"In this course, some frontiers of decision analysis and decision theory are introduced to students. The first part of the course focuses on decision analysis and Excel model building commonly used in decision analysis. We discuss some state of art techniques commonly used in practice by professionals in industry, including decision tree analysis, multi-attribute utility theory, Monte Carlo simulation, risk and sensitivity analysis etc. We focus on illustrating how to apply these techniques in various context of business problems, including valuation of project, real options valuation, and some other real-world problems based on Excel Addins, such as @Risk and PrecisionTree. Teaching notes will be distributed in class. In the decision theory part, we briefly go through some major models and theories in the area, then focus on discussing some recent research topics in decision theory as well as their applications in economics, decision analysis, and operations management. Some relevant academic articles are discussed together with students in class. We will also discuss how the developments of decision theory drives its applications in different areas including decision analysis, finance, and operation management. Through studying the first part, the student will obtain some practical oriented Excel modeling skill, such as how to build and analyze a decision tree in Excel, build a simulation model when uncertainties are involved, and use Bayes rule to update probabilities and calculate value of information in decision tree analysis. Through studying the second part, the student will gain a rough overview of the development of decision theory and its interaction with some other relevant fields."