Measuring Efficiency of Decision Making Units

economics and finance

advanced

EK1_WO4

EK1_UO3

EK1_UO4

EK1_UO9

EK1_kO3

Basics of microeconomics

Basics of mathematics

This course introduces an approach of the evaluation of relative efficiency of private, non-profit and state institutions. This assessment is obtained using the Data Envelopment Analysis (DEA) technique as a managerial audit tool to identify and measure relative inefficiencies - and their sources, among Decision Making Units(DMU) of the same sector. DEA is conceptually a technique based on mathematical programming, with mathematical formalism being kept to a minimum.

The proposed content of this course is strongly practice-oriented. After completing the course, the student is able to carry out his own assessment of the enterprise in terms of its relative position in the sector from the point of view of management efficiency of inputs in relation to revenues, or vice versa, in terms of revenues in relation to inputs. The student is also able to understand the source and nature of possible performance barriers and suggest management implications, both technical and managerial.

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 Constant 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

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

KNOWLEDGE

The student knows the properties of production function and the concept of frontier of production possibilities, He will understand how to use the DEA technique in different aspects contexts, in particular in the case of multiples inputs and outputs and different types of efficiency. The student under-stand how to use the presented software or be able to use the Excel solver for the efficiency performance evaluation. The student knows how to adjust the DEA approach to environmental conditions impacting on the efficiency performance.

SKILLS

The student is able to visualize the efficiency frontier in the both cases of constant return to scale and variable return to scale . He is able to estimate the level of inefficiency irrespective of the orientation of the model(input or output) and the type of return to scale.

The student is able to properly apply the DEA basic software and linear programming technique and interpret main issues of the found results.

COMPETENCES

Student is able to choose the model orientation-input or output, depending on the empirical context of the DMU, estimate the efficiency level of DMU inefficiency irrespective of the type of return to scale and provide the sensitivity analysis with respect with the environmental context. The student can provide technical and managerial advice to a DMU so as to improve its relative efficiency in comparison with its competitors of the same sector.

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