Abstract
Integrated analysis and rational decision-making at the micro-, meso- and macro-levels are needed to mitigate the effects of recession on the construction and real estate sector. Crisis management involves numerous aspects that should be considered in addition to making economic, political and legal/regulatory decisions. These must include social, culture, ethical, psychological, educational, environ- mental, provisional, technological, technical, organizational and managerial aspects. This article presents a model and system for such considerations and discusses certain composite parts of it.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Haslem, J.A., Scheraga, C.A., Bedingfield, J.P.: An analysis of the foreign and domestic balance sheet strategies of the U.S. banks and their association to profitability performance. Management International Review (1992)
Canbas, S., Cabuk, A., Kilic, S.B.: Prediction of commercial bank failure via multivariate statistical analysis of financial structures: the Turkish case. European Journal of Operational Research 166, 528–546 (2005)
Alam, P., Booth, D., Lee, K., Thordarson, T.: The use of fuzzy clustering algorithm and self-organizing neural networks for identifying potentially failing banks: an experimental study. Expert Systems with Applications 18(3), 185–199 (2000)
Tam, K.Y.: Neural network models and the prediction of bank bankruptcy. Omega: The International Journal of Management Science 19(5), 429–445 (1991)
Pasiouras, F., Gaganis, C., Zopounidis, C.: Multicriteria classification models for the identification of targets and acquirers in the Asian banking sector. European Journal of Operational Research 204(2), 328–335 (2010)
Niemira, M.P., Saaty, T.L.: An Analytic Network Process model for financial-crisis forecasting. International Journal of Forecasting 20(4), 573–587 (2004)
García, F., Guijarro, F., Moya, I.: Ranking Spanish savings banks: A multicriteria approach. Mathematical and Computer Modelling 52(7-8), 1058–1065 (2010)
Boyacioglu, M.A., Kara, Y., Baykan, O.K.: Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: a comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey. Expert Systems with Applications 36(2), 3355–3366 (2009)
Frydman, H., Altman, E.I., Kao, D.: Introducing recursive partitioning for financial classification: the case of financial distress. Journal of Finance 40(1), 269–291 (1985)
Chen, X., Wang, X., Wu, D.D.: Credit risk measurement and early warning of SMEs: An empirical study of listed SMEs in China. Decision Support Systems 49(3), 301–310 (2010)
Gao, S., Xu, D.: Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering. Expert Systems with Applications 36(2/1), 1493–1504 (2009)
Lin, S.L.: A new two-stage hybrid approach of credit risk in banking industry. Expert Systems with Applications 36(4), 8333–8341 (2009)
Siriopoulos, C., Tziogkidis, P.: How do Greek banking institutions react after significant events?—A DEA approach. Omega: The International Journal of Management Science 38(5), 294–308 (2010)
Kaklauskas, A.: Multiple criteria decision support system for building life cycle. Habilitation Work. Technika, Vilnius (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kaklauskas, A. et al. (2013). Crisis Management Model and Recommended System for Construction and Real Estate. In: Nguyen, N., Trawiński, B., Katarzyniak, R., Jo, GS. (eds) Advanced Methods for Computational Collective Intelligence. Studies in Computational Intelligence, vol 457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34300-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-34300-1_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34299-8
Online ISBN: 978-3-642-34300-1
eBook Packages: EngineeringEngineering (R0)