Measuring Efficiency of Decision Making Units WSE-EKN-MON-EFF
I. Economic foundations of the production process of the enterprise
a) production processes
b) Properties of the production function
c) Frontier of production possibilities
II. Basics of the Data Envelopment Analysis (DEA) method:
II. 1 Performance Assessment Method
II 2 Case study
II 3 Multiple inputs outputs
II 4 Types of efficiency
II 5 Implications for management
III. Software and practical cases
IV. Mathematical models of the DEA method
IV. 1 Consistent economies of scale
IV. 2 Variable economies of scale
V. DEA extensions
V. 1 Adapting performance to environmental conditions
V. 2 Preferences
V. 3 Sensitivity analysis
V. 4 Time horizon
VI. DEA from Microsoft Excel Solver
VI. 1 Solver
VI. 2 Programming a model of constant return to scale
VII. Empirical research
(in Polish) Dyscyplina naukowa, do której odnoszą się efekty uczenia się
(in Polish) Grupa przedmiotów ogólnouczenianych
Subject level
Learning outcome code/codes
Type of subject
Preliminary Requirements
Course coordinators
Learning outcomes
Student activity Student workload in hours
participation in the lecture 30
preparation for the inter group discussions 25
consultation 5
time to write the work 10
time to the self-assessment of the inter-group work 5
preparation for the exam 25
TOTAL HOURS 100
NUMBER OF ECTS 100 hours / 30 (25) hours ≈ 4
Assessment criteria
2 – a student has not provided the work, or the work is not her independent achievement, is chaotic with regard to the basic technical properties related to economic foundations of the production process of an enterprise, or to the DEA technique as well on the sides of conceptualization as implementation in practice.
3 – a student proves to understand basic concepts of the course in different aspects related to Measuring Efficiency of Decision Making Units shown in the lecture. He can use the taught software during the lectures. He still shows difficulties to master the empiric side of the DEA technique with respect to different scenario analysis.
4 – a student has provided a good work and stated problems and positions correctly. He is able to choose and apply the adequate methods depending on the type of the problem at hand.
5 - a student has provided a good work and stated problems and positions correctly. He is able to choose and apply the adequate methods depending on the type of the problem at hand. He can interpret adequately the solution and can knows which policy a DMU to follow in the case of technical or scale inefficiencies. He can fit the solution to the case of varying environmental conditions.
SKILLS:
The written work is assessed as above.
SOCIAL COMPETENCE
2 – a student do not understand basic concepts related to the techniques of measuring Efficiency of Decision Making Units. He avoids any discussion related to this issue
3 – a student has got basic insights related to measuring Efficiency of Decision Making Units concepts. He does not master some computational techniques but recognizes its usefulness. He would be ready to increase knowledge and competences for professional purposes.
4 – a student initiates discussions related to the techniques of measuring Efficiency of Decision Making Units issues and can understand various technical reports presented specialists of the field.
5 – a student initiates discussions related to the techniques of measuring Efficiency of Decision Making Units issues, knows to select the correct model and apply efficiently computational techniques to solve problems. He understands the implications of the technique measuring Efficiency of Decision Making Units in different context of business, places them in the broader background of everyday.
The final grade consists of: a written test (45%) and self-assessment of work between groups of students (55%), of which 10% of student activity manifested in the quality of assessment of colleagues' work.
10 points - score: 5.0;
8-9 points - score: 4.5;
7-8 points - score: 4.0;
6-7 points - grade: 3.5;
5 - 6 points - mark 3.0;
below 5 points - grade: 2.0
Bibliography
1)Jean-Marc Huguenin, Data Envelopment Analysis (DEA), a pedagogical guide for decision makers in the public sector, 2012 IDHEAP, Lausanne, ISBN 978-2-940390-54-0, https://serval.unil.ch/resource/serval:BIB_0FC432348A97.P001/REF
2) Charnes, A, Cooper, W. W. & Rhodes E. L. (1978). Pomiar efektywności jednostek decyzyjnych. European Journal of Operational Research, 2(6), 429-444.
3) Cooper W.W. [et al.], Handbook on data envelopment analysis, Kluwer Aca-demic, Boston 2004
Teksty fakultatywne:
1)Joanicjusz Nazarko, Ireneusz Jakuszewicz, Joanna Urban, Metoda DEA w analizie jednostek produk-cyjnych, https://depot.ceon.pl/bitstream/handle/123456789/7700/Metoda_DEA_w_analizie_jednostek_produkcyjnych.pdf?sequence=1&isAllowed=y
2)TUTORIAL IN DEA, New York http://apolo.creg.gov.co/Publicac.nsf/0/d7f9626a2dd4d5f00525785a007a6523/$FILE/Anexo9ciruclar031-02.pdf
3)Notatki z badań operacyjnych, http://people.brunel.ac.uk/~mastjjb/jeb/or/dea.html
4)S. Bwanakare, A Stochastic Non-Homogeneous Constant Elasticity of Substitution Production Function as an Inverse Problem: A Non-Extensive Entropy Estimation Approach, Polska Akademia Nauk, Acta Physica Polonica A, vol 123/ 3, march 2013, DOI: 10.12693/APhysPolA.123.502 lub http://przyrbwn.icm.edu.pl/APP/PDF/123/a123z3p02.pdf
Additional information
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