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dc.contributor.authorNavarro Claro, Genny Torcoroma
dc.contributor.authorBayona Soto, José Andrés
dc.coverage.spatialColombiaen_US
dc.date.accessioned2025-03-31T14:32:22Z
dc.date.available2025-03-31T14:32:22Z
dc.date.issued2024
dc.identifier.issn0067-3064en_US
dc.identifier.urihttps://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/5050
dc.description.abstractEl estudio "Análisis de Pronósticos de Quiebra en el Subsector Manufacturero de Norte de Santander, Colombia (2015-2022)" ofrece una evaluación empírica de la estabilidad financiera en esta región, utilizando como fundamento teórico la teoría de la estructura de capital de Modigliani y Miller y el modelo Z-Score de Altman para riesgos de quiebra. Mediante un enfoque cuantitativo que incluye análisis de series de tiempo, se analizan los factores internos y externos que afectan la competitividad financiera del subsector. La investigación destaca las contribuciones y limitaciones de la teoría de la estructura de capital y el modelo Z-Score en la práctica, y analiza la integración de tecnologías avanzadas como la inteligencia artificial para optimizar las predicciones de riesgo financiero. Mediante muestreo intencional y análisis documental, se identifican patrones y se evalúa la solvencia empresarial, proporcionando una visión detallada de la resiliencia del sector ante los desafíos económicos. Este estudio proporciona información valiosa para quienes se interesan en la sostenibilidad financiera del sector manufacturero, destacando la importancia de adaptar las estrategias de gestión de riesgos a las particularidades regionales. Su contribución a la literatura especializada radica en ofrecer una perspectiva actualizada sobre la previsión de quiebras y la gestión financiera adaptada al contexto específico de la economía emergente colombiana.en_US
dc.language.isospaen_US
dc.relationhttps://balticajournal.com/baltica/index.php/pdf/stream/dOR3m/1710362464en_US
dc.titleAnálisis de pronósticos de quiebra: estudio empírico del subsector manufacturero de Norte de Santander, Colombiaen_US
dc.title.translatedBankruptcy forecast analysis: empirical study of the manufacturing subsector of Norte de Santander, Colombiaen_US
dc.contributor.cvlac[0001432379]en_US
dc.contributor.cvlac[0000033854]en_US
dc.contributor.googlescholar[x_HNro8AAAAJ]en_US
dc.contributor.googlescholar[gJseD9IAAAAJ]en_US
dc.contributor.orcid[0000-0003-3225-9028]en_US
dc.contributor.orcid[0000-0002-2722-5053]en_US
dc.contributor.researchgate[Genny-Navarro]en_US
dc.contributor.researchgate[Jose-Soto-72]en_US
dc.contributor.scopus[57195914835]en_US
dc.description.abstractenglishThe study "Bankruptcy Forecast Analysis in the Manufacturing Subsector of Norte de Santander, Colombia (2015 – 2022)" offers an empirical evaluation of financial stability in this region, using the capital structure theory of Modigliani and Miller and the Altman Z-Score model for bankruptcy risks as a theoretical foundation. Through a quantitative approach that includes time series analysis, the internal and external factors that affect the financial competitiveness of the subsector are analyzed. The research highlights the contributions and limitations of capital structure theory and the Z-Score model in real practices, and discusses the integration of advanced technologies such as artificial intelligence to fine-tune financial risk predictions. Using purposeful sampling and documentary analysis, patterns are identified and business solvency is assessed, providing a detailed view of the sector's resilience in the face of economic challenges. This study provides valuable insights for those interested in the financial sustainability of the manufacturing sector, highlighting the importance of adapting risk management strategies to regional particularities. Its contribution to the specialized literature lies in offering an updated perspective on bankruptcy forecasting and financial management adapted to the specific context of the Colombian emerging economy.en_US
