57d847a1-351e-4f28-adf9-03b03bf76eb020250425064021823wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS2224-28991109-952610.37394/23207http://wseas.org/wseas/cms.action?id=40161720251720252210.37394/23207.2025.22https://wseas.com/journals/bae/2025.phpLejlaMünchFaculty of Business and Economics, Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, CZECH REPUBLICDavidHampelFaculty of Business and Economics, Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, CZECH REPUBLICIn the automotive industry, it is common for suppliers to agree with car manufacturers to limit liability or warranty for components supplied to reduce their financial risk in the event of poor-quality delivery. This may be, for example, a maximum amount or percentage of the contract value that the supplier agrees to pay to the car manufacturer in the case of claims by end customers. Currently, there is a phenomenon of non-recourse, where the supplier refuses to share warranty costs even though there is an agreement to this effect. Our research is based on data from a major car manufacturer, where 5451 transactions remained after data cleaning. Among other things, the transaction category, the status of the supplier contract fulfillment process, and the financial year of the transaction were tracked. It is possible to observe an increase in the number of transactions over time, which is mainly due to the progressive digitization of processes and their registration on the car manufacturer's side. Statistically significant differences in the rate of non-recourse across years have been demonstrated, with the COVID-19 pandemic period being characterized by a statistically significantly higher rate of supplier compliance. Based on the results, the non-recourse behavior of suppliers needs to be another parameter by which car manufacturers judge their suppliers.42520254252025719726https://wseas.com/journals/bae/2025/b265107-017(2025).pdf10.37394/23207.2025.22.63https://wseas.com/journals/bae/2025/b265107-017(2025).pdf10.37394/23207.2023.20.219Ma, H., Cost Estimation of Manufacturing Enterprises based on BP Neural Network and Big Data Analysis, WSEAS Transactions on Business and Economics, vol. 20, 2023, pp. 2567–2578. https://doi.org/10.37394/23207.2023.20.219. 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