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Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model

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Abstract

Current financial and economic crisis, as well as growing environmental pressures put seriously under question traditional development patterns. The need to develop alternative models able to address current economic situation through the exploitation of sustainable patterns is of crucial importance. The innovation of this current study is the incorporation of energy and environmental corporate responsibility (EECR) in decision making, supporting particularly the development of a new model for investment evaluation. A bi-objective programming model is introduced in order to provide the Pareto optimal portfolios (Pareto set) based on the net present value of projects and the EECR score of firms. A systematic decision making approach using Monte Carlo simulation and multi-objective programming is also developed in order to deal with the inherent uncertainty in the objective functions’ coefficients. The robustness of the Pareto set as a whole, as well as the robustness of the individual Pareto optimal portfolios is also assessed. The proposed approach facilitates banking organizations and institutions to the selection of firms applying for financial support and credit granting, within the frame of their EECR. Finally, an illustrative real-world application of the proposed model is presented.

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Acknowledgments

The authors would like to thank the anonymous referees. This research has been co-financed by the European Union (European Social Fund) and Greek national funds through the Operational Program “Education and Lifelong Learning”. Olena Pechak would like to thank the Hellenic State Scholarship Foundation (IKY) for financial support of her PhD studies.

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Correspondence to Haris Doukas.

Appendix

Appendix

See Table 4.

Table 4 Projects’ data

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Xidonas, P., Doukas, H., Mavrotas, G. et al. Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model. Ann Oper Res 247, 395–413 (2016). https://doi.org/10.1007/s10479-015-1820-x

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  • DOI: https://doi.org/10.1007/s10479-015-1820-x

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