– PayPal

• Smart cards, electronic cash, digital wallets

• Micropayments

• Wireless payments

• Electronic invoice presentment and payment– Moore

• Required course: Electronic Payment Systems (20-763)


FALL 2003


Databases

• The relational database model• Query specification: SQL (Structured Query Language)• Database management• Databases in eCommerce• Data warehousing

• Required course– Database Management (Heinz School)


FALL 2003


Mass Personalization & Data Mining

• Treating each user as an individual– key is INFORMATION

• How to acquire and store information about customers– Cookies– Question and response– Clickstream analysis– External databases. Allegheny County

• How to use information effectively and instantly• Personalization technology• Customization: Lands’ End

http://www2.county.allegheny.pa.us/RealEstate/Search.asp


FALL 2003


Data Mining

• Extracting previously unknown relationships from large datasets

• Discovery of patterns• Predicting the future

– past behavior as predictor of future purchasing• Market basket analysis

– diapers/beer


FALL 2003


Data Mining Tools• Visualization (“seeing” the data) Table Lens• Predictive Modeling• Database Segmentation

– Classify the users

• Link Analysis– Association discovery

• Neural networks– Systems that learn from data

• Deviation Detection– Are any of the data unusual? Fraud detection

• Elective course: Data Mining (20-852)


FALL 2003


Privacy Technology

• Digital privacy & privacy threats• Technology

– P3P– EPAL

• Anonymity– Mediation– Digital pseudonyms


FALL 2003


ERP (Enterprise Resource Planning) & SCM (Supply Chain Management)

• The supply network• Collaboration models

– Vendor-managed inventory– Scan-based trading

• ERP functions and architecture• EAI (Enterprise Application Integration)• Web Services

• Required course: Supply Chain Management 46-866


FALL 2003


Agents and Electronic Negotiation

Programs to perform tasks on your behalf• Avatars (characters in human form) • Metasearchers, shopping bots, news agents, stock

agents, auction bots, bank bots• How to make agents “intelligent”

– Rule-based systems– Knowledge representation

• Agents that learn– Inductive inference

JULIA from CONVERSIVE

Cooperating Agents

Semantic Web

Lucy’s agent retrieves informationabout Mom’s prescribed treatment

from the doctor’s agent.

Lucy’s agent looks up providers,checks for distance, authorization

and rating.Schedule a treatment plan using only authorized providers within a 20-milesand a rating of excellent or very good.

Lucy’s agent formulates a schedule of appointments for therapists thatfits into Pete and Lucy’s schedule.

SOURCE: WILLIAM HOLMES, LOCKHEED-MARTIN

Pete

Lucy

Doctor


FALL 2003


M2M Commerce & Auction Models

• How can machines do business with other machines?• Electronic discovery• Electronic negotiation

– Auction strategy• The semantic Web

• Two elective courses:– Intelligent agents (Katia Sycara) 20-854– Electronic Negotiation (Tuomas Sandholm) 20-853


FALL 2003


QA&

20-751 ECOMMERCE TECHNOLOGY FALL 2003 COPYRIGHT © 2003 MICHAEL I. SHAMOS eCommerce Technology...

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Transcript of 20-751 ECOMMERCE TECHNOLOGY FALL 2003 COPYRIGHT © 2003 MICHAEL I. SHAMOS eCommerce Technology...