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Vpliv pogodbenih in organizacijskih modelov ter obvladovanja tveganja na uspešnost javno-zasebnih partnerstev : magistrsko delo
ID Mezgec, Andraž (Author), ID Šelih, Jana (Mentor) More about this mentor... This link opens in a new window

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PID: 20.500.12556/rul/a99ff46e-f5c3-48cc-9a3e-14fa376b2853

Abstract
V magistrskem delu je obravnavano področje tveganj, ki se pojavlja v javno zasebnih partnerstvih (JZP). Gre za organizacijsko obliko graditve, ki se v Sloveniji vse bolj pogosto pojavlja, saj lahko z njegovo uporabo zmanjšamo javno zadolževanje. Ker gre za dolgotrajno sodelovanje med pogodbenimi partnerji, je potrebno identificirati in ovrednotiti potencialna tveganja, ki se lahko pojavijo med izvajanjem JZP. V skladu s slovensko zakonodajo je delitev poslovnih tveganj obvezen pogoj, da je posamezno partnerstvo opredeljeno kot javno-zasebno partnerstvo. Uporaba JZP je povezana z različnimi tveganji za deležnike, zato se v predstavljenem raziskovalnem delu osredotočamo na načine obvladovanj tveganj, tehnike analiz tveganj ter organizacijske oblike v posameznih oblikah javno zasebnih partnerstev. Zaradi kompleksnosti in interdisciplinarnosti področja javno-zasebnih partnerstev so potrebni različni pristopi k obvladovanju tveganj, tako s stališča obvladovanja organizacij, projektnega vodenja in gradbeništva. V magistrski nalogi so predstavljene različne metode obvladovanja tveganj. Na tej osnovi podajamo predlog modela za določitev skupnega tveganja projekta z uporabo numerične metode simulacij Monte Carlo. Na podlagi izračunane pričakovane vrednosti in variance stroška tveganja je možna končna analiza sposobnosti prevzemanja tveganja po predstavljenem modelu delitve tveganj. Dobljeni rezultati so lahko v oporo odločanju vseh deležnikov v javno-zasebnem partnerstvu in s tem povečujejo verjetnost uspeha obravnavanega partnerstva.

Language:Slovenian
Keywords:gradbeništvo, magistrska dela, Javno-zasebna partnerstva, modeli JZP, obvladovanje tveganj, Monte Carlo analiza, delitev tveganj
Work type:Master's thesis
Typology:2.09 - Master's Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Place of publishing:Ljubljana
Publisher:[A. Mezgec]
Year:2016
Number of pages:XIX, 140 str.
PID:20.500.12556/RUL-85776 This link opens in a new window
UDC:334.012(043.3)
COBISS.SI-ID:7616097 This link opens in a new window
Publication date in RUL:27.09.2016
Views:2086
Downloads:568
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Secondary language

Language:English
Title:Public Private partnerships in context of risk management and contractual and organisational models
Abstract:
The thesis deals with risk management in Public Private Partnerships (PPP). The use of PPPs is increasing as it leads to lower public debt. The relationship between Public and Private partner is long term, therefore the associated risks have to be carefully identified and analysed. According to the Slovenian PPP Act, risk transfer between Public and Private partner is mandatory for the partnership if it is defined as Public Private Partnership. The use of PPPs is associated with different risks for all stakeholders involved, therefore the research was limited to the method of risk management, risk analysis techniques and organizational forms in the various forms of public-private partnerships. Due to the complexity and interdisciplinary nature of public-private partnerships, different approaches for risk management are required, both in terms of risk management in specific organization, project management and construction. The thesis presents different methods of risk management. Numerical Monte Carlo simulation model for the determination of the overall risk cost is proposed. On the basis of the calculated expected value and variance of the overall risk cost, further analysis of risk-bearing capacity according to the presented model of risk allocation, can be carried out. The results may support the stakeholders during the decision making process and as such, they may increase the probability of success of the PPP.

Keywords:civil engineering, master of science thesis, Public Private partnerships, PPP models, Risk management, Monte Carlo analysis, Risk allocation

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