Contabilidad de Costos Avanzados Aplicada a Operaciones Logísticas Digitalizadas: Evidencia Empírica en Entornos de Alta Incertidumbre

Omar Castillo; Roberto Lugo; Julian Sánchez; Elborín Muñoz; Jonathan Yepes; Carlos Chen

doi:10.70625/rmis/737

Authors

Omar Castillo Universidad de Panamá Author
Roberto Lugo Universidad de Panamá Author
Julian Sánchez Universidad de Panamá Author
Elborín Muñoz Universidad de Panamá Author
Jonathan Yepes Universidad de Panamá Author
Carlos Chen Universidad de Panamá Author

DOI:

https://doi.org/10.70625/rmis/737

Keywords:

Contabilidad de costos, Logística digitalizada, Costos operativos, Incertidumbre, Panamá

Abstract

La creciente incertidumbre económica, tecnológica y operativa ha incrementado la necesidad de aplicar sistemas avanzados de contabilidad de costos en operaciones logísticas digitalizadas. El problema de investigación se centró en la limitada capacidad de muchas organizaciones para vincular información contable especializada con datos logísticos en tiempo real, lo cual dificulta el control de costos, la eficiencia operativa y la toma de decisiones estratégicas en escenarios de alta volatilidad. El objetivo del estudio fue analizar empíricamente la aplicación de la contabilidad de costos avanzados en operaciones logísticas digitalizadas, con énfasis en empresas vinculadas al transporte, almacenamiento y distribución en Panamá. Metodológicamente, se propone un enfoque cuantitativo, de tipo aplicado, con diseño no experimental, transversal y correlacional-explicativo, sustentado en encuestas estructuradas, análisis de indicadores financieros-logísticos, validación por expertos, confiabilidad mediante Alpha de Cronbach y modelación estadística multivariada. Como resultados esperados, se plantea que la aplicación de sistemas avanzados de costeo, analítica financiera, integración ERP y trazabilidad logística mejora significativamente el control de costos y fortalece la toma de decisiones estratégicas. El aporte principal consiste en un modelo empírico aplicable a organizaciones logísticas que operan bajo incertidumbre, integrando contabilidad de costos, digitalización operativa y gestión estratégica.

References

Bertalanffy, L. von. (1968). General system theory: Foundations, development, applications. George Braziller.

Blocher, E. J., Stout, D. E., Juras, P. E., & Smith, S. D. (2022). Cost management: A strategic emphasis (9th ed.). McGraw-Hill Education.

Bowersox, D. J., Closs, D. J., & Cooper, M. B. (2019). Supply chain logistics management (5th ed.). McGraw-Hill.

Büyüközkan, G., & Göçer, F. (2018). Digital supply chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157–177. https://doi.org/10.1016/j.compind.2018.02.010

CEPAL. (2022). Perspectivas del comercio internacional de América Latina y el Caribe 2022. Naciones Unidas.

Christopher, M. (2016). Logistics and supply chain management (5th ed.). Pearson Education.

Christopher, M., & Peck, H. (2004). Building the resilient supply chain. International Journal of Logistics Management, 15(2), 1–14. https://doi.org/10.1108/09574090410700275

Cohen, S., & Roussel, J. (2019). Strategic supply chain management. McGraw-Hill.

Cooper, D. R., & Schindler, P. S. (2019). Business research methods (13th ed.). McGraw-Hill Education.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.

Davenport, T. H., & Harris, J. G. (2017). Competing on analytics: The new science of winning. Harvard Business Review Press.

Dolgui, A., & Ivanov, D. (2022). 5G in digital supply chain and operations management: Fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. International Journal of Production Research, 60(2), 442–451. https://doi.org/10.1080/00207543.2021.2002969

Ellram, L. M., Tate, W. L., & Feitzinger, E. G. (2018). Factor-market rivalry and competition for supply chain resources. Journal of Supply Chain Management, 49(1), 29–46. https://doi.org/10.1111/jscm.12002

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage Publications.

