Acta Univ. Agric. Silvic. Mendelianae Brun. 2015, 63(1), 193-200 | DOI: 10.11118/actaun201563010193
Decision-making on Implementation of IPO Under Topological Uncertainty
- 1 Department of Informatics, Faculty of Business and Management, Brno University of Technology, Kolejní 2906/4, 612 00 Brno, Czech Republic
- 2 Department of Economics, Faculty of Business and Management, Brno University of Technology, Kolejní 2906/4, 612 00 Brno, Czech Republic
IPO (Initial Public Offering) is a complex decision making task which is always associated with different types of uncertainty. Poor accuracies of available probabilities of lotteries e.g. quantification of investor interest is studied in the first part of this paper (Meluzín, Doubravský, Dohnal, 2012). However, IPO is often prohibitively ill-known. This paper takes into consideration the fact that decision makers cannot specify the structure/topology of the relevant decision tree. It means that one IPO task is specified by several (partially) different decision trees which comes from different sources e.g. from different teams of decision makers/experts. A flexible integration of those trees is based on fuzzy logic using the reconciliation (Meluzín, Doubravský, Dohnal, 2012). The developed algorithm is demonstrated by a case study which is presented in details. The IPO case integrates two partially different decision trees.
Keywords: IPO, decision-making, uncertainty, linear programming, fuzzy logic
Grants and funding:
This paper was supported by grant FP-S-13-2148 'The Application of ICT and Mathematical Methods in Business Management' of the Internal Grant Agency at Brno University of Technology. The paper is supported by the Czech Science Foundation. Name of the Project: IPO Strategy - Specific Approaches in the CEE Region. Registration No. 13-38047S.
Prepublished online: March 14, 2015; Published: April 1, 2015 Show citation
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References
- APOSTOLAKIS, G. and LEE, Y. T. 1997. Methods for the estimation of confidence bounds for the top-event unavailability of decision trees. Nuclear Engineering and Design, 41(3): 411-419. DOI: 10.1016/0029-5493(77)90082-6
Go to original source...
- DANIELSON, M., EKENBERG, L. and LARSSON, A. 2007. Distribution of expected utility in decision trees. International Journal of Approximate Reasoning, 46(2): 387-407. DOI: 10.1016/j.ijar.2006.09.012
Go to original source...
- DOHNAL, M., VYKYDAL, J. and KVAPILIK, M. 1992. Practical uncertainty assessment of reasoning paths (fault trees) under total uncertainty ignorance. International Journal of Loss Prevention, 5(2): 125-131. DOI: 10.1016/0950-4230(92)80009-W
Go to original source...
- FEDRIZZI, M., KACPRZYK, J. and VERDEGAY, J. L. 1991. A survey of fuzzy optimization and mathematical programming. Lecture Notes in Economics and Mathematical Systems, 368: 15-28. DOI: 10.1007/978-3-642-45700-5_2
Go to original source...
- HUANG, G. and DAN MOORE, R. 1993. Grey linear programming, its solving approach, and its application. International Journal of Systems Science, 24(1): 159-172. DOI: 10.1080/00207729308949477
Go to original source...
- KIKUCHI, S. A. 2000. Method To Defuzzify The Fuzzy Number: Transportation Problem Application. Fuzzy Sets And Systems, 116(1): 3-9. DOI: 10.1016/S0165-0114(99)00033-0
Go to original source...
- LAI, Y. J. and HWANG, C. I. 1992. Fuzzy Mathematical Programming: Methods and Applications. Berlin: Springer-Verlag.
Go to original source...
- MELUZÍN, T., DOUBRAVSKÝ, K. and DOHNAL, M. 2012. Decision-Making on IPO Implementation under Conditions of Uncertainty. Sborník vědeckých prací University Pardubice, 18(24): 124-136.
- NIE, G., ZHANG, L., LIU, Y. et al. 2009. Decision analysis of data mining project based on Bayesian risk. Expert Systems with Applications, 36(3, Part 1): 4589-4594. DOI: 10.1016/j.eswa.2008.05.014
Go to original source...
- TAN, R. R., BRIONES, L. M. A. and CULABA, A. B. 2007. Fuzzy data reconciliation in reacting and non-reacting process data for life cycle inventory analysis. Journal of Cleaner Production, 15(10): 944-949. DOI: 10.1016/j.jclepro.2005.09.001
Go to original source...
- WATSON, S. R. 1994. The meaning of probability in probabilistic safety analysis. Reliability Engineering and System Safety, 45(3): 261-269. DOI: 10.1016/0951-8320(94)90142-2
Go to original source...
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