APA 6th Edition Düerkop, S. i Huth, M. (2016). RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE. Ekonomski vjesnik, 29 (S), 11-19. Preuzeto s https://hrcak.srce.hr/171941
MLA 8th Edition Düerkop, Sascha i Michael Huth. "RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE." Ekonomski vjesnik, vol. 29, br. S, 2016, str. 11-19. https://hrcak.srce.hr/171941. Citirano 22.01.2021.
Chicago 17th Edition Düerkop, Sascha i Michael Huth. "RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE." Ekonomski vjesnik 29, br. S (2016): 11-19. https://hrcak.srce.hr/171941
Harvard Düerkop, S., i Huth, M. (2016). 'RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE', Ekonomski vjesnik, 29(S), str. 11-19. Preuzeto s: https://hrcak.srce.hr/171941 (Datum pristupa: 22.01.2021.)
Vancouver Düerkop S, Huth M. RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE. Ekonomski vjesnik [Internet]. 2016 [pristupljeno 22.01.2021.];29(S):11-19. Dostupno na: https://hrcak.srce.hr/171941
IEEE S. Düerkop i M. Huth, "RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE", Ekonomski vjesnik, vol.29, br. S, str. 11-19, 2016. [Online]. Dostupno na: https://hrcak.srce.hr/171941. [Citirano: 22.01.2021.]
Sažetak Logistical infrastructure builds the backbone of an economy. Without an effective logistical infrastructure in place, the supply for both enterprises and consumers might not be met. But even a high-quality logistical infrastructure can be threatened by risks. Thus, it is important to identify, analyse, and evaluate risks for logistical infrastructure that might threaten logistical processes. Only if those risks are known and their impact estimated, decision makers can implement counteractive measures to reduce risks.
In this article, we develop a network-based approach that allows for the evaluation of risks and their consequences onto the logistical network. We will demonstrate the relevance of this approach by applying it to the logistics network of the central German state of Hesse. Even though transport data is extensively tracked and recorded nowadays, typical daily risks, like accidents on a motorway, and extraordinary risks, like a bridge at risk to collapse, terrorist attacks or climate-related catastrophes, are not systematically anticipated. Several studies unveiled recently that the overall impact for an economy of possible failures of single nodes and/or edges in a network are not calculated, and particularly critical edges are not identified in advance. We address this information gap by a method that helps to identify and quantify risks in a given network. To reach this objective, we define a mathematical optimization model that quantifies the current “risk-related costs” of the overall network and quantify the risk by investigating the change of the overall costs in the case a risk is realized.