2023-2024 / GEST3032-1

eBusiness and eCommerce

Duration

30h Th

Number of credits

 Master of Science (MSc) in Data Science5 crédits  
 Master of Science (MSc) in Data Science and Engineering5 crédits  
 Advanced Master in Tax Law5 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

Schedule

Schedule online

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 the course focuses on methods and techniques, which are at the crux of e-commerce and digital marketing.These include:

  • Recommender system for personalised product recommendations
  • Link analysis for social network analytics
  • Clustering for customer segmentation 
  • Mining association rules for market basket analysis
The course also comprises of a practical component. Specifically, there will be 2 projects. The first one will require the development of a simple, but comprehensive, e-commerce website. It will include the backend (server-side and database) and front-end (UI). Participants will be exposed to PhP/MySQL and WordPress. The second project will involve the profiling of onlie suppliers using web scarpping. This latter exercice could help custom officers in having a better overview of the characteristic of online traders/suppliers.

Furthermore, if time permits, course participants will have to read and present a scientific article in the area of e-commerce.  A  selection of articles will be made available. Representative topics include ranking methods of search engine, deep learning for recommender systems, evaluating recommender systems, and centrality measures.


Course Structure and Topics

1. Market Basket Analysis:   

  • Apriori algorithm for association
  • Strengths and weaknesses
  • Comparison with sequential pattern mining
 

2. Advertising on the web (AdWords): 

  • Greedy, online algorithms
  • Maximal matching problem
  • Competitive ratios of algorithms
 

3. Recommender systems: 

  • Content-based filtering
  • Collaborative filtering
  • Methods for product/user similarity estimation (cosine distance, Pearson correlation)
 

4. Clustering for Market Segmentation

  • Partitional algorithms (K-means, bisecting K-means)
  • Hierarchical algorithms (AHP)
  • Methods for similarity estimation (Euclidean distance, cosine, complete link,...)
  • Strengths & weaknesses of various clustering methods
  • Data pre-processing & normalisation
  • Demo
 

5. Social Network Analysis

  • Fundamental concepts (centrality, graphs, matrices,...)
  • Methods for estimating centrality (betweenness, in/out degree, eigen vector)
  • Shortest path algorithms (Floyd-Warshall) Partitional algorithms (K-means, bisecting K-means)
 

Practical1:

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)

AJAX/JQuery for responsive UI

Introduction to WordPress

 

Practical2:

Either market basket analysis (Apriori algorithm) or customer segmentation (K-Means algorithm)

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.
  • Critically appreciate the technical architecture of e-commerce applications/websites

Prerequisite knowledge and skills

Students should be well-versed in

  • Programming and databases. Students should have programming experience for the project, even if practical sessions will be organized and help sessions will be planned.

Planned learning activities and teaching methods

Course notes and supplementary materials will be made available to the participants.
 
Course participants will create an e-commerce website. They can use either PhP/MySQL or a CMS like Wordpress. In addition, they will have to construct the profile of a selection of online traders using webscrapping tools.
 

Mode of delivery (face to face, distance learning, hybrid learning)

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

Recommended or required readings

  • Lecture notes, including HTML and PhP for the practical, will be available on Lol@
  • List of scientific articles to be made available on lol@

Exam(s) in session

Any session

- Remote

written exam AND oral exam

Written work / report

Continuous assessment


Additional information:

Project: E-Commerce website: 25%
Project: Trader's Profiling: 25%
Paper presentation: 5% 
Final written exam: 45% (The above is tentative and will be finalized during the course)

Work placement(s)

Organisational remarks and main changes to the course

Contacts

A. Ittoo, ashwin.ittoo@uliege.ac.be
E. Heins, eddy.heins@uliege.be
  
 

Association of one or more MOOCs

Items online

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