The aim of this course is to ensure that students have the necessary qualifications and infrastructure to formulate and solve business decision problems using quantitative techniques such as single and multi-criteria decision analysis, Markov analysis, and simulation modeling.
Course Content
This course contains; Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty),Utility Theory, Rationality and Decision Making,Decision Making Under Ignorance (Uncertainty),Decision Making Under Risk,Multi-Stage Decisions and Decision Trees,Bayesian Decision Analysis,Game Theory,Markov Analysis,Group Decisions and Social Choice,Multi-Criteria Decision Making - Basic Concepts,Multi-Criteria Decision Making - Analytic Hierarchy Process,Multi-Criteria Decision Making - Analytic Network Process,Data Envelopment Analysis,Simulation - Basic Concepts and Applications.
Course Learning Outcomes
Teaching Methods
Assessment Methods
1. Will be able to describe the elements of decision theory and the distinction between individual and group decisions.
10, 12, 16, 9
A
1.1 Explains what should be taken into consideration when determining the objective, alternatives and states of the nature for a decision process
1.2 Describes the characteristics of both individual and group decisions
2. Will be able to realize the solutions of decision making under uncertainty and risk.
10, 12, 16, 9
A
2.1 Uses such basic strategies as maximin, maximax, and regret criteria for decision problems under uncertainty
2.2 Uses such basic strategies as expected value, maximum likelihood, and expected value of perfect information for decision problems under risk
3. Will be able to express the value of experimentation in decision process.
10, 12, 16, 9
A
3.1 Constructs probability tree diagrams
3.2 Estimates revise probability using Bayesian analysis
4. Will be able to determine future states or conditions by using Markov analysis.
10, 12, 16, 9
A
4.1 Explains the place of Markov process models in decision processes
4.2 Computes long-term ( steady-state) conditions by using the transition matrix probabilities
5. Will be able to design multi-criteria decision problems.
10, 12, 16, 9
A
5.1 Explains the importance of building decision frame for a multicriteria decision making problem
5.2 Uses such techniques as AHP, ANP, Topsis, and Vitor for multicriteria decision making process
6. Will be able to explain the advantages and disadvantages of simulation.
10, 12, 16, 9
A
6.1 Identifies the necessity of simulation technique in a decision process
6.2 Constructs simple simulation models using Excel
Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty)
2
Utility Theory, Rationality and Decision Making
3
Decision Making Under Ignorance (Uncertainty)
4
Decision Making Under Risk
5
Multi-Stage Decisions and Decision Trees
6
Bayesian Decision Analysis
7
Game Theory
8
Markov Analysis
9
Group Decisions and Social Choice
10
Multi-Criteria Decision Making - Basic Concepts
11
Multi-Criteria Decision Making - Analytic Hierarchy Process
12
Multi-Criteria Decision Making - Analytic Network Process
13
Data Envelopment Analysis
14
Simulation - Basic Concepts and Applications
Resources
[1] Quantitative Analysis for Management, B.Render & R.M.Stair & M.E.Hanna, 11th Edition, Pearson, 2012
[2] An Introduction to Decision Theory, Martin Peterson, Cambridge University Press, 2009
[3] Multi-Criteria Decision Making Methods: A Comparative Study, Panos M. Pardalos ve Donald Hearn (Editors), Springer Science+Business Media Dordrecht, 2000
[4] Lecture Notes
[5] Çok Kriterli Karar Verme Yöntemleri, B.Fatih Yıldırım ve Emrah Önder (Editörler), 2.Baskı, Dora Yayınları, 2015
[6] Karar Teorisi, Zerrin Aladağ, 2. Baskı, Umuttepe Yayınlar, 2014
[7] Karar Verme, Mustafa Aytaç ve Necmi Gürsakal (Editörler), Dora Yayınları, 2015
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Defines the theoretical issues in the field of information and management.
2
Describes the necessary mathematical and statistical methods in the field of information and management.
X
3
Uses at least one computer program in the field of information and management.
X
4
Sustains proficiency in a foreign language requiredor information and management studies.
X
5
Prepares informatics/software projects and work in a team.
6
Constantly updates himself / herself by following developments in science and technology with an understanding of the importance of lifelong learning through critically evaluating the knowledge and skills that s/he has got.7. Uses theoretical and practical expertise in the field of information and management
7
Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication skills.
X
8
Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication.
X
9
Adopts organizational / institutional and social ethical values.
10
Within the framework of community involvement adopts social responsibility principles and takes initiative when necessary.
11
Uses and analyses basic facts and data in various disciplines (economics, finance, sociology, law, business) in order to conduct interdisciplinary studies.
X
12
Writes software in different platforms such as desktop, mobile, web on its own and / or in a team.
