BA4517 DECISION ANALYSIS: TOOLS AND METHODS

Course Code:3124517
METU Credit (Theoretical-Laboratory hours/week):3 (3.00 - 0.00)
ECTS Credit:6.0
Department:Business Administration
Language of Instruction:English
Level of Study:Undergraduate
Course Coordinator:Assoc.Prof.Dr. GÜLŞAH KARAKAYA
Offered Semester:Spring Semesters.

Course Objectives

By the end of the course the students will be able to

  • attain an understanding on the basic philosophy, tools and techniques related with Decision Analysis  
  • develop the analytical and critical thinking skills to model a decision problem by selecting an appropriate tool/technique
  • follow the steps/procedure of the selected technique by using a spreadsheet program and develop a solution
  • interpret the solution and make a meaningful recommendation to the decision maker
  • prepare a group term-project that involves the application of the techniques learnt in the course to a particular decision problem consisting of real data and real decision makers

Course Content

Decision analysis aims to provide a structured and systematic approach to guide the decision making activities in complex problems. This course attempts to convey the basic concepts and principles on the analytical methods, tools and techniques of decision analysis. Topics to be covered include Multi-Objective Decision Making (MODM), SMART, SMARTER, even swaps, AHP, Multi-Attribute Utility Theory(MAUT), influence diagrams, decision trees and scenario planning.
Prerequisites: BA 3504.


Course Learning Outcomes

By the end of the course the students will be able to

  • make sense of the approach and the philosophy behind Decision Analysis
  • make sense of the properties and components of a decision problem
  • make sense of the intuitive ways of making decisions
  • make sense of various deterministic Decision Analysis techniques such as SMART, SMARTER, Even Swaps and AHP
  • make sense of utility theory and multi-attribute utility theory
  • make sense of influence diagrams and decision trees
  • make sense of the value of information and the Bayesian decision making
  • learn to apply the various techniques by spreadsheet programs (especially MS Excel)
  • evaluate and interpret the solutions obtained by the application of the various techniques 
  • participate in team-work to prepare a term-project that involves the application of the techniques learnt in the course to a particular decision problem consisting of real data and real decision makers

Program Outcomes Matrix

Level of Contribution
#Program Outcomes0123
1They attain advanced level of knowledge in the functional areas of business administration such as strategic management, marketing, accounting, finance, organization management, human resources, and operations management.
2They are capable of identifying and analyzing legal, environmental and social factors, which influence the basic functional areas of the business administration.
3They understand and implement rational, systematic and scientific approaches effectively in problem solving and decision-making processes.
4They are capable of applying, analyzing, synthesizing and evaluating the knowledge they have in diverse fields efficiently
5They are capable of transferring information by using efficient verbal and written communication techniques.
6They are capable of performing professional communication effectively also in English.
7They know the methods of performing efficient teamwork.
8They are capable of following the contemporary techniques, scientific and technological developments in their fields and are able to conduct research and studies in order to develop their business administration related knowledge, skills, and competences.
9They are knowledgeable in the areas of professional ethics and responsibility.
10They are capable of utilizing their knowledge and skills efficiently in global and multicultural contexts.
11They are knowledgeable in the issues of environment, social responsibility, social justice, quality and cultural values
12They have a creative, innovative and critical perspective.

0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution