Decision Theory


  • GENERAL
SCHOOL Faculty of Social, Political and Economic Sciences
ACADEMIC UNIT Department of Economics
LEVEL OF STUDIES Undergraduate
COURSE CODE   SEMESTER 6th
COURSE TITLE Decision Theory
INDEPENDENT TEACHING ACTIVITIES
if credits are awarded for separate components of the course, e.g. lectures, laboratory exercises, etc. If the credits are awarded for the whole of the course, give the weekly teaching hours and the total credits
WEEKLY TEACHING HOURS CREDITS
Lectures and Class exercises 4 6
 
 
Add rows if necessary. The organisation of teaching and the teaching methods used are described in detail at (d).
COURSE TYPE

general background,
special background, specialised general knowledge, skills development

General background
PREREQUISITE COURSES:

 

Statistics, Mathematics, Management
LANGUAGE OF INSTRUCTION and EXAMINATIONS: Greek
IS THE COURSE OFFERED TO ERASMUS STUDENTS Yes (in English)
COURSE WEBSITE (URL) http://www.econ.duth.gr/undergraduate/lessons/st3.shtml

 

 

  • LEARNING OUTCOMES
Learning outcomes
The course learning outcomes, specific knowledge, skills and competences of an appropriate level, which the students will acquire with the successful completion of the course are described.

Consult Appendix A

·     Description of the level of learning outcomes for each qualifications cycle, according to the Qualifications Framework of the European Higher Education Area

·     Descriptors for Levels 6, 7 & 8 of the European Qualifications Framework for Lifelong Learning and Appendix B

·     Guidelines for writing Learning Outcomes

The course is an introduction to decision theory mainly by providing the analysis framework for   probabilistic models, qualitative and quantitative methods to support decision making process and problem solving. Through a systemic approach and a large variety of case studies the appropriate methodological framework is analyzed. Key emphasis is given in modelling and determine the framework which leads to decisions. The uncertainty is analyzed promoting methodologies of determining optimum and/or satisficing solutions. By a series of real life applications, the decision making process is examined and appropriate methods to specific problems are developed.

The decision models presented in this course are using a wide range of mathematical, graphical and statistical analysis background in order to tackle both uni-criterion and multi-criteria decision making problems with quantitative and/or qualitative data.

 

Based on above quantitative and/or qualitative analysis framework, the course learning outcomes could be summarized:

·         Ability to define the key parameters and variables of a decision-making process

·         Ability to choose the appropriate methodology for a decision-making problem

·         Ability to analyze and assess the decision-making outputs as well as to review the process results through sensitivity analysis

·         Ability of modelling using the appropriate:

o    Decision process, variables, parameters, criteria, attributes

o    Measures for Uncertainty and Fuzziness

o    Alterative scenarios

o    Sensitivity analysis

o    Level of confidence in selected solutions

 

After a successful course, the students should be able to understand the main issues and techniques in decision making, develop a decision making process and propose solutions, based on:

·         Statistical analysis: sampling, estimation, regression analysis

·         Decision trees

·         Decision making based on game theory

·         Fuzzy sets

·         Queuing theory

·         Scheduling/Sequencing problems: GANT-CPM-PERT

·         Utility theory

·         Multi-criteria analysis

General Competences
Taking into consideration the general competences that the degree-holder must acquire (as these appear in the Diploma Supplement and appear below), at which of the following does the course aim?
Search for, analysis and synthesis of data and information, with the use of the necessary technology

Adapting to new situations

Decision-making

Working independently

Team work

Working in an international environment

Working in an interdisciplinary environment

Production of new research ideas

Project planning and management

Respect for difference and multiculturalism

Respect for the natural environment

Showing social, professional and ethical responsibility and sensitivity to gender issues

Criticism and self-criticism

Production of free, creative and inductive thinking

……

Others…

…….

 

·         Decision-making

·         Search for, analysis and synthesis of data and information, with the use of the necessary technology

·         Working independently

·         Working in an interdisciplinary environment

·         Production of free, creative and inductive thinking

 

  • SYLLABUS
The course syllabus includes:

i.       Methods of Statistical analysis used in decision making:

·       Sampling theory

·       Statistic distributions

·       Regression analysis

ii.       Decision theory under uncertainty and risk:

·         Decision trees

·         Fuzzy sets

iii.      Decision making based on game theory

iv.      Decision making based on queuing theory

v.       Decision making based on inventory models

vi.      Multiple Criteria Decision Making

vii.      Scheduling/Sequencing network decision techniques i.e. GANT-CPM-PERT

viii.      Simulation models

ix.      Introduction to Decision Support Systems

 

  • TEACHING and LEARNING METHODS – EVALUATION
DELIVERY
Face-to-face, Distance learning, etc.
·         Class lectures

·         Case studies

·         Notes, slides

USE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
Use of ICT in teaching, laboratory education, communication with students
·         Presentations

·         e-class

TEACHING METHODS

The manner and methods of teaching are described in detail.

Lectures, seminars, laboratory practice, fieldwork, study and analysis of bibliography, tutorials, placements, clinical practice, art workshop, interactive teaching, educational visits, project, essay writing, artistic creativity, etc.

 

The student’s study hours for each learning activity are given as well as the hours of non-directed study according to the principles of the ECTS

Activity Semester workload
Lectures 60
Individual assignments and exercises 40
Individual Study 50
Course total 150
STUDENT PERFORMANCE EVALUATION

Description of the evaluation procedure

 

Language of evaluation, methods of evaluation, summative or conclusive, multiple choice questionnaires, short-answer questions, open-ended questions, problem solving, written work, essay/report, oral examination, public presentation, laboratory work, clinical examination of patient, art interpretation, other

 

Specifically-defined evaluation criteria are given, and if and where they are accessible to students.

·         Individual assignments and numerical exercises during the course (20%)

·         Final written exams (80%)

 

 

 

 

 

 

 

 

  • ATTACHED BIBLIOGRAPHY
 

– Bibliography:

 

·         Ι. Κ. Μουρμούρης, «Εφαρμογές Θεωρίας Αποφάσεων Πολλαπλών Κριτηρίων: Μεταφορές, Χωροθέτηση και Ανάπτυξη», ISBN 9789603516880, Εκδόσεις: Α. Σταμούλης, 2007.

 

·         Ν. Ματσατσίνης – Κ. Ζοπουνίδης, «Συστήματα αποφάσεων με πολλαπλά κριτήρια», ISBN 9604610686, Εκδόσεις: Κλειδάριθμος, 2007.

 

 

– Selected referred journals:

 

International Journal of Management and Decision Making

International Journal of Decision Support Systems

Decision-Making for Supply Chain Integration

International Journal of Multicriteria Decision Making

Multiple Criteria Decision Making

Journal of Multi-Criteria Decision Analysis

Decision Support Systems

Journal of Decision Systems

Journal of Soft Computing and Decision Support Systems

Omega

Operations Research

European Journal of Operations Research

Computers and Operations Research

Mathematics of Operations Research

Annals of Operations Research

American Journal of Operations Research

Mathematical Programming

Operations Research Letters