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Central European Journal of Operations Research

, Volume 27, Issue 3, pp 759–781 | Cite as

Modelling decision knowledge for the evaluation of water management investment projects

  • Marjan Brelih
  • Uroš RajkovičEmail author
  • Tomaž Ružič
  • Blaž Rodič
  • Daniel Kozelj
Original Paper

Abstract

Water resources are facing increased stress owing to population growth and environmental pollution. Water utility companies are concerned about this, and they are increasingly utilizing decision support systems to achieve higher transparency in utility investment project selection and to improve the economic management of water supply systems and resource exploitation. However, utility investment project decisions involve a diverse set of quantitative and qualitative criteria. This makes the selection of an appropriate decision method difficult. We have developed a novel hybrid multi-criteria decision method that integrates quantitative and qualitative criteria value domains in the same decision-making model and applied it to a real-world case involving a large multi-utility operator. The method is based on the decision expert and multi-attribute utility theory methods, which were modified to facilitate conversion between criteria domains. Our innovative approach allows for the use of the expressive power and comprehensibility of the qualitative method while maintaining the precision of the quantitative method, enabling decision makers to differentiate more easily between worthwhile and less feasible utility investment projects in the field of safe drinking water supply. The proposed method is applicable to a wide range of decision problems involving a diverse set of decision criteria.

Keywords

Multi-criteria decision method Modelling decision knowledge Quantitative and qualitative knowledge modelling Investment project ranking Effective water utility management 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Organizational SciencesUniversity of MariborKranjSlovenia
  2. 2.Petrol d.d., LjubljanaLjubljanaSlovenia
  3. 3.Faculty of Information Studies in Novo MestoNovo MestoSlovenia
  4. 4.Faculty of Civil and Geodetic EngineeringUniversity of LjubljanaLjubljanaSlovenia

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