dc.subject.proposalPronóstico de quiebraen_US
dc.subject.proposalModelo Altman Z-Scoreen_US
dc.subject.proposalEstructura de capitalen_US
dc.subject.proposalSector manufactureroen_US
dc.subject.keywordsbankruptcy forecasten_US
dc.subject.keywordsAltman Z-Score modelen_US
dc.subject.keywordscapital structureen_US
dc.subject.keywordsManufacturing sectoren_US
dc.subject.lembAnálisis de pronósticos de quiebraen_US
dc.subject.lembestudio empíricoen_US
dc.subject.lembNorte de Santander, Colombiaen_US
dc.subject.lembBankruptcy forecast analysisen_US
dc.subject.lembempirical studyen_US
dc.subject.lembmanufactureroen_US
dc.subject.lembmanufacturingen_US
dc.publisher.facultyFacultad ciencias administrativas y económicasen_US
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTen_US
dc.relation.referencesAdesina, O., & Odularu, G. (2022). Probability of Default, Accountability, Bankruptcy, and Digitization Amid COVID-19 Pandemic. Strengthening Systems Accountability for Enterprise Performance and Development Planning, 1, 103–119. https://doi.org/10.1007/978-3-031-11779-4_6en_US
dc.relation.referencesAhmeti, F., & Prenaj, B. (2015). A Critical Review of Modigliani and Miller’s Theorem of Capital Structure. International Journal of Economics Commerce and Management, 3(6), 1–11. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2623543en_US
dc.relation.referencesAltman, E. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.2307/2978933en_US
dc.relation.referencesAnaya, H. (2018). Análisis Financiero Aplicado, bajo NIIF. Universidad Del Externado de Colombia. https://doi.org/10.2307/j.ctv1dp0wtcen_US
dc.relation.referencesBhuvaneskumar, A., Sivakumar, V., & Pushparaj, N. (2023). Performance assessment and ranking of socially responsible companies in India using FAHP, TOPSIS and Altman Z-score. Benchmarking, 30(3), 736–765. https://doi.org/10.1108/BIJ-09-2021-0512en_US
dc.relation.referencesBotero, S., & Cano, J. (2008). ANÁLISIS DE SERIES DE TIEMPO PARA LA PREDICCIÓN DE LOS PRECIOS DE LA ENERGÍA EN LA BOLSA DE COLOMBIA. CUADERNOS DE ECONOMÍA, 27(48), 173–208. http://www.scielo.org.co/pdf/ceco/v27n48/v27n48a07.pdfen_US
dc.relation.referencesBuele, I., Solano, S., & Mora, A. (2021). ECUADORIAN WHOLESALE AND RETAIL TRADE COMPANIES: ANALYSIS OF THE FINANCIAL SITUATION AND BANKRUPTCY FORECAST UNDER ALTMAN Z-SCORE. Academy of Accounting and Financial Studies Journal, 25(1), 1–11. https://www.abacademies.org/articles/ecuadorian-wholesale-and-retail-trade-companies-analysis-of-the-financial-situation-and-bankruptcy-forecast-under-altman-zscore-10149.htmlen_US
dc.relation.referencesBustamante, A., & Bustamante, J. (2008). Análisis de percepciones sobre la competitividad territorial de tres municipios fronterizos de Norte de Santander y Táchira. Aldea Mundo, 13(25), 13–24.en_US
dc.relation.referencesCalderon, V., Ostos, J., Florez, W., & Angulo, H. (2022). Determinants of credit risk: A multiple linear regression analysis of Peruvian municipal savings banks. Decision Science Letters, 11(3), 203–210. https://doi.org/10.5267/dsl.2022.4.003en_US
