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Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis

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  • Silvia Angilella

    (University of Catania)

  • Maria Rosaria Pappalardo

    (University of Catania)

Abstract

This paper analyses the development of a performance assessment model for the most important listed companies operating in the energy sector, using a dataset obtained merging different sources. The construction of the model is based on a multiple criteria decision aid approach considering various indicators. The multidimensional nature of the topic in this paper requires the definition of a hierarchical structure of criteria, which has been aggregated into a composite index to obtain a final ranking for the energy companies under investigation. To handle with a hierarchical criteria structure and to take into account the space of fluctuations related to the imprecision on criteria weights, we employ the Hierarchy Stochastic Multi-Attribute Analysis. Thus, the proposed model is able to evaluate the performances of energy companies under different uncertainty scenarios. The results indicate that the first and last positions are quite robust in all considered scenarios, while the rankings relative to the intermediate positions vary widely by the chosen set of weights, exemplifying the need to rank companies based on multiple sets of criteria weights.

Suggested Citation

  • Silvia Angilella & Maria Rosaria Pappalardo, 2022. "Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis," Operational Research, Springer, vol. 22(1), pages 299-370, March.
  • Handle: RePEc:spr:operea:v:22:y:2022:i:1:d:10.1007_s12351-020-00567-5
    DOI: 10.1007/s12351-020-00567-5
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