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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Analytics of Decision Making under Multiple Criteria (CMSE11658)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis course provides students with the theory of Multicriteria Decision Analysis (MCDA) and its applications in business.
Course description In practice Multi-Criteria Decision Analysis (MCDA) and Multi-Criteria Decision Making (MCDM) methods are very popular in addressing complex problems involving multiple and typically conflicting criteria as well as several stakeholders or decision makers with different preferences with respect to the evaluation criteria. This course aims at training students in the field of MCDA/MCDM with emphasis on rating, ranking and classification problems and methods with applications in business.

Outline content

1. Basic MCDA/MCDM concepts and terminology along with a general classification of MCDA/MCDM problems

2. Rating problems, their solution methods and the design of multi-criteria indexes, and their use in business applications

3. Ranking problems, their solution methods, and their use in business applications

4. Classification problems, their solution methods, and their use in business applications

5. Practical issues in MCDA/MCDM and how to address them

Student Learning Experience

Weekly lectures and hands-on applications with software or coding.

Teaching will take the form of in class and/or recorded lectures and in person and/or online supervised discussions and lab sessions, as judged appropriate. The live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously. The supervised discussions and lab sessions aim at putting into practice the concepts and methods presented in the lectures and learned from personalised readings. In addition, these sessions also serve as advice/support sessions so that students can seek assistance and formative feedback on their term projects work-in-progress. Some of the material covered in lectures and discussion sessions will be research-led and based on recent publications from the academic literature. Besides attending lectures and supervised discussion and lab sessions, students will work in groups on realistic projects and present their work in class to an audience of practitioners when the term projects are provided by industry.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites Students MUST also take: Prescriptive Analytics with Mathematical Programming (CMSE11431)
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2024/25, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 166 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 60% Class test (Individual) - Assesses all course Learning Outcomes
40% Project report (Group) Includes 20% peer evaluation - Assesses all course Learning Outcomes
Feedback Formative: Feedback will be provided throughout the course.

Summative: Feedback will be provided on the assessment within agreed deadlines.

No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Discuss the concept and methods of MCDA/MCDM using the proper terminology
  2. Identify and properly state MCDA/MCDM problems in different business settings
  3. Address MCDA/MCDM problems and choose the right methods to devise solutions
  4. Use MCDA/MCDM solutions to formulate managerial guidelines and make recommendations
  5. Communicate MCDA/MCDM problems and solutions effectively and efficiently to a critical audience
Reading List
Additional Information
Graduate Attributes and Skills Communication, ICT, and Numeracy Skills

After completing this course, students should be able to:

Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.

Cognitive Skills

After completing this course, students should be able to:

Be self-motivated; curious; show initiative; set, achieve and surpass goals; as well as demonstrating adaptability, capable of handling complexity and ambiguity, with a willingness to learn; as well as being able to demonstrate the use digital and other tools to carry out tasks effectively, productively, and with attention to quality.

Knowledge and Understanding

After completing this course, students should be able to:

Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.

Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore and solve them responsibly.
KeywordsMulticriteria Decision Analysis,Rating,Ranking,Classification,Performance Analytics
Course organiserProf Jamal Ouenniche
Tel: (0131 6)50 3792
Course secretary
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