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ISSN 1895-2038, e-ISSN:1734-459X

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Creative Commons licence CC BY-NC (Attribution-NonCommercial)Logforum. 2016. 12(2), article 2, 123-128; DOI: https://doi.org/10.17270/J.LOG.2016.2.2

ACCOUNTING THE SCALE AND SYNERGIES IN THE DEA-ANALYSIS

Vasilij Alekseevič Novikov1, Ludmila Shipulina2, O. Sapun1

1Belarusian State Agrarian Technical University, Minsk, Belarus
2
International University MITSO, Minsk, Belarus

Abstract:

Background: The proposal is to non-linear performance into account in terms of synergy when conducting DEA (Data Envelopment Analysis). The solution to the problem is produced for interacting schools, which can be regarded as business clusters. The inputs and outputs are selected by importance on the basis of the author's opinion. However, the technique does not change when taking into account other factors that are expressed numerically.

Methods: The proposal is to reduce the number of the inputs and outputs to one input and one output using weighting factors. Thus a solution can be found by linear programming. The D EA algorithm is easily coded in Mathcad.

Results: As a result, we obtain a vector of the effectiveness of each element in the business cluster, including stand-effective and super-efficient elements.

Conclusions: A model of DEA is proposed which takes into account the scale and synergies of the business cluster. This allows a performance rating against the collective interaction to be obtained.

 
Keywords: DEA, business cluster, linear programming, inputs, outputs, synergies, efficiency, super-efficiency
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For citation:

MLA Novikov, Vasilij Alekseevič, et al. "Accounting the scale and synergies in the dea-analysis." Logforum 12.2 (2016): 2. DOI: https://doi.org/10.17270/J.LOG.2016.2.2
APA Vasilij Alekseevič Novikov, Ludmila Shipulina, O. Sapun (2016). Accounting the scale and synergies in the dea-analysis. Logforum 12 (2), 2. DOI: https://doi.org/10.17270/J.LOG.2016.2.2
ISO 690 NOVIKOV, Vasilij Alekseevič, SHIPULINA, Ludmila, SAPUN, O.. Accounting the scale and synergies in the dea-analysis. Logforum, 2016, 12.2: 2. DOI: https://doi.org/10.17270/J.LOG.2016.2.2