- EconStor
- Universitat Politècnica de Catalunya (UPC), BarcelonaTech
- The School of Industrial, Aerospace and Audiovisual Engineering of Terrassa (ESEIAAT), Universitat Politècnica de Catalunya (UPC)
- Journal of Industrial Engineering and Management (JIEM), Universitat Politècnica de Catalunya (UPC), BarcelonaTech
Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen:
https://hdl.handle.net/10419/188767
Autor:innen:
Erscheinungsjahr:
2016
Quellenangabe:
[Journal:] Journal of Industrial Engineering and Management (JIEM) [ISSN:] 2013-0953 [Volume:] 9 [Issue:] 1 [Publisher:] OmniaScience [Place:] Barcelona [Year:] 2016 [Pages:] 152-178
Verlag:
OmniaScience, Barcelona
Zusammenfassung:
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 multi-attribute 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.
Schlagwörter:
Carrot2
cluster
clustering
decision
DEX
DEXi
DEXiTree
hydropower
investment
private hydropower plant investments
qualitative scaled attributes
search results clustering engine
Turkey
cluster
clustering
decision
DEX
DEXi
DEXiTree
hydropower
investment
private hydropower plant investments
qualitative scaled attributes
search results clustering engine
Turkey
Persistent Identifier der Erstveröffentlichung:
Dokumentart:
Article
Datei(en):
Datei
Beschreibung
Größe
Format
Publikationen in EconStor sind urheberrechtlich geschützt.