Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach

Khalili, S.; Mehrjerdi, Y.; Zare, H.

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print) Quarterly Publication Volume 3 Issue 4 pp. 457-466 , 2014

Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach Pages 457-466 Download PDF

Authors: Saeed Khalili, Yahia Zare Mehrjerdi, Hassan Khademi Zare

Keywords:

Abstract: In the past, different methods for asset depreciation have been defined but most of these procedures deal with certain parameters and inputs. The availability of certain parameters in many real world situations is difficult and sometimes impossible. The primary objective of this paper is to obtain methods for calculating depreciation where some of the defined parameters are under uncertainty. Hence, by using the fuzzy science basics, extension principle and ?-cut technique, we rewrite some classic methods for calculating depreciation in fuzzy form. Then, for comparing the methods of fuzzy depreciation under uncertain conditions by using the formula of calculating the Fuzzy Present worth (FPW), the Present worth of Tax saving (PWTS) of any aforementioned methods has been obtained. Finally, since the amount of tax savings achieved for each of the methods is a fuzzy number, one of the fuzzy prioritization methods is used in order to select the best depreciation technique.

How to cite this paper

 Khalili, S., Mehrjerdi, Y & Zare, H. (2014). Choosing the best method of depreciating assets and after-tax economic analysis under uncertainty using fuzzy approach.Decision Science Letters , 3(4), 457-466.

Refrences

Ameli, M., Mirzazadeh, A., & Shirazi, M. (2013). Entropic Economic Order Quantity Model for Items with Imperfect Quality Considering Constant Rate of Deterioration under Fuzzy Inflationary Conditions. International Journal of Industiral Engineering & Producion Research, 24(1), 91-99.

Asady, B. (2010). The revised method of ranking LR fuzzy number based on deviation degree. Expert Systems with Applications, 37(7), 5056-5060.

Asady, B, & Zendehnam, A. (2007). Ranking fuzzy numbers by distance minimization. Applied Mathematical Modelling, 31(11), 2589-2598.

Berg, M., & Moore, G. (1989). The Choice of Depreciation Method under Uncertainty. Decision Sciences, 20(4), 643-654.

Berg, M., Waegenaere, A. D., & Wielhouwer, J. L. (2001). Optimal tax depreciation with uncertain future cash-flows. European Journal of Operational Research, 132(1), 197-209.

Blank, L. T., & Tarquin, A. J. (2008). Basics of engineering economy. McGraw-Hill Higher-Education.

Buckley, J. (2004). Fuzzy probabilities and fuzzy sets for web planning: Springer Verlag.

Chang, P. T., Huang, L. C., & Lin, H. J. (2000). The fuzzy Delphi method via fuzzy statistics and membership function fitting and an application to the human resources. Fuzzy Sets and Systems, 112(3), 511-520.

Cheng, C.-H. (1998). A new approach for ranking fuzzy numbers by distance method. Fuzzy sets and systems, 95(3), 307-317.

Chiu, C.-Y., & Park, C. (1994). Fuzzy cash flow analysis using present worth criterion. The Engineering Economist, 39(2), 113-138.

Chu, T.C., & Tsao, C.T. (2002). Ranking fuzzy numbers with an area between the centroid point and original point. Computers & Mathematics with Applications, 43(1), 111-117.

Davidson, S., & Drake, D. F. (1961). Capital Budgeting and the “Best” Tax Depreciation Method. The Journal of Business, 34(4), 442-452.

Davidson, S., & Drake, D. F. (1964). The “Best” tax depreciation method. The Journal of Business, 37(3), 258-260.

Huang, X. (2008). Mean-variance model for fuzzy capital budgeting. Computers & Industrial Engineering, 55(1), 34-47.

Jackson, S. B., Liu, X., & Cecchini, M. (2009). Economic consequences of firms’ depreciation method choice: Evidence from capital investments. Journal of Accounting and Economics, 48(1), 54-68.

Kahraman, C. (2001). Fuzzy versus probabilistic benefit/cost ratio analysis for public works projekts. Applied Mathematics and Computer Science, 11(3), 705-718.

Kahraman, C., & Kaya, ?. (2008). Depreciation and income tax Considerations under Fuzziness. In C. Kahraman (Ed.), Fuzzy Engineering Economics with Applications (Vol. 233, pp. 159-171): Springer Berlin Heidelberg.

Kahraman, C., Ruan, D., & Tolga, E. (2002). Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows. Information Sciences,142(1), 57-76.

Lee, E. S., & Li, R. J. (1988). Comparison of fuzzy numbers based on the probability measure of fuzzy events. Computers & Mathematics with Applications, 15(10), 887-896.

Moradi, B., Shakeri, H., & NamdarZangeneh, S. (2012). Solving the paradox of multiple IRR & apos; s in engineering economic problems by choosing an optimal-cut. International Journal of Industiral Engineering & Producion Research, 23(1), 45-52.

Nejad, A. M., & Mashinchi, M. (2011). Ranking fuzzy numbers based on the areas on the left and the right sides of fuzzy number. Computers & Mathematics with Applications, 61(2), 431-442.

Roemmich, R., Duke, G.L., & Gates, W.H. (1978). Maximizing the present value of tax savings from depreciation. Management Accounting, 56, 55-57.

Shahriari, M. (2011). Mapping fuzzy approach in engineering economics. International Research Journal of Finance and Economics(81), 6-12.

Wakeman, L. M. (1980). Optimal tax depreciation. Journal of Accounting and Economics, 2(3), 213-237.

Wang, Y. J., & Lee, H. S. (2008). The revised method of ranking fuzzy numbers with an area between the centroid and original points. Computers & Mathematics with Applications, 55(9), 2033-2042.

Wielhouwer, J. L., Waegenaere, A. D., & Kort, P. M. (2002). Optimal tax depreciation under a progressive tax system. Journal of Economic Dynamics and Control, 27(2), 243-269.

Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1), 3-28.