E-commerce Success Factors & AI in Business

Posted on Nov 30, 2024 in Other subjects

E-commerce Success Factors

October 28, 2009

1. Selection and Value

Attractive products, competitive prices, guaranteed satisfaction, and customer support after the sale.

2. Performance and Service

Quick and easy navigation, surveys, shopping, and prompt delivery.

3. Look and Feel

Professional web store, designated shopping areas, and a multimedia product catalog with detailed characteristics.

4. Promotions and Incentives

Targeted web page advertising, email promotions, discounts, and special offers.

5. Personalized Attention

Personal web pages, personalized product recommendations, email newsletters, and interactive support.

6. Community Relations

Virtual communication between customers and suppliers.

7. Security and Reliability

Security of customer information and transactions, and reliability of product information.

Web Store Development

A. Building

  • Website design tools
  • Model site projects
  • Standardized services
  • Hosting

B. Marketing

  • On-page advertising
  • Email promotions
  • Advertising exchanges with associated sites
  • Search engine registration

C. Customer Response

  • Customized pages
  • Interactive multimedia catalog
  • Search engines
  • Shopping cart

D. Sales

  • Flexible application case
  • Credit card processing
  • Tax and shipping calculations
  • Email order notifications

E. Support

  • Online help
  • Email customer service
  • Discussion groups
  • Links to related sites

F. Management

  • Usage statistics
  • Sales and inventory reports
  • Client management
  • Links to accounting systems

G. Operations

  • 24/7 operation
  • Online support
  • Scalable network capacity
  • Backup servers and power

H. Security

  • User password protection
  • Encrypted data processing
  • Encrypted website management
  • Firewall and network security monitoring

E-commerce Market Areas

A. One to Many

  • Supply-side
  • Hosting by a major supplier
  • Example: Cisco, Dell

B. Many to One

  • Demand-side
  • Group of suppliers
  • One large buyer
  • Example: GE, AT&T

C. Some to Many

  • Distribution
  • Important suppliers
  • Attracting a group of buyers

D. Many to Some

  • Provision
  • Key customers
  • Attracting suppliers
  • Increased competition/lower prices
  • Example: Covisint (cars), Patritellos (energy)

E. Many to Many

  • Auctions
  • Freemarks

E-business Systems for Decision Making

MIS -> Management Information Systems
DSS -> Decision Support Systems
EIS -> Executive Information Systems

MIS

  • Traditional management support system
  • Generates information products that support many decision-making needs
  • Example: Sales managers -> sales analysis reports
  • Reports, immediate feedback, and consultation

Report Types

  1. Regularly Scheduled: Daily or weekly sales, monthly financial statements
  2. Exception Reports: Reduce information overload. Example: Customers exceeding credit limits
  3. On-Demand Information and Answers: Information available whenever a manager requests it
  4. Push Reporting: Information is pushed to the manager’s computer over the network

Artificial Intelligence Technologies in Business

November 18, 2009

Artificial Intelligence (AI)

Development of computational functions normally associated with human intelligence.

AI has three main areas of application:

Imagen

  • Expert Systems
  • Fuzzy Logic
  • Genetic Algorithms
  • Neural Networks
  • Intelligent Agents
  • Learning Systems
  • Visual Perception

Cognitive Science

  • Research (biology, neurology, psychology, mathematics, etc.)
  • Research on brain functioning, thinking, and learning

A1. Expert Systems

  • Provides answers in specific areas
  • Examples: Medical diagnosis, assembly planning, suspect identification

A2. Neural Networks

  • Simulates neurons
  • Learns to recognize patterns in data processing
  • Software packages simulate neural network activity
  • Examples: Military inventory systems, imaging, voice recognition, credit risk assessment, check and signature verification

A3. Fuzzy Logic

  • Handles ambiguous and approximate values
  • Uses imprecise terminology like “very high growth”, “reasonable”
  • Operates with incomplete data
  • Provides approximate but acceptable solutions
  • Used in Japan
  • Example: Fuzzy SQL – Select companies from finance where revenues are very large and profits are very high.

A4. Genetic Algorithms

  • Simulates an evolutionary process
  • Constructs models
  • Useful in situations with thousands of possible solutions that need evaluation to reach an optimal solution

A5. Intelligent Agents

  • Assists users
  • Graphical representation
  • Example: Office assistants

B. Natural Systems

B1. Virtual Reality

  • CAD
  • 3D Hypermedia
  • High cost