Application of Multiple Criteria Methods to Investment Project Selection - a Case Study
DOI:
https://doi.org/10.18559/SOEP.2018.3.6Keywords:
Case study, Investment analysis, Investment decisions, Investment consulting, InvestmentAbstract
The article is devoted to the project selection problem. A case study is presented, illustrating the procedure, which was applied to select an expensive production equipment - laser punching. The selection process consisted of two stages: (1) functional and technical parameterization, (2) the selection of a particular machine (puncher). The goal of the paper is to describe the advantages and disadvantages of the procedure applied in practice and to present in what way multiple criteria approach can be used for solving the problem. Taking into account the real decision process, the requirements for decision aiding procedure are formulated. An proposal of such method is also presented. The method takes into account that the decision is made collectively (group decision making).Downloads
References
Costa, J. P., Melo, P., Godinho, P. i Dias, L. C. (2003). The AGAP system: a GDSS for project analysis and evaluation. European Journal of Operational Research, 145(2), 287-303. doi:10.1016/S0377-2217(02)00535-0.
Doerner, K. F., Gutjahr, W. J., Hartl, R. F., Strauss, C. i Stummer, C. (2006). Pareto ant colony optimization with ILP preprocessing in multiobjective project portfolio selection. European Journal of Operational Research, 171(3), 830-841. doi:10.1016/j. ejor.2004.09.009.
Ferrari, P. (2003). A method for choosing from among alternative transportation projects. European Journal of Operational Research, 150(1), 194-203. doi:10.1016/ S0377-2217(02)00463-0.
Ghorbani, S. i Rabbani, M. (2009). A new multi-objective algorithm for a project selection problem. Advances in Engineering Software, 40(1), 9-14. doi:10.1016/j. advengsoft.2008.03.002.
Graves, S. B. i Ringuest, J. L. (2003). Models & methods for project selection: concepts from management science, finance and information technology. Dordrecht: Kluwer Academic Publishers.
Heidenberger, K. i Stummer, Ch. (1999). Research and development project selection and resource allocation: a review of quantitative modelling approaches. International Journal of Management Reviews, 1(2), 197-224. doi:10.1111/1468-2370.00012.
Kearns, G. S. (2004). A multi-objective, multi-criteria approach for evaluating IT investments: results from two case studies. Information Resources Management Journal, 17(1), 37-62.
Lootsma, F. A., Mensch, T. C. A. i Vos F. A. (1990). Multi-criteria analysis and budget reallocation in long-term research planning. European Journal of Operational Research, 47(3), 293-305. doi:10.1016/S0377-2217(90)90216-X.
Marcinek, K. (1998). Finansowa ocena przedsięwzięć inwestycyjnych przedsiębiorstw. Katowice: Wydawnictwo Akademii Ekonomicznej im. Karola Adamieckiego.
Mavrotas, G., Diakoulaki, D. i Capros, P. (2003). Combined MCDA-IP approach for project selection in electricity market. Annals of Operations Research, 120 (1-4), 159-170. doi:10.1023/A:1023382514182.
Mohanty, R. P., Agarwal, R., Choudhury, A. K. i Tiwary M. K. (2005). A fuzzy ANP-based approach to R&D project selection: A case study. International Journal of Production Research, 43(24), 5199-5216. doi:10.1080/00207540500219031.
Moselhi, O. i Deb, B. (1993). Project selection considering risk. Construction Management and Economics, 11(1), 45-52. doi:10.1080/01446199300000063.
Nowak, M. (2005). Investment projects' evaluation by simulation and multiple criteria decision making procedure. Journal of Civil Engineering and Management, 11(3), 193-202. doi:10.1080/13923730.2005.9636350.
Nowak, M. (red.). (2014). Wspomaganie decyzji w planowaniu projektów. Warszawa: Difin.
Rabbani, M., Aramoon Bajestani, M. i Baharian Khoshkhou, G. (2010). A multi- -objective particle swarm optimization for project selection problem. Expert Systems with Applications, 31(1), 315-321. doi:10.1016/j.eswa.2009.05.056.
Roy, B. (1990). Wielokryterialne wspomaganie decyzji. Warszawa: Wydawnictwa Naukowo-Techniczne.
Saaty, T. L. (1980). The analytical hierarchy process. New York: McGraw-Hill.
Trzaskalik T. (red.). (2014). Wielokryterialne wspomaganie decyzji. Warszawa: Polskie Wydawnictwo Ekonomiczne.
Wong, E. T. T., Norman, G. i Flanagan, R. (2000). A fuzzy stochastic technique for project selection. Construction Management and Economics, 18(4), 407-414. doi:10.1080/01446190050024824.
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