Data Envelopment Analysis Coursework
“The module will be assessed 100% by an individual coursework, in which the students will analyse a case study and present their findings in a report.”
This document specifies the requirements you should follow in selecting an appropriate case study and how you should report your findings.
1 Selecting a Case Study
If you are wishing to obtain a mark of 60%+ (ie a first or 2i) you should select your own case study. However if your aspirations are lower and you are happy with a mark of 40% to 60% you are advised to consider the example case study.
If selecting your own case study, a self assessment task has been created where you can post the details about the case study you have are thinking of selecting.
The intention of this task is to allow you to receive feedback on the viability of your proposed case study and will enable me to provide advice as to issues you may need to consider and alternative sources of data.
In selecting a Case study you should consider the following:
1. Availability of suitable data
The data should be publicly available (ideally in electronic form) and ideally should have comparable information for more than one year. Data can come from multiple sources (see examples above). There will need to be data on both the resources used (inputs such as Number and/or cost of staff) and successful production (outputs for example revenue and or number of products sold)
2. Sufficient decision making units for comparisons
What constitutes a sufficient number will depend on the number of inputs and outputs in the DEA models you are using. For the purposes of the coursework you may have a small number of Decision Making Units (DMUs) as long as you consider their performance over several time periods (eg, 15-25 DMUs with 5 to10 years of annual data) or a larger dataset over a shorter period (eg 200 DMUs over two years of annual data).You should have more than one year’s data.
3. Personal interest
You will be spending a considerable amount of time analyzing the data and writing up your report so pick an area that interests you!
4. Ability to demonstrate understanding of the whole DEA module
Pick something which is quite rich in alternative data, so that you can compare alternative models of performance; perhaps where league tables or some other measure of performance is already used so you can compare you results with these. Having data for (mostly) the same DMUs over several years allows you to look at changes over time. You should consider some other groupings of the DMUs (say rural or urban, private or public ownership)
So do not jump to make a selection too quickly, first do some research to find out what data might be available. But also do not spend all your time choosing, you are best making your choice and sticking too it as long as data is available.
You are best writing the report as you go along, that way you can use the surgery sessions to get feedback on your progress. Some tips on where to start are available in blackboard.
There is also a second self and peer assessment task to ensure you have located some appropriate data and have looked at some simple DEA models and obtained feedback to ensure you are on the right track.
2 The Form and Content of the Report
The report that you hand in should be a report on the efficiency of the operations of your case study organization(s) for one of its stakeholders. You should not assume that the stakeholder understands the Data Envelopment Analysis technique and so will need to explain it to the reader (but should include technical details in an appendix). The following is intended as a possible outline for your report it also gives a guideline as to the number of words expected, some variation from this guideline is expected depending on your actual case study.
1. General introduction (250-750 words).
Here you introduce the operations you are studying and what good performance might mean for them. If there is already a method of performance measurement used you should discuss it.
2. Introduction to the Data Envelopment Analysis technique (500-1500 words).
Introduce DEA using simple model(s) that can be shown graphically, using real data from your case study. Show how DEA may be preferred to league tables, rating classifications or ratio measures for your case study organization(s).
3. Exploratory Data Analysis & Model Specification (250-750 words).
In this section you summarize what data is available and could be used in performance analysis. You then justify the inputs and outputs you are going to use in your DEA model(s), also whether input or output orientation is used.
4. Results of DEA analysis for at least one time period (1000-2000 words).
Discuss the targets for inefficient DMUs, and identify their efficient Peers. Compare the results with other methods of performance measurement.
5. Consideration of different groups and/or time periods (750-1500 words).
Here you can examine the Malmquist index (and its decomposition) to see how efficiency has changed over time. Statistics can also be examined to identify efficiency differences between groups of DMUs. Again it is worth using simple models that can be shown graphically to illustrate this (this may well be in addition to your actual models).
6. Overall Conclusions (150-300 words)
Summarize your results here.
Either give the data here and also include output from the DEA software you have used.
3 Marking scheme
The marks are entirely on your final report so the peer and self assessment tasks are learning experiences which ensure that you know you are progressing. The final report is assessed on the following criteria.
Understanding of case study (20%)
The mark here based on your introduction and the specification of the DEA models, and to some extent the conclusions. Have you demonstrated you understand for your case study what constitutes good performance?
Understanding of Basic DEA technique (30%)
The mark here is based on the specification of your DEA models (do the inputs and outputs make sense), explanations of simple graphs of the limited DEA models for your case study and the interpretation of the computer output for more realistic DEA models for a single time period.
More advanced aspects of DEA (25%)
The marks here will depend on your case study but reward is given here for coping with technical difficulties in applying DEA (eg negative values and or restrictions on weights), and your analysis of changes over time and/or between groups as appropriate.
Use of statistical tests etc. (15%)
The marks here are based on the use of statistics as exploratory data analysis to determine sensible DEA models and for the use of statistics in examining the changes over time and/or between groups
Presentation, spelling, grammar etc. (10%)
Originality is also rewarded it will be difficult to attain very high marks if your case study is very close to an example which has been considered in detail in class
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