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1.
A methodology for improving strategic decisions in social systems with a lack of information
Carlos A. Legna Verna, Andrej Škraba, 2010, original scientific article

Abstract: The design of strategies for social systems requires the use of qualitative information owing to the fact that quantitative information can be insufficient to solve the problems involved. The information that the specialists and the decision makers obtain is often incomplete and unreliable. Nevertheless, leaders have to make strategic decisions despite these deficiencies which should be based on the formal models (Kljajić et al. 2000; Škraba et al, 2003; Škraba et al 2007). This paper describes a methodology elaborated to design the strategy of the city of Santa Cruz (on the Canary Islands). It has two main sections: the elaboration of a qualitative model and the use of System Dynamics. We combine them in a way that allows mixing qualitative and quantitative information to achieve a better understanding of the structure of the region, to know the tendencies of the present scenario and to estimate of the effects of alternative strategic decisions. We have obtained these results working with scarce quantitative information. This methodology may be applied to any social systems with similar characteristics.
Keywords: qualitative models, system dynamics, social strategies
Published: 10.07.2015; Views: 349; Downloads: 163
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2.
Obvladovanje tveganj pri »peer to peer« posojilih
Andrej Blagotinšek, 2017, master's thesis

Abstract: Nove digitalne tehnologije botrujejo procesu preoblikovanja obstoječih vrednostih verig finančnih produktov oz. storitev. »P2P« posojila so nov in inovativen način tako investiranja presežkov finančnih sredstev kot tudi prejemanja finančnega kapitala. Število tovrstnih posojil konstantno raste, vendar posojilodajalci niso profesionalni investitorji. Posojilodajalci prevzemajo veliko tveganje, saj so »P2P« posojila izdana brez zavarovanja. V ta namen »P2P« platforme izdajajo historične podatke o posojilojemalcih. V delu se osredotočamo na identifikacijo tveganj, ki so prisotna pri tovrstnem investiranju in na napovedovanje možnosti neplačil posojil. Empirična študija analizira podatke pridobljene iz platforme Bondora (N=1823) od leta 2009 do 2015. Opravili smo statistično analizo spremenljivk. Razvili smo Logit model za napovedovanje neplačil. Kakovost modela smo preverjali z ROC krivuljo, optimizacijo modela pa na osnovi uravnoteženja klasifikacijske natančnosti, kjer smo dololčili optimalno presečno vrednost. Rezultati so pokazali, da kreditni model za napovedovanje neplačil zmanjšuje verjetnost finančne izgube pri »P2P« investiranju.
Keywords: kreditno tveganje, verjetnost neplačila, »P2P« posojila, LOGIT model, obvladovanje tveganj, C25 Discrete Regression and Qualitative Choice Models, G21 Banks, G17, Financial Forecasting and Simulation
Published: 27.10.2017; Views: 787; Downloads: 186
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