Files
Abstract
Running any dairy enterprise is a risky activity: the profitability of the enterprise is affected by the price fluctuation of feed and
animal health products from inputs, as well as by the fluctuation of end-product prices. Under these circumstances, it is essential for the cattle
breeders, in order to survive, to harness the reserves in management as effectively as possible.
In this research the efficiency and risk of 32 sample dairy farms were analysed in the Northern Great Plain Region from the Farm Accountancy
Data Network (FADN) by applying classical Data Envelopment Analysis (DEA) and stochastic DEA models. The choice of this method is
justified by the fact that there was not such an available reliable database by which production functions could have been defined, and DEA
makes possible to manage simultaneously some inputs and outputs, i.e. complex decision problems. By using DEA, the sources that cause
shortfall on inefficient farms can be identified, analysed and quantified, so corporate decision support can be reinforced successfully.
A disadvantage of the classical DEA model is that the stochastic factors of farming cannot be treated either on the side of inputs or outputs;
therefore, their results can be adopted with reservations, especially in agricultural models. This may have been because we could not discover
that many agricultural applications. Considering the price of inputs and outputs as probability variables, 5000 simulation runs have been done
in this research. As a result, it can be stated that at which intervals of the input and output factors can become competitive and the fluctuation
of these factors can cause what level of risk at each farm.