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

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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.

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Acknowledgements

The authors would like to thank the two anonymous Reviewers, whose comments have helped to improve this paper.

For the entire research process of this study, the authors have benefited the PRD fund of the University of Catania “Indebtedness, bank credit and economic activities”. The first author has also benefited the “FFABR” fund of the Ministry of Education, University and Research of the Italian government.

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  1. Department of Economics and Business, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Silvia Angilella & Maria Rosaria Pappalardo

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  1. Silvia Angilella
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  2. Maria Rosaria Pappalardo
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Correspondence to Maria Rosaria Pappalardo.

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Appendix

Appendix

See Tables 11,12, 13, 14, 15 and 16.

Table 11 Cases (1) and (2) “From first to Seventh Scenario”: rank acceptability indices (all the data are expressed in percent.)
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Table 12 Cases (1) and (2) “From first to Seventh Scenario”: downward cumulative rank acceptability indices (all the data are expressed in percent)
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Table 13 Rank acceptability indices on financial macro-criterion
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Table 14 Rank acceptability indices on sustainability macro-criterion
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Table 15 Rank acceptability indices on technical macro-criterion
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Table 16 Rank acceptability indices on market macro-criterion
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Angilella, S., Pappalardo, M.R. Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis. Oper Res Int J 22, 299–370 (2022). https://doi.org/10.1007/s12351-020-00567-5

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