A multi-criteria performance analysis of Initial Public Offering (IPO) firms using CRITIC and VIKOR methods
Abstract
As Initial Public Offering (IPO) is a significant milestone in the financial strategy of a firm, this study aims to evaluate performance of IPOs using multiple measures including accounting-based performance (ABP), value-based performance (VBP) and overall performance (OP) in the pre-and post-IPO periods. Therefore, we present two combined approaches based on a compromise MCDM method-VIKOR and objective weighting methods-CRITIC and MW (Mean Weight) to evaluate and rank IPOs to help shareholders with understanding on how their performance changes under the different measures. Since the compromise solution (one or a set) proposed by VIKOR depends substantially on criteria weights, VIKOR-CRITIC can show more realistic results because of the differential weights assigned to criteria by CRITIC. In this study, a case study is conducted in order to evaluate the performance of Turkish IPOs based on ABP, VBP and OP measures using the combined methods. The results show that the compromise solution results obtained by VIKOR-CRITIC may be a guideline for investors in making more profitable investment decisions before leaping into any investment decision.
First published online: 27 Mar 2017
Keyword : initial public offering, accounting-based performance, value-based performance, MCDM, VIKOR, CRITIC, objective weights
How to Cite
Yalçin, N., & Ünlü, U. (2018). A multi-criteria performance analysis of Initial Public Offering (IPO) firms using CRITIC and VIKOR methods. Technological and Economic Development of Economy, 24(2), 534–560. https://doi.org/10.3846/20294913.2016.1213201
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Hsu, L.-C. 2014. A hybrid multiple criteria decision-making model for investment decision making, Journal of Business Economics and Management 15(3): 509–529. https://doi.org/10.3846/16111699.2012.72256
Hsu, L.-C. 2015. Using a decision-making process to evaluate efficiency and operating performance for listed semiconductor companies, Technological and Economic Development of Economy 21(2): 301–331. https://doi.org/10.3846/20294913.2013.876689
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Kazan H.; Özdemir, Ö. 2014. Financial performance assessment of large scale conglomerates via TOP¬SIS and critic methods, Journal of Management and Sustainability 3(4): 203–224.
Kim, K. A.; Kitsabunnarat, P.; Nofsinger, J. R. 2004. Ownership and operating performance in an emerging market: evidence from Thai IPO firms, Journal of Corporate Finance 10(3): 355–381. https://doi.org/10.1016/S0929-1199(02)00019-6
Lee, S.; Kim, W. G. 2009. EVA, refined EVA, MVA, or traditional performance measures for the hospi¬tality industry?, International Journal of Hospitality Management 28(3): 439–445. https://doi.org/10.1016/j.ijhm.2009.01.004
Liu, H. C.; You, J. X.; You, X. Y.; Shan, M. M. 2015. A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method, Applied Soft Computing 28: 579–588. https://doi.org/10.1016/j.asoc.2014.11.036
Liu, H.-C.; Liu, L.; Wu, J. 2013. Material selection using an interval 2-tuple linguistic VIKOR method considering subjective and objective weights, Materials and Design 52: 158–167. https://doi.org/10.1016/j.matdes.2013.05.054
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Mardani, A.; Zavadskas, E. K.; Govindan, K.; Amat Senin, A.; Jusoh, A. 2016. VIKOR technique: a systematic review of the state of the art literature on methodologies and applications, Sustainability 8(1): 1–38. https://doi.org/10.3390/su8010037
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Opricovic, S. 1998. Multi-criteria optimization of civil engineering systems: PhD dissertation. Belgrade, Faculty of Civil Engineering.
Opricovic, S. 2011. Fuzzy VIKOR with an application to water resources planning, Expert Systems with Applications 38(10): 12983–12990. https://doi.org/10.1016/j.eswa.2011.04.097
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