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dc.contributor.authorWang, Chuanbin
dc.contributor.authorZhou, Hongxia
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.contributor.authorUbay, Gözde Gülseven
dc.contributor.authorUluer, Gülsüm Sena
dc.date.accessioned2020-11-20T07:03:13Z
dc.date.available2020-11-20T07:03:13Z
dc.date.issued2020en_US
dc.identifier.citationWang, C., Zhou, H., Dinçer, H., Yüksel, S., Ubay, G. G. ve Uluer, G. S. (2020). Analysis of electricity pricing in emerging economies with hybrid multi-criteria decision-making technique based on interval-valued intuitionistic hesitant fuzzy sets. IEEE Access, 8, 190882-190896. https://dx.doi.org/10.1109/ACCESS.2020.3031761en_US
dc.identifier.issn2169-3536
dc.identifier.urihttps://dx.doi.org/10.1109/ACCESS.2020.3031761
dc.identifier.urihttps://hdl.handle.net/20.500.12511/6037
dc.description.abstractThis study aims to analyze the factors that influence electricity prices. For this purpose, a hybrid multi-criteria decision-making (MCDM) model based on interval-valued intuitionistic hesitant fuzzy (IVIHF) sets is proposed. Firstly, a large literature review is carried out and 10 different factors that can affect electricity prices are determined. After that, IVIHF decision making trial and evaluation laboratory (DEMATEL) methodology is considered to find which factors are more significant in electricity prices. The finding shows that inflation rate and technological improvement are the most important criteria that affect electricity prices. Thus, the countries should consider expected future inflation rates to take necessary precautions to minimize volatility in electricity prices. Moreover, countries should follow current technologies regularly and make effective research and development to provide electricity with lower prices. In the second stage of the analysis, emerging 7 (E7) economies are ranked with respect to the performance related to the management of electricity price volatility. In this context, IVIHF VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach is considered. It is concluded that Russia and China are the most successful countries in keeping electricity prices away from volatility whereas India and Turkey get the latest order. Furthermore, a comparative evaluation is also implemented by considering IVIHF technique for order preference by similarity to ideal solution (TOPSIS) methodology to check the consistency of the analysis results. The results of both approaches are quite similar which gives information about the consistency of the ranking results. On the other hand, a sensitivity analysis is performed to ten different cases consecutively. It is determined that the ranking results are coherent by considering the changes in the criteria weights.en_US
dc.description.sponsorship2018 National Social Science Fund Key Project: Research on Financial Operation Innovation of Rural Residents' Property Income Poverty Alleviation Model in the New Eraen_US
dc.language.isoengen_US
dc.publisherIEEE-Institute of Electrical and Electronics Engineers Incen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectElectricity Pricesen_US
dc.subjectIVIHF DEMATELen_US
dc.subjectIVIHF VIKORen_US
dc.subjectIVIHF TOPSISen_US
dc.titleAnalysis of electricity pricing in emerging economies with hybrid multi-criteria decision-making technique based on interval-valued intuitionistic hesitant fuzzy setsen_US
dc.typearticleen_US
dc.relation.ispartofIEEE Accessen_US
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümüen_US
dc.authorid0000-0002-8072-031Xen_US
dc.authorid0000-0002-9858-1266en_US
dc.authorid0000-0002-6709-6495en_US
dc.authorid0000-0001-9477-4450en_US
dc.identifier.volume8en_US
dc.identifier.startpage190882en_US
dc.identifier.endpage190896en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1109/ACCESS.2020.3031761en_US
dc.identifier.wosqualityQ2en_US
dc.identifier.scopusqualityQ1en_US


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