2017-2018 / GEST3032-1

eBusiness and eCommerce

Duration

30h Th

Number of credits

 Master in data science (120 ECTS)5 crédits 
 Master in data science and engineering (120 ECTS)5 crédits 
 Master in management (120 ECTS)5 crédits 
 Master in business engineering (120 ECTS)5 crédits 

Lecturer

Ashwin Ittoo

Language(s) of instruction

English language

Organisation and examination

Teaching in the first semester, review in January

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Course Objectives
This course introduces key concepts and technologies in E-Commerce, E-Business and, more general, Digital Business, to participants.
A relatively wide range of topics will be covered, ranging from those with a marketing orientation (e.g. consumer behavior) to those with a more IT/statistical orientation (e.g. sales prediction, recommender system, link analysis)
It comprises a practical component, requiring the development a simple, but comprehensive, e-commerce website from scratch.
Course Structure and Topics
1. E-Commerce Business Models:  

  • Business model elements
  • Importance of revenue models
  • Types of revenue models (subscription, pay-per-view,...)
 
2. Consumer Behavior: 
  • Consumer behavior model and factors (social, cultural, psychological)
  • Consumer buying process (from problem recognition and information search to post-purchase decision)
  • Online (and offline) tools for supporting consumer behavior
  • Clickstream behavior and analysis
  • Net promotor score (NPS)
  • Online trust
 
3. A/B Testing: 
  • Relevance of A/B Testing in E-commerce applications
  • Chi-squared test for A/B Testing
  • Examples in R and Excel
 
4. Security aspects of E-Commerce/E-Business: 
  • Introduction to data encryptions
  • Security in payment systems
 
5. Linear Regression: 
  • Estimating coefficients
  • Evaluating the model quality (accuracy)
  • Application to a marketing plan
 
6. Link Analysis:
  • Introduction to PageRank
  • Efficient computation of PageRank
  • Topic Sensitive PageRank
 
7. Mining Frequent Itemsets:
  • The Apriori algorithm
 
8. Advertising on the web (AdWords):
  • Greedy, online algorithms
  • Maximal matching problem
  • Competitive ratios of algorithms
  • Adwords implementation
 
9. Recommender systems:
  • Content-based filtering
  • Collaborative filtering
  • Dimensionality reduction
Note: we may not be able to cover all these topics due to time constraints
 
Practical: 
  • Introduction to client-server computing
  • Client-side vs. server side programming
  • PhP programming: Revision (basic constructs: loops, conditionals), database connections, session variables
  • SQL statements (select, update, delete)

Learning outcomes of the learning unit

  • Relate the concepts covered in the lectures to real-world business activities
  • Uncover new business opportunities via the application and implementation of E-Commerce and E-Business concepts and technologies
  • Establish an E-Commerce/E-Business strategy to optimize an organization's activities
  • Communicate efficiently about E-Commerce/E-Business projects to various stakeholders, internal and external to the organizations
  • Perform independent research to keep up-to-date with recent development in the field and to adapt his/her managerial practice to the needs of a fast-evolving world.

Prerequisite knowledge and skills

Students should be well-versed in

  • Programming and databases
  • Vector/matrix algebra
  • Basic probability and statistics 

Planned learning activities and teaching methods

This year, the students will have to create a small E-Commerce Website

Mode of delivery (face-to-face ; distance-learning)

  • Lectures and readings
  • Case studies
  • Demonstrations and exercices on computer
  • Real cases presented by firms (to be determined)

Recommended or required readings

  • Dave Chaffey, "eBusiness and eCommerce Management", 4th or 5th edition, Pearson/Prentice Hall
  • Other materials (lecture note, including HTML and PhP for the practical, will be available on Lol@)

Assessment methods and criteria

Project: E-Commerce website (HTML, PhP): 30% Final written exam:70% (The above is tentative and will be finalized during the course)

Work placement(s)

Organizational remarks

Contacts

A. IttooHEC-ULg, Building N1 (335) ashwin.ittoo@ulg.ac.be

Items online

Lecture Notes
All materials from the lecturer will be on lol@