Fosso Wamba, S., Queiroz, M. M., Wu, L., & Sivarajah, U. (2020). Big data analytics-enabled sensing capability and organizational outcomes. International Journal of Information Management, 50, 95–105. https://doi.org/10.1016/j.ijinfomgt.2019.05.015

Grant, R. M. (2019). Contemporary strategy analysis (10th ed.). Wiley.

Gunasekaran, A., Yusuf, Y. Y., Adeleye, E. O., & Papadopoulos, T. (2017). Agile manufacturing practices: The role of big data and business analytics with multiple case studies. International Journal of Production Research, 56(1–2), 385–397. https://doi.org/10.1080/00207543.2017.1395488

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Heizer, J., Render, B., & Munson, C. (2020). Operations management: Sustainability and supply chain management (13th ed.). Pearson.

Hernández Sampieri, R., Fernández Collado, C., & Baptista Lucio, P. (2018). Metodología de la investigación (7.ª ed.). McGraw-Hill Education.

Horngren, C. T., Datar, S. M., & Rajan, M. (2021). Cost accounting: A managerial emphasis (17th ed.). Pearson.

Ivanov, D., & Dolgui, A. (2020). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775–788. https://doi.org/10.1080/09537287.2020.1768450

Ivanov, D., Dolgui, A., Sokolov, B., Ivanova, M., & Werner, F. (2019). A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory Industry 4.0. International Journal of Production Research, 54(2), 386–402. https://doi.org/10.1080/00207543.2014.999958

Kaplan, R. S., & Anderson, S. R. (2007). Time-driven activity-based costing: A simpler and more powerful path to higher profits. Harvard Business School Press.

Krajewski, L. J., Malhotra, M. K., & Ritzman, L. P. (2019). Operations management: Processes and supply chains (12th ed.). Pearson.

Laudon, K. C., & Laudon, J. P. (2022). Management information systems: Managing the digital firm (17th ed.). Pearson.

Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x

Lee, H. L. (2004). The triple-A supply chain. Harvard Business Review, 82(10), 102–112.

Melnyk, S. A., Narasimhan, R., & DeCampos, H. A. (2014). Supply chain design: Issues, challenges, frameworks and solutions. International Journal of Production Research, 52(7), 1887–1896. https://doi.org/10.1080/00207543.2013.787175

Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1–25. https://doi.org/10.1002/j.2158-1592.2001.tb00001.x

Nahmias, S., & Olsen, T. L. (2015). Production and operations analysis (7th ed.). Waveland Press.

O’Brien, J. A., & Marakas, G. M. (2018). Management information systems. McGraw-Hill.

Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. Free Press.

Queiroz, M. M., Fosso Wamba, S., Machado, M. C., & Telles, R. (2020). Smart production systems drivers for business process management improvement: An integrative framework proposal. Business Process Management Journal, 26(5), 1075–1092. https://doi.org/10.1108/BPMJ-03-2019-0134

Romney, M. B., & Steinbart, P. J. (2021). Accounting information systems (15th ed.). Pearson.

Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.

Sekaran, U., & Bougie, R. (2020). Research methods for business: A skill building approach (8th ed.). Wiley.

Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2021). Designing and managing the supply chain (4th ed.). McGraw-Hill.

Skyttner, L. (2020). General systems theory: Problems, perspectives, practice (3rd ed.). World Scientific Publishing. https://doi.org/10.1142/11109

Slack, N., Brandon-Jones, A., & Johnston, R. (2022). Operations management (10th ed.). Pearson.

Tristán-López, A. (2008). Modificación al modelo de Lawshe para el dictamen cuantitativo de la validez de contenido de un instrumento objetivo. Avances en Medición, 6, 37–48.

Turban, E., Pollard, C., & Wood, G. (2018). Information technology for management. Wiley.

Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2020). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365. https://doi.org/10.1016/j.jbusres.2016.08.009

World Economic Forum. (2023). Digital transformation of supply chains. Geneva, Switzerland.