Study Programmes 2017-2018
GEST3032-1  
eBusiness and eCommerce
Duration :
30h Th
Number of credits :
Master in data science (120 ECTS)5
Master in data science and engineering (120 ECTS)5
Master in management (120 ECTS)5
Master in business engineering (120 ECTS)5
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@