2014
DOI: 10.5267/j.dsl.2014.8.001
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Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

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Cited by 6 publications
(5 citation statements)
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References 23 publications
(24 reference statements)
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“…Akan and Kiraci (2023) developed a novel interval type-2 fuzzy depreciation approach and applied in maritime industry. Khalili et al (2014) rewritten some classic methods for calculating depreciation in fuzzy form by using extension principle and α-cut technique. Kahraman and Kaya (2008) presented fuzzy depreciation, fuzzy tax rate, and fuzzy minimum attractive rate of return methods with numerical examples.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Akan and Kiraci (2023) developed a novel interval type-2 fuzzy depreciation approach and applied in maritime industry. Khalili et al (2014) rewritten some classic methods for calculating depreciation in fuzzy form by using extension principle and α-cut technique. Kahraman and Kaya (2008) presented fuzzy depreciation, fuzzy tax rate, and fuzzy minimum attractive rate of return methods with numerical examples.…”
Section: Literature Reviewmentioning
confidence: 99%
“…(1), (2) and (3): D k is the annual depreciation for k th year (k = 1, 2,…., n); P is the purchase price of firm's asset; S is the final salvage value in n th year; n is the asset's useful life expressed in years; D Ã k is the cumulative depreciation for k th year (k = 1, 2,…., n); BV k is the book value for k th year (k = 1, 2,…., n). Due to the uncertainty of parameters n and S, the literature [12] suggests a fuzzy approach for definition of these parameters. At first, on base of Delphi fuzzy method can consider triangular fuzzy numbers for final salvage value and n term [4]:…”
Section: Straight-line Methodsmentioning
confidence: 99%
“…More specifically, it proposes a model for evaluating investments not only in times when cash flows are uncertain, but also in times when depreciation is uncertain. As mentioned above, several studies used fuzzy numbers for cash flow (Berg et al 2001 ; Berg and Moore 1989 ; Khalili et al 2014 ; Samaniego and Sun 2019 ) but in these studies, the depreciation amount was fixed or predictable. However, this is unrealistic for periods when cash flow is completely interrupted such as during the Covid-19 pandemic.…”
Section: Introductionmentioning
confidence: 99%
“…In this study, we developed a novel model for making investment decisions in times when the depreciation amount is uncertain. In a previous study, depreciating assets were included in the fuzzy system (Khalili et al 2014 ), but the IT2FSs approach was not applied in depreciation. As a result, our study varies from others as we integrated the IT2FSs approach into depreciation.…”
Section: Introductionmentioning
confidence: 99%