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
40
Rate of Final Exam to Success
60
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
14
3
42
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
0
0
0
Term Project
0
0
0
Presentation of Project / Seminar
0
0
0
Quiz
0
0
0
Midterm Exam
1
40
40
General Exam
1
68
68
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
150
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(150/30)
5
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
QUANTITATIVE METHODS for BUSINESS DECISION MAKING
MIS3112176
Fall Semester
3+0
3
5
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
English
Course Level
First Cycle (Bachelor's Degree)
Course Type
Required
Course Coordinator
Assist.Prof. Esra BAYTÖREN
Name of Lecturer(s)
Assist.Prof. Esra BAYTÖREN
Assistant(s)
Aim
The aim of this course is to ensure that students have the necessary qualifications and infrastructure to formulate and solve business decision problems using quantitative techniques such as single and multi-criteria decision analysis, Markov analysis, and simulation modeling.
Course Content
This course contains; Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty),Utility Theory, Rationality and Decision Making,Decision Making Under Ignorance (Uncertainty),Decision Making Under Risk,Multi-Stage Decisions and Decision Trees,Bayesian Decision Analysis,Game Theory,Markov Analysis,Group Decisions and Social Choice,Multi-Criteria Decision Making - Basic Concepts,Multi-Criteria Decision Making - Analytic Hierarchy Process,Multi-Criteria Decision Making - Analytic Network Process,Data Envelopment Analysis,Simulation - Basic Concepts and Applications.
Course Learning Outcomes
Teaching Methods
Assessment Methods
1. Will be able to describe the elements of decision theory and the distinction between individual and group decisions.
10, 12, 16, 9
A
1.1 Explains what should be taken into consideration when determining the objective, alternatives and states of the nature for a decision process
1.2 Describes the characteristics of both individual and group decisions
2. Will be able to realize the solutions of decision making under uncertainty and risk.
10, 12, 16, 9
A
2.1 Uses such basic strategies as maximin, maximax, and regret criteria for decision problems under uncertainty
2.2 Uses such basic strategies as expected value, maximum likelihood, and expected value of perfect information for decision problems under risk
3. Will be able to express the value of experimentation in decision process.
10, 12, 16, 9
A
3.1 Constructs probability tree diagrams
3.2 Estimates revise probability using Bayesian analysis
4. Will be able to determine future states or conditions by using Markov analysis.
10, 12, 16, 9
A
4.1 Explains the place of Markov process models in decision processes
4.2 Computes long-term ( steady-state) conditions by using the transition matrix probabilities
5. Will be able to design multi-criteria decision problems.
10, 12, 16, 9
A
5.1 Explains the importance of building decision frame for a multicriteria decision making problem
5.2 Uses such techniques as AHP, ANP, Topsis, and Vitor for multicriteria decision making process
6. Will be able to explain the advantages and disadvantages of simulation.
10, 12, 16, 9
A
6.1 Identifies the necessity of simulation technique in a decision process
6.2 Constructs simple simulation models using Excel
Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty)
2
Utility Theory, Rationality and Decision Making
3
Decision Making Under Ignorance (Uncertainty)
4
Decision Making Under Risk
5
Multi-Stage Decisions and Decision Trees
6
Bayesian Decision Analysis
7
Game Theory
8
Markov Analysis
9
Group Decisions and Social Choice
10
Multi-Criteria Decision Making - Basic Concepts
11
Multi-Criteria Decision Making - Analytic Hierarchy Process
12
Multi-Criteria Decision Making - Analytic Network Process
13
Data Envelopment Analysis
14
Simulation - Basic Concepts and Applications
Resources
[1] Quantitative Analysis for Management, B.Render & R.M.Stair & M.E.Hanna, 11th Edition, Pearson, 2012
[2] An Introduction to Decision Theory, Martin Peterson, Cambridge University Press, 2009
[3] Multi-Criteria Decision Making Methods: A Comparative Study, Panos M. Pardalos ve Donald Hearn (Editors), Springer Science+Business Media Dordrecht, 2000
[4] Lecture Notes
[5] Çok Kriterli Karar Verme Yöntemleri, B.Fatih Yıldırım ve Emrah Önder (Editörler), 2.Baskı, Dora Yayınları, 2015
[6] Karar Teorisi, Zerrin Aladağ, 2. Baskı, Umuttepe Yayınlar, 2014
[7] Karar Verme, Mustafa Aytaç ve Necmi Gürsakal (Editörler), Dora Yayınları, 2015
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Defines the theoretical issues in the field of information and management.
2
Describes the necessary mathematical and statistical methods in the field of information and management.
X
3
Uses at least one computer program in the field of information and management.
X
4
Sustains proficiency in a foreign language requiredor information and management studies.
X
5
Prepares informatics/software projects and work in a team.
6
Constantly updates himself / herself by following developments in science and technology with an understanding of the importance of lifelong learning through critically evaluating the knowledge and skills that s/he has got.7. Uses theoretical and practical expertise in the field of information and management
7
Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication skills.
X
8
Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication.
X
9
Adopts organizational / institutional and social ethical values.
10
Within the framework of community involvement adopts social responsibility principles and takes initiative when necessary.
11
Uses and analyses basic facts and data in various disciplines (economics, finance, sociology, law, business) in order to conduct interdisciplinary studies.
X
12
Writes software in different platforms such as desktop, mobile, web on its own and / or in a team.