dc.relation.referencesCarrasco, C., Marchevsky, M., Scandela, L., David, B., & de la Cerda, M. (2022). Potential implications from the methodological application of Design Thinking in urban design processes. Analysis from the designer’s experience. Revista de Urbanismo, 46, 75–94. https://doi.org/10.5354/0717-5051.2022.61159en_US
dc.relation.referencesContreras, A., Zuñiga, C., Martínez, J., & Sánchez, D. (2016). Analysis of time-series on the forecast of the demand of storage of perishable products. Estudios Gerenciales, 32(141), 387–396. https://doi.org/10.1016/j.estger.2016.11.002en_US
dc.relation.referencesForbring, P., & Sandkuhl, K. (2021). Selected Topics in Management and Modeling of Complex Systems: Editorial Introduction to Issue 27 of CSIMQ. Complex Systems Informatics and Modeling Quarterly, 2021(27), I–II. https://doi.org/10.7250/csimq.2021-27.00en_US
dc.relation.referencesGóis, A., De Luca, M., de Lima, G., & Medeiros, J. (2020). Corporate reputation and bankruptcy risk. BAR - Brazilian Administration Review, 17(2), 1–22. https://doi.org/10.1590/1807-7692bar2020180159en_US
dc.relation.referencesGonzález-Martínez, R., Arteaga, A., & Ruí­z, M. (2018). Cierre empresarial en la región Laja- Bají­o. Management Review, 3(2), 61–76. https://doi.org/10.18583/umr.v3i2.119en_US
dc.relation.referencesGupta, M., Aggarwal, P., & Gupta, R. (2023). Corporate Sustainability with Forensic Auditing: An Evidence from India. International Journal of Experimental Research and Review, 35, 128–137. https://doi.org/10.52756/ijerr.2023.v35spl.012en_US
dc.relation.referencesHair, J., Babin, B., Anderson, R., & Black, W. (2018). Multivariate Data Analysis. In Cengage Learning.en_US
dc.relation.referencesKythreotis, A., & Soltani, M. (2023). Relevance and faithful representation (reliability) of annual and semi-annual financial statements; a trade-off? International Journal of Managerial and Financial Accounting, 15(3), 393–412. https://doi.org/10.1504/IJMFA.2023.131779en_US
dc.relation.referencesLeón, L., & Espinoza, E. (2023). Análisis de los factores que intervienen en el crecimiento de cartera vencida de empresas servicios financieros. INNOVA Research Journal, 8(3), 188–201. https://doi.org/10.33890/innova.v8.n3.1.2023.2342en_US
dc.relation.referencesLončarević, S. (2015). Comparison to Kralicek DF Indicators and Altman Z-Score Model for Serbian Metal Industry. International Journal of Industrial Engineering and Management (IJIEM), 6(4), 199–204. www.iim.ftn.uns.ac.rs/ijiem_journal.phpen_US
dc.relation.referencesLópez, M., Zapata, K., Escalera, A., & Arriaga, F. (2017). The role of the strategic planning in the closing and bankruptcy in construction: The case of Tamaulipas. Revista de Contaduria, Administracion e Informatica, 6(25), 24–46. https://www.redalyc.org/pdf/6379/637967155002.pdfen_US
dc.relation.referencesLord, J., Weech, R., Blackburn, J., & Carroll, N. (2021). Examination of nursing home financial distress via Porter’s five competitive forces framework. Health Care Management Review, 46(3), E50–E60. https://doi.org/10.1097/HMR.0000000000000297en_US
dc.relation.referencesLukáč, J., Olexová, C., & Kudlová, Z. (2022). Factors predicting companies’ crisis in the engineering industry from the point of view of financial analysis. PLoS ONE, 17(2). https://doi.org/10.1371/journal.pone.0264016en_US
dc.relation.referencesMang’ana, K., Hokororo, S., & Ndyetabula, D. (2024). An Investigation of the Extent of Implementation of the Financial Management Practices of Agri-SMEs in developing countries: Evidence from Tanzania. Sustainable Technology and Entrepreneurship, 3(1), 100049. https://doi.org/10.1016/j.stae.2023.100049en_US
