As the present application aims at analysing and evaluatingthe efficiency of different production units, it is necessary to clearly definethe meaning and range of this concept as used in this paper as well as tobriefly discuss the evaluation methods applied.
When talking about the performance of a production unit,the terms ?efficiency? and ?productivity? are generally used interchangeably;however, although both concepts are closely related, they do not mean exactly thesame.
A process productivity is generally measured by the [output/ input] ratio; that is, the output (production) obtained per input unit(supply) used in the production process. Therefore, a production process is thetechnological transformation of input variablesinto output variables.
It must be borne in mind that process productivity isdetermined by variable factors, such as the technology used, the productionprocess environment and the production process efficiency.
Broadlyspeaking, efficiency is a comparative measurement of the input used, the outputobtained and the ideal values for both. In other words, the input suppliedduring the production process is compared to the minimum input needed; and theoutput obtained is compared to the maximum output obtainable.
This is known as technical efficiency, asdescribed in current literature. Most approaches share the idea of relating thesupply used and the results obtained to their ideal values, that is, relatingmeans, ends and optimum values.
Having defined the concept ofefficiency, let us now discuss the measurement techniques that will be appliedto the input- into- output transformation process.
The methods traditionally used are:
a. EconometricTechniques, also known as parametric methods, require the formalisation of theproduction (or frontier) function that relates the variables at work in theproblem. Thus, the parameters that determine the defined function value areestimated. These techniques are stochastic and intended to discriminate therandom error effect from the inefficiency effect
b. Non-stochastic mathematical programming techniques calculate an empiric frontier orconvex hull from the data obtained by using mathematical programming methods.
At present, other authors useMulticriteria Decision-making Aid Methods to measure technical efficiency. Thisapproach considers that the Data Envelopment Analysis (DEA) is a particularcase of Multicriteria Decision techniques (Perez Mackergrang, 2003) and extendsthis view to other Multicriteria decision tools.
This approach proposes to equate a)minimum criteria to input, b) maximum criteria to output and c) the alternatives to theDecision Making Units (DMU); and then, to work out the problem by usingMulticriteria Decision Aid techniques.
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