DOI: 10.32725/978-80-7694-102-1.43



Inproforum 2024 (vol. 18):299-305 | DOI: 10.32725/978-80-7694-102-1.43

The evaluating the financial health of an inter-company network - evidence from the automotive industry

Pražáková Jaroslava, Šindlerová Sandra
University of South Bohemia in České Budějovice, Faculty of Economics, Studentská 13, 370 05 České Budějovice, Czech Republic

The aim of this paper is to assess the financial health of firms involved in an inter-firm network based on supplier-customer relationships. A real fragment of the automotive supply network was analysed. The financial health of each part of the network was assessed using a combination of the following bankruptcy and solvency models: IN01 model, Index Solvency, Taffler's model and Kralick's QT. The results of the bankruptcy models, K-means cluster analysis and functional analysis were complemented by core periphery analysis. By using these methods together, it was possible to identify the centre and periphery of the network and assess the differences in their financial health.

Keywords: networks, bankruptcy predictions, financial health, automotive industry

Published: January 11, 2025  Show citation

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Jaroslava, P., & Sandra, Š. (2024). The evaluating the financial health of an inter-company network - evidence from the automotive industry. Inproforum, 18(1), 299-305. doi: 10.32725/978-80-7694-102-1.43
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    References

    1. Agarwal, V., & Taffler, R. (2007). Twenty-Five Years of the Taffler Z-Score Model: Does It Really Have Predictive Ability? Accounting and Business Research - ACCOUNT BUS RES, 37, 285-300. doi: 10.1080/00014788.2007.9663313. Go to original source...
    2. Fiala, P. (2008). Síťová ekonomika. Praha: Professional Publishing.2008.
    3. Helo, P. & Hao, Y. (2019). Blockchains in operations and supply chains: A model and reference implementation. Computers & Industrial Engineering. (136), 242-251. doi: 10.1016/j.cie.2019.07.023. Go to original source...
    4. Gleissner, W. (2023). Uncertainty and resilience in strategic management: profile of a robust company. International Journal of Risk Assessment and Management. 26(1), 2023. doi. 10.1504/IJRAM.2023.132331. Go to original source...
    5. Naderifar, M., Goli, H., & Ghaljaie, F. (2017). Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research. Strides in Development of Medical Education, 14(3). doi:10.5812/sdme.67670. Go to original source...
    6. Rombach, M. P., et al. (2014). Core-periphery structure in Networks. SIAM Journal on Applied Mathematics, 74(1), 167-190. http://www.jstor.org/stable/24510815. Go to original source...
    7. StatSoft, Inc. (2014). STATISTICA (data analysis software system), (verze 12) [software]. http://www.statsoft.cz
    8. Tao, F., Cheng, Y., Zhang, L. et al., (2017). Advanced manufacturing systems: socialization characteristics and trends. Journal of Intelligent Manufacturing, 28, 1079-1094. doi: 10.1007/s10845-015-1042-8. Go to original source...
    9. Zhang, X., Martin, T. & Newman, M. (2014). Identification of core-periphery structure in networks. Physical review. E - covering statistical, nonlinear, biological, and soft matter physics. 91(3), 032803. doi:10.1103/PhysRevE.91.03 2803. Go to original source...
    10. Valášková, Nagy (2023). An Analysis of the Financial Health of Companies Concerning the Business Environment of the V4 Countries. Folia Oeconomica Stetinensia. 23(1):170-193, doi: 10.2478/foli-2023-0009. Go to original source...
    11. Kamal, C. N. P. (2024). Decoding Corporate Financial Health: A Comprehensive Quantitative Analysis of Annual Accounts and Financing Strategies, February 2024, Business and Investment Review 2(1):108-119, doi: 10.61292/birev.98. Go to original source...
    12. Alaka, H.A., Oyedele, L.O., Owolabi, H.A., Kumar, V., Ajayi, S.O., Akinade, O.O. and Bilal, M. (2018). Systematic review of bankruptcy prediction models: Towards a framework for tool selection, Expert Systems with Applications, 94, 164-184, doi: 10.1016/j.eswa.2017.10.040. Go to original source...
    13. Gu, D., Li, J., Li, X. and Liang, C. (2017). Visualizing the knowledge structure and evolution of big data research in healthcare informatics, International Journal of Medical Informatics, 98, 22-32, doi: 10.1016/j.ijmedinf.2016.11.006. Go to original source...
    14. Du Jardin, P. (2018). Failure pattern-based ensembles applied to bankruptcy forecasting, Decision Support Systems, 107, 64-77, doi: 10.1016/j.dss.2018.01.003. Go to original source...
    15. Kovacova, M., Kliestik, T., Valaskova, K., Durana, P. and Juhaszova, Z. (2019), "Systematic review of variables applied in bankruptcy prediction models of Visegrad group countries", Oeconomia Copernicana, Vol. 10 No. 4, pp. 743-772, doi: 10.24136/oc.2019.034. Go to original source...
    16. Ouyang, W., Wang, Y., Lin, C., He, M., Hao, F., Liu, H. and Zhu, W. (2018). Heavy metal loss from agricultural watershed to aquatic system: A scientometrics review, Science of The Total Environment, 637-638, 208-220, doi: 10.1016/j.scitotenv.2018.04.434. Go to original source...
    17. Soukal, I., Mačí, J., Trnková, G., Svobodova, L., Hedvičáková, M., Hamplova, E., Maresova, P., et al. (2023). A state-of-the-art appraisal of bankruptcy prediction models focussing on the field's core authors: 2010-2022, Central European Management Journal, Vol. ahead-of-print No. ahead-of-print, doi: 10.1108/CEMJ-08-2022-0095. Go to original source...
    18. Wang, F., Wang, X. and Yang, S. (2017), "Mining author relationship in scholarly networks based on tripartite citation analysis", edited by Dorta-González, P. PLOS ONE, 12(11), p. e0187653, doi: 10.1371/journal.pone.0187653. Go to original source...

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