Syllabus
Fall Semester
F1. Customer Relationship Management
This course provides a variety of strategies, applications, tools and techniques of Customer Relationship Management (CRM) proposed
to different businesses for success in the social media in a coherent, conceptual framework.
F2. Business Research Method
This course introduces the fundamental theory of business research, and demonstrates the use of research models with case study
and statistics analysis software SPSS. Students will be able to develop abilities in business research. They also can make research analysis, plan and policy in business.
F3. International Marketing Issues
This course introduces the fundamental theory of international marketing, and demonstrates the use of marketing models
with case study. It also has a team project presentation in final class. Students will be able to develop abilities in international
marketing. They also can make marketing analysis, plan and policy in business.
F4. Research Development Management
This course is intended to introduce the concepts and principles for effective R&D management that are becoming the crucial
competitive advantages for the technology-based business. The course will introduce some related cases and issues to bridge
the national, industrial and corporate R&D activities, along with the presentation of selected approaches, methods and tools to
effectively integrate functional, business and corporate R&D and innovation activities as a whole.
F5. Science and Technology Management
This course mainly introduces the basic concepts of science and technology management, innovation management and the related
industry issues. We would like to help students to understand the value and application of science and technology through lecture
and case study. Further in this course, students may establish the fundamental and essential concept of science and technology
management. The purpose of this course is to guide students understanding the importance of management in developing science and technology.
F6. Data Mining and Enterprise Applications
The goal of this course is to provide students with the core data mining concepts and practical skills for applying data mining
techniques to solve real-world problems. This course presents the main methods of data mining including association rules,
classification and prediction, cluster analysis. Issues regarding enterprise applications and case studies will also be discussed.
F7. Industrial Technology Foresight: Theory and Practice
- Introduction to core concepts of technology foresight (TF)
- Introduction to fundamental TF approaches
- Domain Scoping
- Ecosystem Analysis
- Trends Analysis & Baseline Scenarios
- The Initiatives
- Force of Change & Alternative Scenarios (AS)
- The AS Signposts
- Ideation & Vision Map
- Vision Network & Backcasting
- Preferable Scenarios and the Related Signposts
- Technology Deep Dive
- Initiatives and Signposts Determination
- Strategic Actions & TF Refresh
F8. Seminar of Emerging Management Topics
The related emerging topics include but not limited to the following issues:
1. Service Science & Service Innovation
2. New methods for Operation Research
3. Internet Marketing
4. Electronic Commerce
5. Knowledge Management
6. Business Applications of Big Data & AI
7. Project Management
8. Information Professionals Management
F9. International Finance
This course will be divided into three sections. First, we will develop a feeling for the way that the international financial
markets work, especially the flow of funds across borders and the determination of exchange rate. Second, we will focus
on fundamental (absence of arbitrage) relationships involving exchange rates and applicable derivative securities.
Third, we will focus on the management of exchange rate exposure and interest rate risk. Various hedging strategies will be introduced and evaluated in this section.
Spring Semester
S1. Multivariate Analysis
This course is to make statistics a “easier and Interesting” subject by introducing the various multivariate techniques to students
used in businesses field without hard mathematical derivations. The main emphasis is on when to use the various data analytic
techniques and how to interpret the resulting output obtained from the most widely used statistical packages software. Finally,
we make a statistical decision.
S2. Consumer Behavior Analysis
The course introduces a wide range of behavioral concepts, and explores the strategic implications of customer behavior
for marketers. The course challenges students to explore the realities and implications of buyer behavior in traditional
and e-commerce markets. Key to the course is demonstrating how an understanding of buyer behavior can help to improve strategic decision making.
S3. Investment Management
This course covers the basics of investments. Broad topics include financial markets, time value of money, asset valuation,
investments portfolio. This course will help you understand the finance subject of study better. Those interested in finance
will later be able to direct their interests towards more specialized finance classes. Others will be able to handle the financial
issues faced in their everyday life in a more educated way. By the end of the semester, you will learn how to apply basic
mathematical and statistical knowledge to finance problems. Since finance is an inevitable part of our lives, it is important
to keep up with what’s going on. Current financial information is readily available online and you are encouraged to read them on a regular basis.
S4. Introduction to Data Analytics with Application in Software
Students will be introduced to the latest data analytics tools and techniques, which include, but are not limited to, R, PLS.
In this course, we will be discussing the latest business analytics concepts and techniques along with advances in Data
Science and its applications in various research fields. Background in related studies including probability & statistics, MIS research, predictive analytics,
S5. Advanced Algorithms
This course mainly introduces advanced concept and applications of algorithm. Algorithm is the core base of modern computers. Applications for system control, multi-media, decision making support, FinTech, AR/VR, autonomous vehicles, machine learning and AI all need well designed algorithms. The course includes history of algorithm development, algorithm complexity, classical and advanced algorithms, and modern applications of algorithm. The algorithms for modern machine learning are also included. It is good for students who have basic concepts and experience of computer programming.
S6. Econometric Model Method
The purpose of this course is to provide students with fundamental knowledge on quantitative methodology.
The topics include fundamentals of regression analysis, internal and external validity of regression, regression with panel data and with a
binary dependent variable, instrumental variables regression, and an introduction to time series regression.
S7. Seminar on Financial Management
This course has three main objectives: 1) Learn ratio analysis and DuPont identity that are used to work with financial statements of a company. 2)
Understand the basic issues involved in how company do long-term financial planning and growth. 3)
Explore capital budgeting techniques to evaluate company’s investment project considering operating and financial risks.
Reports writing and oral presentation are required when applying these techniques to a real listed company.