20.500.12556/DKUM-93797 A new logistic regression approach for the identification of factors affecting the partition of costs and risk in the international trade Background: The selection of the right Incoterms is crucial for minimising risks and costs in international trade. This paper aims to develop a model that identifies the key factors influencing the selection of Incoterms. The main contribution of the research is the creation of a new statistical modelling process that effectively identifies the variables impacting trade costs and risk. The study uses import and export data from non-EU countries in the context of a Slovenian case study. Methods: A novel model selection mechanism is developed, combining the logistic regression (logit) modelling with Monte Carlo simulations to identify influential factors in Incoterms selection. This mechanism incorporates heuristic techniques, which guide a sequential process of gradually searching through logit model candidates to determine the bestfit model for both import and export scenarios. Results: The application of the new logit modelling procedure reveals that the delivery location is the most significant factor affecting Incoterms selection. Additionally, the value of goods and the type of transport (containerised vs. noncontainerised) also have a considerable influence. For imports, the mass of goods is found to be a significant factor as well. Conclusions: The research results offer valuable insights for companies formulating their international business strategies. By selecting the appropriate Incoterm, companies can reduce transportation risks and costs. Managing costs and risks is especially important for higher-value goods. The research finds that, for lower-value goods, sellers often take on associated costs and risks. This pattern is particularly notable with imports, where sellers are more likely to assume responsibility for lighter-weight goods. international trade Incoterms Incoterms selection logit regression Monte Carlo simulation mednarodna trgovina Incoterms izbira Incoterms logit regresija simulacija Monte Carlo true false true Wyższa Szkoła Logistyki Angleški jezik Slovenski jezik Znanstveno delo 2025-07-22 03:10:00 2025-07-22 08:25:24 2025-07-23 03:11:06 0000-00-00 00:00:00 2024 0 0 Str. 483-496 št. 4 Letn. 20 Oct./Dec. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-09-02 2024-10-01 2024-12-16 519.6:339.56 222236163 10.17270/J.LOG.001001 1734-459X https://www.logforum.net/volume20/issue4/abstract-4.html 1 97529d4a-6698-11f0-b4a7-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=193883 A_new_logistic_regression_Sternad_2024.pdf A_new_logistic_regression_Sternad_2024.pdf 1 8679D71E6EB60B89998C22AFD5248C65 2be6068e13669a5981f758a85833fa29e4f5b2edd9698614122579beea7b2a8b 56388d40-66c4-11f0-b4a7-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=193888 Fakulteta za logistiko 0 0 0