IMMC-QEF Teachers & Students Workshop
Mathematical Modeling in Business and Management
Date: 28 Mar 2020         Using ZOOM

Dr. Jingqi WANG
Associate Professor, Business School, The University of Hong Kong
https://www.fbe.hku.hk/people/academic/jingqi-wang

Email: jingqi@hku.hk

Research Interests: 
Empirical Studies in Operations Management, Technology Supply Chains, Innovation in Supply Chains.

We have invited Associate Professor Wang Jingqi from the University of Hong Kong to give a workshop on "Teacher Workshop- Applications of Mathematical Modeling in Business and Management" to demonstrate the usefulness of mathematics (modeling) with examples of business applications.


Dr. Wang first mentioned why we should use mathematics to help make decisions as an introduction, and then he entered the main content. He first talked about the concept of regression methods, such as the relationship between variables in the regression method, and the purpose of the regression method: 
1. Understanding the relationship between variables 
2. Predicting the next variable based on previous variables deal with. He also introduced two regression analysis methods, linear and multiple regression.


Besides the theory, DR. Wang also demonstrated how to use Excel for regression analysis. In addition, he mentioned the problems that regression analysis may encounter, such as Multicollinearity, and what is a good regression analysis model.


In the second part, Dr. Wang explained in detail the mathematical model commonly used in resource allocation called linear programming. Similarly, he also explained how to use Excel to deal with linear programming problems and used examples step by step to make the teacher more clear about the process.


Dr. Wang continued to explain different methods and problems, including "Modeling with 0-1 Variables", "Shortest Path Problem" and "Monte Carlo Simulation" and other problems and methods with examples to give a very detailed introduction and discussion in the application of mathematical modeling on business problems.