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

Postgraduate Course: Performance Analytics with DEA: Basic Concepts and Methods (CMSE11424)

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 Credits10 ECTS Credits5
SummaryThis course provide students with fundamental theory of Data Envelopment Analysis (DEA).
Course description Academic Description:
Data Envelopment Analysis (DEA) is a performance evaluation and bench-marking methodology. DEA is a non-parametric and frontier-based methodology that benchmarks against the best or the worst practice frontier. Nowadays, DEA is commonly used for the relative performance evaluation and risk assessment of entities such as banks, bank branches, firms listed on stock markets, investment vehicles including projects, production technologies, suppliers, etc. This course aims at training students in the field of performance evaluation and management using DEA as the main methodology. The course shall cover the key concepts in performance management along with a general classification of performance evaluation methodologies; DEA concepts and generic methodology; static black-box DEA models and their use in business applications; and practical issues in DEA and how to address them.

Outline Content:
1. Key concepts in performance management along with a general classification of performance evaluation methodologies
2. DEA concepts and generic methodology
3. Static DEA models and their use in business applications
4. Practical issues in DEA and how to address them

Student Learning Experience:
Weekly lectures and hands-on programming exercises in Matlab and DEA solvers which enables students to implement the methodologies covered in class.

Tutorial/seminar hours represent the minimum total live hours - online or in-person - a student can expect to receive on this course. These hours may be delivered in tutorial/seminar, lecture, workshop or other interactive whole class or small group format. These live hours may be supplemented by pre-recorded lecture material for students to engage with asynchronously.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements For MSc Business Analytics students, or by permission of course organiser. Please contact the course secretary.
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  None
Course Start Block 3 (Sem 2)
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 88 )
Additional Information (Learning and Teaching) Seminar/Tutorial hrs are the min total live hrs, online or in-person, students can expect to receive
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 40% coursework (group - incl. 20% peer moderation) - assesses all course Learning Outcomes
60% coursework (individual) - assesses all course Learning Outcomes
Feedback Formative: Feedback will be provided throughout the course.

Summative: Feedback will be provided on the assessments 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 performance measurement, evaluation, and management using the proper terminology
  2. Identify and properly state performance problems in different business settings
  3. Address performance problems within a static DEA framework and choose the right basic DEA models to devise solutions
  4. Formulate managerial guidelines in the area of performance management and make recommendations based on basic DEA analyses
  5. Communicate performance problems and basic solutions effectively and efficiently to a critical audience
Learning Resources
Cooper WW, Seiford LM and Tone K. (2007) Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Second Edition. Springer

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.
KeywordsNot entered
Course organiserProf Jamal Ouenniche
Tel: (0131 6)50 3792
Course secretaryMs Heather Ferguson
Tel: (0131 6)50 8074
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