Purpose: The electricity demand in Turkey has been increasing for a while. Hydropower is one
of the major electricity generation types to compensate this electricity demand in Turkey.
Private investors (domestic and foreign) in the hydropower electricity generation sector have
been looking for the most appropriate and satisfactory new private hydropower investment
(PHPI) options and opportunities in Turkey. This study aims to present a qualitative multiattribute
decision making (MADM) model, that is easy, straightforward, and fast for the
selection of the most satisfactory reasonable PHPI options during the very early investment
stages (data and information poorness on projects).
Design/methodology/approach: The data and information of the PHPI options was
gathered from the official records on the official websites. A wide and deep literature review
was conducted for the MADM models and for the hydropower industry. The attributes of the
model were identified, selected, clustered and evaluated by the expert decision maker (EDM)
opinion and by help of an open source search results clustering engine (Carrot2) (helpful for
also comprehension). The PHPI options were clustered according to their installed capacities
main property to analyze the options in the most appropriate, decidable, informative,
understandable and meaningful way. A simple clustering algorithm for the PHPI options was executed in the current study. A template model for the selection of the most satisfactory PHPI
options was built in the DEXi (Decision EXpert for Education) and the DEXiTree software.
Findings: The basic attributes for the selection of the PHPI options were presented and
afterwards the aggregate attributes were defined by the bottom-up structuring for the early
investment stages. The attributes were also analyzed by help of Carrot2. The most satisfactory
PHPI options in Turkey in the big options data set were selected for each PHPI options cluster
by the EDM evaluations in the DEXi.
Originality/value: The recommended DEXi PHPI selection model by the search results
clustering engine within a country wise case offered the possibility of easy, meaningful and
satisfying continental or worldwide applications for the private investors and the international
financial institutions such as the African Development Bank, or the World Bank was the main
contribution.
