N.T. Nguyen et al. (Eds.): Adv. Methods for Comput. Collective Intelligence, SCI 457, pp. 333–343. DOI: 10.1007/978-3-642-34300-1_32 © Springer-Verlag Berlin Heidelberg 2013 Crisis Management Model and Recommended System for Construction and Real Estate Artūras Kaklauskas 1,* , Edmundas Kazimieras Zavadskas 1 , Paulius Kazokaitis 1 , Juozas Bivainis 1 , Birute Galiniene 2 , Maurizio d'Amato 3 , Jurga Naimaviciene 1 , Vita Urbanaviciene 1 , Arturas Vitas 2 , Justas Cerkauskas 1 1 Vilnius Gediminas Technical University, Sauletekio av. 11, Vilnius, LT-10223, Lithuania 2 Vilnius University, 3 Universiteto St, LT-01513 Vilnius, Lithuania 3 Technical University of Bari, via Amendola, 126/B - 70126 Bari, Italy arturas.kaklauskas@st.vgtu.lt 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. Keywords: construction, real estate, crisis management, quantitative and qualitative methods, global development trends, alternatives, Lithuania, Model, System, forecasting. 1 Introduction Various econometrics (e.g., Keynesian models, time-series analysis using multiple regression, Box-Jenkins analysis, Time-varying Parameter Model, duration statistical model, multivariate Logit model, competing-risks hazard models with time-varying covariates, dummy variable approach) and operations research (statistical analysis (discriminant analysis [1], Logit and Probit regression models [2]), artificial neural network models (fuzzy clustering and self-organizing neural networks [3], the back- propagation neural networks model [4]), multiple criteria decision making [5]-[7], artificial intelligence (the support vector machine [8], k-nearest neighbor algorithm [4], and decision tree [9], etc.) methods and models in the construction and real estate sector as well as in separate segments are being applied for crisis management worldwide today. Technical approaches of operations research (decision support systems [5], [10], [11], expert systems [12], mathematical programming [13], multicriteria decision methods [5]) are used for crisis management in different construction and real estate fields. * Corresponding author.