dc.relation.referencesMcCay, D., Borkowski, N., Trimm, J., & Duncan, J. (2019). A Case Study: Organizational and Environmental Factors Associated with Alabama Rural Hospitals’ Reported Levels of Financial Distress. Journal of Health Care Finance.en_US
dc.relation.referencesModigliani, F., & Miller, M. (1958). The Cost of Capital, Corporation Finance and the Theory of Investment. The American Economic Review, 48(3), 261–297.en_US
dc.relation.referencesMohammed, S. (2016). Bankruptcy prediction by using the Altman Z-score model in Oman: A case study of raysut cement company SAOG and its subsidiaries. Australasian Accounting, Business and Finance Journal, 10(4), 75–85. https://doi.org/10.14453/aabfj.v10i4.6en_US
dc.relation.referencesOtzen, T., & Manterola, C. (2017). Sampling Techniques on a Population Study. International Journal of Morphology, 35(1), 227–232. https://doi.org/10.4067/S0717-95022017000100037en_US
dc.relation.referencesPardo, O., Navarro, D., & Moreno, V. (2022). La competitividad de las empresas manufactureras en Colombia (2008-2018): una estimación de sus factores más influyentes. Revista Facultad de Ciencias Económicas, 30(2), 9–20. https://doi.org/10.18359/rfce.6181en_US
dc.relation.referencesPrakash, B., & Verma, J. (2019). Magnitude of Financial Distress in Micro, Small and Medium Enterprises (MSMES) in Bihar, India: A Test of Altman Z’ Score. Journal of Advanced Research in Law and Economics, 10(4), 1227–1239. https://doi.org/10.14505//jarle.v10.4(42).22en_US
dc.relation.referencesRomán, J., Aguilar, J., Suescún, E., Pinto, J., Montoya, A., Restrepo, M., & Córdoba, L. (2023). An intelligent financial management system for optimal resource allocation in an organisation. International Journal of Applied Decision Sciences, 16(5), 565–586. https://doi.org/10.1504/IJADS.2023.133145en_US
dc.relation.referencesSerna-Gómez, H., & Rodríguez, M. (2015). El sector solidario como alternativa para el desarrollo social e inclusivo en el postconflicto colombiano. Cooperativismo & Desarrollo, 23(107), 1–12. https://doi.org/10.16925/co.v23i107.1250en_US
dc.relation.referencesSong, Y., Jiang, M., Li, S., & Zhao, S. (2024). Class-imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system. Journal of Forecasting, 43(3), 593–614. https://doi.org/10.1002/for.3050en_US
dc.relation.referencesTrejo, C., Velandia, M., Tanaka, K., Rignall, K., & Billie, T. (2023). Financial and strategic management analysis of Farmer Foodshare Inc., a nonprofit food organization. International Food and Agribusiness Management Review, 26(1), 11–23. https://doi.org/10.22434/IFAMR2022.0012en_US
dc.relation.referencesUllah, H., Wang, Z., Abbas, M., Zhang, F., Shahzad, U., & Mahmood, M. (2021). Association of Financial Distress and Predicted Bankruptcy: The Case of Pakistani Banking Sector. Journal of Asian Finance, Economics and Business, 8(1), 573–585. https://doi.org/10.13106/jafeb.2021.vol8.no1.573en_US
dc.relation.referencesValverde, R., & Rossi, R. (2023). Analysis of the differences between the means of the financial indicators of fishing companies in the period 2018-2021. Revista Mexicana de Economia y Finanzas Nueva Epoca, 18(3), 1–25. https://doi.org/10.21919/remef.v18i3.820en_US
dc.relation.referencesVinogradova, A., Lazarev, A., & Kharlamov, P. (2021). Software for data analysis and prediction of bankruptcy of organizations in the fuel and energy complex. Proceedings of the 3rd 2021 International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2021, 1–6. https://doi.org/10.1109/REEPE51337.2021.9388039en_US
dc.identifier.DOIhttps://doi.org/10.59879/dor3men_US


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