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  • Data envelopment analysis (DEA) gives a very powerful tool to decision makers in an organization. DEA is then a natural choice for an application of operations research or mathematical modelling of an evaluation of corporate performance. This method was initially proposed to evaluate the efficiency. In our paper the level of efficiency represents the level of corporate performance. The efficiency is in our case represented as a share of output in weighted sum of inputs. In other words, it represents a certain degree to which desirable outputs can o?set environmental, social and corporate governance (ESG) indicators. Hence we have to consider appropriate inputs (data for calculation of ESG key performance indicators) and three outputs (complex environmental, social and corporate governance indicator). In the next stage, the fourth inputs (the chosen economic indicators) are added. Their impacts on the changing of e?ciency score is under consideration with regression analysis, which is done by Maple. At the same time, we have observed a possible connection between the achieved e?ciency score and corporate sustainability. In addition to e?ciency score DEA method provides weights of particular inputs and outputs. These weights are used to ?nd those contributions of particular criteria to the achieved score. This enables us to determine the strong and weak points of the or-ganization.
  • Data envelopment analysis (DEA) gives a very powerful tool to decision makers in an organization. DEA is then a natural choice for an application of operations research or mathematical modelling of an evaluation of corporate performance. This method was initially proposed to evaluate the efficiency. In our paper the level of efficiency represents the level of corporate performance. The efficiency is in our case represented as a share of output in weighted sum of inputs. In other words, it represents a certain degree to which desirable outputs can o?set environmental, social and corporate governance (ESG) indicators. Hence we have to consider appropriate inputs (data for calculation of ESG key performance indicators) and three outputs (complex environmental, social and corporate governance indicator). In the next stage, the fourth inputs (the chosen economic indicators) are added. Their impacts on the changing of e?ciency score is under consideration with regression analysis, which is done by Maple. At the same time, we have observed a possible connection between the achieved e?ciency score and corporate sustainability. In addition to e?ciency score DEA method provides weights of particular inputs and outputs. These weights are used to ?nd those contributions of particular criteria to the achieved score. This enables us to determine the strong and weak points of the or-ganization. (en)
Title
  • Optimization of Corporate Performance Using Data Envelopment Analysis with Maple
  • Optimization of Corporate Performance Using Data Envelopment Analysis with Maple (en)
skos:prefLabel
  • Optimization of Corporate Performance Using Data Envelopment Analysis with Maple
  • Optimization of Corporate Performance Using Data Envelopment Analysis with Maple (en)
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  • RIV/62156489:43110/14:00223932!RIV15-GA0-43110___
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  • P(GA14-23079S)
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  • 34947
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  • RIV/62156489:43110/14:00223932
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  • Corporate Performance; Maple; Optimization; Data Envelopment Analysis (en)
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  • [18E75D2A557E]
http://linked.open...v/mistoKonaniAkce
  • Lisabon
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  • London
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  • In Aurelio Araujo et al. Engineering Optimization 2014
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  • Chvátalová, Zuzana
  • Hřebíček, Jiří
  • Soukopová, Jana
  • Trenz, Oldřich
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  • CRC Press
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  • 978-1-138-02725-1
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  • 43110
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