20 research outputs found

    Apie pedagogų vertinimą LŽŪU

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    Santr. anglVytauto Didžiojo universitetasŽemės ūkio akademij

    Vienlentelės duomenų bazės ir elektroninės lentelės : Metod. priemonė ; LŽŪU. Informatikos kat

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    Bibliogr.: p. 18 (3 pavad.)Vytauto Didžiojo universitetasŽemės ūkio akademij

    Sistema Windows 3.1 ; LŽŪU.Informatikos kat

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    Vytauto Didžiojo universitetasŽemės ūkio akademij

    Apie M.Farrell'o metodo taikymo galimybes

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    Santr. anglBibliogr.: p. 60 (4 pavad.)Vytauto Didžiojo universitetasŽemės ūkio akademij

    Measuring Efficiency of Agriculture Industry Using Multi-Directional Efficiency Analysis Method

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    Multi-directional Efficiency Analysis (MEA), like Data Envelopment Analysis (DEA), is a non-parametric method, differing from DEA in the way in which efficiency is measured. In other words, MEA makes use of an entirely different efficiency index. DEA has become one of the more popular tools for productivity analysis. DEA is especially useful when there are multiple inputs and outputs with different units of measure. There are several ways of applying the DEA methodology that all stem from the seminal papers of Farrell (1957) and of Charnes, Cooper and Rhodes (1978). The input-oriented method as its efficiency is determined by holding outputs constant and inputs to be improved (decreased) in order for a DMU to be considered efficient, thus the output-oriented method by holding inputs constant and outputs be improved (increased). An efficient DMU has no potential improvement, whereas inefficient DMUs have efficiency scores reflecting the potential improvement based on the performance of other DMUs. When utilizing DEA to evaluate a set of (DMUs), an efficient frontier is created that determines which DMUs are performing well (efficient) and which are not (inefficient). The selection of the decision making units (DMUs) to benchmark against is a critical part of this analysis. These different methodologies typically give the same efficient set, although by moving solely along the input space or solely along the output space. The efficiency score, which will be less than one if a DMU is inefficient, is the proportion by which all inputs must be reduced in order to become efficient. This is an important point: for a particular inefficient DMU, the projection onto the frontier is, in essence, calculated by reducing the input dimension until the DMU reaches the frontier. If the purpose of the benchmarking set is to determine those efficient DMUs most like an inefficient DMU, it is better to have the ability to move alongVytauto Didžiojo universitetasŽemės ūkio akademij

    Ekonominės veiklos efektyvumo vertinimas

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    Santr. anglBibliogr.: p. 256 (4 pavad.)Vytauto Didžiojo universitetasŽemės ūkio akademij

    Europos sąjungos šalių ūkio efektyvumo įvertinimas

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    Vertinant daugiafunkcinio žemės ūkio konkurencingumą tikslinga vietoj įprasto darbo našumo rodiklio naudoti efektyvumo rodiklį. Straipsnyje nagrinėjami Europos Sąjungos šalių žemės ūkio gamybos sektoriaus efektyvumo įvertinimo klausimai. Pateikiama efektyvumo samprata bei matavimo metodika. Aptariami daugiafunkcinių procesų vertinimui tinkami stochastinės analizės, laisvai nustatomo paviršiaus, duomenų gaubtinės analizės metodai. Tyrimui panaudoti Europos Komisijos duomenų bazėse sukaupti 2003–2008 m. duomenys. Taikant matematinį modelį, realizuojantį duomenų gaubtinės analizės metodą, apskaičiuoti ES šalių žemės ūkio efektyvumo įvertinimai. Gauti objektyvus efektyvumo įvertinimai rodo, kad naujųjų ES narių, tarp jų ir Lietuvos, žemės ūkis yra vis dar menkai efektyvus, nors daugelyje šalių–naujokių išlaikoma efektyvumo didėjimo tendencija. Pagrindiniais efektyvumo didėjimo veiksniais Lietuvos žemės ūkyje laikytini pigios darbo jėgos ir našios technikos panaudojimasEvaluation of competitiveness of the multifunctional agriculture requires using the efficiency instead of productivity index. The paper addresses the question of the evaluation of efficiency in the agricultural sector of the European Union. The conception of the efficiency is explained and the methods for measurement are provided. The authors discuss the methods of stochastic analysis, Free Disposal Hull analysis and Data Envelopment Analysis that are particularly useful for multi-criteria evaluation of multifunctional processes. Data from the European Commission databases collected in the period of 2003-2008 is used. Applying of the mathematical model, which is based on the Data Envelopment Analysis method, enables to evaluate the efficiency of agriculture in each EU country. The results show that agricultural efficiency of new EU countries, including Lithuania, is still at low level, even though trends to increase are observed. The main factors that could increase the agricultural efficiency in Lithuania are the use of cheap labour force and sophisticated agricultural machiner
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